The subcommissural organ regulates brain development via secreted peptides.

The subcommissural organ (SCO) is a gland located at the entrance of the aqueduct of Sylvius in the brain. It exists in species as distantly related as amphioxus and humans, but its function is largely unknown. Here, to explore its function, we compared transcriptomes of SCO and non-SCO brain regions and found three genes, Sspo, Car3 and Spdef, that are highly expressed in the SCO. Mouse strains expressing Cre recombinase from endogenous promoter/enhancer elements of these genes were used to genetically ablate SCO cells during embryonic development, resulting in severe hydrocephalus and defects in neuronal migration and development of neuronal axons and dendrites. Unbiased peptidomic analysis revealed enrichment of three SCO-derived peptides, namely, thymosin beta 4, thymosin beta 10 and NP24, and their reintroduction into SCO-ablated brain ventricles substantially rescued developmental defects. Together, these data identify a critical role for the SCO in brain development.

The subcommissural organ regulates brain development via secreted peptides.

The subcommissural organ (SCO) is a gland located at the entrance of the aqueduct of Sylvius in the brain. It exists in species as distantly related as amphioxus and humans, but its function is largely unknown. To explore its function, we compared transcriptomes of SCO and non-SCO brain regions and found three genes, Sspo, Car3, and Spdef, that are highly expressed in the SCO. Mouse strains expressing Cre recombinase from endogenous promoter/enhancer elements of these genes were used to genetically ablate SCO cells during embryonic development, resulting in severe hydrocephalus and defects in neuronal migration and development of neuronal axons and dendrites. Unbiased peptidomic analysis revealed enrichment of three SCO-derived peptides, namely thymosin beta 4, thymosin beta 10, and NP24, and their reintroduction into SCO-ablated brain ventricles substantially rescued developmental defects. Together, these data identify a critical role for the SCO in brain development.

Diagnostic value of isolated plasma biomarkers and its combination in neurodegenerative dementias: A multicenter cohort study.

BACKGROUND: Plasma amyloid-ß (Aß), phosphorylated tau-181 (p-tau181), neurofilament light (NfL) and glial fibrillary acidic protein (GFAP) potentially aid in the diagnosis of neurodegenerative dementias. We aim to conduct a comprehensive comparison between different biomarkers and their combination, which is lacking, in a multicenter Chinese dementia cohort consisting of Alzheimer's disease (AD), frontotemporal dementia (FTD), and progressive supranuclear palsy (PSP). METHODS: We enrolled 92 demented patients [64 AD, 16 FTD, and 12 PSP with dementia] and 20 healthy controls (HC). Their plasma Αß, p-tau181, NfL, and GFAP were detected by highly sensitive-single molecule immunoassays. Αß pathology in patients was measured by cerebrospinal fluid or/and amyloid positron emission tomography. RESULTS: All plasma biomarkers tested were significantly altered in dementia patients compared with HC, especially Aß42/Aß40 and NfL showed significant performance in distinguishing AD from HC. A combination of plasma Aß42/Aß40, p-tau181, NfL, and GFAP could discriminate FTD or PSP well from HC and was able to distinguish AD and non-AD (FTD/PSP). CONCLUSIONS: Our results confirmed the diagnostic performance of individual plasma biomarkers Aß42/Aß40, p-tau181, NfL, and GFAP in Chinese dementia patients and noted that a combination of these biomarkers may be more accurate in identifying FTD/PSP patients and distinguishing AD from non-AD dementia.

How well do neural signatures of resting-state EEG detect consciousness? A large-scale clinical study.

The assessment of consciousness states, especially distinguishing minimally conscious states (MCS) from unresponsive wakefulness states (UWS), constitutes a pivotal role in clinical therapies. Despite that numerous neural signatures of consciousness have been proposed, the effectiveness and reliability of such signatures for clinical consciousness assessment still remains an intense debate. Through a comprehensive review of the literature, inconsistent findings are observed about the effectiveness of diverse neural signatures. Notably, the majority of existing studies have evaluated neural signatures on a limited number of subjects (usually below 30), which may result in uncertain conclusions due to small data bias. This study presents a systematic evaluation of neural signatures with large-scale clinical resting-state electroencephalography (EEG) signals containing 99 UWS, 129 MCS, 36 emergence from the minimally conscious state, and 32 healthy subjects (296 total) collected over 3 years. A total of 380 EEG-based metrics for consciousness detection, including spectrum features, nonlinear measures, functional connectivity, and graph-based measures, are summarized and evaluated. To further mitigate the effect of data bias, the evaluation is performed with bootstrap sampling so that reliable measures can be obtained. The results of this study suggest that relative power in alpha and delta serve as dependable indicators of consciousness. With the MCS group, there is a notable increase in the phase lag index-related connectivity measures and enhanced functional connectivity between brain regions in comparison to the UWS group. A combination of features enables the development of an automatic detector of conscious states.

DiffMDD: A Diffusion-Based Deep Learning Framework for MDD Diagnosis Using EEG.

Major Depression Disorder (MDD) is a common yet destructive mental disorder that affects millions of people worldwide. Making early and accurate diagnosis of it is very meaningful. Recently, EEG, a non-invasive technique of recording spontaneous electrical activity of brains, has been widely used for MDD diagnosis. However, there are still some challenges in data quality and data size of EEG: (1) A large amount of noise is inevitable during EEG collection, making it difficult to extract discriminative features from raw EEG; (2) It is difficult to recruit a large number of subjects to collect sufficient and diverse data for model training. Both of the challenges cause the overfitting problem, especially for deep learning methods. In this paper, we propose DiffMDD, a diffusion-based deep learning framework for MDD diagnosis using EEG. Specifically, we extract more noise-irrelevant features to improve the model's robustness by designing the Forward Diffusion Noisy Training Module. Then we increase the size and diversity of data to help the model learn more generalized features by designing the Reverse Diffusion Data Augmentation Module. Finally, we re-train the classifier on the augmented dataset for MDD diagnosis. We conducted comprehensive experiments to test the overall performance and each module's effectiveness. The framework was validated on two public MDD diagnosis datasets, achieving the state-of-the-art performance.

Acoustic-electric trigeminal-nerve stimulation enhances functional connectivity in patients with disorders of consciousness.

AIM: Disruption of functional brain connectivity is thought to underlie disorders of consciousness (DOC) and recovery of impaired connectivity is suggested as an indicator of consciousness restoration. We recently found that rhythmic acoustic-electric trigeminal-nerve stimulation (i.e., musical stimulation synchronized to electrical stimulation of the trigeminal nerve) in the gamma band can improve consciousness in patients with DOC. Here, we investigated whether these beneficial stimulation effects are mediated by alterations in functional connectivity. METHODS: Sixty-three patients with DOC underwent 5 days of gamma, beta, or sham acoustic-electric trigeminal-nerve stimulation. Resting-state electroencephalography was measured before and after the stimulation and functional connectivity was assessed using phase-lag index (PLI). RESULTS: We found that gamma stimulation induces an increase in gamma-band PLI. Further characterization revealed that the enhancing effect is (i) specific to the gamma band (as we observed no comparable change in beta-band PLI and no effect of beta-band acoustic-electric stimulation or sham stimulation), (ii) widely spread across the cortex, and (iii) accompanied by improvements in patients' auditory abilities. CONCLUSION: These findings show that gamma acoustic-electric trigeminal-nerve stimulation can improve resting-state functional connectivity in the gamma band, which in turn may be linked to auditory abilities and/or consciousness restoration in DOC patients.

Effect of topographic comparison of electroencephalographic microstates on the diagnosis and prognosis prediction of patients with prolonged disorders of consciousness.

AIMS: The electroencephalography (EEG) microstates are indicative of fundamental information processing mechanisms, which are severely damaged in patients with prolonged disorders of consciousness (pDoC). We aimed to improve the topographic analysis of EEG microstates and explore indicators available for diagnosis and prognosis prediction of patients with pDoC, which were still lacking. METHODS: We conducted EEG recordings on 59 patients with pDoC and 32 healthy controls. We refined the microstate method to accurately estimate topographical differences, and then classify and forecast the prognosis of patients with pDoC. An independent dataset was used to validate the conclusion. RESULTS: Through optimized topographic analysis, the global explained variance (GEV) of microstate E increased significantly in groups with reduced levels of consciousness. However, its ability to classify the VS/UWS group was poor. In addition, the optimized GEV of microstate E exhibited a statistically significant decrease in the good prognosis group as opposed to the group with a poor prognosis. Furthermore, the optimized GEV of microstate E strongly predicted a patient's prognosis. CONCLUSION: This technique harmonizes with the existing microstate analysis and exhibits precise and comprehensive differences in microstate topography between groups. Furthermore, this method has significant potential for evaluating the clinical prognosis of pDoC patients.

NODDI Identifies Cognitive Associations with In Vivo Microstructural Changes in Remote Cortical Regions and Thalamocortical Pathways in Thalamic Stroke.

The roles of cerebral structures distal to isolated thalamic infarcts in cognitive deficits remain unclear. We aimed to identify the in vivo microstructural characteristics of remote gray matter (GM) and thalamic pathways and elucidate their roles across cognitive domains. Patients with isolated ischemic thalamic stroke and healthy controls underwent neuropsychological assessment and magnetic resonance imaging. Neurite orientation dispersion and density imaging (NODDI) was modeled to derive the intracellular volume fraction (VFic) and orientation dispersion index. Fiber density (FD) was determined by constrained spherical deconvolution, and tensor-derived fractional anisotropy (FA) was calculated. Voxel-wise GM analysis and thalamic pathway tractography were performed. Twenty-six patients and 26 healthy controls were included. Patients exhibited reduced VFic in remote GM regions, including ipsilesional insular and temporal subregions. The microstructural metrics VFic, FD, and FA within ipsilesional thalamic pathways decreased (false discovery rate [FDR]-p < 0.05). Noteworthy associations emerged as VFic within insular cortices (ρ = -0.791 to -0.630; FDR-p < 0.05) and FD in tracts connecting the thalamus and insula (ρ = 0.830 to 0.971; FDR-p < 0.001) were closely associated with executive function. The VFic in Brodmann area 52 (ρ = -0.839; FDR-p = 0.005) and FA within its thalamic pathway (ρ = -0.799; FDR-p = 0.003) correlated with total auditory memory scores. In conclusion, NODDI revealed neurite loss in remote normal-appearing GM regions and ipsilesional thalamic pathways in thalamic stroke. Reduced cortical dendritic density and axonal density of thalamocortical tracts in specific subregions were associated with improved cognitive functions. Subacute microstructural alterations beyond focal thalamic infarcts might reflect beneficial remodeling indicating post-stroke plasticity.

Identification of Candidate Biomarkers of Alzheimer's Disease via Multiplex Cerebrospinal Fluid and Serum Proteomics.

Alzheimer's disease (AD) is the most prevalent form of dementia among elderly people worldwide. Cerebrospinal fluid (CSF) is the optimal fluid source for AD biomarkers, while serum biomarkers are much more achievable. To search for novel diagnostic AD biomarkers, we performed a quantitative proteomic analysis of CSF and serum samples from AD and normal cognitive controls (NC). CSF and serum proteomes were analyzed via data-independent acquisition quantitative mass spectrometry. Our bioinformatic analysis was based on Gene Ontology (GO) functional annotation analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment. In comparison to the controls, 8 proteins were more abundant in AD CSF, and 60 were less abundant in AD CSF, whereas 55 proteins were more and 10 were less abundant in the serum samples. ATPase-associated activity for CSF and mitochondrial functions for CSF and serum were the most enriched GO terms of the DEPs. KEGG enrichment analysis showed that the most significant pathways for the differentially expressed proteins were the N-glycan biosynthesis pathways. The area under the curve (AUC) values for CSF sodium-/potassium-transporting ATPase subunit beta-1 (AT1B1), serglycin (SRGN), and thioredoxin-dependent peroxide reductase, mitochondrial (PRDX3) were 0.867 (p = 0.004), 0.833 (p = 0.008), and 0.783 (p = 0.025), respectively. A panel of the above three CSF proteins accurately differentiated AD (AUC = 0.933, p = 0.001) from NC. The AUC values for serum probable phospholipid-transporting ATPase IM (AT8B4) and SRGN were moderate. The AUC of the CSF SRGN + serum SRGN was 0.842 (p = 0.007). These novel AD biomarker candidates are mainly associated with inflammation, ATPase activity, oxidative stress, and mitochondrial dysfunction. Further studies are needed to investigate the molecular mechanisms by which these potential biomarkers are involved in AD.

Phase Property of Envelope-Tracking EEG Response Is Preserved in Patients with Disorders of Consciousness.

When listening to speech, the low-frequency cortical response below 10 Hz can track the speech envelope. Previous studies have demonstrated that the phase lag between speech envelope and cortical response can reflect the mechanism by which the envelope-tracking response is generated. Here, we analyze whether the mechanism to generate the envelope-tracking response is modulated by the level of consciousness, by studying how the stimulus-response phase lag is modulated by the disorder of consciousness (DoC). It is observed that DoC patients in general show less reliable neural tracking of speech. Nevertheless, the stimulus-response phase lag changes linearly with frequency between 3.5 and 8 Hz, for DoC patients who show reliable cortical tracking to speech, regardless of the consciousness state. The mean phase lag is also consistent across these DoC patients. These results suggest that the envelope-tracking response to speech can be generated by an automatic process that is barely modulated by the consciousness state.

Cortical responses to auditory stimulation predict the prognosis of patients with disorders of consciousness.

OBJECTIVE: This study aimed to assess the prognosis of patients with disorders of consciousness (DoC) using auditory stimulation with electroencephalogram (EEG) recordings. METHODS: We enrolled 72 patients with DoC in the study, which involved subjecting patients to auditory stimulation while EEG responses were recorded. Coma Recovery Scale-Revised (CRS-R) scores and Glasgow Outcome Scale (GOS) were determined for each patient and followed up for three months. A frequency spectrum analysis was performed on the EEG recordings. Finally, the power spectral density (PSD) index was used to predict the prognosis of patients with DoC based on a support vector machine (SVM) model. RESULTS: Power spectral analyses revealed that the cortical response to auditory stimulation showed a decreasing trend with decreasing consciousness levels. Auditory stimulation-induced changes in absolute PSD at the delta and theta bands were positively correlated with the CRS-R and GOS scores. Furthermore, these cortical responses to auditory stimulation had a good ability to discriminate between good and poor prognoses of patients with DoC. CONCLUSIONS: Auditory stimulation-induced changes in the PSD were highly predictive of DoC outcomes. SIGNIFICANCE: Our findings showed that cortical responses to auditory stimulation may be an important electrophysiological indicator of prognosis in patients with DoC.

The changes of central auditory processing function and its electroencephalogram in patients with mild cognitive impairment and early Alzheimer's disease.

Background: The aim of this study is to assess the central auditory processing (CAP) function and its electroencephalogram (EEG) in patients with mild cognitive impairment (MCI) and the early stage of Alzheimer's disease (AD). Methods: In this study, 25 patients with early AD, 22 patients with MCI, and 22 matched healthy controls (HC) were included. After cognitive assessment, binaural processing function was assessed using the staggered spondaic word (SSW) test, and auditory working memory was assessed by auditory n-back paradigm, while EEG was recorded. Patients' behavioral indicators, event-related potentials (ERPs) components, and function connection (FC) were compared between groups and the related factors were analyzed. Results: The difference of the accuracy of behavioral tests for the three groups of subjects was significant and all the behavioral indicators were positively correlated with cognitive function scores. Intergroup differences in amplitude (p < 0.05) and latency (p < 0.01) were significant for P3 in the 1-back paradigm. In the SSW test, AD and MCI patients showed reduced connectivity between the left frontal lobe and the whole brain in the δ-band, while in the n-back paradigm, patients with MCI and early AD showed reduced association of frontal leads with central and parietal leads in the δ-band. Conclusions: Patients with MCI and early AD have reduced CAP functions including binaural processing function and auditory working memory functions. This reduction is significantly associated with reduced cognitive function, and is reflected in different patterns of changes in ERP as well as functional connectivity in the brain.

Consformer: Consciousness Detection Using Transformer Networks With Correntropy-Based Measures.

Consciousness detection is important in diagnosis and treatment of disorders of consciousness (DOC). Recent studies have demonstrated that electroencephalography (EEG) signals contain effective information for consciousness state evaluation. We propose two novel EEG measures: the spatiotemporal correntropy and the neuromodulation intensity, to reflect the temporal-spatial complexity in brain signals for consciousness detection. Then, we build a pool of EEG measures with different spectral, complexity and connectivity features, and propose Consformer, a transformer network to learn an adaptive optimization of features for different subjects with the attention mechanism. Experiments are carried out using a large dataset of 280 resting-state EEG recordings of DOC patients. Consformer discriminates minimally conscious state (MCS) from vegetative state (VS) with an accuracy of 85.73% and an F1-score of 86.95%, which achieves the state-of-the-art performance.

Estimated Burden of Stroke in China in 2020.

Importance: Stroke is the leading cause of death in China. However, recent data about the up-to-date stroke burden in China are limited. Objective: To investigate the urban-rural disparity of stroke burden in the Chinese adult population, including prevalence, incidence, and mortality rate, and disparities between urban and rural populations. Design, Setting, and Participants: This cross-sectional study was based on a nationally representative survey that included 676 394 participants aged 40 years and older. It was conducted from July 2020 to December 2020 in 31 provinces in mainland China. Main Outcomes and Measures: Primary outcome was self-reported stroke verified by trained neurologists during a face-to-face interviews using a standardized protocol. Stroke incidence were assessed by defining first-ever strokes that occurred during 1 year preceding the survey. Strokes causing death that occurred during the 1 year preceding the survey were considered as death cases. Results: The study included 676 394 Chinese adults (395 122 [58.4%] females; mean [SD] age, 59.7 [11.0] years). In 2020, the weighted prevalence, incidence, and mortality rates of stroke in China were 2.6% (95% CI, 2.6%-2.6%), 505.2 (95% CI, 488.5-522.0) per 100 000 person-years, and 343.4 (95% CI, 329.6-357.2) per 100 000 person-years, respectively. It was estimated that among the Chinese population aged 40 years and older in 2020, there were 3.4 (95% CI, 3.3-3.6) million incident cases of stroke, 17.8 (95% CI, 17.5-18.0) million prevalent cases of stroke, and 2.3 (95% CI, 2.2-2.4) million deaths from stroke. Ischemic stroke constituted 15.5 (95% CI, 15.2-15.6) million (86.8%) of all incident strokes in 2020, while intracerebral hemorrhage constituted 2.1 (95% CI, 2.1-2.1) million (11.9%) and subarachnoid hemorrhage constituted 0.2 (95% CI, 0.2-0.2) million (1.3%). The prevalence of stroke was higher in urban than in rural areas (2.7% [95% CI, 2.6%-2.7%] vs 2.5% [95% CI, 2.5%-2.6%]; P = .02), but the incidence rate (485.5 [95% CI, 462.8-508.3] vs 520.8 [95% CI, 496.3-545.2] per 100 000 person-years; P < .001) and mortality rate (309.9 [95% CI, 291.7-328.1] vs 369.7 [95% CI, 349.1-390.3] per 100 000 person-years; P < .001) were lower in urban areas than in rural areas. In 2020, the leading risk factor for stroke was hypertension (OR, 3.20 [95% CI, 3.09-3.32]). Conclusions and Relevance: In a large, nationally representative sample of adults aged 40 years or older, the estimated prevalence, incidence, and mortality rate of stroke in China in 2020 were 2.6%, 505.2 per 100 000 person-years, and 343.4 per 100 000 person-years, respectively, indicating the need for an improved stroke prevention strategy in the general Chinese population.

Negative regulation of TREM2-mediated C9orf72 poly-GA clearance by the NLRP3 inflammasome.

Expansion of the hexanucleotide repeat GGGGCC in the C9orf72 gene is the most common genetic factor in amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). Poly-Gly-Ala (poly-GA), one form of dipeptide repeat proteins (DPRs) produced from GGGGCC repeats, tends to form neurotoxic protein aggregates. The C9orf72 GGGGCC repeats and microglial receptor TREM2 are both associated with risk for ALS/FTD. The role and regulation of TREM2 in C9orf72-ALS/FTD remain unclear. Here, we found that poly-GA proteins activate the microglial NLRP3 inflammasome to produce interleukin-1ß (IL-1ß), which promotes ADAM10-mediated TREM2 cleavage and inhibits phagocytosis of poly-GA. The inhibitor of the NLRP3 inflammasome, MCC950, reduces the TREM2 cleavage and poly-GA aggregates, resulting in the alleviation of motor deficits in poly-GA mice. Our study identifies a crosstalk between NLRP3 and TREM2 signaling, suggesting that targeting the NLRP3 inflammasome to sustain TREM2 is an approach to treat C9orf72-ALS/FTD.

The role of purinergic receptors in neural repair and regeneration after spinal cord injury.

Spinal cord injury is a serious injury of the central nervous system that results in neurological deficits. The pathophysiological mechanisms underlying spinal cord injury, as well as the mechanisms involved in neural repair and regeneration, are highly complex. Although there have been many studies on these mechanisms, there is no effective intervention for such injury. In spinal cord injury, neural repair and regeneration is an important part of improving neurological function after injury, although the low regenerative ability of nerve cells and the difficulty in axonal and myelin regeneration after spinal cord injury hamper functional recovery. Large amounts of ATP and its metabolites are released after spinal cord injury and participate in various aspects of functional regulation by acting on purinergic receptors which are widely expressed in the spinal cord. These processes mediate intracellular and extracellular signalling pathways to improve neural repair and regeneration after spinal cord injury. This article reviews research on the mechanistic roles of purinergic receptors in spinal cord injury, highlighting the potential role of purinergic receptors as interventional targets for neural repair and regeneration after spinal cord injury.

Sensorimotor network connectivity correlates with motor improvement after repetitive transcranial magnetic stimulation in patients with Parkinson's disease.

BACKGROUND: Emerging evidence suggests that repetitive transcranial magnetic stimulation (rTMS) generally improves Parkinson's disease (PD) motor symptoms. However, personal responses to rTMS might be different. In this study, we explore the connectivity changes in PD patients with different responses to rTMS. METHODS: Among PD patients, 25 were treated with 10Hz-rTMS and seven were with sham rTMS over the supplementary motor area for 10 days. Resting-state functional connectivity magnetic resonance imaging (rs-fMRI) was performed in PD patients before and after rTMS stimulation. Neuropsychological scales such as Unified Parkinson's Disease Rating Scale Part III (UPDRS-III) were collected synchronously with rs-fMRI. To explore the connectivity changes after rTMS, degree centrality was calculated. RESULTS: 13 out of 25 participants were responsive to 10Hz rTMS. Degree centrality patterns in the left sensorimotor regions are primarily responsible for the differences between responsive and non-responsive individuals. Improvement in motor symptoms was substantially related to the baseline degree centrality in the left PreCG and the left PoCG. The performance in distinguishing non-responders from responders was further validated by the ROC analysis utilizing DC characteristics. Lastly, we found that connectivity increased in left PreCG and PoCG in patients with a better response to the rTMS. CONCLUSION: Taken together, these results suggest that the sensorimotor network is involved in the motor improvement following rTMS treatment, with patients with lower sensorimotor connectivity showing a tendency for greater motor improvement to HF-rTMS.

Salivary Aß1-42 may be a quick-tested biomarker for clinical use in Alzheimer's disease: a meta-analysis.

OBJECTIVE: Alzheimer's disease (AD) is the most prevalent form of dementia among the aging population. Cumulative studies aim to find non-invasive biomarkers in the early stages of AD. Saliva can be obtained easily, and salivary biomarkers have been proven effective in detecting neurodegenerative diseases. To find effective biomarkers in saliva and to help the diagnosis of AD, we performed a meta-analysis focusing on the salivary biomarkers (ß-amyloid 1-42 (Aß1-42), total tau (t-tau), phosphorylated tau (p-tau) and acetylcholinesterase (AChE)) in AD. METHODS: We conducted a systematic online search for eligible studies reporting data on salivary biomarkers reflecting Aß1-42, t-tau, p-tau, and AChE in AD cohorts versus controls. Biomarkers' performance was assessed in a random-effects meta-analysis with the ratio of mean (RoM). RESULTS: A total of thirteen studies were included in the meta-analysis, of them seven involved salivary Aß1-42 (271 AD and 489 controls), five involved salivary t-tau (324 AD and 252 controls), four involved salivary p-tau (130 AD and 161 controls), and three involved salivary AChE (81 AD and 54 controls). AD showed significantly higher salivary Aß1-42 levels than control (ROM = 1.90 (95% CI 1.28-2.81, P = 0.001), while AD and control did not differ significantly on salivary t-tau, p-tau and AChE (ROM = 0.94, 95% CI 0.67-1.31, P = 0.72; ROM = 0.91, 95% CI 0.56-1.45, P = 0.68; ROM = 0.83, 95% CI 0.24-2.88, P = 0.77; respectively). CONCLUSION: The pooled results provide evidence that salivary Aß1-42 may serve as a sensitive biomarker for AD; nevertheless, larger AD cohorts are required to further confirm the sensitivity and specificity of salivary Aß1-42 for AD diagnosis.

Statistical learning in patients in the minimally conscious state.

When listening to speech, cortical activity can track mentally constructed linguistic units such as words, phrases, and sentences. Recent studies have also shown that the neural responses to mentally constructed linguistic units can predict the outcome of patients with disorders of consciousness (DoC). In healthy individuals, cortical tracking of linguistic units can be driven by both long-term linguistic knowledge and online learning of the transitional probability between syllables. Here, we investigated whether statistical learning could occur in patients in the minimally conscious state (MCS) and patients emerged from the MCS (EMCS) using electroencephalography (EEG). In Experiment 1, we presented to participants an isochronous sequence of syllables, which were composed of either 4 real disyllabic words or 4 reversed disyllabic words. An inter-trial phase coherence analysis revealed that the patient groups showed similar word tracking responses to real and reversed words. In Experiment 2, we presented trisyllabic artificial words that were defined by the transitional probability between words, and a significant word-rate EEG response was observed for MCS patients. These results suggested that statistical learning can occur with a minimal conscious level. The residual statistical learning ability in MCS patients could potentially be harnessed to induce neural plasticity.

Sleep patterns correlates with the efficacy of tDCS on post-stroke patients with prolonged disorders of consciousness.

BACKGROUND: The subclassification of prolonged disorders of consciousness (DoC) based on sleep patterns is important for the evaluation and treatment of the disease. This study evaluates the correlation between polysomnographic patterns and the efficacy of transcranial direct current stimulation (tDCS) in patients with prolonged DoC due to stroke. METHODS: In total, 33 patients in the vegetative state (VS) with sleep cycles or without sleep cycles were randomly assigned to either active or sham tDCS groups. Polysomnography was used to monitor sleep changes before and after intervention. Additionally, clinical scale scores and electroencephalogram (EEG) analysis were performed before and after intervention to evaluate the efficacy of tDCS on the patients subclassified according to their sleep patterns. RESULTS: The results suggest that tDCS improved the sleep structure, significantly prolonged total sleep time (TST) (95%CI: 14.387-283.527, P = 0.013) and NREM sleep stage 2 (95%CI: 3.157-246.165, P = 0.040) of the VS patients with sleep cycles. It also significantly enhanced brain function of patients with sleep cycles, which were reflected by the increased clinical scores (95%CI: 0.340-3.440, P < 0.001), the EEG powers and functional connectivity in the brain and the 6-month prognosis. Moreover, the changes in NREM sleep stage 2 had a significant positive correlation with each index of the ß band. CONCLUSION: This study reveals the importance of sleep patterns in the prognosis and treatment of prolonged DoC and provides new evidence for the efficacy of tDCS in post-stroke patients with VS patients subclassified by sleep pattern. Trial registration URL: https://www. CLINICALTRIALS: gov . Unique identifier: NCT03809936. Registered 18 January 2019.