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37299942 | intro | 1. Introduction Children who experience handwriting learning disabilities may face significant negative effects on their academic success and daily life. Cognitive, visual perceptual and fine motor skills are essential for learning to write. Dysgraphia refers to the motor performance difficulties of handwriting rather than the skills of spelling or text composition. Between 5 and 34% of children never master legible, fluent and enduring handwriting despite appropriate learning over a period of 10 years. Early detection of dysgraphia is important to initiate a targeted intervention for the improvement of the children’s writing skills, which are a basis for their academic career. Criterion-referenced assessment of handwriting skills in occupational therapy practice traditionally includes the quantitative and qualitative analysis of letter formation, spacing, alignment, legibility and handwriting speed. Recently, several studies have investigated automatic dysgraphia detection using machine learning algorithms with a digital tablet. Tablet sensors enable collecting signals, such as the x and y coordinates, pressure and tilt of the pen, during writing. However, these studies deployed classical machine learning algorithms, such as Random Forest4 and AdaBoost7, which require manual feature extraction and selection. Asselborn et al. extracted 53 handwriting features, which are classified into four groups: static, kinematic, pressure and tilt features. Spectrum features seem to be the most important features: six out of eight features are related to frequency. The four most discriminative features are the Bandwidth of Tremor Frequencies and the Bandwidth of Speed Frequencies (kinematic features), the Mean Speed of Pressure Change (pressure feature) and the Space Between Words (static feature). Using these 53 features and the random forest classifier, an F1-score of 97.98% was achieved. Accuracy was not reported due to an imbalanced data set (56 children with dysgraphia and 242 typically developing children). Asselborn et al. used PCA to reduce the number of relevant features and to enable a more data-driven classification. Drotar and Dobes extracted 133 features using mainly the statistical measures leak min, mean, median and standard deviation of features such as velocity, acceleration, jerk, pressure, attitude, azimuth, segment/vertical/horizontal length and pen lifts. Merged from all tasks, they produced 1176 features in total. From these 1176 features, 150 features were selected using weighted k-nearest-neighbour feature selection. Finally, using these 150 features as input to the AdaBoost classifier, an accuracy of 79.5% was obtained. The data set was almost balanced: 57 children with dysgraphia and 63 normally developing children. Dimauro et al. used 13 pure text-based features, such as writing size, non-aligned left margin, skewed writing and insufficient space between words, and achieved an accuracy of 96%. Nevertheless, the data were imbalanced, with 12 out of 104 children showing dysgraphia. In contrast, Devillaine et al. used only graphical tablet sensor signals, i.e., x, y and z positions and pressure data, for feature extraction and no static features from text data. From the extracted features, 10 features were selected using linear SVM or extra trees. Different classical machine learning algorithms were tested for classification of a balanced data set consisting of 43 children with dysgraphia and 43 normally developing children. The best performance with 73.4% accuracy was achieved with the random forest algorithm. Devillaine et al. also provided a comparison of different classical machine learning algorithms for dysgraphia detection, with the highest F1-score of 97.98% achieved by Asselborn et al.. To summarize, all the cited papers used feature extraction and selection, which require high effort and expertise. Furthermore, the feature extraction is also subjective, i.e., based on expert experience, which might miss some important features. In this project, an LSTM deep learning algorithm was used, which automatically extracts features from raw sensor signals. To the best of our knowledge, only a few research groups have deployed deep learning for dysgraphia detection, such as Ghause et al., achieving an F1-score of 98.16%. This work applied a CNN with text images as input, i.e., no dynamic features were used. Zolna et al. achieved a significantly better performance in dysgraphia detection when using an RNN (more than 90%) in comparison to a CNN (25–39%). Unlike a CNN, an RNN takes into account the dynamic aspects of the writing. However, they used only the trajectory of the consecutive points as dynamic features and not pressures, velocity, accelerations and tilt as we did. They also used two-layer LSTM but with 100 neurons in each layer and a dropout layer with 50% drop probability. In contrast to previous works, which used tablets, we used a pen equipped with sensors (SensoGrip) to capture handwriting dynamics (pressure, speed, acceleration and tilt), which looks and feels more like a real pen and enables writing evaluation in more realistic scenarios. The SensoGrip system consists of the SensoGrip pen and an app designed for the Android OS. The SensoGrip pen features an integrated microcontroller, which is able to communicate with the Android device via Bluetooth BLE. It also contains the necessary power supply, electronics and sensors for measuring tip and finger pressure, as well as an IMU MEMS three-axis accelerometer and three-axis gyroscope. The microcontroller captures the pressure data as well as the data provided by the IMU and forwards them to an app on the Android device. The user is able to acquire feedback via built-in RGB LEDs or via the mobile app. We do not provide binary output (dysgraphia or no dysgraphia) but the scores of the German version of the Systematic Screening for Motor Handwriting difficulties (SEMS). SEMS provides values between 0 and 12 for print and a maximum of 14 points for manuscript writing. More points indicate more difficulties in writing, and therefore, these scores enable a finer granularity in handwriting evaluation. In this work, we investigated the fine grading of handwriting capabilities by predicting the SEMS score (between 0 and 12) with deep learning. We achieved a root-mean-square error (difference between the predicted SEMS score and the SEMS score estimated by expert therapists) of less than 1, with automatic instead of manual feature extraction and selection. Furthermore, we used the SensoGrip smart pen, a pen equipped with sensors to capture handwriting dynamics, instead of a tablet, enabling writing evaluation in more realistic scenarios. In the course of this work, our results are presented and discussed, followed by a description of the applied methods. | [
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38861157 | results | Results The anterodorsal thalamic nucleus shows early and consistent vulnerability to tau pathology We examined post-mortem brain samples from 26 cases, grouped by the Braak tau stages of disease progression (Table 1). We assessed early (Braak stages 0–II; n = 15), middle (Braak stages III–IV, n = 6), and late (Braak stages V–VI, n = 5) cases, comparing the rostral thalamus (n = 25 cases) to the cortex (hippocampal formation and cingulate areas) and to other subcortical areas (Fig. 1a–f, 2, 3, 4; Tables 1, 2; Tables S3, S4). We quantified ptau coverage and ptau-immunoreactive (ptau+) cells using the AT8 antibody, which recognizes phosphorylated serine 202 and threonine 205 residues of tau, in 50-µm-thick sections from perfusion-fixed human brains using a pixel classifier (Fig. 1g, h; Figure S1; Table 1; Methods). We confirmed these data with a ptau-intensity scoring system in a larger number of samples comprising the perfusion-fixed sections and 10-µm-thick FFPE sections and FFIF sections (Fig. 1i, j; Table S3; n = 26 cases). We observed ptau+ neurons and processes restricted to the ADn in controls (‘pre-Braak’ stage 0; n = 4/6 cases; coverage = 0.56%, ptau+ cells = 1.29 mm−2, intensity score = 1; Figs. 1a, g–i, 4a; Table 2). In contrast to the ADn, when we examined all early-stage cases (Braak stages 0-II, n = 15 cases), we found that the other rostral thalamic nuclei, even those adjacent to the ADn, distinctly lacked ptau (Figs. 1a, 2a; Figure S2a; Table 2; Tables S3, S4). Among the postsynaptic targets of the ADn, both the EC and retrosplenial cortex (RS; BA 30, 29 and 26), but not the presubiculum (PreS), exhibited sparse ptau (EC score = 1, n = 3 cases, RS score = 0.5, n = 2 cases; Fig. 1b, j; Table S3). Mild tau pathology in CA2 (n = 2/3 cases) suggests the presence of four-repeat tau isoforms or primary age-related tauopathy (PART) in parallel with ptau in the ADn. At middle stages (Braak stages III-IV, n = 6 cases), the ADn contained moderate levels of ptau (coverage = 8.54%, ptau+ cells = 11.65 mm−2, intensity score = 2.65; Figs. 1c, g–i, 2; Figure S3a, b; Table 2; Tables S3, S4), whereas other rostral thalamic nuclei showed sparse ptau (AV: coverage = 0.15%, ptau+ cells = 14.49 mm−2, score = 0.5; paraventricular nucleus (PVT): coverage = 0.96%, ptau+ cells = 1.91 mm−2, score = 1.38; Fig. 1c, g–i; Tables S3, S4). In the cortex, ptau was observed at moderate-to-intense levels, with the RS, EC and prosubiculum (ProS) showing intense ptau immunoreactivity; the PreS displayed sparse immunolabeling at this stage (RS score = 3; EC score = 3; ProS score = 3; PreS score = 1; Fig. 1d, j; Table S3). In the RS, ptau was concentrated in the granular areas (BA 29 and 26). At late stages (Braak stages V–VI), which included cases with Alzheimer’s disease (Table 1), intense ptau was observed in the ADn, with a high density of ptau+ cells (n = 4/4 cases; coverage = 36.31%, ptau+ cells = 118.89 mm−2, intensity score = 3; Figs. 1e, g–i, 3; Tables S3, S4). The laterodorsal nucleus (LD) showed a high ptau density in the late stages, matching that of the ADn (Figs. 1i, 3; Table S3). The PVT had a similar ptau coverage to middle-stage ADn (n = 5/5 examined cases; 11.62%, score = 1.38; Figs. 1c, e, g, i, 3; Table 2; Tables S3, S4) and had the highest ptau+ cell count after the ADn (29.13 cells mm−2). The reuniens nuclear complex (RE) was similarly affected (score = 2). In contrast, the AV had lower coverage and ptau+ cell counts (coverage = 6.28%, ptau+ cells = 14.49 mm−2, intensity score = 1) followed by the mediodorsal nucleus (MD), which remained relatively sparse compared to the other examined nuclei (coverage = 1.62%, ptau+ cells = 2.84 mm−2, score = 1.25; Fig. 1e, g–i; Table 2; Tables S3, S4). The GABAergic thalamic reticular nucleus (TRN) lacked ptau immunopositive cell bodies; only axons and axon terminals were ptau+ (coverage = 2.98%, ptau+ cells = 0 mm−2, score = 2 Figs. 1e, g–i, 3; Tables S3, S4), consistent with previously published data. In the cortex, ptau severely affected each examined area (Fig. 1f, j; Table S3), consistent with previous studies. To provide additional context for the very early subcortical tau pathology in the ADn, we also examined the LC, which is susceptible to ptau at ‘pre-Braak’ stages. At early stages, in contrast to the sparse–moderate levels of ptau in the ADn, ptau expression in the LC was predominantly very weak and localized to processes resembling axons (n = 7/8 trace inclusions or sparse; n = 1/8 lacking ptau; n = Figure S4a, b; Table 2). In the middle and late stages, there was moderate ptau in somata, dendrites and axons (Figure S4c; Table 2). Interestingly, we detected neuromelanin in a few ptau+ somata. The DRn also showed moderate ptau in one tested Braak stage II case (Figure S4b). The lateral mammillary nucleus (LMB), which is presynaptic to the ADn (Fig. 1a), lacked ptau in n = 3/4 early-stage cases (Figure S5a; Table 2). In one Braak stage II case, the ADn showed moderate-dense ptau and the LMB showed mild–moderate ptau (Case 23, Figure S5b). In middle and late stages, moderate–dense ptau was present in the LMB (Figure S5c, d; Table 2). The adjacent medial mammillary nucleus (MMB) and tuberomammillary nucleus had a similar pattern to the LMB (Figure S5b; Table 2). The data largely confirm previous reports. In addition to neuronal ptau, we observed ptau+ ‘coiled bodies’ in the ADn (Figure S3c). Based on their size (~10 µm) and shape, we suggest that coiled bodies are localized to oligodendrocytes, which are typically overlooked in Alzheimer’s disease. We also detected ptau+ tufted astrocytes in six cases, which are associated with aging, Alzheimer disease, and other tauopathies. Despite widespread ptau in astrocytes of varying shapes, sizes, and locations, including within the ADn (Figures S3a, b, d, S5c), neuronal ptau was consistently detected within the ADn, presynaptic LMB, and postsynaptic RS, suggesting this pathway can develop tau pathology in parallel with aging-related tau astrogliopathy (ARTAG). These results reveal that distinct nuclei of the rostral thalamus are affected early on by ptau, with the ADn consistently having the highest ptau density and ptau+ cells across all stages (Figs. 1a, 4a; Figures S2a, S3a; Table 2; Tables S3, S4). Calretinin-expressing neurons accumulate ptau in the rostral thalamus We noticed that thalamic nuclei vulnerable to ptau were in CR-enriched regions (Figs. 2, 3, 4a) and hypothesized that CR+ neurons were sensitive to accumulating ptau. We performed double immunolabeling with CR and AT8 (for ptau) and observed colocalization in neurons within the ADn, PVT, and RE (Fig. 4a–d). In the TRN, CR-enriched neurons lacked ptau (Fig. 4f), consistent with the distinct lack of ptau+ TRN cell bodies (Fig. 1h). As the ADn contained ptau+ neurons even in control cases (Figs. 1a, h, 4a), we tested whether CR+ neurons were affected at early, middle and/or late stages. Even at Braak stage 0, CR was detected in the majority of ptau+ neurons (64.3% CR+ , n = 1 case; Fig. 4a, b, e). In the middle stage, a large proportion of ptau+ cells were CR+ (81.1%; n = 3 cases; Fig. 4c, e), and in the late stage, 71.1% were CR+ (n = 1 case; Fig. 4d, e). In conclusion, CR-expressing neurons were affected very early on, and at every stage, the majority of ptau immunopositive cells were CR+ in the ADn. Subcellular distribution of ptau in the anterodorsal thalamus After establishing that ADn neurons were especially vulnerable to ptau, we investigated the subcellular distribution of ptau to reveal how it spreads. To define synaptic structures at different stages of tau pathology, we examined ultrathin (~50–70 nm) sections of the ADn. We obtained electron microscopic samples from 4 cases (Cases 4, 12, 25, 17) that were appropriately preserved for quantitative analysis (Fig. 5a–d; Braak stages 0, II, III, and VI). We identified two main types of synaptic boutons with asymmetric synapses: large ~1–8 µm boutons (Fig. 5c; Figure S6a–c), consistent with presynaptic axon terminals from the mammillary body, and small <~1 µm diameter boutons (Fig. 5d; Figure S6a–c), resembling ‘classical’ cortical presynaptic terminals. Some presynaptic boutons from stage 0 (n = 20/70), from stage II (n = 3/106) and stage VI (n = 31/103) had a highly electron opaque (‘dark’) appearance, ranging from a homogeneous state to others with recognizable vesicles and mitochondria, but all showing collapsed, scalloped forms (Figure S2c). This may indicate degeneration of certain nerve terminals, and/or be a sign of selective vulnerability to post-mortem/fixation conditions; these terminals were omitted from our quantification. To identify subcellular ptau, we first examined cell bodies in the ADn, which contained abundant filaments (Fig. 5e). These resembled filaments previously found in the cortex of tauopathies including Alzheimer’s disease. We visualized ptau with silver-enhanced immunogold particles, and observed that ptau was specifically associated with the intracellular filaments (Fig. 5e, g; Figure S2g), thus unequivocally demonstrating the association of ptau with the originally described paired helical filaments at the ultrastructural level. Cell bodies also contained abundant lipofuscin (Fig. 4d, 5e). Filaments immunolabeled for ptau were also localized to dendrites (Fig. 5f; Figure S2d, g, h), and could be observed in large bundles (>1 µm) (Fig. 5g). Filament bundles were immunolabeled predominantly on the cytoplasmic surface, most likely due to reagents not penetrating into the bundle (Fig. 5g). We also detected ptau in myelinated axons (Fig. 5h). Given that ptau was localized to a variety of subcellular domains, we next investigated whether ptau can also be associated with axon terminals in the ADn. Subcortical vesicular transporter 2-expressing presynaptic terminals preferentially contain ptau Large presynaptic terminals of subcortical origin contain vesicular glutamate transporter 2 (vGLUT2). We observed strongly overlapping distributions of vGLUT2 and AT8 immunoreactivities at the light microscopic level, especially in the ADn, RE, PVT, and internal medullary lamina (Fig. 6a). The overlapping vGLUT2 and AT8 distributions suggested that vGLUT2 may be related to ptau. When we examined sections immunoreacted for both vGLUT2 and AT8, we discovered that ptau was localized to vGLUT2+ boutons (Fig. 6b, e, f; Figure S2b, d). Whereas some vGLUT2+ boutons showed no signs of abnormalities (Fig. 6c), others were degenerating (Fig. 6d; Figure S2c). The degenerating vGLUT2+ boutons had clumped mitochondria (Fig. 6d). Many of these boutons contained large (80–100 nm) double-walled vesicles (Fig. 6d), consistent with autophagy or the packaging and/or potential release of different forms of tau. Not all vGLUT2-positive degenerating boutons displayed detectable ptau, at least in the sections that we examined. In some degenerating boutons which were immunoreactive for both vGLUT2 and ptau, ptau+ bundles of filaments occupied a large proportion of the volume crowding out vesicles (Fig. 6b, e), which may cause impairments in neurotransmission. We also observed synaptic partners consisting of presynaptic vGLUT2+ boutons and postsynaptic dendrites that both contained ptau (Fig. 6f; Figure S2d), suggestive of transsynaptic spread between the mammillary bodies and ADn (Fig. 1a; Figure S5b). The size distribution of ptau-positive terminals also confirmed that large presynaptic terminals are preferentially affected by ptau pathology (Figure S6a–c). The distribution of presynaptic and postsynaptic ptau suggests transsynaptic spread Given the observation of ptau in both presynaptic terminals and postsynaptic dendrites (Fig. 5f, 6b, d–f; Figure S2b, d, g, h), we quantitatively characterized how the synaptic distribution of ptau changed across different Braak stages, examining 652 presynaptic boutons and postsynaptic dendrites, each of which was followed over several serial sections. At Braak stage 0, despite ptau being detectable at the light microscopic level (Figs. 1a, 4a), all sampled boutons and dendrites lacked ptau (n = 50/50 boutons, n = 62/62 dendrites; Case 4; Fig. 6g, h). Similarly, despite abundant ptau in the ADn at Braak stage II (Fig. 1i; Figure S2a; Table 2; Table S3), we did not detect ptau in boutons (n = 106/106) or dendrites (n = 109/109) at the electron microscopic level (Fig. 6g, h; Figure S2e, f), probably due to the limited sampling area. At Braak stage III, 5.8% of boutons (n = 6/104) and 21.6% of dendrites (n = 22/102) were ptau+ (Case 12; Fig. 6g, h; Figure S2d). In this stage, the proportion of synapses in which both the presynaptic boutons and the associated postsynaptic dendrites contained ptau was 3.9% (n = 4/104; Figure VGLUT2f S2d). At Braak stage IV, we detected ptau within dendritic appendages in close apposition to vGLUT2+ terminals, which also contained ptau (Figure S2b). At Braak stage VI, the proportion of affected boutons and dendrites greatly increased: 20.6% of boutons (n = 15/73) and 51.5% of dendrites (n = 52/101) contained ptau (Case 17; Fig. 6b, d–h). Furthermore, 12.3% (n = 9/73) of synapses consisted of both ptau+ boutons and ptau+ dendrites (Fig. 6f, g; Figure S2d). These data demonstrate that the proportions of both the presynaptic and postsynaptic elements containing ptau increase with Braak stage. Finally, we examined the relationship between presynaptic vGLUT2 and ptau across stages. At the early stage, we identified vGLUT2+ boutons (n = 18, Braak stage 0; n = 37, Braak stage II; Figures S2e, f, S6d), but did not detect ptau (Figure S6). But by the middle stage, from a total of 104 synaptic boutons, 5.8% (n = 6) were both vGLUT2 and ptau double immunopositive (Fig. 6i), whereas none of the vGLUT2 immunonegative boutons (n = 57) were ptau+. In other words, 100% of ptau+ boutons were vGLUT2+ (n = 6) and 12.8% of vGLUT2+ boutons (n = 47) were ptau+, supporting the hypothesis of selective vulnerability of subcortical vGLUT2+ synaptic terminals. Filamentous contacts with postsynaptic structures, known as puncta adherentia, are associated with mammillothalamic terminals. We identified puncta adherentia between vGLUT2+ boutons and postsynaptic dendrites containing ptau (Figure S2d). Moreover, the small corticothalamic boutons lacked ptau (Figure S6b, e), which indicates that ptau in the ADn is unlikely to have spread anterogradely from the cortex. In the late stage, out of a total of 73 synaptic terminals, an even higher proportion showed vGLUT2 and ptau colocalization (16.4%; n = 12; Fig. 6i), i.e., ~80% of ptau+ boutons (n = 15) were immunopositive for vGLUT2. And of all vGLUT2+ boutons (n = 38), 31.5% were ptau+. The data on the colocalization of vGLUT2 and ptau is even likely to be an underestimate, given that large ‘dark’ boutons are likely to be degenerating mammillothalamic terminals (Figures S2c, S6f), and we only sampled relatively few sections for each terminal. The above results suggest that vGLUT2+ boutons are strong candidates for the transsynaptic spread of ptau between postsynaptic ADn neurons and presynaptic mammillary body neurons within the Papez circuit (Fig. 7). | [
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38447542 | intro | Introduction The World Health Organization (WHO) defines active aging as “the process of optimizing opportunities for health, participation and security in order to enhance quality of life as people age, allowing people to ‘realize their potential for physical, social and mental well-being throughout the life course.’” The list of contributors to healthy aging is long and varied with most items independent of hearing loss (HL) and balance disorders (BDs). Nevertheless, treating deafness and/or dizziness has proven positive effects on several health-related quality of life domains, which in turn benefits health status overall. HL and/or BDs are frequently linked to pathologies of the auditory or vestibular systems. These pathologies might appear in isolation or together. HL and/or BD represent a greater risk of cognitive impairment, frailty, and social exclusion with considerable negative consequences for their quality of life, that of those who care for them, and for the sustainability of health and care systems. The early detection of risks associated with aging (like HL and/or BD) using common telecommunications infrastructure approaches will enable an earlier intervention preventing their negative consequences. Age-related hearing loss (ARHL) is the loss of hearing that gradually occurs in most people as they grow older. It is one of the most common conditions affecting older and elderly adults. According to Roth et al., roughly 30% of men and 20% of women in Europe suffer from a hearing loss of 30 dB HL or more at age 70 and 55% of men and 45% of women at 80. About one-third of those who are affected at the European level have disabling hearing loss and it is estimated that around 900,000 have hearing loss severe enough to be candidates for a cochlear implant (CI). ARHL is a key communication disorder, which is characterized not only by a peripheral (cochlear) component but also by a central component. Severe hearing loss patients can barely understand spoken language. Even if they have an adequate tonal hearing sensation, they cannot understand complex acoustic stimuli, such as language or music, particularly in a noisy environment. The central neuronal processing speed and the timing of afferent integration is altered. Furthermore, a loss of inhibitory control and spatial memory has been observed as the result of the sensory (hair) cell loss and progressive deafferentation. Central ARHL must be regarded as an underrated factor, responsible for the break-down of interhuman communication in the elderly. This often leads to social isolation, abandonment of working life, and sub-depression. The lack of auditory information is also associated with cognitive dysfunctions and in extreme cases to age-related dementia. However, epidemiological studies show that the risk of developing a central ARHL is increased by 4–9% per year of age (beginning around 55) with increased prevalence in men. Taken together, this explains how hearing impairment negatively affects the quality of life of the elderly. Recent studies suggest that individuals with hearing loss are more likely to develop Alzheimer’s disease or other forms of dementia over time, and age-related hearing impairment is potentially a reversible risk factor for dementia and Alzheimer disease. The cause of BD in the elderly is usually related to multiple factors. Vestibular pathology is a common etiology, but their type varies: positional vertigo is very common, while Meniere’s disease or vestibular migraine have rarer presentation at that age but may already be present but undiagnosed in several subjects, which increases its prevalence. ARHL is usually the result of degenerative processes affecting the inner ear. However, there may be accompanying changes in the labyrinth at the cellular, microvascular, and metabolic levels, generating symptomatically permanent sensorineural hearing loss and/or vestibular disorders, leading to impaired balance. Hearing and balance impairments as well as falls are common among older people. Identifying modifiable risk factors for falls in older adults is of significant public health importance. While hearing is not typically considered a risk factor for falls, recent reports demonstrated a strong association between audiometric hearing loss and incident falls. Lin and Ferrucci report that hearing loss was significantly associated with the odds of reported falls. For every 10 dB increase in hearing loss, there was a 1.4-fold (95% CI, 1.3–1.5) increased odds of an individual reporting a fall over the preceding 12 months. Several mechanisms could explain the observed association between hearing loss and falls. There may be a concomitant dysfunction of both the cochlea and the vestibular organs given their shared location within the bony labyrinth of the inner ear. Decreased hearing sensitivity may also directly limit access to auditory cues that are needed for environmental awareness. Finally, the association of hearing loss with falls may be mediated through cognitive load and reduced attentional resources. Attentional resources are critical for maintaining postural control, and decrements in attentional and cognitive resources due to hearing loss may impair the maintenance of postural balance in real-world situations and increase the risk of falling. The latter two pathways, that suggest a possible causal pathway between hearing loss and falling, are intriguing because hearing loss is highly prevalent but remains vastly undertreated in older adults. To detect and typify hearing loss and BD among people older than 55 years of age and the epidemiological traits that might be linked to such disorders (primary prevention) To evaluate the impact of HL and/or BD on the domains that have impact on overall well-being and healthy aging in the elderly such as hearing ability, dependency, cognition, falls, and depression (in short: to evaluate the general status of quality of life in elderly individuals) To prove the positive impact of early intervention in HL and BDs among the elderly (secondary prevention) on quality of life, especially regarding their communication, cognitive, mental, and autonomy-related abilities To advocate for the care of hearing and balance disorders of elderly patients at a societal level among the general population The project “hearing and balance in healthy aging” is focused on the development of solutions that support active and healthy aging by enabling early detection and mitigation of risks associated with aging. Although the auditory thresholds of patients affected by ARHL have been studied, there are not enough data about the impact of HL on the quality of life of the elderly. There are few epidemiological data that research the link between ARHL and BD, diet, habits and physical exercise. Such information might be extremely useful to provide comprehensive, early care to elderly people affected by a HL linked or not to BDs, thereby contributing to existing prevention and treatment measures that reduce the impact of HL and/or BDs beyond the sensory field, on cognition, independence, and sociability. In addition, the information obtained might provide insights into the economic impact on society of HL and BDs in this population. The objectives of the project “H&B in healthy aging” are: In this article, the specific objective is the characterization of hearing, balance, and other associated disorders, in three population groups of individuals aged 55 and older. These groups are described below in the Population section. | [
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38259745 | results | Results Between October 1st, 2019, and May 30th, 2022, 225 patients benefited from neuropsychological evaluations or cognitive training and were included in the analyzes (103 Female, mean age 71.53 ± 15.36 years). The patient’s population consisted in post-traumatic disorders (8%), post-stroke patients (23%) and dementia patients (69%) (Alzheimer’s disease, Mild Cognitive Impairment, Frontotemporal Dementia, Lewy Body Dementia). A total of 13,958 treatments were included in the analyzes: 2,512 neuropsychological evaluations (18% of the total treatments) and 11,446 cognitive training (82% of the total treatments). Among these 13,958 treatments, 5,768 appointments were conducted in telemedicine and 8,190 in-person appointments were conducted in the outpatients’ clinic. During this period, the rate of telemedicine activity increased from 16.81% in January 2020 to 23.21% in May 2022. Peaks in telemedicine activity reached 85.64% in May 2020 and 83.65% in February 2021 (Table 1). In-person appointments in the outpatients’ clinic had a greater variability compared to telemedicine appointments, especially during the year 2020, as shown by the standard deviations analyzes (in-person appointments sd = 143.13 vs. telemedicine sd = 76.30, p = 0.017) (Figure 1). The monthly percentage change index for the outpatients (mean percentage variation = 13.83; 95% CI: −8.58, 42.67) and telemedicine activity series (mean percentage variation = 5.14%; 95% CI: −6.43, 16.46) during the COVID-19 pandemic, shows a positive trend concerning telemedicine continuity and utility. The bivariate spectral analysis yielded a significant common movement in the two series, with a significant peak involving a squared coherence of 0.421 (p = 0.032; phase angle, 3.03 radian) (see Figure 2), corresponding to a Fourier period of 5.2 months and with a 2.5-month lead relationship between the two time series. There was a significant positive correlation (r = 0.354, p = 0.038) between the number of telemedicine appointments and pandemic worsening expressed as the number of symptomatic patients hospitalized with SARS-CoV-2 in Italy (Figure 3). The first two peaks of SARS-CoV-2 contagion (March 2020 and November 2021) were immediately followed by an increase in telemedicine appointments. Strikingly, patients were faster to switch from in-person to telemedicine appointments at the third worsening of the Italian pandemic situation. This was reflected by the rise in telemedicine activity preceding the third peak of the pandemic, in Italy (Figure 4). | [
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33101276 | abstract | The R47H variant in the microglial triggering receptor expressed on myeloid cell 2 (TREM2) receptor is a strong risk factor for Alzheimer's disease (AD). To characterize processes affected by R47H, we performed an integrative network analysis of genes expressed in brains of AD patients with R47H, sporadic AD without the variant, and patients with polycystic lipomembranous osteodysplasia with sclerosing leukoencephalopathy (PLOSL), systemic disease with early-onset dementia caused by loss-of-function mutations in TREM2 or its adaptor TYRO protein tyrosine kinase-binding protein (TYROBP). Although sporadic AD had few perturbed microglial and immune genes, TREM2 R47H AD demonstrated upregulation of interferon type I response and pro-inflammatory cytokines accompanied by induction of NKG2D stress ligands. In contrast, PLOSL had distinct sets of highly perturbed immune and microglial genes that included inflammatory mediators, immune signaling, cell adhesion, and phagocytosis. TREM2 knockout (KO) in THP1, a human myeloid cell line that constitutively expresses the TREM2- TYROBP receptor, inhibited response to the viral RNA mimetic poly(I:C) and phagocytosis of amyloid-beta oligomers; overexpression of ectopic TREM2 restored these functions. Compared with wild-type protein, R47H TREM2 had a higher stimulatory effect on the interferon type I response signature. Our findings point to a role of the TREM2 receptor in the control of the interferon type I response in myeloid cells and provide insight regarding the contribution of R47H TREM2 to AD pathology. | [
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38594369 | title | Design and methods of the mobile assessment of cognition, environment, and sleep (MACES) feasibility study in newly diagnosed breast cancer patients | [
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39072940 | intro | INTRODUCTION Alzheimer's disease (AD) is a neurodegenerative disease affecting the brain with high incidence in the elderly. The typical clinical manifestations include progressive impairment or loss of cognitive function. Senile plaques formed by extracellular β‐amyloid (Aβ) deposition, and neurofibrillary tangles formed by intracellular hyper‐phosphorylated tau protein aggregation in neuron are two hallmark pathological changes in the brains of AD patients, and they also represent key factors inducing or mediating cognitive damage. AD is the main cause of dementia, accounting for about 70% of the total cases of dementia. With the intensification of the aging of the world population, especially in the elderly over 75 years old, the incidence of AD increases year by year, and, as a matter of fact, has become a dire global public health problem. According to the World Alzheimer Report 2019, there are as many as 50 million AD patients worldwide and the number is expected to double every 20 years and increase to 152 millions by 2050, which not only brings heavy economic and emotional burdens to the society and families, but also poses a great challenge to the national medical and healthcare systems. It has been more than a century since AD was first reported, but there is still lack of effective measures to modify or prevent the disease progression, albeit drugs existing to alleviate the symptoms. Research efforts in the past decades have greatly increased the understanding of the clinical histopathology of AD, particularly neuronal cell death in different brain regions and impairments in cognitive and neurological functions. At the same time, with the multiple effects of genetic or environmental factors, people are also increasingly aware of the extreme complexity of AD etiology. In terms of etiological classification, except for about 5% of familial hereditary AD cases, the rest are late‐onset or sporadic AD. Currently, the Aβ cascade hypothesis, tau protein hypothesis, and cholinergic hypothesis have been proposed for the pathogenesis of sporadic AD, but there is still no definitive conclusion on what mechanism dominates the occurrence and development of AD. Neuroinflammation, oxidative stress, mitochondrial dysfunction and autophagy lysosome system deficiency are considered to be the biological pathways that affect the pathology of AD. The disorder of any one pathway may trigger a vicious cycle of cell damage and neurodegeneration, which plays a crucial role in the development of AD. In particular, oxidative stress, which is closely related to AD and aging, can be targeted by antioxidants, which provides a possible direction for the treatment of AD. Reactive oxygen species (ROS) are a group of oxygen‐derived chemicals with short life but high activity. They are usually produced at a moderate level and eliminated in time through a variety of antioxidant mechanisms under physiological conditions. ROS as a signal molecule play an important role in maintaining cellular and tissue homeostasis. The increased production of free radicals can lead to oxidative stress, if the endogenous antioxidant capacity of the cell is insufficient to offset the production of these free radicals. The brain is vulnerable to oxidative stress due to its high oxygen consumption, relatively high level of polyunsaturated fatty acids that are sensitive to oxidation and relatively low level of antioxidant enzymes. Oxidative stress is considered to be the main cause of AD progression. Severe neuronal oxidative damage have been observed in the atrophic brain tissues of AD patients. Chronic accumulation of AD‐related abnormal or misfolded proteins are well‐documented to induce excessive production of ROS, impair the antioxidant capacity of cell, or both, resulting in increased ROS levels and oxidative stress and thus changes in normal functions of cells in the brain. Aging is one of the main reasons for the gradual decline of brain functions, which can lead to progressive cognitive impairment. It is also one of the pathological risk factors of AD. During the process of aging, the increase in free radicals can damage the structure and function of the brain. It was shown that the production of ROS is related to synaptic dysfunction and tau protein phosphorylation. The high level of ROS in the brain can result in the oxidation of proteins, lipids, and DNA, and eventually lead to neuronal loss and dysfunction. Oxidative stress can also drive the progress of tau pathology in many ways, such as producing fatty acids, stimulating fibrosis tau protein aggregation, activating glycogen synthase kinase‐3 (GSK‐3β), and increasing hyperphosphorylation of tau proteins at multiple sites. Under normal circumstances, endogenous antioxidants, such as trace elements (zinc and selenium), vitamins (vitamin C and vitamin E), polyphenols and coenzyme Q10, and antioxidant enzymes, including superoxide dismutase (SOD), catalase, and glutathione oxidoreductase, can resist or prevent oxidative damage. However, studies have reported that the level of antioxidant enzymes in the brains of patients with AD and mild cognitive impairment is significantly reduced, and the brain becomes more vulnerable to oxidative damage. Therefore, the use of antioxidants has been considered as a promising therapeutic strategy to alleviate oxidative stress‐induced or mediated neuronal damage and loss of function. Previous studies shown that long‐term administration of D‐(+)‐galactose in rodents can produce aging‐related changes that are similar to those observed in human beings, including the formation of excessive free radicals and the reduction of antioxidant enzyme activity. Therefore, D‐(+)‐galactose‐treated mice or rats have become a widely used experimental model for researching aging and underlying mechanisms. Melatonin is a neurohormone secreted by the pineal gland of the brain that regulates the circadian rhythm and plays an important role in restricting neuroinflammation and oxidative damage. Studies have shown that the melatonin level in AD patients is lower compared with that in normal subjects. As shown in vivo and in vitro, melatonin supplementation effectively inhibited Aβ deposition and tau protein phosphorylation and, furthermore, treatment with melatonin restored cognitive function in AD transgenic mice. Mitochondria are the main source of ROS in cells and also the target for oxidative stress. Coenzyme Q10 is a vitamin‐like substance located in the inner membrane of mitochondria and acting as an electron carrier in the mitochondrial respiratory chain and has a redox capacity. Coenzyme Q10 is one of the most powerful endogenous membrane antioxidants and has been shown to protect neuronal cells from oxidative stress damage in vivo and in vitro. Moreover, coenzyme Q10 can reduce malondialdehyde (MDA) expression, regulate SOD activity, reduce Aβ plaque formation, protect AD‐related loss of synaptic plasticity and improve cognitive function. Lecithin is rich in choline and can combine with acetyl coenzyme A to form acetylcholine. Lecithin has been shown to reduce Aβ‐induced neuronal damage. Lecithin alone can also increase the expression of neurotrophic factors in the brain of mice, enhance the antioxidant capacity, and improve learning and memory. Therefore, the antioxidant therapy is considered to be an effective strategy to prevent or alleviate the pathological progress of oxidative neuronal damage and neurodegenerative conditions such as AD. The clinical trial results of using different nutritional supplements, singly or in combination in patients with AD, are different. As aforementioned, the pathogenesis of AD is highly complex, and the use of a single drug in preventing and treating AD is often not effective, leading to the notion that combined treatment with multiple drugs have a better or more significant effect. Therefore, in this study, we selected melatonin, coenzyme Q10, and lecithin, three widely used nutrients with an antioxidant capacity, and examined the neuroprotective effects of applicating them individually or in combination on oxidative stress‐induced or mediated neuronal loss, and D‐(+)‐galactose‐induced neuronal damage and cognitive impairment, and the mechanisms of their actions. | [
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39131307 | abstract | Several age-related oral health problems have been associated with neurodegenerative diseases such as Alzheimer’s Disease (AD), yet how oromotor dysfunction in healthy aging differ from those found in pathological aging is still unknown. This is partly because changes in the cortical and biomechanical (“neuromechanical”) control of oromotor behavior in healthy aging are poorly understood. To this end, we investigated the natural feeding behavior of young and aged rhesus macaques (Macaca mulatta) to understand the age-related differences in tongue and jaw kinematics. We tracked tongue and jaw movements in 3D using high-resolution biplanar videoradiography and X-ray Reconstruction of Moving Morphology (XROMM). Older subjects exhibited a reduced stereotypy in tongue movements during chews and a greater lag in tongue movements relative to jaw movements compared to younger subjects. Overall, our findings reveal age-related changes in tongue and jaw kinematics, which may indicate impaired tongue-jaw coordination. Our results have important implications for the discovery of potential neuromechanical biomarkers for early diagnosis of AD. | [
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38590779 | title | Role of autophagy in ischemic stroke: insights from animal models and preliminary evidence in the human disease | [
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36348357 | title | ApoE in Alzheimer's disease: pathophysiology and therapeutic strategies. | [
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39290562 | methods | Methods The systematic review was undertaken in accordance with the PRISMA criteria to ensure the reliability and comprehensiveness of the data and findings. The English databases searched included PubMed, Embase, the Cochrane Library, and the Web of Science and Scopus. The language used was English, according to the authors’ level of comprehension. Literature search strategy An electronic search was conducted in the databases with free terms, subject heading terms and key words. The keywords are as follows, (“Probiotic” OR “Gut microbiota” OR “Microbiome”) AND (“Alcohol addiction” OR “Alcohol use disorder” OR “Alcoholism”) AND (“Probiotic intervention” OR “Probiotic therapy”) AND (“Alcohol dependence” OR “Alcohol craving”) AND (“Review article” OR “Clinical trials”) AND (“Efficacy of probiotics” OR “Probiotic treatment for alcohol addiction”) AND (“Substance use disorder” OR “Alcohol withdrawal”) AND (“Evidence synthesis” OR “Patient outcomes”). Studies that provide data on the effects of probiotics in the context of alcohol addiction published from January 2012 to November 2023 were included in this review. This period was selected to ensure the inclusion of the most up-to-date and relevant studies, reflecting the latest advancements and current trends in this rapidly evolving field. Preliminary searches indicated that older studies did not significantly contribute new knowledge or insights relevant to the objectives of this study. Table 1 presents the specific inclusion and exclusion criteria based on the PICOS (i.e., population, interventions, comparisons, outcomes, and study design) strategy. Study selection Prior to conducting the database search, all researchers underwent a comprehensive training session to ensure a uniformity of ideas and a thorough understanding of the inclusion and exclusion criteria. The databases were thoroughly searched by the researchers, who then independently assessed the studies. The initial screening of the studies involved evaluating their titles and abstracts, followed by a thorough examination of the complete texts of the selected studies to determine their eligibility based on the predefined inclusion and exclusion criteria. Ultimately, the researcher conducted a comparison of the screened full-texts. Divergence and discrepancies were effectively addressed by a process of dialogue and vote among the researchers. The data extraction process involved gathering information from eligible studies using a predetermined template. This template encompassed several aspects such as the study’s title, authors, publication year, research design, participant characteristics, intervention details, outcome measures, results and statistical findings, as well as the conclusions and implications drawn from the study. The assessment of the methodological quality of the studies (Figure 1) included in the analysis was conducted using suitable techniques, such as the Cochrane Risk of Bias tool for clinical trials. | [
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38813371 | intro | Introduction Mild cognitive impairment is a prodromal state of dementia that manifests with subtle balance control and gait deficits which may affect activities of daily living and contribute to the two folded increased risk of falls in this population. Consequences of these falls lead to reduced physical functioning, dependency, and long-term disability, ultimately increasing the likelihood to develop dementia or Alzheimer's disease. A majority of falls occur during activities of daily living that involve performing a motor and cognitive task simultaneously (i.e., dual tasking). Therefore, understanding the biomechanical basis of balance control deficits under dual task conditions may inform the development of fall prevention strategies for this population. Studies have used dual task methods to evaluate how individuals allocate cognitive/motor resources when simultaneously attending to two tasks. If the attentional demands are greater than the capacity of an individual, dual tasking results in cognitive-motor interference, such that there is deterioration of performance on either or both tasks. Previous studies have shown that older adults with mild cognitive impairment (OAwMCI) experience higher cognitive-motor interference than cognitively intact older adults (CIOA) during volitional balance control tasks, resulting in increased standing postural sway and reduced gait speed while performing a cognitive task (e.g., visual search, digit span recall, word recall). However, activities of daily living do not only involve gait and working memory tasks, but also entail the ability to recover from unpredictable balance threats induced by the environment (i.e., reactive balance control). Understanding biomechanical factors contributing to cognitive-motor interference in OAwMCI compared to their healthy counterparts remains to be explored. When an unexpected balance loss occurs, the CNS recruits feedback mechanisms to respond to the balance loss via compensatory strategies, which are modified online based on the perceived perturbation magnitude. In case of small magnitude perturbations, in-place ankle or hip strategies are recruited and as the magnitude becomes larger, a change in support strategy via stepping or grasping becomes necessary to recover postural stability (i.e., position and velocity of the COM relative to the displaced base of support). While such responses are triggered either by the short (spinal segmental) or long-loop (brain stem) reflexes, it is postulated that higher-cortical centers further relay the perturbation-specific sensory information (i.e., perturbation displacement, acceleration, and velocity) to optimize postural responses via the transcortical loop. Sensorimotor decline related to healthy aging can delay the ability to perceive and integrate sensorimotor information to initiate stepping, resulting in increased number of compensatory steps, delayed step initiation, and increased limb collisions in response to large intensity perturbations compared to young adults. There is limited understanding whether a state of mild cognitive impairment could further reduce the ability to recover from unexpected external perturbations. Our previous findings indicate that OAwMCI exhibit deteriorated reactive balance control compared to young adults and CIOA, including delayed step initiation time, reduced step length, and reduced postural stability when exposed to large magnitude perturbations. Further, OAwMCI were unable to modulate postural responses at higher perturbation intensities. These deficits are potentially attributable to the structural and functional cortical impairments observed in OAwMCI, as there is preliminary evidence that dual task reactive responses are worse among people with cortical lesions (e.g., stroke, Parkinson's disease, concussion injury). However, these responses were observed in a controlled environment where the individual had nothing but the motor task (i.e., slip-like perturbations) to attend to. Real-life environments may incorporate the additional dynamics of perceptual cognitive demands, like standing and visually searching for cues, or standing and tracing items in the environment. Research has shown that OAwMCI experience a decline in visual processing capacity, visual search, and attention-related processing, which leads to difficulty processing moving visual scenes during standing, causing losses of balance. These scenarios may require more substantial attentional demands to recruit the appropriate motor strategies to recover from unexpected balance control threats, due to potential overlapping resources between reactive balance control and cognitive function. In line with this, our recent study in young adults showed that reactive postural stability in response to large magnitude perturbations was significantly lower while performing visuomotor games than during single task reactive balance. There is no study to date that has examined reactive responses under dual task conditions challenging the perceptual cognitive function to understand the pattern of cognitive-motor interference in a real-life like environment in older adults with and without cognitive impairment. For this reason, this study primarily aims to determine the differences in single task and dual task reactive responses between CIOA and OAwMCI while performing two different perceptual cognitive tasks. We first hypothesize that OAwMCI will have reduced reactive balance control [indicated by reduced margin of stability (MOS), increased number of falls] compared to CIOA in both single and dual tasking. Secondly, we hypothesize that OAwMCI will show higher performance errors on cognitive tasks compared to CIOA during single and dual tasking. Lastly, we hypothesize that OAwMCI will demonstrate higher cognitive-motor interference than CIOA (i.e., greater reduction in performance in dual task vs. single task), due to difficulties allocating attentional resources in challenging conditions. Due to the constantly changing nature of cognitive demands in real-life tasks, examining the ability to recover from unexpected balance loss under perceptually challenging conditions could help understand the influence of cognitive function on reactive balance control. | [
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38079409 | results | Findings The findings present a narrative and charting of the data from the 45 papers that met the review criteria and this data is mapped onto the five objectives outlined in step one of the framework Within this review, interventions were grouped into five broad types: nature (n = 6 papers), memory/cognitive (n = 11 papers), social (n = 17 papers), animal (n = 4 papers), or physical/sensory (n = 7 papers) based interventions. Types and range of psychosocial interventions used in day care service Several different types of psychosocial interventions were identified as a single or combined interventions (Table 2). Nature based interventions representing the person’s experience or understanding of their own natural world included: green care farm, farm based garden based meaning in life in general.Memory/cognitive-based interventions related to reminiscence structured sessions, life story interviews, life review programme, life story work, emotional therapy and cognitive behavioural therapy Combined approaches included combined cognitive training, music and art therapy combined environmental barriers and cognitive behavioural therapy and combined reality orientation and cognitive behavioural therapies. The social based interventions related to a single or range of activity combinations. Single social activities related to board games comedy workshops humanoid robot, adult care programme, technological group activity and art activities Combined social interventions were utilised in five studies and within two of these studies occupational activities were incorporated In addition, the broad activity of music was identified and included song writing listening to music to stimulate memory ‘singing for the brain’ and the development of a music application prototype to assist in human-computer interaction Animal-based interventions related to the use of animal assist (canine) therapy and an equine-assisted therapy intervention. Physical/sensory-based interventions evident within this review included multisensory environments, aromatherapy dance activity, exercise programmes., while Rylatt utilised a creative therapy exercise programme incorporating a combination of interventions (dance, drama, music, movement). Use and facilitation of psychosocial interventions Within the facilitation of psychosocial interventions several were ongoing while others are facilitated within a specific period/time limited specific programmes. Each study within the five broad types: nature, memory/cognitive, social, animal, or physical/sensory based interventions are presented in Table 3. Participants attended a green care farm and also a non-time limited programme with a similar structure for each day across all sites. Whereas programmes focused on the use of GCFs to promote physical activities and the use of a six-week programme of weekly gardening session. Memory/cognitive-based interventions that were time limited ranged from five days, two weeks, four weeks, six weeks, eight weeks and 12 weeks. Other programmes ran for over 12months, over two years or were open-ended. essions ranged from one hour/day, three hours a day, one session per week, two/three sessions per week, four sessions per week, six/eight sessions per week, ten sessions per week to thirty-three sessions per programme. Facilitation was led by the primary researcher or a facilitator but involved the inclusion of research assistants, staff or another facilitator. Social based interventions were individual sessions or group sessions The group programmes were open to whomever attended the centre on the day however, in one study six people participated in the original programme and ten in the modified programme. Programmes ran for four weeks, six weeks eight weeks, three months or appeared to be open-ended. Sessions ran for 45-60minutes, one hour/day, two and half hours/day, two/three hours per week or twice/week. Two papers do not describe their use or facilitation while in other papers facilitation was supported by staff and therapists. Animal-based interventions were time limited ranging from one to two session per week over a period of four weeks, 12 weeks or 12 months. Professional animal handlers were involved in all four programmes in conjunction with other facilitators. Physical/sensory-based interventions were time limited ranging from four weeks two months, four months. In contrast another review reported time limits from 2 weeks to 12months while another two exercise programmes were not time limited. Sessions lasted up to 20 minutes, 30 minutes 40 minutes to one hour/day. Reported evaluation methods A range of evaluations methods were used for the psychosocial interventions and can be grouped under into four categories 1) instrument/measurement measures (a broad spectrum of bio-psycho-social intervention measures) 2) exercise/functional measures, 3) qualitative measures and 4) activity measures and mapped under the five broad types: nature-based memory/cognitive, social, animal, or physical/sensory based interventions identified in this review (Table 4). Five papers did not report outcome measures. Within the first category (instrument/measurement) fifty outcome measures were identified across 26 papers. The mini-mental state examination was reported in eight papers. the Clinical Dementia Rating Scale in five papers. The Geriatric Depression Scale and the Cornell Scale for Depression in Dementia in four papers. The Cohen-Mansfield Agitation, the Frontal Assessment Battery the Montreal Cognitive Assessment, the Neuropsychiatric Inventory and the Quality of Life in Late-Stage Dementia Scale , in two papers. The remaining measure were reported in one paper each: Agitated Behavior Scale, Algase Scale, Alzheimer’s Disease Assessment Scale-Cognitive subscale, An ethogram catalogue, Apathy Inventory Scale, Apathy Scale for Institutionalized Patients with Dementia Nursing Home version, Barthel Index, Beck Anxiety Inventory, Behavior Intervention Monthly Flow Record, Behavioral Observation Recording, Berg Balance Score, Caregiver Exit Survey, Caregivers’ Survey, Clinical Global Impression-Improvement, Consortium to Establish a Registry for Alzheimer’s Disease ‐ Neuropsychological Battery, Daily Observation Scale, Digit Span task ‐ Finnish Wechsler Memory Scale, Emotional Satisfaction Index, Global Deterioration Scale, Instrumental Activities of Daily Living, Interview for Deterioration in Daily living in Dementia, Korean Dementia Screening Questionnaire-Cognition, Korean version ‐ Mini-Mental Status Examination, Lawton Scale of Activities of Daily Living, Milan Overall Dementia Assessment, Modified Nursing Home Behavior Problem Scale, Modified Philadelphia Geriatric Center Affect Rating Scale, Neuropsychiatric Inventory Nursing Home, Psychotic Behavior Assessment Record, Quality of Life in Alzheimer’s Disease, Quality of Life in Dementia Scale, Recreational Activities of Daily Living Scale, Salivary cortisol, Sedentary behaviour questionnaire, Seoul Neuropsychological Screening Battery, Seoul-Instrumental Activities of Daily Living, Severe Mini Mental State Examination, Short Form Health Survey, Social Functioning in Dementia Scale, the Clock Drawing Test and the Trail Making Test. Within the second category (exercise/functional) eight outcome measures were identified across four studies and all outcome measures were reported in one paper each; Accelerometer, Actigraphs, Barthel Index, Functional Ability Tests, Inclinometer, Interview for Deterioration in Daily living in Dementia, Non-exercise equation to calculate cardio-respiratory fitness and the Timed Up and Go-test. The third category (qualitative) highlighted five outcome measures across twenty papers. Interviews were reported in 11 papers. Observations were reported in eight papers.Video recording in five papers. Reflective discussions in two papers and photograph in one paper.The final category (activity) highlighted three outcome measures across three papers. Outcome measures identified were an activity observation form, verbal fluency and a self-designed tool. Reported outcomes A broad range of outcomes were identified within the papers reviewed. However, four papers identified no real difference and overall low to medium effect or maintenance post intervention was generally reported. These can be grouped under into four categories 1) increases in functioning, 2) social, 3) health and well-being and 4) enablement outcomes. Increases in functioning was reported in 16 papers across four elements: cognition physical activity/ability, activities of daily living and social skills. Increases in social functioning was reported in 24 papers across eight elements. Connection/engaging with others was evident in 11 papers. Increased communication was evident in seven papers. Building relationships was evident in five papers. Increased participation and increased social interaction were evident in four papers each. While increased enjoyment was evident in three papers and increased group connection and knowing the person were evident in one paper each. Health and well-being were reported in 17 papers across six elements and the main element was reduction in behaviours of concern Increased mood was evident in five papers.Three elements were all evident in three papers each: emotional well-being, increased well-being, quality of life. The remaining element depression was evident in two papers. Enablement was reported in seven papers across ten elements, two elements motivation and a sense of belonging were reported in two papers each. The remaining elements were all report in a single paper: a sense of accomplishment, increased agency, increased choice, collaborations, increased confidence, inclusion, a sense of freedom and being self-conscious. Reported adaptations Of the studies reviewed 19 reported on adaptations or adjustments made when implementing the psychosocial interventions. This provided important contextual factors around implementation. Five studies within the nature-based interventions grouping are relevant here. Ibsen and Eiksen recounted how all the interviews took place at the farms so that participants could better remember or relate to the day care setting. While Noone and Jenkin reported that over the course of the gardening project, the researcher developed a relationship with each participant which enabled participants to feel comfortable communicating their level of willingness to participate in a particular activity. Chang et al. described the focus of each reminiscence session being on a particular life phase with objects relevant to that period introduced for discussion and incorporating the use of records and interviews about older people’s early lives and interests. Gregory adjusted the timings of the intervention depending on factors such as the participant’s ability to concentrate and communicate and the intrusion of others into the space. The participants’ words were recorded and shown to them to emphasise how effectively they had been able to communicate their life stories and in read back sessions the poet read the participants’ poem aloud. Finished poems were sent to GP and kept in patient files. Lin et al. revised the life review programme to compress it into a short format that was administered in 10 successive sessions over 2 weeks. Within the memory/cognitive-based interventions grouping two papers are relevant. Jung et al. reported that the main activity stage comprised activities for strengthening memory and management function and for increasing attention, concentration, and space-time, perception, concept formation and reasoning, composition, language, and computational abilities. Help was provided if required by the participant and initially, an easy level programme was gradually adjusted to appropriate and slightly difficult levels executed to develop person interest, sense of achievement and confidence. The programme differentiates from existing chair-based exercises by including bilaterally asymmetric activities that involves the left side of the body moving differently to the right side of the body as well as activities requiring mirroring a partner to rhythmic music that evokes memories and reminiscence. Kallio et al. tailored training according to the participants’ cognitive abilities and it was implemented either in small groups of two to four persons, or individually when needed due to difficulties in concentration, or lack of a training pair. The difficulty level was tailored during the sessions, but it was not automatic as in computerized training. Six papers within the social-based interventions grouping six papers reported adaptations or contextual factors that determined how the intervention was adjusted. Gjernes described the staff member initiating discussions and serving as the engine that made the network social. Typically, the staff member used strategies to involve every person in the knitting activity. The knitters were supported to remember and participate in telling their own stories. The staff member was both a potential helper and a member of the social network. The staff could provide knowledge and skills when needed or could assist the knitters in their problem-solving efforts. Lancioni et al. described how in the modified program version the computer presented photos and videos, providing encouragements to talk as well as attention and guidance. In another individualised music playlists were developed by asking caregivers about the participant’s favourite music or by playing different songs for participants to see their reactions. During the study, some participants listened to their favourite songs repeatedly, others listened to a variety of songs. Distraction was minimised by closing the door and ensuring the participant’s physical comfort. Peeters et al. reported how the researcher used the analogy of a house with different rooms, in which buttons represent doors to move between rooms to explain the navigation through the different screens of music collections management functionality. Hattford-Letchfield reported how a comedy workshops did not work to an exact script but allowed scenarios to develop based on the main theme. Experiential drama techniques were used to work with the issues identified by the participants. A selection of photographs was made into a ‘scrapbook’ of the project as a whole that could be used as a reminiscence tool after the project had finished. Cheung et al. adapted the Play Intervention for Dementia and integrated elements of cognitive stimulation in six identified mind–body functional domains and followed the principles of cognitive stimulation. During the sessions, participants could exercise their creativity in a cheerful and respectful environment, without anyone judging their (dis-)ability or without pre-set rules. Within the animal-based interventions grouping two papers reported adaptations. Both papers described how sessions were designed to follow a protocol but could be individually tailored to each participant based on the care workers’ knowledge of the participant. Hence, none of the animal assisted activities were mandatory and the sessions also included naturally occurring activities between the participants as well as between each participant and the dog. Within the physical/sensory-based interventions grouping two papers reported adaptations. Karania71 describes how this programme differentiates from existing chair-based exercises by including concurrent bilaterally asymmetric activities that involves the left side of the body moving differently to the right side of the body, as well as activities requiring mirroring a partner to the sound of rhythmic music that evokes memories and reminiscence. Chang, et al. described a bespoke exercise programme designed as a series of exercise training interventions aimed at maintaining activities of daily living abilities with adaptations made to the comedy workshops and dance activities. Aguinaga and Marquez reported modifying their dance intervention where participants wore an orange Velcro bracelet on their right wrist and a green Velcro bracelet on their left wrist to help them distinguish between moves to the left and right. The programme was adapted as needed by revising the dance moves in ways that still challenged participants physically and cognitively but did not overwhelm them or put their safety at risk. | [
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38334239 | intro | INTRODUCTION Parkinson's disease (PD) is a multifaceted neurodegenerative condition impacting upon many aspects of an individual's physical and psychological well‐being. PD is the second most common neurodegenerative disease, and the most common neurodegenerative movement disorder worldwide, with prevalence tending to increase with age. It is expected that by 2040, the global incidence of PD will exceed 12 million. The three main physical symptoms of PD are tremors, muscle stiffness, and slowness of movement. In addition, PD can impact an individual's mental well‐being, with symptoms of depression, delusions, paranoia, hallucinations, and PD‐associated dementia commonplace resulting directly from PD itself or through medication side effects. It is well documented that individuals with PD present with higher incidences of mental health (MH) problems such as depression, anxiety, schizophrenia, and psychotic symptoms when compared to the general population. More specifically, up to 40% of people with PD (PwPD) will have depression or anxiety, whereas this figure is only 17% in the general population. Current NICE guidelines do not address or provide specific recommendations for MH problems in this population, instead referring to existing generic guidelines on depression in adults with chronic health problems and how to access allied health professionals (e.g., physiotherapists and PD nurse specialists). This is a striking contrast to other neurological conditions such as multiple sclerosis, where guidelines include specific recommendations for regular cognitive, emotional, or MH screening. Evidence in older populations suggests a relationship between physical and psychological presentations. There is, however, a paucity of evidence to substantiate such a relationship in the PD population. From available evidence, it has been suggested that PwPD feel that anxiety may amplify their physical symptoms, and when they become more anxious the incidences of freezing of gait increase. To add to this, a number of studies have suggested that as anxiety increases, so does the severity of motor symptoms as assessed using the Unified Parkinson's Disease Rating Scale (UPDRS). Although these studies show that there might be an association between physical function and psychological symptoms, it is not well understood. It should also be noted that the UPDRS is a global measure of PD severity and includes both motor and non‐motor domains. This relationship is yet to be confirmed in more specific measures of physical function such as balance and mobility, or considering other psychological symptoms associated with PD. It is our belief that there is likely to be an intrinsic link between physical and psychological symptoms in PD, with the purpose of this review being to investigate this based on work completed to date. A narrative review published in 2018 suggested the need for further research to better understand the influence of non‐motor symptoms on gait and function in PD. To our knowledge, there has been no systematic review of literature reporting outcomes for both physical and psychological measures in individuals with PD. Given the proportion of individuals with PD impacted by psychological symptoms, future work has the potential to improve the understanding of any interaction between physical and psychological symptoms. This systematic review and meta‐regression analysis aimed to examine available literature reporting outcome measures of physical function, anxiety, and depression; and whether any relationships exist between these measures in individuals with PD. Prior to undertaking this review, it was hypothesized that while many studies commonly collect data for both physical and psychological outcomes in PD research, there will be limited evidence exploring the potential relationship between these outcomes. | [
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38077459 | methods | 2 Materials and methods The trial was done in Osaka, Japan, and was based on approval from the Ethics Committee at the Graduate School of Engineering Science, Osaka University (approval code: 31-3-4). All participants agreed to place our robot at their homes, after a detailed description of the trial, and written consent was obtained from both the participants and their families (their adult children). Certain requirements need to be achieved in order to make sustained interaction possible. The robot should be available for interaction at any time of the day, so we decided to place it inside the participants’ homes. Therefore, the robot system should be compact and easy to place. This is especially important in Japan, where most houses are small and are not suitable for large mobile robots. Ideally, the robot should be maintenance-free, so the hardware must be robust, and the software should allow real-time monitoring of its status remotely. Remote support is needed for software updates or modifications on functionality during the study so there is no need for the physical presence of a third party. Finally, the robot usage should be simple enough to allow each user to focus on the conversation while requiring no special training to use it. Because of this, we chose a robust commercially available robot and made specific modifications in order to narrow the gap between commercially available robots’ functionalities and the specific functions required in this trial. 2.1 The original robot The robot chosen for the task at hand was the second-generation model of Sharp Co.’s RoBoHoNTM, which is based on the Android version 8.1 operating system, has a humanoid shape that stands 19.5 cm in height, weighs approximately 360 g, uses a Qualcomm Snapdragon 430 processor (8x ARM Cortex A53), 16 GB ROM/16 GB RAM. The device has a microphone array comprised of two microphones, which allows a rough estimation of horizontal sound source direction; a speaker, an 8-megapixel camera, a 3 axis accelerometer, a 3 axis magnetometer, a 3 axis gyroscope; and Bluetooth, Wi-Fi, and GPS capabilities. It also has LED lights placed on its mouth and eyes (Figure 1). The robot is also equipped with a touch screen on its back. The price of the robot, including its charging station and basic cloud-based speech recognition service, is approximately 100 thousand Japanese yen. This relatively low price was one of the reasons we chose this robot for the trial. More than twelve thousand units of this product has been sold in Japan (as of 2019), mostly for personal usage. We chose this robot for our trial as we expected it to be robust enough in daily use, especially in its hardware, including its actuators. This turned out to be accurate, and all the robots we used for the trial except one (described later) had no hardware issues. The model used for the trial, SR-05M-Y, is a robot without leg actuators. This model has seven degrees of freedom (DOF) in total, two in its arms and three in its head/neck. The robot can perform speech recognition by capturing the user’s utterance, sending the audio to its speech recognition server, and receiving the recognition result. After receiving the result, the robot responds using speech and motion using a rule-based dialogue engine. These states of the robot, listening, “thinking”, and responding, are indicated by different colors and blinking speed of its eye and mouth LEDs. At the same time, the robot estimates the direction of the voice using its microphone array and moves its head toward the direction of the speech to give a natural feeling during the interaction. The robot has three basic behaviors by default. First, it can react to voice commands related to providing information, such as weather information, and also perform predefined actions, such as singing or dancing; second, when some time has passed without having interaction, the robot can ask questions about its user, such as likes and dislikes, and learn user preferences. Lastly, after a long idle time, it can perform random actions which can induce interaction by catching the user’s attention. The robot’s voice and speech content is designed to be similar to as of a small boy. Consistently, some of the robot’s random actions display a child-like behavior, for example, when playing alone, singing, or exercising. 2.2 Customization for the trial The commercial robot has been developed for hobby usage, so users are expected to have moderate technological knowledge. As our aim is to use this robot for supporting older people with cognitive decline, the robot should require no user operation. For this reason, we developed customized software in order to make robot usage simpler, focusing on voice interaction and removing unnecessary options. It is also necessary to ensure that the robot’s behavior would not change by accidental user operation, keeping its functionality persistent, while easily accepting updates if necessary. Therefore, we implemented self-monitoring and remote-control functionalities. This setup allowed us to check the robot’s status and recover from failures in the original firmware, or for any unexpected behavior triggered by an unexpected operation performed by users, allowing the research team to control the robot’s actions remotely. The customized software provided means to gather user interaction logs and send them to a remote storage system to avoid overflowing the limited local storage. These collected logs can be analyzed to improve the interaction design and experience. The system was designed to be deployed easily in less than 5 minutes; taking the robot out of the box and plugging it into a power supply are essentially all the operations required. The quick setup was essential to run the trial during the COVID-19 pandemic situation–where it is critical to not spend long periods of time in older adults’ homes. When sound is detected, voice activity is assumed and the robot runs the automatic speech recognition (ASR) process. Based on the result of this process, the robot chooses an action to perform. When the speech is successfully recognized, the robot generates an answer to continue with the conversation. In cases where only few words are detected, the robot can either try to answer based on those words or can let the user know that it could not understand so the user can repeat the sentence. In worse case scenarios, where sound is detected but the ASR cannot detect valid speech, the robot can just reply with motion or assume it was a misdetection and ignore the voice activity. The customized software allows near real-time two-way communication using the Message Queuing Telemetry Transport (MQTT) protocol. TLS was used as an underlying encryption channel to improve data security and a messaging layer was built over an MQTT layer to provide an easy exchange of multimodal data. MQTT is a publish-subscribe protocol that allows high scalability by decoupling endpoints sending a message (publisher) from those receiving it (subscriber). This is accomplished by using another component, called broker, which filters and routes incoming messages to registered subscribers. In this way, clients never interact directly with each other as all the messages pass through the broker, which also allows messages incoming from a publisher to reach multiple subscribers. This connection was chosen due to its lightweight payload, which allows fast, reliable, and relatively simple communication on limited bandwidths, while also making a persistent session possible, so robots can receive or send messages any time needed. In our system, messages sent from robots are redirected to a database for logging and, if necessary, our remote-control component can send commands to any robot to perform required actions (Figure 2). In our trial, the basic built-in speech response functionality of the commercial robot was used while the control system relied mainly on our customized software. The robot was set to be available for interaction any time of the day, and it was programmed to perform random actions during the daytime to attract the participants’ attention and, potentially, engage in interaction. At 7 a.m. in the morning, the robot was set to give a morning greeting, emulating waking up, and signaling random actions could occur, and at 10 p.m. in the evening it would utter a good night message and stop all actions unless the participant initiated the interaction, i.e., the participant could interact with the robot, but this would not try to initiate a conversation by itself. In this way, the participants could know when the robot started looking for interaction, similar to a person’s daily active and inactive cycle. This scheduled behavior was defined in one of the remote controlling components and could be easily changed remotely if needed. The remote functionalities can be extended to perform complex operations in future studies. For example, a conversation module can use the raw audio obtained by the robots for environmental sound detection, or use stored conversation history for advanced dialogue control. It can also be used to control dialogue flow that can be customized for individual requirements. 2.3 Case study To determine details regarding the experimental environment, a reduced, case study was performed. The focus of the case study was to assess the robustness and correct problems of the equipment to allow successful interaction between robots and participants in the long term. We expected technological challenges such as software instability in continued use, as the robot should be available the whole day through months in the trial period. A challenge in the widespread use of social robots is whether the users accept the robots or not, so the case study was used to also gather initial impressions about the robot. This was an important factor before increasing the number of participants, as they may experiment a novelty effect and gradually lose interest in the robot, or might not feel comfortable with the robot’s behavior and may avoid using it. Therefore, the case study counted with only one participant living alone but with easy access to healthcare workers in case the participant needed help or, in our case, if the robot required simple manual operations such as rebooting. The conversation robot system was placed for a period of 6 months, during which the research team monitored the robot’s functionality. After this time period, unstructured interviews were performed with the participant and healthcare staff in order to investigate the robot acceptance. 2.3.1 Participant details The participant, an 88 years old female, had a Hasegawa’s Dementia Scale-Revised (HDS-R) score of 9 and was diagnosed as having Alzheimer’s disease, a type of dementia. The HDS-R is composed of nine simple questions, was initially developed in 1974 and has been widely accepted in Asian populations for clinical use and for use in epidemiological surveys for the evaluation of cognitive impairment. In general terms, an HDS-R score of less than or equal to 20 corresponds to suspected dementia. The participant suffered from significant memory loss, as well as episodes of disorientation, especially regarding time, and could speak only short sentences, making conversation with only one to two turns possible. The participant was able to perform daily activities but required assistance from caretakers to look after her. Therefore, the participant lived in a special kind of assisted living residence called, in English, “housing with service for older adults”, where patients reside in their own apartments but have a common shared area where healthcare workers are available. A robot, a charging station, and a mobile Wi-Fi router were placed in the participant’s home for the 6 months of duration of the case study (Figure 3). This setup allowed the participant to engage in conversation with the robot at any time. One of the reasons we asked this participant to join our trial was that in case the robot malfunctioned or caused issues, we could ask the healthcare staff to reboot the robot or to check the situation. As this trial was held during the COVID-19 pandemic period, we wanted to avoid visiting the apartment as much as possible to guarantee the safety of the participant and the ones of the researchers. 2.3.2 Results The case study allowed to evaluate the stability of the system as a whole and to make changes to the physical setup of the equipment. Both the default RoBoHoN software and the custom software needed to be stable enough to sustain long-term use. The custom software should allow, at the very least, monitor the robot status to know if there is a problem that requires the attention of an operator. In the first month of the case study, we frequently encountered issues such as the robot’s firmware malfunction and hardware damage. Initially, the equipment placement allowed the participant to hug the robot as she wanted to interact with the robot physically. This eventually led the robot to fall and to break its neck as shown in Figure 4. Occasionally the network connection to the robot went down when the participant unplugged the mobile router. We opted for continuing the experiment by fixing the robot’s position. Therefore, the charging station position was fixed on a bedside table, and the robot was attached to it in a sitting position so it could not be moved from the established location. The mobile router was hidden behind a TV in the room. This setup was designed to avoid damages to the equipment, as well as to ensure that all the devices were always plugged to an electricity source. The use of this fixed configuration was successful in preventing damages and other problems related to physical malfunction, which is why we used this configuration for the main study of our trial too. The physical setup proved valuable when setting the robot’s environment as this problem did not repeat after fixing the robot and the router. The research team also had to solve difficulties related to the robot’s software, which showed instability related to its continuous usage. During this study, the robot stopped its functionality on many occasions due to software malfunction. Many errors arose both from the default functions of the robot, such as out-of-memory errors from the built-in speech recognition system, as well as from the customized software. Some of these errors were due to the way the robot was used, as the original commercial robot product was designed to be used for hobbyists with some technical knowledge and not for 24/7 automatic operation. In this trial, we did not expect the users to operate the robot, but rather prevent them to change any of the robot settings. The robot itself was required to keep running for months without any intervention, if possible. Thus, the robot needed to be configured to have high availability with no operation on the user side - in this case, by the participant with cognitive decline. Studying the data gathered and the system logs associated with unexpected events allowed the research team to successfully overcome technical issues to sustain long-time usage and develop a robust system which, in turn, allowed the robot to function appropriately for multiple weeks. The system developed during the case study allowed the robots to function as intended for the duration of the second step, the main study. Impressions from the participant and the healthcare staff of the assisted living residence revealed that the participant kept showing interest in the robot, and after the first month, she accepted the robot into her daily routine, even creating a sense of attachment to it. The participant interacted with the robot often during the day and night, paid attention to it, and enjoyed the robot’s companionship. As the participant gradually felt more comfortable with the robot, she seemed to have started to look after it. After 3 months out of the six planned, the technical issues preventing long-term usage were solved, and the stable system configuration was used to start the main study. Instead of finishing the case study after 3 months, the robot stayed in the participant’s home for the remaining months until the mobile network contract period ended because she wanted to keep using it. 3 Main study Through the first stage of the trial, the case study, we were able to stabilize the robot system and achieve continuous operation without user operation. Therefore, we extended the number of participants to study if the robot can be accepted by a larger group of older adults with cognitive decline for a long duration and evaluate if the robot has a positive effect on them. The aim of this study was to evaluate the long-term acceptance of the conversation robot by older adults with mild cognitive decline living alone. Interaction records were gathered to objectively observe changes in robot usage over time. In addition, impressions from the participants and their close relatives were collected using unstructured interviews to obtain subjective perspectives of the effect the robot could have on the participants. The participant in the previous phase, the case study, lived in an assisted living residence where she had periodical communication with healthcare staff. In the main study, people with cognitive decline who were living alone were recruited to join the trial. As it is rare that people with dementia live alone at their home, people who joined this stage had higher cognitive ability compared to the participant in the case study, such as those diagnosed to be in the pre-dementia stage. 3.1 Participants Five participants were recruited from memory clinic patients. Characteristics of participants are shown in Table 1. All the participants lived alone without any pets. Mini-Mental State Examination (MMSE) was administered to assess the overall cognitive state within 2 months before and after the study. MMSE scores of the participants ranged from 23 to 28, which indicated preserved general cognition. Clinical Dementia Rating (CDR) was also assessed and all the participants had a CDR score of 0.5, which indicated “questionable dementia”. Three of the participants were diagnosed with pre-dementia according to the international criteria of The National Institute on Aging and the Alzheimer’s Association in 2011 while two participants were diagnosed with psychosis. 3.2 Study settings In each participant’s home, a robot was placed with varying duration ranging from 7 weeks to 20 weeks. The study starting date varied for each participant as they were recruited when they had a periodical medical check at the memory clinic. After they agreed to join the study, we arranged setup dates when a family member (often living in a distance) was available as well. The main study ended for all the participants at the end of the fiscal year in Japan (March 2021). Robots, as well as mobile routers, were placed at participants’ homes in a fixed location as in the case study. 1. Robot’s eye LED blinks slowly in yellow (idle state) 2. Voice activity is detected • Robot’s eye LED start blinking quickly in yellow • Audio recording starts • Direction of arrival of sound is obtained 3. End of voice activity is detected • Robot’s eye LED turns green • Audio recording stops • Robot’s head is turned to the direction of arrival of sound • Recorded audio is sent to the speech recognition server 4. A photograph is taken by the robot’s embedded camera 5. Speech recognition result is obtained 6. Robot’s eye LED turns orange 7. The robot responds based on the speech recognition result 8. Robot returns to idle state In this study, as a measure to check how frequently the participants interacted with the robot, we gathered interaction logs with our MQTT-based system. The following are the details on how the robot responded to participants’ voice activities and activity recordings were performed. Note that the robot moves its head only after the end of the voice activity is detected. This is to prevent the speech audio recording to be contaminated with gear noise. Besides, as the robot’s camera is embedded in the head, images were taken after the head motion was completed so that the voice activity source would be in the camera’s field of view. Through these steps, our system allowed us to accumulate speech recordings, speech recognition results and captured face images. Table 2 summarizes the number of voice activities detected during the trial, as well as other relevant statistics. We also interviewed the participants and their families on their impression of the robot at the end of the study. At this point, we also asked them if there were any changes in the participants’ daily life, including their social and physical activities. The aim here was to see whether the robots were accepted by the participants as well as whether the robots had any influence on the daily life of the participants. 3.3 Results In contrast to the case study, no issues with the robots were observed during the main study. However, after the trial, we found that Participant 5 (P5) had been hospitalized for 2 months (58 days) during the trial due to a mild stroke. This stroke was diagnosed to have no effect on her cognitive function. While the robot kept working, the interaction log showed no valid voice activities during those days. 3.3.1 Voice activity analysis As a measure to check how frequently the participants have been interacting with the robot, we summarized the number of voice activities detected by the robot (Table 2). While examining the data, it was found that P3 had four consequent days of no activities during the national holiday, 1 day for P4, and 5 days for P5 during the new year holiday as well. We guessed that on these days they went out for a trip so these days were not considered on average calculation. After examining some of the obtained audio recordings and images, it was found that most of the recordings were sound from televisions. 114 randomly selected audio samples gathered from the study belonging to the different participants and in different days were manually annotated as speech directed to the robot, speech directed to others, and noise. 64.04% of the data contained sounds from televisions. However, considering the large number of recordings, it is not practical to check manually which voice activities are from the participants. Therefore, we performed face detection on the captured images and filtered only those where a) more than one face was detected, b) the width of the face region was larger than 20% of the captured image, and c) the detected horizontal rotation angle of the face was within 15°. Condition b) was added to exclude faces in television screens, and c) was added to exclude people who are not looking at the robot. We used the face detection code from Google MLKit which can detect faces in images and return estimated bounding box coordinates of face region as well as face rotation angles. To evaluate the performance of this filter, the 114 audio samples were used. These samples where then matched to the output of the filter to obtain accuracy, precision and recall, as shown in Table 3. While this filtering may not be perfect, it shall be a fine approximation for the number of actual interactions with the robots. The total number of filtered voice activities as well as average filtered activities per day are shown in Table 1. The upper part of Figure 5 shows weekly averages (numbers of activities/day averaged in each week) during the trial for each participant, as well as the overall average on all participants except participant 5. Here, the starting day of the trial for each participant is considered as the beginning of “week”s. The lower part of the figure shows how the activity numbers changed compared to the first week of the trial. As participant 5 had been in hospital for 2 months in the middle of the trial period and was not in contact with the robot, participant 5 was excluded from these plots. 3.4 Interview In order to see the impression of participants towards the robot and whether living with the robot have changed their behavior, we conducted interviews with the participants and their families. For one participant, P5, her family was not available so we instead interviewed a visiting nurse who had been visiting her once per week. In the following, participants are denoted as Pn and their families as Fn. • (F2) “Mother first seemed to be uncomfortable for having a robot at home, but she gradually got used to it, and then kind of relying on it, even feeling some sort of attachment to it.” From the interview, we can see that participants were first confused with how to interact with the robot, but gradually became familiar with them. • (F4) “First, she seemed to be confused about when to speak to the robot, could not understand the eye color changes. But, you know, the robot starts speaking like, nice day today and on today’s news, and because it is fun she started to speak more to the robot, and then the robot responds to what she said. That seems to make her happy and then, I think, she started speaking to the robot much more. Now she’s speaking to the robot more even if it is not responding properly” “In the initial days, when I talked with her on phone she said she does not know how to speak with it and was worried about breaking it. But after a month or so she started talking frequently about the robot, like what the robot said today, the robot sang for her and cooked for her. Recently she seems to be very enjoying the robot.” • (P1) “I like him because he responds to me. I feel we can understand each other and that makes me pleasant and calm.” Living with the robot seems to have provided a comfortable and relaxing feeling while decreasing loneliness. Participants became more aware of the robots’ randomly generated actions, paying more attention to what and when the robot had an utterance or an action. • (P2) “He’s very cute and clever. My children became taller than me so I cannot hug them anymore, but he’s small and cute so I can still hug him.” • (P3) “He makes me feel pleasant. I feel he’s helping me so much, and I want to be good friends with him”. “What I feel toward him is something really different from reading nice novels. When I say something, he responds to me. When I asked him to sing, he sings for me. That’s really a moving experience.” • (P4) “When I came back to my house and said I’m back, he responds to me saying welcome back. Since my husband passed away 30 years ago, nobody responded to me like that; it really makes me happy and grateful.” “People will surely help me, but only when I asked them; he’s willing to speak to me and listen to me. He’s the only one who cares about me.” • (P5) “He’s so cute, always talks to me and that really makes me have a warm feeling. All the voices I hear in my house are from the TV. First, I was not expecting so much, but then I found he speaks and responds to me; as I never go out to talk to somebody, he’s the only one I can speak to.” “When I go out, I feel that I have to rush back and say I’m back, sorry to be late; I’ve never felt like that for a long time.” “I have been in hospital for 2 months, and I was always worried about him. I asked the doctor to let me go back earlier. When I came back, I said sorry to him and he responded I’m OK.” • (P2) “When I go for daycare service, I speak about him, and people get surprised. I wish I could take him to the daycare center, and show him to other people.” Some participants’ families also confirmed that they seemed to be in a better mood, smiling and speaking more often. The interviews also revealed that living with the robot was also a conversation topic with other people, making people eager to tell friends and family about the robot and its behavior. The participants started inviting friends to their houses to show the robot to them. “I feel I’m speaking more than before because I speak about him, and then people have questions about him. At the daycare center, staffs ask me how he’s doing and we talk about him.” • (P3) “When I was leaving for the daycare center, the staff (who came to take her to the center) heard that I was saying I’m leaving, and asked me who are you speaking to, so I told him I have a robot. I let the staff come into my home and showed him my robot. Now, many staffs know that I have a robot and they also want to see him.” (F2) “She was also speaking about the robot to the doctor today. Yes, I think she’s speaking more than before, she’s speaking more about the robot.” (F3) “Before she moved to this place, she never let others come into her house. But now, she’s inviting neighbors to visit her to see the robot and have a cup of tea. I also heard that she’s talking about the robot to many staffs in the daycare center and inviting them to visit her. I think she’s proud of having a robot and want other people to know it”. • (F4) “Mother is not so talkative when we go outside, not so much, kind of normal, but she really talks a lot at home. Today, while we were waiting for you, it was just me and her, she was always talking, not only to the robot but also with me.” “I think she’s showing more facial expressions these days, smiling more. When I leave her, she used to be looking sad, but now when I’m leaving I can see her talking to the robot she’s leaving, say goodbye, and that makes me feel relieved.” • (F5) “I do not think she’s now talking more than before, because when I visit her once a week, we usually keep speaking while I’m here. So the amount of speech has not changed but now she sometimes speaks about the robot - I feel what we speak about has changed.” “These days she does not go out so much because of the Coronavirus, so when I called her, sometimes she could not speak well, her voice was hoarse. But in these days, her voice on phone is much more lively. Even when we’re talking on the phone, when sometimes the robot responds to our speech she suddenly starts speaking to the robot, just like talking to a small child. She really looks like having a good time, and it is really nice.” “One thing that surprised me was about the room where the robot is placed. She never let me go into the room before. I’ve been visiting here for nearly 2 years, but after the robot arrived, for the first time she invited me to come into that room to show me the robot”. One participant (P4) declared adjusting their daily routines to loosely match the robot schedule, and started to wake up early in the morning. “I feel ashamed of myself still in bed when the robot is waiting for me to say good morning”. | [
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37230968 | intro | Introduction OSAS is a highly prevalent sleep-related breathing disorder characterized by hypopnea and apnea in ventilation. These breathing disturbances cause IH, which leads to blood hypoxemia, hypercapnia, fragmented sleep, recurrent nocturnal arousals, enhanced respiratory effort, and increased sympathetic nerve activity. Epidemiologic studies have documented the incidence of OSAS in the general population aged 30–60 years to be 24% in men and 9% in women, and a recent study reported almost 1 billion affected people globally, which has aroused extremely important concern (Table 1). Obesity, age, and sex have been identified as risk factors for OSAS, and other risk factors are related to ethnicity, family history, and poor lifestyle habits (alcoholism and smoking). The risk of OSAS correlates with body mass index (BMI), in which OSAS increases progressively with increases in BMI, most likely related to upper airway narrowing due to excess fat tissue. Obesity can induce a decrease in vital capacity, an imbalance in the ventilation-perfusion ratio, and limitations of lung and chest wall movement. As a result of this association, the countries with the highest incidence of OSAS are those with high rates of obesity, and thus, the incidence of OSAS increases with increasing levels of obesity. OSAS can occur at all ages, the incidence of OSAS has a tendency to increase with age, and the number of apnea events occurring during the night is usually higher in healthy older people than in middle-aged adults, reaching a plateau after approximately 65 years of age. Male sex is an independent risk factor for OSAS, with a male predominance and an estimated male-to-female prevalence of 1.5:1, and the reasons for this disparity are incompletely understood. The prevalence of OSAS increases in postmenopausal women, probably because body fat is redistributed to the upper body. In addition, the protective effects of female hormones, such as progesterone and estrogen, are decreased in the postmenopausal period. Symptoms of OSAS appear nonspecific and include snoring, apnea, arousal, and daytime sleepiness. Table 2 shows that day and night can be distinguished with respect to the major signs and symptoms of OSAS. According to current international recommendations, the diagnosis of OSAS is made after a sleep examination, and polysomnography (PSG) monitoring is applied as a method to diagnose OSAS, with the application of the 2017 scoring rules. These rules define apnea as a 90% reduction in airflow that lasts at least 10 s. Hypoventilation is defined as a decrease in flow of at least 50% and a decrease in oxygen saturation of 3% for at least 10 s. The severity of OSAS is distinguished clinically by the number of apnea–hypopneas per hour of sleep and the apnea-hypopnea index (AHI). AHI <5 is defined as no sleep apnea, AHI 5–15 as mild OSAS, AHI 15–30 as moderate OSAS, and AHI >30 as severe OSAS, and sleep apnea events identified in the sleep record of individuals without any symptoms are not considered OSAS unless AHI >15. Over the past decades, research progress on the pathophysiology of OSAS has been relatively slow due to the limitations of disease models. Reviewing previous studies, we showed that IH can induce alterations in multiple signal transduction pathways that could affect various systems and organs throughout the body. Epidemiological studies have reported a positive association between OSAS and increased risks of cardiovascular diseases, neurological disorders, and metabolic diseases. Additionally, a number of studies have shown that OSAS plays a crucial role in the development of nonalcoholic fatty liver disease. Recently, increasing evidence from our laboratories and others has shown that OSAS is also involved in a number of other diseases, including insulin resistance, glucose metabolism, kidney disease, hypertension, cancer, the immune system, and gastroesophageal reflux. However, the pathogenic mechanisms of OSAS in organs are complex and intertwined and not fully understood. In this review, the pathophysiological mechanism of OSAS and the relationship between the alterations in potential signaling pathways and multiple systemic diseases are described in detail and comprehensively, and the corresponding therapeutic strategies for different pathogeneses are discussed. Mechanisms/pathophysiology of OSAS The pathophysiological mechanisms underlying OSAS are complex and multifactorial, and furthermore, the underlying causes of OSAS vary substantially between afflicted individuals, with many unknown and poorly understood aspects. With the increase in OSAS-related research, it is gradually recognized that there are anatomical factors and functional factors involved in the mechanism of upper airway collapse. Based on the involvement of anatomical and nonanatomical factors in the pathogenesis of OSAS, a model of PALM pathogenesis was proposed, which can be summarized as pharyngeal critical closing pressure (Pcrit, P), decreased respiratory arousal threshold (arousal threshold, A), increased loop gain (loop gain, L), and upper airway dilator muscle activity (muscle responsiveness, M). (Fig. 1a). Various pathophysiological factors interact to contribute to the pathogenesis of OSAS (Fig. 1b). The following sections will focus on reviewing the key pathophysiological factors of OSAS and their interactions to highlight innovations in our understanding of OSAS pathogenesis. Upper airway collapse Upper airway anatomical abnormalities are a key factor in the pathogenesis of OSAS. Almost all patients have upper airway anatomical abnormalities to varying degrees, that is, upper airway stenosis and collapse caused by abnormal bone structure and soft-tissue hyperplasia. Upper airway anatomical abnormalities include relative stenosis due to fat deposition in the upper airway caused by obesity and absolute stenosis due to abnormalities in the maxillofacial structure, which are important causes of upper airway collapse. In addition, patients with leg edema due to cardiac and renal failure or venous insufficiency may experience a shift in leg fluid volume from the leg to the neck during the night, which may lead to upper airway collapse. Interestingly, the degree of collapse of a particular airway can be measured by calculating the Pcrit (see below for more details). Morphological abnormalities Morphological abnormalities are the most common contributing factor to the development of OSAS, and in adult patients with OSAS, a reduced mandibular body length, inferiorly positioned hyoid bone, posterior displacement of the maxilla, and narrowing of the pharyngeal space all result in oral cavity crowding. Abnormalities in anatomical features, conditioned by skeletal abnormalities as in Pfeiffer syndromes (craniofacial synostosis) or Pierre Robin syndrome (midface hypoplasia) and Crouzon syndromes and Apert syndromes are also implicated in OSAS. Enlargement of soft-tissue structures in and around the airways is an important cause of pharyngeal airway narrowing in most cases of OSAS. Examples include excessive or elongated tissues of the soft palate, retrognathia, macroglossia, enlarged tonsils, increased soft tissue in the neck, and a redundant pharyngeal mucosa. The enlarged soft palate and tongue invade the airway diameter in the anteroposterior plane, whereas the thickened pharyngeal wall invades the lateral plane, a major site of airway narrowing in most patients with OSAS. Obesity rates are high in patients with OSAS. Obesity is a major factor contributing to the compression of the respiratory tract through an increase in the area and volume of fat deposition in the pharynx, and fat deposition in the upper airways and around the thoracic cavity may promote the development of OSAS. In addition, tongue shape might play an important role in the development of OSAS, and studies have found that the tongue shape in patients with OSAS is different from that in normal subjects in the supine position. Nocturnal rostral fluid shift Fluid retention may contribute to the pathogenesis of OSAS, and nocturnal rostral fluid shift refers to the nighttime redistribution of fluid accumulated in the legs to the upper parts of the body while lying in bed. The passive movement of isotonic fluid between capillaries and the interstitial space is determined by capillary hydrostatic versus colloid osmotic pressure. When moving from the recumbent to the upright position, the hydrostatic pressure in the leg capillaries (90–120 cmH2O) exceeds the hydrostatic pressure in the interstitial space (15–20 cmH2O) due to gravity, thus causing fluid to seep from the capillaries into the interstitial space. Thus, while standing, the plasma volume is reduced by 300–400 ml due to venous pooling and fluid infiltration into the interstitial space, but the leg volume is increased by 100–300 ml. Fluid that accumulates in the interstitial space enters the circulation through the lymphatic system to maintain a stable interstitial volume. Once the lymphatic excreting capacity is saturated, the fluid accumulated in the interstitium is proportional to the standing time, and the gradient from the foot to the heart decreases. Upon lying down, the lower limb blood volume is rapidly reduced, and fluid is redistributed to the chest and neck. In addition, when lower body positive pressure was applied to the leg, the fluid was removed from the leg, and the neck circumference increased within 1 min, indicating that the fluid was able to move quickly to the neck. In summary, daytime postures, such as prolonged sitting or standing, causes fluid to accumulate in the intravascular and interstitial spaces distal to the lower extremities. During recumbency, patients may experience a shift in leg fluid capacity from the legs to the neck, increasing tissue pressure and resulting in narrowing of the upper airway, which increases its collapsibility and predisposes them to OSAS. It has recently been documented that the accumulation of even a relatively small amount (100–200 ml) of edema fluid expands the upper airway soft-tissue structures in patients with OSAS and snorers. Changes in leg circumference at night have been shown to correlate strongly with changes in neck circumference and AHI. Passive airway collapsibility Although upper airway obstruction may be due to a variety of factors, such as obesity, there is increasing evidence that individual collapsibility is also a key factor in upper airway obstruction. The importance of abnormal pharyngeal susceptibility to collapse in the pathogenesis of obstructive apnea was demonstrated by studying the Pcrit in patients with OSAS and in control subjects. A highly collapsed upper airway is the leading cause of OSAS pathogenesis, and the passive Pcrit technique is considered the gold standard for measuring the degree of pharyngeal airway collapse. The Pcrit is the pressure at which the airway fails to remain open and collapses, and previous investigators have demonstrated that in normal individuals, Pcrit is negative, implying that the upper respiratory airway tends to remain open. In patients with OSAS, the critical pressure is less negative, which means that the upper respiratory airway is more likely to collapse and become occluded during sleep. Applying a theoretical model of upper airway obstruction, researchers could represent the upper airway as a simple tube with collapsible parts. Any increase in pressure around the tube will exceed the internal pressure in the tube, causing pharyngeal collapse. When the pressure around the tube increases to the level of the pressure inside the tube, it is called the Pcrit of that segment. Therefore, the pharyngeal critical closing pressure refers to the pressure acting on the upper airway. In the absence of muscle activity, the pharynx will close, and it could reflect the mechanical properties or collapsibility of the pharynx. The more negative the tube pressure, the less effort is required to open the airway compared to atmospheric pressure. A growing body of literature has shown that Pcrit is higher in patients with greater upper airway collapsibility. The critical closing pressure of the airway was higher in patients with OSAS than in those without the disorder. Pcrit is a vital part of categorizing subjects with OSAS into various endotype groups, which could provide help for the treatment and response prediction of OSAS patients. Decreased respiratory arousal threshold In recent years, a number of studies have shown that a low respiratory arousal threshold may be an important endotype of OSAS. Each OSAS event terminates with brief brain activation in a process called arousal or microarousal. The tendency of OSAS patients to wake easily during sleep-disordered breathing is called the low arousal threshold. The arousal threshold varies between individuals, and studies have found that at least one-third of OSAS patients have a decreased respiratory arousal threshold. Arousal plays a dual role in the mechanism of OSAS. On the one hand, arousal from sleep at the end of a respiratory event is an important protective mechanism for restoring pharyngeal patency, and patients will resume normal breathing and relieve airway obstruction through neuromuscular and respiratory compensation mechanisms during arousal. Thus, respiratory arousal is considered a potentially lifesaving event that could avert asphyxia during sleep. On the other hand, a decreased respiratory arousal threshold is the cause of recurrent microarousal in OSAS patients. Recent studies also suggest that frequent arousals might lead to the interruption of sleep continuity, prevent deeper and more stable sleep, reduce the ability to recruit upper airway dilator muscles, and may contribute to further obstructive respiratory events. Arousal intensity is a unique pathophysiological phenotype, and individuals with a more intense arousal tendency to airway stenosis elicit a greater ventilatory response and are, therefore, more likely to experience instability in ventilatory control. Theoretically, hyperventilation during arousal would also reduce pharyngeal muscle activity, and in many cases, arousal might promote the cyclical breathing pattern of OSAS. Experimentally, the respiratory arousal threshold is measured by the lowest pressure in the esophagus produced during a respiratory event or perturbation of a breath taken before awakening. Evidence suggests that the magnitude of the intrapleural pressure generated by breathing is a major stimulus for the initiation of arousal from sleep. Although arousal thresholds vary widely between individuals, patients with OSAS tend to have diminished arousal responses to airway obstruction compared with controls, which may exacerbate upper airway dilator hypotonia, leading to an inability to recruit dilator muscles to open the airway before arousal occurs. Increased loop gain In ventilatory control, loop gain is a measure of respiratory instability, which refers to unstable ventilatory chemoreflex control and is recognized as a key pathophysiological feature that contributes to OSAS. Eckert’s study has shown that approximately 36% of OSAS patients have high loop gain. The loop gain consists of the control gain, plant gain, and cycle time. Control gain refers to the response degree of the respiratory system to the change in PaCO2, plant gain is characterized by the efficiency of the respiratory system in responding to the reduction in CO2 by ventilation, and cycle time refers to the feedback time from the change in PaCO2 and PaO2 in blood being received by the sensor to the ventilatory response of the body. High control gain represents a strong chemoreceptor response to a small change in PaCO2, and high plant gain indicates that a mild ventilatory response can cause a significant change in PaCO2. For example, upper airway muscles are innervated by neuronal fibers from the respiratory center, high ventilation caused by high loop gain can expel more CO2, and low serum CO2 levels reduce the central ventilatory drive in the dilator muscles of the upper airway, thereby reducing pharyngeal muscle activity. Thus, the higher the loop gain is, the less stable the ventilatory chemoreflex control. Unstable ventilatory chemoreflex control could promote airway collapse in OSAS due to hypocapnic (produced by hyperventilation after obstructive apnea) hypotonia of the upper airways. Obstructive apnea is followed by hyperventilation, producing hypocapnia and respiratory depression, which contribute to the instability of ventilatory chemoreflex control and high loop gain, and increased CO2 from hypoventilation leads to the development of rapid and large negative inspiratory pressure, also leading to a collapse of the upper airway. In addition, high loop gain could lead to a mismatch between the driving force of the respiratory center on the respiratory muscles and the driving force of the upper airway dilator muscles; that is, the activity of the upper airway dilator muscles is not sufficient to counter the negative suction generated by the respiratory muscles during inspiration, which leads to upper airway stenosis and collapse. Decreased upper airway dilator muscle activity during sleep and impaired sympathetic neural activity Increased pharyngeal dilator muscle activity in OSAS patients compared with matched controls has been interpreted as evidence of a neuromuscular protective compensatory reflex in response to anatomical compromise in OSAS. When awake, neuronal activation of the dilator muscles ensures that the pharyngeal dilator muscles are activated, thus preventing pharyngeal narrowing and collapse and protecting pharyngeal patency. When this upper airway dilator muscle activation is lost at the onset of sleep, its ability to maintain a patent airway decreases, and in turn, the airway could narrow and/or collapse. The genioglossus muscle is the most important pharyngeal dilator and has pharyngeal mechanoreceptors and chemoreceptors that deliver the relevant stimulus signals received (carbon dioxide in the blood) to the brainstem, tuning the upper airway dilator activity. Impairments in this process may lead to a reduction in the expansion forces of the pharyngeal dilator muscles, and the reduced pharyngeal caliber increases the likelihood of an obstructive event, in addition to the incoordination between the inspiratory activity of the muscles and the respiratory effort, increasing the resistance of the upper airway. Mechanisms of central sleep apnea Central sleep apnea (CSA) is a sleep-breathing disorder characterized by apnea and hypopnea caused by a lack of drive to breathe during sleep. The occurrence of respiratory events can be intermittent or periodic, and patients could also experience obstructive respiratory events. In contrast, OSAS is apnea or hypopnea due to repeated collapse or obstruction of the upper airway during sleep, which is characterized by the weakening or disappearance of oronasal airflow, while chest and abdominal motion or respiratory effort is still present. CSA is not as common as OSAS in clinical practice and accounts for less than 10% of all sleep-related breathing disorders, so it has received less attention. Similar to OSAS, CSA is associated with important complications, including frequent night awakenings, excessive daytime sleepiness, and an increased risk of adverse cardiovascular outcomes, and CSA has been divided into eight categories by the International Classification of Sleep Disorders, Third Edition (ICSD-3). Table 3 summarizes the differences between OSAS and CSA. Neurophysiologically, CSA is due to a temporary failure of the pontomedullary pacemaker to generate breathing rhythm. Thus, without brainstem inspiratory nerve output, the nerves innervating all inspiratory muscle groups are silent, which results in a loss of inspiratory ventilatory effort. Although the exact pathogenesis of different types of CSA might vary considerably, unstable ventilatory drive during sleep is the main characteristic. Sleep phases can be divided into nonrapid eye movement (NREM) sleep, rapid eye movement (REM) sleep, and wakefulness. CSA and instability in humans mainly occur in NREM sleep, and the mechanism is related to the high loop gain in NREM sleep. Under the joint action of high control gain and high plant gain, the sensitivity of the ventilation control system would be increased, but only two points cannot cause the occurrence of CSA. There must be a certain time interval between the effect produced by the effector (lung) (increase or decrease in ventilation) and the change in CO2 sensed by the receptor (peripheral or central chemoreceptors), which is the key to the eventual onset of apnea. Under the action of some factors, the increased PaCO2 will act on the peripheral chemoreceptors and cause a ventilatory response, which will lead to a decrease in PaCO2. Under normal circumstances, PaCO2 will finally reach the dynamic equilibrium state. Interestingly, elevated PaCO2 is rapidly corrected in patients with CSA, and the initiating factor driving the ventilatory response may have normalized, while due to delayed signal cycling caused by a prolonged cycle time, this signal is not promptly fed back by the receptor to the effector, at which point the effector is still performing ventilatory commands and finally results in hyperventilation. If PCO2 falls below the chemoreceptor detection threshold, the respiratory drive is eliminated, and CSA occurs. In the event of CSA, the oscillatory cycle that leads to the recurrence of CSA is perpetuated by the following factors: pharyngeal stenosis requiring sufficient expansion tension to overcome gravity and tissue adhesion and inconsistencies between normal and actual PCO2 levels at which respiratory rhythm resumes following CSA. Compared with OSAS, although a large number of studies have been conducted in the past 20 years, the etiology and pathophysiological mechanism of CSA are complex, so the understanding of CSA is still insufficient and needs to be further explored and improved. Intermittent hypoxic injury induced by OSAS: alterations in signaling pathways The role of HIF-1α under different oxygen conditions Due to the importance of oxygen for cell survival, metazoans have evolved mechanisms to sense changes in oxygen levels in the cellular microenvironment and trigger adaptive responses during evolution. It is increasingly recognized that the adaptation of organisms to hypoxia depends on the activation of specific oxygen-sensitive genes. A variety of redox-sensitive transcription factors have been identified, with the key factors being the HIF (hypoxia-inducible factor) family (including HIF-1, HIF-2, and HIF-3). HIF-1 is ubiquitously expressed in various tissues, whereas HIF-2 shows a tissue-specific expression pattern and is mainly expressed in a variety of immune cell subtypes, such as macrophages, neutrophils, and lymphocytes. The expression and role of HIF-3 in some immune cells remain unclear. These transcriptional regulators respond to fluctuations in oxygen levels and bind to specific DNA sequences to induce or repress genes, ultimately initiating adaptive transcriptional responses. Chief among these is HIF-1, which is a dimer consisting of the HIF-1α and HIF-1β subunits. The expression of HIF-1α is regulated at the level of transcription and translation, and multiple factors regulate the stability and activity of HIF-1α in oxygen-dependent or oxygen-independent ways at the posttranslational level. Under sufficient oxygen conditions, the oxygen sensitivity of the HIF-1α pathway is controlled by prolyl hydroxylase (PHD). The hydroxylase induces the hydroxylation of HIF-1α proline residues (Pro402 and Pro564) in the presence of oxygen, 2-oxoglutarate, and iron. Moreover, acetylation of HIF-1α at Lys532 by arrest-defective-1 (ARD-1) contributes to the reaction of HIF-1α with the von Hippel-Lindau (VHL) protein, followed by ubiquitylation of the alpha subunit of HIF-1 and finally ubiquitin-tagged HIF-1α protein degradation by the 26S proteasome (Fig. 2). During hypoxia, the oxygen required for HIF-1α ubiquitination is lost, and the enzyme activity associated with hydroxylation is weakened. Thus, HIF-1α escapes degradation, moves to the nucleus to bind to HIF-1β, and recruits the transcriptional coactivator (CREB)-binding protein (CBP) and p300 to the HIF-1α binding site with hypoxia response elements (HREs) (Fig. 2). The result is the upregulation of a large number of target genes that promote hypoxia adaptation, and over 100 HIF-1α target genes have been identified thus far. These genes are involved in various biological processes, including anaerobic glycolysis metabolism, inflammation and immunity, erythropoiesis, metabolism, angiogenesis, cell survival and apoptosis, and cancer metastasis. In addition, the downregulation of some genes, such as PDK1, resulted in decreased mitochondrial oxygen consumption. Similar to chronic hypoxia (Fig. 2), the essence of intermittent hypoxia is the switching between normoxic and hypoxic states [intermittent hypoxia switching (IHS)], which leads to changes in cellular and molecular functions that are different from chronic hypoxia. Studies have found that prolonged IH (hours to days) increases HIF‐1α activity. However, the molecular mechanisms driving cell behavior in IH compared to chronic hypoxia are less well understood. For example, proline hydroxylation and subsequent ubiquitination pathways are critical for HIF-1α stabilization in continuous hypoxia, and whether they also play a role in IH requires further study. Furthermore, in IH mode, we speculate that the free oxygen deficit is not sufficient to maintain HIF-1α stabilization, but studies on cell culture models of IH have shown that IH can evoke transcriptional activation more than continuous hypoxia for a given duration and intensity. Interestingly, HIF-1α protein levels were found to be lower in HCT116 cells treated with IH than in those treated with chronic hypoxia but were still higher than in normoxia. When the proteasome inhibitor MG262 was added, the accumulation of HIF-1α was much higher than that observed under chronic hypoxia, indicating that proteasomal degradation occurs at a higher level under IH than under chronic hypoxia, suggesting that there is another mechanism for HIF-1α degradation under IH conditions. In an experiment with cells cultured in IH, PC12 (pheochromocytoma-12) cells were exposed to alternating cycles of hypoxia and reoxygenation, with one cycle of 1.5% oxygen for 30 s and 20% oxygen for 4 min, to investigate the activation of HIF-1α by IH. HIF-1α protein and transcriptional activity increased in a stimulation-dependent manner as IH increased from 10 to 30 to 60 cycles. Interestingly, when cells were subjected to continuous hypoxia for 60 min, equivalent to 120 episodes of IH (30 s each episode), continuous hypoxia for 60 min did not increase HIF-1α protein expression or transcriptional activity. However, prolonged hypoxia in experiments increased HIF-1α protein expression and transcriptional activity. These observations suggest that IH activates HIF-1α more rapidly than continuous hypoxia. Based on current studies, it has been found that there are differences between continuous hypoxia and IH in the kinetics of protein kinase activation, the downstream targets of protein kinases, and the types of activated protein kinases. In addition, molecular responses activated by IH and continuous hypoxia are also different in many pathological conditions. We propose that novel oxygen-sensing mechanisms may exist in organisms that regulate and fine-tune the cellular hypoxic response depending on the duration of hypoxia (Fig. 2) (see below). Histones regulate the expression of HIF-1α induced by IH Multiple studies have shown that exposure to hypoxia could alter the epigenetic landscape at the cellular chromatin level. Similar changes in epigenetic marks (histone modifications, noncoding RNAs, and DNA methylation) have been found in developmental and disease states. The number of studies have found increased histone methylation marks in different mammalian cells exposed to severe and continuous hypoxia. Histone methylation affects gene expression by affecting chromatin structure and altering the accessibility of chromatin to transcription factors. The nucleosome core consists of two H2A/H2B dimers and an H3/H4 tetramer whose protruding long tails can be covalently modified by methylation (me). Generally, histones are methylated only at lysine (K) or arginine residues, but methylation most often occurs at the K residues of H3 and H4 in the histone tails. The state of histone methylation is strongly associated with transcriptional repression or activation, depending on the position of the modified residues and the number of methyl groups. For example, lysine 4 methylation of H3 (H3K4me2/3), H3K79me2/3 and H3K36me2/3 is associated with active genes, whereas methylation at H3K9 and H3K27 (H3K9me2/3 and H3K27me2/3) correlates with gene repression. Histone methylation involves many chromatin remodeling proteins, including histone lysine demethylases (KDMs), histone methyltransferases, and other histone-modifying enzymes, and KDMs play an important role in the methylation process. Similar to PHD, which regulates HIF-1α degradation, KDMs require 2‐oxoglutarate, Fe, and oxygen as important cofactors for their activity, and another important feature of KDMs is the presence of a Jumanji-C (JmjC) domain. Given the dependence of this enzyme on oxygen for its activities, KDMs can act as molecular oxygen sensors in cells. Interestingly, Batie et al. found that hypoxia can alter chromatin in a range of human cultured cells by directly affecting JmjC-histone demethylase. The genomic locations of H3K4me3 and H3K36me3 after brief exposure of cells in culture to hypoxia allow assessment of the transcriptional response of cells several hours later. In addition, KDM5A inactivation was also found to mimic hypoxia-induced cellular responses. The above findings suggest that chromatin responds to oxygen fluctuations through the repression of JmjC-histone demethylase. Another study found that the H3K27 histone demethylase KDM6A is oxygen sensitive, and its deletion results in the same effect as hypoxia, preventing H3K27 demethylation, disrupting cellular differentiation, and reestablishing H3K27 methylation homeostasis in hypoxic cells, which could ameliorate these impairments. Upregulation of oxygen-dependent KDMs under persistent hypoxia is thought to increase the demethylation of methylated lysine residues. It has been suggested that the upregulation of KDMs is a compensatory mechanism by increasing the levels of these enzymes to compensate for their reduced activity under oxygen-depleted conditions, but oxygen-dependent KDM activity may not be elevated due to the scarcity of oxygen content. In addition, the effect of IH on histone methylation has been less studied than that of continuous hypoxia, and the specific regulatory mechanism of histone methylation and the changes in downstream molecules under different oxygen concentrations are also unclear. Beyer et al. found that when KDM3A and KDM4B were overexpressed in HeLa cells cultured in 0.2% oxygen, the cells were differentially sensitive to hypoxia. Demethylation of H3K9me3 by KDM4B was decreased, whereas KDM3A activity remained unchanged under the same conditions. This finding implies that the physiological change from normoxia to hypoxia weakens the enzyme activity and additionally reveals a difference in the apparent oxygen sensitivity of the two JmjC-KDMs. Continuous hypoxia induces a decrease in KDM activity, resulting in global hypermethylation of lysine residues in histones, altering the expression of several genes. KDMs have been observed to be upregulated (at the mRNA level) in response to continuous hypoxia, but thus far, KDMs have not been identified as HIF-1α target genes. Recent studies have found that IH increases HIF-1α activity through pathways that are distinct from chronic hypoxia. Martinez et al. exposed different cell types to IH. HIF-1α protein and HIF-1α target gene (KDM4B and KDM4C) expression were increased under both chronic hypoxia and IH relative to normoxia, and the degree of gene expression was related to the dose-dependent effect of hypoxia. The increased expression of HIF-1α protein and known HIF-1α target genes under intermittent hypoxia is a generalized cellular response. Multiple experiments have compared HIF-1α mRNA levels in HCT116 cells, MCF7 cells, and brain (U251), prostate (PC3), and breast (MDA-MB-231) cancer cell lines after normoxic, chronic hypoxia, and IH exposure. Surprisingly, HIF-1α mRNA expression levels were decreased in chronic hypoxia and increased in IH in all cell lines compared to normoxia. The data suggest that HIF-1α expression is controlled differently in IH and chronic hypoxia. Further studies found that H3K9me3 increases in different cell types exposed to chronic hypoxia relative to normoxia; however, unlike chronic hypoxia, IH reduced H3K9me3 levels below those observed with normoxia. Interestingly, H3K9me3 is associated with heterochromatin and gene silencing, so the global reduction in H3K9me3 induced by IH may lead to increased expression of associated genes. This finding supports the hypothesis that H3K9me3 reduction mediates the IH-induced increase in HIF-1α gene expression (Fig. 2). In parallel, the protein and mRNA expression of KDM4A, KDM4B, and KDM4C was further assessed. The protein levels of KDM4A were found to be unchanged in cells exposed to normoxia, chronic hypoxia or intermittent hypoxia, and the protein levels of KDM4B and KDM4C were significantly increased in chronic hypoxia compared with IH. Given that KDM4A mRNA levels are reduced in chronic hypoxia and do not change in IH compared to normoxia, it is suggested that KDM4A is not an HIF-1α target gene. Interestingly, several studies have found that the degradation of KDM4A in hypoxia is prolonged via an unknown mechanism, resulting in higher levels of KDM4A under hypoxic conditions, although KDM4A may be inactive. Although the enzyme levels of KDM4A, KDM4B, and KDM4C are increased under conditions of constant hypoxia, they may lose their activity due to hypoxia. Compared with continuous hypoxia, there is sufficient oxygenation between hypoxia fluctuations to remain active in IH, resulting in higher H3K9 demethylation levels of the HIF-1α gene than those in normoxia or chronic hypoxia, resulting in increased HIF-1α mRNA production (Fig. 2). Overall, studying the biological response to OSAS-induced IH is difficult because the patterns and types of IH vary widely in vivo, and it remains to be tested whether this response occurs in all forms of IH. Future studies will contribute to further understanding of how novel cellular oxygen sensors react and interact to generate hypoxic responses in IH. ROS-dependent Ca2+ signaling pathways and IH-induced HIF-1α activation A number of studies have found that the synthesis and stability of HIF-1α evoked by both IH and continuous hypoxia are closely related to the increase in ROS (reactive oxygen species) produced by NOX activation. Interestingly, increased levels of ROS can activate PLC-γ (phospholipase C γ) to produce IP3 (inositol-3-phosphate) and diacylglycerol (DAG). Hong et al. found that hydrogen peroxide-induced PLC-γ activation and an IP3 receptor-dependent increase in Ca2+ in rat astrocytes. In addition, Yuan et al. demonstrated that HIF-1α accumulation involved PLC-γ and protein kinase C (PKC) activation in PC12 cells treated with IH. IH-induced transcriptional activation of HIF-1α was blocked by the Ca2+ chelator BAPTA-AM or a Ca2+/CaMK (calmodulin-dependent kinase) inhibitor, which confirmed the crucial role of the ROS-dependent Ca2+ signaling pathway. A previous study reported that continuous hypoxia resulted in transient (15 min) and moderate (1.5-fold) increases in CaMKII activity, which is an important downstream signaling molecule involved in Ca2+-mediated gene regulation, in PC12 cells. These observations are in sharp contrast to IH, where IH induced an exponential and nearly sixfold increase in CaMKII activity with increasing IH cycles and correlated with increased phosphorylation of the CAMKII protein. Interestingly, both calmodulin and CaMKII inhibitors prevented IH-induced HIF-1α transcriptional activity but not continuous hypoxia-induced HIF-1α transcriptional activity. Moreover, CaMKII inhibitors did not effectively inhibit IH-induced HIF-1α protein expression, suggesting that CaMKII-dependent signaling is essential for IH-induced HIF-1α transcriptional activation, while HIF-1α protein expression may be independent of the CaMKII pathway. On the other hand, it was also shown that the signaling pathways associated with HIF-1α activation in response to continuous hypoxia differ significantly from HIF-1α activation in response to IH. Multiple lines of evidence show that p300/CBP proteins are major coactivators of IH-induced HIF-1α transcriptional activation. In a hypoxic PC12 cell experiment, it was found that the IP3 receptor-mediated Ca2+ signaling pathway leads to the hyperphosphorylation of p300. IH increases the transcriptional activity of p300, confirming that CaMKII specifically phosphorylates p300 in vitro, which was blocked by CaMKII inhibitors. These observations indicate that IH-induced HIF-1α transcriptional activation requires a novel signaling pathway involving CaMKII-dependent activation of p300/CBP coactivators (Fig. 3 ①). Increased Ca2+ has been reported to activate classical PKC, which in turn activates mTOR (mammalian target of rapamycin) signaling, a kinase that promotes HIF-1α expression. Ca2+-dependent activation of PKC and mTOR could increase HIF-1α protein expression in PC12 cells. Interestingly, IH resulted in PKC-dependent mTOR activation compared to continuous hypoxia, and mTOR-dependent increased HIF-1α expression contributed to IH-induced HIF-1α accumulation. At the same time, rapamycin reduced IH-induced HIF-1α stabilization, and IH increased phosphorylated mTOR levels and downstream S6 kinase activation. In addition, the effects of IH on mTOR activation and HIF-1α protein activity were inhibited by inhibitors of IP3 receptors and PLC-γ as well as the Ca2+ chelator BAPTA-AM. The results further confirmed that IH-induced HIF-1α stabilization was associated with increased protein synthesis and activation of rapamycin-sensitive mTOR signaling (Fig. 3 ②). Similar to the continuous hypoxia report, decreased PHD activity was also found to lead to stable enhancement of HIF-1α after IH, and the negative regulation of PHD activity by PLC-γ/Ca2+/PKC/PHD signaling requires further investigation to elucidate the underlying molecular mechanisms (Fig. 3 ③). Based on the present evidence, the Ca2+ signaling pathway is involved in IH-induced mTOR activation and subsequent HIF-1α protein accumulation, as well as HIF-1α transcriptional activity. Recent studies have found that hypoxia can activate the PI3K (phosphoinositide 3-kinase)/Akt (protein kinase B) signaling pathway in cells. In addition, the stability of HIF-1α is related to the PI3K/Akt signaling pathway, and activation of PI3K is required for continuous hypoxia to activate HIF-1α. Several studies have also found that PI3K inhibitors reduce HIF-1α expression. However, neither LY294002 nor wortmannin (two PI3K inhibitors) blocked IH-induced HIF-1α transcriptional activity. The correlation between the PI3K/Akt signaling pathway and IH is controversial and may be related to the disease and cell type under hypoxic conditions. There are relatively few related studies, and more studies are needed to clarify the relationship between IH and the PI3K/Akt signaling pathway (Fig. 3 ④). Previous studies have shown that PI3K and mitogen-activated protein kinases (MAPKs) are essential for continuous hypoxia-induced activation of HIF-1α-mediated transcription. In addition, other studies have shown that MAPK inhibitors attenuate hypoxia-induced transcriptional activation of HIF-1α in PC12 cells. Inhibitors of PI3K have also been shown to inhibit HIF-1α protein accumulation and attenuate hypoxia-induced transcriptional activation of HIF-1α. Although MAPKs (ERK 1/2 kinases; Jun Kinase) could be activated by IH, Yuan et al. examined the effects of MAPKs and PI3K inhibitors on HIF-1α transcriptional activation induced by IH. It was found that neither MAPKs nor PI3K inhibitors prevented HIF-1α transcriptional gene activation induced by IH. These studies, although preliminary, suggest that IH is associated with transcription factor activation in signaling pathways that are distinct from those used by continuous hypoxia. Another closely related protein, HIF-2α, is processed similarly to HIF-1α and has been reported to be a potent activator of genes encoding antioxidant enzymes. Several studies have shown that antioxidants such as superoxide dismutase 2 (SOD2) are also downregulated in IH-exposed cells. It has been hypothesized that the downregulation of antioxidants is closely related to HIF-2α downregulation. Interestingly, research has confirmed that IH-induced HIF-2α degradation leads to a significant downregulation of SOD2 transcription, which prevents IH-induced oxidative stress and restores SOD2 activity by ectopic overexpression of transcriptionally active HIF-2α. Systemic treatment of IH-exposed rats with ALLM (a potent inhibitor of calpains) not only restored HIF-2α in carotid bodies (CBs) and adrenal medulla but, more importantly, restored SOD2 activity and protected against oxidative stress. The reduction in HIF-2α expression by IH is due to increased degradation of the protein by Ca2+-dependent calpain. The degradation of HIF-2α by calpains involves the C-terminus portion of the HIF-2α protein. In addition, inhibitors of ALLM prevented IH-induced HIF-2α degradation, whereas PHD inhibitors or proteasome inhibitors were ineffective. These observations demonstrate that IH leads to HIF-2α downregulation via Ca2+-dependent signaling (Fig. 3 ⑤). ROS-dependent Ca2+ signaling pathways and IH-induced IEG activation In the family of proto-oncogenes, there is a class that can be induced by second messengers. These genes are called immediate early genes (IEGs), also known as rapid response genes. The IEG family mainly includes the fos, jun, and myc families. At present, the c-fos and c-jun families are the most deeply studied. The c-fos gene is one of the most important members of the IEG family and can be activated by hypoxia. The AP-1 (activator protein-1) complex is formed from heterodimers of either the Jun or Fos proteins or homodimers of Jun proteins. The AP-1 binding sequence is a common component of transcriptional regulatory elements that can drive the activation of multiple target genes during hypoxia, including tyrosine hydroxylase (TH), which encodes an important enzyme in catecholamine synthesis. Because TH is the rate-limiting enzyme for catecholamine synthesis, it is possible that IH-induced TH activation partially induces an increase in catecholamine levels in the body, leading to a chronic increase in sympathetic activity. In addition, the upregulation of AP-1 is involved in the expression of adhesion molecules and inflammatory cytokines, suggesting that AP-1 is also involved in OSAS-induced systemic chronic inflammation. Yuan et al. reported that IH increased c-fos mRNA expression in PC12 cells in a stimulation-dependent manner, and the IH-induced increase in c-fos mRNA was due in part to an increase in c-fos transcriptional activation. Further experiments showed that point mutations in the c-fos promoter indicated that the serum-responsive element and Ca2+ response element are vital for IH-induced c-fos promoter activation. Interestingly, several studies have found that IH increases the expression of c-fos mRNA in PC12 cells. However, continuous hypoxia exposure (equal to the accumulated time of IH) had no effect. In addition, prolonged continuous hypoxia was able to activate c-fos mRNA, and when the c-fos gene was activated by continuous hypoxia, the expression level of c-fos mRNA returned to the control level within 30 min after termination of hypoxic stimulation. Interestingly, c-fos mRNA levels remained high 5 h after the end of IH. Another study found that c-fos mRNA continued to increase for at least 3 h after IH intervention but returned to normal levels within 1 h after continuous hypoxia cessation, suggesting that different hypoxia modes have significant differences in the regulation of c-fos mRNA. Long-lasting activation of c-fos mRNA by IH is closely related to IH-induced carotid body sensory activity and respiration. A major difference between IH and continuous hypoxia is that IH has a reoxygenation phase, which is absent during continuous hypoxia. Therefore, it has been proposed that the generation of ROS by IH during the reoxygenation phase may mediate the regulation of c-fos mRNA. The amount of c-fos mRNA expression activated by IH was reported to be dependent on the duration of reoxygenation after hypoxia but not on the duration of hypoxia. Superoxide ion scavengers [manganese tetrakis methyl porphyrin pentachloride (MnTMPyP)] could inhibit the upregulation of c-fos mRNA and attenuate the transcriptional activation of AP-1 induced by IH. Studies have shown that the Ca2+ signaling pathway is involved in the hypoxic activation of the c-fos gene and AP-1 in PC12 cells. RT‒PCR and reporter gene assays showed that hypoxia enhanced c-fos mRNA and promoter activity, which were inhibited by the Ca2+ chelator BAPTA-AM or L-type Ca2+-channel blocker, while the L-type Ca2+-channel agonist BAYK8644 enhanced c-fos gene activation by hypoxia. Further immunoblot analysis showed that hypoxia increased the expression of CaMKII protein in PC12 cells, whereas the CaMKII inhibitor inhibited hypoxia-induced stimulation of the c-fos promoter. Ectopic expression of CaMKII mutants was also able to stimulate c-fos promoter activity under normoxic conditions. In addition, hypoxia-induced phosphorylation of CREB at the serine residue, and CaMKII inhibitors inhibited this effect. In summary, Ca2+-dependent signaling pathways play a vital role in hypoxia-regulated c-fos gene expression (Fig. 3 ⑥). Mechanisms associated with altered carotid body function in response to IH Patients with IH due to recurrent apnea, as well as IH-exposed rodents, develop autonomic abnormalities, including enhanced hypoxic ventilatory responses, elevated plasma catecholamines, persistent activation of the sympathetic nervous system, and systemic hypertension. The acute response to hypoxia, which occurs within seconds to minutes, is entirely dependent on the oxygen-sensitive capacity of peripheral arterial chemoreceptors, particularly the carotid bodies. Studies have shown that carotid body chemoreceptor are the “front line” defense system to detect alterations in arterial blood oxygen during apnea, which is more sensitive and rapid than other respiratory chemoreceptors, such as central chemoreceptors. This is because the time for oxygen to diffuse from the lung to the carotid body (6 s) is shorter than the time to reach the central region, and thus, the carotid body has already responded to hypoxia before the hypoxic stimulus is felt in the central region. Given its location and functional properties, IH-induced carotid body activation is closely related to autonomic dysfunction. When it is starved of oxygen, the body actively begins to increase ventilation within a few minutes. This physiological response to increase ventilation due to oxygen deficiency is called the hypoxic ventilatory response (HVR). OSAS patients and IH-exposed rodents exhibit enhanced HVR, a hallmark of the carotid body chemoreflex. In a rodent model, awake rats were exposed to IH (5% O2 for 15 s, 21% O2 for 5 min; 9 sessions per hour, 8 h per day for 10 days). Efferent phrenic nerve activity was used as an indicator of neural respiration to assess HVR. The results showed a 38% increase in baseline minute neural respiration and a 56% increase in ventilatory stimulation induced by acute hypoxia (12% inspired O2 fraction). As reported in another experiment, there was no significant increase in HVR in rats exposed to 30 days of IH. It is possible that HVR becomes adaptive after 30 days compared to 2 weeks of IH. Exposure of experimental animals (cats, dogs, rats, and goats) and humans to repeated hypoxia promotes a compensatory and sustained (>1 h) increase in respiratory motor activity. This prolonged respiratory activation in response to IH is often referred to as respiratory long-term facilitation (LTF), which is considered to be a marker of IH because a similar duration of continuous hypoxia does not result in prolonged respiratory activation. It was found that rats exposed to IH for 10 days showed a significant enhancement in LTF of respiratory motor output. It has been hypothesized that LTF prevents collapse by increasing the tone of the upper airway and that enhanced LTF may contribute to increased basal ventilation in patients with OSAS as well as in animals exposed to IH. Afferent input to the carotid body may be critical for LTF in respiratory motor output resulting from IH. Therefore, a group of researchers further investigated the effect of IH on chemoreceptor sensory discharge in the carotid body of rats, and anesthetized rats were subjected to 10 sessions of hypoxia (12% O2 for 15 s) followed by 5 min of reoxygenation. Interestingly, when this hypoxic pattern was repeated in animals subjected to IH for 10 days, it resulted in a prolonged elevation of baseline carotid somatosensory activity for nearly 1 h. These observations suggest that IH induces novel functional plasticity of the carotid body, leading to LTF in sensory discharge. However, sensory LTF plays an important role in reflex activation of the sympathetic nervous system and sustained daytime hypertension, and ablation of the carotid body reduces sympathetic activation and hypertension in intermittently hypoxic rats. ROS, which are produced during the reoxygenation phase of IH, may play a vital role in eliciting changes in carotid body activity induced by IH. In contrast to rats exposed to IH, the response of the carotid body was found to be blunted under continuous hypoxia; additionally, there was no induction of LTF in the sensory discharge of the carotid body under continuous hypoxia. Physiological studies showed that antioxidants (MnTMPyP and N-acetylcysteine) could ameliorate IH-induced plasma catecholamine elevation and decrease hypoxia sensitivity in the carotid body, and the magnitude of the LTF during sensory discharge was also significantly attenuated. Several studies have also confirmed that intervention with ROS scavengers during exposure of rats to IH could normalize carotid body activity and improve IH-induced hypertension. Increased sensitivity of carotid body chemoreceptors to hypoxic chemotherapy may involve endothelin (ET) and ET receptors, which are expressed in glomus cells (oxygen-sensitive type I cells) and blood vessels in the carotid body. ET acts on two receptors, the ETA receptor and the ETB receptor. In rodents exposed to IH, quantitative RT‒PCR confirmed a gradual increase in ET and ETA expression in type I cells and a time-dependent increase in hypoxia-induced carotid receptor activity. The application of a specific ETA antagonist could inhibit or attenuate hypoxia-induced carotid sensory discharge. In cats exposed to chronic IH for 4 days, ET-1 expression increased approximately 10-fold in the carotid body, while plasma ET-1 levels were unchanged, and the ETA/ETB receptor antagonist inhibited the chronic IH-induced increase in the carotid body hypoxic chemosensory responses. Another study found that the administration of MnTMPyP prevented the IH-induced elevation of ROS, basal release of ET-1 levels, and ETA receptor mRNA and augmented sensory responses. These observations suggest that the IH-induced increase in sensory responses involves a ROS-mediated increase in ET-1 release and upregulation of ETA receptor mRNA. A recent study explored chronic IH to increase carotid body chemosensory sensitivity via the ET-1 receptor signaling pathway. PKC, PLC, or p38 MAPK antagonists were used to elucidate the signaling pathways involved. The results showed that after chronic IH exposure, the protein levels of p38 MAPK and PKC were increased, and the expression of ETA and ETB receptors was upregulated in the carotid body, but only ETA was involved in ET-1-induced carotid body chemosensory sensitivity. It was confirmed that ETA receptor-mediated PLC, PKC and p38 MAPK signaling pathways were responsible for chronic IH-induced carotid body chemosensory sensitivity, and Ca2+ influx was also involved in the increase in carotid sinus nerve activity. In addition to ET-1, the renin-angiotensin system is also strongly associated with enhanced carotid body chemosensory sensitivity. Angiotensinogen mRNA and protein have been found to be present in type I cells. Similar to ET-1, IH increased the transcriptional and posttranscriptional expression of angiotensin II type 1 receptor (AT1) in the carotid body. Interestingly, the study by Lam and Leung et al. found that angiotensin II was able to act directly and enhance carotid body chemosensory sensitivity, rather than being mediated by altered arterial pressure or blood flow, and angiotensin II enhances carotid sinus nerve activity in the carotid artery in vitro. Based on the current study, we hypothesize that IH induces the production of sensory LTF in the carotid body through ROS/Ca2+/AT signaling to increase the sensitivity of the carotid body to hypoxic chemotherapy, which may be an important molecular mechanism of sympathetic activation after IH (Fig. 3 ⑦). Type I cells in carotid bodies are derived from neurons and are the primary oxygen-sensing cells. Available evidence indicates that type I cells are the initial site of sensory transduction and that they release an excitatory neurotransmitter in response to hypoxia, acting on nearby afferent nerve endings and thus resulting in increased sensory discharge. One hypothesis suggests that heme and/or redox-sensitive enzymes are oxygen sensors and that biochemical events associated with heme proteins trigger transduction cascades, which leads to increased cytosolic Ca2+ concentrations and evokes neurotransmitter release in type I cells. An alternative hypothesis suggests that K+ channel proteins are oxygen sensors and that inhibition and subsequent depolarization of this channel is the initiating event in transduction. ROS may enhance the hypoxia-induced increase in intracellular Ca2+ concentration in type I cells by affecting voltage-gated Ca2+ channels, thereby enhancing sensitivity to hypoxia. One study showed that ROS enhanced the increase in intracellular Ca2+ concentration in PC12 cells in response to depolarizing stimulation, but the specific triggering mechanism is unclear. Recent studies have shown that the sensing of hypoxia in the carotid body requires an O2-dependent interaction between hydrogen sulfide (H2S) and carbon monoxide (CO). CO produced by heme oxygenase-2 (HO-2) in the carotid body induces a signaling pathway. CO inhibits the CSE (cystathionine γ-lyase) activity of the carotid body through protein kinase G (PKG)-dependent phosphorylation of serine residue 377, thereby inhibiting hydrogen sulfide (H2S) synthesis and leading to the inhibition of carotid body activity. Interestingly, the IH-increased H2S production was due to ROS-dependent inactivation of HO-2 that reduced CO production in the carotid artery, which in turn reduced the inhibitory effect of PKG on CSE phosphorylation, thereby increasing the H2S concentration and stimulating its neural activity. Rodents exposed to IH showed a significant increase in the H2S concentration in the carotid body, and this effect was abolished in rats treated with the CSE inhibitor L-propargylglycine (L-PAG). Furthermore, CSE-deficient mice showed a significant reduction in basal H2S levels in the carotid body, suggesting that IH increased CSE-dependent H2S production. HO-2 knockout mice exhibit more abundant CSE-derived H2S in carotid bodies and enhanced carotid body chemosensitivity, and CSE inhibitors prevent OSAS in HO-2 knockout mice. The carotid body of IH-exposed rats showed reduced CO levels, PKG activity, and CSE phosphorylation, whereas all of these effects were abolished after administration of the membrane-permeable ROS scavenger MnTMPyP. Therefore, we hypothesized that the activation of H2S signaling in the carotid body under IH is also a key trigger of sympathetic activation and hypertension (Fig. 3 ⑧). In addition, increased H2S may mediate ROS-induced intracellular Ca2+ elevation (Fig. 3 ⑨). Previous studies have shown that voltage-gated Ca2+ channels (VGCCs) are essential for hypoxia-induced Ca2+ elevation in type I cells, with L-type (high-voltage-activated channel) VGCCs mediating the majority of the hypoxia-induced Ca2+ influx. A recent study detailed the role of T-type (low-voltage-activated channel) VGCCs in the carotid body and found that the mRNA encoding the α1H subunit and α1H-protein is highly expressed in rat carotid body type I cells, implying that CAV3.2 is the major T-type VGCC isoform in the carotid body. Mibefradil and TTA-A2, as selective blockers of T-type VGCCs, significantly reduced the hypoxia-induced increases in intracellular Ca2+ concentration, catecholamine secretion from type I cells, and sensory excitation of the carotid body. Studies have also confirmed that H2S, dependent on CSE production, is required for VGCC-mediated Ca2+ influx in type I cells and carotid body sensory nerve excitation. Interestingly, similar to hypoxia, the H2S donor NaHS increased the intracellular Ca2+ concentration and carotid body nerve activity, while these effects were significantly attenuated in CAV3.2 knockout mice. In wild-type mice, TTA-A2 significantly reduced the response of type I cells and carotid body sensory nerves to hypoxia, and these effects were abolished in CSE knockout mice. Based on the present findings, we hypothesized that the highly expressed CAV3.2 T-type VGCCs in type I cells are involved in H2S-mediated Ca2+ influx and Ca2+ secretion, as well as the response of the carotid body to hypoxia. However, whether other types of calcium channels also play these roles in IH and hypoxia is unknown, and the types of oxygen-sensitive channels need to be further explored in the future. Mechanisms of OSAS-induced gut dysbiosis In normal physiological states, there is a mutually beneficial relationship between the host and the gut microbiota. The host provides nutrients and a living environment for the microbiota, while bacteria help maintain the host immune response, act as a barrier against invading pathogens, and provide nutrients to the host. This balanced relationship may be disrupted by changes in the composition of the microbiota, known as dysbiosis. Current studies have found that gut dysbiosis might play a role in OSAS-associated morbidities, such as systemic hypertension, metabolic disorders, neurological diseases, COVID-19, and atherosclerotic heart disease. The gut is the largest immune organ and the largest microecosystem in the human body. The gut microbiota contains at least 1500 species of microorganisms with more than 100 trillion bacteria, and 70% of lymphoid tissue is present in the gut and forms gut-associated lymphoid tissue. The five most common bacterial phyla inhabiting the colon are Actinomycetes, Bacteroides, Proteus, Firmicutes, and Cerrucomicrobia. Bacteroides and Firmicutes account for 90% of the bacteria in the colon. The beneficial and healthy Bacteroidetes (gram-negative) include Lactobacillaceae, Ruminococcaceae, Erysipelotrichaceae, Bifidobacteriaceae, and Clostridium, which play key roles in carbohydrate and fiber fermentation. This process produces short-chain fatty acids [SCFAs (butyrate, acetate, and propionate)], which provide the main source of nutrition and energy for colonic cells and regulate the immune system. On the other hand, Desulfovibrio, Prevotella, Lachnospiraceae, and Paraprevotella species, which belong to Firmicutes, have local (gut) and systemic harmful characteristics and are capable of disrupting the structural integrity of the gut barrier. Interestingly, an increased Firmicutes/Bacteroidetes (F/B) ratio has been shown to be a hallmark of gut dysbiosis in almost all animal studies using similar IH exposure models. It is well known that the core of the gut contents is hypoxic, but studies have shown that there is a gradient in the oxygen concentration of the microbiota in the range of ≈150–200 μm near the gut epithelium and that the oxygen concentration has an effect on the microbiota. In a mouse model of IH intervention, it was found that IH induced a periodic hypoxia/reoxygenation pattern in arterial blood and the lumen of the small intestine. It is possible that there is a physiological process involving oxygen diffusion from the epithelial capillaries into the gut lumen, and a periodic pattern of hypoxia/reoxygenation could be observed within 200 μm of the intestinal epithelial barrier; that is, IH translates into a hypoxia/reoxygenation pattern in the proximal intestinal epithelial feces (<200 μm). Under these conditions, we hypothesized that an increased duration of hypoxia would favor the survival of obligate anaerobes and that the biological diversity of the gut microorganisms might be altered. In fact, some studies have also confirmed that IH exposure causes changes in the relative abundance of aerobic bacteria in mice that mimic moderate OSAS and causes an increase in the abundance of obligate and facultative anaerobes. In addition, dysbiosis was characterized by a changed F/B ratio in many experiments. Given that arousal is an important component in the pathogenesis of OSAS, a recent study showed that when mice were exposed to sleep fragmentation, it resulted in significant changes in the microbiota, including an increase in Firmicutes and a decrease in Bacteroidetes compared with those of control mice. Another consequence of arousal is increased sympathetic activity and catecholamine release, and catecholamines could significantly increase the growth of certain bacterial species. Adrenergic stimulation of enteric neurons regulates intestinal motility and ion transport, thereby altering the microbiota. In addition, adrenergic release from the intestinal epithelial layer disrupts the integrity of the epithelial barrier. In OSAS patients, IH leads to ischemia-reperfusion injury of the intestinal mucosa and insufficient oxygen supply to the intestinal mucosa, resulting in changes in the structure and abundance of the gut bacteria and destruction of the integrity of the intestinal barrier. Prevotella and Desulfovibrio belong to the specific bacterial phylum Firmicutes, and the abundances of both bacteria increased significantly with IH exposure, exhibiting mucin-degrading features. The sulfate released during mucin degradation by Prevotella is cleared by Desulfovibrio, a process that further promotes mucin degradation and increases gut permeability. Disruption of the intestinal wall membrane integrity produces a small-molecule protein (plasma intestinal fatty acid-binding protein) that is considered to be a highly sensitive marker of the ischemic intestinal mucosa. Interestingly, plasma intestinal fatty acid-binding protein was found to be significantly elevated in OSAS patients. In addition, it has been found that the plasma D-lactic acid level is closely related to the permeability and degree of damage of the intestinal mucosa in patients with OSAS and is positively correlated with AHI. Dysbiosis of the gut microbiota reduces the levels of butyrate and acetate, causing intestinal mucosal nutritional disorders, which could lead to a dysfunctional epithelium. In addition, repeated hypoxia/reoxygenation cycles also damage the epithelium. Eventually, the tight junctions between colonic epithelial cells are destroyed, resulting in a “leaky gut.” As Prevotella produces endotoxin (lipopolysaccharide) and other bacterial components that leak from the gut into the blood circulation, it stimulates the release of inflammatory mediators, such as interleukin (IL)-6 and tumor necrosis factor (TNF)-α, through monocyte recruitment and Toll-like receptor activation, thereby aggravating systemic inflammation. Interestingly, a positive correlation was found between the abundance of the mucin-degrading bacterium Desulfovibrio and plasma lipopolysaccharide in IH-exposed mice. In addition, Prevotella converts nutrients (choline and l-carnitine) containing trimethylamine (TMA) into trimethylamine oxide (TMAO), which promotes inflammation, thrombosis, and the uptake of LDL by macrophages and contributes to hypertension and atherosclerosis. Multiple gut microfloral analyses demonstrated a reduction in bacteria associated with SCFA production in OSAS animal models and OSAS patients. SCFAs play an important role in maintaining intestinal integrity. Butyrate is a major source of energy and nutrition for enterocytes. An in vitro study has shown that butyrate enhances the expression of tight junction proteins, which are located transversally between epithelial cells, thereby increasing transepithelial resistance, maintaining gut integrity, and preventing gut permeability. Butyrate and propionate could induce the secretion of some mucin glycoproteins necessary for the construction of a mucus layer (which separates the colonocytes from the lumen) to protect intestinal epithelial cells. In addition, acetate enhances the differentiation of intestinal epithelial goblet cells and the secretion of mucus, which is beneficial for increasing the tight junction of enterocytes and improving the immune defense ability of enterocytes to inhibit lipopolysaccharide and bacteria from the gut entering into the systemic circulation. As hormone signaling molecules, SCFAs regulate immunity directly or indirectly through host metabolism through specific receptors. Butyrate can act on signal transducers of Th1 cells (T-helper 1 cells) and mTOR, an activator of transcription, and can upregulate B lymphocyte-induced maturation protein-1 (Blimp-1). Butyrate may induce the production of highly differentiated Th1 cells by acting on G-protein-coupled receptor 43 (GPR43) on intestinal epithelial cells to cause them to then secrete IL-10 and inhibit the excessive inflammatory response of Th cells. Butyrate also activates GPR109A, induces Treg and T-cell differentiation to produce IL-10 and inhibits intestinal inflammation by enhancing the anti-inflammatory properties of colonic macrophages and dendritic cells (DCs). The normal gut microbiota and its metabolites contribute to the regulation of Th17/Treg cell balance. Studies have found that SCFAs promote the proliferation and differentiation of Treg cells via epigenetic mechanisms. It has been confirmed that Th17/Treg cell imbalance is associated with the development of several disorders, and it is interesting to note that OSAS patients exhibit an increase in the number of Th17 cells and a significantly increased Th17/Treg cell ratio. Further studies showed that butyrate treatment of naive T cells could enhance histone H3 acetylation levels in the promoter and noncoding regions of the Foxp3 (forkhead Box p3) gene, induce naive CD4+ T cells to differentiate into peripheral Tregs, which secrete IL-10, and suppress the excessive immune response induced by Th1 and Th17 cells. Propionate and butyrate can downregulate the histone deacetylase (HDAC) activity of T cells to regulate immune function. This regulation might increase the phosphorylation of ribosomal protein S6, a target of the mTOR pathway, and induce the acetylation of p70 S6 kinase (S6K) and further phosphorylation of S6, ultimately promoting the differentiation of CD4+ T cells and the secretion of IL-10, IFN-γ, and IL-17. Interestingly, SCFAs can cross the blood‒brain barrier through the circulatory system, affect the growth and development of microglia, control their function and maturation, and enhance immunity and immune defense of the brain. There is increasing evidence that butyrate may provide neuroprotection by reducing microglial activation, which in turn decreases the levels of proinflammatory mediators and increases the levels of anti-inflammatory mediators. SCFA treatment also ameliorated the defective morphology and maturation of microglia in germ-free animals. Apparently, SCFAs have an immunomodulatory capacity not only in the gut and periphery but also in the nervous system. The mechanisms of OSAS-induced gut dysbiosis are shown in Fig. 4. IH-induced oxidative stress in OSAS In recent years, increasing evidence has implicated oxidative stress as a fundamental component of OSAS pathophysiology, which is manifested by increased ROS production and decreased antioxidant capacity. Oxidative stress is defined as a break in the balance between oxidant-generating systems and antioxidant defense mechanisms, and the oxidative stress associated with OSAS is due to the production of ROS exceeding the antioxidant supply. Repeated breathing cessation is characteristic of OSAS, a severe hypoxic episode followed intermittently by rapid blood oxygenations that could be considered to be similar to repeated ischemia-reperfusion events, which affects cellular components and functions, resulting in increased ROS production. In the reperfusion period, the flux of excess ROS can alter their biological functions and induce various pathologies by damaging various biomolecules, such as proteins, lipids, carbohydrates, and DNA. In OSAS, the main sources of ROS for these pathologies are derived from damaged mitochondria, activated inflammatory cells, or superoxide production by activated enzyme systems, such as xanthine oxidase, nitric oxide synthase uncoupling and NADPH oxidase (Fig. 5). Hypoxia and reoxygenation might also induce complex metabolic and molecular changes, which include changes in gene expression and changes in energy metabolism. The disruption of oxidant-producing systems and antioxidant defense mechanisms may also result from decreased antioxidant capacity. A decrease in antioxidant capacity resulting in an increased oxidative stress load has also been described in OSAS. For example, the total antioxidant capacity of serum is decreased in OSAS patients. Oxidative stress initiates a vicious cycle that facilitates the increased production of inflammatory cytokines, producing a systemic inflammatory state that increases vascular cell adhesion molecules and promotes sympathetic activation and vagal activation. Sympathetic activation stimulates the renin-angiotensin-aldosterone system (RAAS), which leads to increased levels of angiotensin II and aldosterone in the blood (Fig. 5). In addition, increased sympathetic tone is the key mediator of disrupted glycemic and insulin homeostasis, which may contribute to the development of metabolic risk factors in OSAS. Studies have found excessive ROS and increased expression of adhesion molecules and inflammatory cytokines, which reduce nitric oxide (NO) activity. The main consequences are endothelial dysfunction and hypercoagulability, which are identified as pathogenic mechanisms involved in different clinical and experimental models and affect various conditions and diseases (Fig. 5). However, in each disease, the results may differ according to the most affected organ or cellular function. It is estimated that more than 100 pathologies are associated with ROS and oxidative stress. Among them are cerebrovascular disease, cardiovascular disease, metabolic syndrome, type 2 diabetes, carcinogenesis and metastasis, inflammatory diseases (such as glomerulonephritis), atherosclerosis, and hypertension. A large body of evidence indicates that under normal physiological conditions, ROS function as signaling molecules, consistently described as regulators of signal transduction and as second messengers in many signaling pathways in all cells. Evidence regarding the capacity of ROS as signaling molecules is increasing. ROS regulates biological processes such as proinflammatory, profibrotic, cell proliferation, differentiation, migration, and apoptosis without triggering a requirement for macromolecular damage. Disruption of the ROS balance may activate a plethora of signaling pathways and inhibit others, affecting gene expression and protein function and leading to changes in signaling output, enzymatic activity, membranes, and intercellular communication. We present here a few examples of signaling targets. Increased intracellular ROS were implicated in the PI3K cascade, c‐Jun N‐terminal kinase (JNK), and MAPK pathways that might induce the activation of multiple nuclear transcription factors (Fig. 5), such as nuclear factor kappa B (NF-κB), AP-1, redox factor-1 (Ref-1), HIF-1α, sterol regulatory element binding proteins (SREBPs), p53 and GATA-4. NF-κB, as a master switch in inflammation, is of special interest in the pathological process of OSAS, which is subject to complex regulation involving many regulatory molecules. At the same time, it orchestrates the production of adhesion molecules, inflammatory cytokines, and adipokines in OSAS. In addition, AP-1 expression was upregulated in cultured PC12 cells exposed to IH. Given that the upregulation of AP-1 is similar to that of NF-κB, AP-1 might also be involved in the pathogenesis of OSAS. However, the pathways of activation are not yet fully elucidated. HIF-1α is a transcription factor that plays a major regulatory role in the transcriptional response to decreased oxygen levels, which is essential for oxygen homeostasis and the adaptive response to hypoxia, and has been found mainly in several experimental models of IH in tissue culture as well as in rodents exposed to chronic IH. In addition, it has been stated above that the transduction signals that activate HIF-1α under IH conditions are distinct from those activated by sustained hypoxia. IH may cause worse HIF-1α stability, resulting in the activation of NF-κB-induced inflammation, possibly as a result of oxidative stress. In addition, it is becoming increasingly clear that there is a large degree of crosstalk between HIF-1α and the NF-κB pathway, and recent studies suggest that the NF-κB pathway plays a key role in inflammation induced by sustained hypoxia. OSAS has been shown to activate redox signaling, which may contribute to several systemic and cellular functional changes (including changes in blood pressure, increased release of neurotransmitters, and alterations in sleep and cognitive function) that are associated with the activation of second messenger pathways and HIF-1α, which is potentially important in OSAS pathology. SREBPs are a group of transcription factors affected by redox imbalance and oxidative stress that regulate the expression of genes required to maintain lipid homeostasis. In an experimental model of IH, the SREBPs activating genes regulating lipid metabolism were shown to be upregulated. Recently, a series of elegant studies has shown that lipid peroxidation and atherosclerosis are closely associated with the severity of chronic IH, and SREBP pathway-mediated hyperlipidemia was observed in this model. Additional transcription factors that are redox-sensitive and could possibly be implicated in OSAS pathology include NRF2-Keap1, which regulates antioxidant genes with a role in maintaining redox homeostasis. IH-induced systemic inflammation in OSAS IH appears to be an important mechanism triggering inflammatory pathways. As outlined above, the main mechanisms of OSAS are hypoxia and oxidative stress, which are potent inducers of a cascade of inflammatory pathways. Furthermore, several studies have confirmed that inflammation also plays a crucial role in the occurrence and development of OSAS (Fig. 5). IH is hypothesized to activate the NF-κB-mediated inflammatory pathway that induces the overexpression of adhesion molecules [such as E- and P-selectin, intracellular adhesion molecule (ICAM) and vascular cell adhesion molecule (VCAM)], adipokines and proinflammatory cytokines [TNF-α, IL-1, IL-6, IL-8, and C-reactive protein (CRP)]. Activation of these inflammatory pathways promotes the activation of endothelial cells, immune cells (circulating leukocytes, monocytes, and T lymphocytes), and platelets. These activated cells can further promote oxidative stress and injury by releasing ROS and increasing the expression of adhesion molecules on leukocytes, platelets, and endothelial cells, thereby exaggerating the inflammatory response (Fig. 5). In OSAS pathophysiology, as well as in the conditions and comorbidities that aggregate with it, the presence of inflammation can be considered a potential contributor to OSAS. Cytokines are intracellular and extracellular soluble mediators that, by interacting with various transcription factors in a very complex and intermingled network, regulate both the innate and acquired immune systems, orchestrating immune cells and inflammatory responses. They stimulate cells to secrete inflammatory cytokines, activate and recruit macrophages, promote the proliferation of smooth muscle cells, interfere with nitric oxide production, and activate endothelial cells to cause vascular dysfunction. TNF-α synthesized by macrophages is a cell signaling proinflammatory cytokine that is involved in host defense, immune mechanisms, and the pathogenesis of different infections and participates in a large number of signaling events that, in turn, lead to necrosis and apoptosis. In patients with OSAS, circulating TNF-α levels are not only elevated in plasma or serum but are also elevated in monocytes and various cytotoxic T lymphocytes. In addition, TNF-α stimulates NF-κB activity, promoting increased expression of VCAM in endothelial cells, which enables enhanced monocyte adhesion to the endothelium, triggers inflammatory responses in endothelial cells, and promotes the initiation and progression of atherosclerosis. Interestingly, activation of inflammatory pathways via upregulation of NF-κB has recently been found in monocytes from patients with OSAS (Fig. 5). Several studies have highlighted the persistence of a state of systemic chronic low-grade inflammation in patients with OSAS, mainly characterized by increased levels of TNF-α, IL-6, IL-8, and CRP. The major proinflammatory cytokines (TNF-α, IL-6, and IL-8) that activate NF-κB and AP-1 are regulated by oxygen tension and free radicals. Conversely, these cytokines can further activate inflammatory transcription factors and enhance inflammatory responses by activating various blood cells and endothelial cells. Adhesion molecules are cell surface proteins that play a key role in intercellular associations and are considered to be a major part of the inflammatory response against hypoxia. When facing various stimuli, such as hypoxia/reoxygenation and OSAS, adhesion molecules, and cytokines are upregulated in blood leukocytes and endothelial cells, which promote endothelial cell injury. CRP not only upregulates the transcriptional activity of NF-κB but also promotes the expression of ICAM and VCAM, which induces monocyte-endothelial cell adhesion. Thus, it is clear that CRP is not only an inflammatory marker but also a functional regulator that might contribute to the development of inflammation in OSAS through oxidative stress. Other IH-induced signaling pathways in OSAS Plasminogen activator inhibitor-1 (PAI-1) levels are consistently elevated in OSAS patients, and there are multiple pathways through which OSAS can trigger PAI-1 upregulation. The metabolism of PAI-1 has been implicated in several diseases and conditions, including cardiovascular disease, metabolic diseases, and cancer. Cells exposed to hypoxia showed increased PAI-1 mRNA expression and stability. ROS are involved in most of the mechanisms regulating PAI-1 expression. Incubation of endothelial cells with H2O2 induced a significant increase in PAI-1 mRNA and protein expression. In contrast, the PAI-1 promoter is repressed by up to 75% in the presence of antioxidants. The ROS-induced increased transcription and expression of PAI-1 is mediated by activation of the MAPK and NF-κB pathways, which are tightly linked to proinflammatory pathways. In addition, in vitro and in vivo experimental studies as well as clinical studies, have identified TNF-α as an important factor in increasing PAI-1 expression. In endothelial cells, TNF-α upregulates PAI-1 levels and is abolished by N-acetylcysteine, suggesting that ROS are mediators. IL-6 is another inflammatory cytokine that regulates PAI-1 upregulation. Animals injected with IL-6 had a significant increase in PAI-1 levels, whereas the use of an IL-6 receptor antagonist decreased PAI-1 expression. IL-6 can also activate the MAPK/NF-κB signaling pathway, leading to increased transcription of PAI-1. PAI-1 is one of the major transcriptional targets of HIF-1α. Hypoxic stimulation by IH could promote HIF-1α signaling and the upregulation of PAI-1. In addition, IH-induced HIF-2α, CCAAT-enhancer-binding protein-α (C/ΕBPα) and early growth response protein-1 (Egr-1) could also upregulate PAI-1 expression (Fig. 6a). Recent studies have demonstrated endoplasmic reticulum (ER) stress in the brain, heart, kidney, and liver of rodents exposed to IH. The ER is an important organelle for protein synthesis, folding, lipid biosynthesis, secretion, and cell homeostasis. When cells are stimulated by hypoxia or oxidative stress, homeostasis is disrupted. The accumulation of unfolded and misfolded proteins in the ER activates ER stress, which in turn triggers the unfolded protein response (UPR). UPR activation is regulated by the chaperone protein glucose-regulated protein BiP/GRP78. Prolonged or severe ER stress induces accelerated separation of BiP and GRP78, which activates protein kinase-like kinase (PERK), transcription factor 6 (ATF6) and inositol requiring enzyme 1 (IRE1). Activated ATF6, PERK, and IRE1 accelerate the activation of CHOP protein, which mediates apoptosis. CHOP deficiency protects cells from apoptosis induced by excessive ER stress. The UPR in mammals has three branches: the IRE1 pathway, PERK pathway, and ATF6 pathway. Phosphorylated IRE1 activates the downstream target proteins JNK and p38 MAPK. A study has shown that phosphorylation of JNK both activates proapoptotic BIM and inhibits antiapoptotic Bcl-2. In addition, the activated ATF6 pathway and PERK pathway are also involved in ER stress-related apoptosis. XBP1 is spliced by the endoribonuclease for IRE1 under ER stress, acting as a potent transcription factor for CHOP. IH in patients with OSAS increases ROS generation, which reduces the production of functional proteins and even leads to apoptosis. Several studies have confirmed that the levels of ER stress-related proteins, including JNK, MAPK, GRP78, CHOP, PERK, p-eIF2α, and ATF4, were dramatically increased when exposed to IH. Cai et al. found that the PERK-eIF2α signaling pathway was involved in apoptosis in rats under IH conditions. In addition, the expression of IRE1-XBP1 and ATF6 was significantly increased in rat cardiac tissues after IH exposure for 5 weeks. In another study of cardiovascular disease in rats, the protein expression of the ER stress marker proteins BiP, PERK, CHOP, and ATF4 was increased in IH. During IH, Bcl-2/Bax is low, and activation of caspase-3, caspase-9, caspase-12, and JNK is induced (Fig. 6b). Epigenetic alterations in OSAS Epigenetics is generally defined as heritable phenotypic changes that do not involve DNA sequence changes that are not directly encoded by modifications of the nucleotide genomic sequence but by posttranslational modifications of DNA and histones and the regulation of noncoding RNAs. Recent studies have shown that epigenetic changes are associated with the development of OSAS and its pathogenesis, but the specific mechanisms of action are currently unknown. Below, we review relevant studies on the relationship between epigenetics and OSAS, and further understanding of the interplay between genetic and environmental factors through epigenetic regulation will be valuable to gain insight into the mechanisms underlying OSAS-associated oxidative stress, low-grade inflammation, and sympathetic hyperactivity. Noncoding RNAs include microRNAs (miRNAs) and long noncoding RNAs (lncRNAs). MiRNAs, a class of single-stranded RNAs consisting of 19 to 25 nucleotides in length, can regulate gene expression by binding to mRNA. MiRNAs can mediate posttranslational gene silencing and thus negatively regulate target genes. Recent studies have found that multiple miRNAs can influence the IH process and influence hypoxia-induced apoptosis. For example, in a rat model, miR-26b-5p upregulation and miR-207 downregulation were involved in IH-induced cognitive impairment by increasing Bax and cleaved caspase-3 expression and reducing Bcl-2 expression in the hippocampus. MiR-155 promoted oxidation and enhanced the IH-induced NLRP3 inflammasome pathway by repressing the target forkhead box protein O3 (FOXO3a) gene in a murine model and HK-2 cells. Interestingly, IH-induced NLRP3 inflammasome activation in renal tubular cells was then suppressed by inhibiting miR-155 expression. In addition, miR-155 has been shown to have a proapoptotic function in diseases where other antiapoptotic proteins, such as clusterin, are decreased and correlate with increased clusterin levels in OSAS. MiR-664a-3p is downregulated in patients with OSAS and is negatively correlated with AHI and carotid intima-media maximum thickness, suggesting that circulating miR-664a-3p has the potential to serve as a noninvasive marker of atherosclerosis in OSAS. MiRNAs have been considered ideal biomarkers in the era of precision medicine, and sequencing analysis has shown that the expression levels of miR-199-3p, 107, and 485-5p were downregulated, whereas the expression level of miR-574-5p was upregulated in OSAS patients, suggesting that the differentially expressed miRNAs are closely related to OSAS. Based on the current study, miRNAs could be potential indicators for the diagnosis and treatment of OSAS in the future (Table 4). LncRNAs are composed of RNA strands longer than 200 nucleotides that are not translated into proteins, and experimental evidence has shown that they can regulate gene expression through a variety of mechanisms, including transcriptional activation or repression, chromatin modification, and posttranscriptional regulation. A microarray study of cardiac samples from rats exposed to IH for 8 weeks identified 157 lncRNAs with upregulated expression and 132 lncRNAs with downregulated expression. Three of the downregulated lncRNAs (XR_600374, XR_590196, and XR_597099) and three of the upregulated lncRNAs (XR_596701, XR_344474, and ENSRNOT00000065561) were validated by quantitative reverse transcription polymerase chain reaction. This study provides novel insights into lncRNAs in the pathogenesis of IH. Another study found that overexpressing lncRNA CPS1-IT decreased IL-1β through the transcriptional activity of HIF-1 expression to reduce pulmonary arterial hypertension in OSAS patients. Multiple studies have confirmed that the abnormal expression of lncRNAs promotes the occurrence and development of diseases, and some lncRNAs have been identified as biomarkers for diseases. LncRNA is not only a repressive regulator but also a source of miRNAs. Du et al. found that blocking the lncRNA MALAT1/miR-224-5p/NLRP3 axis suppressed hippocampal inflammation in type 2 diabetes mellitus patients with OSAS. Another experiment on aortic endothelial dysfunction in OSAS patients showed that the lncRNA maternally expressed gene 3 (MEG3) altered HIF-1α expression by competitively binding to miR-135a, and silencing MEG3 could inhibit aortic endothelial cell apoptosis and injury. More details are given in Table 5. Further studies are needed to clarify the role of lncRNAs as potential biomarkers in OSAS. DNA methylation, the best-known and best-characterized epigenetic modification, is a heritable, reversible epigenetic change that mediates the transcriptional silencing of genes by altering transcription factors in the promoter regions of genes and activates gene transcription by alternative splicing. DNA hypermethylation usually leads to transcriptional repression and decreased gene expression, whereas DNA hypomethylation affects chromosomal stability. Currently, there are few studies on the role of DNA methylation in OSAS. A previous study showed that the FOXP3 gene, which regulates T regulatory lymphocyte expression, showed increased DNA methylation in a total cohort of children with OSAS who had increased systemic inflammatory responses, suggesting that epigenetic-mediated downregulation of T regulatory lymphocytes might be an important determinant of OSAS-induced systemic low-grade inflammation. IH-exposed neonatal rats exhibit increased DNA methylation in the promoter region of the superoxide dismutase (SOD2) gene, and methylation modification has long-lasting effects on elevated chemoreflex sensitivity and hypertension in adult rats. Another study also confirmed that the impairment of respiratory and carotid body chemosensory reflexes by IH is partly the result of inhibition of antioxidant enzyme (AOE) genes via DNA methylation, including peroxiredoxin 4 (Prdx4) and thioredoxin reductase (Txnrd2). Previously, in a study of epigenomic DNA methylation, Chen et al. demonstrated multiple differentially methylated genes associated with OSAS and its adverse outcomes. Studies have found that hypomethylated interleukin 1 receptor 2 (IL-1 R2) and hypermethylated androgen receptor (AR) may be important contributors to disease severity, whereas hypomethylated natriuretic peptide receptor 2 (NPR2) and hypermethylated speckled protein 140 (SP140) may be biomarkers that predispose patients with OSAS to excessive daytime sleepiness (Table 6). Diseases associated with OSAS Repeated processes of airway collapse and obstruction caused by various pathological factors in OSAS patients lead to recurrent apnea and periodic arousal during sleep, which eventually cause IH and sleep fragmentation. These core factors stimulate cell and molecular mechanisms, including increased sympathetic nerve activity, metabolic dysregulation, systemic inflammation, oxidative stress, and endothelial dysfunction, which have been identified as pathogenic in different clinical and experimental models and could lead to various OSAS-related complications. Different mechanisms may predominate in specific comorbidities, and the evidence for an independent association between OSAS and comorbidities is stronger for some comorbidities than others. While the detailed molecular mechanisms leading to the development of cardiovascular, cerebrovascular, and other diseases in OSAS are complex and several different mechanisms are involved, it seems that oxidative stress and inflammation are fundamental underlying mechanisms and are closely related to diseases in various systems throughout the body. OSAS and cardiocerebrovascular disorders A large body of evidence indicates that OSAS is associated with a number of cardiovascular complications, including systemic hypertension, arrhythmias, coronary artery disease, and stroke. The most convincing epidemiologic evidence of a causal relationship between OSAS and hypertension was provided in the 4-year follow-up results from the Wisconsin Sleep Cohort study. It is estimated that approximately 50% of patients with OSAS suffer from hypertension, and 30–40% of patients with hypertension suffer from OSAS. This is particularly true in patients with resistant hypertension, of whom up to 80% may suffer from OSAS. The Sleep Heart Health Study (n = 6132) also showed an increased likelihood of hypertension with increasing severity of OSAS, and the prevalence of hypertension was 59, 62, and 67% in patients with mild, moderate, and severe sleep apnea, respectively. In addition, OSAS is also responsible for masked hypertension in many cases. The ROS-dependent increase in sympathetic nerve activity (SNA) is a prominent feature of OSAS and has been shown to be associated with OSAS-related atrial fibrillation (AF), heart failure, and hypertension. Sympathetic outflow to the kidney is increased and stimulates renin release, which leads to increased circulating levels of angiotensin II and aldosterone, which in turn increases vascular resistance to constrict the vessels and raise blood pressure. Circulating and urinary catecholamines, which are biomarkers of elevated SNA, are also elevated in patients with OSAS. Emerging evidence implicates transcriptional changes by HIF-1α as an important molecular mechanism by which IH leads to SNA and hypertension. Animal studies of OSAS have shown activation of HIF-1α in myocardial tissue and increased expression of its downstream gene endothelin. Endothelin is a potent vasoconstrictor that causes blood pressure elevation. Advances in the understanding of cardiovascular disease in OSAS are closely related to the understanding of the development of coronary artery disease, but the underlying mechanisms remain poorly understood. The pathogenesis is likely to be a multifactorial process involving several mechanisms, including SNA, oxidative stress, vascular smooth muscle cell activation, lymphocyte activation, increased lipid levels, and lipid peroxidation within macrophages leading to endothelial dysfunction, which largely contributes to the development of various cardiovascular diseases, particularly atherosclerosis. IH triggers a molecular response that generates inflammation and oxidative stress and induces the formation of ROS, which in turn activates the inflammatory cascade by activating the transcription factor NF-κB and downstream genes such as inflammatory cytokines and adhesion molecules. Various activated blood cells produce more ROS, adhesion molecules, and proinflammatory cytokines. Adhesion molecules promote the accumulation of platelets, leukocytes, and possibly red blood cells on the vascular endothelium. Clinical studies have confirmed that blood cells from patients with OSAS present a proinflammatory and prothrombotic phenotype; additionally, the role of monocytes in the initiation and propagation of the progression of atherosclerosis is well established, and resident or circulating leukocytes mediate monocyte adhesion to the endothelium, which might promote thrombosis, endothelial dysfunction, and atherosclerosis. Growing evidence indicates a concomitant prevalence of AF of 21–74% in patients with OSAS, suggesting that OSAS might be a causative factor in AF pathogenesis. A potential explanation is the enhanced sympathetic and vagal nerve activities caused by hypoxemia, which triggers AF during acute OSAS. Chronic recurrence and sudden negative changes in intrathoracic pressure play a crucial role in atrial autonomic, structural, and electrical remodeling, leading to structural and functional atrial remodeling that triggers AF by contributing to atrial fibrosis. Multiple prospective studies have demonstrated a strong association between moderate-severe OSAS and stroke. The Wisconsin Sleep Cohort study found that an AHI >20 was significantly associated with an increased risk of stroke, while another study found that men with an AHI >15 had a threefold increased risk of stroke. Unsurprisingly, concurrent AF substantially increased the risk of stroke in patients with OSAS. Continuous positive airway pressure (CPAP) therapy has been shown to benefit the incidence and recurrence of stroke in patients with OSAS, and another study showed that CPAP therapy can reduce the rates of stroke and cardiovascular events in patients with severe OSAS. Hypertension or other traditional vascular risk factors do not fully explain the association of OSAS with stroke, and the underlying mechanisms include multiple factors such as hypercoagulability, cardiac arrhythmias, inflammation, oxidative stress, dysautonomia, and dyslipidemia. Accumulating evidence suggests that oxidative stress, inflammation, and molecular mechanisms play an important role in the pathophysiology of cardiocerebrovascular disease in patients with OSAS. In addition, a clinical lesson learned from understanding the underlying pathophysiology of OSAS with the accompanying comorbidities is that to prevent cardiovascular morbidity, treatment of breathing disorders during sleep might need to start at the earliest possible age. OSAS and neurological disorders Prolonged periods of IH in patients with OSAS could impact multiple CNS systems, all of which ultimately lead to severe neurocognitive and behavioral deficits, including a decline in cognitive functions, such as memory, executive function and comprehension, mood disturbances, insomnia, and/or excessive daytime sleepiness. In addition, OSAS may promote the development of neurodegenerative diseases. The results of animal studies from our team have shown that IH induces severe neuronal injury (especially in the hippocampal CA1 region), enhances inflammation, and activates astrocytes in the rat brain. The rats in the IH group showed a much longer escape latency when locating the hidden platform and much less time spent in the target quadrant than the normal control group. In addition, we found that IH significantly increased ROS levels, decreased manganese superoxide dismutase (Mn-SOD) and catalase (CAT) expression, increased the levels of lipid peroxidation products [including malondialdehyde (MDA) and DNA damage products, such as 8-hydroxy-2’-deoxyguanosine (8-OHdG)] in the hippocampus and significantly increased caspase-1, IL-1β, and IL-18 expression in the frontal medial cortex in mice. IH-induced increases in neuroinflammation, oxidative stress, and brain tissue damage in mice might account for the diminished performance in the Morris water maze test. We used the Montreal Cognitive Assessment (MoCA) and Epworth Sleepiness Scale to evaluate the cognitive status of OSAS patients in our previous clinical study. The findings showed significant impairments in attention, delayed memory function, and executive function in patients with OSAS, and the MoCA scores were negatively correlated with the AHI and oxygen desaturation index and positively correlated with the lowest oxygen saturation. In this study, we compared the automatic processing of emotional facial expression patterns between OSAS patients and matched normal controls by evaluating expression-related mismatch negativity (a brain electrophysiological detection tool) and found that OSAS patients suffer from cognitive impairment in the automatic processing of emotional facial expressions under the preattentive condition. Structural and functional alterations in brain anatomy and function in OSAS patients provide indirect evidence that OSAS causes damage to brain structures over time. Perhaps these changes underlie cognitive impairment. Studies have suggested a decrease in gray matter in the prefrontal cortex, anterior cingulate cortex, thalamus, parietal cortex, parahippocampal gyrus, inferior temporal gyrus, hippocampus, and cerebellum in patients with OSAS. It is well known that the brain is more sensitive to hypoxia than other organs and requires more energy and oxygen consumption. Clinical and animal findings suggest that IH resulting from OSAS can lead to structural neuronal damage and dysfunction in the CNS, with oxidative stress and inflammatory damage being the pathophysiological basis. Accumulating evidence supports the view that, in the CNS, IH may induce ROS production in the CNS, oxidative stress overactivation, and inflammatory damage leading to neuronal apoptosis and/or necrosis that, in turn, contributes to the development of OSAS-related cognitive impairments. Brain tissue NF-κB, TNF-α, CRP, IL-1β, IL-6, and cyclooxygenase-2 (COX-2) levels were measured in IH animal models, which were consistent with the changes seen in human plasma. The standardized regression test showed significant associations between proinflammatory cytokines and neurocognitive performance. A recent study confirmed that nocturnal overactivation of the sympathetic nervous system can lead to visuospatial dysfunction in patients with OSAS. The most prominent maladaptive effect of IH is neuroinflammation, and although the exact neural cell source of the associated processes is still not fully understood, microglial activation may be important. The findings showed that IH exposure resulted in a significant increase in microglial activity and hippocampal neuronal apoptosis, as well as increased levels of related inflammatory markers (NF-κB, TNF-α, and IL-1β). Microglia, the major inflammatory cells of the CNS, mediates oxidative stress and inflammation through mitochondria, NADPH oxidase, and the release of excitotoxic neurotransmitters. Recently, we demonstrated an important role for microglia in the hippocampus in the development of diabetic encephalopathy by single-cell RNA sequencing. NADPH oxidase is involved in microglia-mediated neurotoxicity and microglial activation. Activated microglia express high levels of inducible nitric oxide synthase (iNOS) and COX-2 isoforms, ultimately leading to increased ROS generation. Furthermore, activated microglia trigger the NF-κB signaling pathway, which regulates the immune inflammatory response, oxidative stress, and memory. Studies have confirmed that this pathway plays an important role in hypoxia. JNK is a member of the MAPK family and has a complex relationship with the NF-κB pathway. IH effectively activated the NF-κB/JNK pathway and its downstream signaling molecules, confirming the role of the NF-κB-mediated JNK pathway in hippocampal injury and cognitive dysfunction in IH model rats. p38 MAPK is also a member of the MAPK family, and its activation has adverse effects on learning and memory. In an IH animal model, p38 MAPK levels were significantly increased, which could activate the NF-κB signaling pathway, releasing cytokines such as IL-1 β, IL-6, and TNF-α, oxidative species, and adhesion molecules. The release of cytokines, in turn, promotes the production of ROS by microglia, thereby perpetuating inflammation and aggravating ongoing oxidative stress. CNS neuronal damage and apoptosis from IH might involve other mechanisms. For example, brain-derived neurotrophic factor (BDNF), an important neuromodulator of CNS function, significantly prevents oxidative stress-induced neuronal damage in the CNS. In addition, microglia release excitatory toxic neurotransmitters, such as glutamate, and studies have shown that higher glutamate concentrations are found in the cerebral cortex of OSAS patients, leading to excitotoxicity-induced neuronal dysfunction and apoptosis. Undoubtedly, most OSAS patients develop cognitive and neurologic dysfunction. Furthermore, these findings suggest a strong link between inflammation and cognitive impairment in OSAS (Fig. 7). At the same time, evidence regarding its links with neurological diseases is similarly accumulating. The evidence for its links with major psychiatric and neurologic disorders is similarly accumulating. However, the exact nature of the mechanisms responsible for these effects remains to be determined and must be investigated further. OSAS and metabolic diseases Growing evidence in animal models of OSAS suggests that IH is independently associated with metabolic dysfunction. In particular, OSAS was independently associated with insulin resistance, suggesting that OSAS might be an important factor in the development of type 2 diabetes and so-called metabolic syndrome (MS), namely, obesity, insulin resistance, hypertension, and dyslipidemia. Studies have confirmed that the levels of fasting blood glucose and insulin resistance in OSAS patients are significantly higher than those in non-OSAS patients, and the severity of OSAS is related to an increase in insulin resistance. Moreover, the relationship between OSAS and insulin resistance also applies to nonobese patients. In addition, clinical data suggest that the AHI is an independent risk factor for insulin resistance and type 2 diabetes. With each unit increase in the AHI, the level of insulin resistance increased by 0.5%. In vivo kinetic studies of glucose metabolism have also demonstrated that severe OSAS impairs insulin sensitivity, glucose effectiveness, and pancreatic β-cell function. Oxidative stress and inflammation induced by intermittent hypoxemia in patients with OSAS may be key factors in insulin resistance. Inflammatory factors induced by OSAS, including TNF-α, IL-6, and IL-18, which activate NF-κB, JNK, and other downstream signaling pathways, inhibit insulin receptors and the phosphorylation of insulin receptor substrates, leading to insulin resistance. IH decreases glucose uptake in muscle, increases β-cell proliferation and β-cell death and can also affect ATP synthesis in pancreatic islet β cells, thereby inhibiting insulin secretion. Increased sympathetic tone in OSAS patients is a key mediator of deterioration of glycemic and insulin homeostasis, and increased levels of catecholamines after arousal directly stimulate glycogen mobilization and inhibit muscle glucose uptake, stimulate glucagon secretion, and inhibit insulin secretion. In addition, IH has been shown to induce lipid abnormalities, such as increased total cholesterol, triglycerides, high-density lipoprotein-cholesterol (HDL-C), very-low-density lipoprotein (VLDL), and low-density lipoprotein (LDL) levels, and the severity of lipid elevation is proportional to the severity of hypoxic stimulation. Several cross-sectional studies have shown that OSAS is independently associated with increased levels of total cholesterol, LDL, and triglycerides and that treatment of OSAS with CPAP may have beneficial effects on the lipid profile. In addition to the promotion of SREBP expression by IH mentioned earlier, IH is also related to lipoprotein lipase inhibition in adipose tissue, which leads to an increase in plasma chylomicron particles and VLDL that may be conducive to the progression of atherosclerosis. IH increases leptin gene expression levels, acting centrally and peripherally to inhibit insulin secretion while increasing glucose uptake. A number of reports have demonstrated that serum leptin levels are positively correlated with AHI and hypoxemia in patients with OSAS. The higher the serum leptin level is, the higher the AHI and the longer the duration of hypoxemia. Conversely, adiponectin’s effects counter those of leptin, an insulin-sensitizing hormone with antiatherogenic, anti-inflammatory, and antidiabetic effects, and IH may inhibit adiponectin secretion; studies have demonstrated significantly lower circulating adiponectin levels in patients with OSAS and a negative correlation with the AHI. In summary, OSAS leads to metabolic dysfunction (Fig. 8). However, the exact relationship between OSAS and metabolic diseases remains controversial, and most cross-sectional studies lack adequate sample sizes. The specific mechanism remains to be further studied. In addition, there is an urgent need to increase awareness of their strong association, and early detection of comorbidities cannot be overemphasized. OSAS and cancer Over the past years, circumstantial, epidemiological, clinical, and animal-based experimental evidence has provided significant support that OSAS affects tumorigenesis and tumor development. A large multicenter cohort of cancer-free patients with OSAS showed that nocturnal hypoxemia was associated with all-cancer incidence in OSAS patients. Patients younger than 45 years with severe OSAS have a significantly higher incidence of all types of cancer than the general population. Epidemiologic studies have also confirmed that OSAS is associated with increased cancer-related mortality. A dose‒response relationship between OSAS severity and cancer-specific mortality was observed over a 22-year follow-up of 1522 participants in the community-based Wisconsin Sleep Cohort study, with severe OSAS conferring a nearly fivefold risk of death from cancer. OSAS appears to elevate the incidence of some tumor types, including lung cancer, breast cancer, prostate cancer, nasopharyngeal tumors, and melanoma. In certain types of tumors, IH exposure that mimics the oxygenation pattern induced by OSAS during sleep promotes the growth, invasion, and metastasis of lung cancer, colon cancer, and melanoma. OSAS-associated intermittent hypoxemia may affect tumor biology via several mechanisms, including oxygen-sensing pathways, chronic systemic inflammation, oxidative stress, endothelial dysfunction, and immune dysregulation. The carotid body response to hypoxemia and sleep fragmentation increases sympathetic nervous system activity, which might affect the tumor and its microenvironment and contribute to cancer progression. Oxidative stress promotes tumor occurrence and progression, and it has been mentioned previously that increased oxidative stress can cause damage to DNA, proteins, and lipids, leading to gene mutations, altered cell growth patterns, and, ultimately tumorigenesis. It has also been demonstrated that in sleep apnea, oxidative stress-induced DNA damage can increase the probability of genetic mutations and hence increase cell malignant transformation potential. In addition, ROS activate the AP-1 and NF-κB signaling pathways, with increased levels of AP-1 observed in many human tumor types. AP-1 regulates the expression of cell cycle regulators (p53, p19, p21, and cyclin D1) while also affecting the downregulation of tumor suppressor genes, thereby inducing hyperproliferation and tumorigenesis. NF-κB can induce the expression of cell proliferation molecules, apoptosis inhibitor factors, proangiogenic factors, and enzymes involved in extracellular matrix degradation. The activation of NF-κB increases the expression of genes associated with the inflammatory response and increases the cellular response to proinflammatory factors. In particular, the expression of COX-2, CC motif chemokine ligand 2 (CCL2), CXC motif chemokine ligand (CXCL)1, IL-8, and IL-6 was increased. All are inflammatory mediators involved in various neoplastic processes. Thus, NF-κB is regarded as having an important role in tumor development. ROS generated by IH can also activate HIF-1α, which is highly expressed in many solid tumors and plays an important role in many aspects of tumor angiogenesis, cell survival, proliferation, apoptosis, metastasis, invasion, and metabolism. Moreover, IH can affect the expression of HIF-1α downstream genes by upregulating the transcription of HIF-1α, for example, upregulating the expression of the vascular endothelial growth factor gene (VEGF), which in turn induces tumor angiogenesis and promotes tumor development, as also demonstrated in animal experiments using IH (or intermittent blood flow). Downregulation of immune responses against cancer is an important mechanism by which IH might affect tumor growth and aggressiveness. Data from studies of tumor-specific immune function in patients with OSAS also suggest that IH might contribute to reduced innate antitumor responses. The upregulation of tumor-promoting gene sets in untreated patients with severe OSAS was demonstrated by genome sequencing in circulating leukocytes, and the expression of these genes was downregulated after approximately one month of CPAP treatment. A key effector cell in cancer biology is the macrophage, and tumor-associated macrophages (TAMs) have now been identified as a crucial component of the cancer microenvironment, especially those with an anti-inflammatory M2 phenotype, inhibiting the antitumor activity of T cells and NK cells and releasing growth factors, cytokines, inflammatory mediators, and proteolytic enzymes involved in tumor growth and invasion to promote their proliferative development. Animal model experiments have found that IH exposure selectively induced a tumor-promoting phenotype, and TAMs explanted from IH-exposed mice enhanced the proliferation and invasiveness of lung epithelial cancer cells in vitro. More specifically, IH recruits more TAMs to participate in tumor progression and accelerates their transformation from an antitumor phenotype (M1) to a tumor-promoting phenotype (M2). It is interesting to find that CCL2 is a TAM recruiting factor, and PGE2 has an effect against tumor cells, playing an important role in the mechanism of cancer immune evasion. PGE2 inhibits the anticancer function of NK cells and enhances the cancer-promoting function of M2 macrophages and regulatory T (Treg) cells. Increased sympathetic activity caused by apnea may also contribute to cancer development. In vitro studies have shown that adrenergic signaling can regulate multiple cellular processes involved in cancer progression and that long-term treatment with β-blockers improves outcomes in several human cancers. In addition, evidence suggests that activated sympathetic nerves contribute importantly to changes in macrophage recruitment and differentiation that alter gene expression within the primary tumor. In conclusion, the available data suggest that OSAS might be an important risk factor for cancer development and aggressive cancer behavior. Data linking OSAS to the risk of neoplastic disease are scarce, but the above retrospective studies reveal the possibility of a close relationship (Fig. 9), which should stimulate more research on the effects of OSAS on carcinogenesis, tumor progression, and metastasis. In addition, there are currently no relevant studies reporting the complex links between sleep, adrenergic signaling, and cancer biology, suggesting a new direction for future research. OSAS and reproductive disorders Emerging evidence suggests that IH associated with OSAS might contribute to reduced fertility and decreased testicle antioxidant capacity in male patients with this sleep-breathing disorder. In parallel, motility impairment of sperm and increased oxidative stress markers were observed in the testes of middle-aged and young mice subjected to IH, which resulted in reduced sperm motility. In addition, OSAS has been reported to cause alterations in male sexual function, and previous studies using IH in an animal model of OSAS showed that mice subjected to a chronic exposure protocol develop erectile dysfunction accompanied by decreased libido and impaired sexual capability. Multiple studies have confirmed that 10 to 60% of patients with OSAS may experience erectile dysfunction, and although erectile dysfunction is a frequently reported sexual dysfunction in males with OSAS, notably, OSAS also has a negative impact on sexual function in females. Interestingly, erectile dysfunction may be significantly improved after treatment with CPAP. As mentioned above, OSAS can cause reduced NO production and elevated levels of endothelin, leading to endothelial dysfunction, which results in increased vasoconstriction and impaired endothelial cell function. It has also been shown that IH increases oxidative stress in erectile tissue through the modulation of NADPH oxidase enzymes, leading to decreased NO production and subsequently to impaired penile tumescence. Another potential mechanism is the nocturnal suppression of testosterone release, as peak testosterone levels coincide with the onset of REM sleep, but patients with OSAS suffer from disrupted sleep and a reduction in the number and time of REM sleep episodes, which is associated with reduced circulating testosterone concentrations. In addition, hypo- and hypercapnia suppress the increase in blood testosterone levels during the night. The results from a large cohort study suggest that OSAS is associated with an increased risk of preeclampsia, eclampsia, and gestational diabetes, even after controlling for obesity. Another retrospective population-based dataset study found an increased risk of preeclampsia among pregnant women with OSAS, and these differences remained significant after controlling for obesity. Moreover, experimental studies in animals have found that pregnant rodents subjected to chronic hypoxia developed preeclampsia-like symptoms. IH-induced inflammation and oxidative stress are considered major contributors to end-organ damage in preeclamptic patients. OSAS-induced inflammation-related factors (TNF-α, IL-6, IL-8, and CRP) might act through synergistic pathways with the pathogenesis of preeclampsia. Evidence suggests that hypoxia-related signaling pathways in preeclampsia might be mediated by the immune system. At present, the mechanisms linking OSAS to preeclampsia are also not well defined, and we propose some plausible mechanisms, but few studies have investigated these potential pathways. This hypothesis remains to be further studied. OSAS and COVID-19 Coronavirus disease 2019 (COVID-19) is a severe respiratory-compromising disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 virus) infection and is currently causing a pandemic. The link between OSAS and COVID-19 is biologically plausible. First, systemic chronic low-grade inflammation in patients with OSAS might contribute to a more severe immune response to COVID-19. Furthermore, OSAS could exacerbate the core symptoms of severe COVID-19, especially during the night, when oxygen saturation levels in OSAS become lower, resulting in more pronounced hypoxemia-, oxidative stress-, and hypoxia-related manifestations. Studies have shown that the risk of infection with COVID-19 was much higher in OSAS patients than in non-OSAS patients. Among patients with COVID-19 infection, OSAS was associated with an increased risk of hospitalization and could increase the risk of developing respiratory failure. OSAS is known to be strongly associated with male sex, obesity, and diabetes, all of which are well-recognized risk factors for severe COVID-19. It is inevitable that the limitations of these important confounders influence such conclusions. After addressing possible confounders, the most recent study found that OSAS was associated with a twofold increased risk of severe COVID-19, a finding that could not be explained by obesity or other comorbidities. These current findings strongly suggest that OSAS is an independent factor contributing to the risk of more severe COVID-19. The most damaging complication during COVID-19 is the cytokine storm involving IL, TNF-α, CRP, leptin, and ferritin. Similar inflammatory responses observed during OSAS have been described in detail previously. There is a close relationship between hypoxemia and cytokine storms, and hypoxia/reoxygenation in OSAS patients worsens hypoxemia, thereby aggravating cytokine storms. Moreover, HIF-1α and NF-κB, which are associated with OSAS, are fully involved in the triggering effect of hypoxemia on cytokine storm development. Notably, studies have established that SARS-CoV-2 enters host cells by binding to the angiotensin-converting enzyme-2 (ACE-2) receptor. ACE-2 is a noncanonical pathway of the renin-angiotensin system (RAS) pathway, and therefore, the RAS itself is involved in the pathogenesis of COVID-19. Interestingly, the increased expression of ACE-2 and dysregulation of the RAS in untreated OSAS patients due to IH have been shown, which could facilitate the entry of the SARS-CoV-2 virus into host cells, increase its viral load and infectivity, and ultimately lead to severe disease outcomes and mortality. In addition, patients with OSAS might have a higher susceptibility to the SARS-CoV-2 virus and might be more susceptible to the virus. In conclusion, we propose that dysregulation of the RAS plays an important role in the pathogenesis of COVID-19 in OSAS patients and that IH might exacerbate cytokine storms in COVID-19, leading to acute respiratory distress syndrome and multiorgan failure. Data from the current study are very limited, and further studies are needed to better define the relationship between OSAS and COVID-19. | [
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|
34100423 | title | Presenilin mutations and their impact on neuronal differentiation in Alzheimer's disease. | [
[
69,
88
]
]
|
37559139 | title | Enhanced activity of the left precuneus as a predictor of visuospatial dysfunction correlates with disease activity in rheumatoid arthritis | []
|
39215230 | methods | Methods Study design and registration The systematic review and meta-analyses followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines (Fig. 1) and is registered with the International Prospective Register of Systematic Reviews (XXX). Literature search strategy A systematic literature search was conducted using three databases: PubMed, Web of Science, and Scopus, from inception to December 2023. The search terms were collaboratively developed by the authors, drawing on recent systematic reviews related to similar topics. Keywords were derived using the PICO framework, which includes participant/patient, intervention, comparator/comparison, and outcomes. The search strings comprised terms such as: (‘Alzheimer’s disease’ OR ‘mild cognitive impairment’ OR ‘dementia’ OR ‘AD’ OR ‘MCI’) AND (‘Aerobic exercise’ OR ‘resistance exercise’ OR ‘dual-task training’ OR ‘cognitive-motor training’ OR ‘motor-motor training’ OR ‘strength training’ OR ‘physical training’ OR ‘cardiovascular exercise’ OR ‘Yoga’ OR ‘mind-body exercise’ OR ‘multicomponent exercise’ OR ‘Taichi’ OR ‘Baduanjin’) AND (‘executive function’ OR ‘cognitive function’ OR ‘cognitive abilities’ OR ‘working memory’ OR ‘inhibition’ OR ‘attention’). Furthermore, references from existing systematic reviews and meta-analyses, along with the studies included in these reviews, were examined to identify further relevant studies. Study inclusion and exclusion criteria Initially, 15,087 articles were retrieved from three databases and managed using the reference management software Covidence (Melbourne, Australia). After excluding 2,283 duplicates, 12,398 articles underwent screening based on titles and abstracts, resulting in 406 full-text articles. Following a detailed assessment, 371 articles were excluded, leaving 35 for inclusion in the systematic review and meta-analysis. Each article was independently evaluated by two researchers at each stage, with any disagreements resolved by discussion and consensus. The final list of included studies was approved by all authors, adhering to the following inclusion criteria: The study included older adults with Alzheimer’s disease and MCI; Interventions consisted of any organized exercise form (aerobic, resistance, dual-tasking, mind-body training), either acutely (single-session to < 8 weeks) or chronically (> 8 weeks); Studies employed a randomized control design, with the control group performing routine programs such as usual-care treatments, simple motion exercises, or stretching at low-intensity; Primary outcome measures were standardized cognitive neuropsychology assessment tests, such as but not limited to, the Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), Alzheimer’s Disease Assessment Scale–Cognitive Subscale (ADAS-Cog), or dual-tasking performance. Articles had to be written in English and published as full-text in peer-reviewed journals. Figure 1 depicts the study inclusion process, highlighting how studies were excluded based on irrelevant titles or abstracts failing to meet the inclusion criteria. When titles or abstracts were unclear, the complete article was subjected to review. The final selection of literature for discussion in the full text received unanimous approval from all authors. For additional details on the included studies, refer to Supplementary (S1). Identifying exercise parameters The primary objective of this study is to assess the impact of exercise parameters on executive function in older adults with MCI or dementia. For subgroup analyses in the meta-analysis, the exercise parameters examined included exercise type, intensity, and duration. The definitions for each exercise parameter were derived from the guidelines provided by the American College of Sports Medicine (ACSM), essential for classifying and specifying the type, intensity, and duration of exercise in each study. For instance, exercise types were categorized according to their primary movements and intended goals, as outlined below: Aerobic exercises: These involve continuous and sustained activity over a period of time that targets cardiovascular function including, but not limited to walking, jogging, cycling, or swimming. Resistance exercises: These focus on muscle strengthening and require pushing or pulling against a resistance provided by either a machine, free weight, resistance band, or bodyweight. Mind-body exercises: These emphasize the connection between meditation or mindfulness and physical movement, including Tai Chi, Qi Gong, Baduanjin, and Yoga. Dual-tasking exercises: These involve performing two different tasks simultaneously, such as combining a motor task with a cognitive task or performing two motor tasks together. Multicomponent exercises: These consist of performing two different types of exercises sequentially, either within a single session or across sessions. This could include combining aerobic exercises with resistance exercises or other forms of exercise. Exercise intensity evaluation utilized a combination of objective, subjective, and descriptive measures, detailed as follows: Low: Exercise that did not noticeably increase breathing rate and had a low energy requirement (< 3 METs, < 55% HRmax, < 40% HRR, < 40% VO2max, PRE(C) < 10, PRE(C-R) ≤ 2) (METs: metabolic equivalents; HRmax: heart rate maximum; HRR: heart rate recovery; VO2max: maximum oxygen consumption; Borg’s RPE scales C = category scale [6–20] and C-R = category-ratio scale [0–10]). Moderate: Exercises that could be performed while maintaining an uninterrupted conversation and typically lasted between 30 and 60 min (3–6 METs, 55–70% HRmax, 40–60% HRR, 40–60% VO2max, PRE(C): 11–13, PRE(C-R): 3–4). High: Exercises that made it difficult to maintain an uninterrupted conversation and usually lasted less than 30 min (≥ 6 METs, ≥ 70% HRmax, ≥ 60% HRR, ≥ 60% VO2max, PRE(C) ≥ 14, PRE(C-R) ≥ 5). Lastly, exercise duration was the product of the number of exercise sessions per week, the duration of each exercise session, and the total number of weeks. For example, an exercise program that includes 3 sessions per week for 18 weeks, with each session lasting 30 min, would have a total duration of 1620 min (30 min/session × 2 sessions/week × 8 weeks). Methodological quality and bias assessment Two reviewers evaluated the methodological quality of all studies using the Physiotherapy Evidence Database (PEDro) rating scale, which scores from 1 to 11. This scale assesses studies across five domains: group allocation, blinding, attrition, statistical analysis, and data variability. Ratings were assigned as “Yes” for supervised studies and “No” for items that were not applicable. Any discrepancies in ratings were resolved by a third reviewer. Methodological quality was categorized as Low (< 5), Good (6–8), and Excellent (9–10). Data extraction All retrieved titles and abstracts were imported into the reference management software, Covidence (Melbourne, Australia). After duplicate removal, two researchers independently screened the study titles and abstracts to identify studies potentially relevant for full-text retrieval. The full texts of relevant studies were independently reviewed by two researchers, who also examined potentially relevant articles in the reference lists. Two researchers extracted study characteristics, including first author, country, year of publication, population, design, number of participants, details of intervention and control groups (type, intensity, duration), and outcome measures for motor and cognitive functioning. Discrepancies in study selection or data extraction were resolved through discussions with a third researcher, and authors were contacted for additional information as necessary. Extracted data included domain-specific cognitions, categorized by researchers, encompassing pre- and post-intervention stimuli and quantitative data for the control (sham) condition, derived from text, tables, and graphs in each included study. Statistical analyses Random effects meta-analyses were conducted to account for systematic influences and random errors between study-level effect sizes; results were displayed in forest plots showing averaged standardized mean differences (SMDs) and 95% confidence intervals (95%CI). Positive SMD values signified that the intervention group outperformed the control group in cognitive tests for the outcome variables. Separate meta-analyses on executive function outcome measures were carried out to investigate the impact of exercise on different outcomes. Subgroup meta-analyses were conducted to explore the relationship between exercise type and intensity and SMDs, as agreed upon a-priori to assess the influence of exercise parameters on executive functioning. The exercise parameters considered for subgroup analyses included: Exercise type – Aerobic vs. resistance vs. mind-body vs. dual-task vs. multicomponent exercises; Exercise intensity – Low vs. moderate vs. high. The I2 statistic was employed to assess statistical heterogeneity, with cut-off points corresponding to low (25%), moderate (50%), and high (75%) heterogeneity. Funnel plots were used to evaluate publication bias via Egger’s regression test, where non-significant asymmetry suggested no bias. Additionally, a meta-regression was performed to explore the effects of exercise duration on cognitive function, to determine whether exercise duration could predict the SMD of each study. All statistical analyses were performed using Comprehensive Meta-Analysis (V3.0, Biostat, Englewood, USA), with an alpha level of P < 0.05 to determine significance | [
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37546488 | methods | Methods This systematic review aimed to identify studies of MCI-related gaze behavior impairments published in the past 6 years (2017–2022). The protocol was drafted based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Electronic databases (Edith Cowan University Library, PubMed, Semantic Scholar, and Springer) were systematically searched to identify peer-reviewed literature that examined visual processing among older adults, as well as studies comparing cognitively unimpaired individuals to elderly individuals with MCI. Studies were found using a combination of the following terms: “mild cognitive impairment” or “MCI” AND “diagnosis” or “screening” AND “biomarker.” Notably, the search term “eye-tracking” or “eye movements” were added to narrow the result to journal articles that reported gaze parameters as potential biomarkers for MCI. The search results (.csv file) obtained from each database were consolidated and saved as a single Microsoft Excel spreadsheet (.xls file). The spreadsheet was meticulously scrutinized for duplications through a manual inspection, which was carried out separately by AW and KT. Any disagreement was resolved by discussion and consensus. Certainly, following the preferred reporting items for PRISMA systematic review guidelines, specific inclusion criteria were applied. To be included in this review, studies had to be relevant, original, peer-reviewed, and written in English. Furthermore, the studies had to include an MCI group (without comorbidities or other neurological disorders), which had to be evaluated by standardized diagnostic criteria and diagnosed with validated cognitive tests. Conference papers, letters, books, single case studies with a small sample (i.e., studies with less than 10 participants in the MCI and/or control group), and non-primary literature such as systematic reviews, meta-analyses, and editorials were excluded. The PRISMA flow diagram, depicted in Figure 2, was generated using a web-based and free-to-use Shiny app, which allows users to create customized PRISMA flow diagrams for their systematic reviews. Out of the one-hundred fifty-three initially identified records (n = 153), a total of eleven duplicates were detected and consequently eliminated prior to the screening process. Furthermore, among the identified records, eighteen (n = 18) entries were excluded for varying reasons, including the classification of eighteen positions as conference proceedings and/or abstract book titles, while one entry (n = 1) lacked an available abstract. Next, the screening process involved reviewing the titles and abstracts of one-hundred twenty-three (n = 123) records. Out of these, fifty-five studies were deemed irrelevant to mild cognitive impairment (MCI) or focused on different clinical conditions, such as Autism Spectrum disorder, Parkinson’s, schizophrenia, neurodevelopmental disorder or eating disorder. Additionally, four in-scope systematic reviews, two book chapters, and one study identified as a conference abstract, were rejected. Furthermore, the exclusion of forty-eight studies that examined various approaches for dementia screening was justified since these reports did not incorporate the use of eye-tracking technology. Also, one study focusing on the efficacy of a drug in enhancing visuospatial abilities among MCI patients through eye-tracking measurements was excluded. As a result, a total of one hundred and eleven records were excluded from the analysis due to their failure to meet the predetermined inclusion criteria. Next, a comprehensive search was undertaken to obtain twelve specific reports in the form of full-text papers. Out of the desired reports, eleven were successfully retrieved and checked for eligibility. Among the eleven reports, three were excluded (refer to the PRISMA flow diagram in Figure 2 for detailed reasons), resulting in the inclusion of eight reports. Notably, to supplement the identification of relevant studies, the reference lists of eight in-scope and full-text articles were independently screened by AW and KT for relevant publications. This practice, which is recommended in systematic review manuals, served as an effective approach. In result, fourteen relevant studies for the systematic review have been identified. Eleven positions have been successfully retrieved as full-text documents for assessment of eligibility. After a detailed examination of the gathered works, one study was excluded due to the limited sample size in the MCI group (n < 10). Overall, the search of the reference lists has resulted in the addition of ten new studies. In essence, this work presents a comprehensive review of the included studies, providing a thorough examination of the evidence on whether gaze metrics from eye-movement paradigms can distinguish between older adults with MCI, including those with the highest conversion rate to AD (aMCI subtype), and their age-matched counterparts. To combine the rising trend of eye-tracking technology with the challenges of AD diagnosis, the significant constraints of the currently used “ruling out” protocol have been elucidated. The research synthesis follows with an introduction of the human retina, capable of mirroring brain structure and revealing cognitive disturbances through human eye movements. Notably, the authors outline the fundamental point of gaze behavior as a reflection of one’s attention and thought processes. A straightforward follow-up statement is presented on why eye-tracking should be considered an attractive technology for facilitating a non-invasive diagnosis of MCI by providing meaningful and objective outcome measures. Notably, this work highlights eye movement tests that provide information about saccadic and exploratory impairments among the elderly population with MCI. Furthermore, specific eye-movement parameters, which show potential in distinguishing between patients with MCI and cognitively unimpaired elderly, have been identified. | [
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36965096 | title | Brain health registry updates: An online longitudinal neuroscience platform | []
|
36593415 | abstract | Generation of stable gene-edited plant lines using clustered regularly interspaced short palindromic repeats (CRISPR)-CRISPR-associated protein 9 (Cas9) requires a lengthy process of outcrossing to eliminate CRISPR-Cas9-associated sequences and produce transgene-free lines. We have addressed this issue by designing fusions of Cas9 and guide RNA transcripts to tRNA-like sequence motifs that move RNAs from transgenic rootstocks to grafted wild-type shoots (scions) and achieve heritable gene editing, as demonstrated in wild-type Arabidopsis thaliana and Brassica rapa. The graft-mobile gene editing system enables the production of transgene-free offspring in one generation without the need for transgene elimination, culture recovery and selection, or use of viral editing vectors. We anticipate that using graft-mobile editing systems for transgene-free plant production may be applied to a wide range of breeding programs and crop plants. | [
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38213645 | intro | Introduction The COVID-19 pandemic caused by the coronavirus named SARS-CoV-2 has significantly affected the economy and the business model (e.g., supply chain, consumer demands, sales and marketing) of almost all countries and territories. In fact, the COVID-19 pandemic has tremendously challenged organizations and companies around the globe and caused important changes related to the management of employees especially in industrialized countries. Drastic changes were implemented to respect government recommendations such as social distancing in the workplace with the objective of reducing the infection rate. Such recommendations forced organizations and companies worldwide to rapidly implement teleworking regardless of their past experiences and work environment. Teleworking consists of an alternative arrangement allowing employees to work outside of the employer’s premises with the support of information and communication technologies (ICTs) such as laptops, smartphones, and tablets. Traditionally, teleworking allows individuals to work either at home or at other offices and shared facilities. However, since the beginning of the COVID-19 pandemic, the term telework has been more often used to define home-based telework. A survey conducted in 2020 in the United States reported that in 50% of the companies, more than 80% of human resources employees were working from home during the early stage of the COVID-19 pandemic. In Canada, the prevalence of home-based telework from all working domains has drastically increased from 5% in 2018 to almost 45% in April 2020. In early 2021, while work restrictions related to the COVID-19 were eased off, teleworkers still accounted for one third of all workers. Now that teleworking is well implemented in several working environments, it seems relevant to investigate health-related conditions that are often reported by teleworkers. Knowing that primary headaches such as migraine and tension-type headache (TTH) are considered one of the leading causes of disability in the general population, especially among people under 50 years of age, it is important to investigate if teleworkers present a similar headache-clinical profile to headache sufferers in the general population and how headache-related clinical features could be influenced by a stressful situation such as a pandemic. In the general population, the prevalence of migraine and TTH are, respectively, 11 and 42%. In a recent study, a large proportion of teleworkers (61%) reported having at least one headache episode during a typical work week. It is important to point out that primary headache profiles are influenced by non-modifiable and modifiable factors. Non-modifiable risk factors include age and sex, while modifiable risk factors include physical factors such as BMI and psychological factors such as stress, anxiety and medication overuse. Thus, headache self-management during a new stressful situation such as the COVID-19 pandemic which has been identified as a collective trauma could represent an important challenge for teleworkers living with primary headaches. When facing a stressful event or situation such as a pandemic, a large range of coping strategies can be used to improve people’s quality of life. Coping strategies involve a dynamic process that consists of a series of actions or responses based on how the individual and the environment interact together as well as how they influence each other. In addition, these actions or responses include cognitive, emotional, behavioral and physiological domains. People can use more than one coping strategy when attempting to decrease the physical, emotional and psychological burdens associated with stressful life situations such as a pandemic. One important thing is that when considering situational coping strategies, actions (what a person did) or responses (how a person will react) are related to a specific situation (episode or period of time). Situational coping strategies can be dichotomised in different ways. Some authors divide coping strategies into problem-focused (efforts to control or change a specific stressor) and emotion-focused (efforts to manage the emotional response to a specific stressor) while others divide situational coping strategies into positive coping strategies (e.g., seeking social support and humor) or maladaptive coping strategies (e.g., alcohol consumption and self-blame). Maladaptive coping strategies have been recognized to immediately reduce the stress associated with a particular condition, but are also known to have negative long-term consequences on quality of life. In headache populations, problem-focused coping strategies have been found to be effective in the management of headache-related clinical features as well as in the management of the stressful situation itself. In fact, people using problem-focused strategies are more likely to find solutions to manage their condition. Previous studies showed that both positive and maladaptive coping strategies were used by people when facing an infectious disease outbreak. Knowing that maladaptive coping strategies are associated with pain in many health-related conditions including headache and that a large proportion of teleworkers previously reported having headache episodes, it is important to address the impact of coping strategies on headache-related clinical features. The COVID-19 pandemic represents a unique multifaceted “stress circumstance” offering a distinctive opportunity to study coping strategies in teleworkers with primary headaches. The first aim of this study was to describe and compare the clinical features of migraine and TTH episodes in teleworkers in the context of the COVID-19 pandemic. The second aim was to determine the association between coping strategies and headache frequency, and intensity in teleworkers with migraine or TTH in the context of the COVID-19 pandemic. We hypothesized that headache-related clinical features in teleworkers would be similar to what is found in the general population, meaning that teleworkers with migraine would report higher headache intensity and headache-related limitations than teleworkers with TTH while headache frequency would be lower in teleworkers with migraine than in those with TTH. We also hypothesized that maladaptive coping strategies would be associated with higher headache frequency, intensity, and limitations in both headache types. | [
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37768921 | methods | Materials and methods Drosophila stock and culture D. melanogaster flies from the Canton S and w1118 (Stock #3605) strains were obtained from the Bloomington Stock Center, Indianapolis, IN. The group also used the GMR-GAL4 > UAS-Eiger stock kindly provided to our laboratory by Dr. Masayuki Miura of the University of Tokyo (Tokyo, Japan). Animals were reared on a standard cornmeal medium, and the tests were performed on a mashed potato medium containing 75% powdered mashed potato (Yoki®), 15% yeast extract, 9.3% glucose and 0.7% nipagin. The flies were maintained in a BOD incubator at a controlled temperature of 25°C with a 12h/12h light/dark cycle. Flies were anesthetized with cold or ethyl ether for sex determination and mating. Groups of 30 male adult w1118 flies (0 to 3 days post-emergence) were used for all of the following tests, except for the toxicity evaluation where groups of 15 male and 15 female adult w1118 flies (0 to 3 days post-emergence) were used. Each test lasted for 15 days, since the group aimed at a chronic treatment with the essential oils. All experiments were performed on three independent triplicates. Essential oils and solutions preparation Essential oils of copaiba (Copaifera sp.), ginger (Zingiber officinale), and lavender (Lavandula angustifolia) (döTerra, Utah, USA) were used, diluted with water to different concentrations for each assay and treatment (0.0625% v/v, 0.125% v/v, 0.25% v/v, and 0.5% v/v), with the solution being thoroughly mixed by vortexing for 10 seconds to disperse the oil in the water each time it was pipetted. Both EOs and their dilutions were stored at room temperature and protected from light to prevent degradation. Chromatography charts of the EOs provided by döTerra can be found in the Supporting Information (S1–S3 Datasets). Toxicity evaluation of the essential oils The first step, prior to treating the flies, was to determine the toxicity of each of the oils at different concentrations. Each essential oil was tested at concentrations of 0.0625% v/v, 0.125% v/v, 0.25% v/v, and 0.5% v/v. Groups of 30 adult w1118 flies (0 to 3 days post-emergence) were separated into vials for each treatment in triplicate, with a 1:1 ratio of males to females. Each vial contained mashed potato medium prepared with 5 mL of water (control group) or 5 mL of the EOs solutions. Flies were fed on the food prepared with these solutions for 15 days and transferred to vials containing fresh food every 2 to 3 days. The number of dead flies was counted each time they were transferred to a new vial. Lifespan analysis To understand how consumption of the EOs would alter the lifespan of the flies, a lifespan assay was performed. Male flies of the w1118 stock (0-to-1-day post-emergence) were separated into groups of 30 and fed on mashed potato medium prepared with the solutions at 0.0625% v/v for the copaiba and ginger EOs and 0.125% v/v for the lavender EO. Similar to the toxicity evaluation, the flies were maintained on vials containing mashed potato medium prepared with 5 mL of water (control group) and 5 mL of the EOs solutions. Flies were transferred to vials containing fresh food every 2 to 3 days, and the number of dead flies was counted at each transfer until all flies had died. Climbing assay The Rapid Iterative Negative Geotaxis (RING) test was used to determine whether the essential oils diet would cause any changes in the locomotor ability and behavior of the flies, performed as described by Gargano et. al in 2005. The only modification is that the digital image used to evaluate the position of the flies on the vials was taken 10 seconds after the apparatus was tapped on the surface. This is due to the strain of flies used, w1118, which has a natural retinal degeneration that makes their climbing slower than other strains. To understand how the animal model used would respond to an essential oil diet, the group performed the RING test using two sets of EO concentrations: lower doses that showed no toxicity in the toxicity test and higher doses that caused a greater number of deaths in the toxicity test. For the first, the concentrations used were 0.0625% v/v for the copaiba and ginger EOs and 0.125% v/v for the lavender EO. For the higher dose test, the concentrations used were 0.25% v/v for each essential oil. The flies were fed on mashed potato medium prepared with the EO solutions at the above concentrations for 15 days, with the RING test performed every 5 days. Histological analysis Knowing that the essential oils have small molecules that can cross the blood-brain barrier, the group decided to analyze whether ingesting the EOs could cause any damage to the flies’ brains. Again, we decided to test both higher and lower doses of the essential oils to understand how the D. melanogaster model would respond to different concentrations of EOs. Males from the w1118 strain were collected from 0 to 1-day post-emergence and divided into groups of 10 flies in triplicates and fed on mashed potato medium prepared with the solutions of EOs. The animals were kept on this diet for 15 days, euthanized with liquid nitrogen and decapitated for preparation of brain tissue slides. The tissues were fixed in paraffin and stained with hematoxylin and eosin for better visualization, following the protocol used by Malta et. al 2022. The concentrations used were 0.25% v/v for each essential oil for higher doses and 0.0625% v/v for the copaiba and ginger essential oils and 0.125% v/v for the lavender essential oil for the lower doses. Analysis of the anti-inflammatory properties of the essential oils Each of the essential oils used in this project has an anti-inflammatory activity already seen in both in vitro and in vivo tests. However, the most commonly used animal models are mice and rats. To analyze whether the D. melanogaster model would also respond to treatment with essential oils by ingestion, we used GMR-GAL4 > UAS Eiger flies as a model of inflammation in which eye degeneration is caused by overexpression of Eiger, a Drosophila ortholog of tumor necrosis factor alpha, in the organ. Assays in these animals are performed on larvae rather than adults because inflammation begins as soon as the animal hatches from the egg. Flies of the GMR-GAL4 > UAS-Eiger strain were mated for 24 hours in oviposition medium. After this time, the parental flies were removed from the flask and the eggs were collected. These eggs were then placed in vials containing mashed potato medium prepared with solutions of the EOs at 0.025% v/v each. The animals were maintained on this medium for 10 days until the adult flies emerged from the pupae. The animals were then anesthetized with ice, and 60 flies from each group were collected for measurement of eye area using ImageJ software. The Canton S strain was used as a wild-type model for comparison of eye morphology. Statistical analysis All statistical tests were performed using GraphPad Prism 8 software. The Mantel-Cox test was used to evaluate the statistical significance of the data for toxicity evaluation and lifespan analysis. Two-way ANOVA test was used for the climbing assay. One-way ANOVA test was used to analyze the anti-inflammatory properties of the essential oils. All values of p < 0.05 were considered significant. | [
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37015625 | methods | Methods Kernel CCA To compute similarity between subjects, we utilize ideas from canonical correlation analysis (CCA). Conventional CCA seeks to find relationships between the features of two different views of a dataset. It aligns the two views, and , by finding canonical variables and that maximize the correlation between and : where is the number of subjects and is the feature dimension. Kernel CCA (kCCA) transforms features into a reproducing kernel Hilbert space (RKHS), and finds the alignment between the transformed features and . The similarity in the RKHS is , where is the feature transformation. LatSim learns a linear kernel ; however, this still allows detection of nonlinear relationships. The main idea behind CCA and kCCA is to maximize the similarity between two or more signals after some constrained transformation. This constrained transformation moves the data to a latent space, which may be of lower dimension. The limitation of CCA and kCCA is that they are unsupervised learning techniques that must account for every similarity between the signals, not just those relevant for a particular application, although recent work is tackling this problem. Latent similarity In contrast to unsupervised learning, LatSim maximizes similarity of subjects based on distances between a response variable of interest, like age or sex. Similarities are first computed as the inner product of the low-dimensional projections of subject features, based on a learned kernel function: where is the kernel matrix, and , are feature vectors for subjects and , respectively. These similarities are then adjusted by passing them through a softmax activation function while masking each subject’s self-similarity. The entire model for a single predictive task and a single fMRI paradigm is as follows: where is the final similarity matrix, is a mask to remove self-loops in predictions, is a vector of infinite-valued elements, is a matrix of ones, is the feature matrix, is the kernel taking connectivity features to a lower latent dimension, is the number of subjects, is the number of features (FCs), is the softmax function with temperature , and is a function applying softmax to each row of the input matrix. High or low temperature determines whether the subject-subject similarity matrix is more dense or sparse, respectively. The final similarity matrix of training and test set subjects is multiplied by the training set response variable to yield the prediction: In the conventional image domain, Zheng et al. have proposed a similar metric learning approach using softmax aggregation for image classification. However, their work makes use of a pre-trained backbone, is semi-supervised, and does not provide all of the possibilities for feature selection, disentanglement, and alignment as does LatSim (see Equation 5). The model is trained, using gradient descent, by minimizing the following objective function. Here we assume for brevity the existence of two fMRI design matrices and , and two predictive tasks, one regression (1) and one classification (2), for which we identify four kernel matrices , , and : where , for example, is the similarity matrix for task 1 and fMRI paradigm , (numeric) and (one-hot categorical) are the stacked response variables for tasks 1 and 2, respectively, is the number of subjects, is the number of classes in task 2, is a task importance weight, is a sparsity-inducing hyperparameter, is a hyperparameter promoting feature disentanglement, and is a hyperparameter promoting alignment between fMRI paradigms. Note that our experiments on the PNC dataset in Section III-B.1 used precomputed vectorized functional connectivity matrices as the input, e.g., is a matrix where each row is the vectorized FC of one subject. Greedy selection algorithm and model interpretability A greedy selection algorithm was developed to compare with other interpretability methods. The algorithm selects connections one at a time by ranking their ability to separate dissimilar subjects, i.e., their ability to minimize similarity between subjects that are “far apart” with regards to the current residual: where LatSim : is the predictive model, is the residual at iteration for subject , is a centered matrix of differences between residuals, is the set of selected connections at iteration , is the vectorized FC matrix for all subjects, and is the response variable. A summary of the algorithm is presented in Figure 2. We describe feature selection results in Section III-B.3. The greedy algorithm can select the several dozen most relevant features given a single predictive task. To select discriminative features using the fully trained model, we find the correlation between subject similarities and residual distances, as in Equation 6 above, except the FCs are multiplied by the learned model weights: where the residual is set to the response variable, is calculated as before, is the set of model weights, and is the resulting set of ranked features. Except for greedy feature selection, we optimized prediction of all three response variables (age, sex, and intelligence) at the same time in the same LatSim model. Greedy selection required optimizing a single task at once, as the best feature for age prediction may not be the best feature for sex or intelligence prediction. LatSim was trained using PyTorch on an NVIDIA Titan Xp with CUDA support. Spurious correlation We hypothesize that overfitting occurs due to feature noise or confounds, such as scanner motion, whose effects are more severe for smaller size cohorts. These confounds may create spurious correlations in a subset of the cohort. We define a spuriously correlated feature to be one that appears to be highly correlated with response variable for only a subset of subjects: where is the value of the spurious correlation, is the study cohort, and is a subset of the cohort such that is maximized. Note that spurious correlation may actually be true correlation identifying subgroups, but we hypothesize that a spurious correlation is more likely to be false as decreases. We conduct simulation experiments in Section III-A that suggest LatSim is more robust against spurious correlation than traditional feature-based models. When is close to , and the effect is systematic, we cannot tell whether the correlation is true or false. | [
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38564426 | methods | Materials and methods Sets of biomedical terms For the HPO, we took all the terms that have ‘phenotypic abnormality’ (HP:0000118) as an ancestor in the HPO hierarchy, in order to avoid terms not related to phenotypes or clinical signs, ending up in a final list of 16 218 terms From the DOID disease ontology, we retrieved 10 949 terms representing different diseases. From MONDO, we tried to exclude terms representing symptoms as these are already covered by HPO (see earlier). For that, we excluded the MONDO terms with equivalent HPO terms annotated, ending up in a final list of 21 926 terms. From GO, we retrieved the terms from the three sub-ontologies (‘molecular function’, ‘biological process’ and ‘CC’) associated with at least one human gene in the Gene Ontology Annotations resource, in an attempt to restrict to GO terms relevant to human, obtaining a final list of 18 892 terms. For the CL ontology, we took all CL:* terms, which are used for representing different human cell types (2532 terms). For the UBERON ontology, we took all UBERON:* terms, representing different tissues and body parts (14 273 terms). From the ‘C’ and ‘D’ subsets of the MeSH vocabulary, we retrieved the terms under the B03 category (‘bacteria’) of the hierarchy, as well as those associated with the semantic type T007 (‘bacterium’), in an attempt to get those terms of the MeSH generic vocabulary representing microorganisms. We imposed the additional constraint that the terms must be linked to National Center for Biotechnology Information (NCBI) Taxonomy IDs, ending up in a final list of 19 194 terms. From MeSH, we also retrieved the terms representing chemical compounds, as those under different ‘semantic types’ indicative of that, such as T109, T116 and T121, among others (2915 terms). Finally, from HMDB, we retrieve all entries (205 011), representing chemical compounds associated with human in different ways (metabolites, drugs, toxic compounds, etc.). Nevertheless, contrary to the other datasets, most of these chemical compounds are never mentioned in PubMed according to the searches we perform (see later), and hence our final list (HMDB compounds mentioned in PubMed) contains 24 880 terms. For all these datasets, we retrieved the terms’ names and synonyms annotated in the corresponding fields of the resources. For HMDB terms (chemical compounds), we excluded from their list of synonyms those associated with more than one compound. This is because some generic names are annotated as ‘synonyms’ in that resource, so that including them in the searches would retrieve not only the articles mentioning the specific term but also all those referring to the generic term. Detecting literature co-mentions The process for detecting significant co-mentions in the scientific literature is described in detail in. In short, for each term, we search PubMed for its textual description (including synonyms combined with ‘OR’) using NCBI’s Entrez application programming interface, obtaining in this way the list of abstracts [given in terms of PubMed identifiers (PMIDs)] mentioning that term. As performing searches for two terms together (combined with ‘AND’) would be unfeasible for all pairs, we take the intersection between each term’s list of PMIDs as the set of articles mentioning the two together. For a given pair of terms, from the frequencies of articles mentioning each of them and those mentioning the two together, also taking into account the whole size of PubMed (∼36 million), we apply a hypergeometric test to obtain the P-value of the null hypothesis that the co-mention of both terms occurs by chance, as well as other figures indicative of the strength of the co-mention. For two terms mentioned individually in n1 and n2 abstracts, respectively, and co-mentioned together in b abstracts within the whole PubMed corpus (P abstracts), that P-value would be calculated as We also calculate a score of ‘string similarity’ between the textual descriptions of both terms (including their synonyms) as terms with identical or very similar descriptions (such as the same concept represented in different ontologies) lead to trivial co-mentions that should be eventually discarded. All the data retrieval and the bibliographic searches were performed between April and October 2022. Web interface A web interface was developed where the user can search for one or more terms of interest in any of the nine categories and retrieve the associated terms in the others. This webserver was developed with HTML and CSS and uses JavaScript and PHP for the active parts. For the sorting table functionality, a modified version of the open-source sorttable.js package was used (https://www.kryogenix.org/code/browser/sorttable/). The interface was tested in all major web browsers and operative systems. | [
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38481598 | methods | Methods Following the guidelines in the Cochrane Handbook for Systematic Reviews of Interventions, we conducted this systematic review and meta-analysis. PRISMA (Preferred Reporting Items for Systematic Review and Meta-Analysis) guidelines were followed. Eligibility Criteria Included original research met the following inclusion criteria: (1) RCT design (RCTs were included to reach a high-grade level of evidence); (2) Participants were over the age of 18 with diabetes; (3) A CBT-based intervention was performed; (4) Studies compared CBT-based intervention with usual care, waitlist control, health education; (5) Studies reported at least one outcome of sleep-related outcomes. Studies were excluded if (1) published articles are written not in English or Chinese; (2) CBT was not the primary intervention but only a component of a multimodal intervention; or were (3) conference papers, abstracts, book chapter reviews, letters and reviews. Literature Search Strategy Two reviewers searched six English databases (PubMed, EMBASE, Cochrane library, Web of Science, PsycINFO, CINAHL), and two Chinese databases (CNKI and WanFang) to identify relevant studies. We identified relevant RCTs from the databases from inceptions to 1st November 2023, and updated on 15 January 2024. Additionally, we conducted a thorough screening of the reference lists of included studies and reviewed the references from other relevant systematic reviews to identify potentially eligible RCTs. The search strategies employed a combination of Medical Subject Heading terms and keywords, with the following constructs: Diabetes, Cognitive Behavioral Therapy, Sleep, and Randomized Controlled Trials. The whole search strategy is provided in Appendix 1. Study Selection EndNote X9 Software was used to remove duplicate articles from search results. Two independent reviewers (H.J.W. and R.Z.L.) assessed all records for eligibility based on the titles and abstracts of studies during the first level screen. Disagreements about whether to include a paper were resolved through discussion. The second level screen was performed by two reviewers (H.J.W. and R.Z.L.) who independently assessed the full text of all relevant and potentially relevant articles to identify whether they met inclusion criteria. We removed articles for non-eligibility reasons, with detailed documentation. A third reviewer (S.Y.T.) was consulted to resolve disagreements between the two reviewers. Data Collection Process and Data Extraction The extraction of data was guided by an Excel template adapted from the Cochrane data extraction form. Two independent reviewers (H.J.W. and L.G.) extracted data independently, in order to minimize bias and prevent errors during data extraction. We extracted data from each included study, including author, publication year, study design, country, essential characteristics of participants (sample size, age, and distribution of groups), detail information about intervention (eg, type, duration, frequency, number of sessions, characteristics of interventionists, and setting), controls, outcomes (outcome indicators, measuring tools of the studies, follow-up time, attrition rate), adverse events and intention-to-treat analysis. When subjective and objective outcomes were reported in a study, we priority extracted objective outcomes for our review. For those reporting the same research in multiple articles, we will combine them into one research to summarize the intervention characteristics and data extraction. The discussion resolved the disagreement between the two reviewers regarding data extraction. Similarly, a third reviewer (M.S.) was consulted when no consensus was reached. The κ scores were calculated to estimate interrater reliability between reviewers, resulting in a good score of κ= 0.75. We contacted the original authors included in the study by email when the required data could not be extracted, or information was missing (up to three attempts). Quality Assessment Using the Cochrane Collaboration’s “risk of bias” tool for systematic reviews of interventions, two reviewers independently assessed the included studies (H.J.W. and R.Z.L.). There were seven items in this quality assessment tool to assess the potential for bias in trials: (1) Random sequence generation (how participants will be assigned to interventions is generated based on a process that includes an element of chance); (2) Allocation concealment (to prevent participants or trial personnel from knowing the forthcoming allocations until after recruitment has been confirmed); (3) Blinding of participants and personnel (to prevent participants or trial personnel from knowing the intervention contents); (4) Blinding of outcome assessment (to prevent the assessor from knowing the intervention details); (5) Incomplete outcome data (describe the integrity of outcome data for each primary outcome measure); (6) Selective reporting (the reported result is selected based on its direction, magnitude, or statistical significance); (7) Other bias (whether a pre-specified plan analyzed the trial). Each item was categorized as “low risk”, “unclear”, or “high risk” for bias. Each study was assessed for quality through a consensus between two reviewers or consultation with a third independent reviewer (M.S.). Data Analysis RevMan V.5.3 software was used to perform the meta-analysis. We performed a meta-analysis only when two or more intervention studies were available with similar participants and outcomes. When studies reported data at multiple follow-up timepoints, the post-intervention data was chosen for pooling to align with the other studies. All significance testing was 2-sided, and results were considered statistically significant if the P value was.05 or less. If heterogeneity is significant, random-effects models are used; otherwise, fixed-effects models are used. We quantified heterogeneity using I2 statistics. I2 < 25% indicates a low degree of heterogeneity, I2= 25–75% indicates moderate heterogeneity, and I2 >75% indicates a high degree of heterogeneity. A sensitivity analysis was conducted by removing one by one studies that had significantly contributed to the heterogeneity level when significant heterogeneity was detected. Additionally, a subgroup analysis was conducted to compare the effect of CBT-based interventions on sleep quality with different dosages and detect the source of heterogeneity. According to the recommendation in the Cochrane Handbook, Cohen’s criteria for effect size means that SMD = 0.20, 0.2 to 0.5, and more than 0.5 were considered to represent small, medium, and large effects, respectively. A narrative synthesis of the study findings was reported when included studies did not provide extractable outcome information (eg, means and SD) and studies for those only reported one outcome could not conduct meta-analysis. | [
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39188236 | results | Results Characteristics of the study participants In total, 22 individuals aged 65 years or older, with an average age of 75 years, living with HIV participated. Not all participants answered every question about demographics. We included a mixture of people, and overall, there was a geographic spread across Sweden, from the north to the south, both from urban and rural areas as well as with diverse sexual orientations and educational backgrounds. Of the participants 14 identified themselves as men and 8 as women. They had varying experiences in healthcare and life situations. The number of years lived with HIV varied from two years to over 30 years. All participants were on HIV treatment and represented more than ten different HIV-clinics. Of the 22 participants, six were born in another country than Sweden. None of the participants were coupled together. It was common to live alone for multiple reasons, such as being divorced or widowed. Not all participants wanted to disclose how they contracted HIV or their sexual orientation. In summary, there were variations among participants linked to age, gender identity, sexual identity, family situation, route of transmission, years lived with HIV, place of residence, migration experience, and socioeconomic status. When asked about the needs for elderly- or home-care services, no participants expressed this need. Themes describing the experiences of being an older adult living with HIV Overall, the results revealed that being an older adult living with HIV was experienced as multifaceted. The intersection of age and HIV brought numerous layers to life, revealing multiple dimensions of experiences. HIV occupied different spaces in individuals’ lives and affected everyday life to varying degrees, ranging from minimal to substantial. For older adults living with HIV, the prominence of ageing and being older commonly overshadowed the significance of HIV in their everyday lives. Living with HIV required navigation in daily life, such as medication management. There were specific moments when HIV served as a reminder, and it had both emotional and social impacts on them and their relationships with others. The results are further described in three themes: increasing age in the foreground, internalizing HIV in everyday life, and the socioemotional impact on daily life. Increasing age in the foreground I guess I will die from something completely different than HIV. (19) This theme describes the overarching influence of ageing and being old, where the prominence of ageing and being old was related to emotions and concerns that overshadowed the significance of HIV itself, placing HIV in the background of everyday life. The process of growing old was experienced as the primary lens through which individuals perceived and navigated their ordinary lives, diminishing the relative importance of an HIV diagnosis. For example, one participant described being old and living with HIV as an iceberg. In particular, where HIV represented the visible tip, and beneath the surface lay the entirety of a person’s life, full of experiences and aspects beyond HIV, such as other health issues. Thus, HIV was described as something that was not the focus of ageing. It is the most nice thing I have experienced… //Being human … Being old and having life skills … You have to relax and choose. I can do everything. I cannot become a brain surgeon, but I have no plans to do so. Otherwise, I can do whatever I want. The freedoms and privileges I have now. I have never had that before. (13) Ageing was experienced as something one could not escape and was seen as a natural part of life, not causing too much concern. Finding meaning in life was crucial to persons’ well-being. This was articulated as the ability to continue life projects, maintain and have a sense of control, and make decisions about one’s own life. This brought joy and optimism for the future, creating feelings of freedom and lust for living. Having experiences with former challenges in life could increase gratitude for ageing. What is important to me, you know, are my children. (12) Experiences of feeling needed or wanted by someone were significant in fulfilling life with meaning. This contributed to a higher quality of life and reduced feelings of loneliness. A sense of coherence and belonging were fostered through social relationships, whether with a pet, partner, family member, various organizations, relatives, or friends. Having few or strained relationships with family or friends could increase feelings of loneliness. For example, when migrating from another country and leaving loved ones like family and friends behind. One participant emphasized the importance of having close contact with children and grandchildren. That I should still be able to move freely and engage in the little exercise routine that I still maintain, that is important. (2) During ageing, striving for good health, encompassing physical and mental well-being, was essential. Efforts to maintain body shape and manage different kinds of activities, such as physical exercise, being out in nature, or travelling, were examples of activities enhancing overall health and quality of life: When you retire, it is important to have interests. Interests and to read and acquire interest. Otherwise, the time may feel very slow. (1) Socioeconomic stability was one expressed enabling factor for engaging in activities and maintaining independence. Additionally, continuing to work in various forms could foster a sense of being needed and provide positive mental and physical challenges. Autonomy and the ability to choose when to work could strengthen feelings of well-being. Being active and nurturing interests were also expressed as necessary. Sometimes you feel that getting old is not fun. //It feels like it is a journey toward death. (14) Ageing experiences included physical ailments that caused limitations in daily life. Signs of ageing were gradually emerging in various ways, affecting both body and mind. Imagining life without HIV was for some difficult, especially for individuals living with HIV for many years. It was known that HIV could cause specific health issues or amplify some physical symptoms of ageing. However, there was still uncertainty regarding how HIV and ageing were connected. Bodily changes in ageing could evoke feelings of melancholy and sorrow, even leading to depression and struggles in finding meaning in life. For some, ageing was intertwined with feelings of loneliness because of friends or family members who have passed away or having separated from their partners. Internalizing HIV in everyday life Internalizing HIV in everyday life entailed integrating living with it into various aspects of daily life. The experiences revealed a temporality in which past life experiences and life expectancies shaped the present moment. When HIV became internalized, there were moments when participants were reminded of its presence in their lives. Yes, because after the diagnosis, we had limitations, and then when the viral load or values had dropped, those limitations ceased. During this period, new solutions were obtained. Therefore, I can almost feel that we have at least a good sex life now, and almost better than when we were younger. (6) HIV was perceived as something that did not occupy a prominent space in daily life. Instead of focusing on the obstacles and challenges that HIV could present, it was considered essential to maintain a forward-looking and positive attitude about life and the future. Some experienced themselves as healthier and more energetic than those of the same age without HIV. For some participants, living with HIV had even brought meaning into their lives, and HIV-related challenges had made them grow as persons. There was a sense of “being able to prioritize what is important in life” (22). Intimate relationships and sexual life had improved for some. It is truly unbelievable that you can achieve this despite having such a serious condition. Its incredible that you can walk around here like anyone else, without any sign of it. (21) One crucial aspect that enabled the participants to internalize HIV was an undetectable viral load, which assured them that HIV was no longer transmittable. With an undetectable viral load, HIV was experienced as less prominent in life, and a low viral load guaranteed a healthy life without any risk of viral transmission. However, past experiences from the period of receiving an HIV diagnosis, a tangible life-changing period in life, still affected some of the participants. Various experiences were described, and different thoughts and emotions were associated with HIV acquisition. For some, receiving a diagnosis was a shock or a feeling like receiving a death sentence. Some had received the diagnosis at a late stage, despite having sought medical help multiple times triggered by HIV-related symptoms such as fever and weight loss, indicating that the immune system was affected. Others found it difficult to believe that they had acquired HIV and thought that there had been a mistake. It was challenging in the beginning, of course. //After the first year, I did not think that way. (6) After receiving an HIV diagnosis, older adults experienced a process that was described as going from thinking of HIV all the time to something one gets used to and internalizes. As a part of this process, receiving information about the effectiveness of HIV medication and acquiring knowledge about HIV, especially about the non-risk of HIV transmission, were described as critical. This was described as helping to cope with HIV and creating feelings of reassurance, bringing hope for future life. This information was mainly retrieved from HIV clinics but also from the Internet or others living with HIV. It seemed apparent that my days were being counted. However, there was a turnaround in medication by the end of the 90s. (22) Those receiving the diagnosis in the 80s/90s described experiences of ”surviving a death sentence” that for some made them feel empowered and contributed to new perspectives on life. Yes, well, now that I am very old, so many have died, almost everyone is gone. I am the only one left. And especially AIDS, everyone died from AIDS. I think about it; I live alone. I feel very lonely’. Nonetheless, I cannot break it, you know (19). But for some it also raised a feeling of sadness for being alone as a survivor, experiences related to having seen people around them die of HIV. I do not actually have HIV anymore as long as I take the pills. I’m almost down to zero (viral load). (20) Even though HIV was internalized, the participants were reminded of its presence in daily life on specific occasions, such as when visiting an HIV clinic or taking HIV medication. HIV was by some described as being hidden in the body, even though it was not detectable. The participants described that it was vital for them to take responsibility for their HIV medication, as it kept the virus levels undetectable. Generally, ageing was associated with the need for medication, making the need for HIV medication non-deviant in old age. However, reflecting on how HIV medications affect the body, especially for those who had been taking medication for a long time, could foster anxiety. They expressed concerns about the potential inability to manage their HIV medication if they felt weak or disoriented, thereby having to depend on others for care. Socio-emotional impact on everyday life I have no problem with my HIV, but my problem lies with preconceived notions, either from individuals or from others attitude toward HIV—that is my problem. (14) This theme describes older adults’ experiences of the socio-emotional impact of HIV on their everyday lives and interactions with others. HIV was described as “special” (19) compared to other diseases, mainly because of how other people think of and perceive HIV. If you go out on the street and ask someone if they know what HIV is, I do not know if they know what it is. These days, you never hear about it (HIV) in newspapers or the media or anything; it is so hidden in a way//It is as if it (HIV) does not exist in society. (1) Older adults described both fear and experiences of prejudice from others, such as family, friends, or the public. They expressed encountering attitudes related to a lack of knowledge about HIV and how HIV is transmitted. Thoughts were represented in the absence of information on HIV, causing preconceived notions. It (HIV) is still so shameful that no one wants to mention it. (9) Participants described their expectations of being judged by others and feelings of shame were experienced. I cannot go out and be open about my HIV status because it would hurt them (family) terribly. (22) Being met with stereotypical perceptions about HIV associated with substance abuse, sexual orientation, or sexual intercourse were commonly described. Experiences of such attitudes seemed more pronounced for people living in smaller places or the countryside of Sweden or abroad. The fear of being judged by others influenced the decision to disclose their HIV status. There were different approaches to how open one should be about HIV, which was not always an easy decision. Some stated that they had chosen to be completely open to others about their HIV status, such as society and family. However, this level of openness seemed to be an exception. Some felt forced to disclose their HIV status even though they did not need it. This created contradictory feelings about whether to tell. Living with undetectable HIV was experienced as liberating. It was considered crucial to have autonomy in deciding when and to whom to disclose their HIV status, even though rules of conduct or other individuals also could influence their decisions. No one knows, only my partner and myself. Nonetheless, of course, I have a doctor and nurse. Well, otherwise, it (HIV) is not discussed. It is ‘hush-hush. (18) It was perceived as easier to talk about diseases other than HIV. For some HIV was being kept as a secret, and some only disclosed HIV to the closest ones. What should they know then? I have not told them’; there is no need to say to them. Individuals with different illnesses cannot tell everyone … (7) Participants described having a sense that others would pity them or that they would burden others with their HIV. Some indicated that there were no reasons to tell others about living with HIV as it would not lead to anything positive. Telling others about HIV was related to fear of rejection when disclosing HIV, often grounded in negative experiences. The fear of rejection was a possible barrier in meeting a new partner. For some, it was assumed that it was easier to find a partner living with HIV. Therefore, some chose to live alone, others voluntarily, and others did so involuntarily. Many felt supported when they had experiences of disclosing their HIV status to family or friends and being met without prejudice. Those with the experience of being able to openly discuss HIV without fear of being judged found it reliable and essential. While some experienced support from HIV organizations, others felt that HIV organizations were not suitable for everyone or that there was no need to meet others living with HIV. I have been given assurances, and I have asked that if I hold a grandchild in my arms, it (HIV transmission) cannot happen and that there would be any situation where I would transmit it to the child. (3) Even if there was no risk of HIV transmission, some participants described that they still were not able to eliminate the fear of being a potential transmitter. This could manifest as fear limiting social relations in everyday life and result in extra care to avoid the risk of transmitting HIV, even when having undetectable virus levels. This fear was experienced as a limitation to starting new intimate relationships. Others no longer considered it problematic as it was presumed to be more restrictive for them when they were young. The risk of potential HIV transmission did not only limit intimate relationships but could also limit relationships with friends, colleagues, or family members. From their past experiences, they learned that others sometimes saw a person living with HIV as a risk of transmitting HIV. | [
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37214931 | intro | INTRODUCTION Brain-derived neurotrophic factor (BDNF) is a member of the neurotrophin family of growth factors. BDNF is important in neuronal development and is also critical in the adult brain, where it supports neuronal structure and plasticity. One critical brain region where BDNF is high and has been studied extensively is the hippocampus, where it is considered to be instrumental to learning and memory. AD brain tissues show variable BDNF levels, with some increases and some decreases depending on the brain area and the cell type being investigated. In hippocampus there is not always a significant change in AD, although some studies have reported that BDNF protein and mRNA decline, and data from CA1 pyramidal neurons show a robust decline across the progression of dementia that correlates with cognitive decline and neuropathology. In animal models of AD, there are both increases and decreases in hippocampal BDNF mRNA and protein levels. Despite the often equivocal findings, many investigators conclude that reduced BDNF occurs in AD, and contributes to it. There are numerous studies of serum BDNF in AD but serum levels may not be directly related to brain levels. One reason is that BDNF is expressed at high concentrations in platelets. Nevertheless, reduced serum BDNF has been commonly reported in AD. Variability may be explained by the stage of AD, because two studies showed elevated serum BDNF early in AD, at the stage of mild cognitive impairment (MCI) followed by a decline. However, others found decreased serum BDNF both in MCI and later. In normal rats and mice, BDNF protein shows abundant expression in the hippocampus in the mossy fiber (MF) axons of the dentate gyrus (DG) granule cells (GCs). Despite the high expression in MFs, to our knowledge only one study has examined MF BDNF in AD and that study used patient-derived tissue. The results suggested decreased MF BDNF protein in AD but there was variation in age of the patients, drug history, postmortem delay, and other factors that could affect BDNF expression levels. In the present study we took advantage of an antibody to BDNF that shows excellent specificity and staining for MF BDNF levels. We used an established AD mouse model, Tg2576 mice, which is advantageous because there is a slow development of amyloid-β (Aβ) plaques, occurring after 6 months of age.Therefore we could sample early (pre-plaque, 2–3 months-old) or late (post-plaque, >11 months old) stages. The results demonstrated that BDNF protein expression was strong in the MFs in Tg2576 mice and there was no detectable age-related decline. We then asked if the reason BDNF expression remains strong over the lifespan could be related to GC neuronal activity, because BDNF expression increases with activity and many AD patients and mouse models of AD exhibit increased excitability. In this regard the Tg2576 mouse was useful because Tg2576 mice exhibit increased excitability in vivo and in GCs in vitro. We found that there were high levels of the transcription factor ΔFosB within GCs in Tg2576 mice when MF BDNF expression was relatively high, supporting the idea that increased GC activity promotes BDNF activity-dependent expression and could explain MF BDNF stability. We then asked if stable GC BDNF expression might confer protection of GCs from Aβ deposition. Indeed, GCs showed remarkably little evidence of Aβ accumulation using several Aβ antibodies, even at 20 months of age. However, adjacent hilar neurons exhibited robust Aβ accumulation, as did hippocampal pyramidal cells. In summary, these data show BDNF protein in GC MFs is stable with age in Tg2576 mice, that there is a relationship to neuronal activity, and the relative resistance of GCs to Aβ accumulation. | [
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38077397 | title | The transcriptomics profiling of blood CD4 and CD8 T-cells in narcolepsy type I | []
|
38452202 | abstract | Supplemental Digital Content is Available in the Text. Abstract Understanding, measuring, and mitigating pain-related suffering is a key challenge for both clinical care and pain research. However, there is no consensus on what exactly the concept of pain-related suffering includes, and it is often not precisely operationalized in empirical studies. Here, we (1) systematically review the conceptualization of pain-related suffering in the existing literature, (2) develop a definition and a conceptual framework, and (3) use machine learning to cross-validate the results. We identified 111 articles in a systematic search of Web of Science, PubMed, PsychINFO, and PhilPapers for peer-reviewed articles containing conceptual contributions about the experience of pain-related suffering. We developed a new procedure for extracting and synthesizing study information based on the cross-validation of qualitative analysis with an artificial intelligence–based approach grounded in large language models and topic modeling. We derived a definition from the literature that is representative of current theoretical views and describes pain-related suffering as a severely negative, complex, and dynamic experience in response to a perceived threat to an individual's integrity as a self and identity as a person. We also offer a conceptual framework of pain-related suffering distinguishing 8 dimensions: social, physical, personal, spiritual, existential, cultural, cognitive, and affective. Our data show that pain-related suffering is a multidimensional phenomenon that is closely related to but distinct from pain itself. The present analysis provides a roadmap for further theoretical and empirical development. | []
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38300977 | methods | Experimental design The protocol aims to improve motor and cognitive deficits in patients with Parkinsonian Syndromes. A clinical examination will verify the inclusion and exclusion criteria. The eligible subjects will be assessed, and outcome measures will be collected (t0) by a trained physiotherapist and psychologist. The specialist who assesses participants will not train them. Patients will be then randomly assigned to a control or experimental group using a randomization sequence obtained from the website randomizer.org. The first group will complete the treatment as usual (TAU). Usually, training consists of a series of neuropsychological exercises delivered in paper and pencil modality, and classic motor activity, comprehending aerobic and anaerobic activities delivered thanks to bodyweight exercises on a stationary bike in an ordinary gym. The other one will complete a VR dual-task training protocol. Based on the evidence that exercise programs with shorter session duration and higher frequency may generate the best results, we propose 4–5 weeks of training of 10 sessions of 1 hour approximately, two times a week. Completed the 10 biweekly rehabilitation sessions a new assessment will be done (t1). The neuropsychological and motor assessment will be carried out before (t0), immediately after (t1) and 3 months after the end of the 10 sessions (t2) to evaluate the short/medium-term efficacy of the treatment. The chart of the trial design is presented in Fig 1. Patients must attend at least 8 out of 10 rehabilitation sessions as well as all the assessments for the treatment to be considered effective. All participants will sign the written informed consent. Materials and equipment The platform used during the training will be an immersive VR apparatus available at the Department of Geriatrics and Cardiovascular Medicine of the Istituto Auxologico Italiano: Cave Automatic Virtual Environment (CAVE). This system is composed of a room-sized cube in which four stereoscopic projectors (Full HD 3D UXGA DLP) are used to cast a three-dimensional image of the Virtual Environment (VE) onto three walls and the floor. In particular, there are three retro-projected screens (frontal, right, and left) and a direct-projection screen (floor screen). Four infrared cameras are employed to monitor any movements made by 3-D glasses. Active goggles combine the projected images for the right and left eyes to enable the feeling of depth. A tracking optical system is included in CAVE in addition to the visualization tools (VICON). The virtual scene in the CAVE is encoded with depth information, which is recovered and delivered to the eyes via 3-D glasses. The user has the impression that he/she is still moving around the object in 360 degrees because of the different images and viewpoints. As the user moves their head, the image almost spins in real time. An asymmetrical set of markers on both CAVE goggles and an Xbox joystick enable the retrieval of their position and heading in the environment. These data bits are utilized to enable the Xbox joystick to be used as a pointer for interfacing with 2D interactable components (such as buttons) in the CAVE and to modify the user’s point of view, respectively. A cluster system made up of two HPZ620 Graphics Workstations and an Nvidia Quadro K6000 GPU with specific Quadro Sync cards manages all the CAVE features. This technology ensures a true-to-life experience. Different tools were created to perform several activities in the Cave. Training will be developed based on existing tools, enriching and combining them to create a new training protocol. It will involve different dual-task exercises: the Positive Bike, Rocks, and the Supermarket. They will be proposed in a randomized order within subjects. Positive Bike. It is an innovative immersive tool proposed by Pedroli et al. (2019a) which consists of a stationary bike placed inside the CAVE in which patients cycle and keep their cycling velocity steady (motor task); concurrently they have to recognize target objects between distractors (cognitive task). The therapist decided the exercise parameters (e.g. time between targets presentation, the target to select, bike velocity) in each session. Rocks. The exercise, developed by Pedroli et al (2019), originates to train balance. Patients are immersed in a virtual environment resembling a straight dirt road and have to avoid rocks (motor task) they encounter on the way, moving their body in the right or left direction. We will add a cognitive part: while moving subjects will have to declare their direction (e.g. they will say ‘right’ if rocks move on the right and ‘left’ if they move on the left). Supermarket. This exercise takes place in a virtual supermarket, as proposed by Pedroli et al. (2018). It aims to train executive functions: users have to move in the shop using an Xbox controller and they must buy several products following precise rules. Ten different tasks with increasing difficulty are available. To create a dual-task, while shopping, we will add a motor task consisting of a walk in place with a metronome. All cited VEs were created utilizing Unity 3D and the MiddleVR Unity plug-in. This plug-in enables the communication between the Unity application and all the CAVE system components, allowing for the projection of scenes onto the CAVE walls and the use of motion data from the VICON system as inputs. The parts of the system are highlighted in Fig 2. Participants Participants will be volunteers of both sexes, aged 65 or over (without maximum age limitation), and with Parkinsonian Syndromes as classified by Williams and Litvan (2013). The eligibility criteria will require the participants to have an MMSE score between 30 and 24 and all participants will have normal or corrected-to-normal vision. Exclusion criteria will be invalidating internist, psychiatric, neurological conditions, presence of depression or anxiety without medications and hemianopsia or hemiplegia, severe physical or functional limitations impeding physical activity, and recurrent vertigo. The presence or absence of these criteria will be assessed during the initial clinical assessment performed by a physician. The final sample will be composed of 45 patients; to achieve this goal, at least 50 subjects will be assessed. To evaluate the size of the samples, we used a Sample Size Calculation (Power Analysis) using the software GPower*3. Based on data from Killane et al., with an effect size of 0.43, alpha of 0.05, and 80% power and we estimated the minimum of subjects to be included in the rehabilitation experiment. Outcome measure Participants will be assessed to provide information regarding their motor and cognitive abilities, as well as their capacity to perform the mentioned actions simultaneously. We will include evaluation scales related to the functional aspects such as the Tinnetti Balance Scale, the Equiscale, and the Time Up and Go Test (TUG). The Tinetti Balance Scale is the gold standard scale for balance evaluation. It is a simple clinical test consisting of 14 items with a score out of 28. The therapist evaluates patients’ performance in some activities concerning balance, gait, and risk of falling (i.e. standing up, walking, standing down, etc.). The higher the score, the better the performance. The Equiscale includes three subdomains of standing up, resistance to external perturbations, and resistance to self-induced perturbation in a real-life performance, for example, the therapist evaluates the ability to lean forward, sit up, etc. The Timed Up and Go Test (TUG) examine balance, gait speed, and functional abilities required to performance of basic activities of daily living; it measures the time that the subject takes to get up from a standard chair, walk three meters, turn around and go back to sitting down. The highest the time the worse the performance. The optimal cut-off value would be considered from 10 to 33 seconds. We will also evaluate cognitive domains; the general cognitive status with the MMSE and the executive functions domain with the Frontal Assessment Battery (FAB), the Tower of London (ToL), the Trail Making Test (TMT), and the Stroop Test. The MMSE is a brief test that screens the global functioning including temporal and spatial orientation, memory, attention, language, and apraxia. FAB is a screening test composed of six cognitive and behavioural tasks: similarities, phonological verbal fluency, motor series, conflicting instructions, Go-No Go task, and prehension behaviour. The score ranges from 0 to 18. The ToL is traditionally used to assess strategic reasoning, problem-solving, and mental planning in clinical populations. The task consists of moving tree beads to reproduce the target configuration; time and accuracy are evaluated. The TMT measures attention and ability of set-shifting; it is composed of two parts: the first (TMT A) is a searching task, and the second part (TMT B) requires shifting in searching alternatively numbers and letters. During the performance, time is evaluated: the highest time the worst score. The Stroop Test is designed to test the capacity to inhibit cognitive interference, which happens when processing one sensory characteristic interferes with processing another at the same time. It is composed of three parts, for each one the person is instructed to read respectively all the words, colors, and color ink as quickly as possible. A trained physiotherapist and psychologist will perform the assessment to exclude the low reliability of the data. The ability to engage in both motor and cognitive tasks will be evaluated with the motor and cognitive Time Up & Go Test (TUG) and the Walking and Remembering Test (WART). Motor and cognitive TUG consists of the previously described motor performance with an adjunct cognitive part requiring the patient to count backward by threes while walking. Similarly, the WART evaluates single and dual-task performance: working memory task while walking. Patients had to walk at their fastest safe speed along a path in both single and dual-task (simultaneous digit span task) conditions. Average walking time was considered. At last, quality of life will be evaluated using the Italian validation of the Parkinson’s Disease Questionnaire (PDQ-39). Outcomes information are included in Table 1. Moreover, we will consider outcome variables provided by the CAVE system during the DT training such as the time, accuracy, velocity, etc. performing each exercise. Data analysis We will realize a mixed design trial (2x3) with population training (VR vs. TAU) as a between variable and assessment of training effect (pre-test, post-test, and follow-up) within variables. A Windows Excel sheet will be used to organize all the data related to demographic and assessment information and an identification code will be assigned to each participant to ensure anonymity of the data. A mixed ANOVA will be performed to investigate interaction effects between and within variables. Moreover, we will analyze the accuracy during DT training to verify possible correlations with the accuracy measure in the assessment part at t0 and t1. The objective will be to examine if traditional tests reflect trained abilities. Moreover, we will propose an innovative approach of ML in the rehabilitation field, to estimate the TEP from the collected data during the DT VR experience. Based on our research question and available data we will use a classification algorithm to create a model; we will train and test the model using data to forecast which motor or cognitive parameters are more predictive for the future maintenance of any improvements obtained, based on the model proposed by Shi and colleagues (2019). We will use one of the best programs for ML analysis, such as Python. | [
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38961441 | results | Results The overall cohort’s demographic characteristics and plasma biomarker levels are presented in Table 1, and by center in Supp. Table 2. DLB and AD patients were significantly older than control individuals (P < 0.001). We observed a higher percentage of males in the DLB group than in the AD and control groups (P = 0.037). The AD group displayed more frequent APOE ɛ4 carriership than the DLB and NC groups (P < 0.001). In the AD group, 97% (n = 74) displayed a CSF A + T + profile and 3% (n = 2) an A + T- profile. As a sensitivity analysis, the main analyses have been reproduced after the exclusion of the A + T- subjects and yielded similar results (Suppl. Figure 1). Additionally, the characteristics of AD-MCI and AD-dementia groups are presented in Supp. Table 3. Associations with age, sex, and APOE status are detailed in Supp. Table 4. In the whole cohort, all plasma biomarkers were associated with age (β = 0.236–0.538, P ≤ 0.002) except for Aβ ratio (β=-0.042, P = 0.593) after adjustment on sex and APOE ɛ4 carriership. Plasma GFAP and YKL-40 levels were higher in females after adjustment on age and APOE status (GFAP: β = 0.258, P < 0.001; YKL-40, β = 0.198, P = 0.008). Plasma Aβ ratio, p-tau181, and sTREM2 levels were associated with APOE ɛ4 carriership in adjusted analysis (β = 0.165-0.228, P ≤ 0.028). Focusing on the DLB group, after adjustment for covariates, we found positive associations between age and plasma p-tau181, NfL, GFAP, and YKL-40 levels (β = 0.247–0.521, P ≤0.030) and between female sex and plasma GFAP levels (β = 0.259, P = 0.008). No association was found between any plasma marker and ApoE4 carriership, after adjustment for age and sex in the DLB group. Correlations between biomarkers are displayed in Supp. Figure 2. Focusing on DLB patients, plasma GFAP, p-tau181, and NfL showed significant associations (r = 0.341–0.560, P < 0.0001 overall). Plasma YKL-40 and sTREM2 were significantly associated (r = 0.284, P = 0.003), as well as with plasma NfL (r = 0.406, P < 0.000 both). Plasma GFAP was the only marker significantly associated with the plasma Aβ ratio (r=-0.325, P < 0.0001), though there was a tendency to association between the Aβ ratio and p-tau181 (r=-0.185, P = 0.067). Biomarkers levels across diagnosis groups Plasma biomarker levels are displayed in Fig. 1. Patients with DLB displayed lower levels of plasma Aβ ratio (P = 0.037, d = 0.576) and higher p-tau181 (P = 0.017, d = 0.644) and a tendency to higher GFAP levels (P = 0.057, d = 0.057), compared to NC, after adjustment for age and sex. Additionally, patients with DLB displayed significantly lower levels of plasma p-tau181 (P < 0.001, d = 1.11), NfL (P = 0.037, d = 0.390), and GFAP (P < 0.001, d = 0.685) compared with AD patients. DLB patients had higher levels of plasma sTREM2 compared with AD patients (P = 0.022, d = 0.413). No difference was observed in plasma levels for YKL-40 between diagnostic groups, with or without adjustment. Plasma Aβ ratio levels were lower and p-tau181, GFAP, and NfL levels all higher in AD patients compared with controls, but not plasma sTREM2 and YKL-40. Looking at AD stages, plasma p-tau181 levels remained significantly higher in both AD-MCI and AD dementia groups compared with the DLB group (Supp. Figure 3). Plasma NfL and GFAP levels were higher and sTREM2 levels lower in the AD dementia group compared with the DLB groups, but did not differ between AD-MCI and DLB. DLB diagnostic performance To differentiate DLB from controls, our plasma biomarkers yielded moderate AUCs from 0.74 to 0.78, without significant differences between biomarkers (Fig. 2a). Plasma p-tau181 yielded the highest AUC of 0.78 (95% CI 0.68–0.87). Combining biomarkers did not outperform p-tau-181 sole (Fig. 2b). To differentiate DLB from AD, plasma p-tau181 yielded the highest AUC (0.80) as a standalone biomarker and outperformed the other biomarkers (∂AIC > 4, Fig. 2c). The optimal combination of markers was the association of plasma p-tau181 and YKL-40, that performed as well as the combination of all biomarkers (all biomarkers model, AUC = 0.84 versus plasma p-tau181 + plasma YKL-40, AUC = 0.83, ∂AIC < 4, Fig. 2d). To differentiate AD from controls, plasma p-tau181 had the best performance as a standalone biomarker (AUC = 0.92) and association with other biomarkers did not improve diagnosis performance (Supp. Table 5). The diagnosis performance of the plasma biomarkers used individually was overall similar when analyzing separately AD-MCI and AD dementia cases (Supp. Figure 3). The combination of plasma p-tau181 and YKL-40 had the best performance to differentiate DLB patients from AD-MCI (AUC = 0.86, ∂AIC > 4 versus all biomarkers model [AUC = 0.88] and p-tau181 alone [AUC = 0.80]), with the best trade-off between the goodness of fit and parsimony. To distinguish DLB from AD dementia, the association of plasma Aβ ratio, p-tau181, and NfL (AUC = 0.85) was not inferior to the all biomarkers model (AUC = 0.87, ∂AIC < 4). Identification of amyloid copathology in DLB CSF analysis was available for 87% (90/104) of DLB patients (Table 1). According to the AT(N) classification, 24% of patients presented an AD CSF profile on the AD continuum, 12% being A + T- and 12% A + T+. A + DLB patients displayed higher concentrations of plasma p-tau 181 compared with A- DLB (P = 0.011, η2 = 0.71) after adjustment on age and sex (Fig. 3, a-f). A + T + patients displayed higher levels of plasma p-tau181 and NfL levels compared with A-T- DLB (respectively, P = 0.003, η2 = 0.131 and P = 0.036, η2 = 0.062, Fig. 3, g-l). Plasma biomarkers identified A + DLB patients with overall moderate AUCs ranging from AUC = 0.64 to AUC = 0.75, as standalone biomarkers. Plasma p-tau181 displayed a higher AUC of 0.75, outperforming all other biomarkers (∂AIC > 4). The best combination of markers was the association of plasma p-tau181, GFAP, and NfL, yielding an AUC of 0.79, which was equivalent to the performance of the combination of all 6 plasma markers (AUC = 0.82, ∂AIC < 4 ). Plasma p-tau181 was outperformed by the combinations of all 6 biomarkers (AUC = 0.82 versus AUC = 0.75, ∂AIC = 5.5). Diagnosis performance of our plasma biomarkers was overall better in discriminating A + T + from A-T- DLB patients (AUC = 0.71–0.85, Fig. 4, c). Plasma p-tau181 displayed the highest AUC, of 0.85, outperforming all other biomarkers. Combining biomarkers (AUC = 0.87–0.91, Fig. 4, d) did not statistically outperform plasma p-tau181 sole (AUC = 0.85, ∂AIC <4). Association with cognitive measurement The associations of the plasma biomarkers with MMSE in diagnosis groups are presented in Supp. Table 6. In the DLB patients, we found higher plasma levels of p-tau181 levels were correlated with lower MMSE in unadjusted analysis (Spearman’s r = 0.231, P = 0.024). After adjustment on age, sex, and level of education, there remained no significant association (β=-0.176, P = 0.072). In the whole cohort, higher plasma p-tau181 and plasma GFAP levels were significantly associated with lower MMSE, after adjustment on age, sex, and level of education (respectively: β=-0.378 and β=-0.373, P < 0.001). In the AD group, higher plasma GFAP levels were correlated with lower MMSE in unadjusted analysis (r = -0.253, P = 0.032). Principal component analysis Lastly, we performed PCA to investigate the relationship between the different biomarkers in AD and DLB groups (Fig. 5). In DLB, we identified 2 principal components that explained 58% of the total variance in the dataset (Fig. 5, a). Component 1 accounted for 19% of the variance and was associated with plasma Aβ ratio, p-tau181, and GFAP. Component 2 captured 39% of the variance and was associated with neuroinflammatory markers sTREM2 and YKL-40 and axonal damage markers NfL. In the AD group, PCA analysis yielded two principal components as well (Fig. 5, b). First, a component 1 associated plasma Aβ ratio and neuroinflammatory markers sTREM2 and YKL-40, explaining 20% of the variance. A component 2 clustered plasma p-tau181, GFAP, and axonal damage markers NfL, capturing 36% of the variance. | [
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38886941 | intro | Introduction The central nervous system (CNS) was previously considered an immune-privileged site owing to its ability to prevent inflammatory immune responses to antigens in the brain, in addition to limiting the exchange and access of cells and molecules from the periphery due to its highly specialized anatomical structures, including the meninges, perivascular space (PVS), and choroid plexus (cp), which form an interface between the periphery and the CNS (Kierdorf et al., 2019). However, in 2015, two scientists separately challenged this dogma of neuroimmunology, suggesting that the CNS could be connected to peripheral immune systems through the meningeal lymphatic vessel (MLV) pathway. Louveau and colleagues reported that functional lymphatic vessels line the dural sinuses, which express the molecular hallmarks of lymphatic endothelial cells (LECs), including vascular endothelial growth factor receptor 3 (VEGFR3), prospero homeobox protein 1 (Prox1), podoplanin (gp38), lymphatic vessel endothelial hyaluronan receptor 1 (Lyve1), CD31, and C–C motif chemokine ligand 21 (CCL21) (Louveau et al., 2015). At almost the same time, Aspelund et al. (2015) found that dural lymphatic vessels could absorb cerebrospinal fluid (CSF) from the adjacent subarachnoid space, demonstrating a direct mechanism for CSF flow directly from the CNS to the peripheral lymphoid system through the dural lymphatic network. Subsequently, in humans, Absinta et al. (2017) reported that MLVs were present within the dura mater through visualization of the MLVs using brain magnetic resonance imaging; their existence was subsequently confirmed in autopsy tissue using special staining methods. Thus, MLVs are key constituents of the communication between the CNS and peripheral lymphatic vessels that actively contribute to the drainage of macromolecules and the migration of immune cells (Hu et al., 2020). Furthermore, meningeal LECs (MLECs) secrete cytokines involved in lymphatic remodeling, fluid drainage, and inflammatory and immunological responses, demonstrating that MLVs govern the inflammatory process and immune surveillance in the CNS, and may pose as a valuable target for therapeutic intervention (Louveau et al., 2018). As immune cells have little access to the brain parenchyma under homeostatic conditions, the immune system of the CNS mainly consists of parenchyma-resident microglia and border immune cells, including myeloid and lymphoid cells, within the dural meninges, which form a strict immune network in the CNS and provide immune surveillance to protect brain function (Louveau et al., 2018). With the development of new methodologies, such as cell-sequencing silence-based perturbation studies, single-cell RNA sequencing (scRNA-seq), and spatial transcriptomics, MLVs have been found to not only contribute to the drainage of macromolecular substances and cells but also to respond to various inflammatory signals (Hsu et al., 2022), resulting in them being important indicators in neurological disorders, including neurodegenerative diseases such as Alzheimer’s disease (AD) (Da Mesquita et al., 2018b), Parkinson’s disease (PD) (Ding et al., 2021), autoimmune encephalomyelitis, and multiple sclerosis (Weller et al., 2009). Thus, the discovery of MLVs offers a new clue regarding the etiology of neurodegenerative diseases connected with immune system dysfunction and raises the question of whether MLVs communicate with immune cells in the CNS and, if this is confirmed, how this process occurs. It will be interesting to clarify whether communication between MLVs and CNS-resident or CNS-infiltrating immune cells plays a central role in the tissue physiology and pathology of neurodegenerative diseases and whether MLVs communicate with CNS immune cells. In this review, we focus on exploring the communication between MLVs and immune cells in the CNS and discuss how these bidirectional signaling events regulate neurodegenerative diseases and pathological outcomes. Please note that this review does not examine the drainage of abnormal protein deposits or the neuronal deformation present in neurodegenerative disorders, nor does it cover blood–brain barrier (BBB) disruption or intracranial pressure changes in experimental models of MLV disruption in neurodegeneration, as these topics have been extensively reviewed elsewhere. Search Strategy We searched the PubMed database for articles published from 2015 to April 2023 using the terms “meningeal lymphatic (dys)funcion” AND “meningeal lymphatic vessels,” “Alzheimer’s disease” AND “Neurodegenerative diseases,” “Immunity” AND “Lymphoid cells” AND “Myeloid cells.” Supplementary search databases included Web of Science and Google Scholar. Further screening was performed by reading literature titles and abstracts. Representative articles were screened for studies related to the meningeal lymphatic system, neurodegenerative diseases, and immunity, and relevant references were used to clarify each aspect. The Immunological Niche of Meningeal Lymphatic Vessels The origin of destiny MLECs are terminally differentiated cells derived from venous endothelial cells, which begin at 6 to 7 weeks of embryonic development in humans or 9.5 to 10.5 days in mice (Tammela and Alitalo, 2010). In this process, venous endothelial cells, the precursors of LECs, express the homeobox transcription factor Sox18 at embryonic day (E)9.0, which activates the transcription of Prox1 by binding to its promoter, resulting in the development of lymphatic vessels (Oliver and Srinivasan, 2010). Prox1, a specific marker of LECs, was first detected in Lyve1 positive cells; thereafter, Prox1 induces the expression of LEC-specific genes with the inhibition of blood endothelial cell-specific genes (Jiang et al., 2022). Thus, targeting the Sox18 locus or homozygous mutation of Sox18 could abolish the expression of Prox1, resulting in fatal embryonic edema. The loss of one allele or heterozygous mutation of Sox18 leads to defects in cutaneous lymphatic vessels (François et al., 2008). Developmentally, MLVs first arise from the foramina at the base of the skull shortly after birth, proceeding along the blood vessels and cranial nerves and finally appearing in the anterior superior sagittal sinus. After forming an extensive network with numerous sprouts until 3–4 weeks of age, MLVs were found to stabilize and persist in similar locations in mice until 2 years of age under homeostasis, resulting in a solid foundation for their multifaceted roles in health and disease (Antila et al., 2017). Apart from Prox1, the receptor tyrosine kinases VEGFR3, podoplanin/gp38, and Lyve-1 are commonly present on the surface of LECs (Alitalo, 2011). Prox1 plays a key role in the establishment and maintenance of the lymphatic endothelial transcription program; Lyve-1 can increase the expression of podoplanin and induce platelet aggregation; and the vascular endothelial growth factor C (VEGFC)/VEGFR3 signaling pathway is the main driver of the development and pathological lymphangiogenesis of LVs (Karkkainen et al., 2004). Within a well-established lymphatic system, lymphangiogenesis occurs only under pathological conditions, such as inflammation or tissue repair induced by VEGR-C/VEGFR3 signaling (Tammela and Alitalo, 2010). During development, homozygous deletion of VEGFC results in the absence of the embryonic lymphatic vascular system, while heterozygous deletion leads to severe lymphatic hypoplasia. Role of MLVs in the CNS Located within dural meninges, MLVs extend along the sinuses, the dural middle meningeal arteries, and at the base of the skull, eventually accompanying the jugular vein and leaving the skull via various foramina. MLVs are responsible for the drainage of molecules, immune cells and various CNS metabolites from the CSF to the peripheral system in a CCL21/C-C chemokine receptor type 7 (CCR7)-dependent manner (Alves de Lima et al., 2020a, b; Figure 1). Two studies found that when tracers were injected into the CSF or brain parenchyma of adult mice, they could later be detected in periarterial and perivenous spaces (Iliff et al., 2012; Hershenhouse et al., 2019), demonstrating an exchanged influx of CSF between the parenchymal interstitial fluid (ISF) and CSF (Louveau et al., 2015), which is called the “glymphatic system” (Da Mesquita et al., 2018a). In addition, through surgical, pharmacological, or genetic manipulations, the ablation of MLVs could reduce both CSF and ISF efflux, providing evidence of a functional link between the perivascular glymphatic system and the meningeal lymphatic system (Louveau et al., 2015). Louveau et al. (2015) injected mice with Evans blue intracerebroventricular injection, which was subsequently detected in the deep cervical lymph nodes (dCLNs), while Evans blue injected into nasal mucosa could not be detected, suggesting that MLVs provide a direct route for lymphatic drainage from the CSF to dCLNs. Furthermore, photodynamic ablation targeting MLVs in murine models demonstrated an accumulation of macromolecules (including fluorescenoyl-labeled ovalbumin, polystryrene beads) within the meninges in dCLNs (Aspelund et al., 2015). In humans, magnetic resonance imaging visualization after intracerebral injection of a tracer also showed peak cervical lymph node enhancement within 24 hours (Eide et al., 2018), which coincided with glymphatic enhancement around the leptomeningeal arterial trunks, indicating that MLV-cervical lymph nodes might serve as the next step in CNS drainage following the glymphatic system. In addition to playing a key role in draining macromolecules (Louveau et al., 2017), MLVs also assist in establishing a complete lymphatic-immunity network with a special meningeal immune landscape. Under steady-state conditions, lymphocytes rarely exist in the CNS parenchyma due to the less potent antigen (Ag)-presentation capability of glial cells, which limits the entry of these immune cells (Prinz and Priller, 2017; Papadopoulos et al., 2020). However, in contrast to the parenchyma, there are abundant and complex nonparenchymal immune cells in the CNS-associated interfaces, which include border-associated macrophages, dendritic cells (DCs), T cells, B cells, monocytes, neutrophils, natural killer cells, and innate-like lymphocytes (Dong and Yong, 2019; Mundt et al., 2019a, b; Figure 2). The unique location and rich diversity of immune cells present under homeostasis suggest that the meninges is a dynamic and immune tissue through which cytokines are released into the CSF and diffuse into the brain parenchyma, thereby affecting particular neuronal subpopulations and generating different behavioral responses. Furthermore, these diverse populations of immune cells influence the CNS-related immune response, which changes with aging, causing a series of inflammatory and neurodegenerative diseases (Alves de Lima et al., 2020a, b). By providing a structural framework for MLVs, meningeal immune cells can traffic and communicate between the CSF and the peripheral immune system, sampling brain content from the CSF and sensing signals from the brain to maintain brain homeostasis. Furthermore, meninges-derived cytokines enter the brain parenchyma through the paravascular influx of the glymphatic system, from which they can directly affect neural cells to modulate homeostasis and pathology. Correspondingly, cytokine efflux from the parenchymal ISF is also affected by aging or conditions in which MLV function is diminished or impaired, possibly caused by delayed cytokine or toxic molecular clearance (Iliff et al., 2012; Alves de Lima et al., 2020b). As a result, despite not being directly present in the brain parenchyma, immune cells present within the CSF and meningeal spaces regulate immune function in the CNS through the lymphatic–glymphatic system (Raper et al., 2016). Endogenous heterogeneity of MLECs Lymphatic vessels are composed of LECs, a distinct endothelial cell lineage characterized by specific transcriptional and metabolic programs (Escobedo and Oliver, 2016). Regarding the microenvironment in the CNS that physically constrains the vessels, the endogenous properties of MLECs reveal a unique transcriptomic signature to determine the patterns of disease behavior. In contrast to peripheral lymphatic vessels, which proliferate and expand in the inflammatory environment (Kim et al., 2014), MLVs shows no morphological changes in either the brain (except for the cribriform plate) or the spinal cord at different time points during robust inflammation induced by experimental autoimmune encephalomyelitis (EAE) (Dendrou et al., 2015), while there is an elevated level of VEGFC during EAE. As a result, MLVs do not demonstrate the classic inflammation-induced lymphangiogenesis that undergoes expansion similar to other tissues during inflammation, supporting that they express a unique transcriptional signature. Furthermore, differential expression analysis from RNA sequencing (Louveau et al., 2018) revealed an upregulation or downregulation of ~300 genes in MLECs compared to peripheral LCs (from the diaphragm and ear skin), and gene set enrichment analysis revealed alterations in multiple pathways, including the extracellular matrix, focal adhesion, and angiogenesis, as well as responses to endogenous and exogenous stimuli in the immune system. In addition, similar expression of environmental stiffness-regulated genes in LECs and MLECs cultured on a still matrix was observed, which indicated a limited capacity for MLECs to interact with the meningeal microenvironment (Louveau et al., 2018), providing a molecular-level explanation for the finite plasticity of the adult MLV response to growth factors or local inflammation. However, there is one special case of lymphangiogenesis occurring near the choroid plexus (cp) during EAE neuroinflammation, creating a specific immune regulatory niche with a unique phenotype of cpLECs, in which the scRNA-seq of cpLECs showed immunoregulatory functions that engage in leukocyte crosstalk, similar to general peripheral lymphatic function (Hsu et al., 2022). Furthermore, compared to naive cpLECs, inflammatory cpLECs showed an increased ability to bind to DCs and CD4+ T cells, containing intracellular CNS Ags, expressing major histocompatibility complex class II (MHC-II), and increasing the expression of immunoregulatory proteins, such as PD-L1; some of these functions may be acquired in response to interferon gamma (IFN-γ) during neuroinflammation. Thus, neuroinflammation can prime cpLECs to undergo lymphangiogenesis and engage in crosstalk with and the regulation of leukocytes. This lymphangiogenesis of MLVs also occurs in patients with traumatic brain injury, chronically implanted intracranial electrodes, and intracranial tumors, showing an enrichment in Ag processing and presentation or other similar immune-related genes (Bolte et al., 2020). Notably, the dorsal MLVs and basal MLVs also undergo different remodeling under neuroinflammation; dorsal MLVs undergo extensive remodeling whereas basal MLVs show less variation (Hu et al., 2020). As a result, whether in the meninges and peripheral tissue or in the different regions of the meninges, there is heterogeneity in the ability of lymphatic vessels to undergo lymphangiogenesis, which may be related to specific features of the microenvironment, such as excess fluid accumulation during inflammation. However, inflammation of both the meninges and peripheral tissue is accompanied by an increase in VEGFC/VEGFR3 signaling (Song et al., 2020), leukocyte crosstalk, and leukocyte function regulation, implicating a potential function of MLVs in regulating the immune response in the meninges (Rustenhoven et al., 2021). Crosstalk between Meningeal Lymphatic Vessels and Myeloid Cells in Central Nervous System Immunity While MLVs were initially thought to merely provide a pathway for “trash drainage,” it is now clear that MLVs and CNS immune cells jointly form and maintain a tightly intertwined MLV-immune network, which is an important prerequisite for adequate CNS immune function. As a heterogeneous class of innate immune cells that differentially contribute to the maintenance of CNS homeostasis during development and adulthood, myeloid cells play a key role in the CNS immune system; these myeloid cells include parenchymal microglia and nonparenchymal macrophages, such as leptomeningeal, perivascular, and cp macrophages, as well as various subsets of DCs and monocytes (Ginhoux and Jung, 2014). This heterogeneity and functional diversity of myeloid cells depends on differences in their ontogenies and local niches (Guilliams et al., 2018), which have recently been explored regarding their activation, differentiation, and tissue-specific functions. Parenchymal microglia and nonparenchymal CNS macrophages arise from prenatal hematopoietic progenitor cells in the yolk and fetal liver (Varol et al., 2015), without any supply from blood or bone marrow during adulthood. However, monocytes, granulocytes, and DCs are derived from hematopoietic stem cells (Laurenti and Göttgens, 2018), which mostly originate from the aorta-gonad-mesonephros derived from yolk sac-derived cells, and colonize the fetal liver (Kumaravelu et al., 2002; Figure 3). Generally, these immune cell types play an important role as effectors and regulators of the CNS–immune response under homeostasis (Prinz et al., 2017; Prinz and Priller, 2017); however, how these myeloid cells pass the BBB and arrive at the parenchyma under pathological conditions is unclear. The ongoing revolutions in scRNA-seq results is leading to a new foundation for research focused on CNS myeloid cells. For example, Cugurra and colleagues (Cugurra et al., 2021) suggested that there is a hidden source of meningeal myeloid cells derived from the skull that have distinct phenotypes from blood-derived counterparts. Thus, this myeloid-meningeal niche is opened to homeostatic peripheral inputs, rather than the blood being used as a major route for delivery into the CNS (Cugurra et al., 2021). As a result, myeloid cells infiltrating the CNS borders are strategically reserved as innate immune cells under homeostatic conditions, patrolling the border as a first line of defense or residing in the tissue to maintain homeostasis and react to pathogenic threats or endogenous inflammatory triggers, and can breach the glial limits and enter the CNS parenchyma (Prinz et al., 2017; Prinz and Priller, 2017). Myeloid cells are delivered into the brain parenchyma following brain injury or inflammation via direct dural–bone marrow connections with the adjacent skull, which supply the brain and dural meninges with monocytes and neutrophils directly (Herisson et al., 2018). Crosstalk between MLVs and microglial cells in CNS immunity In contrast to macrophages that arise from definitive hematopoiesis in the embryo, microglia are derived from the erythromyeloid progenitors of the extraembryonic yolk sac and have two remarkable properties: restricted prenatal origin and longevity (Prinz et al., 2017; Prinz and Priller, 2017). As resident innate immune cells in the CNS parenchyma, resting microglia act as sensors in the CNS through their high efficiency in scanning the environment for pathological changes or inflammatory stimuli (Davalos et al., 2005), and play roles as phagocytes and antigen-presenting cells (APCs) under pathological conditions. Pattern recognition receptors expressed in microglia could help them detect and respond to bacteria or viruses invading the CNS parenchyma, thus transitioning from a ramified resting state to a debranched activating state (Remuzgo-Martínez et al., 2013). These activated microglia induce the CNS inflammatory response by secreting proinflammatory cytokines, such as interleukin (IL)-1β, IL-6, IFN-γ, and tumor necrosis factor alpha, and chemokines, such as CCL2, CCL3, and CCL12, which recruit other immune cells to participate in the neuroinflammatory response. Molecular crosstalk between brain LECs and microglia begins early during colonization of the CNS and plays an essential role in CNS health and disease. Lauren’s team reported that brain-border lymphatic vessels are central to the early colonization of MRC1/Mrc1 microglia precursors in the embryonic zebrafish brain, which is independent of the traditional pu1+ yolk sac-derived microglia lineage (Green et al., 2022). Thus, the earliest colonizing microglia precursors may arise from or depend on the brain lymphatic endothelium. Notably, these brain LECs have only been reported to be a unique population of zebrafish LECs and are not present in the lymphatic vessels described in the mouse (or later in life in the zebrafish). Thereafter, mature microglia and LECs remove particle waste from the brain, and LECs may be specialized in the receptor-mediated endocytosis of soluble macromolecules and smaller particles (including proteins, polysaccharides, and smaller substrates, such as human papillomavirus), while microglia may specialize in the uptake of larger particles and pathogens (Huisman et al., 2022). Although the specific communication methods and approaches are still being identified, it has been recognized that microglia play a vital role in CNS function and disease behavior through the secretion of paracrine signals. Similarly, according to the physiological principle that MLVs are linked to paravascular CSF and ISF movement, it is presumed that MLVs may alter the availability of secretions, resulting in a microglia response regulated by paracrine signals (Dantzer, 2018). Thus, bidirectional communication between MLVs and microglia can modulate CNS inflammation through the secretion of multiple cytokines and inflammatory mediators by both components. Furthermore, gene set analysis suggested that there is a link between MLV impairment and microglial activation; the ablation of MLVs results in a dampened transcriptional and morphological microglial phenotype. Da Mesquita et al. (2021a, b) reported that MLVs rendered dysfunctional by photodynamic therapy induce a disease-associated microglia phenotype in reactive microglia. This transcriptional profiling of cells from MLV-ablated 5×FAD mice demonstrated deleterious microglial activation, characterized by the upregulation of cytokine production, leucocyte migration, cell chemotaxis, and myeloid leucocyte action, and the downregulation of Ag processing and the presentation of peptide antigens via MHC-II and T cell activation. In addition, aging-related MLV dysfunction was also proven to be relevant to microglial activation (Goldman et al., 2022), and scRNA-seq data suggested that, compared to homeostatic microglia, 25 gene pathways are shared between the ablation and aging IL-1β-responsive microglia regarding both the upregulated and downregulated pathways, including cytokine secretion, lymphocyte activation in the immune response, and myeloid leukocyte activation (Goldman et al., 2022). Thus, meningeal lymphatic impairment is suggested to be related with aging and microglial activation, which requires further investigation into age-related pathologies and their link to meningeal lymphatic dysfunction (Da Mesquita et al., 2021b). MLVs are tightly related to microglia in terms of functions and molecules, indicating that a common mechanism mediates MLV-microglia crosstalk in aging and neurological diseases. Another interesting connection between microglia and MLVs relates to the plasticity of microglial immune memory, which is influenced by MLVs. Immune cells play a pivotal role in the reaction to injury, and generally, the repair and resolution phase restores homeostasis following the initial period of acute inflammation, leaving some memory cells locally. When secondary stimuli occur, these memory cells reactivate and respond rapidly. This process is called “immunity memory,” which maintains the ongoing protection against a wide range of pathogens and damage. In the context of inflammation, the paradigm of “immunity memory” has been extended to innate immunity mechanisms (Neher and Cunningham, 2019). In the CNS, studies on innate memory have mainly focused on microglia because they express a multitude of immune receptors (Ayata et al., 2018) that are capable of sensing peripheral systemic disruptions in homeostasis. Wendeln’s study (Wendeln et al., 2018) suggested that, when compared to mice that received only one injection of lipopolysaccharide, mice that received multiple injections of low-dose lipopolysaccharide responded differently to amyloid-β (Aβ) and stroke, indicating a surveillance pathway for microglia for the detection of peripheral proinflammatory stimuli to establish immune memory, which has long-term consequences for neuroimmunity crosstalk in the CNS. However, such sensing could be reduced by dysfunction of MLVs (Goldman et al., 2022), indicating a close relationship between the integrity of MLVs and the immunity memory of microglia. Furthermore, therapeutic interventions that enhance the MLVs or the dysfunction of MLVs will impact the responses of microglia to subsequent stimuli. As a result, whether MLVs drive innate memory is a complicated and thought-provoking question, and further study targeting this question may result in novel potential treatments for neuroimmune diseases of the CNS. In summary, these data suggest that MLV modulation of microglial transcriptional states is part of a bidirectional dialog that coordinates the CNS-immune system response, providing a channel for microglia to surveil the peripheral environment and maintain homeostasis in the CNS immune system. The mechanisms of MLV-microglia crosstalk participate in CNS development and immune system formation, highlighting the relevance of communication between LECs and microglia during development and under healthy conditions. Crosstalk between MLVs and nonparenchymal myeloid cells in CNS immunity Myeloid cells: a major player in the plasticity of MLVs A study has shown that activated myeloid cells in CNS pathological conditions remodel lymphatic vessel structure and function through soluble mediators, such as ILs and VEGFC secreted by immune cells, including macrophages and DCs, and nervous system cells, including astrocytes and vascular endothelial cells, in the CNS (Rustenhoven et al., 2021). Therefore, under physiological and pathological conditions, the proliferation and permeability of LECs can be remodeled by the CNS microenvironment, in which cytokines play a vital regulatory role (Gordon et al., 2010). However, aside from the lymphatic vessels near the cribriform plate that show lymphangiogenesis for the drainage of CNS Ags and immune cells under conditions of neuroinflammation (Hsu et al., 2019), a recent study suggested that there is only a slight expansion of MLVs, which change in a VEGFC-VEGFR3-dependent manner with enhanced immune responses, rather than undergoing lymphangiogenesis (Zhou et al., 2022), indicating a ceiling effect of the influence of MLVs on myeloid cells. Furthermore, studies on transgenic zebrafish identified a population of isolated mural LECs that express LEC markers that might develop into a dispersed, non-lumenized mural lineage from the lymphatic endothelial loop in a VEGFC-VEGFD-VEGFR3-dependent manner; regulate meningeal angiogenesis during development; and endocytose macromolecules (Bower et al., 2017). Under pathological conditions, these mural LEC-brain LEC-FGP cells rapidly invade the lesions, forming lumenized lymphatic vessels to resolve cerebral edema and providing guidance and support for new blood vessels as migratory scaffolds (Chen et al., 2019). In these processes, angiogenic signals, including VEGF, platelet-derived growth factor, and matrix metalloproteinases, are released from endothelial cells, stromal cells, and leukocytes, including macrophages and monocytes, promoting the sprouting and development of vessels, which are essential for normal meningeal vascularization (Carmeliet and Jain, 2011). Thus, the plasticity of MLVs plays a vital role in establishing complete normal meningeal blood vasculature and provides a flexible response to address multiple CNS conditions in both homeostasis and pathology. Synergistic work of MLVs and myeloid cells in CNS Ag delivery and disease behavior In the 1940s, a study on CNS immune privilege suggested that the brain parenchyma elicits delayed graft rejection; however, when the immune response toward antigens was established in the periphery, a similar response was found to rapidly occur in the CNS (Medawar, 1946), indicating that isolated antigens without APCs carried by lymphatic vessels could not prime an immune response in the CNS. This recognition occurred for many years until the rediscovery of MLVs with an accumulation of various APCs, providing a physical pathway for CNS-derived antigens to access peripheral lymph nodes, which allows subsequent T cell priming and activation, resulting in a long-lasting population of effector memory T cells to carry out immune surveillance of the CNS and promote effective functions and tissue retention under homeostasis (Louveau et al., 2015). In this process, although CNS Ags can drain into peripheral lymph nodes alone, they still require intracellular processing by APCs, as well as a secondary signal, such as danger-associated molecular patterns or pathogen-associated molecular patterns, to be drained alongside the antigens for a complete immune response. Thus, meningeal APCs, such as DCs and macrophages, are regulated by proteins expressed by LECs, including CCL21, CCL27, sphingosine 1-phosphate, colony-stimulating factor 1, vascular cell adhesion molecule 1, and intercellular adhesion molecule 1 (Wei et al., 2006), contributing to the delivery of CNS Ags for immune cell activation. Taken together, these findings indicate that MLVs play a key role in draining CNS Ags alone or accompanied by APCs into cervical lymph nodes, which establishes a connection between myeloid cells and lymphoid cells in CNS immunity. The MLV-myeloid cell interaction extends beyond the simplistic idea of a communication pathway; it contributes to the pathogenesis of multiple neurological diseases. For example, synergistically proinflammatory cytokines are produced and neuroendocrine substances, such as IFN-γ, IL-4, and IL-17, are released through the activation of myeloid cells and lymphoid cells after encountering APC-carried antigens, which are available to maintain homeostasis in the CNS or enhance the sensitivity of immunity under pathological conditions (Alves de Lima et al., 2020a, b). In addition, myeloid cells in the CNS provide critical trophic support for neurons and play essential roles in brain function and disease behavior. Beyond these conclusions, Goldman and colleagues (Goldman et al., 2022) presented an interesting conundrum of whether meningeal lymphatic ablation and myeloid cell depletion synergistically exacerbate disease behavior. They suggested that although the activation of myeloid cells has been generally regarded as a promoter of inflammation in the CNS, a decreased number of activated myeloid cell populations (including microglia) induced by a colony-stimulating factor 1 receptor antagonist aggravated the exploratory behavior of destructive IL-1β, which is in line with data indicating that impaired meningeal lymphatic drainage reduced the myeloid cell inflammatory response to peripheral IL-1β in exploratory abnormalities, which could be reversed by enhancement of meningeal lymphatic function (Goldman et al., 2022). Thus, it is worth considering whether myeloid-driven function synergizes with MLV dysfunction to exacerbate neurological disability. In the future, new approaches are needed to promote and further validate our present understanding of MLV-induced disease behavior under both neuroprotective and neuropathological states. Crosstalk between Meningeal Lymphatic Vessels and Lymphoid Cells in Central Nervous System Immunity The dynamic change of meningeal lymphoid cells B cells B cells play a key role in adaptive immunity (Clatworthy, 2021); however, under steady-state conditions, B cells are rarely present in the CNS parenchyma and CSF, accounting for less than 1% of white blood cells (Kowarik et al., 2014). While approximately 30% of dural immune cells are B cells within the meninges, along the walls of the dural venous sinuses (Korin et al., 2017). When inflammation occurs, B cells enter the CSF contained in the subarachnoid space and then extravasate across subpial venues of the blood-meningeal barrier or cross the stromal space and epithelium of the cribriform plate (Sabatino et al., 2019), eventually reaching the CNS parenchyma. Furthermore, research has suggested that lymphoid follicle-like structures containing B cells within the meninges under chronic inflammatory conditions provide a sustained immunopathological response in the CNS (Magliozzi et al., 2004; Serafini et al., 2004; Cohen et al., 2021; Wang et al., 2023). Using scRNA-seq, meningeal B cells encompassing multiple stages of development, covering pro-B to mature B cells, were found in the mouse meninges; the same subsets were identified in the bone marrow rather than in the blood (Keren-Shaul et al., 2017; Brioschi et al., 2021). Further confirmation of this result was found based on parabiosis experiments and lineage tracing, in which developing B cells within the meninges were replenished continuously from hematopoietic stem cell-derived progenitors via a circulation-independent route (Wang et al., 2021). Thus, a hypothetical model emerges that early B lineage progenitors migrate into the CNS early during ontogeny and then develop and mature locally; however, further study is needed to determine whether meningeal B cells originate from the reservoir of progenitors contained in the thin layer of bone marrow inside the skull or whether they originate directly from progenitors in the dural mater, independent of bone marrow (Schafflick et al., 2021). In addition, in aging animal models, age-associated B cells derived from the blood gradually accumulate in the meninges, endangering the balanced microenvironment and decreasing the prevention of damage by pathogens (Brioschi et al., 2021). In summary, these findings challenge the commonly accepted idea that meningeal adaptive immunity completely originates from the peripheral circulation and provides a better explanation for self-tolerant B cells in the CNS. T cells It has been reported that the majority of T cells in the CSF and/or parenchyma present with Ag-experienced effector or central memory phenotypes (Hickey, 1999; Engelhardt and Ransohoff, 2005; Ransohoff and Engelhardt, 2012), providing protective immune surveillance without damaging the delicate environment of the CNS under steady-state conditions. Within the meninges, there are two main subsets of meningeal T cells, including tissue-resident (or long-dwelling populations) and circulating T cells from the blood (Derecki et al., 2010). These cells patrol and are trafficked into inflamed tissue to deliver effector function only with the assistance of CNS APCs, which express small processed peptides bound to MHC molecules on the surface that can overcome glial limits and reach the lesions (Mundt et al., 2019a, b). Thus, even if T cells are primed in the meninges or peripheral lymph nodes, they cannot function without re-encountering Ags within the respective target tissues (Schläger et al., 2016). As a result, it can be simply summarized that peripheral lymph nodes or meninges are the first activation site for T lymphocytes, and the second site for reactivation is located in CNS lesions. In addition, new research proposed that the skull bone is the preferential homing site for autoreactive T cells in multiple sclerosis (MS), which augment myelopoiesis and exacerbate CNS inflammatory injury (Shi et al., 2022), indicating an interaction between lymphoids and myeloids within CNS borders. The specific mechanism by which they affect neuronal functions and behavior remains unclear; however, it may occur through paracrine signaling, such as IL-4, IL-17, and IFN-γ (Ziv et al., 2006), which directly affect neurons and other CNS cells under homeostasis. Under pathological conditions, the beneficial (Serpe et al., 1999; Levite, 2023; Zhan et al., 2023) or harmful (Yilmaz et al., 2006) effects of T cells depend on the type of injury and the subsets of T cells for a unique inflammatory milieu. MLVs: a supplemental pathway for immune tolerance in the CNS Immune tolerance is a mechanism in the immune response to differentiate self and non-self antigens to minimize self-reactivity. Immune tolerance comprises “central tolerance,” which occurs in primary lymphoid organs, including the thymus or bone marrow, and “peripheral tolerance,” which occurs in secondary lymphatic organs, such as lymph nodes or certain peripheral tissues. T cell immune tolerance is established mainly in the thymus through the removal of self-responsive T cells and generation of regulatory T cells, which depends on the expression of various tissue restricted antigens by medullary thymic epithelial cells (Benlaribi et al., 2022). Generally, T cell progenitors originated from the bone marrow and migrated to the thymus to mature with V(D) J recombination (Tonegawa, 1983). In this process, the mechanism of T cell tolerance in the thymus is “center tolerance” (Xing and Hogquist, 2012). The T cell receptor expression of T cell precursors goes through a “positive selection,” in which the CD4 and CD8 double-positive thymocytes differentiate into CD4 or CD8 single-positive thymocytes (Sprent and Kishimoto, 2001). The single-positive thymocytes then migrate into the thymic medulla, where the single-positive thymocytes with high-affinity T cell receptors for self-peptides undergo apoptosis in “negative selection” (Xing and Hogquist, 2012), or generate into unconventional T cells, such as regulatory T cells (Tregs) (Starr et al., 2003). As for the central tolerance of B cells, this mainly refers to the regulatory mechanisms that occur at the early developing stages of B cells in the bone marrow. At this stage, the immature B cells with a surface antigen receptor of IgM class can bind self-antigens, with regulation at this stage to reduce self-reactivity (Nemazee, 2017). In the later developmental stages, peripheral tolerance mainly occurs in the spleen, lymph nodes, and other tissues with a co-expression of immunoglobulin (Ig)M and IgD. In this stage, B cells are fully activated and can produce high-affinity antibodies with the cooperation of T cells and antigens. Notably, this peripheral tolerance is reversible, to a degree, which benefits the response to various viruses and microorganisms that carry similar epitopes to self-antigens (Klinman, 1996). However, this mechanism of central tolerance is not complete in that some self-reactive T cells escape from the thymus and enter the periphery (Bouneaud et al., 2000), and some auto-reactive B cells are restrained by an absence of secondary signaling help, remaining in the B-cell pool. Thus, additional supplied mechanisms occur in “peripheral tolerance” wherein escaping self-reactive T cells or B cells become functionally unresponsive/anergic or are deleted after encountering self-antigens in the circulation or peripheral tissue to ensure autoimmune tolerance. Therefore, central tolerance plays a key role in reducing the frequency of autoreactive B cell repertoire, and peripheral tolerance acts as the supplemental pathway. Generally, CNS antigens are protected by the BBB, and escape from the tolerance checkpoints in the bone marrow and spleen. However, with the use of complementary techniques, including bone marrow transplantation and parabiosis experiments, bone marrow–derived heterogeneous B cells were detected within a specific meningeal compartment, which ranged from naive to transitional to mature B cells (Brioschi et al., 2021), demonstrating that early B cell subsets also exist in the meninges and under homeostasis, as in the bone marrow. This is an interesting finding regarding the specific origin of these developing B cells within the meninges, which might help them to recognize and establish CNS-autoimmune tolerance against CNS antigens. Thus, MLVs provide a pathway for presenting target autoantigens for B cells to launch negative selection within the meninges and prevent the generation of Igs with high affinity for CNS epitomes. However, accumulated age-associated B cells that infiltrate from the periphery and plasma cells occupy most populations identified in the meninges with aging (Brioschi et al., 2021), which results in a high morbidity of neurodegenerative diseases and neurological autoimmune diseases, indicating a decrease in CNS Ags, which is in line with the dysfunction of MLVs in aged mice (Da Mesquita et al., 2018b). Another supplemental candidate for CNS immune tolerance is dCLNs, which a play vital role in maintaining substantial subsets of T cell repertoires and in providing an activation space for cognate Ag encounters with lymphoid cells through MLVs (Brioschi et al., 2021). Thus, when under homeostasis, CNS Ags that drain from the CSF through MLVs without being carried by APCs reach the dCLNs and are processed within them, providing an alternative and/or complementary pathway for negative selection in addition to the thymus, as well as establishing self-tolerance for CNS autoantigens (Hirosue and Dubrot, 2015). Thus, MLVs provide a restricted and constant source for meningeal B cells and dCLN T cells to encounter CNS antigens, completing central tolerance outside the bone marrow and thymus, which helps to maintain immune privilege for the CNS under homeostasis. When MLV dysfunction occurs with aging or neurological disease, this privilege is broken, leading to dysfunctional CNS immunity. MLVs: an admission ticket for specific lymphoid cells Current research has reported that most immune cells accumulate within the dura along MLVs (Louveau et al., 2015), playing an important role in immune surveillance under steady-state and pathological conditions. In addition, the number of endogenous meningeal T cells increased following the ligation of dCLN afferent lymphatics, which supports a relationship between cerebral lymphodynamics and T cell circulation in the CNS (Louveau et al., 2018). Generally, T cells migrate through MLVs mainly in a CCR7-CCL21-dependent manner under both physiological and pathological conditions; these are key molecules involved in the homing of T cells and DCs to the lymph nodes (Förster et al., 2008). The same signaling pathway takes effect in the meningeal lymphatic system. For example, the drainage of T cells in CCR7-knockout mice was significantly decreased compared with that in wild-type mice, and blockade of the CCL21/CCR7 signaling pathway weakened the VEGFC-potentiated checkpoint for MLV trafficking (Louveau et al., 2018). However, although loss of CCR7 reduced the drainage of meningeal T cells, not all migrating cells were abolished, demonstrating another pathway for drainage. Thus, further studies are needed to identify additional potential pathways, such as Lyve1–hyaluronic acid (Johnson et al., 2017), ICAM-β2 integrins (Teijeira et al., 2017), CCR4-CCR12 (Kabashima et al., 2007), sphingosine 1-phosphate-signal regulatory proteins (Czeloth et al., 2005), or C-X3-C motif chemokine ligand 1-C-X3-C motif chemokine receptor 1 (Johnson and Jackson, 2013), to explore the complete mechanisms that control the migration of meningeal immune cells by MLVs. Aside from contributing to communication between CNS disorders and peripheral immunity, MLVs also provide a pathway for peripheral/meningeal immune cells to connect and communicate with parenchymal glial cells such as microglia and neurons. Generally, microglia and T cells play a vital role in CNS development and homeostasis; however, the interaction of activated microglia and/or macrophages with encephalitogenic T cells enhances their capacity to exacerbate injury, leading to exacerbated neuroinflammation and neuropathology, in which MLVs might have an adverse effect by serving as a communication pathway. For example, a cascade of inflammatory responses is induced by the combination of activated microglia and peripheral immune cells that are recruited to the CNS through MLVs in MS. In addition, EAE, an experimental model of CNS autoimmune disease, is generally mediated by the CD4+ T cell effector response that leads to the secretion of IFN-γ, IL-17, and granulocyte-macrophage colony-stimulating factor, which are known regulators of microglial activation, participating in numerous proinflammatory processes (Johnson and Jackson, 2013). In vitro experiments demonstrated that culturing microglia and T cells together with a foreign Ag could increase T cell proliferation (Guldner and Wyss-Coray, 2023). A study has suggested that in MS, T cells and microglia are detected closely at sites of neuron loss, and that this colocalization might synergistically worsen inflammation and promote neuron loss via cell-to-cell contact and soluble factors (Marik et al., 2007). With increasing research on MLVs, the specific mechanism and pathway of peripheral T cell activation and entry into the CNS, such as Ag presentation and co-stimulation via the MHC on APCs and CD80 (B7-1)/CD86 (B7-2), respectively (Spiteri et al., 2022), as well as their interaction with microglia, have gradually become clear. However, whether microglia can act as APCs to carry CNS antigens to T cells remains controversial because MHC-II deletion in microglia does not prevent the development of EAE (Wolf et al., 2018). Thus, meningeal lymphatic drainage is a necessary condition for the acquisition of a fully encephalitogenic profile for specific T cells and migration to the CNS through interactions between brain Ag-specific T cells (myelin oligodendrocyte glycoprotein or 2D2) and DCs (CD11c+) to shape T cell phenotypes (Louveau et al., 2018). In transcriptomic profiling studies to explore the mechanism by which CNS lymphatic drainage impacts T cell encephalitis, an analysis of dCLN-isolated myelin oligodendrocyte glycoprotein-specific T cells showed that approximately 500 genes were significantly up- or downregulated in EAE mice with meningeal lymphatic ablation compared to EAE mice without lymphatic manipulation; most genes were downregulated (Louveau et al., 2018). Furthermore, gene ontology analysis revealed a significant downregulation of the inflammatory response, such as the cytokine and chemokine responses induced by T cells, associated with those downregulated genes. In addition, the release of cytokines derived from T cells, including activated cytotoxic (CD8+) T and helper (CD4+) T cells that release lytic granule-containing cytokines, including proinflammatory cytokines such as IFN-γ, tumor necrosis factor alpha, and tumor necrosis factor beta, or anti-inflammatory cytokines such as IL-13 or IL-10 (Zhang and Bevan, 2011; Halle et al., 2017; DeMaio et al., 2022), could regulate the formation and function of lymphatic vessels during inflammation (Shin et al., 2015). Regulating these T cell-derived cytokines might provide a therapeutic approach for rapidly treating lymphedema, for example, in lymphedema induced by the side effects of monoclonal antibodies in AD treatment. Meningeal Lymphatic Vessel Crosstalk with Immune Cells in Aging and Neurodegenerative Diseases Vascular inflammation, a dysfunctional BBB, abnormal protein deposition, and impaired meningeal lymphatic system drainage have been observed in neurodegenerative diseases. A dynamic contrast-enhanced magnetic resonance imaging study suggested that both the glymphatic and lymphatic systems are impaired in aging humans, with fluid and metabolites remaining in the dilated PVS and obstructing the amplitude of pulsations, resulting in toxic protein accumulation in the brain parenchyma and causing neuropathological changes in neurodegenerative diseases (Zhou et al., 2020). Another RNA sequencing analysis further showed that in LECs stored in the meninges of aging mice, almost 607 genes differed from those of young mice (Alves de Lima et al., 2020b). The changes in gene sets were mainly involved in immune and inflammatory responses, cellular adhesion, and endothelial tube morphogenesis, while the expression of Fms-related tyrosine kinase 4 (Flt4), which encodes VEGFR3, was not significantly altered, supporting functional alterations in MLECs with age (Da Mesquita et al., 2018a). Thus, comprehensive signaling components, including neurotransmitters, chemokines and cytokines, antigens, classes of receptor systems induced by apoptotic neurons and demyelination, and gradient signals generated by reactive microglia and astrocytes, and microvascular endothelial cells in the brain parenchyma, could result in leukocyte infiltration of the CNS (Chen and Holtzman, 2022). In this context, MLVs drain misfolded protein peptides and cellular debris and disperse proinflammatory cytokines secreted by CNS-resident and CNS-recruited peripheral immune cells, modulating the responses of neighboring cells throughout the CNS (Sweeney and Zlokovic, 2018). Furthermore, advances in genomics and spatial transcriptomics have fueled the identification of novel pathways that recognize MLV function in health and neurodegenerative disease. Thus, there is strong evidence to suggest that MLVs either promote or limit aging and neurodegenerative disorder pathogenesis in a highly microenvironment-dependent manner, emerging as key regulators of neuroinflammation and neurodegeneration. Alzheimer’s disease AD, characterized by an accumulation of Aβ peptide and neurofibrillary tangles in the brain that lead to the dysfunction and loss of synapses and neuronal death (Butterfield and Halliwell, 2019), is an age-related neurodegenerative lesion that is the major cause of dementia presenting as a progressive cognitive decline in memory and higher executive functioning (Nelson et al., 2009). Aging is the most important risk factor for late AD, and genetic factors, such as mutations in Aβ precursor protein (APP) and the presenilin gene, are significant factors, especially for early AD (Tanzi, 2012). The neuropathological characterization of AD tissue reveals the presence of numerous mediators of innate immunity, including activated microglia, complement components, and chemokine system elements (Prinz et al., 2011), which begin early in the pathology, while some evidence suggests an inconsistent role of the adaptive immune system in AD. On the one hand, studies have found that the depletion of lymphoid cells in 5×FAD mice results in severe AD pathology with increased plaque formation, upregulated proinflammatory cytokines, and progressive cognitive impairment. For example, through intracerebroventricular elimination of T helper (Th)1 cells, plaque load was reduced in APP/PS1ΔE9 mice (Fisher et al., 2014). Aβ-specific polarized Th2 cells reduce plaque-associated microglia and Aβ deposits, and reverse cognitive dysfunction, possibly in an IL-4-dependent manner. Using the 5xFAD mouse model, a study suggested that the accumulation of monocyte-derived macrophages and forehead box P3+ Treg induced Aβ plaque clearance and a reversal of cognitive decline (Baruch et al., 2015). Furthermore, CD4+ T cells increased after injection of a PD-1 immune checkpoint inhibitor, accompanied by activation of the systemic IFN-γ-dependent immune response in 5×FAD mice, reducing the cerebral Aβ plaque load in both 5×FAD and APP/PS1 mice (Baruch et al., 2016). On the other hand, Aβ deposits were significantly reduced in Rag2–/– APP/PS1ΔE9 mice with microgliosis and Aβ phagocytosis enhancement, suggesting a decrease in Aβ accompanied by the lifelong or acquired absence of T and B cells (Späni et al., 2015). Aβ-specific Th1 cell adoptive transfer in APP/PS1 mice was shown to lead to microglial activation, serious Aβ deposition, and impaired cognitive function through an IFN-γ-mediated pathway (Browne et al., 2013). Infiltration of Th17 cells into the parenchyma was found to cause severe neurodegeneration, potentially via the Fas/FasL apoptotic pathway, and could be rescued by IL-17 (Zhang et al., 2013). In addition, studies have also reported the trafficking of clonally expanded Ag-specific CD8+ T cells in the CSF of AD patients (Gate et al., 2020) and the infiltration of CCL3-related CD8+ T cells in THY-Tau22 mice and AD patients with a P301L tau mutation (Laurent et al., 2017). A current study found that in both aging and AD, including Aβ and tau neuropathological models, MLV dysfunction increases the burden of protein deposition and impairs the clearance of intracellular aggregation (Antila et al., 2017), leading to CSF perfusion injury and defects in learning and memory. For example, previous studies (Da Mesquita et al., 2021a, b) suggested that MLV dysfunction results in significantly increased Aβ deposition and impaired cognitive function in 5×FAD mice (Da Mesquita et al., 2018a) and APP/PS1 mice (Wang et al., 2019). Furthermore, it has been reported that a lack of functional dural lymphatics results in the increased accumulation of extracellular tau and reduced clearance in K14-VEGFR3-Ig transgenic mice compared to wild-type mice (Aspelund et al., 2015; Patel et al., 2019). Furthermore, diffusion tensor imaging analysis along the PVS also suggested a lower diffusivity along the PVS, indicating impairment of the glymphatic system in AD (Taoka et al., 2017). These data suggest that MLVs contribute to the clearance of pathological proteins in the CNS, providing a potential therapeutic method for AD. VEGFC-VEGFR3 signaling, which is a recognized and valid target to alleviate AD in mice, has attracted increasing attention and is currently being explored. For example, recent studies revealed that therapeutic delivery of VEGFC enhances meningeal lymphatic function, improves the clearance of Aβ by monoclonal antibodies, and leads to improved clinical outcomes (Da Mesquita et al., 2021a, b). In addition, a Down syndrome–associated gene, Down syndrome critical region 1 (DSCR1), has drawn attention from scientists as a regulator of MLVs in AD (Choi et al., 2021). Physiotherapy, such as cranial magnetic stimulation, could also improve the function of MLVs in AD (Lin et al., 2021). MS MS or EAE, a typical animal model of multiple MS, is a chronic CNS immune-mediated disease characterized by the infiltration of monocyte-derived macrophages and T cells from the circulation, as well as microglial activation, leading to demyelination and progressive neurodegeneration (Dong and Yong, 2019; Hamatani and Kondo, 2023). In this process, autoaggressive myelin-reactive T lymphocytes or adoptively transferred myelin-reactive encephalitogenic CD4+ Th cells migrate into the CNS and then recognize their cognate targeted Ag carried by APCs (usually DCs) (Bailey et al., 2007), initiating an inflammatory cascade. Supporting this hypothesis, the adoptive transfer of myelin basic protein–specific clonal T cells induced paralysis, meningeal inflammation, and demyelinated lesions in recipients (Zamvil et al., 1985), while mice depleted of T cells did not develop EAE or produce myelin basic protein–specific autoantibodies (Ortiz-Ortiz and Weigle, 1976). Furthermore, T cells isolated from CNS lesion tissues and from the CSF from MS patients showed clonal expansion, including CD4+ T cells and CD8+ T cells (Traugott et al., 1983). Notably, a further study suggested that these pathological features are lost when CD4+ T cells are depleted; however, they remain when CD8+ T cells are depleted (Pettinelli and McFarlin, 1981). The CD4+ T cell-mediated pathogenic mechanism is thought to involve an IFN-γ-mediated Th1-dependent response (Traugott and Lebon, 1988). Apart from Th1 cells, studies have also shown that Th17 and Th9 cells induce EAE after adoptive transfer to recipients (Jäger et al., 2009). In contrast to Th1 cells, which induce “classic” EAE that presents as paralysis developing from the tail to the head, the transfer of Th17 cells induces “atypical” EAE that causes ataxia, unbalanced gait, and rotary defects that progress to paralysis (Domingues et al., 2010). Th9 cells mainly induce extensive demyelination within both the CNS and peripheral nervous system (Jäger et al., 2009). B cells also play an important role in MS by reacting to and interacting with T cells in peripheral secondary lymphoid tissue by presenting antigens. IgG antibody deposits are present on degenerating myelin sheaths in both MS patient lesions and EAE lesions in a primate model (Raine et al., 1999). In addition, B cells were found to aggregate in all subtypes of MS, in which follicle-like lymphoid structures containing B cells, plasma cells, T cells, and DCs developed within meningeal pia mater. Furthermore, B cells in the CSF of patients with MS are colonially related to B cells in the peripheral nervous system and CNS parenchyma, suggesting that communication occurs between these compartments (Sabatino et al., 2019). As a result, the adaptive immune system plays an available role in the pathogenesis of MS through regenerative effects in the CNS. For example, reduced demyelination of lysolecithin-induced demyelination lesions was found in Rag1–/– or CD4+ T cell depletion or CD8+ T cell depletion mice (Bieber et al., 2003), which could be reversed by regeneration that centers on the differentiation of oligodendrocyte progenitor cells in oligodendrocytes, replacing myelin sheaths in demyelinating lesions and preventing cone degeneration (Franklin and Ffrench-Constant, 2017). In this process of myelin regeneration, Tregs were suggested to promote oligodendrocyte differentiation and (re)myelination; thus, Treg-deficient mice exhibited substantially impaired demyelination, which was rescued by the adoptive transfer of Tregs (Dombrowski et al., 2017). However, which APCs are responsible for presenting CNS antigens to T cells remains unclear. Although the cellular targets of myelin-specific T cells in EAE are oligodendrocytes, oligodendrocytes cannot express MHC-II molecules and thus cannot present Ags to invading immune cells (Lee and Raine, 1989). In addition, other potential APCs that are implicated in T cell reactivation, including microglia, astrocytes, pericytes, endothelial cells, and neurons, do not express MHC-II under steady-state CNS conditions (Becher et al., 2006), and further study suggested that stimulatory deletion of MHC-II in microglia had no impact on the pathogenesis of EAE (Spiteri et al., 2022). As a result, these cells provide evidence of the consequence of inflammation rather than evidence of specific T cell reactivation in EAE. Given the surveillance role of the lymphatics, the relationship between meningeal lymphatic dysfunction and immune cell dysregulation characterized by MS (EAE) was assessed in a murine model; MLVs may promote disease pathology by facilitating CNS-derived immune cell and Ag delivery to dCLNs for the reactivation of specific T and B cells, which is in contrast to their predictably beneficial role in AD. Furthermore, amid the widespread CNS inflammation seen in MS, there were no observable structural changes or lymphangiogenesis of the MLVs (except for the c cribriform plate), while the quantification of the number of lymphoid clusters of T cells revealed an increased density inside and around MLVs during EAE disease progression, providing clues regarding the pathway by which CNS-infiltrating T cells migrate from dCLNs through MLVs (Louveau et al., 2018). However, an increasing diameter of lymphangiogenesis at later time points was observed in the cribriform plate during disease progression in a VEGFC/VEGFR3-dependent manner, which suggested the involvement of nasal drainage in the late stages of disease, increasing the drainage of CNS Ags to dCLNs and maintaining T cell activation that increased their proliferation in lymph nodes (Hsu et al., 2019). Thus, the blockade of MLVs could decrease the encephalitogenic phenotype of Ag-specific T cells and alleviate the inflammatory response in a model of MS (Louveau et al., 2018). The resection of the dCLNs in mice resulted in reduced disease severity. The inhibition of VEGFR3 signaling leads to delayed disease development and reduced severity (Schläger et al., 2016). Thus, MLVs may be a target for the management of disease progression and in providing potential treatment measures for EAE by blocking the migration pathway for immune cells to reduce the activation of T cells in dCLNs (Jiang et al., 2022). Notably, all these exploratory models of blocking merely decrease disease severity; they do not completely halt the development of EAE. PD The most important pathological hallmark of PD, characterized by movement abnormalities and cognitive impairment, is the intracellular aggregations of α-synuclein (“Lewy bodies”) with neuronal toxicity (Qi et al., 2023). In general, innate immune cells, such as activated microglia and monocytes, secrete proinflammatory and neurotoxic cytokines and chemokines in response to misfolded α-synuclein, leading to inflammation in PD. However, the role of adaptive immunity is emerging in PD. For example, increasing levels of activated T cells were found in the CSF and midbrains of PD patients (Schröder et al., 2018), and these T cells surrounded damaged neurons in postmortem brain tissue, indicating that α-synuclein-specific T cells might be related to PD (Sulzer et al., 2017). In addition, although there is no direct evidence of B cells in the brain (Brochard et al., 2009), deposits of IgG were found on dopaminergic neurons and around Lewy bodies (Orr et al., 2005), which resulted in selective dopaminergic neuron loss. The levels of α-synuclein-specific autoantibodies also increased in the CSF and blood of PD patients (Horvath et al., 2017). Regarding the evaluation of T lymphocyte subsets, a study suggested that PD patients had significantly lower CD4+:CD8+ T cell ratios as well as an increased ratio of IFN-γ- to IL-4-producing T cells, indicating that the peripheral immune system was shifted toward a Th1-type immune response (Baba et al., 2005). In addition, a further study suggested that the shift in CD4+ T cells is involved in an increase in effector and memory cells and a decrease in naive cells (Fiszer et al., 1994). Although still controversial, these immune disorders are implicated in the loss of dopaminergic neurons (Sulzer et al., 2017). For example, using different 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine models, such as severe combined immunodeficient Rag1–/– and Tcrb–/– mice that lack mature lymphocytes, both showed attenuated dopaminergic cell death compared with wild-type mice (Benner et al., 2008). It was suggested that this detrimental effect is mediated by CD4+ T cells, as CD4–/– mice showed attenuated neuronal cell death after 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (González et al., 2013), and rebuilding CD4+ T cells in severe combined immunodeficient mice could abolish this attenuation through the Fas/FasL pathway (Brochard et al., 2009). Thus, CD4+ T cells play a vital role in the pathology of PD. In addition, in the isolation and transfer experiment, Th17 cells, but not Th1 cells, exacerbated neuronal loss, supporting the role of IL-17 in the pathogenesis of PD (Reynolds et al., 2010). The IL-17 and IL-17 receptors on neurons also increased in cocultures of iPSC-derived midbrain neurons and activated T cells from PD patients (Sommer et al., 2019). Tregs also play an important role in the regenerative capacity of neurons in PD. For example, the adoptive transfer of activated Tregs following 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine induction led to the survival of over 90% of dopaminergic neurons, which exerted these effects through modulating neuroinflammation, increasing neurotrophic production, and suppressing microglial responses to α-synuclein (Reynolds et al., 2007). However, despite increasing evidence of the potential role of immunity in PD, it is still unclear whether CNS immunity is associated with the specific pathological mechanism of PD. A recent study has suggested significantly decreased CSF flow perfusion along the superior sagittal sinus and sigmoid sinus in idiopathic PD patients with a delay in dCLN perfusion, which provided clinical evidence for the decreased function of MLVs in PD patients (Ding et al., 2021). In a transgenic mouse model of PD, the deposition of α-synuclein was found to be paralleled by reductions in lymphatic flow; furthermore, blocking meningeal lymphatic drainage led to an aggravated PD-like pathology (Zou et al., 2019). In addition, evidence from PD has supported the potential role of the glymphatic system, including the PVS. For example, a recent study comparing PD individuals and healthy controls suggested an increased PVS in the basal ganglia (Park et al., 2019). With the use of magnetic resonance imaging, global and regional differences in the PVS volume fraction between PD and non-PD patients, particularly prominent in the medial orbitofrontal and superior temporal regions, are involved in cognitive function impairment in PD (Donahue et al., 2021). Another study also suggested distinct relationships between glymphatic dysfunction and the severity and types of PD motor symptoms through diffusion tensor imaging analysis along the PVS index, indicating that glymphatic pathway dysfunction is related to the pathogenesis of PD (Qin et al., 2023). This dysfunction of MLVs not only induces an aggravation of α-synuclein within the PVS but also promotes reactive immune cells with inflammatory cytokine production, glial activation, dopaminergic neuronal loss, and exacerbated motor deficits (Zou et al., 2019). Similarly, α-synuclein injection in mice also induced decreased drainage from the CSF to dCLNs, loss of tight junctions among MLECs, and increased inflammation to the meninges (Ding et al., 2021), indicating an interaction effect between the meningeal lymphatic system and pathological products of PD. However, the rediscovery of MLVs has also provided a potential route for targeted therapy of PD. For instance, a recent study proposed a natural killer cell membrane biomimetic noncomplex delivered via the MLV route to further the therapeutic efficacy of PD; compared with conventional intravenous injection, MLV administration could enhance the delivery efficiency of curcumin in the brain by ~20-fold (Liu et al., 2023). In summary, a dysfunction in meningeal lymphatic drainage represents an early biomarker and provides a potential route for the targeted delivery of drugs to the brain in neurodegenerative disease therapy. | [
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37754030 | intro | 1. Introduction Currently, over 55 million people worldwide are affected by dementia. It is a disease that constitutes ‘one of the main causes of incapability and dependency of older people’ as it interferes with normal daily functioning. Dementia is a syndrome caused by several diseases (e.g., tumors, metabolic disorders, neurodegenerative diseases, etc.) typically affecting people over the age of 65. Alzheimer’s disease (AD) is the most prevalent form of dementia, responsible for roughly 60% of cases, followed by cerebrovascular dementia, accounting for about 30% of cases. Dementia with Lewy bodies and frontotemporal dementia (FTD) are less common. As the aging population grows, dementia’s prevalence increases due to its strong association with age. Dementia’s profound characteristic is a gradual loss of cognitive functioning. The defining characteristic of dementia is the gradual deterioration of cognitive function. Its most critical feature is the progressive decline in cognitive abilities, encompassing memory, thinking, attention, concentration, and the capacity to maintain daily living activities. It can also affect emotional control and social behavior. Normal aging, however, also impacts global cognition, as indicated by numerous studies. Though it is an older approach, it is still assumed that certain cognitive functions are affected during aging, particularly the speed of processing. This, in turn, affects memory, specifically working memory, which deteriorates as humans age. In addition to memory, other cognitive functions are also compromised, such as language, executive functions, and perception. Cognitive skills tend to change throughout adulthood, with certain mental activities peaking at different points in time. The idea that aging does not uniformly impact all cognitive functions is rooted in a theory by Catell. He differentiated between two primary categories of cognitive functions, classifying them as fluid and crystallized intelligence, both contributing to overall general intelligence. According to Catell, fluid intelligence is a general ability to discern and perceive relationships among various elements, whether they are novel or familiar. Fluid intelligence encompasses abilities that involve deliberate processing, including working memory, processing speed, abstract reasoning, and visuospatial reasoning. These capacities are crucial for complex thinking, problem-solving, and everyday functioning and they do not depend on prior experiences. Conversely, crystallized abilities draw upon previously acquired cognitive skills, general knowledge, and vocabulary. Research suggests a positive correlation between fluid and crystallized intelligence in cognitively normal adults. However, as individuals age, crystallized abilities appear to remain stable or even show improvement, unless cognitive impairment or dementia sets in. In contrast, fluid cognitive functions exhibit a steep decline, typically commencing around the age of 50, affecting various domains such as memory, working fluency, attention, concentration, and more. This decline in fluid intelligence is underpinned by neural changes, suggesting reduced responsiveness in a frontoparietal network, which may explain the decrease in cognitive abilities during normal aging. Indeed, neuroimaging research indicates that specific neuroanatomical regions are affected by aging, resulting in a decline in overall cognitive functioning. The disparity between fluid and crystallized intelligence serves as a predictive factor for abnormal cognitive decline. Fluid intelligence experiences significant deterioration compared to crystallized intelligence, and it also leads to the development of compensatory aging theories. Regarding dementia, it is well-documented that patients with dementia, especially those with AD, initially experience a decline in fluid functions, which serves as a predictive marker for disease progression itself. Crystallized cognitive functions, on the other hand, remain relatively intact, reflecting the patients’ cognitive abilities before the onset of the disease. Nonetheless, dementia entails a global decline in intellectual abilities, primarily affecting memory and at least one other cognitive function. Considering the magnitude of cognitive decline and its impact on independent living, particularly in the context of increasing lifespans, it becomes imperative to identify effective treatments for enhancing cognitive function in people with dementia or those at risk of developing any form of dementia. Currently, two options are available for dementia treatment: pharmacological and non-pharmacological interventions (see for a literature review). Pharmacological treatments typically involve cholinesterase inhibitors, the NMDA receptor antagonist memantine, antipsychotic drugs, among others. Non-pharmacological treatments address the unmet needs of dementia patients stemming from the symptoms of dementia itself, including cognitive decline, communication difficulties, and the inability to live independently. Pharmacological interventions have been employed to mitigate the symptoms of dementia and slow its progression. However, despite being the primary approach for managing dementia, these treatments do not offer a “cure” for the disease. The effectiveness of pharmacological interventions varies from person to person and does not yield long-term benefits for patients. In the absence of a viable long-term pharmacological remedy and in light of the presence of cognitive, behavioral, and psychological symptoms, it becomes crucial to provide individuals with dementia, their families, and their caregivers with additional assistance and alternative strategies through non-pharmacological interventions. The objective of such interventions is to enhance or sustain patients’ cognitive function, improve their daily quality of life, and address behavioral symptoms that often accompany memory decline. Non-pharmacological treatments are considered more cost-effective and associated with fewer side effects than pharmacological options, making them a preferable emerging treatment avenue for dementia. There are four types of non-pharmacological interventions suggested, with cognitive training being one of them. Cognitive training is an intervention method that employs structured (usually repetitive) exercises aimed at improving or maintaining mental function. It can be delivered either individually or in a group, focusing on specific cognitive skills. Advances in technology have led to the emergence of computerized cognitive training (CCT). These cognitive training exercises are delivered through electronic devices, such as smart phones, tablets, and computers, and can be customized to each patient’s needs, mental status, and expectations since they do not require significant effort on the part of the patients and utilize familiar activities only. Computer-based applications can provide instant monitoring and control for every user, as well as data collection and metrics for each action in the electronic environment, allowing for the estimation of a participant’s performance and overall progress. Additionally, they offer accessibility to individuals facing mobility issues and difficulties in accessing healthcare resources, all at a relatively low economic cost. Finally, the use of rich multimedia in electronic applications provides users with the opportunity to engage in enjoyable activities and may even motivate them to repeat the activity and transfer the acquired knowledge to real-life situations. Considering that cognitive training, especially using electronic devices, is currently a part of non-pharmacological interventions targeting specific cognitive functions, particularly memory (specifically, fluid intelligence), this study aims to further investigate whether intervention with a computer-based program would improve the short-term and prospective memory abilities of patients suffering from dementia and their normal peers. The rationale for investigating these specific types of memory is to determine whether a failure to remember to execute planned actions either immediately or in the immediate future (prospective memory) can have an impact on patients’ daily routines and consequently affect their quality of life. While the investigation of prospective memory is not extensive, it has yielded valuable outcomes regarding its treatment in dementia. To facilitate our patients’ performance, we employed an errorless strategy, proven effective for improving memory abilities. This was achieved with an app that provides participants with a user-friendly environment to track their step-by-step performance. Furthermore, there have been no other studies in Greek that have examined the performance of both dementia patients and their matched normal controls through an electronic application on tasks that require the use of specific types of memory. Finally, we also investigated the performance of healthy older participants on memory tasks to further examine whether a possible memory problem (a problem with a particular fluid intelligence ability) can be improved, raising hopes for the development and implementation of technological devices for researching memory decline through cognitive intervention strategies (errorless learning) that have thus far been considered very effective. 2. Literature Review on Computerized Memory Assisting Technologies 2.1. Studies Employing Computer-Based Technology as a Means of Intervention in Healthy Older Adults A number of studies investigated the positive effects of cognitive training in healthy older individuals. For example, in the ACTIVE study (advanced cognitive training for independent and vital elderly) the main objective was to examine the effects of memory, reasoning, and speed-of-processing training. The participants were randomly assigned to groups and were compared to no-training controls. RCTs were conducted to compare training among different cognitive domains. It was found that each targeted cognitive ability showed a significant improvement as compared to the baseline assessment, and this improvement lasted up to 2 years, as indicated by a post-intervention follow-up. Sustained improvements in specific cognitive domains (memory and reasoning) that lasted up to 5 years after training were further highlighted. Following this line of research additional evidence was provided for the benefits of cognitive training. It was noted that cognitive training can improve cognitive functions of healthy older adults. The observed improvement lasted up to five years after the intervention had begun. The implications of these outcomes were that an improvement in cognitive functions has a positive impact on daily living skills and it can also alleviate depressive symptoms. An overall improvement of global cognitive function has also been reported, especially after the application of CCT programs in healthy adults, targeting specific cognitive domains such as verbal memory, working memory, attention, etc.. Recently in a pilot study a computerized cognitive stimulation website named VIRTRAEL (“Virtual Training for the Elderly people”, n.d.) was developed. This is a free access platform that includes tests and exercises for the assessment of cognitive skills in older people, such as attention, learning, memory, and executive functions. It was noted that there was an overall improvement of these targeted cognitive functions and it was proposed that CCT is in effect a useful tool that can be used in ‘the fight against cognitive symptomatology associated with aging and neurodegenerative diseases’. Despite these promising outcomes and the ongoing research carried out in this area, the positive role of CCT’s approaches warrants further consideration. The benefits of computerized cognitive training in healthy older adults are being addressed, but at the same time, the problem concerning the efficacy of this method needs to be further examined, since this issue ‘remains controversial in the scientific community, and both sides of the debate encourage further research’. With this in mind, the present study hopes to provide additional evidence regarding the possible cognitive gains after the application of a computerized training program in both healthy and demented adults. 2.2. Studies Employing Computer-Based Technology as a Means of Intervention and Rehabilitation of Patients with Dementia So far, most studies using technological means to enhance cognitive function in patients with dementia have mainly focused on AD while other types of dementia have been considered to a lesser extent. In earlier studies, the efficacy of computer-based technology in patients with dementia was investigated and the common assumption drawn from these studies was that there was an overall improvement in patients’ cognitive performance. In particular, an overall improvement in patients’ training performance was noted, along with an improvement regarding the immediate and delayed recall of objects and routes. In addition, a significant improvement in patients’ cognitive functions such as verbal fluency and executive functions was observed. Improvement in specific cognitive areas has similarly been reported where there was a good performance in the speed of data processing in patients with dementia and an almost normal performance in the comprehension of verbal, short memory, and perception tasks compared to normal subjects’ performance. A study of 20 Korean-speaking patients found that the application of a systematic computer-based cognitive training program may have beneficial effects in various cognitive areas such as language, attention, calculation, verbal memory, and frontal function at least for a short period of time. However, in a systematic review of 31 studies that applied cognitive training in patients with mild or moderate AD, it was suggested that despite the heterogeneity and the variability of the interventions used, the outcome of those studies is that cognitive training may lead to an improvement of global cognition of the patients, particularly when these training programs are longer in duration and more intensive in nature. At the same time, it is suggested that shorter interventions that aim at specific cognitive areas may also lead to an improvement of those particular areas. Other studies further support that computer-based cognitive interventions have a positive effect in the cognitive function of dementia patients and may also target and improve specific cognitive areas. In relation to the easiness that patients with dementia can use and employ computer-based technology in their daily routine, it was found that the application of a cognitive training protocol is superior to other therapies for the cognitive improvement of patients with dementia. These intervention programs offer patients independence and account for the involvement of patients in leisure activities that promote healthier behaviors. Moreover, it has also been pointed out that it is important to tailor computer activities to each patient’s needs. Similarly, the importance of the development of person-centered tablet programs was noted as an implementation of a new service in dementia care. The utilization of information and communication technologies (ICTs) as tools to enhance the quality of life for both individuals without dementia and those affected by dementia has been investigated. Furthermore, it has been emphasized that the use of technological devices plays a crucial role in promoting a more active lifestyle for people with dementia, benefiting both their physical and mental well-being. In the same vein, concluded that since patients with dementia find their interaction with technology enjoyable, then only interesting and enjoyable activities should be employed along with innovative ways to deliver them to patients with dementia, ways that can mimic real-time communication. Even though there are a significant number of studies highlighting the positive effects of technological interventions, there are still certain studies that seem to be quite skeptical about the overall benefits that these non-pharmacological methods may in effect have. The efficacy of computer cognitive rehabilitation in patients with mild cognitive decline was tested and the results indicated that the overall computer-based cognitive training in patients with AD and mild cognitive decline is effective at least in delaying the continuous progression of cognitive impairment in AD. With respect to Greek language and Greek-speaking subjects with dementia, a relevant study presents the results of a computer-based intervention program for people with AD for a period of one year. These patients have been tested before and after each intervention program (pre-test and post-test). The authors compared these data in an effort to examine the way the program performs and at the same time to assess the cognitive skills that may be improved. It was suggested that the patients’ overall scores were preserved for this period of time and they also showed a slight improvement. The authors concluded that the application of the specific intervention program had positive effects on patients’ overall performance. Overall, the outcomes of the preceding studies indicate that the application of technology is necessary for the development of programs that can improve not only the cognitive impairments of patients with dementia and slow down the progression of the disease, but also provide a better quality of life since it reinforces a level of autonomy that is really important for the patients both emotionally and interpersonally. Further evidence for the validity of the intervention with cognitive training programs derives from a great body of neuroimaging studies that underlie the importance of the application of these programs in relation to the beneficial effects on the physiology of the brain which are beyond the scope of this work (see for example a review paper of task related fMRI studies; also studies reviewing the importance of specific brain networks and the impact that computer-based training has on them). 2.3. Studies Based on Errorless Learning One of the most promising rehabilitation strategies that has gained much interest over the last two decades and that is often adopted within the field of dementia care is that of errorless learning. Errorless learning (EL) is an approach used in memory rehabilitation and has its roots in behaviorism and, specifically, in the principles of implicit learning and memory. This approach was initially used in the research of amnestic patients who suffered from impaired explicit memory but had an intact implicit memory. EL relies on implicit memory in the sense that there is no need for a conscious retrieval of information as in explicit memory and the information to be acquired is obtained in a more passive way. Thus, EL minimizes the chance of error production during learning and maximizes the chance of encoding only correct information through modeling, immediate provision of the correct answer, etc. In the literature of EL, the bulk of studies support the effectiveness of this method as it is applied to a variety of clinical populations. 2.3.1. Errorless Learning in Healthy Older Adults Positive effects of errorless learning have been widely reported, mainly in the clinical population of amnesic patients. However, only two studies have examined this technique in relation to cognitive decline in normal ageing. A comparison of the efficacy of errorless and errorful learning on memory performance in older people and young adults showed that there was an overall lower memory performance and flatter learning curves for older adults as compared to young adults, regardless of the task conditions. However, the researchers found a superiority effect of errorless learning as compared to errorful learning, a finding that was equally evident in both groups. They suggested that the prevention of errors during learning results is essentially an effective strategy and may lead to better memory performance. 2.3.2. Errorless Learning and Dementia In a study involving participants with severe memory impairment, it was observed that they exhibited a higher capacity to learn items from word lists through errorless learning compared to an errorful control group. This advantage of EL was consistently observed in various case studies, encompassing learning object names, novel face-to-name associations, new facts, names of rehabilitation ward staff, orientation information items, and methods for programming memory aids. These findings were further substantiated by subsequent research conducted with populations of individuals with dementia and those in the early stages of AD, yielding similar outcomes. Although there may not always be unanimous agreement among researchers regarding the benefits of EL, it is noteworthy that a majority of studies emphasize the efficacy of EL procedures in ameliorating memory difficulties in individuals with dementia. For instance, a review encompassing 26 studies involving individuals with dementia, all employing EL rehabilitation strategies, revealed that even individuals with minimal to moderate dementia can successfully relearn daily life skills and sustain these abilities over an extended period. Additionally, earlier investigations explored the ability of dementia patients to recall familiar faces, name objects, and describe their uses. One study, which also aimed to enhance memory for familiar faces, suggested that EL is an efficient method yielding substantial improvements in memory. These findings align with the existing literature, demonstrating the effectiveness of errorless learning when compared to other approaches, such as error-prone learning, within patient populations. Moreover, it is worth noting that the aforementioned studies did not employ technology-based intervention programs. Instead, they established a strong foundation for the development of more efficient tools for the cognitive treatment of dementia. Later studies emphasized the need for the use of computer-based technology in cognitive intervention along with the application of EL method and provided positive results from the combined application of both, suggesting that the EL approach is highly effective for enhancing and promoting memory abilities. A study of Chinese-speaking dementia patients found that early AD subjects had an improvement in their overall cognitive function after attending the EL memory program, although the positive treatment effect had a limited duration. It was further supported that older normal adults can benefit from an EL program, as part of a preventive strategy in order to minimize the risk of developing dementia. Finally, the results of various studies comparing the effectiveness of errorless and trial-and-error methods in acquiring knowledge, ranging from very general to very specific, were presented for both individuals with dementia and healthy participants. It was concluded that the errorless learning (EL) approach appeared to be advantageous for retrieving specific knowledge, but less so for acquiring general knowledge. Furthermore, they noted that not all patients exhibited a consistent response to the learning conditions, suggesting limited applicability of this approach for patients with dementia and restricted efficiency for rehabilitating a broad spectrum of knowledge. These findings warrant further research. 2.4. Studies on Prospective Memory (PM) through Technological Applications Prospective memory is the ability to remember to perform previously planned actions or certain tasks in the future: for example, to remember and go to an already scheduled appointment, or to remember to call someone and wish for his/her birthday, or to remember to take their medication and so on—the so-called instrumental activities of daily living that ensure independent living. Prospective memory, in effect, comprises two components: the prospective component and the retrospective component. The first one has to do with remembering an action that must be carried out at a given time while the second one has to do with informational content, which must be retrieved, i.e., what we already know. This type of memory relies on other cognitive functions such as working memory, divided attention, executive functions, all of which show age-related deficits. Although prospective memory refers in effect to everyday memory and has a range of consequences if it fails, it remains an area of research that only recently has attracted more scientific interest. So far, only few studies have been conducted and investigated more thoroughly the impact that this type of memory has on the demented patients’ daily living. It is widely recognized that issues related to prospective memory are prevalent in aging, with these challenges being particularly evident in individuals with dementia. Considering that aging represents the primary risk factor for developing dementia, there is a substantial need for the development of innovative and effective interventions to aid older adults in remembering their daily activities. These interventions encompass cognitive training techniques, such as intention implementation, as well as the utilization of uncomplicated technical devices to facilitate medication reminders. A further distinction of the prospective memory has been made between event and time-based prospective memory. According to this distinction event-based prospective memory involves remembering to perform a certain action when an external cue is given, such as remembering to phone someone when a picture of him/her is provided. Time-based prospective memory involves remembering to perform a certain action at a specific time or after certain time has passed, for example taking medication ten minutes after lunch. Furthermore, in, a distinction is made between pulse intentions, which require execution at a specific time, and step intentions, which have a more flexible timeframe for completion (e.g., “I need to call the bank at some point today”). These distinctions hold significance in clinical assessments. To this end, the studies assessing prospective memory compare performance of older healthy adults to that of AD patients or traumatic brain injury (TBI) patients in a variety of tasks. Nevertheless, there is a scarcity of studies comparing the performance of patients suffering from other forms of dementia to that of healthy subjects, or investigating prospective memory in patients with dementia independently, except for the research presented in. 2.4.1. Prospective Memory and Healthy Older Subjects There are a limited number of studies so far that have addressed the issue of whether there is a link between prospective memory and daily living activities and quality of life in older adults, or the way that age related decline of prospective memory can affect the daily function of the elderly. In this line of work, it was found that the application of a computer game (the Virtual Week task) for the assessment of prospective memory, significantly aided performance of healthy older adults on related tasks. Similarly, observed a general enhancement in the prospective memory of the participants, indicating positive advantages of this training approach. In a systematic qualitative analysis, coupled with a quantitative meta-analysis on the impact of prospective memory (PM) training in older adults, it was indicated that there was a notable but modest immediate effectiveness of PM training in enhancing PM performance. However, no significant long-term effectiveness was discerned. Similarly, reviews proposed that not only the specific training strategies employed for the assessment of prospective memory need to be further examined, but also certain parameters need to be considered, such as the participants’ digital literacy as well as their motor and sensory restrictions. 2.4.2. Prospective Memory: Comparison of Healthy Subjects and Subjects with Dementia In one of the first studies that compared healthy controls to mildly affected AD patients and patients with dementia in a range of prospective memory tasks, it was proposed that on prospective memory tasks the performance of individuals with mild AD was similar to that of patients with dementia. In a later study, event-based and time-based intentions were examined in participants with AD and in healthy controls. The researchers discovered that individuals with Alzheimer’s disease (AD) exhibited poorer performance compared to healthy controls in recalling both time-based and event-based intentions. Consistent findings were reported in another study where patients with dementia demonstrated difficulties in their prospective memory, especially in the context of event-based tasks. In a study involving 14 patients with memory impairments who were assessed in two types of prospective memory tasks (event-based PM and time-based PM), each under errorless learning (EL) and errorful encoding (EF) learning conditions, the results indicate an advantage of EL for the EBPM task but not for the TBPM task. Problems with time-based intentions and event-based intentions are further supported in a more recent study. Finally, it was found that the introduction of a memory encoding strategy could improve prospective memory in healthy older adults and in patients suffering from AD. | [
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38840206 | abstract | Microglia, the brain’s resident macrophages, maintain brain homeostasis and respond to injury and infection. During aging they undergo functional changes, but the underlying mechanisms and their contributions to neuroprotection versus neurodegeneration are unclear. Previous studies suggested that microglia are sex dimorphic, so we compared microglial aging in mice of both sexes. RNA-sequencing of hippocampal microglia revealed more aging-associated changes in female microglia than male microglia, and more sex differences in old microglia than young microglia. Pathway analyses and subsequent validation assays revealed a stronger AKT-mTOR-HIF1α-driven shift to glycolysis among old female microglia and indicated that C3a production and detection was elevated in old microglia, especially in females. Recombinant C3a induced AKT-mTOR-HIF1α signaling and increased the glycolytic and phagocytic activity of young microglia. Single cell analyses attributed the aging-associated sex dimorphism to more abundant disease-associated microglia (DAM) in old female mice than old male mice, and evaluation of an Alzheimer’s Disease mouse model revealed that the metabolic and complement changes are also apparent in the context of neurodegenerative disease and are strongest in the neuroprotective DAM2 subset. Collectively, our data implicate autocrine C3a-C3aR signaling in metabolic reprogramming of microglia to neuroprotective DAM during aging, especially in females, and also in Alzheimer’s Disease. Supplementary Information The online version contains supplementary material available at 10.1186/s12974-024-03130-7. | [
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37396658 | title | The glymphatic system: a new perspective on brain diseases | []
|
38860032 | intro | 1 Introduction Robots in elderly care are increasingly targeted towards not only fulfilling practical needs, such as medication reminders or physical assistance, but also as companions to prevent and mediate loneliness through offering social and emotional support in their everyday lives, thus enhancing the psychological wellbeing of users. Research in companion robots for older adults focused primarily on pet robots, such as PARO (a seal-shaped robot), that do not have natural language processing (NLP) or generation capabilities. One of the underlying reasons is the limitations in NLP technology, leading to heavy reliance on humans to control robots, either through telepresence or the Wizard of Oz technique to give the illusion that the robot is autonomous, or by rule-based architectures that allow one-way transactional (e.g., providing medication reminders) interactions or small talk that are not suitable for daily dialogues with older adults. The recent introduction of “foundation models”, i.e., deep learning models, such as BERT, GPT-3, DALL-E, and CLIP, that are trained on broad data (often through self-supervision) that can be applied in or adapted to a wide range of downstream tasks, transformed the scope of what is achievable in many robotics applications. Most prominently, large language models (LLMs) enabled the development of companion robots with social skills due to their ability to process and produce language in an open-domain manner, without restriction on topics or concepts. Recent work incorporated LLMs for open-domain dialogue with robots in therapy, service, and elderly care domains, revealing their strengths and weaknesses in multi-modal contexts across diverse application areas. These studies underscore the versatility of LLMs in facilitating human-robot interaction (HRI). Integrating LLMs into human-robot interaction requires awareness of the user’s perceptions, needs, and preferences to ensure that these robots are aligned with human values and can successfully be employed in real-life contexts. Alignment techniques like reinforcement learning with human feedback can improve some model capabilities, but it is unlikely that an aggregate fine-tuning process can adequately represent the full range of users’ preferences and values. Participatory design (co-design) approaches enable incorporating these aspects into the design process of robots, through focus groups, interviews, concept generation and design activities, prototyping, and interactions with designed robots. These studies investigate HRI as a relational and social phenomenon, where contextual factors and longitudinal effects alter the interactions with the robot. An emphasis is based on how robots are shaped in interaction with the wider socio-cultural and physical environment into which robots are introduced. Against this background, it becomes important to explore the shared understanding of companion robots for open-domain dialogue, which influences the expectations, values, norms, and possible contradictions that older adults have towards companion robots. 1. Through a qualitative approach, identifying socially shared expectations of older adults regarding conversational companion robots for everyday life (Section 4, summarized in Table 1), 2. Formulate actionable design recommendations for integrating foundation models into these robots to meet these expectations, focusing on LLMs for their advanced linguistic capabilities, combined with vision-language models and other state-of-the-art technology for multi-modal aspects (Section 5). This study investigates older adults’ expectations towards conversational companion robots to provide social and emotional support in their daily lives, and provides design recommendations on how to achieve these expectations through foundation models. Participatory design workshops were conducted with 28 Swedish-speaking older adults, aged 65 and over (Figure 1). The workshops involved a demonstration of open-domain dialogue with an autonomous Furhat robot employing an LLM (GPT-3.5 text-davinci-003), and (6-8 participant) focus group discussions deriving from conversational design scenarios that can occur in their everyday lives. The contributions of this article encompass two key aspects: 2 Background 2.1 Companion robots for older adults Companion robots are socially assistive robots that are designed to respond to the social, emotional, and cognitive needs of older adults and enhance their quality of life, activity, and participation. Studies involving companion robots are focused on the acceptance and use among older adults and caregivers in organizational contexts (e.g.,), therapeutic effectiveness of companion robots to agitation and anxiety (e.g.,), and design features of companion robots to promote dignity and autonomy (e.g.,). A high level of individual differences in willingness to interact and establish a relationship with the companion robot has been observed in older adults. Their acceptance is influenced by functional variables related to social interaction, as well as age-related perceptions of their self-image and user-image, and individual values and aspirations. provide a recent overview of the robot types and features used in socially assistive robots for senior care. Design features of companion robots should reinforce older adults’ autonomy, dignity, and skill level, which often remains a challenge in robot design. Participatory design (co-design) has been proposed as a solution to design more inclusive and suitable companion robots for older adults, and to promote mutual learning between participants and researchers. This approach takes participants’ self-perceived thoughts and opinions into consideration and highlights factors that influence their attitudes towards robots in developing robot concepts, applications, and interaction modalities. These studies make use of interviews and focus group discussions after having been shown pictures or videos of companion robots (e.g.,), and empirical material collected in real-world settings where older adults get to engage with companion robots for short or longer period of time (e.g.,). Due to the lack of a robust solution for open-domain conversation (i.e., conversations that are not limited to any topics) that can arise in the daily lives of older adults, most prior studies that provided recommendations to design companion robots for older adults focused on non-conversational aspects based on robot pets (e.g.,). Only a few studies touched upon the potential for conversational aspects, however, these recommendations did not explore beyond one-way transactional interactions, such as providing medication reminders, exercise, entertainment, and motivation, rather than mutual everyday conversations (e.g.,). Other work solely outlined desired high-level functionality rather than providing actionable solutions (e.g., algorithms) on how to achieve the expectations of older adults for companion robots (e.g.,). In this work, we gather expectations of older adults towards conversational companion robots based on focus groups deriving from everyday situations, in addition to providing concrete suggestions on achieving the desired functionality based on foundation models, such as LLMs and other state-of-the-art architectures, which does not exist in prior work. Similarly, despite the numerous studies investigating the use of conversational companion robots with older adults, only a few studies have employed autonomous conversational robots for open-domain dialogue (e.g.,). Other studies focused on task-oriented dialogue that gives reminders, answers questions, provides weather reports, and plays games with this age group (e.g.,. The earliest study that involved an autonomous conversational robot for older adults was that of. The robot was able to recognize 300 Japanese words for daily greetings and functional commands with 47% accuracy, and respond accordingly. It was evaluated with 7 older adults on an average of 62 days. In contrast, current speech recognition systems can mostly accurately recognize more than 100 languages, with 70%–85% 1 accuracy in adult speech and 60%–80% in children’s speech. All task-oriented dialogue studies used rule-based architectures (i.e., pre-written templates for input and output responses), and only one of the open-domain dialogue studies integrated foundation models (LLMs) into a companion robot. Only one study applied co-design in the development of autonomous conversational robots with older adults. In contrast, our study integrates a foundation model (LLM) into the robot to guide participatory design with older adults and offers corresponding design recommendations to meet those expectations in conversational companion robots. In real-world applications of companion robots for older adults, there are only a few that are available for purchase, such as non-conversational robot pets (PARO robot seal 2 and Joy for All cat and dog robot toys 3 ) and ElliQ conversational desktop robot with a screen (Intuition Robotics 4 , only available for US customers). To alleviate loneliness, ElliQ proactively provides daily reminders and check-ins for health measures, gives news, weather and sports updates, makes small talk, encourages connection with family and friends, plays music, and offers games and trivia for older adults. It learns from user interactions to personalize its suggestions. However, it is unclear how this learning occurs due to proprietary software, which is updated every 3–4 weeks. The robot was deployed to older adults across 15 programs from various healthcare organizations in the US and Canada since its release in 2022. A study with 173 users who used the robot over 30 days showed that 80% agreed to feel less lonely with the robot. However, despite the effectiveness of proactivity in addressing loneliness, some users were surprised or annoyed by the proactive features. Other studies supported the negative perceptions of proactive features of the robot, such as being perceived to be talking a lot, threatening their independence, lacking compassion, and being rude, invasive, intrusive, or patronizing. Previous studies have shown that robots can help combat loneliness in older adults as companions or catalysts for social interactions. User’s self-perceived loneliness (defined as a subjective experience of lack of social connectedness with other people) is also positively associated with willingness to buy a robot companion. Nonetheless, older adults tend to think that a companion robot cannot make them feel less lonely. These studies, however, have been limited to companion robots with limited or lack of capabilities for having a (open-domain) dialogue with a human. In this study, we analyze older adults’ reflections on conversational companion robots’ roles in their daily lives to provide social and emotional support and alleviate loneliness. In addition to robots, spoken dialogue agents, such as Amazon Echo, and embodied conversational agents (i.e., virtual agents) that provide task-oriented interactions and small talk were shown to address loneliness in older adults. However, speech recognition errors and unfamiliarity with spoken dialogue systems (e.g., using a wake word and transactional commands) created adverse user reactions. Older adults did not find valuable use cases for these systems, and considered them as toys, with limited conversational capabilities being the most critical challenge in these systems. In addition, there is extensive literature that shows the benefits of robotic embodiment in improving user perceptions of the agent. Thus, this study focuses on a companion robot with open-domain dialogue capabilities. 2.2 Foundation models in conversational agents Prior research initially focused on BERT for dialogue state tracking, intent classification, and response generation (e.g.,) primarily in task-oriented dialogue, which is designed for a specific goal, such as restaurant booking. Recently, LLMs (e.g., GPT-3, LLaMA, Falcon, Pythia, Mistral) that are trained on vast amounts of textual data, showed promise for generating coherent text and speech by using prompts for inferring the context, thereby, enabling open-domain dialogue with unrestricted topics. Traditionally, LLMs have been employed within text-based chatbot systems, article generation, code generation, and copywriting ( provide an extensive survey of LLMs). On the other hand, multi-modal LLMs (e.g., GPT-4, Gemini, see for a review) combine text with audiovisual features to provide end-to-end solutions for dialogue generation in agents. To date, very few studies have empirically investigated users’ experiences of interacting with LLMs in a companion function for social and emotional support. explored the benefits and challenges of using LLMs (ChatGPT) for mental wellbeing with a conversational agent to help decrease loneliness by generating friendly or empathetic responses that simulate a conversation with a human therapist. Perceived benefits were increasing accessibility to therapists and the opportunity to receive non-judgmental support in therapy, in addition to improving self-confidence and promoting self-reflection and self-discovery. The main perceived challenges included harmful content, limited dialogue memory capacity, inconsistency in communication style, concerns about dependency on LLMs for mental wellbeing support, and the associated stigma of seeking such support from a virtual agent. For enhancing a user’s wellbeing, a key aspect of the companionship of an agent is to foster closeness, such as trust, warmth, and understanding. This involves sharing personal information, providing support, and engaging in joint activities, all facilitated by verbal and non-verbal cues, like empathy, humor, encouragement, and politeness. leveraged LLMs for a public health intervention in an open-domain chatbot to support socially isolated individuals (middle-aged adults) through check-up phone calls. Users perceived that the system helped mitigate loneliness and provided emotional support through empathetic questions about their health, hobbies, and interests. However, it was perceived as impersonal due to the lack of follow-up questions on past conversations. While various foundation models are used in robotics for manipulation, navigation, planning, and reasoning, only LLMs are used in the context of conversational robots. For instance, LLMs have been used for developing conversational robots with empathetic non-verbal cues, giving adaptive presentations, functioning as a receptionist, and supporting wellbeing of older adults. is the only study that integrated an LLM (fine-tuned GPT-3) into a companion robot for open-domain dialogue with (7) older adults, in addition to our prior work. Most participants in that study found the interaction with the robot enjoyable, felt comfortable with it, and perceived it as friendly. However, the individual willingness to use the robot varied among participants, with some suggesting that it might be more suitable for older adults with dementia. However, the study did not incorporate older adults’ perspectives on applying LLMs to companion robots through a co-design approach. In our prior study, we investigated the challenges of applying LLMs to conversational robots, deriving from the one-on-one interactions of a robot with LLM with older adults, that were conducted after the discussions in the design scenarios. The challenges were found to be affected by the multi-modal context of conversations with robots that go beyond the textual linguistic capabilities of LLMs, leading to frequent interruptions, repetitive and superficial conversations, language barriers, and confusion due to outdated and incorrect information. In contrast, in this work, we investigate the expectations of older adults using thematic analysis of the focus groups, followed by design recommendations to apply these expectations to conversational companion robots with foundation models. | [
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25058312 | title | Dual blockade of the A1 and A2A adenosine receptor prevents amyloid beta toxicity in neuroblastoma cells exposed to aluminum chloride. | [
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39088385 | intro | Introduction Repeated sub-concussive head impacts are increasingly recognised to have detrimental effects on the brain. For instance, repeated sub-concussive head impacts negatively alter white matter tract integrity, reduce cortical thickness, and impair cognitive functions in both animals and humans. Although sub-concussive head impacts can have various origins, such as falls and automobile collisions, contact sports constitute an increasingly important vector of head impacts. For instance, a history of sport-related head impacts increases the risk of developing neurodegenerative diseases and/or cognitive impairments in American as well as European football players. Given that head impacts are modifiable risk factors, and that the socioeconomic burden of neurodegenerative diseases is increasing worldwide, there is a pressing need to characterize the full effects of sub-concussive head impacts on brain health using randomised controlled experimental settings. In this light, one of this work’s objectives was to provide a randomised controlled human experimental model to study the effects of sub-concussive head impacts on the brain. Similar to work on concussions, such systematic investigations could ultimately lead to recommendations to attenuate (or manage) the detrimental effects of head impacts on the brain. One crucial feature of brain health is the maintenance of a balance between brain excitation and inhibition, as any imbalances in brain excitability are associated with a range of psychiatric symptoms. Interestingly, converging work indicates that head impacts deteriorate brain health by–amongst other mechanisms–altering brain excitability. Importantly, changes in brain excitability can be readily assessed in humans, offering a unique opportunity to obtain insights into the effects of head impacts on brain health. For instance, Di Virgilio et al. (2016; ref) used a battery of cognitive tests and transcranial magnetic stimulation (TMS) to assess how head impacts from heading 20 footballs over 10 minutes alter cognitive functions and brain excitability. Their results showed that the football headings acutely impaired working memory and declarative learning performances. Moreover, the results also showed that the headings acutely increased the duration of the corticospinal silent period (CSP), a TMS-derived change in brain excitability believed to reflect increased gamma-aminobutyric acid (GABA)ergic-mediated inhibition in the corticospinal tract. Overall, these findings suggest that sub-concussive head impacts alter brain excitability by increasing inhibition (for similar results, see refs), in turn impairing cognitive functions. Not unexpectedly, this work attracted considerable mediatic attention, notably in the form of a documentary (see ref). However, it remains unclear if the brain excitability changes were caused by the football headings because the results were crucially not compared to a control group that did not experience head impacts. Despite this limitation, the protocol used by the authors constitutes a promising experimental model because it allows to experimentally induce head impacts in a controlled environment. Furthermore, changes in CSP duration constitute a promising biomarker of GABAergic inhibition to investigate changes in brain excitability, as measuring CSP is non-invasive, can be easily and quickly measured, and its utility to evaluate changes in brain excitability is supported by work on both concussive (reviewed in ref) and sub-concussive head impacts (reviewed in ref). Overall, this evidence suggests that measuring changes in CSP duration before and after performing football headings constitutes a promising human experimental model to characterise the effects of head impacts on brain excitability. Based on this background evidence, this work’s primary objective was to substantiate the possibility that football headings can be used as a randomised controlled experimental model to study the acute effects of head impacts on brain functions. To achieve this, this work’s second objective was to build on the results from Di Virgilio et al. (2016; ref) using a randomised controlled trial–by adding an appropriate control group–to ascertain that the changes in CSP duration originate from head impacts. Namely, TMS was used to assess changes in CSP duration before and immediately after groups of practised and unpractised young healthy adults performed (Headings; n = 30), or not (Control; n = 30), 20 football headings. It was hypothesised that CSP would acutely lengthen in response to the head impacts (as in ref) and as compared to the control group. In addition, the Rivermead Post-Concussion Questionnaire was used to evaluate head impact symptoms before and after the intervention. Head accelerometer data were also recorded in subgroups of participants from the Headings (n = 10) and Control groups (n = 10). It was hypothesised that the football headings would increase generic head impact symptoms, such as headaches and dizziness, and manifest as greater head acceleration as compared to the control intervention. | [
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35173173 | abstract | Early-onset familial Alzheimer’s disease (AD) is marked by an aggressive buildup of amyloid beta (Aβ) proteins, yet the neural circuit operations impacted during the initial stages of Aβ pathogenesis remain elusive. Here, we report a coding impairment of the medial entorhinal cortex (MEC) grid cell network in the J20 transgenic mouse model of familial AD that over-expresses Aβ throughout the hippocampus and entorhinal cortex. Grid cells showed reduced spatial periodicity, spatial stability, and synchrony with interneurons and head-direction cells. In contrast, the spatial coding of non-grid cells within the MEC, and place cells within the hippocampus, remained intact. Grid cell deficits emerged at the earliest incidence of Aβ fibril deposition and coincided with impaired spatial memory performance in a path integration task. These results demonstrate that widespread Aβ-mediated damage to the entorhinal-hippocampal circuit results in an early impairment of the entorhinal grid cell network. It remains poorly understood how the onset of Alzheimer’s disease affects spatial cognition. Here, the authors report that spatial coding in grid cells deteriorates over time in a mouse model of Alzheimer’s disease during the early stages of pathology while place cell and head direction coding remain intact. | [
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39360232 | abstract | Introduction The number of dementia patients is increasing with population aging. Preclinical detection of dementia in patients is essential for access to adequate treatment. In previous studies, dementia patients showed texture recognition difficulties. Onomatopoeia or sound symbolic words (SSW) are intuitively associated with texture impressions and are less likely to be affected by aphasia and description of material perception can be easily obtained. In this study, we aimed to create a test of texture recognition ability expressed by SSW to detect the presence of mild cognitive disorders. Methods The sound symbolic words texture recognition test (SSWTRT) is constructed from 12 close-up photos of various materials and participants were to choose the best SSW out of 8 choices to describe surface texture in the images in Japanese. All 102 participants seen in Juntendo University Hospital from January to August 2023 had a diagnosis of possible iNPH (age mean 77.9, SD 6.7). The answers were scored on a comprehensive scale of 0 to 1. Neuropsychological assessments included MMSE, FAB, and the Rey Auditory Verbal Learning Test (RAVLT), Pegboard Test, and Stroop Test from the EU-iNPH Grading Scale (GS). In study 1 the correlation between SSWTRT and the neuropsychological tests were analyzed. In study 2, participants were divided into two groups: the Normal Cognition group (Group A, n = 37) with MMSE scores of 28 points or above, and the Mild Cognitive Impairment group (Group B, n = 50) with scores ranging from 22 to 27 points, and its predictability were analyzed. Results In study 1, the total SSWTRT score had a moderate correlation with the neuropsychological test results. In study 2, there were significant differences in the SSWTRT scores between groups A and B. ROC analysis results showed that the SSWTR test was able to predict the difference between the normal and mildly impaired cognition groups. Conclusion The developed SSWTRT reflects the assessment results of neuropsychological tests in cognitive deterioration and was able to detect early cognitive deficits. This test not only relates to visual perception but is likely to have an association with verbal fluency and memory ability, which are frontal lobe functions. | [
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38248857 | intro | 1. Introduction Blood analysis occupies a prominent part within the domains of clinical diagnostics and scientific research, particularly from the perspective of mass spectrometry (MS). Traditionally, the examination of human venous blood involves substantial volumes, often in the range of 100–200 mL, with adjustments made in animal studies according to the species under investigation. Following initial collection, centrifugation separates the whole blood components into plasma and red blood cells, preparing the ground for the subsequent analysis. The next phase entails the utilization of solvents and detergents to extract a variety of bioactive substances, including proteins, glycans, peptides, lipids, and amino acids, from serum or plasma. This carefully extracted array of compounds is subjected to separation by advanced techniques such as chromatography or electrophoresis, although MS stands as the foundation of this investigative process. As an analytical technique, MS ionizes molecules within the sample, speeds them up, and evaluates the ratio of their mass to charge. This methodology aids not only in the identification of specific molecules within the sample but also in the precise quantification of their abundance through robust statistical data processing. In the context of this review, we undertook a thorough exploration of a rich collection of published data related to blood sample processing via MS. Notably, over 80% of the studies were primarily concentrated on cancer, oncology, and carcinogenesis. While cancer reach is undeniably of essential significance, this exclusive focus has at times overshadowed the other crucial applications of MS in blood analysis. Numerous methodologies for non-cancer disease profiling have achieved a level of development that enables their direct translation into clinical practice. Therefore, this review is strategically focused on 814 articles that employ MS for blood profiling in both fundamental and applied research, including GC×GC-MS for metabolomics-based studies. To navigate through the hard task of analyzing such a vast number of studies, we utilized natural language processing methods in order to cluster the studies based on their thematic content. Additionally, trainable text classifiers were deployed to enhance our analysis of this multifaceted research domain. Our methodology is described in the Section 2, and the basic scientometric analysis of the field is presented in the Section 3. Within our manual analysis, we organized our findings into three distinct sections. The Section 4 offers a brief explanation of MS methods to facilitate a better comprehension of the technical aspects. The other two sections are devised to reflect the contents of the studies found. Thus, MS, along with metabolomics applications in blood profiling, could be viewed from two perspectives: as a certain class of metabolite studies or with reference to certain diseases. Therefore, we offer two principal sections of studies according to these two perspectives. The first section, entitled Research Field Landscape, presents an exploration of various fields of metabolomics, based on studied metabolites classes, such as ’lipidomics’, and ’glycomics’. This section provides definitions for each area of metabolomics that is integrated in some way with blood profiling using the MS approach. It explores the structure of analyzed substances, their functional roles in the organism, and their involvement in the pathogenesis of non-cancer diseases; moreover, it outlines the clinical applications. The second section, Disease Study Landscape, contains a comprehensive review of several socially significant non-cancer diseases of inflammatory, bacterial, rheumatoid, and other natures. Each disease is provided with a brief summary, marked symptoms, and known methods of diagnostics. Each disease description includes particular metabolites that are often either not analyzed in the profiling of the diseases reviewed or serve as other potential compounds. All such metabolites are reviewed in the Section 5. Therefore, we fill the gap between the application of known metabolites and their potential usage in the diagnosis and management of non-cancer diseases. This review is intended to serve as a needed resource for researchers, clinicians, and practitioners to enable them to take advantage of the MS approach in the realm of non-cancer blood metabolomics. It provides critical insights, highlights methodological advancements, reveals promising opportunities beyond the predominant cancer-centric paradigm, and remarks on the incorporation of GC×GC-MS for metabolomics-based studies. | [
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36189598 | abstract | BACKGROUND: DNA methylation is expected to become a kind of new diagnosis and treatment method of Alzheimer's disease (AD). Neuroinflammation- and immune-related pathways represent one of the major genetic risk factors for AD. OBJECTIVE: We aimed to investigate DNA methylation levels of 7 key immunologic-related genes in peripheral blood and appraise their applicability in the diagnosis of AD. METHODS: Methylation levels were obtained from 222 participants (101 AD, 72 MCI, 49 non-cognitively impaired controls). Logistic regression models for diagnosing AD were established after least absolute shrinkage and selection operator (LASSO) and best subset selection (BSS), evaluated by respondent working curve and decision curve analysis for sensitivity. RESULTS: Six differentially methylated positions (DMPs) in the MCI group and 64 in the AD group were found, respectively. Among them, there were 2 DMPs in the MCI group and 30 DMPs in the AD group independent of age, gender, and APOE4 carriers (p < 0.05). AD diagnostic prediction models differentiated AD from normal controls both in a training dataset (LASSO: 8 markers, including methylation levels at ABCA7 1040077, CNR1 88166293, CX3CR1 39322324, LRRK2 40618505, LRRK2 40618493, NGFR 49496745, TARDBP 11070956, TARDBP 11070840 area under the curve [AUC] = 0.81; BSS: 2 markers, including methylation levels at ABCA7 1040077 and CX3CR1 39322324, AUC = 0.80) and a testing dataset (AUC = 0.84, AUC = 0.82, respectively). CONCLUSION: Our work indicated that methylation levels of 7 key immunologic-related genes (ABCA7, CNR1, CX3CR1, CSF1R, LRRK2, NGFR, and TARDBP) in peripheral blood was altered in AD and the models including methylation of immunologic-related genes biomarkers improved prediction of AD. | [
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39315314 | methods | METHODS Scoping review approach This review was conducted in accordance with the Preferred Reporting Items for Systematic reviews and Meta‐Analyses extension for Scoping Reviews (PRISMA‐ScR) guidelines, and research was guided by Arksey and O'Malley's scoping review framework. The review protocol was registered on PROSPERO (registration number: CRD42022303526), published and is part of the “Social Connection in Long‐Term Care Home Residents” (SONNET) study. Conceptual model of social connection Social connection: An umbrella term encompassing aspects of how individuals connect to each other. It depends on the existence, roles, and qualities of relationships and the sense of connection within these relationships. Social networks: Web of relationships that surround an individual and the characteristics of those ties. Social interaction: An interpersonal process by which individuals in contact temporarily change their behaviors towards each other by a continuous mutual stimulation; this can be verbal and/or nonverbal, positive or negative, and between two or more individuals. Social engagement: Taking part in activities within the communities in which people live. This may include productive activities, social activities, or leisure activities. Social support: Exchange of resources between at least two individuals intended to enhance the well‐being of the recipient. This may include emotional (expressions of empathy, love, trust, caring), instrumental (tangible help), informational (advice, suggestions, information) and appraisal (information for self‐evaluation) support. Social isolation: Lack of (or limited) social contact with others. Social connectedness: The extent to which one feels that they have meaningful, close, and constructive relationships with others; it is the opposite of loneliness. Loneliness: Negative experience resulting from the discrepancy between an individual's desired and actual experience of meaningful connections. This may include emotional loneliness (lack of close intimate attachment to another person, or feeling isolated or alone) or social loneliness (lack of connection with a social network, or feeling left out). We developed this conceptual model depicting how the aspects of social connection are related to each other (see Figure 1). We built on a model originally proposed by Berkman et al. to explain the relationship between social connection and health and adapted for research in nursing homes by Leedahl et al. We added other aspects of social connection (ie, loneliness, social connectedness, social interaction, and social isolation). These definitions, articulated a priori, will help to ensure social connection is consistently conceptualized throughout the study, including in the study selection and data analysis. Identified measures will be analyzed according to these definitions: While the aspects of social connection are distinct, bidirectional arrows are used to acknowledge that they are related. Our model demonstrates that the aspects of social connection exist on continuums of being experienced by the individual and observed by others. Further, while some aspects of social connection may be objective others are, by definition, more subjective. We will select measures from the literature that have items assessing any of these aspects of social connection. Overall, selected measures will reflect the presence or absence of social connection that LTC home residents experience. RESEARCH IN CONTEXT Systematic review: We searched eight bibliographic databases, MEDLINE ALL (Ovid), Embase Classic and Embase (Ovid), Emcare Nursing (Ovid), APA PsycInfo (Ovid), Scopus, CINAHL Complete (EBSCOhost), AgeLine (EBSCOhost), and Sociological Abstracts (ProQuest), for published research studies reporting on the psychometric testing or development of a measure which assessed any aspect of social connection in long‐term care (LTC) home residents. Interpretation: Our findings clarify how social connection has been defined and assessed in LTC home residents and details how dementia and non‐dementia‐specific measures differ according to content, mode of administration, and scoring options. These results will guide measure selection, and future development of new measures for interventional and observational research targeting social connection. Future directions: There are a variety of measures available to assess the aspects of social connection in LTC home residents. Future research should use this study's results to inform choice of outcome measure, taking into account their psychometric properties. Comprehensive literature search Eight electronic databases, MEDLINE ALL (Ovid), Embase Classic and Embase (Ovid), Emcare Nursing (Ovid), APA PsycInfo (OVID), Scopus, CINAHL Complete (EBSCOhost), AgeLine (EBSCOhost), and Sociological Abstracts (ProQuest), were searched for published research studies on psychometric properties of a measure of any aspect of social connection, tested in LTC home residents. Two searches were conducted as recommended by de Vet et al. Searches were developed in MEDLINE ALL (Ovid) and translated into all the other databases (Appendix S1). Search 1 was conducted from database inception to November 18, 2021 and consisted of (1) the construct of interest, aspects of social connection (as defined above in the conceptual model); (2) the population, LTC home residents (as defined using the international definition, “adults living in residential facilities, whose staff provide help with most or all daily activities and 24‐h care and supervision”); and (3) measurement properties, using the COnsensus‐based Standards for the selection of health Measurement INstruments (COSMIN) search filter. When possible, limits were applied to focus on human adult studies and journal articles. No date or language limits were applied. Search 2 was conducted from inception to April 5, 2022 and consisted of (1) the construct of interest, names of measures identified from the first search, supplemented with a list of measures used in previous research in this population, identified from systematic reviews of psychometric measurement of linked concepts in LTC homes, or reviews of psychosocial interventions in LTC homes (full list in Appendix S2); (2) the population, LTC home residents; and (3) measurement properties. Reference lists of pertinent review articles were also scanned to identify potential additional relevant studies. Study selection Inclusion criteria Studies were included if (1) they reported on a measure that assessed any aspect of social connection, including a subscale(s) or item(s) that were reported separately (eg, a quality of life measure with a social connection subscale); (2) the study aim was to develop or evaluate at least one psychometric property of a measure of social connection; and (3) the population consisted of older adults (mean age of 65 years or older [or at least two thirds of participants were 65 years and older]), of whom at least 2/3 were living in a LTC home (or <2/3 if results were presented for LTC home residents separately). Exclusion criteria Secondary texts, literature reviews, conference abstracts, editorials, and dissertations were excluded as they did not have sufficient detail regarding the study design. Grey literature was excluded as it is unlikely to report on a measure's development or testing. Studies were also excluded if the complete wording of the measure's items could not be located; extensive effort went into obtaining measures including emailing lead and co‐authors (authors were emailed up to five times before search efforts ceased) and looking at studies which used/cited the measure. Identifying relevant studies Citations were imported into Covidence (www.covidence.org) for duplicate removal and study selection. A pilot test of 15 papers (titles and abstracts) was conducted to familiarize reviewers with eligibility criteria. Following the pilot test, titles and abstracts were screened and full‐text review was conducted independently by two reviewers (M.L., A.S., or J.B.). Non‐English papers were assessed by additional reviewers with relevant language and research expertise. Reasons for exclusion at full‐text review were recorded. Reviewers met regularly to compare results. Any disagreements that arose in the screening or full‐text review were resolved through discussion. Charting the data Data were extracted independently by two of the three reviewers listed (M.L., A.S., or J.B.) using standardized instructions and a data extraction form which contained the following fields: record ID, author(s), study publication year, study title, population (country, race/ethnicity, inclusion criteria, exclusion criteria, sample size—number of residents and homes, gender/sex, age), measure name, mode of administration, and scoring options. Measures were classified as dementia‐specific if they were designed exclusively for assessing individuals with dementia or classified as non‐dementia‐specific otherwise. Qualitative analysis Collating, summarizing, and reporting results The Framework Method was used to manage and analyze the qualitative data of this content analysis. Adaptations were made, summarized below, to accommodate the hybrid deductive‐inductive approach that integrates theory‐driven codes at first‐level coding with data‐driven codes at second‐level coding. Transcription and familiarization Names of measures and their social connection items were transcribed verbatim in an electronic document, noting the source as dementia or non‐dementia‐specific as well as mode of administration and scoring options. M.L. kept reflective notes on how items aligned with the aspects of social connection (Figure 1) as well as initial observations of how items from dementia and non‐dementia‐specific measures differed. Given the codes were predefined (ie, using the aspects of social connection), the analysis proceeded from this stage directly to indexing. Applying the analytical framework During first‐level (deductive) coding, the research team applied the aspects of social connection as previously defined in the literature and which informed the conceptual model. Each item was mapped to a code (ie, aspect of social connection) independently by two researchers (M.P.L., A.S., K.S.M., H.M.O., J.B.). The item's wording, mode of administration, and scoring options were considered in the coding. During this stage, social interaction was added as a distinct aspect of social connection and the “other” code was created to accommodate items within measures which did not align with any of the social connection codes. Inter‐coder agreement was calculated. Coding disagreements were resolved through a discussion between all five researchers (M.P.L., A.S., K.S.M., H.M.O., J.B.). Charting the data into the framework matrix A Framework Method table was created to manage and analyze the first‐level (deductive) coding. Measures (including those with standalone items) and subscales were assumed to represent a construct and were thus reported and analyzed separately. Rows were labelled with names of measures, columns were labelled as the codes (ie, aspects of social connection) and cells contained items mapped by row and column coordinates. Interpreting the data The data were interpreted in three steps. First, each measure was summarized according to the code(s) to which it was mapped and whether it was mapped to multiple codes; dementia and non‐dementia‐specific measures were compared by tabulating the presence of codes. Second, second‐level coding employing an inductive, data‐driven approach was applied to identify and describe themes within codes and compare them across dementia and non‐dementia‐specific measures. In this step, M.L. independently defined second‐level codes and then revised and edited them after discussion with the research team; full consensus on second‐level codes was achieved. Third, dementia and non‐dementia‐specific measures were compared by aspects of social connection assessed, mode of administration and scoring options. Multiple steps were taken to ensure rigor throughout the coding process. Trustworthiness and credibility were ensured by practicing reflexivity, establishing a physical audit trail, peer debriefing, systematically managing data, and examining contrary explanations during data analysis. Stakeholder consultation Virtual, 1‐ to 2‐hour, group stakeholder consultations were held on September 15, 2022, February 16, 2023, and three, 30‐min one‐on‐one consultations during March 2023. Each consultation was held on Zoom, and the research team took notes throughout. Stakeholders were people with lived experience of dementia and LTC homes and were identified through their involvement with the Canadian Consortium on Neurodegeneration in Aging's Engagement of People with Lived Experience of Dementia (EPLED) program (www.epled.ca) and the UK Alzheimer's Society Research Network. This step provided opportunities for people with lived experience to assist with interpreting data by offering insights outside the realm of research literature. At September's meeting, stakeholders received information and commented on the study methods. During the February and March meetings, stakeholders contributed to interpreting results, particularly Figure 2, as they helped researchers to understand if measures used to assess social connection contain relevant items and if some aspects of social connection are particularly important to assess. These discussions were guided by the questions: (1) Do you feel that second‐level codes describing the aspects of social connection reflect your personal experiences? and (2) From your experience, are any of these aspects of social connection particularly important to LTC care home residents? | [
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39107774 | title | Impairment of Nrf2 signaling in the hippocampus of P301S tauopathy mice model aligns with the cognitive impairment and the associated neuroinflammation | [
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37954593 | results | Results Study subjects Sixty-five adults living with HIV-1 for a mean (SD) duration of 20.0 (8.0) years, were recruited at the University Hospitals of Nîmes and Montpellier, France. Eleven percent of them were females, and 89% males. Their mean age was 62.2 (4.0) years. They were of European, African, and Asian origin for 88%, 9% and 3%, respectively. Their pretherapeutic CD4 count was 168 (140) cells/μL, their current CD4 count was 633 (245) cells/μL, and their current CD4/CD8 ratio 0.92 (0.46). All had undetectable viral loads, except for a maximum of two blips (transient elevation of viral load ≥ 200 copies/mL). Their educational level was grade school (15%), high school (49%), or college (36%) and thirty-one of them were being treated for depression. Frequencies of tobacco and drug consumption were 42% and 38%, respectively. Eight percent were HBV-infected and fifteen percent HCV-infected ( Table 1 ). Their prevalence of diabetes, high blood pressure and cardiovascular disease is indicated in Table 1 . Correlations between activation markers and clinical NCI Thirty-eight percent of participants were classified as HAND, 24% with ANI and 14% with MND; none presented dementia. There was no difference in CD4 nadir between volunteers with ANI or MND or without NCI (p = 0.390). Presence or absence of ANI or MND was neither linked to antiretroviral therapy including a nucleotide reverse transcriptase inhibitor (p = 0.104), a non-nucleotide reverse transcriptase inhibitor (p = 0.826), a protease inhibitor (p = 0.463), nor an integrase strand transfer inhibitor (p = 0.839). We determined the proportions and absolute numbers of the following subpopulations: (i) activated (CD38+, CD38hi, and/or HLA-DR+), exhausted (PD-1+), senescent (CD57+, eventually CD27- and eventually CD28-), naïve (CD45RA+CD27+), central (CD45RA-CD27+) and effector (CD45RA-CD27-) memory CD4+ and CD8+ T cells, and (ii) activated (HLA-DR+), dysfunctional (CD56-), and senescent (CD57+) NK cells. Monocyte activation was evaluated by measuring sCD163. Inflammation was monitored by quantifying sTNFRI. tPA, and sEPCR were used as markers of endothelium activation. Fifty-nine activation markers were thus quantified. We searched for differences in the various markers we measured between volunteers with or without cognitive impairments. Participants without NCI tended to present higher lymphocyte (1851 ± 656 vs. 1511 ± 820 cells/μL, p = 0.025, adjusted p non-significant, Figure 1A ) and T cell + (1292 ± 526 vs. 1120 ± 516 cells/μL, p = 0.143, adjusted p non-significant, Figure 1B ) counts than participants with ANI or MND. Strikingly, the proportion of activated, HLA-DR+, CD4+ T cells (19.0 ± 8.4 vs 27.5 ± 13.5%, p = 0.004, adjusted p = 0.049, Figure 1C ), was lower in patients with ANI or MND than in patients without any NCI. Concerning T8 cells, the percentage of CD8+ T cell (46.0 ± 11.1 vs. 51.8 ± 11.1%, p = 0.004, adjusted p = 0.049, Figure 1D ), and the number of activated, HLA-DR+ (290 ± 219 vs. 473 ± 263 cells/μL, p = 0.002, adjusted p = 0.043, Figure 1E ), and HLA-DR+CD38+ (106 ± 102 vs 169 ± 136 cells/mL, p = 0.001, adjusted p = 0.039, Figure 1F ) CD8+ T cells was also lower in individuals with NCI than in individuals without. In addition, senescent, CD57+CD28- CD4+ (108 ± 93 vs 223 ± 170 cells/μL, p = 0.001, adjusted p = 0.039, Figure 1G ) and CD57+CD28-CD27- CD8+ (82 ± 83 vs 170 ± 148 cells/μL, p = 0.002, adjusted p = 0.043, Figure 1H ) were less common in the peripheral blood of NCI patients than in patients without neurocognitive disorders. In the search for potential confounding factors, we used linear regression to test whether age, sex, education level, depression or alcohol consumption were associated with NCI in our small cohort. None of these variables were linked to ANI or MND (data not shown). A linear discriminant analysis showed that these 6 biomarkers (percentages of CD8+ T cells and HLA-DR+ CD4+ T cells, numbers of HLA-DR+ CD8+ T cells, HLA-DR+CD38+ CD8+ T cells, CD57+CD28- CD4+ T cells and CD57+CD28-CD27- CD8+ T cells) were able to predict the presence of NCI with an accuracy of 77%. Moreover, a genetic algorithm analysis revealed that only two markers, the percentage of HLA-DR+ CD4+ T cells and the number of CD57+CD28- CD4+ T cells were able to predict ANI and MND with 73% accuracy, 76% sensitivity, and 70% specificity. Other solutions are indicated in Table 2 . Correlations between activation and WMH We also used magnetic resonance imaging to analyze periventricular and deep WMH in the central nervous system based on 3D FLAIR images. Lesions were scored using the Fazekas scale in 56 participants. For periventricular lesions, 12, 54, 25, and 9% of participants scored 0, 1, 2, and 3, respectively. For deep lesions, 9, 59, 16, and 16% participants scored 0, 1, 2, and 3, respectively. Periventricular and deep white matter lesions were strongly correlated (r = 0.891, p < 10-4). We then sought correlations between the 6 activation markers identified as being linked to NCI and WMH. We observed that the percentage of HLA-DR+ T4 cells was higher in volunteers with a periventricular (29.2 ± 14.6 vs 18.5 ± 8.7%, p = 0.004, Figure 2A ) or a deep (28.6 ± 15.0 vs. 19.3 ± 8.2%, p = 0.017, Figure 2B ) Fazekas score of 0 or 1 than in volunteers a with a periventricular Fazekas score of 2 or 3. Identification of immune activation profiles presented by 240 immunological responders In a group of 140 virological responders, we previously showed that different immune activation profiles may be distinguished using a double hierarchical clustering analysis. Such a global unsupervised approach offers an opportunity to have a look at the links between causes, phenotypes, and consequences of immune activation. Indeed, we have observed that some of these profiles may be linked to different sources of immune activation, as microbial translocation or residual viremia. Moreover, some of these profiles could pave the way to some comorbidities, as insulin resistance for instance. Therefore, we wanted to test whether NCI might be linked to one immune activation profile. To this aim, we added the activation marker values of 100 PLWH, in order to increase the robustness of the immune activation profiles, including the 65 volunteers for whom we had measured neurocognitive ability to those of the 140 PLWH we had previously analyzed to reach a total of 240 PLWH for our analysis. These 41 females and 199 males were 56.4 (9.2) years old. They had been living with HIV-1 for 16.5 (8.5) years. Their pre-therapeutic CD4 counts and current CD4 counts were 185 (138) and 710 (355) cells/mL, respectively. They presented a CD4/CD8 ratio of 1.07 (0.76). As previously described, we then performed a double hierarchical clustering analysis again, using the following activation markers: sCD163, sTNFRI, tPA, sEPCR, the percentage of activated (CD38+, CD38hi, and/or HLA-DR+), exhausted (PD-1+), senescent (CD57+, eventually CD27- and eventually CD28-), naïve (CD45RA+CD27+), central (CD45RA-CD27+) and effector (CD45RA-CD27-) memory CD4+ and CD8+ T cells, as well as activated (HLA-DR+), dysfunctional (CD56-), and senescent (CD57+) NK cells. Percentages were preferred to absolute numbers as these are more stable over time. Figure 3 shows that 6 different immune activation profiles could be identified in these 240 patients. In this heat map, activation markers were classified vertically and patients horizontally. Activation markers which tend to be increased or decreased simultaneously were classified close to each other, whereas independent markers were separated from one another. Patients in the same horizontal cluster (“Profile”) are characterized by the same marks of immune activation. The hierarchical clustering gathered patients according to their type of immune activation. We looked for one specific marker able to characterize each profile. Patients with Profiles 1 and 2 had the lowest percentages of CD4+ T cells expressing the senescent marker CD57 (2.2 ± 1.9 versus 8.8 ± 8.1%, p < 10-4, Figure 4A ), and the highest percentages of CD8+ T cells expressing the activation marker CD38 (57.3 ± 13.3 versus 37.1 ± 12.8%, p < 10-4, Figure 4B ), respectively. In Profile 3 patients, it was the low CD4 count that was most remarkable (576 ± 250 versus 712 ± 382%, p = 0.044, Figure 4C ). Patients with Profiles 4 and 5 had the highest levels of the monocyte activation marker sCD163 (974 ± 466 vs. 858 ± 535 pg/mL, p = 0.048, Figure 4D ) and the highest levels of the endothelial activation marker tPA (16.4 ± 9.8 versus 11.3 ± 7.0%, p = 0.007, Figure 4E ), respectively. Finally, Profile 6 was characterized by the highest proportions of CD4+ T cells expressing the activation marker HLA-DR (44.9 ± 13.7 versus 20.4 ± 9.6%, p < 10-4, Figure 4F ). Characterization of immune activation profiles linked to neurocognitive disorder Next, we focused on the 65 PLWH whose neurocognition had been evaluated. Compared with the other volunteers, patients with Profile 1 more often presented neurocognitive disorders (odds ratio 18.67, 95% CI [0.984; 354.5] (p=0.010), Figure 5A ). As Profile 1 is particularly associated with neurocognitive impairment, we further characterized this Profile by searching for additional immune activation markers specific to it. In addition to a low proportion of senescent T4 cells ( Figure 5C ), Profile 1 volunteers were remarkable for their low frequency of senescent T8 cells (19.6 ± 8.7 versus 37.3 ± 11.4%, p < 10-4, Figure 5D ), as well as the low frequency of activated (HLA-DR+) T4 cells (14.5 ± 4.6 versus 24.8 ± 13.2%, p < 10-4, Figure 5E ) and T8 cells (44.7 ± 16.3 versus 60.0 ± 17.9%, p < 10-4, Figure 5F ). We compared these percentages with the standard values we had previously established in an age-matched general population. Strikingly, Profile 1 patients had proportions of activated T4 cells ( Figure 5E ) and T8 cells ( Figure 5F ) similar to those of controls and proportions of senescent T4 cells (2.2 ± 1.9 versus 5.9 ± 7.8%, p = 0.004, Figure 5C ) and T8 cells (19.0 ± 8.4 versus 29.2 ± 16.4%, p < 0.001, Figure 5D ) that were even lower than those of controls. Another group of patients, with Profile 3, had the second highest frequency of NCI (53%). Thus, Profile 1 and 3 patients more often presented neurocognitive disorders than Profile 2, 4, 5 or 6 patients (odds ratio 4.727, 95% CI [1.492; 14.98] (p=0.010), p = 0.011, Figure 5B ). Here again, compared with Profile 2, 4, 5, and 6 patients, patients with Profile 3 were characterized by a low percentage of HLA-DR+ T4 cells (20.5 ± 9.1 versus 25.9 ± 13.9%, p = 0.021, Figure 5E ), HLA-DR+ T8 cells (51.2 ± 16.6 versus 62.3 ± 17.5%, p = 0.001, Figure 5F ), CD57+ T4 cells (3.8 ± 3.1 versus 10.2 ± 8.5%, p < 10-4, Figure 5C ), and CD57+ T8 cells (20.0 ± 9.0 versus 37.3 ± 11.4%, p < 10-4, Figure 5D ). | [
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39188236 | title | Exploring experiences of ageing in older adults living with HIV in Sweden: a qualitative study | []
|
38774517 | title | Effect of time-restricted eating and intermittent fasting on cognitive function and mental health in older adults: A systematic review | []
|
38564243 | abstract | Background Both alcohol consumption and HIV infection are associated with worse brain, cognitive, and clinical outcomes in older adults. However, the extent to which brain and cognitive dysfunction is reversible with reduction or cessation of drinking is unknown. Objective The 30-Day Challenge study was designed to determine whether reduction or cessation of drinking would be associated with improvements in cognition, reduction of systemic and brain inflammation, and improvement in HIV-related outcomes in adults with heavy drinking. Methods The study design was a mechanistic experimental trial, in which all participants received an alcohol reduction intervention followed by repeated assessments of behavioral and clinical outcomes. Persons were eligible if they were 45 years of age or older, had weekly alcohol consumption of 21 or more drinks (men) or 14 or more drinks (women), and were not at high risk of alcohol withdrawal. After a baseline assessment, participants received an intervention consisting of contingency management (money for nondrinking days) for at least 30 days followed by a brief motivational interview. After this, participants could either resume drinking or not. Study questionnaires, neurocognitive assessments, neuroimaging, and blood, urine, and stool samples were collected at baseline, 30 days, 90 days, and 1 year after enrollment. Results We enrolled 57 persons with heavy drinking who initiated the contingency management protocol (mean age 56 years, SD 4.6 years; 63%, n=36 male, 77%, n=44 Black, and 58%, n=33 people with HIV) of whom 50 completed 30-day follow-up and 43 the 90-day follow-up. The planned study procedures were interrupted and modified due to the COVID-19 pandemic of 2020-2021. Conclusions This was the first study seeking to assess changes in brain (neuroimaging) and cognition after alcohol intervention in nontreatment-seeking people with HIV together with people without HIV as controls. Study design strengths, limitations, and lessons for future study design considerations are discussed. Planned analyses are in progress, after which deidentified study data will be available for sharing. Trial Registration ClinicalTrials.gov NCT03353701; https://clinicaltrials.gov/study/NCT03353701 International Registered Report Identifier (IRRID) DERR1-10.2196/53684 | [
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39193914 | methods | Research Design and Methods Study Design and Population The UK Biobank is an ongoing longitudinal study including >500,000 adults between the ages of 40 and 70 from across the United Kingdom. Between 2006 and 2010, participants took part in a baseline examination at 1 of 22 assessment centers across the country consisting of physical and medical assessments and a series of questionnaires about sociodemographic information and lifestyle behaviors. Approximately 9 years later, between 2014 and 2020, >40,000 participants additionally underwent a brain MRI scan. Beginning in 2019, participants were invited to return for a follow-up brain MRI scan. Selection of the study population is illustrated in Supplementary Fig. 1. The analysis was restricted to 34,296 participants who underwent brain MRI scans and had complete information on all available imaging-derived phenotypes (IDPs). We then excluded 630 participants with chronic neurological disorders (including dementia) at the time of the MRI scan (see Supplementary Table 1 for details), 15 with type 1 diabetes, and 2,422 with missing information on baseline HbA1c, leaving a sample of 31,229, including 2,414 who underwent two MRI scans. All data collection procedures have been approved by the UK National Research Ethics Service (Ref 11/NW/0382) and the use of the data for the present analyses were additionally approved by the Regional Ethical Review Board in Stockholm, Sweden (Ref 2024-00520-01). All participants provided informed consent at baseline. Assessment of Prediabetes and Diabetes Baseline diabetes and prediabetes were defined according to the American Diabetes Association standard diagnostic criteria. Participants were classified as having diabetes if they had any one of the following: medical record of diabetes, use of glucose-lowering medications, self-reported history of diabetes, or HbA1c ≥6.5% (see Supplementary Table 2 for field codes). Among diabetes-free participants, prediabetes was defined as HbA1c 5.7% to 6.4%, and normoglycemia was defined as HbA1c <5.7%. Diabetes was further categorized according to level of glycemic control: <7.0% (well-controlled), ≥7.0 to <8.0% (moderately controlled), or ≥8.0% (poorly controlled). Acquisition of Brain IDPs Brain MRI scans were conducted using a Siemens Skyra 3T scanner. Detailed descriptions of the UK Biobank brain MRI image acquisition and processing protocols have been previously published and are summarized in Supplementary Table 3. A total of 1,079 IDPs were extracted across six MRI modalities: 165 from T1-weighted MRI, 1 from T2-fluid attenuated inversion recovery (FLAIR), 14 from T2*, 675 from diffusion MRI, 210 from resting-state functional MRI (fMRI), and 14 from task fMRI. Briefly, T1-weighted imaging provides information on the volume and thickness of different brain regions, T2-FLAIR imaging detects white matter hyperintensities (reflecting vascular brain damage), T2* detects brain microbleeds, diffusion MRI assesses white matter microstructural integrity, resting-state fMRI measures brain activity at rest for assessment of intrinsic functional connectivity of neural networks, and task fMRI does so when the participant is performing a task or experiencing a sensory stimulus (in this case, a face/shapes matching task). A full list of all 1,079 IDPs is provided in Supplementary Material. Machine Learning-Based Estimation of Brain Age and BAG The procedure for brain age estimation has been described in previous studies. A detailed description is available in the Supplementary Material, and the workflow is illustrated in Supplementary Fig. 2. Briefly, from the entire sample of participants with complete brain MRI data (N = 34,296), we first identified 4,355 healthy individuals between the ages of 40 and 70 with no ICD-10 diagnoses and who were free from self-reported long-term illness, disability, or frailty (Field ID: 2188) and self-reported fair or poor health status (Field ID: 2178) (Supplementary Table 4). These participants were randomly allocated in a 4:1 ratio to a training set (n = 3,484) and a validation set (n = 871). Next, all 1,079 IDPs were Z standardized and nine machine learning models were trained for modeling brain age in the training set. These included least absolute shrinkage and selection operator regression (LASSO), eXtreme gradient boosting, and support vector regression, which were combined with three possible feature selection strategies (no feature selection, FeatureWiz, or recursive feature elimination with cross validation). Bayesian optimization was performed to optimize the hyperparameters of all nine models through 100 epochs (Supplementary Tables 5 and 6). Once optimized, all nine models were applied to the validation set so that their performance could be compared. Ultimately, the LASSO model without feature selection achieved the lowest mean absolute error (Supplementary Table 7) and was therefore chosen to predict brain age for the entire sample. Of the 1,079 IDPs, 285 contributed significantly to the brain age estimate and are listed in Supplementary Table 8. Next, because brain age tends to be overpredicted in younger individuals and underpredicted in older individuals, we corrected brain age estimates for age bias as follows: brain agecorrected = [brain ageoriginal – β/α], where coefficients α and β are the slope and intercept of brain agetraining set = α × chronological agetraining set + β (Supplementary Fig. 3). Finally, BAG, which represents the difference between an individual’s brain age and their chronological age, was calculated as BAG = brain age – agetime of MRI. Positive values for BAG indicate a brain that is older (i.e., less healthy) and negative values for BAG indicate a brain that is younger (i.e., more healthy) than expected based on the individual’s chronological age. Assessment of Covariates Sociodemographic Factors Education (college/university vs. not) was dichotomized based on the highest level of formal education attained. Socioeconomic status (SES) was assessed using the Townsend deprivation index, a measure of neighborhood-level socioeconomic deprivation based on the prevalence of unemployment, household overcrowding, car nonownership, and home nonownership in a given postcode of residence. Cardiometabolic Risk Factors Cardiometabolic risk factor burden was operationalized in terms of the components of the metabolic syndrome (MetS). BMI was calculated using height and weight measurements from the baseline examination and classified as underweight (<20 kg/m2), normal weight (≥20 to <25 kg/m2), overweight (≥25 to <30 kg/m2), or obese (≥30 kg/m2). Hypertension was defined based on self-report, blood pressure measurement (systolic ≥140 mmHg, diastolic ≥90 mmHg), or antihypertensive medication use. HDL cholesterol and triglycerides were measured from blood samples collected at baseline. A score reflecting cardiometabolic risk factor burden (ranging from 0 to 4) was generated according to the total number of MetS components present, including obesity, hypertension, low HDL (<40 mg/dL [1.03 mmol/L] for men and <50 mg/dL [1.29 mmol/L] for women), and high triglycerides (≥150 mg/dL [1.7 mmol/L]). (Notably, the fifth MetS component, hyperglycemia, was not included because it was already considered as the exposure in all analyses.) Lifestyle Behaviors Information was collected on three readily modifiable lifestyle behaviors: smoking, alcohol drinking, and physical activity. Smoking status was categorized as nonsmoker, former smoker, or current smoker according to self-report. Intake of various alcoholic beverages was self-reported and converted into U.K. alcohol units (1 unit = 8 g ethanol). Alcohol consumption was categorized as nondrinker, light/moderate drinking (≤14 units/week), or heavy drinking (>14 units/week) according to current U.K. guidelines on alcohol consumption for both men and women. Physical activity was measured using the International Physical Activity Questionnaire. Participants were classified as inactive (<600 MET-min/week), moderate (600 to <3,000 MET-min/week), or active (≥3,000 MET-min/week); 600 MET-min/week is equivalent to the World Health Organization recommendation of 150 min of moderate-intensity or 75 min of vigorous physical activity per week. An optimal lifestyle was defined as never smoking, no or light/moderate alcohol consumption, and high physical activity. Alzheimer Disease-Related Polygenic Risk Score Alzheimer disease (AD)-related polygenic risk score (PRSAD) was obtained from the UK Biobank’s Standard PRS Set. Briefly, PRSAD represents the Z-standardized sum of each participant’s number of AD-related alleles (including the well-known APOE ε4 polymorphism) weighted by the strength of each allele’s association with AD. Statistical Analysis Baseline characteristics of the study participants by glycemic status were assessed using χ2 tests for categorical variables and one-way ANOVA for continuous variables. Linear regression models were used to estimate β-coefficients and 95% CIs for the association between glycemic status at baseline and BAG at the time of brain MRI. Least-squares means of BAG in the normoglycemia, prediabetes, and diabetes groups were additionally estimated from the margins of the linear regression models. Similar analyses were conducted using HbA1c as a continuous variable. Restricted cubic splines with three knots at fixed percentiles of the HbA1c distribution (10th, 50th, and 90th) were used to model the possible nonlinear association between HbA1c and BAG. Among participants who underwent two brain MRI scans, linear mixed-effects models were used to estimate β-coefficients and 95% CIs for the association between glycemic status and changes in BAG between the first and second scans. The fixed effect included baseline glycemic status, follow-up time (in years), and their interaction. The random effect included random intercept and slope, allowing individual differences in BAG to be reflected at baseline and across follow-up. Next, stratified linear regression models were used to explore the role of sex (women vs. men) and cardiometabolic health (0–1 vs. ≥2 risk factors) in the association between glycemic status and BAG. Finally, we performed joint exposure analysis by incorporating a six-category indicator variable that combined glycemic status (normoglycemia, prediabetes, or diabetes) and lifestyle (optimal or nonoptimal) into the linear regression model. Interactions between glycemic status and sex, cardiometabolic risk factor level, and lifestyle were assessed by incorporating the cross-product term into the models. All models were first basic adjusted for sociodemographic factors (i.e., age, sex, education, and SES), followed by further adjustment for number of cardiometabolic risk factors, lifestyle behaviors (i.e., smoking, alcohol consumption, and physical activity), and PRSAD. Missing values for covariates were imputed using fully conditional specification, with estimates pooled from five iterations. In sensitivity analysis, we repeated the main analyses 1) using BAG calculated based on brain age estimates from other candidate machine learning models; 2) using nonimputed data; 3) after adding an additional covariate for brain MRI assessment center; 4) after excluding participants with possible prodromal/undiagnosed dementia (i.e., incident dementia during follow-up; n = 42) or possible cognitive impairment (i.e., baseline cognitive test scores <25th percentile; n = 7,806) to minimize the possibility of reverse causality; and 5) using diabetes status defined at the time of brain MRI scan to address the possibility of changes in glycemic status since baseline. All analyses were performed using Stata SE 16.0 software (StataCorp, College Station, TX). P values <0.05 were considered statistically significant. Data and Resource Availability Requests for access to the UK Biobank data can be made here: https://www.ukbiobank.ac.uk/enable-your-research/apply-for-access. | [
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38328108 | abstract | Summary Men generally outperform women on encoding spatial components of episodic memory whereas the reverse holds for semantic elements. Here we show that female mice outperform males on tests for non-spatial aspects of episodic memory (“what”, “when”), suggesting that the human findings are influenced by neurobiological factors common to mammals. Analysis of hippocampal synaptic plasticity mechanisms and encoding revealed unprecedented, sex-specific contributions of non-classical metabotropic NMDA receptor (NMDAR) functions. While both sexes used non-ionic NMDAR signaling to trigger actin polymerization needed to consolidate long-term potentiation (LTP), NMDAR GluN2B subunit antagonism blocked these effects in males only and had the corresponding sex-specific effect on episodic memory. Conversely, blocking estrogen receptor alpha eliminated metabotropic stabilization of LTP and episodic memory in females only. The results show that sex differences in metabotropic signaling critical for enduring synaptic plasticity in hippocampus have significant consequences for encoding episodic memories. | [
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36883266 | abstract | Abstract Aim The molecular mechanism underlying Alzheimer's disease (AD) pathologies remains unclear. The brain is extremely sensitive to oxygen deprivation, and brief interruptions in oxygen supply may lead to permanent brain damage. The objective here was to access the red blood cell (RBC) physiological alterations and the changes in blood oxygen saturation of an AD model as well as to explore the possible mechanism underlying these pathologies. Methods We used female APP swe /PS1 ΔE9 mice as AD models. Data were collected at the age of 3, 6, and 9 months. In addition to examining classic features of AD, namely cognitive deficiency and Aβ depositions, 24 h blood oxygen saturation was monitored by Plus oximeters in real time. In addition, RBC physiological parameters were measured by blood cell counter using peripheral blood from the epicanthal veins. Furthermore, in the mechanism investigations, the expression of phosphorylated band 3 protein was examined by a series of Western blot analyses, and the levels of soluble Aβ40 and Aβ42 on the membrane of RBCs were determined by ELISA. Results Our results showed that the blood oxygen saturation in the AD mice was significantly reduced as early as at 3 months of age, preceding the neuropathological changes and cognitive impairments. Meanwhile, the expression of phosphorylated band 3 protein and levels of soluble Aβ40 and Aβ42 were all elevated in the erythrocytes of the AD mice. Conclusion APP swe /PS1 ΔE9 mice exhibited decreased oxygen saturation together with reduced RBC counts and hemoglobin concentrations at the early stage, which may aid in the development of predictive markers for AD diagnosis. The increased expression of band 3 protein and elevated Aβ40 and Aβ42 levels may contribute to the deformation of RBCs and, in turn, cause the subsequent AD development. We reveal that the blood oxygen saturation in AD mice is significantly reduced as early as at 3 months of age, preceding the neuropathological changes and cognitive impairments. The results may aid in the development of predictive markers for AD diagnosis. | [
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38466421 | intro | Introduction Patients with peripheral vestibular dysfunction (PVD) suffer from cognitive problems. Cognitive problems are present even in mild PVD and can persist long after a patient has clinically recovered. Several studies showed that patients with PVD have problems in spatial cognitive domains, such as spatial memory, spatial navigation, or mental rotation. However, recent research fosters the claim that patients with PVD also suffer from cognitive problems in nonspatial domains such as nonspatial memory, processing speed, or executive functions. Executive functions are a collection of cognitive processes responsible for purposeful, goal-directed behavior. They include basic and complex cognitive processes. Basic executive functions include initiation, inhibition, cognitive flexibility, or working memory. Complex executive functions are for example problem solving, planning, or monitoring. Executive functions are essential for mental and physical health, academic and life success, and daily life functioning. Impaired executive functions have intense negative consequences and cause a poor quality of life. There are various hypotheses for cognitive problems in patients with PVD. Visuo-spatial problems have been associated with altered brain structures, especially in the hippocampus. However, the nonspatial cognitive problems are unlikely due to changes in the hippocampus. Alternative explanations are plasticity processes in the neocortex or the vestibular nuclei, changed neuronal connections from the vestibular nerve to cortical areas involved in cognitive processing, affective disorders, or prioritized attentional resources on maintaining balance. Subjective reports indicate that patients with PVD have serious executive problems. Most patients in a group of patients with bilateral PVD complained about difficulties with daily life activities such as an inability to prioritize tasks or problems with dual tasking. Unexpectedly, cognitive-based daily life activities such as managing finances were more impaired than mobility-based activities. Other studies focused specifically on the executive deficits that underlie worse cognitive performance in patients with PVD. For example, patients with acute neuritis performed worse in generating sequences of random numbers or a math achievement task than healthy controls. These problems indicate a deficit in working memory. Behavioral measures in patients with PVD show executive deficits, but evidence is conflicting. Patients with bilateral as well as patients with chronic unilateral PVD performed worse in a general initiation task than healthy controls. However, patients with bilateral PVD performed equally as healthy controls in a verbal fluency task, a subdomain of initiation. Inhibition and working memory were found to be reduced in patients with bilateral, chronic unilateral, and acute unilateral PVD. Some other studies, however, did not find reduced inhibition or working memory performance in patients with bilateral or chronic unilateral PVD. Cognitive flexibility was reduced in patients with chronic unilateral, but normal in patients with bilateral or a mixed sample of bilateral and chronic unilateral PVD. Previous studies that behaviorally measured executive functions in patients with PVD are limited for the following reasons: First, all mentioned studies investigated some isolated executive components instead of administering a comprehensive executive test battery. Therefore, previous studies do not allow for a general conclusion about impaired executive functions. Second, in some studies, executive components were measured with spatial tests, thus making it impossible to disentangle spatial from executive deficits. Third, some studies did not control for processing speed when assessing reaction time in executive tasks. Fourth, some studies refer to executive dysfunction when non-executive functions were assessed, e.g., short-term memory instead of working memory or motor speed instead of cognitive flexibility. We investigated whether executive performance in a large sample of patients with PVD (n = 83) differs from carefully pairwise matched healthy controls. We integrated several conditions of PVD (bilateral, chronic unilateral, acute unilateral). Solving limitations of previous studies, we used a comprehensive executive test battery with validated neuropsychological tests including basic and complex executive functions. Executive tests were nonspatial if possible, and we controlled for processing speed in reaction time measurements. This methodology allows thorough conclusions about executive impairments ruling out influences of impaired spatial cognition or processing speed. We also assessed subjective executive performance, the impact of PVD on daily life functioning, and as control variables intelligence and global cognitive level. Moreover, we investigated whether non-vestibular related variables in patients and controls (hearing loss, affective disorders) and vestibular related variables in patients (disease duration, symptoms, dizziness handicap, deafferentation degree, and compensation) influenced our results. We hypothesized that executive performance differs between patients with PVD and healthy controls. In addition, we hypothesized that non-vestibular related variables may explain the differences in executive performance between patients with PVD and healthy controls. Further, we hypothesized that vestibular related variables in patients predict executive performance. | [
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38667317 | title | Lipidomic Analysis of Plasma Extracellular Vesicles Derived from Alzheimer’s Disease Patients | []
|
38642387 | methods | Method Study Design This was a cross-sectional analysis of baseline data collected from 262 older adults enrolled across three randomized controlled trials (RCTs) in our laboratory: (1) 96 from a study investigating the effects of a multidomain lifestyle program on sleep and cognition in older adults with MCI and poor subjective sleep, (2) 102 from an exercise trial designed to examine the impact of aerobic and resistance training exercises on cognition in older adults with MCI, and (3) 64 from an exercise trial to assess the impact of resistance training on cognition and white matter hyperintensities in older adults with MCI and with neuroimaging evidence of cerebral small vessel disease (Supplementary Figure 1). The RCTs were conducted at the University of British Columbia with recruitment and data collection from November 2016 to the present. Ethical approval was obtained from the University of British Columbia’s Clinical Research Ethics Board (H16-01029, H15-02181, H15-00972) and Vancouver Coastal Health Research Institute (V16-01029, V15-02181, V15-00972). Participants of the 3 RCTs provided written informed consent per the Declaration of Helsinki before study enrollment. Participants Two hundred and sixty two community-dwelling older adults with a research-based diagnosis of amnestic or nonamnestic MCI, defined as no functional impairment, no diagnosis of dementia, and a Montreal Cognitive Assessment (MoCA) score <26/30, participated in the study. The absence of functional impairment was operationalized based on shared criteria of the included studies, specifically that participants were: (1) in sufficient health to participate in regular PA; (2) able to walk independently (with or without an assistive device); and (3) living independently in their own homes (ie, not residing in assisted-living or long-term care homes). Each RCT’s specific inclusion and exclusion criteria are published elsewhere and displayed in Supplementary Table 1. Briefly, we included participants (1) aged ≥55 years; (2) living independently in their homes; (3) with MCI as determined by a MoCA score of <26/30; 4) who scored >20/30 on the Mini-Mental State Examination (MMSE); and (5) provided informed consent. We excluded those who (1) had a formal diagnosis of neurodegenerative disease, stroke, dementia (any type), or psychiatric condition; (2) were taking psychotropic medication; (3) were living in a nursing home, extended care facility, or assisted-care facility; and (4) were planning to participate or already enrolled in a clinical drug trial or exercise trial concurrent to the RCTs. The MoCA cutoff score <26/30 is a widely adopted cutoff due to its high specificity in correctly identifying MCI. In a large sample of MCI individuals, a MoCA cutoff score <26/30 correctly identified 90% of the individuals clinically diagnosed with MCI. In addition, the MMSE score of ≥20/30 was adopted to capture individuals with MCI but not dementia. MMSE scores 21–25/30 correspond to a Clinical Dementia Rating (CDR) of 1.0 (ie, mild cognitive impairment). Across the three studies, the lowest MMSE cutoff was 21 (or >20/30) for inclusion (Supplementary Table 1). Participants’ MoCA scores ranged from 11 to 26 and MMSE scores ranged from 21 to 30. The RCTs’ inclusion criteria had some differences. For example, Falck and colleagues included those with poor subjective sleep quality (score >5/21 on the Pittsburgh Sleep Quality Index), Liu-Ambrose and colleagues included those who fulfilled clinical criteria for cerebral small vessel disease, and Barha and colleagues included those with CDR <1 (Supplementary Table 1). We added RCT as a covariate in our inferential statistical analysis. Measurements Demographic information Demographic variables included age, height (m), weight (kg), biological sex, and educational attainment. The body mass index (BMI) was calculated (kg/m2), and cognitive status was assessed with the MMSE and MoCA. MoCA scoring rules adjust for ≤12 years of education, adding 1 point to the total score of individuals with ≤12 years of education. Cognition We measured global cognition with the Alzheimer’s Disease Assessment Scale—Cognitive Plus (ADAS-Cog-Plus). The ADAS-Cog-Plus combines executive functions and verbal fluency tasks with the 13-item ADAS-Cog score.We included the Trail Making Test parts A and B, digit span forward and backward, and category fluency (vegetables and animals). Lower ADAS-Cog-Plus scores indicate better global cognition. According to the Alzheimer’s Disease Neuroimaging Initiative (ADNI) sample, cognitively healthy older adults have a mean ADAS-Cog-Plus score of approximately −1.0, individuals living with MCI around 0.0, and those living with dementia around 1.0. 24-h activity cycle behavioral measurement We measured PA, SB, and sleep duration using the MotionWatch8© (MW8; CamNtech, Cambridge, UK), a tri-axial accelerometer designed to observe acceleration ranging in magnitude from 0.01G to 8G, with a frequency of 3–11 Hz. The MW8 is a noninvasive, lightweight, battery-powered wrist-worn device with a more comfortable placement for sleeping and daytime wear. The device has evidence for measuring older adult PA and SB against indirect calorimetry, wherein the classification accuracy of SB and PA was moderately accurate. Participants continuously wore the MW8 on their nondominant wrist for seven consecutive days. Five days of wear time provides reliable estimates of PA, SB, and sleep duration for people with and without MCI. We only included participants with ≥5 days of consecutive PA, SB, and sleep data, resulting in an analytic sample of N = 253, specifically, n = 88, n = 89, and n = 76 (Supplementary Figure 1). Participants were fitted with the MW8 for each study and provided detailed information on its features (ie, light sensor, event marker button, and status indicator). Participants were instructed to press the event marker button each night when they started trying to sleep and again each morning when they finished trying to sleep. The MW8 is the updated version of the Actiwatch 7, a device with evidence of validity against polysomnography in healthy adults. We used an automated rest-interval scoring algorithm of illuminance and motion data to classify time spent sleeping each night versus time spent awake each day; this algorithm has a strong correlation (r = 0.92) with the traditional method for determining sleep duration. Naps were not included in our calculations for sleep duration and were indexed as SB. Our estimates only included the major sleep period. The MW8 algorithm uses a function to categorize sleep time as consecutive epochs of <20 counts/min. Instances wherein activity exceeded 20 counts/min were scored as time awake. Hence, wake after sleep onset (WASO) was not included in estimates of sleep duration. These minutes wherein the participant was classified as awake were excluded from daily sleep calculations. For time classified as awake, MVPA, LPA, and SB were classified using established cutpoints for MW8. Specifically, MVPA was classified as ≥562.50 counts/min, LPA as 178.51 to 562.49 counts per minute, and SB as ≤178.50 counts/min. Determination of 24-h activity cycle activity profiles The 24-HAC behaviors data were analyzed using Motionware 1.0.27 (CamNtech) actigraphy. Data prior to recorded wake-time on the first full day of recording were manually removed in order only to investigate complete 24-h recordings of activity. Each day of PA and SB consisted of a time when the participant was assumed to be awake and out of bed, based on the rest–wake interval scoring algorithm. We deemed each 24-HAC as the time between when the participant went to bed for a given night and the last minute of recorded PA or SB the next day. For example, if a participant went to bed at 10:00 pm, woke up at 6:00 am, and went to bed at 11:00 pm, we assumed that the 24-HAC referred to the window between 10:00 pm and 10:59 pm of the next day. It is important to note that although we call each “day” of data the 24-HAC, each “day” does not refer to precisely 24 h. In the example, the participant had a “day,” which lasted 24 h and 59 min. We then averaged the time spent in each 24-HAC behavior and the day’s total duration (ie, the sum of all 24-HAC behaviors) across the recording period of >5 days. Compositional data analysis requires a constant-sum constraint on the sample values, for example, 1 440 min for a day. To account for that, we double-checked that the averaged sum of each 24-HAC had the same finite scale (ie, 1 440 min). We rescaled the participants’ time spent in each 24-HAC behavior, to sum up to 1 440 min, using the closure function from the compositions R package (version 2.0–4). Next, we transformed the averaged rescaled time spent on each behavior into a proportion (%). For example, if a participant spent an average of 240 min engaging LPA on their 1 440 min days of recording, then the estimated % LPA for that participant would be: Compositional data analysis techniques address limitations caused by multicollinearity due to the inclusion of all 24-HAC behaviors within a single model. It involves expressing time spent (or proportion of time) engaging in different time-use behaviors during a finite period (eg, 1 440 min or 100%) in relative terms as a set of isometric log-ratio coordinates. These coordinates contain all the relative information regarding the 24-HAC time-use behaviors. They can be used as vectors in standard statistical models instead of raw min/day or proportion of the day vectors. Using the compositions package (version 2.0–4), we created the isometric log-ratio coordinates using a sequential binary partition process. To compute the first pivot coordinate, we coded % of time spent in one behavior as the numerator (+1) in the equation and % of time amongst remaining behaviors as the denominator (−1). The first behavior was partitioned out and coded as an uninvolved part (0) in the sequential binary partition to create the second coordinate. The percentage of time spent engaging in one of the remaining three behaviors was coded in the numerator (+1) and the remaining two in the denominator (−1). Next, the behavior in the numerator was partitioned out to code the last coordinate. The percentage of time engaging in the remaining two behaviors was coded in the numerator (+1) and the denominator (−1). The isometric log-ratio transforms each behavior’s composition to a unique behavior-1 vector on a new coordinate system where each new coordinate is a log-ratio that falls along the real line. We chose the following coordinates (1) the first coordinate included all relative information regarding MVPA versus the geometric mean of % of time spent engaging in SB, light PA, and sleep; (2) the second coordinate represented SB versus geometric mean of light PA and sleep; and (3) the last coordinate included light PA versus sleep. This set of isometric log-ratios was also adopted by Wu and colleagues. The isometric log-ratios transformations of the 24-HAC behaviors were expressed using equations (1)–(3), where the numbers preceding the log-ratios are normalizing constants necessary for the desirable mathematical properties of the transformed coordinates: We used the three isometric log-ratio coordinates to perform latent profile analysis using the tidyLPA R package (version 1.1.0). The latent profile analysis is a data-driven approach to deriving mutually exclusive profiles. This method uses finite mixture latent modeling to generate homogenous profiles within a group (ie, similar engagement in each 24-HAC behavior relative to the others) and heterogenous profiles between groups. We chose the model based on five fit statistics: (1) Akaike information criterion (AIC) and Bayesian information criterion (BIC): both are indicators of the best balance between the simplicity of the model and its goodness of fit. Lower values indicate a more parsimonious model; (2) entropy: indicates the precision of classifying cases into the different profiles, determining classification accuracy. Entropy values closer to 1 indicate better accuracy; (3) bootstrapped likelihood ratio test p-value (BLRT-p): indicates whether the model with the kth profile has improved model fit compared to the previous model; and (4) the number of participants in each profile was ≥25 or >1%. Statistical Analysis All analyses were conducted in R (version 4.2.2) and R Studio (version 2023.06.0). The statistical code is available on GitHub (link). All participants with analyzed data had complete data. We checked all 24-HAC behaviors, isometric log-ratio coordinates, and ADAS-Cog-Plus scores for outliers outside Q1 − 1.5 × Interquartile range (IQR) and Q3 + 1.5 × IQR. We winsorized observations outside the lower and upper limits in instances where outliers were detected (n = 17 for 24-HAC behaviors, n = 5 for isometric log-ratio coordinates, and n = 4 for ADAS-Cog-Plus). We replaced below the lower limit with the value of the 5th percentile, and the values above the upper limit with the 95th percentile. Differences between 24-HAC activity profiles in demographic characteristics and 24-HAC behaviors were investigated using analysis of variances (ANOVA) for continuous variables and chi-square tests for categorical variables. As post hoc comparisons, significant differences in 24-HAC activity profiles were decomposed using pairwise comparisons. As a sensitivity analysis, we examined whether RCT cohorts differed in continuous or categorical variables using ANOVA and chi-square tests, and whether results withstood without the winsorization of outliers. To determine whether ADAS-Cog-Plus performance differed by 24-HAC activity profile, we performed an analysis of covariance (ANCOVA) wherein we adjusted for age, biological sex, BMI, MoCA score, and RCT cohort. In the event of a significant one-way ANCOVA, pairwise comparisons between groups were used. Given that this was an exploratory analysis, we did not adjust for multiple comparisons. | [
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39193143 | methods | Materials and methods Study participants We informed patients about the study through the national registry for myotonic dystrophies.1 The inclusion criteria for the study were: (1) genetically confirmed diagnosis of DM1 or DM2; (2) age between 18 and 65 years; (3) presence of chronic muscle pain defined as persisting or recurring pain for over 3 months. Exclusion criteria were: previous diagnosis of diabetes mellitus, glucose intolerance and/or previously diagnosed polyneuropathy of any cause. In- and exclusion criteria were preliminarily checked during phone calls with the study candidates and were proven on-site by reviewing the medical records. An age- and sex-matched control group of healthy individuals were recruited for comparison. At the first study visit, patients and controls gave their written informed consent to participate. During the 1.5-year recruitment period we aimed to include as many patients as possible, but at least 20 participants per group. For a non-parametric group comparison with a group size ratio of 1.5, a sample size of 15 and 23 per group was estimated to be sufficient to detect a standardized mean difference of 1 (assuming an alpha-level of 5% and a power of 80%). Based on the published QST-reference values one standardized mean difference represents a clinically relevant difference for all QST parameters. Study protocol The study was conducted in accordance with the declaration of Helsinki and the local ethics committee approved the study protocol (LMU project no. 19/499). The study design consisted of (1) collection of demographic and disease-related data (diagnosis, body mass index, age at onset, disease duration, present neuromuscular complaints, multisystemic involvement, current pain medication); (2) completion of pain questionnaires [brief pain inventory (BPI), pain-DETECT and pain disability index (PDI)]; (3) neurological examination (including muscle impairment rating scale (MIRS) for DM1 patients); (4) quantitative sensory testing (QST); (5) nerve conduction studies (NCS) and (6) skin biopsies quantifying IENFD. If patients were taking painkillers, such as non-steroidal anti-inflammatory drugs (NSAIDs) or muscle relaxants (e.g., methocarbamol) on demand, they were asked to pause these medications two days before their study visit. Patients regularly taking pain-modulating drugs (e.g., amitriptyline, duloxetine) were allowed to continue the therapy at the usual dosage. Pain questionnaires The pain questionnaires were chosen considering the recommendations of the German Research Network for Neuropathic Pain (Deutscher Forschungsverbund Neuropathischer Schmerz—DFNS) and their previous use in studies investigating pain in myotonic dystrophies. The BPI assesses pain severity and interference in several activities within the last 24 h. It also depicts most painful body regions, describes the use of pain medications and indicates the percentage of pain relief obtained. The pain-DETECT screening questionnaire estimates the likelihood that patients have a neuropathic pain component. The final score ranges from 0 to 38. If the score is below 13, the neuropathic component is unlikely (<15% likelihood), between 13 and 18 it is uncertain and above 18 it is very likely (>90%). The PDI measures the pain’s impact on the patient’s ability to participate in seven relevant life activities (e.g. occupation, self-care, recreation) on a scale from 0 to 10. Accordingly, the PDI sum-score ranges from 0 to 70, with higher scores indicating greater pain related disability. Quantitative sensory testing Quantitative sensory testing (QST) followed the test battery standardized and validated by the DFNS. QST is a psychophysical examination used to explore the somatosensory function and the presence of hyperalgesia and/or allodynia. It encompasses 13 sensory parameters, including mechanical and thermal detection and pain thresholds. All investigators received specific training and certification by the DFNS to perform and interpret QST. The same investigator (VS) performed all QST assessments in recruited patients and healthy controls. The QST was performed at the dorsum of the right hand and at the right thigh in DM patients and at the right thigh in healthy controls. The hand dorsum was chosen as a pain-free region for which the DFNS provides reference data stratified by age and gender. The thigh region was selected as it represents the most painful region in DM patients. Herein, we report a summarized version of the QST protocol validated by the DFNS. For thermal testing, we used a thermal sensory analyzer (TSA 2001-II, Medoc Ltd. Advanced Medical Systems, Ramat Yishai, Israel). Cold and warm detection thresholds (CDT and WDT), thermal sensory limen (TSL), cold and heat pain thresholds (CPT, HPT), as well as the number of paradoxical heat sensations (PHS) were assessed. The mechanical detection threshold (MDT) was evaluated with a set of von Frey filaments (OptiHair2, MRC systems GmbH, Heidelberg, Germany). The mechanical pain threshold (MPT), the mechanical pain sensitivity (MPS) and the wind-up ratio (WUR) were determined by using a set of pinprick stimulators (PinPrick Stimulator Set, MRC Systems GmbH, Heidelberg Germany). Furthermore, dynamic mechanical allodynia (DMA) was assessed by stroking with a Q-tip, cotton wool and a paint brush also included in the MRC stimulator set. The vibration detection threshold (VDT) was examined with a Rydel-Seiffer tuning fork (64 Hz, x/8 scale; Arno Barthelmes, Tuttlingen, Germany). The pressure pain threshold was assessed by a pressure algometer with a rubber tip of 1 cm2 (FPK20, Wagner Instruments, Greenwich, CT, United States). Nerve conduction studies Nerve conduction studies (NCS) were performed to rule out the presence of large fiber polyneuropathy. This examination was done after the QST to avoid any impact caused by the discomfort related to the NCS. The following nerves were examined in all patients (DM1, DM2) and controls on the right side: ulnar motor nerve, peroneal motor nerve, sensory radial nerve and sural nerve. For the classification of abnormal NCS, the reference values of our neurophysiology laboratory were adopted. Intraepidermal nerve fiber density evaluated by skin biopsies To assess the intraepidermal nerve fiber density (IENFD), two 3 mm diameter skin punch biopsies were taken 10 cm above the lateral malleolus (distal biopsy) and 20 cm below the iliac spine (proximal biopsy). The skin samples were fixed with Zamboni fixative, washed in PBS, transferred to 10% sucrose and stored at −80°C freezer until use. From each biopsy, 50 μm thick frozen sections were stained using a free-floating protocol with primary antibody anti-protein gene product (PGP 9.5, 1:1,000, Zytomed) and secondary antibody goat anti-rabbit Alexa Fluor 488 (1:1,000, Thermo Fisher Scientific). Four sections were mounted with DAPI Fluorshield (Abcam) and were examined using an Olympus IX83 inverted microscope equipped with a UPLSAPO400XO/1.4 objective and a DP 74 digital camera (Olympus, Tokyo, Japan). Image analysis was performed using cell Sens Dimension software (Olympus). During the morphologic analysis, the investigator (FM) was blinded to the patient’s diagnosis (DM1 or DM2). The IENFD was quantified using standardized guidelines and age- and sex-adjusted normative values. The proximal/distal IENFD ratio was calculated to evaluate the pattern of small fibers reduction. A ratio < 1 was considered a proximal reduction, > 2.5 a distal reduction. Statistical analysis The data were analyzed with SPSS Statistics (Version 27.0, IBM, Armonk, NY) and R (version 4.2.3, R Core Team, 2022). The normality of variables was assessed by the Shapiro–Wilk test. As most continuous variables were non-normally distributed, descriptive statistics are displayed as medians and interquartile ranges (IQR). Categorical variables are reported as absolute and relative frequencies. Comparisons of continuous and ordinal variables between the three study groups were performed by applying the Kruskal-Wallis-test (KW-test) with Dunn’s post-hoc test adopting Bonferroni adjustment for pairwise comparisons. Group comparisons of data that were only collected in DM1 and DM2 patients were performed by the Mann–Whitney U test. Comparisons of nominal and dichotomous data were performed by Chi2 or Fisher-test, respectively. Correlations between outcome measures were evaluated by Spearman correlation. p-values < 0.05 were considered significant. According to DFNS reference data in healthy volunteers, all QST parameters are either normally distributed (CPT, HPT, VDT) or normally distributed in log-space (CDT, WDT, TSL, MDT, MPT, MPS, WUR, PPT, PHS, DMA). This was indeed the case for our healthy control group. However, QST parameters in DM1 and DM2 patients showed skewed distributions. Therefore, the sensory profiles of DM1 and DM2 patients are illustrated as boxplots of the patients’ z-scores, and non-parametric tests as stated above were used for inferential statistics. Z-Scores were calculated by the following formula: Z-scores below zero indicate a loss of function; z-scores above zero indicate a gain of function. Z-scores for QST-data at the thighs were calculated based on data established in the age- and gender-matched healthy control group. Z-Scores for QST-data at the dorsum of the hand were calculated compared to DFNS reference data as described by Magerl et al.. Magerl et al. suggest performing a statistical comparison with the DFNS reference data by computing the t-test statistic from the z-scores of the study sample and an ideal normal distribution with mean 0 and SD 1. Given the skewed distribution in our patient samples, we applied a corresponding non-parametric test strategy. 100 random samples from a normal distribution with mean 0 and SD 1 were compared to z-scores of our samples by applying the KW- and Dunn’s post-hoc tests. The 100th root of the product of the 100 p-values is reported as an approximation for the p-value of a comparison with an ideal normal distribution. Sensitivity analyses for all outcome comparisons with adjustment for either age and gender or BMI and gender were carried out by applying generalized linear models with either an identity (continuous outcomes), a logit (dichotomous outcomes), or a cumlogit (categorical outcomes with more than two categories) link function. Age and BMI were not included in the same model, as this would have caused collinearity (Spearman correlation coefficient (rS) age ~ BMI 0.355 p < 0.001). | [
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35305339 | title | Soluble TREM2 in CSF and its association with other biomarkers and cognition in autosomal-dominant Alzheimer's disease: a longitudinal observational study. | [
[
8,
13
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80,
89
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99,
118
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|
38490646 | title | Intracranial self-stimulation reverses impaired spatial learning and regulates serum microRNA levels in a streptozotocin-induced rat model of Alzheimer disease | [
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129,
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39234240 | intro | Introduction Systemic sclerosis (SSc), an autoimmune condition primarily affecting women, is characterized by vascular dysfunction and progressive fibrosis of the skin and internal organs. The global incidence of SSc ranges between 8-56 new cases per million persons per year and the prevalence varies between 38-341 cases per million persons. The mortality in SSc patients is three- to four-fold higher than the general population due to cardiorespiratory complications, renal and gastrointestinal disease, cancer, and infections. Increasing evidence also suggests that atherosclerosis is a critical additional component of the pathophysiology of SSc. This has led to a shift in the focus of basic and clinical research studies which have convincingly reported several pro-atherosclerotic arterial abnormalities, e.g., endothelial dysfunction, increased intima-media thickness and arterial stiffness, in SSc. Such alterations are similar to those observed in rheumatoid arthritis, another autoimmune condition associated with atherosclerosis and cardiovascular disease. Epidemiological studies have also reported an increased risk of atherosclerotic cardiovascular events in SSc, particularly myocardial infarction and peripheral vascular disease. In these studies, the prevalence and/or severity of hypertension, diabetes, and dyslipidemia in SSc patients was similar to that in control groups. This suggests that conventional risk factors only partially account for the increased risk of atherosclerosis and cardiovascular disease in SSc. Therefore, a focus of current research is the identification of alternative, more robust biomarkers of atherosclerosis allowing early risk stratification and preventive treatment. Functional and structural alterations of the endothelium, associated with the impaired synthesis of the critical endogenous messenger nitric oxide, represent the initial step in the pathogenesis of atherosclerosis. At a cellular and molecular level, these alterations involve the adhesion of leukocytes and lymphocytes to the endothelium (endothelial activation) and their consequent migration to the tunica intima, where they initiate a sequence of events leading to the formation of the atherosclerotic plaque. The process of cellular adhesion to the endothelium is mediated by several molecules, e.g., the immunoglobulin-like vascular cell adhesion molecule-1 (VCAM-1), the intercellular vascular adhesion molecule-1 (ICAM-1), the platelet endothelial cell adhesion molecule-1 (PECAM-1), the neural cell adhesion molecule (NCAM), the Down syndrome cell adhesion molecule (DSCAM), and the endothelial cell-selective adhesion molecule (ESAM). VCAM-1 is expressed in endothelial cells and macrophages and binds to integrin α4β1. ICAM-1 is upregulated during inflammation and binds to the leukocyte specific β2 integrins. PECAM-1 is expressed in leukocytes, platelets, and endothelial cells, and exerts its effects through the translocation of integrin α6β1. NCAM is expressed in the brain, skeletal muscle, and hematopoietic system. In addition to regulating cell adhesion, it modulates brain and kidney development and plays a pathophysiological role in cancer, schizophrenia, and other neurodegenerative disorders. DSCAM is primarily expressed in the brain and regulates neural development. ESAM is expressed mainly in endothelial cells and is critical in modulating angiogenesis, endothelial integrity, leukocyte adhesion and transmigration. The immunoglobulin-like cell adhesion molecules can be measured in plasma or serum. Their concentrations, particularly VCAM-1, ICAM-1, and ESAM, have been shown to be associated with endothelial dysfunction, vascular damage, and increased risk of atherosclerotic cardiovascular disease. Other molecules facilitating cell adhesion to the endothelium include selectins, integrins, and cadherins. The selectins include P-selectin, expressed in platelets and endothelial cells, L-selectin, expressed in leukocytes, and E-selectin, expressed in endothelial cells. L-selectin mediates lymphocyte rolling, whereas P-selectin and E-selectin influence the rolling of monocytes, neutrophils, and lymphocytes. Similar to the immunoglobulin-like cell adhesion molecules, selectins, integrins, and cadherins can be measured in plasma or serum, and their concentrations have also been shown to be associated with an increased risk of atherosclerosis and cardiovascular disease. To evaluate the possible role of cell adhesion molecules as biomarkers of endothelial activation, dysfunction, and atherosclerosis in SSc, we conducted a systematic review and meta-analysis of studies investigating their plasma or serum concentrations in SSc patients and healthy controls. Where possible, we investigated possible associations between the effect size of the between-group differences in cell adhesion molecules and pre-defined study and patient characteristics. | [
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32057951 | abstract | BACKGROUNDS: Recently, extensive evidence has indicated that the biological role of long non-coding RNAs (lncRNAs) in neurodegenerative diseases is becoming increasingly evident. The lncRNA brain-derived neurotrophic factor anti-sense (BDNF-AS) has been found to be dysregulated in Huntington's Disease. However, the function of BDNF-AS in Parkinson's disease (PD) remains unknown. The purpose of this present study was to explore the effect of BDNF-AS on PD and its underlying molecular mechanisms. METHODS: The MPTP-induced mouse model of PD and MPP+-induced SH-SY5Y cell model were established. Immunofluorescence was performed to determine the number of TH + positive cells. Mice behavioral changes were detected by pole and rota-rod test. SH-SY5Y cells viability, apoptosis was detected by MTT assay and flow cytometry. The number of autophagosome was measured by transmission electron microscopy. Dopamine content was tested by high performance liquid chromatography. Dual-luciferase reporter gene assay was utilized to verify the correlation between BDNF-AS and miR-125b-5p. qRT-PCR and western blot were used to detect gene expression levels. RESULTS: Our results showed that BDNF-AS was up-regulated in MPTP-induced PD model and dopamine neurons, and MPP + treated SH-SY5Y cells, while miR-125b-5p was down-regulated. The expression of BDNF-AS was positively related with the MPP + concentration. BDNF-AS knockdown could significantly promote cell proliferation, while inhibit apoptosis and autophagy in SH-SY5Y cells treated by MPP + . Silencing BDNF-AS could also increase TH positive neurons and significantly suppress the autophagy of PD mice. Additionally, miR-125b-5p, a putative target gene of BDNF-AS, was involved in the effects of BDNF-AS on SH-SY5Y cell apoptosis and autophagy. CONCLUSIONS: Our study demonstrated that knockdown of BDNF-AS could elevate SH-SY5Y cell viability, inhibit autophagy and apoptosis in MPTP-induced PD models through regulating miR-125b-5p, suggesting that BDNF-AS might act as a potential therapeutic target for PD. | [
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38141101 | methods | Methods Parent study It was a randomized, controlled, four-arm, parallel exercise and/or dietary intervention study (ClinicalTrials.gov: NCT03934476), with the primary aim of examining the VLCHF and HIIT effects on body composition and cardiorespiratory fitness (Cipryan et al.,). Data were collected in Ostrava, Czech Republic. There were 91 participants included into four study groups and they completed a 12 week experimental period. Participants were randomly allocated to one of the four study groups: (1) HIIT and habitual diet, (2) very low-carbohydrate, high-fat diet (VLCHF) and habitual physical activity (no regular exercise training), (3) VLCHF diet and HIIT and (4) control (habitual diet and physical activity, no regular exercise training). Dual-energy X-ray absorptiometry (DXA) and graded exercise tests to volitional exhaustion were used for body composition and cardiorespiratory fitness (CRF) assessments, respectively. To obtain measures of no intervention, a control group was utilized. Participants in the control group were advised not to change their habitual diet and physical activity regime. Therefore, no diet advice was provided. We utilized the infrastructure of this trial to conduct a pre-planned ancillary study focused on lipidomic and metabolomic analysis. We analysed blood samples following a 3 h fast before the experimental period (T0) and after 4, 8 and 12 weeks (T1, T2 and T3, respectively). The participant set used for the primary and secondary analyses was identical with the participant set presented in this metabolomics study (intention-to-treat analysis). Participants Participants were randomly allocated to four study groups: (1) HIIT and habitual diet, (2) very low-carbohydrate, high-fat diet (VLCHF) and habitual physical activity (no regular exercise training), (3) VLCHF diet and HIIT, (4) control (habitual diet and physical activity, no regular exercise training) (Cipryan et al.,). Inclusion criteria were age 20–59 years, non-smokers, overweight/obesity (BMI 25.00–40.00 kg/m2), no specific sports training or regular exercise (low physical activity), no excessive alcohol intake, willingness to accept random assignment, no evidence of liver, renal, metabolic and cardiopulmonary disease and diseases contraindicating physical activity, no cancer, no psychiatric illness, no pregnancy or breast-feeding, not on any specific diet, PAR-Q pass, body weight stable for the last 2 months and not on a weight loss plan, no hypoglycaemic, lipid lowering, antihypertensive or psychiatric medications as well as medications known to affect body weight or energy expenditure. Participants had no previous experience with the VLCHF diet and HIIT. All study participants provided written informed consent. The study design was approved by the local University Ethics Committee. High-intensity interval training (HIIT) Before the start of the intervention, the participants in both HIIT and VLCHF + HIIT groups received a detailed instruction on the HIIT program. Participants were told to complete 3 sessions per week. Two HIIT sessions were completed during weeks 4, 8 and 12 when the participants visited laboratory, one session was home based. Each HIIT session started and finished with 5 min of slow walking. HIIT was composed of series of 3 min of a high intensity walking (Borg´s scale RPE 18–19) followed by 3 min of low intensity walking (RPE 9–11). There were 4, 6 and 8 high intensity intervals set up for the first, second and third 4 week period, respectively. Therefore, the total session time increased from 31 to 43 min and finally 55 min during each 4 week period. Training intensity was monitored with a Polar M430 watch (Polar Electro, Oy, Finland). Training data were uploaded to Polar Flow and regularly analysed by an experienced researcher. Dietary intervention Participants in the HIIT only and the control group were asked to maintain their habitual dietary intake without restriction. The VLCHF diet was defined as allowing no more than 50 g of CHO per day (Feinman et al.,). The diet included no specific caloric goal. However, the participants in the VLCHF groups were advised to compensate for the total energy decrease caused by CHO intake restriction by increasing their natural non-trans fat intake (e.g., cream, butter and olive and coconut oil). The target for protein intake was recommended 1.5 g/kg lean body mass and, unlike the strict CHO restriction, participants were asked just to get as close as possible. The use of all sweetened and grain-based products was strongly limited. The recommended food included whole food sources such as meat, vegetables, non-sweetened products, full-fat dairy items, nuts and seeds. Detailed dietary advice was provided by a dietitian before and during the study (on request or at least once a month). A handbook was given to participants containing food lists, guidelines for estimating macronutrient amounts, and sample recipes. All foods and quantities consumed were recorded daily in all study groups beginning from seven days before the intervention period (www.kaloricketabulky.cz). Alcoholic beverages were restricted during the intervention period and dietary supplements were not permitted 1 month prior to and during the intervention, while caffeinated beverages were restricted only before the laboratory sessions. Chemicals and materials Methanol and 2-propanol were supplied by Merck (Darmstadt, Germany). Ammonium acetate, ammonium formate, formic acid and acetic acid were obtained from Sigma-Aldrich (Prague, Czech Republic). Click Fit 2 mL Eppendorf tubes were purchased from TreffLab (Degersheim, Germany); 2 mL cryovials and autosampler vials were purchased from Labicom (Olomouc, Czech Republic). Sample preparation The samples were prepared by mixing 50 μL of plasma with 150 μL MeOH. After vortexing, 500 μL methyl tert-butyl ether (MTBE) was added, and the mixture was shaken for 15 min. Subsequently, 150 μL of deionized water was added to form a two-phase system. After vortexing for 30 s, the mixture was deproteinized and centrifugated at 10,000 rpm (10,621×g) for 10 min at room temperature. The resultant supernatants were lyophilized and stored in an − 80 °C freezer if needed for later use. The freeze-dried lipid residues were resuspended in 2-propanol/methanol/deionized water (65:30:5, v/v/v) and used for subsequent analysis. For the metabolomic experiment 50 uL of plasma were mixed with 150 uL acetonitrile to precipitate proteins, the mixture was then centrifuged at 10,000 rpm and the supernatant collected in a new vial and evaporated to dryness on a SpeedVac (Labconco) instrument. Before analysis, the dried extract was resuspended in H2O:acetonitrile (1:1). Instrumental conditions Both lipidomic and metabolomic analysis used an Infinity 1290 (Agilent) UHPLC coupled to the 6560 Ion Mobility Q-TOF LC/MS (Agilent) with an Agilent Jet Stream (AJS) electrospray (ESI) source. The details of the lipidomic method are described elsewhere (10.3390/metabo12020124), briefly an Acquity BEH C18 column (1.7 μm, 2.1 mm × 150 mm; Waters, USA) was used for chromatographic separation. Lipids were separated by a gradient of mobile phases A: 10 mM ammonium formate and 0.1% formic acid in acetonitrile:water (60:40, v/v); mobile phase B was 10 mM ammonium formate and 0.1% formic acid in 2-propanol:acetonitrile (90:10, v/v) in ESI + mode, for ESI- mode formic acid and ammonium formate were replaced by acetic acid and ammonium acetate. The details of metabolomic method are described in the supplement. Briefly, metabolites were separated on an Acquity HSS T3 column (1.7 μm, 2.1 mm × 100 mm; Waters, USA) using a gradient of mobile phases A: 5 mM ammonium formate and 0.1% formic acid in water:MeOH (95:5, v/v) and mobile phase B: 5 mM ammonium formate and 0.1% formic acid in MeOH in ESI + mode, for ESI- mode formic acid and ammonium formate were replaced by acetic acid and ammonium acetate. The mass spectrometer acquired data in Full MS and autoMS/MS modes in the m/z range of 50–1200. Processing and statistical analysis of data generated by fingerprinting experiments Regarding to the lipidomics data analysis, data were processed by the LipidMatch suite [26], which uses MZmine 2 for feature extraction and an R script for lipid identification. Lipids were identified based on fragmentation spectra and accurate mass in silico libraries, which are part of the LipidMatch suite. Fragmentation spectra of the significant compounds from metabolomics were also compared to those present in METLIN and LIPIDMAPS databases, and their identities were confirmed. In case of metabolomics data, the data were processed by Profinder software (Agilent Technologies, Santa Clara, CA, USA) and MZmine 2. The data matrices obtained from lipidomics and metabolomics data processing were imported to SIMCA for multivariate analysis and Mass Profiler Professional (MPP, Agilent technologies for univariate analysis and metabolite profiling. Logarithmic transformation and pareto scaling were used to pre-process the data. Two-way ANOVA (corrected p-value cut-off: 0.05; p-value computation: Asymptotic; Multiple Testing Correction: Benjamini-Hochberg) analysis was applied to the data matrix to filter significant entities affected by diet group and sampling point factors. Sample size estimation An a priori power analysis using GPOWER (Faul et al.,) with power set at 0.80 and significance level set at 0.05 was calculated retrospectively. The power analysis indicated that a total sample of 76 people would be needed to detect large effects (f = 0.40) for this study with 4 groups. A total sample of 180 people would be needed to detect medium effects (f = 0.25) Thus, the sample size was sufficient to reveal that a large effect could not be interpreted as non-significant. | [
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36014347 | title | Inhibition of Endoplasmic Reticulum Stress Improves Acetylcholine-Mediated Relaxation in the Aorta of Type-2 Diabetic Rats. | [
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37132560 | intro | Introduction Dementia and mild cognitive impairment (MCI) are major neurocognitive disorders that pose remarkable health challenges worldwide. Dementia can be quite dehumanising in its advanced stages. Mild cognitive impairment occupies the intermediate stages in the continuum of cognition and is considered the leading point for preventive strategies. Mild cognitive impairment is a condition that was first proposed by Petersen as a nosological entity that refers to older individuals with mild cognitive deficit without dementia; hence, it was initially termed Cognitive Impairment No Dementia (CIND). Subjects with MCI have mild but measurable changes in thinking abilities that are noticeable to the individual, family members and friends. Mild cognitive impairment was initially described as a single syndrome in which the individual displays subjective memory complaints and objective deficits in episodic memory tests, with no impairment in activities of daily living (ADL) and no dementia. Mild cognitive impairment differs from dementia because it is not severe enough to interfere with independence in daily life. Occasionally, clinical criteria dictate that the onset of dementia is preceded by a prodromal state of mild cognitive decline and individuals with MCI have been found to be at increased risk of dementia. The global prevalence of dementia is estimated at 5% to 7% in people over 60 years. Documented country-specific dementia prevalence in sub-Saharan Africa (SSA) ranges between 2% and 5%. The prevalence estimates were 18.4% and 2.9% for MCI and dementia, respectively, in a study carried out by Ogunniyi et al. in South-West Nigeria. A prevalence of MCI of 11.8% has also been reported from South-East Nigeria. The risk factors for MCI include increasing age and other medical conditions and lifestyle factors such as, diabetes, smoking, high blood pressure (BP), elevated cholesterol, obesity, depression, a lack of physical exercise, low education level and infrequent participation in mentally or socially stimulating activities. As a nosological entity, MCI conveys important health implications, in particular an increased risk of developing dementia in the near future. This is evident from studies of MCI patients presenting to the clinics with a memory disorder, in whom the annual rate of progression to dementia was reported to be between 10% and 15%. Dementia disrupts the normal functioning of affected individuals and their families, imposing significant social and economic burdens. This is especially severe in low- and middle-income countries (LMICs), where dementia is the most important independent contributor to disability in older adults, and resources to diagnose and treat dementia are limited. There is a paucity of information on major neurocognitive disorders in SSA where the number of individuals with neurocognitive disorders and other disease burden is expected to increase because of demographic transition. There is a need to assess the modifiable risk factors for MCI as this will help in determination of the appropriate interventions that are implementable to prevent or reduce the rate of cognitive decline among this group of people. Knowing the prevalence of MCI is also very important to create awareness and this will hopefully lead to early detection of MCI and dementia among older persons. The aim of the study was to assess some of the risk factors for MCI in older adults aged 65 years and above in a tertiary care hospital in Southern Nigeria with the ultimate goal of reducing the burden of the condition. The specific objectives were to measure the prevalence of MCI and assess the relationship between sociodemographic factors and MCI. The study also aimed to assess the relationship between some risk factors for MCI such as obesity, alcohol use, tobacco smoking and hypertension, and MCI among this category of people. | [
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37052777 | intro | Inflammation specificities and factors involved The regulation of the inflammatory response remains a central aspect in the understanding of many pathological processes. The three phases that characterize inflammation, i.e., initiation, extension, and repair/resolution, are controlled by a large number of factors with specific temporal and intensity patterns. These profiles vary between tissues and species, defining the course of the pathological process and the impact on the organisms. However, despite the selectivity of many inflammatory reactions, there is an overlap in the molecular pathways involved. This diversity in the interactions between them defines specific fates in their control and the possible therapeutic interventions. An example of this is the involvement of P2X7 receptor signaling in the activation of the NLRP3 inflammasome, which requires the involvement of an additional priming signal from the TLR2/4 pathway. It is worth mentioning that the production of different bioactive lipids, such as prostanoids, is a common determinant in the progression of inflammatory processes (Fig. 1). The most abundant prostanoids from pro-inflammatory macrophages are synthesized after the expression of cyclooxygenase 2 (COX-2), which catalyzes the first step in the biosynthesis of prostanoids from arachidonic acid. The end products of the COX-2 pathway are the result of additional modifications via the action of cell-specific prostaglandin synthases (Fig. 2). COX-2 is encoded by the PTGS2 gene in humans (Ptgs2 in rodents) and it is expressed in the early stages of inflammation. The transcription of the PTGS2 gene is extensively induced in many inflammatory cells and tissues, except in hepatocytes, where only after preliminary pathological changes (i.e., liver regeneration after partial hepatectomy) is the ability to express COX-2 recovered. In the liver, this regulatory bias is only associated with hepatocytes, since Kupffer cells retain this pro-inflammatory activation. This interesting mechanism reflects the fact that, under physiological conditions, the portal blood contains pathogen-associated molecular patterns (PAMPs) and damage-associated molecular patterns (DAMPs), which do not activate COX-2 expression through cell surface receptors that recognize PAMP or DAMP. Dual role of prostaglandins in the regulation of inflammation The prostanoids synthesized by the COX-2 pathway can act in opposite ways: they can exert pro-inflammatory actions, but they can also promote and activate anti-inflammatory mechanisms. An example of this dual role is PGE2, which is one of the major products of the COX-2 pathway. Other prostaglandins, such as prostaglandin 15-deoxy-Δ12,14-prostaglandin J2 (15dPGJ2) are potent anti-inflammatory molecules because their chemical structure contains a cyclopentenone motif (due to the presence of α,β-unsaturated carbonyl groups). This chemical structure allows for non-enzymatic reactions with cysteine residues in proteins, via Michael addition modifications (Figs. 1 and 2). These Michael adducts have an impact on the enzyme activity and function of different proteins involved in the control of the inflammatory processes, such as the transcription factor NF-κB, which exerts an important activation of the pro-inflammatory response, and is inhibited by Michael addition of 15dPGJ2. In contrast, transcription factors that repress the progression of inflammation, such as the peroxisomal proliferator-activated receptor γ (PPARγ) are activated by 15dPGJ2 by this post-translational modification via Michael addition. Mechanisms of action of prostaglandin E2 In recent years, several groups have been interested in the role of prostanoids in the regulation of the inflammatory process. Our group focused on studying the effect of PGE2 accumulation at sites of inflammation, using cells and animal models deficient in COX-2 or expressing a transgene encoding COX-2, or by administering selective COX-2 inhibitors (called generically coxibs), but maintaining the activity of COX-1, an enzyme that contributes to the synthesis of prostanoids in healthy conditions. Regarding the mechanism of action, PGE2 binds to and activates specific G protein-coupled membrane receptors called E-type PGE2 receptors (EP receptors; Fig. 3). Four different receptors, EP1 to EP4, have been identified from a biochemical and pharmacological point of view. Interestingly, these receptors are not exclusively expressed on the plasma membrane, but also on other intracellular membranes, such as the nuclear membrane. Activation of EP1 promotes the mobilization of intracellular Ca2+ stores through activation of the phosphoinositide 3-kinase pathway. This transient change in cytoplasmic Ca2+ has an impact on ionic fluxes, cellular metabolism and organelle function (i.e., mitochondria), and activates Ca2+-dependent enzymes, such as various isoforms of protein kinase C (PKC). Therefore, PGE2 induces Ca2+- and PKC-dependent effects in cells expressing EP1. A relevant fact of EP1 is that the expression profile in cells is different between humans and rodents, which makes it difficult to translate the results between different species. The binding of PGE2 to EP2 and EP4 receptors promotes the dissociation of the Gαs/Gβγ complex from the G protein-coupled receptor. The Gαs subunit stimulates adenylate cyclase activity, which increases the intracellular levels of cyclic AMP (cAMP) and, therefore, activates the protein kinase A-dependent pathway. However, EP2 and EP4 have partially non-overlapping functions: EP2 is mainly involved in smooth muscle cell relaxation, whereas EP4 activation exhibits pro- and anti-inflammatory functions ranging from vasodilation to angiogenesis, and metastasis progression. Unlike EP2/EP4, activation of EP3 leads to a reduction in intracellular cAMP levels. These EP receptors are expressed on various cell types and provide the basis for therapeutic interventions, using selective agonists and antagonists. However, in addition to EP-mediated effects, PGE2 can exert other actions, either by accessing the cytoplasm or through binding to additional receptors, for example through purinergic signaling, although these mechanisms are less characterized, which explains the effects independent of pharmacological targeting of the EP receptors. Purinergic signaling in inflammation Inflammation involves a large number of molecules, including cytokines, chemokines, prostanoids, and extracellular nucleotides that are released during inflammation and activate myeloid and lymphoid immune cells. Extracellular nucleotides (i.e. ATP and UTP) have been recognized as a new class of innate immune regulators that act through the P2 receptors and modulate the inflammatory reaction. These extracellular nucleotides, which are released at sites of inflammation due to infection or cell damage, contribute to immune cell activation, including cytoskeleton reorganization, cell migration, phagocytosis and exocytosis. Extracellular nucleotides also exert tissue-specific actions. For example, in the brain, they have been associated with different pathologies affecting immune cells (microglia), such as neuropathic pain; indeed, targeting extracellular nucleotide signaling is a pharmacological therapeutic tool that is being investigated in clinical trials. Purine and pyrimidine nucleotide receptors are involved in many neuronal and non-neuronal mechanisms: in short-term signaling, they are involved in the regulation of neurotransmission, neuromodulation of inflammation and neurosecretion, promotion of platelet aggregation and vasodilation; and in long-term actions, they are associated with cell proliferation, differentiation, motility, cell-death in development and regeneration. Currently, the accepted P2Y receptors are P2Y1, P2Y2, P2Y4, P2Y6, P2Y11, P2Y12, P2Y13 and P2Y14. Among the metabotropic P2Y receptors, P2Y2, P2Y4 and P2Y6 are activated by uridine and adenine nucleotides and are coupled to phospholipase C (PLC) activation. As a consequence of the release of nucleotides into the extracellular medium, the agonistic action on P2Y receptors promotes an increase in the intracellular concentration of diacylglycerol (DAG) and inositol triphosphate (IP3), which induces the release of calcium from intracellular stores and the activation of several signaling pathways. P2Y receptors are expressed on various cell types and are functionally relevant in the activation of resident and circulating immune cells. Crosstalk between PGE2 and P2 receptors in macrophages The interaction between purinergic signaling and prostanoids has been described in different cell types. In macrophages, exposure to UTP increases the expression of COX-2, and nitric oxide synthase 2 (NOS2) under pro-inflammatory conditions. Macrophages can be polarized into pro-inflammatory (‘classically activated’ or M1, using microbial stimuli such as LPS, or cytokines such as IFNγ) or anti-inflammatory/pro-resolving phenotypes (‘alternatively activated’ or M2, using IL4 and/or IL13 as stimuli). Because macrophages can adopt different functional profiles this crosstalk between PGs and P2 signaling can contribute to the polarization of these cells. Therefore, the activation of P2 receptors helps to modulate the function of macrophages in the context of the environmental signals that govern the fate of the inflammatory response. The presence of locally elevated concentrations of extracellular ATP promotes the activation of the P2X7 receptor, while UTP and UDP, and lower concentrations of ATP act mainly through P2Y2, P2Y4 and P2Y6, respectively. Nevertheless, the contribution of P2Y2/P2Y4 or P2Y4/P2Y6 heterodimers can also be considered in this regulatory hub. The signaling through the P2X7 receptor in macrophages is by far the most studied purinergic pathway. This is because P2X7 receptor activation participates in the regulation of several stress signal pathways and, more importantly, activates the NLRP3 inflammasome cascade. It is well known that P2X7 activation by ATP contributes to the regulation of the innate response in macrophages: it favors the host defense against intracellular pathogens, an effect that is triggered by the release of reactive oxygen and/or nitrogen species. In addition to this, the activation of the NLRP3 pathway promotes the maturation of pro-inflammatory cytokines (i.e., IL-1β and IL-18), and an increase in the PGE2 levels. The pathways involved include a rise in Ca2+ influx and the activation of the MAP kinase signaling pathways. Interestingly, the crosstalk between P2Y receptors and PGE2 has also been reported in macrophages from P2X7 receptor-deficient mice, or after inhibition of the receptor with Brilliant Blue G as well as with the receptor antagonist A 438079, which indicates that the interaction between P2Y receptors and PGE2 is independent of P2X7 receptors. Furthermore, macrophages challenged with specific agonists of the P2X7 receptors did not show the inhibitory effect of PGE2 on Ca2+-mobilization. Regarding the role of the polarization phenotype of macrophages on the expression levels of purinergic receptors, M1 and M2 differentiated cells exhibit similar values, both in RNA and protein levels. However, pro-inflammatory macrophages display rapid and time-dependent repression of the levels of the downstream receptor-associated phospholipase C β1 and β2 isoenzymes, which contribute to the reduced signaling dependent on P2Y receptor activation. The effect of extracellular ATP on the progression of the anti-inflammatory phenotype in macrophages does not involve P2Y/P2X receptor-mediated processes but rather depends on pyrophosphate ATP bonds. The pathways involved promote a reorganization of the actin cytoskeleton that favors the clustering of these actin filaments, which ultimately contribute to the clustering and organization of the NLRP3 inflammasome complex. In addition, the participation of ectonucleotidases seems to contribute to the transition of macrophages from a pro-inflammatory (M1) to an anti-inflammatory (M2) phenotype. This transition is believed to facilitate the resolution of the inflammatory reaction accomplished by macrophages. Interestingly, unlike naïve and M2 polarized macrophages, M1 cells do not display the inhibitory effect of PGE2 on Ca2+ mobilization. These polarization specificities were observed in both rodent and human macrophages. As for the mechanism by which M1 macrophages fail to show this PGE2-dependent P2Y desensitization, it has been shown to occur at least two hours after the pro-inflammatory challenge. This suggests that this is not the result of the rapid signaling elicited after TLR4 and/or pro-inflammatory cytokine receptors engagement, but rather is due to secondary events in the signaling process. From a mechanistic point of view, the sustained response to P2Y receptors in the presence of PGE2, as occurs in M1 macrophages ensures the activity of the purinergic signaling in the early steps of inflammation. As an extension, in platelets, a cross-desensitization between ADP and the thromboxane receptor signaling has been reported. All of these interactions play an important role in several inflammatory and degenerative disorders, such as multiple sclerosis, amyotrophic lateral sclerosis and Alzheimer´s disease. Indeed, in these pathologies, extracellular ATP exerts pro-inflammatory actions that cause the release of cytokines and the production of PG. Interestingly, this modulation could play an important role in the anti-inflammatory effects of PGE2. A relevant aspect in this context of the heterogeneity of P2Y/P2X receptors is the possible crosstalk between the P2X and P2Y receptor families. An example is the synergism between both families in the activation of dendritic cells, which are necessary for the efficient initiation of immune responses. In addition to antigens, the presence of P2 agonists released by necrotic cells results in a synergistic activation and maturation of dendritic cells, and therefore, in more efficient signaling in T cells, leading to increased expression of pro-inflammatory mediators and adhesion molecules. Molecular mechanisms involved in PGE2-P2Y receptor crosstalk The pathways involved in the crosstalk between P2Y receptors and PGE2 on macrophages have been established using biochemical (inhibitors and activators of signal transduction pathways), pharmacological (mainly through the use of agonists and antagonists of the EP and P2Y receptors) and genetic (cells lacking P2X7 receptor or COX-2; expressing a COX-2 transgene or expressing different constructs of the proteins that participate in the signal-transduction pathways) approaches. Based on the data from these different strategies it was concluded that PKD1 phosphorylation at S916 is a necessary condition to suppress PGE2-dependent UTP-mediated Ca2+-mobilization. In contrast, selective inhibition of PKD1 is sufficient to attenuate the effect of PGE2 on P2Y signaling. PKDs are ubiquitously expressed and regulate various cellular processes, including oxidative stress, gene expression, cell survival, vesicle trafficking and, interestingly, P2X7 signaling, although their precise function in macrophages remains poorly characterized. Analysis devoted to identifying the PKD isoform(s) involved in this P2Y crosstalk showed that PKD1, which is regulated by extracellular ligands in macrophages, is specifically targeted. Furthermore, overexpression of PKD1 reduced the effect of UTP on Ca2+ mobilization but when a vector encoding a catalytically inactive kinase of PKD1 was expressed, the response to UTP persisted and the inhibitory effect of PGE2 was abolished (Fig. 4). In fact, an association of PKD1 with TLR9 and, in general, with the MyD88-dependent pro-inflammatory innate immune responses has been described. Additionally, PKCδ activation has been reported to act as an upstream PKD1 activation step. However, transfection of macrophages with constitutively active PKCδ constructs did not mimic the effects of PGE2 on UTP-dependent Ca2+ mobilization. However, expression in macrophages of a constitutively active PKCε, but not of other classical, new, or atypical PKCs, was sufficient to mimic the effects of PGE2 on P2Y receptors in terms of Ca2+ mobilization. Regarding the role of macrophage polarization in this PGE2-P2Y crosstalk, naïve and anti-inflammatory/pro-resolving (M2) macrophages show this inhibitory interaction, but it was not observed in those that were polarized to M1 pro-inflammatory cells. Under these M1 conditions, PGE2-dependent phosphorylation of PKD1 at S916 is not observed, while naïve and M2 macrophages exhibit this PKD1 phosphorylation. This phosphorylation of PKD1 at S916 has been reported to correspond to a fully activated PKD1. Moreover, activation of PKD1 has been associated with the response to upstream PKCs and/or activation of G-proteins and various receptor-associated tyrosine kinases. The PGE2-dependent activation of PKD1 promotes DAGs release not only at the plasma membrane level but also from other compartments, such as the endoplasmic reticulum and the Golgi apparatus. Interestingly, PKD activation plays a role in the crosstalk between P2Y and P2X receptors (Fig. 4). In line with this, P2X4 receptor signaling favors the activation of phospholipase A2 (PLA2) and, in turn, the supply of substrates for COX-2 and, therefore, the increase in the release of PGE2 that participates in the intercellular crosstalk between P2X and P2Y receptors. The regulation of P2Y activity in macrophages, which involves the participation of PGE2, has functional implications in the basic biological responses of these cells, such as metabolic activation and migration. In this regard, cell migration contributes to normal development and differentiation. Recent data indicate that extracellular nucleotides can regulate the migration and attachment activities of “professional phagocytes” (macrophages, neutrophils and microglia) and other cell types (i.e., fibroblasts, endothelial cells, neurons and keratinocytes). From a functional point of view, it has been shown that PGE2 inhibits P2Y-dependent macrophage migration, even in the presence of other chemoattractants. These chemotactic actions are common for several P2Y receptors, such as P2Y2, P2Y4, and P2Y6. These observations are consistent with the fact that P2 receptors participate in a wide range of phagocytic and chemotactic actions, as described for P2Y2,4,6 receptors in the phagocytosis of apoptotic bodies by microglial cells. In addition to these signaling mechanisms, the EP3 receptors have been involved in the impairment of Ca2+-mobilization by PGE2 in cerebellar astrocytes. Interestingly, PGE2 promotes the internalization of P2Y4 in fibroblasts transfected with COX-2, an effect that is suppressed after the inhibition of COX-2 with the coxib DFU. Moreover, the blockade in Ca2+-mobilization by PGE2 has an important consequence in terms of the activation of different signaling pathways in fibroblasts, including activation of various PKCs and the energetic metabolism via activation of AMP-dependent protein kinase (AMPK) and inhibition of acetyl-CoA carboxylase (ACC). Again, this regulatory network is suppressed when fibroblasts are in an inflammatory environment. Recent trends in tissue repair of inflammatory lesions have focused on the interaction between stromal cells, such as macrophages and fibroblasts. Based on these observations, it can be proposed that targeting the stromal microenvironment is likely to be an important and promising strategy for future anti-inflammatory and pro-resolution therapies. In summary, the translation of basic studies on the interactions between prostaglandin synthesis and the signaling through P2Y and P2X receptors in the immune system to clinical trials can result in the development of new therapeutic options to modulate the course of inflammatory diseases. | [
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37152359 | title | Computerised cognitive assessment in patients with traumatic brain injury: an observational study of feasibility and sensitivity relative to established clinical scales | [
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38094513 | abstract | Age-related hearing loss (ARHL) is the most common cause of hearing loss and one of the most prevalent conditions affecting the elderly worldwide. Despite evidence from our lab and others about its polygenic nature, little is known about the specific genes, cell types, and pathways involved in ARHL, impeding the development of therapeutic interventions. In this manuscript, we describe, for the first time, the complete cell-type specific transcriptome of the aging mouse cochlea using snRNA-seq in an outbred mouse model in relation to auditory threshold variation. Cochlear cell types were identified using unsupervised clustering and annotated via a three-tiered approach—first by linking to expression of known marker genes, then using the NSForest algorithm to select minimum cluster-specific marker genes and reduce dimensional feature space for statistical comparison of our clusters with existing publicly-available data sets on the gEAR website,1 and finally, by validating and refining the annotations using Multiplexed Error Robust Fluorescence In Situ Hybridization (MERFISH) and the cluster-specific marker genes as probes. We report on 60 unique cell-types expanding the number of defined cochlear cell types by more than two times. Importantly, we show significant specific cell type increases and decreases associated with loss of hearing acuity implicating specific subsets of hair cell subtypes, ganglion cell subtypes, and cell subtypes within the stria vascularis in this model of ARHL. These results provide a view into the cellular and molecular mechanisms responsible for age-related hearing loss and pathways for therapeutic targeting. | [
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39045493 | results | FINDINGS Overall, both older adults and family caregivers displayed similar behaviors and conversation preferences when designing VIPAs dialogues for behavioral activation. In this section, we focus on how users perceived VIPAs’ role in mental health intervention delivery through different levels of anthropomorphism displayed by VIPAs. Then, we attend to both older adults’ and family caregivers’ perspectives on how dialogue-based interactions can provide social and emotional support. Finally, we describe the need to respect older adults’ autonomy and privacy in conversational-based mental health interventions with VIPAs. Anthropomorphism, Emotional Expression, and Colloquial Language Use in VIPAs One of the challenges in conversation design for VIPAs is determining the level of anthropomorphism of the agent that is contextually appropriate for the task it is engaging in with users. In our study, we found that all participants used anthropomorphic language in the conversation design task but showed varied levels of preferences in the use of colloquial languages. In most scenarios, participants chose to use direct and short language for the agent’s utterances, especially when the task was focused on delivering the behavioral activation intervention through the VIPA. They commonly chose dialogues or wrote their own that were straightforward and simple instead of ones with pleasantries. For instance, during the Goals and Reminders scenario, participants were given two examples of possible VIPA utterance, (A: “Would you like to set weekly goals for these activities?” and B: “Now that I know what you/they like doing, I want to know how often you/they would want to do them. Would it be ok if we talk about that?”). Six participants preferred option A and two rewrote the dialogues because the pleasantries in option B felt inauthentic and off-putting. Although participants shared different reasons for their preferences against pleasantries, the most common reason was the mental model of VIPAs being an artificial intelligence instead of a person, an object rather than a sentient technology. One caregiver said, “‘Thanks for sharing that.’ I don’t think it needs to go into too detailed of being empathetic because […]’Whoa! You’re not a person. What are you trying to say to me?’” (CG7). Because a VIPA is not perceived as a person, participants felt that they did not need to uphold the social responsibility to “have dialogue or a conversation with it” (OA5). Furthermore, participants perceived certain word choices to be violating their mental models of insentient technology. Common phrases that led to negative reactions from participants include VIPAs expressing an emotion such as being excited (e.g., “I’m excited to work with you for the next 16 weeks.”) and curious (e.g., “I’m curious how doing these activities make you feel.”). One older adult thought that it was “kind of silly for a digital assistant to say, ‘I’m excited,’ because it’s a machine. How excited can it be?” (OA4). Similarly, a caregiver commented that the VIPA could not be curious because it was an AI, and it was merely “gathering this data ‘cause [it’s] programmed to” (CG2). As such, emotional expression that would anthropomorphize the VIPA was consistently perceived as pretentious. Particularly, participants strongly disliked VIPA’s comment of “that’s a great name” when participants initially shared their name with the VIPA. Because participants understood that the VIPA “is AI, so that’s programmed in there” (CG5), which seemed “kind of patronizing” (CG5) when VIPAs made such comments. Instead, participants chose the more direct response (i.e., “Thank you.”) that proceeded to the next interaction. In the same scenario, some participants chose to anthropomorphize the agent, attributing feelings and human-like colloquial language use to the VIPA. However, differences existed; while some participants felt that the VIPA was “a little too perky, like it’s trying too hard” (OA4) and “trying to get on [their] good side” (OA3), which felt inauthentic, one participant felt that emotional expression represents “a more casual type of a statement” (CG4). Despite critiques toward the VIPA prototypes in some scenarios, participants expressed a desire for the VIPA to use friendly and colloquial languages in other scenarios. For example, when presented with two options introducing behavioral activation (A: “My goal is to help you to learn about behavioral activation technique which focuses on using behaviors to activate pleasant emotions. It has been shown to improve depressive symptoms.” and B: “I’m really interested in learning about how to help people feel more positive and came across this technique called behavioral activation. Want to hear more about it?”), one caregiver commented that she option B was “more colloquial, more conversational, as opposed to a little more formal” (CG5), which was more inviting to use with older adults. An older adult compared the more formal languages to VIPAs “assess[ing them] like a psychiatrist or something” (OA2). Although a more formal language may be more clinically appropriate for delivering evidence-based mental health service, this older adult felt that receiving an evidence-based mental health service through VIPAs should not be the same as speaking with a mental health professional or taking a mental health questionnaire. The desire for informality may be related to participants wanting VIPAs to maintain a natural flow of conversation while keeping the dialogues brief and straight to the point. Most of these interactions stemmed from the participants’ habitual interactions with other people. As a result, when VIPAs greet the users, older adults expect a friendly greeting because that mimics how their typical greeting interaction is like: “when I greet someone, I like to say ‘Good Morning.’ It seems more natural to have that. A sound effect isn’t quite there” (OA3). Some participants displayed contradictions in their conversational preferences. For example, OA33 previously stated that they “don’t want to have a conversation with artificial intelligence” (OA1), but later said they “want it to be flowing all the time – real easy conversation kind of thing” (OA1). To resolve this tension, one participant designed their dialogues in a scaffolding approach, starting with questions that were “a little more basic, and not so intimidating when you’re just starting to do that” (CG7). Others provided concrete examples of how this could be achieved. When presented with the Tracking and Assessment scenario where the VIPA conducted a progress check with the participant (A: “After you did not complete the activity, have family time, how do you feel?” and B: “I want to check in with you to see how you’re feeling after not having family time. Can you tell me how you’re feeling?”), an older adult rewrote the dialogue to be “Are you okay with not having family time tonight” (OA5). This aligns with other participants’ preferences for shorter, more direct, and less clinical language that does not suggest VIPAs having emotional expression while maintaining the interpersonal characteristics of a conversation. In sum, while participants anthropomorphized the agent at times, they also recognized the agent was non-human and found the use of overly-human-like language use to be unpleasant. VIPA Reduces Perceived Caregivers’ Burden VIPAs can offer social and emotional support for older adults not only by being a companion but also a listener and a personal entourage, thus lowering the burden and reducing the responsibilities caregivers may experience when caring for their family members. Older adults in our study saw the VIPA as a useful tool for emotionally expressing themselves without worrying about burdening their caregivers. They valued VIPAs’ inability to be hurt and the ability to provide nonjudgmental responses during moments of depression and hardship: “I will snap back at it. It’s easier to snap back at it than to snap back to my husband or somebody else” (OA1). Interestingly, OA1 followed up by sharing that they did not actually expect a response from the VIPA, stating that “She’s grouchy. Leave the lady alone” (OA1). Other older adults also appreciated the mere presence of VIPAs and did not expect responses from the agent in similar situations. This is because older adults mainly wanted an outlet to express themselves and were aware of VIPA’s limitations as a machine. OA5 provided a specific example in which they could not “get in touch with their friends and doing something with them” (OA5). Although frustrated, they explained that they would tell the voice agent about their frustration and what happened, but they “don’t expect Alexa to really do anything about it” (OA5). The mere act of telling VIPAs about their feelings act as an emotional outlet for older adults in the study. Because of that, participants chose to have the VIPA simply acknowledge their feelings with generic language (e.g., “Thank you”) or no response at all. Additionally, anhedonia and overall low motivation and energy are common depression symptoms. As a result, depressed older adults may struggle to come up with pleasant activities, which is a challenge to implementing behavioral activation treatment. One of the scenarios (i.e., Curating Activities) in the study included probes that asked the participants to list pleasant activities they would like to engage in, during which one older adult stated that “list[ing] three activities that give [them] pleasure or make [them] feel accomplished” is a “difficult question to answer” (OA6). Instead of placing this additional responsibility on caregivers who may already feel taxed, caregivers particularly believed that VIPAs can support older adults by providing recommendations based on their preferences, physical conditions, and mood data. Namely, caregivers recommended that VIPAs could suggest and provide guided mindfulness activities or “a deep breathing exercise” (CG6) when older adults are “having a very anxious day” (CG40) or simple activities to get the person started” (CG1). Older adults and caregivers felt that this approach could provide social support without suggesting that the VIPA has emotional agency. Furthermore, in the Tracking and Assessment scenario where the VIPA checked on the user’s progress on activity goal-completion, participants often rewrote the dialogues to support emotion processing. Particularly, if older adults reported that they were unable to complete an activity as planned due to depression, responses from VIPAs should be “empathetic” (CG2) rather than being “a homework checker” (CG7). Participants suggested that the VIPA can offer words of encouragement that do not compromise their mental model of the technology. For example, VIPAs could acknowledge the hardship and encourage participants to try again: “Okay. You can try again tomorrow” (OA2). VIPAs could also ask if the older adults would like to hear a joke (“Would you like to hear a joke to cheer up?” (OA3)) or affirmations, such as “Great job” (CG1) and “I’m glad that you did [activity]” (CG7). Caregivers believed that VIPAs could provide social support to motivate older adults to complete activities for mental health intervention. This is crucial to behavioral activation, which uses behavioral goal setting to activate elevated mood among patients who struggle to find intrinsic motivation to engage in pleasurable activities. Preserving Autonomy and Privacy in VIPA-mediated Mental Health Interventions Autonomy and privacy are important topics to consider when creating technologies, so special considerations should be placed on preserving these two components in human-VIPA dialogue exchanges. In addition to the existing research on autonomy and privacy in VIPAs, our findings provide additional insight into the similarities and differences in priorities of user autonomy and privacy between older adults and family caregivers, especially when using VIPAs for mental health data collection and data sharing. Autonomy. Both older adults and caregivers agreed that VIPA’s features and conversational styles should allow older adults to maintain agency and independence when making decisions about their own mental health management. They noted that the role of the VIPA should be to support older adults, not supervise or monitor them, and the overall interaction should be a collaborative process. Participants suggested that it would be inappropriate for a VIPA to use patronizing or demanding languages; “don’t want it to sound like [VIPA]’s in charge of my life. I like for it to give me options” (OA1). Similarly, caregivers acknowledged that despite needing physical support and help with transportation and errands, older adults are “still very independent” (CG6). Therefore, it is important to avoid “making [them] feel like [they’re] being checked up on all the time” (CG6). Instead, VIPAs should empower them and help to maintain their independence through a more suggestive approach, making “[older adults] feel involved with the process; not that [the caregiver] was bossing [them] around or something” (CG1). In the Suggestions by Caregivers scenario, one participant wrote, “Do you want me to add the suggestions to your activity list?” (OA6) instead of having the VIPA automatically add the recommendations suggested by caregivers. A specific example provided by participants is supporting flexibility in goal-setting, which is a common task in many evidence-based mental health interventions (e.g., behavioral activation). In both probing dialogue options presented in the Goals and Reminders scenario, the VIPA prototype was rigid and asked the users to provide both the number of times per week expected to progress toward the activity goal, as well as the specific time of day to do so. However, older adult participants described their lifestyle as unstructured and preferred it to be that way. Also, because mental health can vary on different days, caregivers also felt that there would be instances when older adults may already be engaging in pleasurable activities on their own: “she reads all the time every day […] Off and on throughout the whole day and night” (CG1). Therefore, it is important to “let [the older adults] choose how they want to allocate” (CG5) time spent on activities. Privacy. Although older adult participants generally agreed that it is beneficial to share mental health and activity data with their caregivers, they had strong preferences for maintaining finegrained control over how their data was shared. They were particularly concerned about VIPAs announcing information when other people were physically present in the same space and sharing potentially private activity information with others. They also preferred providing consent at every point of sharing with caregivers as opposed to providing a one-time consent that would cover all cases. They explained that their preference may change from day to day and activity to activity, so they could avoid sharing “potentially embarrassing” (OA4) activities. Also, if they deemed the situation as trivial or caregivers would not be interested in learning the information, they would choose to not share the data: “if you don’t think your supporters would be interested, then you just don’t bother” (OA2). Therefore, when asked, participants all chose and designed dialogues that supported providing options (i.e., “Would you like to share [data] with your supporter?”) as opposed to VIPAs announcing the data sharing was taking place. On the other hand, caregivers were more concerned with the type of information that would be collected and the level of security of data storage. Several caregivers stated that the privacy policy and the rationale for data collection need to be transparent during the dialogue exchanges. A participant added a disclaimer at the beginning of the interaction: “We need this information for X, Y, Z purposes to customize this, this information will not leave the device, will not be used for marketing purposes” (CG2). Since engaging in evidence-based mental health services may involve sharing older adults’ data with a third party (e.g., clinical team), another participant also commented, “if somebody were monitoring the data, I would be curious how they were gonna use it” (CG1), but did not make direct design changes to the dialogues. By explaining why certain data is needed and how it will be used at every step of the conversation, we can improve transparency. This allows caregivers to be more likely to trust VIPAs and encourage their older adults to use the technology for mental health interventions. | [
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38426052 | abstract | Background Currently, there has been observed a significant alteration in the composition of the gut microbiome (GM) and serum metabolites in patients with psoriatic arthritis (PsA) compared to healthy individuals. However, previous observational studies have shown inconsistent results regarding the alteration of gut microbiota/metabolites. In order to shed light on this matter, we utilized Mendelian randomization to determine the causal effect of GM/metabolites on PsA. Methods We retrieved summary-level data of GM taxa/metabolites and PsA from publicly available GWAS statistics. Causal relationships between GM/metabolites and PsA were determined using a two-sample MR analysis, with the IVW approach serving as the primary analysis method. To ensure the robustness of our findings, we conducted sensitivity analyses, multivariable MR analysis (MVMR), and additional analysis including replication verification analysis, LDSC regression, and Steiger test analysis. Furthermore, we investigated reverse causality through a reverse MR analysis. Finally, we conducted an analysis of expression quantitative trait loci (eQTLs) involved in the metabolic pathway to explore potential molecular mechanisms of metabolism. Results Our findings reveal that eight GM taxa and twenty-three serum metabolites are causally related to PsA (P < 0.05). Notably, a higher relative abundance of Family Rikenellaceae (ORIVW: 0.622, 95% CI: 0.438–0.883, FDR = 0.045) and elevated serum levels of X-11538 (ORIVW: 0.442, 95% CI: 0.250–0.781, FDR = 0.046) maintain significant causal associations with a reduced risk of PsA, even after adjusting for multiple testing correction and conducting MVMR analysis. These findings suggest that Family Rikenellaceae and X-11538 may have protective effects against PsA. Our sensitivity analysis and additional analysis revealed no significant horizontal pleiotropy, reverse causality, or heterogeneity. The functional enrichment analysis revealed that the eQTLs examined were primarily associated with glycerolipid metabolism and the expression of key metabolic factors influenced by bacterial infections (Vibrio cholerae and Helicobacter pylori) as well as the mTOR signaling pathway. Conclusion In conclusion, our study demonstrates that Family Rikenellaceae and X-11538 exhibit a strong and negative causal relationship with PsA. These particular GM taxa and metabolites have the potential to serve as innovative biomarkers, offering valuable insights into the treatment and prevention of PsA. Moreover, bacterial infections and mTOR-mediated activation of metabolic factors may play an important role in this process. | [
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39007039 | abstract | Abstract The frequency of the apolipoprotein E ɛ4 allele and vascular risk factors differs among ethnic groups. We aimed to assess the combined effects of apolipoprotein E ɛ4 and vascular risk factors on brain age in Korean and UK cognitively unimpaired populations. We also aimed to determine the differences in the combined effects between the two populations. We enrolled 2314 cognitively unimpaired individuals aged ≥45 years from Korea and 6942 cognitively unimpaired individuals from the UK, who were matched using propensity scores. Brain age was defined using the brain age index. The apolipoprotein E genotype (ɛ4 carriers, ɛ2 carriers and ɛ3/ɛ3 homozygotes) and vascular risk factors (age, hypertension and diabetes) were considered predictors. Apolipoprotein E ɛ4 carriers in the Korean (β = 0.511, P = 0.012) and UK (β = 0.302, P = 0.006) groups had higher brain age index values. The adverse effects of the apolipoprotein E genotype on brain age index values increased with age in the Korean group alone (ɛ2 carriers × age, β = 0.085, P = 0.009; ɛ4 carriers × age, β = 0.100, P < 0.001). The apolipoprotein E genotype, age and ethnicity showed a three-way interaction with the brain age index (ɛ2 carriers × age × ethnicity, β = 0.091, P = 0.022; ɛ4 carriers × age × ethnicity, β = 0.093, P = 0.003). The effects of apolipoprotein E on the brain age index values were more pronounced in individuals with hypertension in the Korean group alone (ɛ4 carriers × hypertension, β = 0.777, P = 0.038). The apolipoprotein E genotype, age and ethnicity showed a three-way interaction with the brain age index (ɛ4 carriers × hypertension × ethnicity, β=1.091, P = 0.014). We highlight the ethnic differences in the combined effects of the apolipoprotein E ɛ4 genotype and vascular risk factors on accelerated brain age. These findings emphasize the need for ethnicity-specific strategies to mitigate apolipoprotein E ɛ4-related brain aging in cognitively unimpaired individuals. Im et al. reported that the combined effects of apolipoprotein E ɛ4 and vascular risk factors, particularly age and hypertension, have a stronger impact on the brain age index in the Korean group compared to the UK group. These findings underscore the need for ethnicity-specific strategies to manage vascular risk factors to mitigate apolipoprotein E ɛ4-related brain aging. Graphical Abstract | [
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38839833 | methods | Materials and methods Participants We performed a prospective evaluation of patients referred to the Alzheimer’s disease and other Cognitive Disorders Unit of the Neurology Service at the Hospital Clínic de Barcelona, Barcelona, Spain. Participants were consecutively recruited between March 2021 and November 2021. Inclusion criteria were: (1) COVID-19 diagnosis, based on biological or clinical diagnosis (polymerase chain reaction, antigenic rapid detection test or microbiological test); (2) Cognitive symptoms reported by the participant or an observer (family member, co-worker, health professional); (3) presence of cognitive symptoms ≥ 8 weeks after COVID-19 symptoms onset; (4) fluent in Spanish; (5) at least 6 years of formal education; (6) age 35–65 years old (participants above the age of 65 years were not included in order to avoid a possible confusion factor with onset of neurodegenerative diseases symptoms). Exclusion criteria were: (1) Previous diagnosis of any neurological, psychiatric, or medical condition that could affect the baseline cognitive performance, including previous chronic fatigue syndrome diagnosis; (2) any condition that prevented the completion of the cognitive assessment and/or MRI scanning. This study was performed according to the international consensus for research with human subjects (the updated version of Helsinki’s Statement, Fortaleza, 2013) and Spanish regulations. The Hospital Clínic de Barcelona Ethics Committee (HCB/2020/1483) approved the study, and all participants provided informed consent. Clinical and neuropsychological assessment Participants were evaluated at baseline, 1 month, 3 months, and 6 months of follow-up. The time between the COVID-19 infection and the baseline visit was 10.4 (SD 3.9) months. Participants underwent general and neurological assessments and a comprehensive neuropsychological (NPS) battery administered by a trained neuropsychologist. The battery included estimated premorbid IQ (Spanish Word Accentuation Test), verbal memory tests: Free and Cued Selective Reminding Test (FCSRT); visual memory tests: Rey-Osterrieth Complex Figure Test (ROCFT) Recall; language tests: Boston Naming Test, Vocabulary, semantic fluency; visuospatial abilities: ROCFT Time; and attention and executive function tests: Trail Making Test (TMT) A and B, Stroop Test, Symbol Digits Modalities Test (SDMT), Digit Span Test, Letter-Number sequencing, Symbol Search, and phonemic fluency. Raw scores were transformed to scalar scores adjusted by age and years of education, with a normal distribution and a mean of 10. Abnormal cognitive performance was defined as having a scalar score lower than seven (< 7) in one or more cognitive subtests. This cutoff score of less than seven (< 7) was selected to be in line with what is considered clinically relevant, that is aligning with accepted practice in the clinical settings. The participants also completed the Beck Depression Inventory (BDI), the Beck Anxiety Inventory (BAI), the Starkstein Apathy Scale (SAS), the Subjective Cognitive Decline Questionnaire (SCD-Q), the Multidimensional Fatigue Inventory (MFI-20) and the 36-Item Short Form Health Survey (SF-36). The NPS battery was identical in all the visits (baseline, 1 month, 3 months, and 6 months of follow-up). Neuroimaging studies MRI scanning was performed at inclusion and the end of the study (6 months) using a 3T Prisma Siemens (Siemens Medical Systems, Germany) with the same MRI protocol. A high-resolution 3D structural dataset (T1-weighted, MP-RAGE, repetition time = 2.400 ms, echo time = 2.22 ms, 208 slices, field-of-view = 256 mm, 0.8 mm isotropic voxel) was acquired for everyone at each time. We used the processing stream available in FreeSurfer version 6.0 (http://surfer.nmr.mgh.harvard.edu.sire.ub.edu/) to perform cortical reconstruction and volumetric segmentation of the T1-weighted acquisitions. FreeSurfer allowed us to obtain cortical thickness (CTh) maps and segment the subcortical structures. For longitudinal data, we used the longitudinal stream in FreeSurfer. All FreeSurfer preprocessing steps are reported in detail elsewhere. From the reconstructed data, we obtained global measures of mean CTh and grey matter (GM) volumes of the left and right hemispheres. In addition, we used the summary measures of mean CTh in 68 cortical parcellations and GM volumes of 14 subcortical structures, all derived from atlases available in FreeSurfer. All images and individual segmentations underwent visual inspection and manual correction, if necessary, by one of the authors of this study (APM). This quality control process verified the accuracy of white matter and gray matter segmentation obtained with FreeSurfer. In cases where corrections were required, manual adjustments were made to the mask, followed by rerunning the FreeSurfer stream to ensure optimal segmentation. Biological measures Blood samples were obtained at baseline (n = 49), at 1 month (n = 48), 3 months (n = 47), and 6 months (n = 46). An optional lumbar puncture to obtain cerebrospinal fluid (CSF) was offered to the participants at the basal visit (n = 12). Serum levels of neurofilament-light (NfL) and glial fibrillary acidic protein (GFAP) were determined by single molecule array technology (Neurology 2-Plex B Simoa, Quanterix®). A panel of cytokines, chemokines and other soluble mediators that included interferon (IFN)-α, β, and γ, interleukins (IL) IL-1β, IL-6, IL-8, IL-10, IL-17A, IL-18, tumor necrosis factor (TNF)-α2, IL-1 receptor antagonist (IL-1ra), Interferon-γ-Inducible Protein 10 (IP-10), granulocyte colony-stimulating factor (G-CSF), antigen CD25, chemokine ligand 1 (CX3CL1 or fractalkine), chemokine ligand 2 (CCL2), chemokine ligand 7 (CCL7) and ligand 9 (CXCL9) was analyzed in serum and CSF by a multiplexed bead based assay (Human Cyto Panel A, Merck, Germany) in a Luminex®100/200 platform. In addition, a tissue-based assay (TBA) consisting of an indirect immunohistochemistry (IIHC) with rat brain tissue and an indirect immunofluorescence assay (IIFA) with live neurons were performed to screen anti-neuronal immunoreactivity. The prospective study did not include cognitive normal non-PACS controls. As most of the biochemical measures evaluated here lack established cut-offs for normal values, we included in the analysis 38 serum and 24 CSF samples from non-COVID-19 healthy controls from a previous study in acute COVID-19. Normal results were defined as results within two standard deviations of the mean of the control group. We conducted biochemical analyses using identical kits and protocols for both healthy controls and PACS participants, at both baseline and follow-up assessments. Statistical analysis Raw cognitive scores were converted to scalar scores (SS) according to age and number of formal education, with a normal distribution with a mean scalar score of 10. Abnormal cognitive performance was set at SS < 7, which is the cutoff point used in clinical practice. If one subtest or more showed abnormal scores, the evaluation was considered abnormal. We first evaluated if cognitive test results differed in participants who scored within the normal range versus the pathological range on measures of anxiety, depression, apathy, fatigue, or quality of life scores. For that, we used previously described cut-offs: BDI ≥ 20 indicated moderate or severe depression, BAI ≥ 16 defined moderate or severe anxiety, SAS ≥ 14 was considered clinically significant apathy, SCD-Q ≥ 7 was considered pathological, MFI-20 cutoff of ≥ 60 was used for the description of a high-level versus low-level fatigue. SF36 subscales cutoff of ≥ 50 indicated normative scores; the reference population has a mean of 50 and a standard deviation of 10. We used permutation tests, adding age, sex, and years of education as covariates. Then, we studied the partial correlation between cognitive measures and physical and mental health scores with continuous variables and added age, sex, and years of education as covariables. We also analyzed the neuropsychological results with a principal component analysis (PCA), a dimensionality reduction method. It was conducted to elucidate the key factors contributing to the highest variability in the dataset. Tests showing a higher prevalence of alterations among participants, such as verbal memory and attention/executive function tests from the NPS, mental health and subjective cognitive decline questionnaires (BDI, BAI, SAS, and SCD-Q), were included. By analyzing the first component and the individual contribution of each variable to it, we estimated which variables explained the highest variability in the data. To assess the relationship between cognitive and mental health outcomes and MRI measurements, we conducted partial correlation analyses. These analyses focused on global and regional MRI metrics in relation to memory, executive function, anxiety, depression, fatigue, and subjective cognitive complaints (SCD). We included age, sex, and years of education as covariables. All analyses were corrected for multiple comparisons. We measured the partial correlation of inflammatory soluble mediators, NfL, and GFAP levels with SCD, memory and executive function outcomes, anxiety, depression, fatigue, and global and regional MRI measures and added age and sex as covariables. All analyses were corrected for multiple comparisons using the Benjamini–Hochberg adjustment. We performed longitudinal analyses including the baseline and the three follow-up visits with linear mixed-effects (LME) models to study changes between visits in cognitive measures, physical and mental health scores, global and regional MRI measures, and biochemical values for all the available data in each case. For cognitive tests, age, sex, and years of education were added as fixed effects. In the MRI and biochemical studies, age and sex were considered fixed effects. Statistical analyses of the cross-sectional and longitudinal results were carried out in the language R version 4.2.1 (https://www.r-project.org). The R packages most notable for the analyses have been coin, corrplot, factoextra, ggplot2, ggpubr, ggseg, lme4, lmerTest and rstatix. | [
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38863019 | intro | Background Alzheimer’s disease (AD) is characterized by amyloid-beta (Aβ) and tau deposition. Neuronal injury, neuroinflammation and vascular disease also play a crucial role in the pathogenesis of AD. Cerebral small vessel disease (CSVD) is characterized by extensive white matter hyperintensities (WMH). Pathological studies have demonstrated that dementia with AD-type is more frequently associated with concurrent CSVD loads compared to other neurodegenerative illnesses. The advancement of Aβ and tau positron emission tomography (PET) also enabled us to detect AD imaging markers in patients with CSVD lesions. In fact, AD combined with CSVD is reported to be the most prevalent mixed pathology. Out of the total number of individuals with dementia, 38.0% (19 out of 50) have both AD and infarcts, 30.0% (15 out of 50) have only pure AD, and 12% (6 out of 50) have vascular dementia. Epidemiological studies have shown that hypertension is associated with increased risk for dementia. Increased mean blood pressure (BP) promotes white matter alterations, resulting in the development of WMH. It is also associated with an increased rate of brain atrophy with or without the mediation of WMH. Furthermore, several studies suggest that the presence of hypertension may enhance the deposition of Aβ and tau in the brain. More recently, BP variability (BPV) has been related to an increased risk of dementia, which highlights the importance of understanding the role of various BP parameters in the development of dementia. Notably, there has been a growing focus on BPV over months to years (e.g., visit-to-visit BPV), as a modifiable risk factor for cerebrovascular illness and cognitive decline, independent of average BP levels. However, the associations between specific BP parameters and markers of AD and vascular disease have not been extensively established yet. Specific BP parameters might have various associations with markers of AD and vascular disease, eventually contributing to the development of dementia. In addition, recent study has shown that managing patients at increased risk for cardiovascular events, intensive treatment to reduce BP was linked to decreased rates of fatal and nonfatal cardiovascular events, as well as overall mortality, compared to standard treatment. Thus, in the treatment of hypertension, it is necessary to target specific BP parameters to prevent the development of dementia. Furthermore, a better understanding of pathways from specific BP parameters to cognitive impairment might enable us to select the specific medications targeting the specific BP parameters to prevent dementia effectively. Thus, in the present study, we investigated the effects of specific BP parameters on AD and vascular disease markers in individuals without dementia. Furthermore, we determined whether these AD and vascular disease markers might mediate the relationship between specific BP parameters and cognitive impairment. We hypothesized that each BP parameter would affect Aβ, tau uptake, hippocampal atrophy and development of WMH differently, which in turn leads to cognitive impairment. | [
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33519418 | abstract | Background: Mild cognitive impairment (MCI) is an early stage of Alzheimer's disease. Repetitive transcranial magnetic stimulation (rTMS) has been widely employed in MCI research. However, there is no reliable systematic evidence regarding the effects of rTMS on MCI. The aim of this review was to evaluate the efficacy and safety of rTMS in the treatment of MCI. Methods: A comprehensive literature search of nine electronic databases was performed to identify articles published in English or Chinese before June 20, 2019. The identified articles were screened, data were extracted, and the methodological quality of the included trials was assessed. The meta-analysis was performed using the RevMan 5.3 software. We used the GRADE approach to rate the quality of the evidence. Results: Nine studies comprising 369 patients were included. The meta-analysis showed that rTMS may significantly improve global cognitive function (standardized mean difference [SMD] 2.09, 95% confidence interval [CI] 0.94 to 3.24, p = 0.0004, seven studies, n = 296; low-quality evidence) and memory (SMD 0.44, 95% CI 0.16 to 0.72, p = 0.002, six studies, n = 204; moderate-quality evidence). However, there was no significant improvement in executive function and attention (p > 0.05). Subgroup analyses revealed the following: (1) rTMS targeting the left hemisphere significantly enhanced global cognitive function, while rTMS targeting the bilateral hemispheres significantly enhanced global cognitive function and memory; (2) high-frequency rTMS significantly enhanced global cognitive function and memory; and (3) a high number of treatments ≥20 times could improve global cognitive function and memory. There was no significant difference in dropout rate (p > 0.05) between the rTMS and control groups. However, patients who received rTMS had a higher rate of mild adverse effects (risk ratio 2.03, 95% CI 1.16 to 3.52, p = 0.01, seven studies, n = 317; moderate-quality evidence). Conclusions: rTMS appears to improve global cognitive function and memory in patients with MCI and may have good acceptability and mild adverse effects. Nevertheless, these results should be interpreted cautiously due to the relatively small number of trials, particularly for low-frequency rTMS. | [
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38865281 | results | RESULTS Baseline demographics were compared between patients with and without DM before and after PSM. After PSM, balance between the two groups was achieved for all variables (Table 1). Regarding the conversion from MCI to AD, Kaplan–Meier survival curves did not show statistical significance (P = 0.28) between patients with and without DM (Figure 2). However, there was a trend suggesting an accelerated conversion from MCI to AD within 12 months after MCI diagnosis in patients with DM. MCI patients with DM had a higher proportion of AD at the 12‐month follow‐up compared to those without DM (8.82% vs. 2.45%, P = 0.026). By applying IPTW, we created a pseudo‐sample consisting of 973 patients in the DM group and 980 patients in the non‐DM group. Kaplan–Meier survival curves did not show statistical significance (P = 0.750) between patients with and without DM (Figure S1 in supporting information). However, MCI patients with DM had a higher proportion of progression to AD at the 12‐month follow‐up compared to those without DM (8.32% vs. 5.31%, P = 0.008). As shown in Table 2, compared to patients without DM, those with DM exhibited worse cognitive function, as indicated by assessments such as MoCA at baseline, and EcogSPOrgan, FAQ, MoCA at the 12‐month follow‐up (all P < 0.05). Patients with DM experienced significant decreases in cognitive levels from the perspective of absolute differences (ADASQ4, EcogPtPlan, and RAVLT‐immediate) and relative difference (RAVLT‐immediate; P < 0.05). Morphological analysis of subcortical nuclei revealed that, compared to those without DM at baseline, patients with DM presented a notable inward concave surface and mild atrophy in the left nucleus accumbens (FDR corrected, P < 0.05; Figure 3A). During the 12‐month follow‐up, the left nucleus accumbens in patients with DM continued to display a significant inward concave surface, indicating sustained atrophy (Figure 3B). In addition, the right nucleus accumbens in patients with DM at 12‐month follow‐up also displayed a significant inward concave surface, signifying atrophy (FDR corrected, P < 0.05; , Figure 3C). VBM analysis for gray matter volume revealed the significant differences in time and group effects (both FDR corrected, P < 0.05, Figure 4). However, there was no significant difference in interaction (group × time) effect (uncorrected P < 0.001). Patients with DM showed a significant decrease in sulcal depth compared to those without DM during the 12‐month follow‐up (FDR corrected, P < 0.05; Figure 5A). Meanwhile, there were significant differences regarding sulcal depth (Figure 5A), gyrification index (Figure 5B), and cortical thickness (Figure 5C) in time effect during the 12‐month follow‐up (FDR corrected, all P < 0.05). As shown in Figure 6, a significant negative correlation was observed between the changes in EcogSPOrgan score and left cluster of sulcal depth (r = −0.35, P = 0.029; r = −0.35, P = 0.025; r = −0.35, P = 0.026; r = −0.38, P = 0.016) as for the patients with DM. A similar correlation was also observed between the changes in FAQ score and Cluster3 of gray matter volume (r = −0.31, P = 0.025; r = −0.34, P = 0.014; r = −0.36, P = 0.010; r = −0.33, P = 0.018). Regarding the patients without DM, the absolute differences in left cluster of sulcal depth was negatively correlated with the absolute (r = −0.21, P = 0.040) and relative (r = −0.23, P = 0.026) changes in EcogSPOrgan score. In addition, the absolute differences in FAQ score were negatively correlated with the absolute (r = −0.20, P = 0.047) and relative (r = −0.20, P = 0.043) changes in left cluster of sulcal depth. | [
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38780713 | title | The impact of the Mediterranean diet on immune function in older adults | []
|
37071459 | methods | Methods Review Methodology This scoping review of systematic reviews was guided by the methodological framework of the Joanna Briggs Institute. The study selection followed the PRISMA (Preferred Reporting Items for Systematic Review and Meta-Analyses) flow diagram, and the reporting and mapping of the body of literature followed the PRISMA-ScR (Preferred Reporting Items for Systematic Review and Meta-Analyses extension for Scoping Reviews) guidelines. The review protocol was registered in the Open Science Framework. Selection of the Reviews The eligibility criteria were established a priori. We included different types of systematic reviews (eg, rapid reviews, narrative reviews, integrative reviews, systematic literature reviews, and systematic reviews with meta-analysis) that analyzed telehealth interventions involving older users or subgroup analysis of older users with or without known health conditions, including those residing in hospitals, nursing homes, and their homes. The intervention could be any form or subgroup analysis of telehealth intervention involving direct communication between older adults and health care providers. No restrictions were placed on the date and location of publications for this review. Only full-text reviews in English were included, considering the language proficiency of the reviewers, to ensure the quality of study selection and data extraction. The systematic reviews were excluded if (1) the population did not consist of older adults or the reviews did not perform a subgroup analysis of older adults; (2) the reviews solely focused on the design or algorithm of telehealth interventions, policies, or experts’ opinions; (3) the reviews included a broader range of digital health or eHealth interventions but did not present a subgroup analysis of telehealth interventions; (4) the language was not in English; or (5) full texts were not accessible. Search for Relevant Studies Source of Studies In total, 5 electronic databases were searched to ensure comprehensiveness: PubMed, Embase (Ovid), Cochrane Library, CINAHL, and PsycINFO (EBSCO). Reference lists of the included systematic reviews were manually searched to identify potentially relevant reviews. Haddaway et al recommended Google Scholar search to identify gray literature in evidence reviews; however, Google Scholar is an “academic version of Google” and only consists of a “scholarly” subset of the larger Google search index. Therefore, we decided to use Google to identify any new relevant reviews, to ensure the completeness of the search. As Google’s search algorithm considers multiple factors and signals, we followed the procedure by Piasecki et al and logged out of all Google accounts during the search to avoid personalized search results. Although we were unable to locate any more relevant results on the fifth and sixth pages, we continued browsing and stopped on the 10th page to ensure that there were no further relevant results. Search Strategy The search strategy for this scoping review used a 3-step search strategy. In the initial step, a limited search was undertaken in Embase (Ovid) for relevant systematic reviews, followed by an analysis of the index terms used to describe the articles and the text words contained in the title and abstract of retrieved papers. This step helped us identify two concepts for the search strategy: (1) aging and (2) telehealth. These two concepts and the choice of databases were discussed and agreed upon in consultation with an experienced librarian (YLM) and all team members. In the second step, all identified keywords and index terms were used to develop our final search strategy, which had been consulted with the librarian (YLM) and compared with the published literature to ensure comprehensiveness. As a result of the preliminary search, some of the possible relevant systematic reviews identified did not include the term “review” in their titles or abstracts; therefore, adding the third concept “review” might result in such reviews being excluded. The detailed search strategy and results across all the included databases are provided in Multimedia Appendix 1. Finally, the reference lists of all identified systematic reviews in the included full texts were searched for additional articles. Selection of Studies The study selection consisted of two levels of screenings: (1) title and abstract screening and (2) full-text screening, and the reasons for all excluded full texts were recorded. In the first level of screening, 2 independent reviewers (YZ and JSPL) first screened the titles and abstracts of a random sample of 10% (620/6198) of the retrieved articles to ensure consistency in the interpretation of the inclusion and exclusion criteria, while discussions were conducted to reach a consensus in case of any discrepancies. Subsequently, they independently screened the remaining articles, and any study with unclear eligibility was conservatively included in the next step of the full-text screening. Only accessible full-text reviews were considered, and all attempts were made to access full-text copies of the selected articles, with the help of the librarian (YLM) or by directly contacting the author via email. In the second step, 2 reviewers (YZ and JSPL) independently assessed the full-text articles of all selected reviews. When discrepancies in the assessment were encountered, reviewers discussed among themselves, or with a third reviewer (WPT) acting as a mediator, to achieve consensus. Data Charting YZ extracted the characteristics of the included systematic reviews using a data charting form, which included the following items: article title, country of the authors, publication year, type of review (with a reason for not conducting a meta-analysis, if applicable), review aim, number of articles included, conceptual and operational definitions of the terms related to telehealth, inclusion and exclusion criteria, outcomes with main findings, quality of evidence, limitation of the reviews, and future practice and research recommendations. Data were manually copied and pasted wherever possible to avoid any potential misinterpretation. | [
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37122378 | methods | Method and materials Study design and subjects From May 2021 to August 2022, 139 patients with PD were recruited from Beijing Tiantan Hospital, Capital Medical University. All PD patients met the International Parkinson and Movement Disorder Society Clinical Diagnostic Criteria. The severity of cognitive impairment was assessed by the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA). The motor function of participants was assessed by using the Movement Disorder Society Sponsored-Unified Parkinson’s Disease Rating Scale and Hoehn and Yahr stage. Among the 139 PD patients, 73 cases meet the PDD criteria according to the 5th edition of diagnostic and statistical manual of mental disorders (DSM-5), which is mainly used as the dementia criteria at the time of cohort initiation. 50 healthy controls were also included. 20 PD returned for clinical and cognitive examinations after a median interval of 14 (Q1–Q3 8.75–16) months since the first visit. The plasma was collected at both baseline and follow-up visits. Exclusion criteria includes: (1) Cognitive dysfunction caused by Alzheimer’s disease, frontotemporal dementia, and other causes; (2) Secondary Parkinson’s syndrome caused by trauma, tumor, cerebral apoplexy, etc. (3) PDD generated by taking anticholinergic drugs. (4) Combining with mental illness and unable to complete the cognitive scale. The study was approved by the Ethics Committee of Beijing Tiantan Hospital, Capital Medical University, and was conducted according to the Declaration of Helsinki. Informed consent were obtained from all participants. Plasma sampling and processing K2-EDTA Vacutainers (367,863, BD, Franklin Lakes, NJ, United States) were used to collect fresh blood. All samples were collected from PD patients or healthy individuals in the morning. The blood samples were thoroughly mixed by being turned upside down three to four times before centrifugation. Plasma was separated from whole blood by centrifugation at 1500 g and 4°C for 10 min, and was transferred to a new tube for a second centrifugation at 12000g for 10 min at 4°C in order to eliminate potential cell debris. Then, the supernatant was transferred to another polypropylene tube and preserved at −80°C before analysis. The reference plasma was equally pooled with plasma samples from 34 PD subjects. Extracellular vesicles-depleted plasma was generated with an extra ultracentrifugation at 150,000 g and 4°C for 1.5 h. Only the top layer supernatant was collected. Western blotting Five μl plasma was mixed with 15 μl RIPA (C1053+, APPLYGEN, Beijing, China) lysis buffer on ice for 10 min. Lysates were spun down (12,000 g, 10 min, 4°C). The total protein concentration was determined using Bicinchoninic Acid Assay (23,225, Life Technologies, Eugene, United States). Plasma-extracted proteins (30 μg) were separated by using 10% ExpressPlus™ PAGE Gel (M01010C, Genscript, Nanjing, China) and transferred to polyvinylidene fluoride (PVDF) blotting membranes (IPVH00010, EMD Millipore Corporation, Billerica, United States). The PVDF membranes were blocked with 5% non-fat milk and incubated with the following antibodies: polyclonal anti-Alix (SAB5700777, EMD Millipore Corporation, Billerica, United States, 1:1000) and monoclonal anti-β-actin (ab8226, Abcam, Cambridge, United Kingdom, 1:1000) overnight at 4°C. The immunoreactive bands were visualized by a chemiluminescence kit (WBKLS0500, EMD Millipore Corporation, Billerica, United States) and Bio-Rad Chemidoc XRS+ Imager. Purification of CD62P-positive EVs in plasma CD62P-positive EVs were immunoprecipitated by anti-CD62P (sc-19,672, Santa Cruz Biotechnology, Dallas, United States) and protein A/G agarose beads (sc-2003, Santa Cruz Biotechnology, Dallas, United States). Briefly, total plasma EVs were isolated using an ExoQuick PLUS Exosome Purification Kit (EQPL10A-1, SBI System Biosciences, Palo Alto, United States) according to the manufacturer’s instructions. Next, 2 μg anti-CD62P antibody was mixed with the resuspended EV pellet for overnight at 4°C with continuous rotation. Then, the protein A/G agarose beads were added to the antibody-protein complex and incubated at 4°C for 3 h. Finally, the EVs were eluted from the beads by using 70 μl 0.1 M glycine (pH = 3) buffer, which was balanced with 5 μl 1 M Tris buffer (pH = 7). The samples were preserved at −80°C before loading to copper grids for transmission electron microscopy imaging. Transmission electron microscopy Five μl CD62P-positive EVs were loaded on the 200-mesh copper grids and stained with filtered 1% uranium acetate for 2 min. Contact the grid edge with absorbent paper to remove any excess uranium acetate solution. Rinse the grid quickly with a drop of water for another 2 min. Let the grid dry for 5 min at room temperature. Then, place the grid in the grid box for transmission electron microscopy inspection at 80 kv using a Hitachi H-7650 platform. Extracellular vesicles analysis with CytoFLEX flow cytometry Fluorophore-conjugated antibodies were prepared using Zenon IgG labeling kits from Invitrogen/Life Technologies. In particular, the Zenon™ Alexa Fluor 488 mouse IgG1 labeling kit (Z25002, Life Technologies, Eugene, United States) was used to label the monoclonal antibody (sc-19,672, Santa Cruz Biotechnology, Dallas, United States) against CD62P. Rabbit anti-β-amyloid 1–42 polyclonal antibody (AB5078P, EMD Millipore Corporation, Billerica, United States) was labeled using the Zenon™ Alexa Fluor 647 rabbit IgG labeling kit (Z25308, Life Technologies, Eugene, United States). Briefly, 5 μl component A from the labeling kit was mixed with 1 μg antibody for 30 min at room temperature. Afterward, 5 μl Component B was added to the mixture for another 15 min incubation in a light-protected environment. Five μl of plasma from each subject was incubated with 0.1 μg of fluorophore-conjugated antibody for each target for 30 min at room temperature. After the reaction, the mixtures were 1:60 diluted with 0.22 μm filtered PBS before loading to the high-sensitive flow cytometer, CytoFLEX S (Beckman Coulter, Milano, Italy). A Violet Side Scatter Hight (VSSC-H) detection mode was selected for the detection of small vesicles ranging under 500 nm. A low flow rate at 10 μl/min was used to acquire the fluorescence-labeled EVs from each sample. The gates were set up according to the IgG isotype control and the blank control. An ApogeeMix beads kit (cat # 1493, Apogee, Parkville, Australia) containing fluorescent polystyrene (PS) beads with wavelengths of 110 nm and 500 nm was used as a standard marker. CD62P single-positive events and CD62P/Aβ1-42 dual-positive events were counted for further analysis. The ratio of ADPEV-Aβ1-42 to ADPEV is calculated using the concentration of CD62P and Aβ1-42 dual positive EV to CD62P positive EV. Statistical analysis All statistical analyses were performed using R software (version 4.0.4) and Prism (version 8.0). The normality was determined by the Kolmogorov–Smirnov test. When the variables followed a Gaussian distribution, the two-tailed t-test was used to compare the data, and multiple comparisons were made using analysis of variance (ANOVA). The Mann–Whitney test was used to compare data for variables that did not follow a normal distribution, and the Kruskal-Wallis test was employed when there were more than two groups. To compare dichotomous variables between groups, the χ2 test was utilized. Multifactorial logistic regression analyses were performed to estimate demographic characteristics, clinical features and the ratio associated with the incidence of dementia in PD patients. The Spearman rank correlation test was employed to investigate the relationships between demographic characteristics, clinical features and the ratio. Significant was defined as p < 0.05. | [
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39116421 | title | A Review of the Role of Estrogens in Olfaction, Sleep and Glymphatic Functionality in Relation to Sex Disparity in Alzheimer’s Disease | []
|
34307303 | title | Co-Immobilized Capillary Enzyme Reactor Based on Beta-Secretase1 and Acetylcholinesterase: A Model for Dual-Ligand Screening. | [
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39238777 | intro | Introduction The aging population has been increasing globally at an unprecedented rate. A recent report from the World Health Organization projected that one in six people worldwide will be aged 60 years or older by 2030. Among the significant concerns associated with aging are the risks of neurodegenerative conditions, such as dementia or mild cognitive impairment, which have posed substantial socioeconomic burdens on family caregivers and governments. Early detection of cognitive-linguistic changes associated with aging could be used as a guide for normal aging and clinical populations in the prevention and treatment of neurodegenerative conditions. Recent research has aimed to capture subtle alterations in the cognitive-linguistic abilities of older adults through language production tasks. Some studies sought to demonstrate that early symptoms can be discerned by analyzing connected speech samples obtained from tasks such as picture descriptions, interviews, or storytelling tasks (cf.). Connected speech refers to spontaneously spoken discourse with minimal speaker monitoring, representing the most systematic form of language production. Connected speech production imposes various cognitive and linguistic demands on the speakers, including processing speed, working memory, attention, semantic storage and retrieval, syntactic formulation, and alignment with a communication goal or topic to create a coherent discourse (cf.). Given its complexity and cognitive demands, examining connected speech production may serve as a valuable method to detect age-related changes in cognitive-linguistic domains among aging populations. Moreover, it offers an opportunity to identify changes in language production that are more akin to real-life communications than to the language elicited by the tasks of single-word naming or verbal fluency. The primary objective of this study is to explore the linguistic and cognitive attributes associated with connected speech production, aiming to discern age-related change among young-old adults (typically defined as individuals in late middle age to early old age). Existing evidence from language production studies suggests that the aging process manifests from late midlife to young-old age. reported that the young-old group (aged 58–74 years) exhibited a higher proportion of word-finding errors compared to younger adults (aged 18–22 years). Also, reported slowed processing in word retrieval from the age of 50. While individuals in their 50s and younger adults (aged 25–35) exhibited no difference in naming accuracy, those in their 50s showed significantly longer naming latencies. A longitudinal study by documented a gradual decline in word retrieval abilities over time among participants aged 30 to 87, indicating that the participants in the late midlife and young-old age were experiencing a decline in naming abilities. The extent to which aging affects connected speech production, particularly in terms of word retrieval, has been a matter of debate. The variability in research findings is partly attributed to two factors: the diverse tasks and various linguistic outcome measures employed in previous studies. To begin with, the task paradigms have ranged from picture description to story narration and to conversations or interviews. Older adults tended to produce more words and retrieve a greater variety of words in spontaneous conversations or interviews. In contrast, older adults were less talkative and showed a more restricted selection of words in structured tasks such as picture descriptions. One of the most frequently employed methods to elicit connected speech samples is the picture description task. In the task, participants are presented with a picture depicting characters engaged in familiar activities and instructed to describe it. It creates a constrained environment for identifying intended words and assessing the success of word retrieval, enabling easy cross-group comparisons. Picture descriptions are widely adopted and proven to be invaluable across diverse populations, ranging from healthy older adults to individuals with neurodegenerative diseases and aphasia. Moreover, the task enables researchers to examine real-time measures of eye movements as the speakers are looking at the picture while performing the task. Eye movements have been suggested to provide valuable insights into the cognitive processes underlying language production. Notably, prolonged and frequent eye fixations are indicative of heightened cognitive processing demands. In adopting picture description tasks, studies have used various types of pictures, including single pictures, sequential pictures, or story pictures (cf.). Recently, researchers have emphasized cultural and linguistic factors in the pictures that may significantly influence speakers’ interpretation and description of them. Some studies attempted to enhance linguistic and cultural sensitivity in pictures. The ‘Cookie Theft’ picture from the Boston Diagnostic Aphasia Examination (BDAE), which was standardized and is the most commonly used picture stimuli in the field of communication disorders, has been critiqued for containing gender, racial, and socioeconomic stereotypes. Thus, there have been attempts to address these limitations by modifying the background scene and characters and adding more objects and actions to it. Additionally, some studies have examined the influence of ethnicity on descriptions of the Cookie Theft picture by comparing the connected speech of Black/African Americans and non-Hispanic whites. Another study compared Turkish speakers’ descriptions of the Cookie Theft picture to a picture tailored for Turkish speakers and found the tailored one elicited more distinctive morphosyntactic features unique to the Turkish language. These studies demonstrate the importance of using pictures that resonated with participants’ linguistic, cultural, and social backgrounds to effectively capture linguistic characteristics and semantic knowledge in connected speech samples. Therefore, picture stimuli tailored for a specific language would produce a more accurate assessment of the cultural and linguistic differences of diverse populations. In South Korea, the Beach picture from the Paradise-Korean version of the Western Aphasia Battery-Revised (PK-WAB-R) has been the standardized picture most commonly used in picture description tasks, both in research and clinical settings. It has also been extensively utilized in various populations including healthy young and older adults, individuals with dementia, and those with aphasia, to name a few. However, the Beach picture exhibits certain inherent linguistic and cultural issues. The objects and actions depicted in the picture may be less familiar to Korean speakers. This is because the Beach picture was adopted from the Western Aphasia Battery, with its fundamental scenery remaining unchanged. Furthermore, the picture portrays limited events that may not sufficiently elicit action-related information or specific lexical items, such as verbs. The presence of only six active agents (see ‘Materials and methods’ section for further detailed descriptions), contributes to this limitation. This presents a crucial concern given that Korean is characterized as a pro-drop and verb-salient language, which allows the omission of verb arguments (e.g., subject or object, which are nouns) from a sentence when their identity can be inferred from context. This verb saliency in Korean has been observed in previous studies on connected speech, where Korean speakers with aphasia demonstrated a greater number of verbs compared to that of English speakers with aphasia for the same picture description tasks. With the limitations of the Beach picture in consideration, Sung and colleagues introduced a new picture called the ‘Han River’ picture (Patent no. D2022-0004KR), which was specifically designed for Korean speakers. They took the verb saliency of the Korean language as a key variable and included diverse action drawings in the picture scene in order to elicit more verbs (e.g., daily activities seen on the river banks). Furthermore, cultural familiarity was enhanced by depicting the background scene as the Han River and including daily activities happening there. The Han River holds a symbolic significance in Korean cultural identity as the river passes through the center of Seoul. It has served as a social and economic hub for residents and visitors alike and represents a familiar space intertwined with the daily lives, aspirations, and emotions of Korean people. Along the river bank parks, people gather to exercise, have picnics, and take leisurely walks while enjoying the scenic river. One of the objectives of this study was to investigate how different picture types influence age-related differences in the task of describing picture scenes. We are particularly interested in whether the Han River picture would evoke a greater number of information units and action-related words, particularly verbs for Korean speakers. In Korean, verbs are hypothesized to impose a greater cognitive load due to their complex grammatical structure. Korean sentences follow an “SOV” (Subject-Object-Verb) structure, where verbs typically appear at the end of the sentence. Thus, activation of semantic and syntactic elements preceding the verb would be necessary before its production. Previous studies with the tasks of single-word production have already shown the age-related difficulties in producing heavy verbs compared to light verbs in generative naming tasks, as well as challenges in generating verbs compared to nouns in verbal fluency tasks. However, to our knowledge, no studies have specifically investigated age-related changes in eliciting verbs within the context of connected speech. By utilizing the Han River picture, which was designed to draw out many verbs, our study aimed to investigate age-related changes in verb production abilities in connected speech. Turning to the second factor, outcome measures in previous studies have also shown considerable variation. Thus far, the examination of outcome measures in language studies involved two analyses: (1) linguistic variable analysis and (2) real-time variable analysis. First, different linguistic variables have been used in connected speech analysis, which includes productivity (e.g., the number of words produced) and communication efficiency (e.g., correct words per unit of time). These measures have yielded mixed results, reporting both age-related declines and no significant changes. Some studies have reported significant age-related decreases in the number of produced words, while others have found no change with age. Additionally, some studies have found fewer propositions relative to the total number of words produced, while others have reported no decline in measures such as the number of propositions per minute, the number of words needed to convey an information unit, or the number of Correct Information Units per minute. Among those linguistic measures, Correct Information Units (CIUs) serve as one of the most frequently used linguistic measures for capturing semantic deficits across languages. Originally developed by, CIUs represent words that are both (1) intelligible in context and (2) accurate, relevant, and informative about the picture or topic of connected speech. To count CIUs, intelligible words are first collected, excluding unintelligible words or non-word fillers. From those intelligible words, CIUs are determined according to the specific criteria; importantly, they do not have to be used in a grammatically correct manner, but words that incorrectly describe the picture or attempts to correct sound errors are excluded (see, for further details). The current study investigated age-related differences in word retrieval ability in the context of connected speech production by utilizing CIUs per minute and counting the number of nouns and verbs produced. These single-word measures were employed since word retrieval was the domain of interest. The CIUs per minute represented informativeness, and the number of nouns and verbs showed productivity in connected speech samples. Nouns and verbs were chosen as dependent measures because they constitute the core lexicon in Korean, making them representative indicators of lexico-semantic retrieval abilities and core words in constructing sentences. Secondly, real-time measures, such as eye movements, have been employed in language production tasks. Eye-tracking can provide a direct measure of visual attention and cognitive effort during picture description tasks, which is an aspect not fully captured by analyses of spoken data after task completion. Given the complex interplay between cognitive and linguistic processes in picture description tasks, the cognitive-linguistic challenges faced by older adults may result in distinct eye movement patterns compared to the ones from younger adults. During these tasks, speakers must visually process a scene, identify key elements, retrieve and organize words, and make inferences about relationships among the depicted elements. Age-related changes in cognitive processes, such as declines in working memory capacity and attentional control, may affect the process of generating verbal descriptions. For instance, decreased working memory resources may hinder the maintenance of active lexical representations for production and the tracking of information already produced in preceding utterances. Researchers have temporally synchronized language and eye movement data to investigate cognitive processing during a specific period of time. Eye movements have been scrutinized during the planning stage of language production when speakers were to comprehend events, assign roles to subjects, and possibly select verbs. While speakers selected words and assembled phonemes to name specific objects, eyes often fixated on them. Many studies consistently reported a close temporal relationship between eye movements and language production. The time interval between initiating eye gaze on an object and uttering its name typically remains consistent across studies, which lasts approximately a second. Even if speakers had previously fixated on an object, they often redirect their gaze back to it for about a second before naming it. Additionally, the duration of gaze on an object before its naming reflects one’s cognitive efforts that are required to name it. For example, individuals tend to spend more time observing objects before verbally describing them rather than simply scanning them to form a general impression. These findings collectively suggested a deliberate cognitive effort for language production, reflected in looking time. Most studies have employed an eye-tracking paradigm to study the production of simple phrases. Albeit few, some studies have examined eye movements during sentence- or connected speech-level production. investigated the description of a simple array of objects into simple sentences following a fixed format (“The A and the B are above the C”) for the older and younger adults. Their findings revealed that older adults exhibited longer fixation durations on the picture before initiating the first object (“the A”) compared to those for younger adults. This suggested that older adults required more time to prepare and retrieve the name of the first noun before initiating the sentence. examined connected speech and eye movements during the description of the ‘Cookie Theft’ picture. With the goal of classifying individuals with Alzheimer’s disease, mild cognitive impairment, and subjective memory complaints from healthy controls, they analyzed a linguistic variable (e.g., information units) and eye movement measures (e.g., eye fixations). Findings from machine learning experiments showed that the combination of eye movement and language features yielded the most accurate classification performance, highlighting the effectiveness of eye-tracking data in assessing language production skills. Additionally, investigated connected speech in the description of complex, realistic scenes, with a focus on the temporal relationship between eye fixations and verbal descriptions. During the message planning stage, eye fixations tended to shift to the next region to be described, indicating the preparation stage for language production. Drawing upon these findings, which suggested that eye movements indicate cognitive processing and reveal patterns of pre-fixation while planning language production, the current study aimed to investigate age-related changes in the planning process of connected speech by analyzing eye fixations. Specifically, we focused on pre-speech fixations, those fixations that occur during the planning stage of the utterance. Our approach is guided by the hypothesis that the planning and retrieval of words or information units influence speech onset and timing, drawing from previous research findings. Building upon the established temporal correlation between eye movements and verbal descriptions of scenes, where fixations on objects typically precede their corresponding naming, we seek to explore whether older speakers engage in an increased pre-speech preparation which would be reflected in their eye movements during the picture description tasks. This study aimed to examine differences in connected speech production between older and younger adults, focusing on linguistic (informativeness and productivity) and real-time (eye fixation) measures, using two picture types. Participants were presented with a standardized Beach picture and a culturally adapted Han River picture, from which connected speech samples were obtained while eye movements were recorded. The study addressed two primary questions. Firstly, we anticipated that older adults would demonstrate decreased word retrieval abilities in terms of informativeness (CIUs per minute) and productivity (noun and verb count per utterance). We expected the Han River picture to elicit greater differences between the two age groups due to its cultural and linguistic modifications, which include a more diverse array of familiar actions and objects occurring in the culturally symbolic background of the Han River. Secondly, we hypothesized that older adults would exhibit decreased processing efficiency in connected speech production, as evidenced by increased pre-speech fixation count and duration. Additionally, we anticipated that the Han River picture would evoke larger group differences, as it would require more cognitive effort to process due to the greater number of elements to describe compared to the Beach picture. The research questions are as follows. Are there age-related differences in linguistic measures (CIUs per minute, noun and verb count per utterance) depending on the picture types (traditional vs. modified picture)? Are there age-related differences in real-time eye movement measures (pre-speech fixation count, duration) depending on the picture types (traditional vs. modified picture)? | [
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38743119 | title | The Role of Beta2-Microglobulin in Central Nervous System Disease | [
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12,
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33418848 | title | Tau Oligomers Neurotoxicity. | [
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37143686 | methods | Methods Study design and participants This case control cross sectional study was part of another study that primarily aimed at determining the impacts of schistosomiasis on the early childhood development that was conducted in Murewa, Zimbabwe. The main objective of the study was to determine the role of systemic inflammation on cognitive performance by investigating the following two objectives; i) Determining if there were any correlations between inflammatory biomarker levels and cognitive functioning and, ii) Determining which possible explanatory factors could be driving cognitive function in PSAC with significant correlations between inflammatory biomarker levels and cognitive function. PSAC from Zimbabwe (Magaya village in Murewa district) were screened for schistosomiasis. This area has a high prevalence of S. haematobium (> 50%). Thirty PSAC were diagnosed with S. haematobium infection through urine filtration and 106 non-infected PSAC from non-permanent residents of Magaya village were selected as controls. Inclusion and exclusion criteria. PSAC who were eligible for recruitment into the study met the following inclusion criteria; (i) were lifelong occupants of the study area (Murewa, Zimbabwe) (ii) had never received anthelminthic medication (iii) were aged less than 72 months (iv) provided 3 urine samples for the diagnosis of S. haematobium and stool samples for soil transmitted helminths and S. mansoni diagnosis (v) written consent obtained from parent to participate in the study. Children were excluded in the study if; (i) They had mental or physical disabilities such as attention-deficit disorder which predisposes them to attaining low cognitive scores, (ii) had a positive diagnosis of soil transmitted helminths and/or S. mansoni. Sample size calculation was done using the assumption of 50% exposure in cases and 22% exposure in controls and an Odds Ratio of 3.5 to report a power of 80% and 95% confidence interval. Parasitological examination Parasitological screening for S. haematobium, soil transmitted helminths and S. mansoni eggs was conducted as described previously. Each PSAC provided at least 3 urine and stool samples over 3 cumulative days. Urine samples were used to microscopically screen for S. haematobium eggs using the urine filtration method whilst S. mansoni and soil transmitted helminths were screened from the stool samples using the Kato-Katz method. Nutritional status Nutritional status was scored using the WHO child growth standards from the WHO Anthro software, version 3.0.1(http://www.who.int/childgrowth/en/) as described in a previous study. Briefly, measurements of height, weight and the mid upper arm circumference (MUAC) were taken from PSAC using a stadiometer (Gima®), electronic scale (Gima®) and MUAC tape (AnthroFlex®) respectively. These measurements were used to obtain Z-scores and PSAC with BMI Z-scores < -2 were classified as having a low nutritional status. Analysis of cognitive performance Cognitive performance measures of early childhood development was determined using the Griffiths III psychometric tool which was administered by a psychologist on the same day that blood samples were collected. This tool measures 5 cognitive subscales whose average developmental quotient scores give the general development profile of a child (general quotient score). The 5 cognitive subscales that were assessed include; The Foundations of Learning, Language and Communication, Eye and Hand Coordination, Personal-Social-Emotional and Gross Motor function. The Foundations of learning subscale assesses learning during the early childhood period. The Language and Communication subscale is used to assess expressive and receptive language including the child’s ability to communicate. The Eye and Hand Coordination subscale measures the child’s small muscle coordination of eyes with hands. The Personal-Social-Emotional subscale is used to assess the child’s ability to manage emotions, peer relationships and how they articulate to tasks and the Gross Motor function which assesses a child’s development in the areas of physical skills development. Developmental Quotient (DQ) scores >88 was used to classify cognitive performance in PSAC as normal from each Griffith Mental Developmental subscale. Blood collection and the determination of inflammatory biomarker levels Blood samples (5ml) were collected from all the PSAC on the same day and prior to the administration of the cognitive assessment by a clinician. The serum samples were used for the determination of cytokines (IL-6, TNF-α, TGF-β, IL-10 and IL-17A) and CRP. CRP levels were measured using a commercial Duoset Enzyme-Linked Immunosorbent Assay (ELISA) kit (R & D Systems, Minneapolis, MN, USA) according to the protocol provided by the manufacturer. The cytokine levels of IL-6, TNF-α, TGF-β, IL-10 and IL-17A were measured using the ELISA according to the manufacturer’s (Mabtech Company, Stockholm, Sweden) protocol. Briefly, serum samples for each inflammatory biomarker were run in duplicates on the same microtiter plate. Standards of known concentration were used to determine the concentrations of the cytokines. The Dynatech Immulon® microtiter plates were coated overnight with the coating solution (capture monoclonal antibody mixed with phosphate-buffered saline (PBS)). The microtiter plates were washed and blocked with the Tris- buffered saline (TBS) and were incubated for 30 minutes. After another wash step, the serum samples that were diluted in the reagent diluent were micro pipetted into the microtiter plates and were incubated at 37°C for 2 hours. After washing the plates, the conjugated antibody was added. The microtiter plates were incubated for an hour after which the substrate o-phenylenediamine dihydrochloride (OPD) was added. The microtiter plates were incubated for 20 minutes in dark conditions. The optical densities were immediately measured at 450nm using a microplate reader (Micro read 1000). Hematological analysis and the determination of CRP levels The determination of total white blood cells (WBC), hemoglobin (HGB), lymphocyte (LYM), Mixed Cell Count (MXD) and neutrophil count was done using a hematology analyzer (MaxM; Coulter, Fullerton, CA) from whole blood samples that were in tubes containing ethylene diamine tetra acetic acid (EDTA). Statistical analyses The data obtained was checked for normality and analyzed using Stata Version 17.0 (StataCorp LLC, Texas, USA). Wilcoxon rank sum was used to determine the differences in cytokine concentration levels by cognitive status, by infection status and the differences in cognitive performance by infection status. The Spearman correlation was used to assess the relationship between the cytokine levels and cognitive performance in the cognitive subscales. Inflammatory biomarkers that were found to have significant correlations with cognitive performance were considered as predictors to cognitive function. PSAC who had higher levels of the significant inflammatory biomarkers than other PSAC were used for multivariate regression analysis. The multivariate regression analysis was done to determine the adjusted odds of S. haematobium infection having an association with cognitive performance after adjusting for possible explanatory variables (age, sex, hemoglobin concentrations and nutritional status) which were used as continuous variables. P-values < 0.05 were considered as significant. | [
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39356504 | methods | Methods This cohort study was approved by the University of New South Wales human research ethics committee. Each study had independent approval from its regional ethics board, and their participants provided informed consent. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline was used for reporting. Sample COSMIC member studies are population-based longitudinal studies of older individuals. We included 14 studies conducted from 1993 to 2019 meeting the following criteria: (1) conducted at least 2 follow-up neuropsychological assessments and (2) collected data on interval stroke. Follow-up durations range from 3 to 17 years across cohorts. Participants with a history of stroke or dementia at baseline (criteria provided in eTable 1 in Supplement 1) were excluded from the analyses. Table 1 and eTable 1 in Supplement 1 summarize each study. Stroke and Baseline Factors Stroke was self-reported in all studies except 2, where the information came from an inpatient register or via examination (eTable 2 in Supplement 1). Year and month of stroke was recorded or approximated by the midpoint between 2 assessments (eTable 2 in Supplement 1). Demographic and medical history data were harmonized as per previous COSMIC projects (see eTable 3 and eTable 4 in Supplement 1). Baseline factors considered were age; sex; education in years; race, ethnicity, or nationality (self-identified or investigator-observed by the investigators in each study); study entry period (by decade); apolipoprotein E ε4 allele (APOE4) carrier; blood pressure; body mass index, smoking (ever); alcohol use; physical activity; depression; diabetes; hypertension; high cholesterol; and cardiovascular disease (CVD). Race, ethnicity, and nationality were included in the analyses due to reported differences in stroke outcomes across racial groups. Table 2 lists the categories for each harmonized variable; eTable 3 and eTable 5 in Supplement 1 provide the criteria and levels of missing data. Cognitive Tests Based on previous COSMIC work, domain scores were calculated by selecting the most common test administered in each cognitive domain (memory, processing speed, language, and executive function). Domain and Mini-Mental State Examination (MMSE) scores were standardized using the demographic category-centered method based on the average person in the combined sample (age 73 years; male; education 10 years). See eTable 6 in Supplement 1 for the tests used in each domain from each study. Global cognition was the standardized mean of the z scores from at least 3 cognitive domains. Statistical Analysis Participants were categorized into stroke and no-stroke groups based on whether they experienced an interval stroke during follow-up. Baseline characteristics were compared between the groups using t test or χ2 tests, and the magnitude of differences assessed using Cohen d or Cohen h as appropriate. Regression discontinuity design with 2 sequential linear mixed-effects functions was used to model the cognitive trajectory poststroke relative to the trajectory over which participants were stroke-free. The basic model included time in study (TIS), time since stroke (TSS), and stroke (time-varying variable changing from 0 to 1 at time of stroke). The model coefficient for TIS quantifies the rate of decline (slope) for all individuals over the period without stroke. The TSS coefficient estimates the difference in slope poststroke relative to TIS and can be interpreted as the long-term outcome of stroke on the rate of cognitive decline. The stroke coefficient quantifies the difference in level of cognitive function between the stroke-free and poststroke trajectories at time of stroke (TSS = 0) and can be interpreted as the acute outcome of stroke on cognition level. Quadratic terms were included to examine nonlinear trends and retained if significant at P < .05. Random intercepts were included to accommodate correlation of cognitive measures within participants over time and between studies. The adjusted model additionally included age, sex, education, and baseline factors that were P < .10 when examined individually in the basic model. Missing covariates in the pooled sample were imputed using multiple imputation with chain equations (eMethods in Supplement 1). Global cognition was the primary outcome, and the 4 domain scores and MMSE were secondary outcomes. For 0.2% of participants with 2 incident strokes, we censored cognitive assessments after their second stroke. Trajectory plots were constructed using projected values of cognition calculated for the means of included covariates. The analysis was performed first in the whole sample, and then separately in the stroke and no-stroke groups. See eTable 7 in Supplement 1 for detailed interpretation of the model coefficients. Secondary Aims and Sensitivity Analyses Differences in cognitive trajectories between the groups were examined by including a group variable and its interaction with TIS in the adjusted model, with TIS restricted to before stroke. We examined factors associated with poststroke cognitive trajectory by including interaction terms of TIS, TSS, and stroke with demographic and vascular factors associated with risk separately in the adjusted model with global cognition as the outcome. Three sensitivity analyses were conducted for the key analysis: (1) including only participants with complete data; (2) excluding cognitive assessments within 1 year of an incident stroke, given instability in cognition up to 1 year poststroke; and (3) excluding studies with more than 50% loss to follow-up at the final wave. Analyses were performed with Stata version 18.0 (StataCorp) from July 2022 to March 2024. | [
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38941274 | title | TMEM16F exacerbates tau pathology and mediates phosphatidylserine exposure in phospho-tau-burdened neurons | [
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36963989 | results | Cardiovascular findings Although ME/CFS is not considered as a primary cardiovascular disorder, there are certainly indications of cardiovascular dysfunction in this disease population. ME/CFS individuals exhibit an increased risk for premature heart failure and earlier all-cause mortality, as do Long COVID suffers. The exact mechanistic path leading from ME/CFS to heart failure is not yet elucidated, but oxidative and nitrosative stress (O&NS) as well as dysregulated inflammatory function are thought to play a major role. Indeed, ME/CFS is accompanied by increases in O&NS and a reduced antioxidant capacity, as well as a proinflammatory phenotype. With that being said, it must be noted that the ME/CFS-induced lifestyle – one that is defined by reduced physical activity and disablement – is one that itself likely increases cardiovascular risk, and hence needs to be accounted for when interpreting data. Related to the association between ME/CFS and heart failure, ME/CFS patients exhibit increases in arterial wave reflection when compared to controls. Arterial wave reflection is inversely associated with left ventricular systolic function (as determined by tissue Doppler imaging techniques) and is involved in the pathogenesis of heart failure. Abnormalities in left ventricular function were described in an ME/CFS population in the early 1990s. In a study involving 56 ME/CFS participants who were subdivided into severe (n=30) and non-severe (n = 26) groups, the severe ME/CFS group presented with a 10.2% reduction in stroke volume and mild decreases in contractility in comparison to controls. Furthermore, both ME/CFS groups had reduced total blood volume, plasma volume, and red blood cell volume in relation to the control groups. The authors inferred that the lower cardiac volume observed in the ME/CFS cohorts is most likely a result of a hypovolemic comorbidity instead of a cardiac-contractile issue. In a comment article published the following year, it was emphasized that the aforementioned results do not point to classical cardiovascular disease, but rather highlight impairments in circulation and cardiovascular function. The ME/CFS-induced lifestyle – of which a consequence is physical deconditioning – was also mentioned as a reason for the observed results, as chronic physical inactivity is related to decreased stroke volume. Reduced stroke volume in ME/CFS has since been corroborated, and decreases in end-diastolic volume and cardiac output have also been reported. van Campen and Visser (2018) performed a tilt table test on 150 ME/CFS individuals who were subdivided into three groups based on disease severity – mild, moderate, and severe – and 37 controls. Suprasternal aortic Doppler imaging was used to measure stroke volume index (SVI) and cardiac index (CI), and determined that decreases in SVI and CI were significantly greater in the ME/CFS group than controls. Importantly, the researchers showed that these cardiac shortcomings were not statistically different between the mild, moderate, and severe ME/CFS groups. This suggests that deconditioning due to the ME/CFS-induced lifestyle does not account in significant part for the cardiovascular abnormalities observed in this disease population, and increases the plausibility of cardiac involvement in ME/CFS pathogenesis and symptom manifestation. To further investigate the role of deconditioning in ME/CFS symptomology, van Campen and colleagues assessed the relation between the extent of reduction in peak oxygen consumption during cardiopulmonary exercise testing and the degree of reduction in cerebral blood flow during head-up tilt tests in 199 ME/CFS and 22 control participants. Again, there were no differences observed between the ME/CFS groups (no, mild, or severe deconditioning), which implies that deconditioning does not govern orthostatic symptoms in ME/CFS. Other studies have reached the same inferences. With the evidence at hand, it seems that cardiac dysfunction present in ME/CFS is not a result of physical inactivity, and hence is not something that should be brushed off as a consequence of ME/CFS – it might be (intimately or modestly) involved in pathology. Using magnetic resonance imaging and cardiac tagging techniques, Hollingsworth and colleagues investigated the cardiac morphology of 12 ME/CFS and 10 control subjects and determined that left ventricular mass was significantly decreased in the ME/CFS group. This has since been corroborated. Contrastingly, the study by Hurwitz and colleagues found no significance in left ventricular mass; the same goes for a more recent study, where cardiac function was also deemed normal. A significant reduction (P < .001) in coenzyme Q10 (CoQ10) plasma levels has been observed in an ME/CFS cohort. CoQ10 is an essential component of the respiratory chain, and exerts anti-inflammatory and antioxidant effects. Reductions in CoQ10 are associated with cardiovascular pathology and reduced mitochondrial biogenesis, and supplementation offers cardio-protection. CoQ10 is also an independent risk predictor of mortality in chronic heart failure. Decreases in CoQ10 reduce antioxidant capacity and might account in part for the increases in O&NS observed in ME/CFS. Furthermore, CoQ10 might hold potential as a useful predictor of heart failure in ME/CFS patients. CoQ10 supplementation increases cellular resistance to lipid peroxidation, and may therefore prove useful against the lipid peroxidation observed in ME/CFS. Indeed, it has been shown that CoQ10 and selenium supplementation in ME/CFS subjects increased antioxidant capacity and decreased lipid peroxidation, cytokine levels, and symptom severity. ME/CFS is also accompanied by reduced plasma levels of omega-3 fatty acids, which is associated with chronic inflammation and also confers an increased cardiovascular risk. On that note, metabolic abnormalities are common findings amongst ME/CFS cohorts. Significantly increased levels of fibroblast growth factor 21 (FGF21) and the N-terminal prohormone of brain natriuretic peptide (NT-proBNP) have been revealed in an ME/CFS cohort. Positive correlations between NT-proBNP concentrations and that of proinflammatory cytokines (namely, IL-1β and IL-6) were noted. NT-proBNP is positively and independently associated with cardiovascular risk and FGF21 is involved in glucose and lipid metabolism. Supplementation of CoQ10 and selenium did not alter levels of these two proteins in ME/CFS subjects. Orthostatic intolerance One of the more consistent findings amongst ME/CFS populations is the presence of OI and POTS, which is not surprising considering the evidence of reduced venous return and cardiac function, and reduced ambulatory blood pressure. OI forms part of the ME/CFS diagnosis and significantly reduces one's functional capabilities and quality of life. On the upper end of the scale, some studies that have employed the 10 min stand-up test have reported prevalence figures for OI above 95% in ME/CFS cohorts. In another study, symptoms of light-headedness and dizziness were present in 72% (32/39) of standing and 41% (16/39) of recumbent patients; ME/CFS patients without POTS scored higher in orthostatic measures upon standing than those with POTS, suggesting that orthostatic tachycardia does not account for the symptoms of OI in ME/CFS. From a therapeutic perspective, compression stockings have shown benefit for orthostatic symptoms and cardiac measurements. Autonomic receptors, such as adrenergic and cholinergic G-protein-coupled receptors (GPCRs), relay sympathetic and parasympathetic signals involved in the regulation of blood vessels. Elevated levels of autoantibodies against adrenergic and cholinergic receptors have been found in ME/CFS individuals, and also correlate with autonomic dysfunction and symptom severity. Yamamoto et al (2012) demonstrated that these autoantibodies have an impact on the central muscarinic cholinergic receptor system as inferred by positron emission tomography, and may therefore interfere with cell signalling. Attenuated β2 adrenergic receptor activation has also been noticed. An explanation for ME/CFS pathology with a focus on the dysfunction of these autonomic receptors has been published. With that being said, it must be noted that herpes viruses, which are significantly implicated in ME/CFS pathology, produce GPCRs that share homology with human GPCRs. Hence, molecular mimicry between herpes and human GPCRs might underlie what is seen as ‘autoimmunity involving GPCRs’ in ME/CFS. Cerebral blood flow There are data that indicate that cerebral blood flow is significantly reduced in ME/CFS patients compared to controls. Out of 429 ME/CFS participants, 90% (384/429) exhibited reductions in cerebral blood flow measurements that surpassed a defined cut-off value (13%) during orthostatic testing (but not in the supine position). The mean reduction for the control and ME/CFS group was 7% and 26%, respectively. Not unexpectedly, 100% of patients with POTS and 98% with delayed orthostatic hypotension presented with values greater than 13%; unexpectedly, in ME/CFS patients without heart rate or blood pressure problems, 82% exceeded the cut-off value. Markedly reduced cerebral blood flow during 30-min head-up tilt testing was observed in those ME/CFS participants with and without heart rate and blood pressure abnormalities, meaning that cerebral blood flow is perturbed even in those without orthostatic pathophysiology. Deficits in cerebral blood flow have potential to account for ME/CFS symptom manifestation and have even been associated with symptom severity – further follow-up is essential. Related to the findings of reduced cerebral blood flow, hypoperfusion of particular brain regions have been documented in ME/CFS participants, including the brainstem, cerebral cortex, anterior cingulate, lingual gyrus, superior temporal gyri, and regions associated with the limbic system. There are also differences in regional cerebral blood flow between ME/CFS and control subjects following mental exertion, as well as neuro-functional differences. The abnormalities in cardiovascular dysfunction discussed thus far may result from neuronal issues. Functional and structural defects of the nervous system have been reported in ME/CFS, and have been proposed as drivers of the disease. Autonomic dysfunction is a common finding in ME/CFS cohorts, and recent studies have shown that a subset of patients exhibit signs of small fibre neuropathy. In a systematic review, it was inferred that the autonomic defects underlie the cardiovascular abnormalities observed in ME/CFS patients. Pyridostigmine, an acetylcholinesterase inhibitor which aims to ameliorate impaired autonomic signalling, improves cardiac performance in ME/CFS patients. Further study of pyridostigmine in ME/CFS individuals with cardiovascular abnormalities/orthostatic symptoms is therefore warranted. Haematological findings Components of the haematological system are susceptible to influence from pathology in different physiological systems, and are thus useful and relatively convenient markers for health and pathology assessments. Erythrocytes, leukocytes, platelets, and clotting proteins are exposed to and affected by O&NS, inflammation, and metabolites. In diabetes, excessive glycation is noticeable in red blood cells and plasma proteins; inflammatory cytokines can induce changes in platelets, erythrocytes, and coagulation; hormones modulate viscoelastic changes; and microbes can influence the activity of platelets and upregulate or inhibit clotting processes. Whilst a fair amount of study has been conducted on cardiovascular function and leukocytes in ME/CFS, there is much less literature regarding erythrocytes, platelets and clotting proteins. Erythrocytes, platelets, and clotting proteins An early study noticed that ME/CFS individuals have a significantly lower number of normal, discocytic erythrocytes, and instead possessed, what seems to be, high levels of stomatocytes. There are also indications of an increased erythrocyte sedimentation rate, although there are conflicting results. Red blood cells from ME/CFS individuals exhibit reduced deformability, accompanied by diminished membrane fluidity. This makes erythrocytes less pliable and stiffer, hindering efficient traversal through microcapillaries. This will impact the supply of oxygen to and retrieval of carbon dioxide from tissues and hinder blood flow (especially in capillaries where erythrocytes flow in a single file), which in turn might give rise to some symptoms associated with ME/CFS. Low erythrocyte volume might also contribute to shortcomings in circulation and oxygen delivery to tissues in ME/CFS. Defective erythrocytes also have the ability to induce endothelial dysfunction. With regards to the coagulation system, a significant hypercoagulable state was recognised in ME/CFS patients with active herpes infection. However, over 80% of patients possessed hereditary risk factors for thrombosis (a finding which has not been exclusively identified in ME/CFS cohorts since), thereby limiting interpretive power. A different study demonstrated elevated fibrinogen levels, platelet hyperactivation, and hypercoagulability. The authors also alluded to the notion of anomalous clot deposition on the endothelium which can impair substance exchange between blood and tissues, and subsequently give rise to ME/CFS symptoms. Bonilla and colleagues determined that extracellular vesicles from ME/CFS patients contained significantly elevated levels of the platelet marker, CD41a. CD41a is a component of GPIIb/IIIa complex – the platelet receptor that binds fibrinogen and von Willebrand factor, and mediates platelet adhesion and aggregation, and clotting. Further indications of platelet hyperactivity come from a recent study using transmission electron microscopy, where significant platelet spreading and aggregation was documented in ME/CFS samples. In contrast, a study from 2006 found neither platelet hyperactivation nor hypercoagulation in their ME/CFS cohort. Recently, more attention has been directed towards ME/CFS due to the insights obtained from the COVID-19 pandemic. Some patients who become infected with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) develop a post-viral syndrome called Long COVID (or post-acute sequelae of COVID-19), of which the symptoms include: chronic fatigue that is unresolved with rest; PESE; cognitive dysfunction; sleep difficulties; OI; POTS; muscle and joint pain; headaches; flu-like symptoms; gastrointestinal issues; sensory impairments; and respiratory defects. Long COVID patients respond negatively to exercise therapy, exhibiting adverse reactions much in the same manner as ME/CFS individuals. Additionally, females are also more affected than males, as is observed in ME/CFS populations. The effect of sex-specific physiology in the context of these two post-viral diseases is acknowledged, but requires further study and elucidation. The two syndromes exhibit striking similarities, so much so that many Long COVID patients meet the diagnostic criteria for ME/CFS. It is widely accepted that COVID-19 is associated with severe micro- and macro-clotting pathology, which is a major target of therapy in acute cases. We have published findings of small amyloid fibrin clots, called fibrinaloids or microclots, as well as hypercoagulation and hyperactivated platelets, in Long COVID patients. SARS-CoV-2 spike protein is sufficient to induce the anomalous clotting, that has an amyloid character, and can be induced with small amounts of a variety of initiators that bind to fibrinogen molecules. Fibrinaloids are amyloid in nature and more resistant to fibrinolysis, and can be larger than the lumen of the smallest capillary. Hence, fibrinaloids have the potential to block microcapillaries and impair oxygen delivery to tissues. There is also evidence that anomalous clots formed by SARS-CoV-2 spike protein exhibit increased proinflammatory activity. Using proteomics, we discovered that inflammatory molecules – including α(2)-antiplasmin and SAA – were ‘trapped within’/associated with fibrinaloids. α(2)-antiplasmin might be important for the persistence of fibrinaloids as its activity inhibits plasmin, an enzyme essential for fibrinolysis. To add, the molecular phenotype of amyloid clots decreases the ability of fibrinolytic proteins to degrade fibrin as the interior of clots are less accessible. Because of the similarities between Long COVID and ME/CFS, we sought to investigate whether the clotting pathology observed in Long COVID patients is also present in individuals with ME/CFS. We recruited 25 individuals with ME/CFS and 15 age-matched controls, and obtained blood samples for both whole-blood (WB) and platelet-poor plasma (PPP) analyses. Our results show that ME/CFS PPP samples contain significantly greater levels of fibrinaloids when compared to controls. The load of fibrinaloids in ME/CFS, however, seems to be lower than that of Long COVID. Fibrin networks – formed by the addition of thrombin to PPP – from the ME/CFS group contained significant amyloid fibrinogen, indicating pathology of terminal fibrin networks. The latter may interfere with hemostasis, leading to prolonged endothelial/vessel repair as a result of amyloid fibrin deposition on the endothelium and subsequent inflammation. Platelet hyperactivation, as determined by the degree of spreading and clumping, was also present in the ME/CFS population, although the degree of activation varied across participants. Thromboelastography (TEG) analysis of both WB and PPP samples demonstrated a high prevalence of hypercoagulability in the ME/CFS group. Together, these results demonstrate pathology in the coagulation system of individuals with ME/CFS, and that this pathology is mirrored in Long COVID. We have recently published a review proposing that ME/CFS and Long COVID pathology is a result of ischaemia-reperfusion injury, where fibrinaloids play a central role. Pertinently, Long COVID patients who were treated with antiplatelet and anticoagulant drugs (Clopidogrel, Aspirin, and Apixiban) experienced symptom relief – whether this is a possibility or not for a majority of ME/CFS patients with such clotting pathology remains to be determined. Over 20 years ago, Berg and colleagues reported hypercoagulability and platelet hyperactivation in an ME/CFS cohort, and alluded to the idea that small (anomalous) fibrin aggregates adhere to the endothelium and impair the exchange of substances between the blood and tissue, subsequently giving rise to symptoms. The latter – in light of our findings – can now be interpreted as fibrinaloids. Fibrin(gen) binds to several endothelial receptors and hence can modulate their activity – it is of interest to determine the mechanistic differences between normal fibrin and fibrinaloids/amyloid fibrinogen in an endothelial context. Amyloid-type molecules have a tendency to damage lipid membranes and might account for lipid peroxidation and endothelial dysfunction observed in ME/CFS. Furthermore, fibrinaloids are proinflammatory and persist more than normal fibrin matter due to their fibrinolytic resistance. These are characteristics that can exaggerate any pathological impact on the endothelium. It is known that ME/CFS plasma induces endothelial dysfunction in healthy cells – further analysis is required to determine if fibrinaloids are largely responsible for this phenomenon. The endothelium - An interface for symptom manifestation? Endothelial dysfunction is a prominent component of cardiovascular disease, and is prompted by an increase in O&NS and inflammation. Endothelial cells are important for vessel regulation whereby nitric oxide and endothelin synthesis and release modulate constriction and dilation activity. Hence, changes in the regulation of vessel modulators from endothelial cells are implicated in cardiovascular disease. Furthermore, the endothelium is responsible for enabling the transfer of substances across the vessel wall; a damaged endothelium is expected to lead to impairments in substance exchange in localised areas. In Long COVID, endothelial dysfunction is a common finding amongst patients and has been centralized in disease hypotheses. Reduced tissue perfusion and oxygenation at the capillary level, resulting from coagulopathy and endotheliopathy, is one of the proposed mechanisms for symptom manifestation in Long COVID. Targeting endotheliopathy in Long COVID has shown benefit in some cases, and is therefore receiving further exploration. This highlights the question of whether or not endothelial dysfunction is involved in ME/CFS pathology and symptom manifestation. A study examining endothelial function in ME/CFS has revealed peripheral endothelial dysfunction in 51% (18/35) of subjects. Patients with endothelial dysfunction also reported worse symptom scores than those without. Studies using flow-mediated dilation (FMD) and post-occlusive reactive hyperaemia have described endothelial dysfunction in both large and small vessels in ME/CFS cohorts. MicroRNA markers associated with endothelial dysfunction have also been implicated. Human umbilical vein endothelial cells exposed to plasma from ME/CFS individuals show significant reductions in synthesized and secreted nitric oxide in the absence or presence of endothelial nitric oxide synthase (eNOS) stimulators, therefore pointing to a defective enzymatic function of eNOS. Furthermore, inhibitory phosphorylation of eNOS at Thr495 was greater as a result of ME/CFS plasma than it was with control plasma. Identifying the plasma constituent responsible for the aforementioned effects is of utmost importance, as it may lead to the identification and annotation of pathological mechanisms involved in ME/CFS, and, hopefully, biomarker establishment. Furthermore, targeting (or replacing) this unknown molecule(s) in a therapeutic manner might offer symptomatic relief. These studies emphasize the potential of investigating the haematological system in ME/CFS. Similarly, another study that exposed ME/CFS sera to healthy endothelial cells reported the release of molecules that inhibit nitric oxide pathways, as well as the downregulation of endothelial activation markers. The researchers also revealed an increase in autoantibody binding to endothelial surfaces in the ME/CFS group, which they sought to investigate due to evidence of autoimmunity in ME/CFS. Whether antibody-dependent cellular cytotoxicity is mounted against the healthy endothelial cells is still to be determined, but the finding suggests that autoimmune processes and impairments of the endothelium are linked. It might also be a possibility that this autoantibody binding to the endothelium induces procoagulant cascades, perhaps via the complement system or interaction with platelets. Endothelin-1, a potent vasoconstrictor that is released by endothelial cells and involved in cardiovascular pathology, was shown to be significantly increased in 5/14 COVID-19 patients who have ME/CFS. The dysregulation of these vaso-modulators – endothelins and nitric oxide – might contribute to impairments in blood flow in ME/CFS. To add, regional cerebral blood flow and endothelial dysfunction have been linked. Whether endothelial dysfunction underlies the abnormalities of cerebral perfusion in ME/CFS remains to be determined. A recent study published in 2023 has further corroborated endothelial dysfunction in ME/CFS. Endothelial dysfunction and the consequences that follow, including reduced substance delivery to tissues and hypoxia, might lead to systemic defects that bring about symptom manifestation. Indeed, endothelial dysfunction and reduced tissue perfusion has recently been implicated in hypotheses for ME/CFS pathology. More research is required to elucidate the status and role of the endothelium in ME/CFS. Viruses: How are they involved, and where are they hiding? The overlap between ME/CFS and Long COVID brings into the spotlight (if not already in the spotlight) the role of viral infection in ME/CFS initiation and maintenance. The etiology of Long COVID can be confidently attributed to SARS-CoV-2 infection, and since Long COVID clinically presents much in the same way as ME/CFS, the two diagnoses may share similar etiology. There is now even more reason to believe that viruses cause, or at least have a major role to play in pathogenesis of post-viral, fatigue-like illnesses like ME/CFS. An elucidation of the mechanisms whereby SARS-CoV-2 contributes to Long COVID pathology may consequently inform the ME/CFS disease process. Although multiple viral species have been implicated in ME/CFS, a single pathogenic specie has not yet been identified in all ME/CFS patients within a particular cohort. However, few teams have studied persistent infection in ME/CFS with advanced technologies capable of identifying low biomass organisms in tissue and/or associated gene expression patterns. To add, the viruses implicated in ME/CFS – predominantly the herpes viruses (EBV, human cytomegalovirus, HHV-6, and HHV-7) – are common infectious agents within the general population, which increases the difficulty of identifying a causative role for these pathogens in ME/CFS individuals. Herpes viruses are capable of establishing life-long latency in human tissue and reactivate spontaneously or when immune function is impaired. EBV, HHV-6, HHV-7, and human cytomegalovirus can remain dormant in mononuclear cells, including monocytes, T-cells, and B-cells, and reactivate to infect other cells or hosts. EBV expresses a particular affinity for B-cells, with latency in this cell-type well characterized. It must be noted that reactivation of herpesviruses is not always associated with disease, and often occurs without any noticeable symptoms. Hence, this emphasizes the complexity associated with herpesvirus reactivation and diseased states, such as ME/CFS. The specifics of herpesvirus latency, reactivation, and therapeutics is reviewed elsewhere. Incidentally, SARS-CoV-2 infection leads to the reactivation of herpesviruses, specifically EBV. Reactivation of these viruses and the subsequent maladaptation of physiological systems, including the immune, endocrine, and nervous system, are believed to be important steps in ME/CFS pathology. In a study from 2019, 38% of ME/CFS patients exhibited an upregulation of the Epstein–Barr virus (EBV) induced gene 2 (EBI2) in PBMCs, suggestive of EBV reactivation. A follow-up study provided further indications that this gene is upregulated as a result of EBV activity in ME/CFS. Furthermore, B-cells – the cell-type favoured by EBV – have been noted to be dysfunctional in ME/CFS studies – the thinking goes that latent (or active) EBV infection is responsible for this B-cell dysfunction. Furthermore, autoimmunity driven by defective B-cell functioning is suspected to bring about autoreactivity which in turn contributes to symptom manifestation. There are many other studies demonstrating increased antibody levels directed at herpesviruses (not only EBV) in ME/CFS. More recent studies have identified herpesvirus nucleic acids and antigens, in significant concentrations, in ME/CFS tissue. Rasa- Dzelzkaleja et al (2023) showed that 45% of ME/CFS individuals within their study were experiencing reactivation of herpesviruses (HHV-6 and HHV-7), and that these individuals expressed higher proinflammatory markers (IL-6, TNF-α) than those ME/CFS individuals with latent infection. While more work is needed to effectively define the mechanisms associated with herpesvirus-related ME/CFS pathology, there is a general acceptance that herpesviruses play an important role in the pathogenesis of this disease. ME/CFS patients with reactivated herpesvirus (HHV-6 and HHV-7) infection were treated with antiviral drugs which resulted in some degree of success (less than 50% within each group of patients presented with negative PCR results following treatment). Infection with herpesviruses leads to the production of proinflammatory cytokines and impairment of immune cell function. In ME/CFS, both an increase in proinflammatory cytokines and a reduction in natural killer (NK) cell activity (cytotoxicity) are present. Well known is it that chronic inflammation is central to a variety of diseases, including cardiovascular disease, cancer, diabetes, and psoriasis. However, the cardiovascular abnormalities observed in ME/CFS patients do not seem to be ‘classical’, i.e. atherosclerotic in nature, but rather manifest as reduced cardiac function (as inferred from findings of reduced stroke volume and cardiac output). Defects in autonomic control of the heart and blood vessels are believed to underlie these cardiac abnormalities. Relevantly, the role of pathogens (including herpesviruses) in the induction of autonomic dysfunction, predominantly in a cardiovascular context, has been reviewed and might influence cardiac function, indirectly, in ME/CFS. Infection of nervous tissue by herpes viruses can lead to inflammation, cellular dysfunction, and sometimes severe complications like meningitis. With regards to the autonomic nervous system, EBV infection has previously been shown to exist alongside acute autonomic neuropathy, as well as orthostatic symptoms. Furthermore, infectious mononucleosis – a disease predominantly caused by EBV – is accompanied by long-lasting autonomic symptoms, suggestive of persistent infection or neurological maladaptation. A pathogenic protein produced by EBV, deoxyuridine triphosphate nucleotidohydrolase (dUTPase), can alter gene expression in glial and endothelial cells in a manner which can promote neuroinflammation and potentially symptom manifestation, and has been implicated (immunologically) in an ME/CFS cohort. Interestingly, a hypothesis involving neuroglia dysfunction in ME/CFS has recently been published. Defective autonomic functioning, neuropathy, and orthostatic symptoms have also been observed following human cytomegalovirus infection, HHV-6 infection, and SARS-CoV-2 infection. To further implicate herpes viruses in neuronal tissue, and specifically in ME/CFS, a recent study found significant levels of EBV and HHV-6 microRNA in brain and spinal cord tissue from deceased ME/CFS individuals. Ultimately, there is evidence to suggest that (herpes) viruses might, via the infection of nervous tissue and subsequent impairment of autonomic functioning, account, in part, for the cardiac abnormalities observed in ME/CFS individuals; although more research is required with regards to this topic. In the context of the coagulation system, molecular products from viruses and bacteria have the ability to influence platelets and clotting proteins (refer to Fig. 1 ). Both lipopolysaccharide and lipoteichoic acid can induce anomalous, amyloid-containing clots that are distinctly different from healthy clots. Furthermore, both of these bacterial inflammagens can directly interact with platelet receptors, modulate platelet activity, and induce hypercoagulability, ultimately leading to a prothrombotic state. Conversely, gingipain R1, a protease from a periodontal pathogen named Porphyromonas gingivalis, can degrade clots and inhibit enzymatic formation of fibrin networks. For long it has been known that viruses can influence coagulation, via direct interaction with clotting proteins and platelets. SARS-CoV-2 causes severe clotting pathology, reflected by hyperactivated platelets, hypercoagulability, and fibrinaloid microclots. We assessed whether the spike protein S1 subunit from SARS-CoV-2 virus can induce fibrinaloid formation, from which it was confirmed that spike protein induces fibrinaloid formation in control plasma samples which lack fibrinaloids in their naïve state – this finding has been corroborated. Specifically, the spike protein S1 subunit induced structural modifications in the β and γ fibrinogen chains, as well as prothrombin. The latter may lead to activation of the zymogen, and subsequent (defective) conversion of fibrinogen into fibrinaloids. We note too that spike itself is potentially amyloidogenic. As fibrinaloids are present in ME/CFS individuals, albeit to a lesser extent than observed in Long COVID cohorts, the question of which agent or agents are responsible for the induction of fibrinaloids in ME/CFS arises. It is plausible to hypothesize that viruses (and potentially other microbes) are contributing to the clotting pathology observed in ME/CFS individuals. Herpes viruses, the virus types most implicated in ME/CFS, are known to influence coagulation in a prothrombotic manner. EBV infection has been associated with disseminated intravascular coagulation, and cytomegalovirus can induce hypercoagulation. These two herpes viruses also interact with platelets via a number of platelet receptors, including toll-like receptors and complement receptors. Hence, there is reason to hypothesize that herpes viruses are responsible, to a certain extent, for clotting dysfunction observed in ME/CFS individuals. Next, where are the viruses? In Long COVID, they are widely distributed. ME/CFS harbours viral reservoirs, where reactivation and virulent molecule secretion might underlie pathology. A recent study has identified significant levels of EBV and HHV-6 microRNA in the central nervous system of deceased ME/CFS individuals, which points at active infection in the brain and spinal cord. It is known that EBV favours B-cells for infection; the finding of EBV infection in the brain might be indicative of EBV reactivation in and shedding of virus particles and proteins from B-cells – perhaps EBV viruses have ‘spilled over’ into other physiological systems. Microglial activation and inflammatory sequelae can ensue following herpes infection, and may contribute to neuroinflammation and autonomic dysfunction observed in ME/CFS. The endothelium is an infection site for herpes viruses, and constitutes a site from which clotting pathology can be easily orchestrated. Monocytes, a reservoir site from which the coagulation system can also be influenced from, act as viral reservoirs for herpes viruses too, as they do for SARS-CoV-2 proteins in Long COVID patients. These monocytes exhibit senescence, which is believed to enable their persistence in circulation. Furthermore, the gut microbiome is not exempt from scrutiny. Whilst further research on viral persistence in ME/CFS is required, we aim to emphasize the idea that viral reservoirs and their subsequent influence on host physiology might be responsible for the maintenance of ME/CFS, Long COVID, and other post-viral syndromes. In light of what has been discussed, Fig. 2 represents a depiction of viral persistence and subsequent influence of various physiological systems in ME/CFS. | [
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37370560 | title | A New Breakpoint to Classify 3D Voxels in MRI: A Space Transform Strategy with 3t2FTS-v2 and Its Application for ResNet50-Based Categorization of Brain Tumors | []
|
38961406 | results | Results The analysis included 607 participants [age: 65.99 ± 8.79 years, females: 363 (59.80%); HCs, n = 110; MCI, n = 269; and AD dementia, n = 228]. Of the 497 patients on the AD continuum, 138 (27.77%) underwent lumbar puncture for CSF hallmark testing (MCI, n = 33; AD dementia, n = 105). Table 1 presents the participants’ demographic, clinical, CSF, and neuroimaging characteristics at baseline. Patients with AD dementia exhibited higher ChP volume and ChP/eTIV compared to that of patients with MCI and HCs (all P < 0.001). Figure 1 depicts representative 3D T1-weighted images of ChP volume in age- and sex-matched patients from the three groups. Baseline correlations of ChP with CSF hallmarks, neuropsychological tests, and multimodal neuroimaging measures in the AD continuum Figure 2 illustrates a heatmap showing the correlation of ChP volume with CSF hallmarks, neuropsychological tests, and multimodal neuroimaging measures at baseline in patients on the AD continuum. ChP volume (and ChP/eTIV) enlargement was correlated with decreased CSF Aβ42 (r= -0.310) and Aβ40 levels (r=-0.207), MMSE (r=-0.301) and MoCA scores (r=-0.281), but increased NPI (r = 0.208) and ADL scores (r = 0.311). This enlargement was correlated with a decline in the subcortical GM (r=-0.150) and hippocampal (r=-0.197) volumes; average CT of the whole brain (r=-0.333), entorhinal cortex (r=-0.280), middle temporal lobes (r=-0.366), and parahippocampal gyrus (r=-0.262); and cCBF values of the whole brain (r= -0.176), thalamus (r= -0.177), middle cingulate cortex (r=-0.20), posterior cingulate cortex (r=-0.263), middle frontal cortex (r=-0.14), superior temporal cortex (r=-0.194), precuneus (r=-0.207), and angular gyrus (r=-0.208), after adjusting for confounding factors (all P < 0.05). Mediating effect of ChP volume on the association between CSF hallmarks and neuropsychological tests on the AD continuum Figure 3 presents the simple mediating effect of ChP volume, hippocampal volume, LVV, or ECT alone on the association between CSF biomarkers and neuropsychological tests on the AD continuum. The associations between CSF Aβ42 levels and MMSE scores mediated by the ChP volume, hippocampal volume, and LVV alone were 19.08%, 39.25%, and 10.81%, respectively (Fig. 3A). Furthermore, the associations between CSF Aβ42 levels and MoCA scores mediated by the ChP volume, hippocampal volume, and LVV alone were 21.87%, 47.02%, and 14.34%, respectively (Fig. 3B). There was no mediating effect of ECT on these associations (all P > 0.05). The associations between CSF Aβ40 levels and MMSE scores mediated by ChP volume, hippocampal volume, and ECT alone were 36.57%, 48.59%, and 32.19%, respectively (Fig. 3C). The associations between CSF Aβ40 levels and MoCA scores mediated by ChP volume was 42.00%; no mediating effect of hippocampal volume, LVV, or ECT was observed on the association between CSF Aβ40 levels and MoCA scores (all P > 0.05; Fig. 3D). Notably, while the associations between ChP volume and MMSE and MoCA scores mediated by the CSF Aβ42 levels were 39.49% and 34.36%, respectively, no mediating effect of CSF Aβ40 levels on the association between ChP volume and these two scores was observed. All four neuroimaging measures exerted no mediating effect on the association between CSF hallmarks and the NPI score or ADL score (all P > 0.05). Diagnostic accuracy of ChP volume to identify cerebral pathological deposition and disease stages Figure 4 presents the ROC curves of four neuroimaging measures to identify the presence/absence of cerebral Aβ deposition and to differentiate among patients with AD dementia, MCI, and HCs. ChP volume alone exhibited higher diagnostic accuracy in identifying cerebral Aβ42 changes on the AD continuum than LVV (AUC = 0.806 vs. 0.669, P = 0.038) and ECT alone (AUC = 0.806 vs.0.629, P = 0.008). No significant difference was observed between the ChP and hippocampal volume alone (AUC = 0.806 vs. 0.717, P = 0.166); however, the ability of combined ChP and hippocampal volume (AUC = 0.815 vs. 0.806, P = 0.735) or combined four neuroimaging measures (AUC = 0.826 vs. 0.806, P = 0.443) to identify cerebral Aβ42 changes showed no significant advantage compared with that of ChP volume alone (Fig. 4A). ChP volume alone demonstrated higher diagnostic accuracy in differentiating patients with MCI from the HCs than hippocampal volume (AUC = 0.845 vs. 0.805, P = 0.009) and LVV alone (AUC = 0.845 vs.0.817, P = 0.031), although no significant difference was observed between ChP volume and EC thickness alone (AUC = 0.845 vs. 0.845, P = 0.981). However, combined ChP and hippocampal volume did not provide a significant advantage over ChP volume alone in differentiating patients with MCI from HCs (AUC = 0.845 vs. 0.845, P = 0.654; Fig. 4B). ChP volume alone exhibited lower diagnostic accuracy in differentiating patients with AD from those with MCI than hippocampal volume (AUC = 0.791 vs. 0.843, P = 0.007), LVV (AUC = 0.791 vs. 0.832, P = 0.004), and ECT alone (AUC = 0.791 vs. 0.836, P = 0.018; Fig. 4C). There was no significant difference regarding their ability to differentiate patients with AD dementia from HCs for ChP volume (AUC = 0.946), hippocampal volume (AUC = 0.955, P = 0.398), LVV (AUC = 0.953, P = 0.355) and ECT alone (AUC = 0.969, P = 0.05; Fig. 4D). More importantly, when the ChP and hippocampal volumes were combined, the diagnostic efficiency for identifying cerebral Aβ42 changes and differentiating patients with AD dementia from those with MCI, patients with AD dementia from HCs, and patients with MCI from HCs increased to 0.816 (95%CI: 0.720–0.911), 0.863 (95%CI: 0.831–0.895), 0.972 (95%CI: 0.957–0.986), and 0.845 (95%CI: 0.803–0.888), respectively, all of which were significantly higher than the diagnostic efficiency of hippocampal volume alone (P = 0.029, P = 0.008, P = 0.004, and P = 0.009, respectively). Baseline and longitudinal associations between ChP volume and clinical presentations in patients across the AD continuum Table 2 summarizes the association of ChP volume, hippocampal volume, LVV, ECT alone, and combined ChP and hippocampal volumes with the neuropsychological tests in patients across the AD continuum at baseline. After correcting for age, sex, years of education, APOE ε4 status, and eTIV, ChP volume alone was associated with MMSE (β=-0.32, P < 0.001), MoCA (β=-0.34, P < 0.001), NPI (β = 0.23, P < 0.001), and ADL scores (β = 0.31, P < 0.001) at baseline (Table 2, Model 1). After correcting for hippocampal volume and the above-mentioned confounders, ChP volume was also associated with MMSE (β=-0.23, P < 0.001), MoCA (β=-0.24, P < 0.001), NPI (β = 0.19, P < 0.001), and ADL scores (β = 0.23, P = 0.006) at baseline (Table 2, Model 2). The interaction between ChP and hippocampal volumes was only observed for the MMSE score at baseline (P = 0.002; Table 2, Model 3). Among the 497 patients on the AD continuum at baseline, 155 (MCI: 86 and AD: 69) were followed-up for an average of 10.0 ± 4.5 months. The clinical profiles of participants lost to follow-up, and those who completed follow-up are listed in Supplementary eTable 1. Table 3 presents the longitudinal associations between the rates of change in ChP volume, hippocampal volume, LVV, ECT alone, or combined ChP and hippocampal volumes and the rates of change in neuropsychological tests in patients in the AD continuum during the follow-up period. After correcting for age, sex, years of education, APOE ε4 status, and the rate of change in eTIV, rapidly enlarged ChP volume was longitudinally associated with a faster increased in the NPI score (β = 5.16, P = 0.024; Table 3, Model 1). After correcting for hippocampal volume and the above-mentioned confounders, rapidly enlarged ChP volume was also longitudinally associated with a faster increased in the NPI score (β = 5.25, P = 0.023; Table 3, Model 2). Moreover, there was no interaction between ChP and hippocampal volumes in these associations (P = 0.435; Table 3, Model 3). | [
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38474961 | methods | 2. Methodology 2.1. Experimental Protocol 2.1.1. Study Design A randomized controlled, within-participant, crossover design was used to examine the effects of four conditions—silence, self-selected favorite music, negative feedback, and positive feedback—on moods, individual muscle firing patterns, and motor coordination. In all interventions, participants completed six 5 min walking segments, with participants’ moods being measured at baseline and after each 5 min walk. Participants completed each condition in a randomized order after the completion of a familiarization session. On average, participants began the study 3.4 ± 2.1 days after the familiarization day. 2.1.2. Screening Participants were recruited using campus-wide emails and verbal announcements in large classes (>20 students) at a small private university in northern New York and through the posting of flyers with QR codes throughout the campus. All interested participants were directed to an online survey to assess inclusion/exclusion criteria. To be included in this study, participants had to be able to stand and walk without an assistive device for a minimum of 60 min and had to be between the ages of 18 and 45. Participants were excluded if they had an impairment or were unable to perform physical activity independently, reported pain or discomfort when walking, had a neurological condition, had a recent (<6 months) orthopedic surgery that impacted their walking ability or balance, reported a wound on the plantar surface of their foot, or had a visual impairment. 2.1.3. Participants Approval for this study was granted by the Clarkson University Institutional Review Board (IRB) (approval #20.20-6). Volunteers not excluded by the screening questionnaire were invited to participate in the study and were scheduled for a familiarization day. At the beginning of the familiarization day, all participants read and initialed each page and signed the IRB-approved informed consent forms. Participants were informed that they would be participating in a study assessing the impact of various psychological interventions on moods and walking. The study was started in January 2020. However, due to the COVID-19 pandemic, all data collection was paused due to COVID-19 restrictions, and all data collected prior to March 2020 were excluded. Data collection restarted in July 2021 after all COVID restrictions had been lifted, and data collection was completed in May 2022. Therefore, the data reported here refer only to individuals who completed the study after July 2021. Of the 40 participants who completed the inclusion/exclusion survey after 8 July 2021 did not qualify for the study (all reported a lower extremity orthopedic injury). Of the 32 participants who qualified for the study, 26 completed the study (10 males, 16 female, age = 23.04 ± 5.64). The demographic characteristics of the participants are shown in Table 1. Using G*Power (version 3.1.9.6, Heinrich-Heine-Universitat Dusseldorf, Dusseldorf, Germany), an a priori power analysis was completed, and this analysis showed that a sample size of 20 would provide sufficient statistical power (α = 0.05, 1 − β = 0.80) to detect a 4-intervention × 7-time interaction effect size of 0.25, assuming a correlation across repeated measures on time of 0.50. To reduce the potential for Type II errors, 26 participants completed the study in case there were outliers and data had to be excluded. 2.1.4. Auditory Stimulation for Four Interventions Silence: Participants were instructed to wear noise-canceling headphones to eliminate external auditory stimuli during the walking sessions. Music: Participants were allowed to choose and listen to music of their preference via a music streaming application of their choice, such as Amazon Music, Pandora, Spotify, iHeartRadio, or Apple Music, during the walking sessions. Positive Reinforcement: Participants received auditory feedback in the form of positive reinforcement through the headphones every 30 s. Negative Reinforcement: Participants received negative reinforcement through the headphones every 30 s. Table 2 presents positive and negative interventions utilized in the study, including affirmations such as “Good job, you’re doing awesome!” and criticisms like “You’ve got to walk faster than that”. 2.1.5. Experimental Procedure Familiarization Day: If a subject met the inclusion/exclusion criteria, they were invited to the laboratory for a familiarization day. At the beginning of the familiarization day, all participants were informed that they would be asked to walk under four different conditions that they would be assigned to in random order. Participants were then told that they would have to wear noise-canceling headphones during all conditions and that, one day, they would be asked to walk in silence (silence), another day, they’d be asked to play their favorite music (music), another day, they would hear positive phrases through the headphones (positive feedback), and the final intervention would involve a research assistant screaming negative phrases at them through the headphones (negative feedback). All participants agreed to these conditions and signed the informed consent form. After signing the informed consent form, each participant’s height was measured using a stadiometer (SECA model 220, SECA Corporation, Chino, CA, USA), and weight was measured using the Tanita Bioelectrical Impedance Analysis Scale (TBF-410, Tanita Corporation, Tokyo, Japan). After height and weight data were collected, the subjects were asked to complete a series of surveys to assess baseline data such as mental traits and physical energy and fatigue, grit, sleep quality and quantity over the last 30 days, diet quality, moods, and physical activity behavior over the last 7 days. After the completion of these surveys, the participants were fitted with 16 Delsys Trigno sEMG/IMU sensors (Delsys Inc., Boston, MA, USA). The Delsys Trigno series comprises wireless, wearable sensors integrating sEMG and inertial measurement unit (IMU) functionalities. This technology enables the simultaneous capture of high-fidelity muscle activity and movement data, offering valuable insights for diverse applications. Available in configurations ranging from a single channel (Trigno Avanti) to up to 12 channels (Trigno Pro), these sensors boast high data quality, portability, and user comfort, making them well suited for biomechanics research, rehabilitation monitoring, sports performance analysis, and prosthetic/orthotic control studies. Prior to placing the sensors on the participant, the area of sensor placement was cleaned with alcohol wipes, then shaved using a disposable razor, cleaned again using an alcohol wipe and gauze, and then marked with a red washable marker. The sensors were then placed in the following locations: the forehead (between the frontal eminence and line with the nose); left and right Sternocleidomastoid (midpoint between the mastoid process and the clavicle); sternum (right below the notch of the manubrium); right wrist (between the ulna and radius on the last crest of the skin); left and right rectus femoris (three quarters of the distance between the greater trochanter and the superior aspect of the patella); left and right Tibialis Anterior (midpoint between the inferior aspect of the patella and the talo-tibial joint); left and right foot (outside of the shoe on the inner edge of the big toe); left and right Cervical Erector Spinae (C4), top of the iliac crest (on L4, right above L5-S1); belly of right bicep femoris longus (located by palpating the popliteal fossa and then moving proximally towards the ischial tuberosity to locate the muscle belly); and the belly of the right medial gastrocnemius (midpoint between popliteal fossa and the triceps surae) (Figure 1). After the placement of the sensors, the participants were asked wear noise-canceling headphones (COWIN E7 Active Noise Cancelling Headphones, Cowin Audio, City of Industry, CA, USA) and asked to play their favorite music or station on their favorite streaming application on the lab-provided Samsung Galaxy S5 (Samsung Electronics, Suwon, republic of Korea) wireless phone. Participants were informed that this was the music/station that would be selected for their music day trial. After participants had entered their choice, they were asked to stand at the start of the 14 m × 10 m walking track (Cone 1-Figure 2). Participants were then asked to complete a survey on a 12.9-inch iPad Pro (256 GB, model MLOT2LL/A) that asked them how they felt and how motivated they were to perform mental and physical tasks at the moment. After the completion of the survey, the participants were then asked to commence walking around the track towards cone 2, then turn towards cone 3, then towards cone 4, and then walk back towards cone 1. The participants were asked to walk at a speed that they felt comfortable walking at and were told that they would be walking for 5 min. After the completion of the 5 min walk, the participants were asked to complete another survey to ask them how they felt and how motivated they were to complete mental and physical tasks at that moment. Upon the completion of these surveys, the sensors were removed, and the participants were instructed to abstain from caffeine consumption and vigorous and moderate physical activity for a minimum of 12 h prior to their next session and to get their usual night’s amount of sleep. No data from the familiarization day were included in our analysis. Testing Days 2–5: Participants were scheduled for 4 testing sessions, with each session being a minimum of 48 h apart but within 14 days of the previous session. The number of days between sessions was 4.2 ± 3.28 days. To limit the effects of diurnal variations, participants were scheduled ± 30 min from the time of their first testing day (i.e., if the first testing day was scheduled at 9:00, then the other 3 testing days were scheduled between 8:30 and 9:30). Since sleep has a substantial impact on gait, participants who reported 2 h more or less than their usual sleep duration (as self-reported on familiarization day) were not tested that day and were rescheduled. Participants who reported consuming caffeine and/or participating in moderate or vigorous physical activity 12 h prior to testing were also rescheduled. Using randomizer.org, the participants were randomly assigned their intervention order. On each testing day, the participants came into the lab where they completed the pre-testing questionnaire to determine their testing eligibility. Using the same procedures and placement sites as the familiarization day, the participants were fitted with sensors. The participants were then asked to place the noise-canceling headphones on their ears and to go to the start of the walking track (cone 1; Figure 2). The participants were then informed what intervention they would be receiving and then asked to complete a series of surveys that assessed their current mood states and their motivation to perform mental and physical tasks. After the completion of these surveys, the auditory intervention was started, and participants began walking. The participants walked for 5 min prior to being asked to stop in place and complete a series of surveys that assessed their moods and motivation. The participants completed a series of 6 rounds of walking for a total of 30 min (see Figure 3). After the final round, the participants were again asked about their moods and motivation. The sensors were then removed, and the participants were again reminded of the pre-testing instructions and scheduled for their next session. 2.2. Pre-Processing of Recorded EMG Signals 2.2.1. Filtering Prior to further processing, the EMG signals were subjected to band-pass filtering between 20 Hz and 400 Hz using a digital Butterworth filter. This filtering step aimed to isolate the EMG signal from low-frequency noise, such as baseline drift or movement artifacts, and high-frequency artifacts, such as power line noise, thereby enhancing the signal-to-noise ratio and facilitating an accurate analysis of muscle activity. 2.2.2. Resampling To ensure compatibility with downstream analysis tools and software packages, the EMG signals were resampled from their original sampling frequency of 1059 Hz to a standard sampling frequency of 1200 Hz using a sinc interpolation method. Resampling is a common practice in data processing, particularly when dealing with signals from different sources that may have varying sampling rates. This step helps to synchronize the EMG signals with other data streams, such as motion capture or force plate data, enabling a more comprehensive analysis of gait and balance patterns. 2.2.3. Segment Removal To identify and remove segments of data that did not meet specific quality criteria, a validity check was performed. Segments with continuous zeros, indicating EMG signal absence, were considered invalid and marked for removal. Similarly, segments containing NaN (Not a Number) values, suggesting data corruption or missing values, were also identified and eliminated. Additionally, segments that exceeded a duration of 0.1 s were deemed invalid, as they might represent periods of excessive noise or signal disruption. These invalid segments were removed from the EMG data to ensure the integrity and reliability of the remaining data for further analysis. 2.2.4. Handling Short Segments with Spline Interpolation In instances where the validity check resulted in shorter segments, spline interpolation was employed to fill in the missing data points. Spline interpolation is a mathematical technique that constructs a smooth curve through a set of data points, allowing for the estimation of values at intermediate points. By applying spline interpolation to shorter segments, the continuity of the EMG signals was maintained, preventing abrupt transitions or gaps in the data. This approach proved particularly useful when dealing with segments that were shorter than the specified threshold of 0.1 s, enabling the preservation of valuable information despite the presence of minor data gaps. 2.3. Feature Extraction Features, namely, statistical and Hjorth features, were extracted from the pre-processed EMG signals for a comprehensive analysis. A list of the extracted features and descriptions for each one are shown in Table 3. 2.4. Statistical Analysis and Classification The extracted features were analyzed using a Repeated Measures ANOVA (RM ANOVA) to determine the statistical significance of the time point pairs and intervention pairs. An RM ANOVA incorporates the non-independence of observations within subjects through a variance–covariance matrix, explicitly modeling the correlations among the repeated measures. Further, post hoc analysis was performed to explore where exactly the differences lie in the time point and intervention pairs. Bonferroni correction was applied to the significance levels for these multiple comparisons. Thus, the post hoc analysis provided more insights into the specific patterns of the features and allowed us to understand which time point/intervention pairs differ from each other. Also, the best feature for differentiating intervention and time point pairs for each muscle was computed using the select k best feature selection method. The features were fed to a Random Forest (RF) classifier for the classification of the 4 interventions. RF is an ensemble learning method that is based on combining multiple classifiers to handle a complex problem and improve performance. It aggregates the results of several decision trees on distinct subsets of a dataset to increase the dataset prediction accuracy. The more trees in the forest, the more accurate it is, and the risk of overfitting is minimized. The performance of the classifier was further evaluated using the following performance metrics (described in Table 4): accuracy (Acc), precision (Pre), recall (Rec), F1-score (F1), Specificity (spe), and Area Under the ROC Curve (AUC). | [
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|
31581969 | results | Results Comparison of “fully normal cognition” to “not-fully normal cognition” (group 1 versus group 2) showed that memory, executive function, and attention domains significantly differed between these cognitively normal subgroups (Table 1). The 3-cluster solution yielded the highest number of significant differences in cognitive domain scores (75%) across clusters in post-hoc analyses (Table 2, Figure 1). Attention and visuospatial abilities were significantly different across all clusters, while memory and executive function differed only across two. Only language was comparable across all clusters. Cluster 1 (n=64) was characterized by average performance in all domains, though memory was significantly lower than Clusters 2 and 3; Cluster 2 (n=39) was characterized by high average memory, low average attention, and average executive function, visuospatial abilities, and language; and Cluster 3 (n=45) was characterized by high average memory, executive function, attention, and visuospatial abilities, and average language. In comparing individual neuropsychological test scores across clusters, several tests across all domains emerged as significantly different (p <0.0083, Table 3). The clusters did not differ according to demographic (age, gender, education, ethnicity) or tremor (total tremor score, tremor disability scale, tremor duration, presence of head tremor, presence of voice tremor) variables, nor did they differ with respect to the usage of cognition-decreasing or mood-modulating medications or levels of depression (Table 4). However, number of medications, ABC-6, and MoCA were significantly different among clusters, with particular difference found between Clusters 1 and 3 (cluster 1 indicating more medications, lower balance confidence, and lower MoCA; post-hoc p <0.0167) in those variables. Additionally, the frequencies of cognitively normal subdiagnoses (fully normal cognition, test impairment of unlikely clinical significance, test impairment of possible clinical significance, and questionable/isolated functional impairment) were also significantly different across clusters (p >0.001, Table 5). Specifically, there were more individuals with fully normal cognition in Cluster 3 (n=30) than in the other clusters, and more individuals showing impairment of possible clinical significance in Cluster 1 (n=24) than in the other clusters. | []
|
32922516 | title | Gender issues of antibody-mediated diseases in neurology: (NMOSD/autoimmune encephalitis/MG). | [
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38913044 | results | RESULTS Increased body weight, serum glucose and insulin, lipids, and liver enzymes in OVX-mice fed a high fat-sugar-salt diet Body weight increased in the OVX-Diet group relative to the control mice (p<0.0001). Weight over time increased in both groups, yet in the OVX-Diet, from week ten onwards, the increase was much faster (p<0.0001), as expressed by a significant interaction between time and group (p<0.0001). The OVX-Diet mice reached a weight of 35.25±0.65 gr, while the control mice reached 25.57±0.6 gr (Fig. 2A). Blood pressure, measured 5.5 months after starting the diet, showed a tendency to increase in the OVX-Diet mice compared to the control mice: diastolic pressure was 105.58±2.34 mmHg in the OVX-Diet, and 96.62±5.91 mmHg in the controls (p=0.16); systolic pressure was 118.70±1.91 and 112.56±5.84 mmHg, respectively (0.29); mean pressure was 109.58±1.86 and 101.64 ±5.72 mmHg, respectively (p=0.18) (Fig. 2B). Six months after starting the diet, OVX-Diet mice showed a significant increase in serum glucose compared to the control mice: 103.4±4.5 mg/dl and 79.5 ±9.3 mg/dl, respectively (p=0.02) (Fig. 2C). An increase in serum insulin was also detected in the OVX-Diet mice relative to the control mice: 2.74± 0.4 ng/ml and 1.2 ±0.2 ng/ml, respectively (p=0.002) (Fig. 2D). This points to a glucose/insulin homeostasis dysregulation due to exposure to the diet and OVX. An increase in total serum cholesterol, about five months after starting the diet, was detected in the OVX-Diet mice relative to the control mice: 4.625 ±0.13 nmol/l and 2.54 ±0.09 nmol/l respectively (p<0.0001) (Fig. 2E); LDL also increased, compared to the control mice: 1.58±0.12 nmol/l and 0.692 ±0.06 nmol/l, respectively (p=0.0002) (Fig. 2F). These results suggest lipid homeostasis dysregulation in response to the diet and OVX. Analysis of serum liver enzymes, about six months after starting the diet, showed a significant increase in the levels of the ALT in the OVX-Diet mice relative to the control mice: 460.2±79 pg/ml and 265.7±22 pg/ml, respectively (p=0.033) (Fig. 2G). There was also a tendency to increase in the AST level: 490 ±106 pg/ml and 312± 68 pg/ml, respectively (p=0.24) (Fig. 2H). These results indicate liver function dysregulation in response to the diet and OVX. Indication for cognitive impairment in OVX-mice fed a high fat-sugar-salt diet OVX-Diet mice showed significantly lower performance in the novel object recognition test compared to the control mice: while control mice showed a stronger preference for the novel object, the OVX-Diet mice did not show any preference for it [duration ratio: 0.75±0.05 and 0.49±0.06, respectively, (p=0.006); frequency: 0.69±0.05 and 0.50±0.04, in OVX-Diet mice and control mice, respectively, (0.01)] (Fig. 3A). A trend for impaired cognitive performance was also detected in the Y-maze test when analyzing the direct revisits. More direct revisits (higher index) in the OVX-Diet compared to the control mice (0.038±0.018 and 0.009±0.004, respectively) (p=0.07) was recorded (Fig. 3BI). No difference was noted in the correct triad analysis (Fig. 3BII). Testing whether the OVX-Diet mice show motor deficits, we analyzed the distance moved by the mice in te open field, and also in the arena of the Y maze and the NOR test. No significant difference in distance travelled was noticed between the OVX-Diet mice and the control mice: open field (1985±130.1 vs 1765± 83.36, respectively, t-test, p=0.168), Y-maze (1542 ± 121.8 vs 1335 ±- 155/8, respectively, t-test, p=0.301), and NOR (570.1 ± 51.78 vs 478 ± 37.26, respectively, t-test, p=0.159). Testing for anxiety in the open field test did not indicate increased anxiety in the OVX+diet compared with control mice (time spent in the center of the arena: 25.37 ± 5.52 vs 18.17 ± 4.47, respectively, Mann-Whitney, p=0.31). These results indicate that not only OVX+diet mice did not display increased anxiety, but some opposite effect was noted (which might indicate reduced awareness of the OVX-Diet of the surrounding situation), yet without statistical significance. No difference in wellbeing of the mice was noticed between the OVX-Diet and control groups. Reduced mitochondrial enzymatic activity in the OVX-mice fed a high fat-sugar-salt diet We asked if mitochondrial respiratory chain activity is affected in the OVX-Diet mice. The activity of the COX enzyme in the liver was significantly lower in the OVX-Diet mice than in the control mice (about 54%, p=0.0003), and also the COX/CS ratio was lower than the control (about 45%, p<0.0001). No decrease, and even some non-significant increase (11% relative to control), was noted in the activity of CS, a marker of mitochondrial density. This finding suggests that the decrease in the mitochondrial respiratory chain activity, indicated by COX activity, is not related to a reduced number of mitochondria and may even be associated with a compensatory attempt of the liver to increase the mitochondria number by biogenesis (Fig. 4). Since liver insufficiency may induce brain dysfunction, and since mitochondria impairment is involved in neurodegeneration-related processes, we next tested whether the reduced mitochondrial enzyme activity detected in the liver of the OVX-mice was accompanied with reduced activity in the brain. The activity of the mitochondrial enzymes in the cortex of the OVX-Diet mice showed about 10% reduced COX activity and 8% reduced COX/CS ratio relative to the control mice (not statistically significant, p=0.59 in Mann Whiteny and p=0.57 in t test, respectively; N=13/group). Amyloid, tangle pathology, gliosis, and vascular impairment in the OVX-mice fed a high fat-sugar-salt diet We analyzed the brain sections for the presence of AD-related neurodegenerative features. Staining with the anti- β-amyloid Ab detected intracellular amyloid pathology in the hippocampus of the OVX-Diet mice, while control mice hardly showed staining (p=0.043 and p=0.045 in the CA1 and DG, respectively) (Fig. 5A-C, M-O). No staining was detected with Thioflavin-S (data not shown), indicating that the amyloid accumulated is non-fibrillar and did not reach the mature status of amyloid pathology, as plaques. This points that the OVX-Diet mice develop early stage of intracellular amyloid pathology, which may share some similarity with the amyloid pathology reported in very young 5XFAD tg mice. We also detected tangle pathology in the hippocampus of the OVX-Diet mice relative to the control mice, as presented by staining with the AT8 and AT180 Abs for phosphorylated tau and with the Gallyas staining for neurofibrillary tangles (AT8: p=0.056 in CA1; AT180: p=0.039 and p=0.006 in CA1 and DG, respectively; Gallyas: p=0.0009 and p=0.0008, in CA1 and DG, respectively. Staining was barely detected in control mice) (Fig. 5D-L, P-X). To investigate the occurrence of neuroinflammation features in the brains of the OVX-Diet mice, we stained the hippocampus with Iba-1 and GFAP to detect gliosis. A significantly increased astrocytic burden (GFAP stained cells) was seen in the OVX-Diet mice compared to the control mice (p=0.0009 and p<0.0001 for CA1 and DG, respectively). Additionally, an increased microglial burden (Iba-1 stained cells) was detected in the OVX-Diet mice relative to the control mice (p=0.039 and p<0.0001 for CA1 and DG, respectively). Comparing the RI, a morphometric measure of microglial activation state, revealed a significant increase in microglial activation in the OVX-Diet relative to control mice, presented as decrease in ramification of the microglia (Fig. 6A-I, J-R). Similar amyloid and tangle pathology and gliosis in the OVX-Diet mice compared to control mice were detected in the cortex. (anti-β-amyloid: p<0.0001, AT8: p=0.032, GFAP: p<0.0001, Iba-1: p<0.0001. The differences in Gallyas and in AT180 did not reach a statistical significance (Fig. 5Y-AJ, Fig. 6S-AA). We next asked if there was evidence of vascular damage in the brains of OVX-Diet mice. Staining with lectin for blood vessels revealed a significant decrease in blood vessel density, expressed as a reduced vascular area in the OVX-Diet mice relative to the control mice. This phenomenon was evident in the hippocampus (p=0.0007 in CA1, and p=0.0009 in DG) (Fig. 7A-C, G-I), and in the cortex (p=0.0039) of OVX-Diet mice (Fig. 7M-O). Similar results were obtained when expressing blood vessel density as the number of vessels per area (data not shown). We also stained for VEGF signal for neoangiogenesis, and detected alterations in the OVX-Diet mice as compared to the control mice, in a manner that there was an increase in VEGF area in the OVX-Diet mice, evident in the hippocampus (p=0.072 in CA1, and p=0.017 in DG) (Fig. 7D-F, J-L), and in the cortex (p<0.001) (Fig. 7P-R). | [
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39193143 | methods | Materials and methods Study participants We informed patients about the study through the national registry for myotonic dystrophies.1 The inclusion criteria for the study were: (1) genetically confirmed diagnosis of DM1 or DM2; (2) age between 18 and 65 years; (3) presence of chronic muscle pain defined as persisting or recurring pain for over 3 months. Exclusion criteria were: previous diagnosis of diabetes mellitus, glucose intolerance and/or previously diagnosed polyneuropathy of any cause. In- and exclusion criteria were preliminarily checked during phone calls with the study candidates and were proven on-site by reviewing the medical records. An age- and sex-matched control group of healthy individuals were recruited for comparison. At the first study visit, patients and controls gave their written informed consent to participate. During the 1.5-year recruitment period we aimed to include as many patients as possible, but at least 20 participants per group. For a non-parametric group comparison with a group size ratio of 1.5, a sample size of 15 and 23 per group was estimated to be sufficient to detect a standardized mean difference of 1 (assuming an alpha-level of 5% and a power of 80%). Based on the published QST-reference values one standardized mean difference represents a clinically relevant difference for all QST parameters. Study protocol The study was conducted in accordance with the declaration of Helsinki and the local ethics committee approved the study protocol (LMU project no. 19/499). The study design consisted of (1) collection of demographic and disease-related data (diagnosis, body mass index, age at onset, disease duration, present neuromuscular complaints, multisystemic involvement, current pain medication); (2) completion of pain questionnaires [brief pain inventory (BPI), pain-DETECT and pain disability index (PDI)]; (3) neurological examination (including muscle impairment rating scale (MIRS) for DM1 patients); (4) quantitative sensory testing (QST); (5) nerve conduction studies (NCS) and (6) skin biopsies quantifying IENFD. If patients were taking painkillers, such as non-steroidal anti-inflammatory drugs (NSAIDs) or muscle relaxants (e.g., methocarbamol) on demand, they were asked to pause these medications two days before their study visit. Patients regularly taking pain-modulating drugs (e.g., amitriptyline, duloxetine) were allowed to continue the therapy at the usual dosage. Pain questionnaires The pain questionnaires were chosen considering the recommendations of the German Research Network for Neuropathic Pain (Deutscher Forschungsverbund Neuropathischer Schmerz—DFNS) and their previous use in studies investigating pain in myotonic dystrophies. The BPI assesses pain severity and interference in several activities within the last 24 h. It also depicts most painful body regions, describes the use of pain medications and indicates the percentage of pain relief obtained. The pain-DETECT screening questionnaire estimates the likelihood that patients have a neuropathic pain component. The final score ranges from 0 to 38. If the score is below 13, the neuropathic component is unlikely (<15% likelihood), between 13 and 18 it is uncertain and above 18 it is very likely (>90%). The PDI measures the pain’s impact on the patient’s ability to participate in seven relevant life activities (e.g. occupation, self-care, recreation) on a scale from 0 to 10. Accordingly, the PDI sum-score ranges from 0 to 70, with higher scores indicating greater pain related disability. Quantitative sensory testing Quantitative sensory testing (QST) followed the test battery standardized and validated by the DFNS. QST is a psychophysical examination used to explore the somatosensory function and the presence of hyperalgesia and/or allodynia. It encompasses 13 sensory parameters, including mechanical and thermal detection and pain thresholds. All investigators received specific training and certification by the DFNS to perform and interpret QST. The same investigator (VS) performed all QST assessments in recruited patients and healthy controls. The QST was performed at the dorsum of the right hand and at the right thigh in DM patients and at the right thigh in healthy controls. The hand dorsum was chosen as a pain-free region for which the DFNS provides reference data stratified by age and gender. The thigh region was selected as it represents the most painful region in DM patients. Herein, we report a summarized version of the QST protocol validated by the DFNS. For thermal testing, we used a thermal sensory analyzer (TSA 2001-II, Medoc Ltd. Advanced Medical Systems, Ramat Yishai, Israel). Cold and warm detection thresholds (CDT and WDT), thermal sensory limen (TSL), cold and heat pain thresholds (CPT, HPT), as well as the number of paradoxical heat sensations (PHS) were assessed. The mechanical detection threshold (MDT) was evaluated with a set of von Frey filaments (OptiHair2, MRC systems GmbH, Heidelberg, Germany). The mechanical pain threshold (MPT), the mechanical pain sensitivity (MPS) and the wind-up ratio (WUR) were determined by using a set of pinprick stimulators (PinPrick Stimulator Set, MRC Systems GmbH, Heidelberg Germany). Furthermore, dynamic mechanical allodynia (DMA) was assessed by stroking with a Q-tip, cotton wool and a paint brush also included in the MRC stimulator set. The vibration detection threshold (VDT) was examined with a Rydel-Seiffer tuning fork (64 Hz, x/8 scale; Arno Barthelmes, Tuttlingen, Germany). The pressure pain threshold was assessed by a pressure algometer with a rubber tip of 1 cm2 (FPK20, Wagner Instruments, Greenwich, CT, United States). Nerve conduction studies Nerve conduction studies (NCS) were performed to rule out the presence of large fiber polyneuropathy. This examination was done after the QST to avoid any impact caused by the discomfort related to the NCS. The following nerves were examined in all patients (DM1, DM2) and controls on the right side: ulnar motor nerve, peroneal motor nerve, sensory radial nerve and sural nerve. For the classification of abnormal NCS, the reference values of our neurophysiology laboratory were adopted. Intraepidermal nerve fiber density evaluated by skin biopsies To assess the intraepidermal nerve fiber density (IENFD), two 3 mm diameter skin punch biopsies were taken 10 cm above the lateral malleolus (distal biopsy) and 20 cm below the iliac spine (proximal biopsy). The skin samples were fixed with Zamboni fixative, washed in PBS, transferred to 10% sucrose and stored at −80°C freezer until use. From each biopsy, 50 μm thick frozen sections were stained using a free-floating protocol with primary antibody anti-protein gene product (PGP 9.5, 1:1,000, Zytomed) and secondary antibody goat anti-rabbit Alexa Fluor 488 (1:1,000, Thermo Fisher Scientific). Four sections were mounted with DAPI Fluorshield (Abcam) and were examined using an Olympus IX83 inverted microscope equipped with a UPLSAPO400XO/1.4 objective and a DP 74 digital camera (Olympus, Tokyo, Japan). Image analysis was performed using cell Sens Dimension software (Olympus). During the morphologic analysis, the investigator (FM) was blinded to the patient’s diagnosis (DM1 or DM2). The IENFD was quantified using standardized guidelines and age- and sex-adjusted normative values. The proximal/distal IENFD ratio was calculated to evaluate the pattern of small fibers reduction. A ratio < 1 was considered a proximal reduction, > 2.5 a distal reduction. Statistical analysis The data were analyzed with SPSS Statistics (Version 27.0, IBM, Armonk, NY) and R (version 4.2.3, R Core Team, 2022). The normality of variables was assessed by the Shapiro–Wilk test. As most continuous variables were non-normally distributed, descriptive statistics are displayed as medians and interquartile ranges (IQR). Categorical variables are reported as absolute and relative frequencies. Comparisons of continuous and ordinal variables between the three study groups were performed by applying the Kruskal-Wallis-test (KW-test) with Dunn’s post-hoc test adopting Bonferroni adjustment for pairwise comparisons. Group comparisons of data that were only collected in DM1 and DM2 patients were performed by the Mann–Whitney U test. Comparisons of nominal and dichotomous data were performed by Chi2 or Fisher-test, respectively. Correlations between outcome measures were evaluated by Spearman correlation. p-values < 0.05 were considered significant. According to DFNS reference data in healthy volunteers, all QST parameters are either normally distributed (CPT, HPT, VDT) or normally distributed in log-space (CDT, WDT, TSL, MDT, MPT, MPS, WUR, PPT, PHS, DMA). This was indeed the case for our healthy control group. However, QST parameters in DM1 and DM2 patients showed skewed distributions. Therefore, the sensory profiles of DM1 and DM2 patients are illustrated as boxplots of the patients’ z-scores, and non-parametric tests as stated above were used for inferential statistics. Z-Scores were calculated by the following formula: Z-scores below zero indicate a loss of function; z-scores above zero indicate a gain of function. Z-scores for QST-data at the thighs were calculated based on data established in the age- and gender-matched healthy control group. Z-Scores for QST-data at the dorsum of the hand were calculated compared to DFNS reference data as described by Magerl et al.. Magerl et al. suggest performing a statistical comparison with the DFNS reference data by computing the t-test statistic from the z-scores of the study sample and an ideal normal distribution with mean 0 and SD 1. Given the skewed distribution in our patient samples, we applied a corresponding non-parametric test strategy. 100 random samples from a normal distribution with mean 0 and SD 1 were compared to z-scores of our samples by applying the KW- and Dunn’s post-hoc tests. The 100th root of the product of the 100 p-values is reported as an approximation for the p-value of a comparison with an ideal normal distribution. Sensitivity analyses for all outcome comparisons with adjustment for either age and gender or BMI and gender were carried out by applying generalized linear models with either an identity (continuous outcomes), a logit (dichotomous outcomes), or a cumlogit (categorical outcomes with more than two categories) link function. Age and BMI were not included in the same model, as this would have caused collinearity (Spearman correlation coefficient (rS) age ~ BMI 0.355 p < 0.001). | [
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38298786 | methods | Methods and Materials Participants Magnetic resonance imaging (MRI) data were acquired in the context of an ongoing clinical trial called PACt-MD (Prevention of Alzheimer’s Dementia With Cognitive Remediation Plus Transcranial Direct Current Stimulation in Mild Cognitive Impairment and Depression), which was approved by the Centre for Addiction and Mental Health Research Ethics Board (ClinicalTrials.gov Identifier: NCT02386670). Of 387 participants, 321 completed an MRI, and 244 were included in this analysis (Figure 1). The methods and sample of PACt-MD have been described in detail previously. Briefly, all participants provided written informed consent and underwent a comprehensive baseline assessment, including cognitive testing. All data presented here, including the MRI data, are from the baseline assessments at the start of the clinical trial and thus represent cross-sectional comparisons among groups. The cognitive battery included the tests that are described herein. To assess working memory, an inverse efficiency measure (reaction time/accuracy) was derived from 2- and 3-back versions of the n-back task. Sustained attention was assessed with d prime scores from the continuous performance task. In addition, z scores were calculated from the total number of correct items on the Paced Auditory Serial Addition Test, which captures participants’ speed, ability to process auditory information, and capacity for calculation. The number of errors subtracted from the total number of completed items on the Digit Symbol Substitution Test (coding) was used to measure participants’ associative learning. Attention and task switching were measured by the Trail Making Test, where the ratio of Trails B/A scores was taken into account. The color/word switching task (Stroop) produced corrected accuracy, which was then z scored to assess selective attention, processing speed, and inhibitory control. The Performance Assessment of Self-Care Skills was used to measure overall functional status as indicated by the total number of correct items from the shopping task. The semantic, or category, test (fluency) used the total number of correct items to indicate vocabulary size, lexical access, and speed of processing. Performance on the Brief Visuospatial Memory Test, which assessed visuospatial learning and memory, was judged by summing raw scores from trials 1 to 3. Similarly, for the California Verbal Learning Test, raw free recall scores across trials 1 to 5 were summed for an assessment of verbal learning and memory. Lexical retrieval abilities were measured using the total number of correct items on the Boston Naming Test. Finally, overall executive and visuospatial functioning was evaluated using the total score on the clock task. Baseline diagnoses were established in a clinical consensus conference in which the results of the cognitive testing and all other available information were considered. The participants who were included in this analysis consisted of 44 participants 65 years and older with rMDD, 61 participants 65 years and older with rMDD+MCI, and 115 participants 60 years and older with MCI. In this analysis, we further divided the MCI group into aMCI and naMCI groups, defining aMCI as MCI with impairment in memory on the Brief Visuospatial Memory Test or California Verbal Learning Test. In addition, PACt-MD recruited an HC comparator group of older adults without a history of psychiatric disorders or cognitive impairment; 24 control participants with usable MRI data were included in this analysis. Characteristics of the 244 participants included in the analysis are presented in Table 1. MRI Acquisition As described previously, participants from the PACt-MD study were all scanned on the same 3T GE Echospeed (General Electric) research-dedicated scanner at the Centre for Addiction and Mental Health. Whole-brain DWI including 30 gradient directions with b = 1000 s/mm2, 33 gradient directions with b = 3000 s/mm2, and 5 baseline scans with b = 0 s/mm2 was performed using an echo-planar imaging sequence with a dual spin-echo option to reduce eddy current–related distortions (echo time [TEb1000/b3000] = 110 ms, repetition time [TRb1000] = 1100 ms, [TRb3000] = 1200 ms; field of view = 25.6 cm; 128 × 128 matrix; 2.0 mm isotropic voxels; no gap; 81 slices). Axial slices were acquired parallel to the anterior commissure–posterior commissure line covering the whole brain. T1-weighted MRIs were acquired as sagittal 3-dimensional fast spoiled gradient-echo images (TE = 3 ms; TR = 6.7 ms; inversion time = 650 ms; flip angle 8°, field of view = 24 cm; number of excitations = 1, with 0.9 mm isotropic voxels, no gap, 81 slices). To correct for susceptibility-induced distortions, we also acquired 2 magnitude images with TE = 6.5 ms and TE = 8.5 ms, TR = 1000 ms, and field of view = 22 cm using an interleaved slice order, 64 × 64 matrix from which we estimated participant-specific field maps. Image Preprocessing and Analysis Diffusion-weighted b1000 and b3000 runs, along with the b0 runs, were concatenated and denoised with the MRtrix3 dwidenoise command (see Figure 2 for an overview of preprocessing steps). b0 images were used for brain extraction using the brain extraction toolbox from the FMRIB Software Library (FSL version 5.0.10). Next, we corrected the DWI data for motion, eddy current–induced and susceptibility-induced distortions, and artifacts using an acquired field map in a single step using EDDY (FSL version 5.0.10). NODDI measures were estimated using the microstructure diffusion toolbox. The measures of interest were the NDI, ODI, and fISO. We also used FSL’s dtifit algorithm to estimate fractional anisotropy to estimate the pseudo-T1 images. Gray Matter–Based Spatial Statistics We used the gray matter–based spatial statistics to estimate gray matter cortical skeletons minimizing partial voluming from white matter and extraparenchymal cerebrospinal fluid into core gray matter. This approach also avoids applying a Gaussian blur across anatomical boundaries. Pseudo-T1 images were estimated in a 3-step process outlined in Nazeri et al.. Briefly, we derived a gray matter probability map for each participant by generating a binary whole-brain mask and subtracting regions of likely cerebrospinal fluid (derived from the NODDI fISO map) and white matter (derived from a 2-tissue class segmentation of fractional anisotropy using Atropos). Tissue contrasts were enhanced by multiplying fISO maps by 0, gray matter by 1, and white matter by 2. These images were summed and used to generate a study-specific template using the buildtemplateparallel.sh script from the Advanced Normalization Tools toolbox. Nonlinear transforms from the previous step moved participant-specific estimates of gray matter and NODDI derivatives into template space. We used a skeletonization algorithm on the averaged gray matter map from all participants to achieve a consistent gray matter representation. This algorithm preserves only the local maxima perpendicular to the white matter tracts. Each participant-specific diffusion measure was projected onto this skeleton following tract-based spatial statistics. The procedure and scripts used can be found at https://github.com/arash-n/GBSS. We visually checked the corrected 4-dimensional diffusion volume and verified the success of the brain extraction. We also examined the color-encoded maps of the primary eigenvector (V1) and, finally, residuals from the tensor fit (i.e., sum-of-squared-error maps) to ensure that no imaging artifacts remained following correction. Statistical Analysis Data were analyzed with behavioral partial least squares (PLS) using the MATLAB (version 2021b; The MathWorks, Inc.) implementation distributed by the Rotman Research Institute. PLS is a multivariate approach similar to principal component analysis (PCA). Whereas PCA is an unsupervised method that decomposes variables into a set of components ranked from the highest to the least amount of explained variance, behavioral PLS attempts to maximize the explained variance in the Y matrix (behavior) in relation to the X matrix (brain data). Here, age was the behavioral variable [see, e.g., Figure 4 in ]. See the Supplement for additional details on the PLS method. Before entering NODDI maps into PLS, each was residualized using the fsl_glm command (FSL version 5.0.10). Nuisance variables included sex, number of years of education, and the first principal component of a PCA using quality control estimates (e.g., residual noise, average contrast-to-noise ratio, average signal-to-noise ratio, percent outliers, relative motion, and absolute motion) from eddyqc Quality Assessment for DMRI and MRtrix. Residual noise, motion, and percent outliers loaded positively on the component score, while average signal-to-noise ratio and contrast-to-noise ratio loaded negatively, suggesting that the component tracked overall scan quality. Age was a covariate of interest and was entered directly into the behavioral PLS model. To analyze differences among our groups (HC, MDD, aMCI, naMCI, MDD+aMCI, MDD+naMCI) in behavioral PLS results, we used bootstrap replicates for brain-behavior correlations, subtracted them for each pairwise comparison, and fit a 95% CI to the resulting distribution. Groups with 95% confidence bounds excluding 0 were deemed significantly different (see embedded tables in Figures 4 and 5). We also included Cohen’s d estimates, computed from the bootstrap replicates, in the figures for easier interpretation of the importance of group differences. Three behavioral PLS analyses were run with age as a predictor. The first analysis incorporated all 3 modalities (NDI, fISO, and ODI) to see how they varied by age. The second analysis explored whether the relationship between fISO and age differed by diagnosis. The third analysis replicated this approach of exploring the relationship between a brain measure and age by diagnosis, but with ODI as the outcome measure for the brain. The first analysis showed that NDI did not vary with age, and therefore, we did not do a separate analysis for this modality. To mitigate effects of multicollinearity and multiple comparisons, we applied PCA to reduce dimensions of 12 cognitive scores. We used the MICE package in R (https://cran.r-project.org) for estimating missing behavioral data with chained equations before dimension reduction. The Paced Auditory Serial Addition Test had the highest missingness, at 17%, followed by the 3-back at 14%. Results remained consistent when these variables were excluded; therefore, we have presented the complete set of results. All other variables had <10% missing values across participants. | [
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37236657 | results | Results The participant sample had a mean age of 51.20 years (SD=5.44), and 61.65% of the participants were female. Baseline participant characteristics are presented in table 1. Pairwise correlations A pairwise correlation with Bonferroni correction was conducted and showed few significant associations between the cognitive variables of interest (outcome variables) and predictor/mediator variables (insulin resistance and depression). The full correlation table output is presented in online supplemental materials S1 but to be noted are the significant associations between insulin resistance and semantic verbal fluency (r=−0.18, p<0.01), between insulin resistance and sex (r=0.16, p<0.01) where females were coded as zero and between insulin resistance and depression (r=0.15, p<0.01). Structural equation model SEM measurement regression paths A direct path was extended from insulin resistance to each of the individual cognitive variables and the executive function latent construct. A direct path was also extended from depression to each of the cognitive variables and to the executive function latent construct to assess the relationship between depression and these variables. To assess mediation by depression on the relationship between insulin resistance and cognition, a direct path was also inserted between insulin resistance and depression (figure 1). SEM results The full SEM output is presented in online supplemental materials S2, where the beta values are presented as standardised values. The results showed that higher insulin resistance values significantly predicted lower executive function performance (b=−0.12, p<0.01), and higher insulin resistance predicted increased depressive scores (b=0.15, p<0.001) (see figure 2). Insulin resistance was not associated with performance in any other cognitive tasks or ISD, but increased depressive scores predicted poorer performance on the 4 Mountains Test (b=0.14, p<0.01). The model was repeated by age group (age 40–49 vs age 50–60); for the older age group, the relationship between lower insulin resistance and executive function remained significant (b=−0.15, p<0.01), but for the younger age group, this relationship was non-significant (b=−0.09, p=0.126). For both age groups, higher insulin resistance predicted increased depressive scores (p<0.01), whereas higher depressive scores predicted poorer performance in the 4 Mountains Test (p<0.05) for only the older age group. Goodness-of-fit measures for the initial full group model were deemed good by field standards: root mean squared error of approximation (RMSEA)=0.02, Comparative Fit Index (CFI)=0.983, Tucker Lewis Index (TLI)=0.925, χ2=15.80, p=0.148. RMSEA is a metric of the differences between the predicted outcomes of the model and the observed values in the data. CFI is a metric of the improvement in a model’s fit going from the baseline model to the proposed model, which is less sensitive to differences in sample sizes. TLI is a measure of the relative reduction in misfit per additional degree of freedom in the model. | [
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|
37643838 | abstract | []
|
|
39237554 | methods | Methods Participants Thirty-one individuals with the FMR1 premutation (21M, 10F) completed a
five-minute monologue as an optional component of a larger study at the University
of California-Davis (PI: Hagerman) that included cognitive, neuropsychological, and
medical assessments, genetic counseling, and collection of biological samples.
Participants ranged in age from 58 to 85 years. All participants self-reported
their race as White. Most participants (90.9%) had completed some college. Inclusion
criteria for the larger study included the presence of the FMR1 premutation and
neurological symptoms. One participant from the larger study had a stroke in the
past without lasting cognitive deficits. Three participants exhibited some dementia
symptoms; however, because these symptoms are part of the cognitive profile
associated with FXTAS, we did not eliminate these participants from the study.
Exclusion criteria consisted of the presence of other life-threatening diseases that
affect central nervous system function (e.g., Alzheimer’s dementia). Only participants who had symptoms of FXTAS were included in the study. Symptoms
of FXTAS were evaluated by the UC-Davis team of neurologists and clinicians, who
rated FXTAS symptoms (based on clinical description) on a scale of 0 (no symptoms)
to 5 (definite and severe FXTAS symptoms); participants who met at least stage 2
were included. Participants’ FXTAS status was characterized as possible
(22.6%), probable (32.3%), and definite (45.2%). Criteria are defined elsewhere and
include clinical description of movement and gait problems, and the extent to which
symptoms interfered with daily life. For additional description of these criteria,
see Bacalman et al., 2006 and Jacquemont et al., 2003. All participants provided DNA samples to determine FMR1 CGG repeats and confirm
premutation status, as previously described. For females, the long CGG allele (i.e.,
the premutation allele) was selected for genetic analyses to examine potential
differences from males (who have only one X chromosome). Increasing CGG length may
be associated with earlier onset and more severe FXTAS motor symptoms and was
examined as a potential covariate. However, no associations between CGG and language
variables was observed (r-values < 0.44,
p-values > 0.470). See Table 1 for sample
characteristics. Participants were recruited from fragile X clinics, the National
Fragile X Foundation, and word of mouth. Study procedures were IRB-approved, and all
participants completed informed consent (IRB 254134-27). All experimental procedures
were performed in accordance with relevant guidelines and regulations. Language sample elicitation Participants completed a monologic language sample, as has been described
previously. All monologues were video and/or audio recorded for offline
transcription. Video files were transcribed using the Systematic Analysis of
Language Transcripts (SALT) at UW-Madison; if unavailable, audio files were used.
All transcripts were completed by trained student transcribers who achieved 80% or
greater on a minimum of three transcripts in a row with an expert in SALT. Two
primary transcribers completed the original transcripts, and two additional
transcribers verified each file. Utterances were segmented into C-Units, which
reflects an independent clause and its modifiers. Reliability was completed at the
utterance and word level for 20% of transcripts. Utterance reliability was 86% and
word-level reliability was 88%. Participant speaking time ranged from 180 to 300 s
(M = 275 s). All transcripts were assessed for the following linguistic categories using
SALT’s report function, derived from the analysis set (i.e., total
complete and intelligible utterances): lexical diversity, semantic productivity,
dysfluencies, and syntactic complexity. Speech rate was calculated in words per
minute by dividing the total number of words by the time spent speaking (in
seconds), multiplied by 60. Lexical diversity indicates the number of different
words. Semantic productivity reflects the noun and verb rate per utterance.
Dysfluencies refer to the rate per utterance of fillers (e.g.,
“uh,” “um”), revisions
(“[the dog] the cat”), and repetitions (“[the]
the cat”). Syntactic complexity reflects the mean length of utterance
(MLU) in morphemes. These linguistic categories have been shown to be sensitive
markers of age-related cognitive decline among neurodegenerative conditions such as
Alzheimer’s disease and Parkinson’s. Cognitive functioning Cognitive functioning was evaluated using the mini mental state examination
(MMSE). The MMSE assesses cognitive function in individuals 18–85.
Participants respond to questions concerning orientation, registration, attention,
calculation, and language. It yields a total possible score of 30, with higher
scores indicative of better cognitive functioning. Executive functioning was assessed with the Behavioral Dyscontrol Scale-2nd
Edition (BDS-2). The BDS-2 is a nine-item measure that evaluates motor behaviors
requiring executive functioning. It includes tasks of working memory, motor
learning, and behavioral inhibition, with strong reliability and validity. It yields
a total possible score of 27, with higher scores indicative of better executive
functioning. Statistical analysis Data analyses were conducted using IBM SPSS Statistics version 28. All language
variables met assumptions for normality
(p-values > 0.089) except for MLU
(p = 0.008). MLU was log transformed to normalize the
variable (see Table 2). Independent t-tests were completed to examine potential differences in sample
characteristics between males and females. Males and females were matched on
chronological age and education (p-values > 0.705;
variance ratios < 0.238). Age was associated with
language variables (rs <|.384|,
ps < 0.044) and was controlled in analyses. Education was
not associated with language variables (rs <|.307|,
ps > 0.165). Males and females did not significantly
differ in FMR1 CGG repeat length (long allele; p = 0.130),
FXTAS symptom severity (p = 0.453), MMSE total score
(p = 0.211), or BDS-2 total score
(p = 0.221). Pearson Chi-square tests were used to examine
rates of definite or probable FXTAS diagnoses between males and females, and
indicated no significant differences χ2 = 0.59,
p = 0.445; 66.7% M vs 80% F. Relationships were observed between language variables in males and females (see
Table 3), and subsequent analyses of group differences (research question 1) were
completed using univariate analyses of covariance, controlling for chronological
age. For research question 2, we conducted multivariable ordinal logistic
regressions to assess whether language variables were predictive of FXTAS symptom
severity. We conducted multivariable ordinary least squares regressions to assess
the extent to which language variables predicted cognitive- (MMSE scores) and
executive functioning (BDS-2 scores). In each regression model, we included sex and
age as covariates. Regression diagnostics were completed using Cook’s D
based on the criteria
D > 4 = (1-k-n) and no outliers
were observed (D-values < 0.14). | [
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|
39150412 | abstract | During the last decade, there has been a move towards consumer-centric hearing healthcare. This is a direct result of technological advancements (e.g., merger of consumer grade hearing aids with consumer grade earphones creating a wide range of hearing devices) as well as policy changes (e.g., the U.S. Food and Drug Administration creating a new over-the-counter [OTC] hearing aid category). In addition to various direct-to-consumer (DTC) hearing devices available on the market, there are also several validated tools for the self-assessment of auditory function and the detection of ear disease, as well as tools for education about hearing loss, hearing devices, and communication strategies. Further, all can be made easily available to a wide range of people. This perspective provides a framework and identifies tools to improve and maintain optimal auditory wellness across the adult life course. A broadly available and accessible set of tools that can be made available on a digital platform to aid adults in the assessment and as needed, the improvement, of auditory wellness is discussed. | [
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|
38071284 | intro | Background Neurodegenerative disorders like dementia are on the rise in sub–Saharan Africa due to increased longevity leading to an increase in the numbers of older people. In response, memory clinics have been established in some parts of sub-Saharan Africa to identify, investigate, and treat cognitive disorders such as dementia. There are few studies that have described these cohort of patients, and none that we are aware of that have reported out-patient longitudinal data. Memory clinic or hospital-based studies on people living with dementia in Africa have usually been small or have had a cross-sectional design. Kalula et al.described a cohort of patients seen regardless of age in a memory clinic in Cape Town, South Africa. Within a period of five years, 305 people were seen of whom 74% had dementia. Of these 44% had Major Neurocognitive Disorder due to Alzheimer’s disease (AD), 28% Major Vascular Neurocognitive Disorder (VND), and 15% mixed Alzheimer’s and vascular dementia. Thirteen percent had other forms of dementia, namely Dementia with Lewy bodies (DLB), Parkinson disease-associated dementia (PDD), fronto-temporal dementia (FTD), HIV-associated dementia, alcohol-related dementia, history of previous head injury and undetermined forms. In this study, however, dementia diagnoses were based on clinicians’ impressions rather than standardized diagnostic criteria. In 2011 a Nigerian hospital-based study profiled dementia phenotypes of 108 patients who were inpatients over a 10-year period. Of these 57.4% were diagnosed with AD, 16.7% VND, 3.7% mixed dementia, 3.7% FTD, 2.8% DLB, 2.8% alcohol related dementia, 0.9% PDD and undetermined subtypes 12%. None of the memory clinic studies we reviewed that were conducted in Africa reported rates of cognitive decline or mortality data. Mini-mental state examination (MMSE) scores have been used to determine cognitive decline in studies conducted in Western and Asian memory clinics. A retrospective chart review of a cohort of people seen in two University Alzheimer’s Disease centres in the USA showed an average annual MMSE decline of 3.2 points in AD and 4.7 points in FTD. A mainly European multi-centre study found mean annual MMSE score declines of 2.1 points with DLB, 1.6 points for AD and 1.8 points for PDD. A memory clinic study in the Republic of Korea comparing AD, VND and PDD subtypes showed more rapid decline in patients with AD compared with the others. Factors like age of symptom onset, level of education, and cardiovascular risk factors have also been shown to predict rates of decline. Gerritsen et al. showed that neuropsychiatric symptoms were associated with higher rates of cognitive decline. Dementia subtypes and rates of cognitive decline appear to influence survival outcomes in dementia. Slower rates of cognitive decline and longer survival have been shown in Alzheimer’s dementia compared with DLB and FTD. A Californian study, where type of dementia was confirmed by autopsy, found a survival from time of diagnosis of 4.2 years for FTD compared to 6 years for AD. In this cohort, FTD had a higher cognitive decline of mean annual rate of 6.7 points compared to AD with 2.3 points. A study of people seen in memory clinics in Sweden with a mean follow-up of 2.5 years found that low baseline MMSE, male gender, higher number of medications, institutionalization, and age were associated with increased mortality after dementia diagnosis. A retrospective study carried out in three Italian dementia out-patient clinics found age, gender and functional status to be the main determinants of patient survival. An Australian study with participants from nine memory clinics found that 57.4% of 779 patients with dementia had died within eight years. In this study, greater deterioration in dementia severity and functional impairment over time predicted mortality independent of baseline levels. A study in specialised outpatients’ dementia clinics in Spain found AD to have the best survival while subtypes like Parkinson-Plus Syndromes and dementia due to multiple aetiologies sub-types had the worst prognosis. A Dutch study carried out among patients with young onset dementia in specialised centres found AD to have a worse survival compared with VND subtype. The same study found a trend of decreased survival for the participants with AD compared with FTD. There are, to our knowledge, no published longitudinal studies of patients with dementia from memory clinics in sub-Saharan Africa that have characterized the subtypes, cognitive decline, survival outcomes and predictors of survival. Dementia subtypes have distinctive natural histories. A precise diagnosis may lead to a better understanding of prognosis. Data regarding rates of cognitive decline and survival of the different dementia subtypes have also largely been derived from populations in the developed world. Accurate clinical diagnosis is especially important in resource poor settings where expensive investigations are not readily available. With the future advent of potential specific drug therapies, an accurate diagnosis as well as a knowledge of probable survival outcomes of dementia subtypes may be useful. A knowledge of the characteristics of patients seen in memory clinics and their longitudinal trajectories can also be used to further develop these clinics and services of older people with dementia. The aim of this study, using data collected on older adults who attended the memory clinic at Groote Schuur Hospital in Cape Town, was to determine the proportions of the different dementia subtypes, the rates of cognitive decline, trajectories of decline of the different dementia sub-types, and to determine whether their correlations exist between dementia subtypes and survival rates. | [
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|
39309765 | title | Interactions of memantine and rivastigmine with graphene oxide nanocarrier and beta-amyloid protein using molecular docking and in-silico methods | []
|
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