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Nasim Montazeri Ghahjaverestan,1,2 Sina Akbarian,1,2 Maziar Hafezi,1,2 Shumit Saha,1,2 Kaiyin Zhu,1 Bojan Gavrilovic,1 Babak Taati,1– 3,* Azadeh Yadollahi1,2,* 1Kite - Toronto Rehabilitation Institute, University Health Network, Toronto, ON, Canada; 2Institute of Biomedical Engineering, University of Toronto, Toronto, ON, Canada; 3Computer Science, University of Toronto, Toronto, ON, Canada*These authors contributed equally to this workCorrespondence: Azadeh YadollahiKite - Toronto Rehabilitation Institute, University Health Network, Room 12-106, 550 University Avenue, Toronto, ON M5G 2A2, CanadaTel +1 416 597 3422 Ext 7936Fax +1 416 597 8959Email Azadeh.Yadollahi@uhn.caPurpose: The current gold standardto detect sleep/wakefulness is based on electroencephalogram, which is inconvenient if included in portable sleep screening devices. Therefore, a challenge in the portable devices is sleeping time estimation. Without sleeping time, sleep parameters such as apnea/hypopnea index (AHI), an index for quantifying sleep apnea severity, can be underestimated. Recent studies have used tracheal sounds and movements for sleep screening and calculating AHI without considering sleeping time. In this study, we investigated the detection of sleep/wakefulness states and estimation of sleep parameters using tracheal sounds and movements.Materials and Methods: Participants with suspected sleep apnea who were referred for sleep screening were included in this study. Simultaneously with polysomnography, tracheal sounds and movements were recorded with a small wearable device, called the Patch, attached over the trachea. Each 30-second epoch of tracheal data was scored as sleep or wakefulness using an automatic classification algorithm. The performance of the algorithm was compared to the sleep/wakefulness scored blindly based on the polysomnography.Results: Eighty-eight subjects were included in this study. The accuracy of sleep/wakefulness detection was 82.3± 8.66% with a sensitivity of 87.8± 10.8 % (sleep), specificity of 71.4± 18.5% (awake), F1 of 88.1± 9.3% and Cohen’s kappa of 0.54. The correlations between the estimated and polysomnography-based measures for total sleep time and sleep efficiency were 0.78 (p< 0.001) and 0.70 (p< 0.001), respectively.Conclusion: Sleep/wakefulness periods can be detected using tracheal sound and movements. The results of this study combined with our previous studies on screening sleep apnea with tracheal sounds provide strong evidence that respiratory sounds analysis can be used to develop robust, convenient and cost-effective portable devices for sleep apnea monitoring.Keywords: sleep apnea, apnea/hypopnea index, principal component analysis, classification, imbalanced data

SUMMARYThe pathophysiology of epilepsy underlies complex network dysfunction, the cell-type-specific contributions of which remain poorly defined in human disease. In this study, we developed a strategy that simultaneously isolates neuronal, astrocyte and oligodendroglial progenitor (OPC)-enriched nuclei from human fresh-frozen neocortex and applied it to characterize the distinct transcriptome of each cell type in temporal lobe epilepsy (TLE) surgical samples. Differential RNA-seq analysis revealed several dysregulated pathways in neurons, OPCs, and astrocytes, and disclosed an immature phenotype switch in TLE astrocytes. An independent single cell RNA-seq TLE dataset uncovered a hybrid population of cells aberrantly co-expressing canonical astrocyte and OPC-like progenitor markers (GFAP+OLIG2+ glia), which we corroborated in-situ in human TLE samples, and further demonstrated their emergence after chronic seizure injury in a mouse model of status epilepticus. In line with their immature signature, a subset of human TLE glia were also abnormally proliferative, both in-vivo and in-vitro. Generally, this analysis validates the utility of the proposed cell type-specific isolation strategy to study glia-specific changes ex vivo using fresh-frozen human samples, and specifically, it delineates an aberrant glial phenotype in human TLE specimens.

Backgrounds: To assess the role of socio-economic inequality in visual impairment (VI) in Varamin district, Iran.Patients and Methods: Using multistage cluster sampling method, 60 clusters (each with 50 subjects) were recruited and underwent clinical eye examinations. Socio-economic status (SES) was identified based on education, occupation, family assets and housing conditions that were measured at the participants' households using a semi-structured questionnaire and a two-step cluster analysis model. In addition, principal component analysis and the concentration index were used to identify the gap between high and low SES groups.Results: Participants were categorized in high (522, 24.4%), moderate (974, 43.1%) and low (763, 33.7%) socio-economic levels. In these levels, the prevalence of VI was 5.9% (95% CI: 3.3 to 8.6), 10.4% (95% CI: 8.4 to 12.4), and 12.6% (95% CI: 10.1 to 15.1), respectively. The prevalence of VI in people with low SES was significantly greater than those in high SES level. The proportions of avoidable causes were relatively high in all SES levels (more than 80%) with no significant difference between different levels.Conclusions: There is significant inequality in VI prevalence in Varamin district. Avoidable causes are high in all SES groups. Therefore, community-based modalities and preventive programs with a specific notice to poorer SES groups are recommended to improve eye health in this district.

BACKGROUND Elucidating the genetic architecture of neuropsychiatric disorders remains a major scientific and medical challenge. Emerging genomic technologies now permit the analysis of somatic mosaicism in human tissues. The measured frequencies of single-nucleotide variants (SNVs), small insertion/deletion (indel) mutations, structural variants [including copy number variants (CNVs), inversions, translocations, and whole-chromosome gains or losses], and mobile genetic element insertions (MEIs) indicate that each neuron may harbor hundreds of somatic mutations. Given the long life span of neurons and their central role in neural circuits and behavior, somatic mosaicism represents a potential mechanism that may contribute to neuronal diversity and the etiology of numerous neuropsychiatric disorders. ADVANCES Somatic mutations that confer cellular proliferative or cellular survival phenotypes have been identified in patients with cortical malformations. These data have led to the hypothesis that somatic mutations may also confer phenotypes to subsets of neurons, which could increase the risk of developing certain neuropsychiatric disorders. Genomic technologies, including advances in long-read, next-generation DNA sequencing technologies, single-cell genomics, and cutting-edge bioinformatics, can now make it possible to determine the types and frequencies of somatic mutations within the human brain. However, a comprehensive understanding of the contribution of somatic mosaicism to neurotypical brain development and neuropsychiatric disease requires a coordinated, multi-institutional effort. The National Institute of Mental Health (NIMH) has formed a network of 18 investigative teams representing 15 institutions called the Brain Somatic Mosaicism Network (BSMN). Each research team will use an array of genomic technologies to exploit well-curated human tissue repositories in an effort to define the frequency and pattern of somatic mutations in neurotypical individuals and in schizophrenia, autism spectrum disorder, bipolar disorder, Tourette syndrome, and epilepsy patient populations. Collectively, these efforts are estimated to generate a community resource of more than 10,000 DNA-sequencing data sets and will enable a cross-platform integrated analysis with other NIMH initiatives, such as the PsychENCODE project and the CommonMind Consortium. OUTLOOK A fundamental open question in neurodevelopmental genetics is whether and how somatic mosaicism may contribute to neuronal diversity within the neurotypical spectrum and in diseased brains. Healthy individuals may harbor known pathogenic somatic mutations at subclinical frequencies, and the local composition of neural cell types may be altered by mutations conferring prosurvival phenotypes in subsets of neurons. By extension, the neurotypical architecture of somatic mutations may confer circuit-level differences that would not be present if every neuron had an identical genome. Given the apparent abundance of somatic mutations within neurons, an in-depth understanding of how different types of somatic mosaicism affect neural function could yield mechanistic insight into the etiology of neurodevelopmental and neuropsychiatric disorders. The BSMN will examine large collections of postmortem brain tissue from neurotypical individuals and patients with neuropsychiatric disorders. By sequencing brain DNA and single neuronal genomes directly, rather than genomic DNA derived from peripheral blood or other somatic tissues, the BSMN will test the hypothesis that brain somatic variants contribute to neuropsychiatric disease. Notably, it is also possible that some inherited germline variants confer susceptibility to disease, which is later exacerbated by somatic mutations. Confirming such a scenario could increase our understanding of the genetic risk architecture of neuropsychiatric disease and may, in part, explain discordant neuropsychiatric phenotypes between identical twins. Results from these studies may lead to the discovery of biomarkers and genetic targets to improve the treatment of neuropsychiatric disease and may offer hope for improving the lives of patients and their families.

Lupus erythematosus (LE) is an autoimmune disease. The mortality rate and causes of death are different in various countries. The present study is done to find out the causes of mortality in the systemic lupus erythematosus (SLE) patients in lupus unit of Rheumatology Research Center and other wards of Shariati Hospital. This study was retrospective according to medical records of patients who were referred to Lupus Unit of Rheumatology Research center, ICU, Gynecology and Nephrology wards of Shariati hospital during 10 years, from 1991 till 2001. Of 2021-recorded patient’s files, 165 (7.8%) deaths were already recorded. 84.8% were female and 15.2% male. The duration of disease was 36±12 months. The mean duration of follow up from entering the study till time of death was 25.9±16.8 months. The causes of mortality were as follows: infection (12.1%), respiratory (8.5%), CNS (13.9%), kidney (3.6%), malignancy (1.2%), unknown (7.8%), active lupus (3%). Infection accompanied with other causes (27.9%) , respiratory with other causes (11.5%), CNS with other causes (5.5%) and renal with other causes (4.8%). Infections are the most common cause of death in SLE Iranian patients, which is compatible with some multicentric studies. But in some previous studies myocardial infarction was reported as the main cause of death.