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Accumulating evidence shows that most chronic neurological diseases have a link with sleep disturbances, and that patients with chronically poor sleep undergo an accelerated cognitive decline. Indeed, a single-night of sleep deprivation may increase metabolic waste levels in cerebrospinal fluid. However, it remains unknown how chronic sleep disturbances in isolation from an underlying neurological disease may affect the glymphatic system. Clearance of brain interstitial waste by the glymphatic system occurs primarily during sleep, driven by multiple oscillators including arterial pulsatility, and vasomotion. Herein, we induced sleep fragmentation in young wildtype mice and assessed the effects on glymphatic activity and cognitive functions. Chronic sleep fragmentation reduced glymphatic function and impaired cognitive functions in healthy mice. A mechanistic analysis showed that the chronic sleep fragmentation suppressed slow vasomotion, without altering cardiac-driven pulsations. Taken together, results of this study document that chronic sleep fragmentation suppresses brain metabolite clearance and impairs cognition, even in the absence of disease. [ABSTRACT FROM AUTHOR]

We propose a novel approach for predicting stress severity by measuring sleep phasic heart rate variability (HRV) using a smart device. This device can potentially be applied for stress self‐screening in large populations. Using a Holter electrocardiogram (ECG) and a Huawei smart device, we conducted 24‐h dual recordings of 159 medical workers working regular shifts. Based on photoplethysmography (PPG) and accelerometer signals acquired by the Huawei smart device, we sorted episodes of cyclic alternating pattern (CAP; unstable sleep), non‐cyclic alternating pattern (NCAP; stable sleep), wakefulness, and rapid eye movement (REM) sleep based on cardiopulmonary coupling (CPC) algorithms. We further calculated the HRV indices during NCAP, CAP and REM sleep episodes using both the Holter ECG and smart‐device PPG signals. We later developed a machine learning model to predict stress severity based only on the smart device data obtained from the participants along with a clinical evaluation of emotion and stress conditions. Sleep phasic HRV indices predict individual stress severity with better performance in CAP or REM sleep than in NCAP. Using the smart device data only, the optimal machine learning‐based stress prediction model exhibited accuracy of 80.3 %, sensitivity 87.2 %, and 63.9 % for specificity. Sleep phasic heart rate variability can be accurately evaluated using a smart device and subsequently can be used for stress predication. [ABSTRACT FROM AUTHOR]

Summary: Napping during night shifts effectively reduces disease risk and improves work performance, but few studies have investigated the association between napping and physiological changes, particularly in off‐duty daily lives. Changes in the autonomic nervous system precede diseases like cardiovascular disease, diabetes, and obesity. Heart rate variability is a good indicator of autonomic nervous system. This study aimed to investigate the link between night shift nap durations and heart rate variability indices in the daily lives of medical workers. As indicators of chronic and long‐term alterations, the circadian patterns of heart rate variability indices were evaluated. We recruited 146 medical workers with regular night shifts and divided them into four groups based on their self‐reported nap durations. Heart rate variability circadian parameters (midline‐estimating statistic of rhythm, amplitude, and acrophase) were obtained by obtaining 24‐h electrocardiogram on a day without night shifts, plotting the data of the heart rate variability indices as a function of time, and fitting them into periodic cosine curves. Using clinical scales, depression, anxiety, stress, fatigue, and sleepiness were assessed. Linear regression analysis revealed a positive relationship between 61–120‐min naps and 24‐h, daytime, and night‐time heart rate variability indices, and the parasympathetic activity oscillation amplitude (indexed by high‐frequency power, the square root of the mean of the sum of squares of differences between adjacent normal intervals, standard deviation of short‐term R‐R‐interval variability) within one circadian cycle. This study indicated that napping for 61–120 min during night shifts could benefit medical workers' health, providing physiological evidence to promote nap management. [ABSTRACT FROM AUTHOR]

Objective: Neuromyelitis optica spectrum disorder (NMOSD) is an inflammatory demyelinating disease that leads to severe disability. A large proportion of NMOSD patients are seropositive for aquaporin‐4 autoantibodies (AQP4‐IgG, named as NMO‐IgG) targeting AQP4, which is selectively expressed on astrocytes in the central nervous system. This study tests the hypothesis that in response to NMO‐IgG, the pathogenic astrocyte‐derived exosomes are released and injure the neighboring cells. Methods: IgG purified from serum of either NMOSD patients or healthy controls was used to generate astrocyte‐derived exosomes (AST‐ExosNMO vs AST‐ExosCON) in cultured rat astrocytes. The exosomes were respectively delivered to cultured rat oligodendrocytes in vitro, tissue culture of rat optic nerve ex vivo, and rat optic nerve in vivo to evaluate the pathogenic roles of AST‐ExosNMO. The microRNA (miRNA) sequencing of AST‐Exos and verification were performed to identify the key pathogenic miRNA. The custom‐designed adeno‐associated virus (AAV) antagonizing the key miRNA was evaluated for its therapeutic effects in vivo. Moreover, the serum levels of the key exosomal miRNA were measured between NMOSD patients and healthy controls. Results: AST‐ExosNMO led to notable demyelination in both cultured oligodendrocytes and optic nerve tissue. Exosomal miR‐129‐2‐3p was identified as the key miRNA mediating the demyelinating pathogenesis via downstream target gene SMAD3. AAV antagonizing miR‐129‐2‐3p protected against demyelination in an NMOSD rodent model. The serum exosomal miR‐129‐2‐3p level was significantly elevated in NMOSD patients and correlated with disease severity. Interpretation: Astrocytes targeted by NMO‐IgG release pathogenic exosomes that could potentially be used as therapeutic targets or disease monitoring biomarkers in NMOSD. ANN NEUROL 2023;94:163–181 [ABSTRACT FROM AUTHOR]