Sleep Stages Research Articles

An Interpretable Single-Channel EEG Sleep Staging Model Based on Prototype Matching and Multitask Learning

An Interpretable Single-Channel EEG Sleep Staging Model Based on Prototype Matching and Multitask Learning

Sleep-wake patterns of fencing athletes: a long-term wearable device study

Objective Sleep is the most efficient means of recovery for athletes, guaranteeing optimal athletic performance. However, many athletes frequently experience sleep problems. Our study aims to describe the sleep-wake patterns of fencing athletes and determine whether factors, such as sex, competitive level and training schedules, could affect the sleep-wake rhythm. Methods Sleep data from 23 fencing athletes were collected using the Huawei Band 6, monitoring key sleep parameters such as bedtime, wake time, duration of deep and light sleep, wake periods, REM sleep duration, and nap duration. During this period, athletes were required to wear the band continuously for 24 hours daily, except bathing, charging, and competition times. Results Athletes averaged 7.97 hours of sleep per night, with significant differences observed in wake time (p = 0.015) and midpoint of sleep (p = 0.048) between high-level and low-level athletes, as well as a higher frequency of naps among high-level (χ2 = 11.97, p = 0.001) and female (χ2 = 3.88, p = 0.049) athletes. Nap duration was negatively correlated with night sleep duration (r = − 0.270, p < 0.001). Athletes were observed for changes in sleep-wake patterns from Monday to Sunday. On Mondays, Wednesdays, and Fridays, when there was no morning training, the athletes’ wake-up time and the midpoint of sleep were shifted significantly backward, and there were significant differences in sleep parameters between training days and rest days. Conclusion The sleep patterns of athletes differ according to level and gender. The sleep-wake patterns of athletes are influenced by training schedules, indicating the presence of sleep rhythm disruption.

A randomized, crossover trial of one night of oxygen therapy for obstructive sleep apnea in patients with fibrotic interstitial lung disease.

There is no satisfactory treatment for obstructive sleep apnea (OSA) in patients with interstitial lung disease (ILD) because of poor tolerance of positive airway pressure (PAP) therapy. Supplemental oxygen therapy has been shown to reduce hypoxemia and is well tolerated in patients with ILD. However, little is known about the effect of nocturnal oxygen supplementation (NOS) on OSA in patients with ILD. In this study, we evaluated one night of oxygen therapy in ILD patients with OSA. Forty-one patients with fibrotic ILD and OSA were randomized to receive supplemental oxygen or air for one night each in a crossover design separated by a washout period of one week. Polysomnography was performed, and sleep-disordered breathing, nocturnal desaturation, sleep architecture, and cardiovascular reactions were monitored. During nights with sham oxygen, the median (interquartile range) apnea-hypopnea index (AHI) was 14.1/h (10.4/h-24.1/h). The percentage of patients in the N3 sleep stage (N3%) was 19.5% (14.0-31.2%). NOS significantly decreased the AHI by a median of 9.3/h (95% CI, 7.6/h-14.4/h; P < 0.001), increased N3% by 4.4% (95% CI, 0.3-10.1%; P = 0.049), and lowered the sleep stage change index by 1.6/h (95% CI, 0.0/h-4.8/h; P = 0.036). NOS improved the oxygen desaturation index (ODI) by -8.8/h (95% CI, -13.4/h to -5.9/h; P < 0.001) and the mean SpO2 by 3.0% (95% CI, 2.6-4.5%; P < 0.001). The mean heart rate during sleep was reduced with the NOS; however, total sleep time and nocturnal blood pressure did not change. In patients with OSA and ILD, one night of oxygen therapy significantly improved sleep-disordered breathing, sleep architecture, nocturnal oxygenation, and heart rate. NOS may be a therapeutic option for ILD patients with OSA.

The Influence of Serotonergic Signaling on Quality of Life, Depression, Insomnia, and Hypoxia in Obstructive Sleep Apnea Patients: Cross-Sectional Study

Background/Objectives: Serotonin and the serotonin transporter (SERT) may have a multifaceted, but not fully understood, role in obstructive sleep apnea (OSA) and its impact on mental health in this group of patients. This study aimed to investigate changes in serotonin and the serotonin transporter (SERT) and their association with depressive and insomnia symptoms. Methods: This study included 76 participants (OSA group: n = 36, control group (CG): n = 40) who underwent polysomnography, while venous blood samples (evening and morning) were analyzed for serotonin and the SERT using ELISA. SERT mRNA expression in peripheral leukocytes was measured via quantitative reverse-transcription polymerase chain reaction (qRT-PCR). Participants were evaluated for depression, insomnia, and quality of life (QoL). Results: This study found no significant differences in SERT mRNA or serotonin between the OSA group and CG. In the CG, individuals without mood disorders had higher baseline SERT levels and evening/morning SERT ratios than those with depression. Among the OSA participants, those with good QoL had elevated serotonin levels in the evening (p = 0.028) and morning (p = 0.043) compared to those with poor QoL. Baseline SERT protein levels were higher in the CG than in the OSA group for insomnia, while SERT mRNA expression was higher in the OSA group. Linear regression models showed 13.3% and 13.1% for non-rapid eye movement sleep (NREM) apnea/hypopnea index (AHI) and AHI variability, respectively, which was accounted for by the morning SERT level, while 30.8% of the arousal index variability was explained by the morning serotonin level. Conclusions: Serotonergic signaling may influence quality of life, depression, and insomnia in OSA, as well as the severity of the disease itself. Stratifying patients by clinical and laboratory phenotypes could enable more personalized treatment.

Phasic dopamine release in the nucleus accumbens influences REM sleep timing.

Based on the activity of dopamine (DA) neurons during behavioral states, the DA system has long been thought to be foundational in regulating sleep-wake behavior; over the past decade advances in circuit manipulation and recording techniques have strengthened this perspective. Recently, several studies have demonstrated that DA release in regions of the limbic system is important in the promotion of REM sleep. Yet how DA dynamics change within bouts of sleep, how these changes are regulated, and whether they influence future state changes remains unclear. To address these questions, in mice of both sexes we used in vivo fiber photometry and inhibitory optogenetics to identify a specific role of DA transients in the nucleus accumbens (NAcc) in state transitions from NREM sleep. We found that DA transients increase their frequency and amplitude over the duration of NREM sleep and that this increase is more pronounced during NREM bouts that transition into REM sleep. Next, we found that DA transients in NREM sleep are influenced by changes in REM sleep pressure. Finally, we show that transient DA release in the NAcc plays a functional role in regulating the timing of REM sleep entrances, as inhibition of midbrain DA neuron terminals in the NAcc prolonged bouts of NREM sleep and decreased the frequency of bouts of REM sleep. These findings demonstrate that DA release in the NAcc is dynamically regulated by sleep pressure and has a functional role in transitions from NREM sleep, particularly those into REM sleep.Significance Statement Sleep is a central component of daily life and is heavily influenced by midbrain dopamine neurons. Dopamine release in limbic regions, such as the nucleus accumbens, has been implicated in the promotion of REM sleep. However, dopamine release dynamics during sleep and how these influence future changes in state remain unclear. We used a fluorescence-based dopamine biosensor to elucidate the pattern of dopamine release during sleep and inhibitory optogenetics to disrupt dopamine release. Dopamine release increases across the duration of NREM sleep bouts and is sensitive to REM sleep need. Inhibition of dopamine terminals in the nucleus accumbens decreases the frequency of REM sleep. This suggests that phasic dopamine release during NREM sleep functionally influences REM sleep timing.

Royal jelly reduced non-rapid eye movement sleep fragmentation and restored sleep stability in diet-induced obese mice.

Royal jelly (RJ) is recognized due to its high nutritional value and potential health benefits. Previous research showed that RJ supplementation decreased fat accumulation, resulting in weight loss and improvements in hyperglycemia and insulin resistance in high-fat diet (HFD)-induced obese mice. To expand the weight-reducing properties of RJ, this study aimed to investigate the effects of RJ supplementation on HFD-induced obese mice with impaired sleep stabilization. Over a 20-week period, the C57BL/6J mice were divided into the following dietary groups: normal diet (ND), ND supplemented with 5% lyophilized RJ powder (ND + RJ), HFD, and HFD supplemented with 5% lyophilized RJ powder (HFD + RJ) groups. Compared with the HFD group, the HFD + RJ group exhibited a significant reduction in body weight via a decrease in fat mass. Moreover, much like the ND group, the HFD + RJ group demonstrated improvements in the fragmentation of non-rapid eye movement (NREM) sleep and wakefulness. These processes contributed to the reestablishment of sleep/wake continuity and restored the overall stability of sleep. In contrast, the ND + RJ and ND groups exhibited a similar sleep/wake architecture. Thus, RJ supplementation in the ND demonstrated no substantial effect on sleep/wake. According to these findings, dietary RJ improves the sleep/wake architecture and restores sleep stability. Hence, RJ is a promising dietary component for addressing obesity and restoring sleep stability.

Fractal cycles of sleep, a new aperiodic activity-based definition of sleep cycles.

Sleep cycles are defined as episodes of non-rapid eye movement (non-REM) sleep followed by an episode of REM sleep. Fractal or aperiodic neural activity is a well-established marker of arousal and sleep stages measured using electroencephalography. We introduce a new concept of 'fractal cycles' of sleep, defined as a time interval during which time series of fractal activity descend to their local minimum and ascend to the next local maximum. We assess correlations between fractal and classical (i.e. non-REM - REM) sleep cycle durations and study cycles with skipped REM sleep. The sample comprised 205 healthy adults, 21 children and adolescents and 111 patients with depression. We found that fractal and classical cycle durations (89±34 vs 90±25 min) correlated positively (r=0.5, p<0.001). Children and adolescents had shorter fractal cycles than young adults (76±34 vs 94±32 min). The fractal cycle algorithm detected cycles with skipped REM sleep in 91-98% of cases. Medicated patients with depression showed longer fractal cycles compared to their unmedicated state (107±51 vs 92±38 min) and age-matched controls (104±49 vs 88±31 min). In conclusion, fractal cycles are an objective, quantifiable, continuous and biologically plausible way to display sleep neural activity and its cycles.

Day-to-day variability in sleep and activity predict the onset of a hypomanic episode in patients with bipolar disorder.

Detecting transitions in bipolar disorder (BD) is essential for implementing early interventions. Our aim was to identify the earliest indicator(s) of the onset of a hypomanic episode in BD. We hypothesized that objective changes in sleep would be the earliest indicator of a new hypomanic or manic episode. In this prospective, observational, contactless study, participants used wearable technology continuously to monitor their daily activity and sleep parameters. They also completed weekly self-ratings using the Altman Self-Rating Mania Scale (ASRM). Using time-frequency spectral derivative spike detection, we assessed the sensitivity, specificity, and balanced accuracy of wearable data to identify a hypomanic episode, defined as at least one or more weeks with consecutive ASRM scores ≥10. Of 164 participants followed for a median (IQR) of 495.0 (410.0) days, 50 experienced one or more hypomanic episodes. Within-night variability in sleep stages was the earliest indicator identifying the onset of a hypomanic episode (mean ± SD) sensitivity: 0.94 ± 0.19; specificity: 0.80 ± 0.19; balanced accuracy: 0.87 ± 0.13), followed by within-day variability in activity levels: sensitivity: 0.93 ± 0.18; specificity: 0.84 ± 0.13; balanced accuracy: 0.89 ± 0.11. Limitations of our study includes a small sample size. Strengths include the use of densely sampled data in a well-characterized cohort followed for over a year, as well as the use of a novel approach using time-frequency analysis to dynamically assess behavioral features at a granular level. Detecting and predicting the onset of hypomanic (or manic) episodes in BD is paramount to implement individualized early interventions.

Clinical validation of a wireless patch-based polysomnography system.

Onera Health has developed the first wireless, patch-based, type-II PSG system, the Onera Sleep Test System (STS), to allow studies to be performed unattended at the patient's home or in any bed at a medical facility. The goal of this multicenter study was to validate data collected from the patch-based PSG to a traditional PSG for sleep staging and AHI. Simultaneous traditional PSG and patch-based PSG study data were obtained in a sleep laboratory from 206 participants with a suspected sleep disorder recruited from 7 clinical sites. Blinded, randomized scoring of the traditional PSG and patch-based PSG recordings was completed according to The AASM Manual for the Scoring of Sleep and Associated Events, version 2.6 criteria by three independent scorers. Concordance correlation coefficients were high between the patch-based device and traditional PSG across essential sleep and respiratory variables - TST (0.87); Wake (0.84); NREM (0.80); N1 (0.72); N2 (0.71); N3 (0.64); REM (0.80) and AHI (0.94). There was substantial agreement between epoch sleep staging scored on the patch-based device and traditional PSG (average Cohen's kappa of 0.62 ± 0.13 across all scorers). The patch-based type-II PSG had a similar performance on sleep staging and respiratory variables when compared to Traditional PSG, thus making it possible to use the patch-based PSG for a routine PSG study. These results open the possibility of performing unattended PSG studies efficiently and accurately outside the sleep laboratory improving access to high quality sleep assessments for patients with sleep disorders. Registry: ClinicalTrials.gov; Identifier: NCT05310708.

Transcriptional regulation of daily sleep amount by TCF4–HDAC4–CREB complex in mice

Abstract Histone deacetylase HDAC4/5 cooperates with cAMP response element-binding protein (CREB) in the transcriptional regulation of daily sleep amount downstream of LKB1-SIK3 kinase cascade in mice. Here, we report a significant enrichment of the E-box motifs for the basic loop–helix–loop (bHLH) proteins near the CREB- and HDAC4-binding sites in the mouse genome. Adeno-associated virus-mediated expression of class I bHLH transcription factors, such as TCF4, TCF3, or TCF12, across the mouse brain neurons reduces the duration of rapid eye movement sleep (REMS) and non-REMS (NREMS). TCF4 requires its bHLH domain to regulate REMS or NREMS amount, of which the latter is mostly independent of the E-box-binding activity. Consistent with that TCF4 interacts with CREB and HDAC4 via the bHLH domain, TCF4 relies on CREB and partly on HDAC4 to regulate NREMS/REMS amount. Conversely, the ability of CREB to regulate sleep duration also requires its binding to TCF4 and HDAC4. Together, these results indicate that TCF4, HDAC4, and CREB could function cooperatively in the transcriptional regulation of daily sleep amount in mice.

Anything but small: Microarousals stand at the crossroad between noradrenaline signaling and key sleep functions.

Continuous sleep restores the brain and body, whereas fragmented sleep harms cognition and health. Microarousals (MAs), brief (3- to 15-s-long) wake intrusions into sleep, are clinical markers for various sleep disorders. Recent rodent studies show that MAs during healthy non-rapid eye movement (NREM) sleep are driven by infraslow fluctuations of noradrenaline (NA) in coordination with electrophysiological rhythms, vasomotor activity, cerebral blood volume, and glymphatic flow. MAs are hence part of healthy sleep dynamics, raising questions about their biological roles. We propose that MAs bolster NREM sleep's benefits associated with NA fluctuations, according to an inverted U-shaped curve. Weakened noradrenergic fluctuations, as may occur in neurodegenerative diseases or with sleep aids, reduce MAs, whereas exacerbated fluctuations caused by stress fragment NREM sleep and collapse NA signaling. We suggest that MAs are crucial for the restorative and plasticity-promoting functions of sleep and advance our insight into normal and pathological arousal dynamics from sleep.

Relating Photoperiod and Outdoor Temperature With Sleep Architecture in Patients With Neuropsychiatric Sleep Disorders.

While artificial light in urban environments was previously thought to override seasonality in humans, recent studies have challenged this assumption. We aimed to explore the relationship between seasonally varying environmental factors and changes in sleep architecture in patients with neuropsychiatric sleep disorders by comparing two consecutive years. In 770 patients, three-night polysomnography was performed at the Clinic for Sleep & Chronomedicine (St. Hedwig Hospital, Berlin, Germany) in 2018/2019. Sleep times were adjusted to patients' preferred schedules, patients slept in, and were unaware of day-night indicators. Digital devices and clocks were not allowed. Days were spent outside the lab with work or naps not allowed. After exclusions (mostly due to psychotropic medication), analysis was conducted on the second PSG-night in 377 patients (49.1 ± 16.8 year; 54% female). Sleep parameters were plotted as 90-day moving-averages (MvA) across date-of-record. Periodicity and seasonal windows in the MvA were identified by utilizing autocorrelations. Linear mixed-effect models were applied to seasonal windows. Sleep parameters were correlated with same-day photoperiod, temperature, and sunshine duration. The MvA of total sleep time (TST) and REM sleep began a 5-month-long decline shortly after the last occurrence of freezing 24-h mean temperatures (correlation of TST between 2018 and 2019 at 2-month lag: rs361 = 0.87, p < 0.001; maximum peak-to-nadir amplitude: ΔTST ~ 62 min, ΔREM ~ 24 min). The MvA nadirs of slow wave sleep (SWS) occurred approximately at the autumnal equinox (correlation between 2018 and 2019: rs361 = 0.83, p < 0.001). Post hoc testing following significant linear mixed-effect model indicate that TST and REM sleep were longer around November till February than May till August (ΔTST = 36 min; ΔREM = 14 min), while SWS was 23 min longer around February till May than August till November. Proportional seasonal variation of SWS and of REM sleep as percentages of TST differed profoundly (SWS = 31.6%; REM = 8.4%). In patients with neuropsychiatric sleep disorders living in an urban environment, data collected in 2018 show similar patterns and magnitudes in seasonal variation of sleep architecture as the 2019 data. Interestingly, whereas SWS patterns were consistent between years with possible links to photoperiod, annual variations of TST and REM sleep seem to be related to times of outside freezing temperature. For generalization, the data need to be confirmed in a healthy population. No clinical trial was registered.

Sleep stages classification based on feature extraction from music of brain.

Sleep stages classification one of the essential factors concerning sleep disorder diagnoses, which can contribute to many functional disease treatments or prevent the primary cognitive risks in daily activities. In this study, A novel method of mapping EEG signals to music is proposed to classify sleep stages. A total of 4.752 selected 1-min sleep records extracted from the capsleep database are applied as the statistical population for this assessment. In this process, first, the tempo and scale parameters are extracted from the signal according to the rules of music, and next by applying them and changing the dominant frequency of the pre-processed single-channel EEG signal, a sequence of musical notes is produced. A total of 19 features are extracted from the sequence of notes and fed into feature reduction algorithms; the selected features are applied to a two-stage classification structure: 1) the classification of 5 classes (merging S1 and REM-S2-S3-S4-W) is made with an accuracy of 89.5% (Cap sleep database), 85.9% (Sleep-EDF database), 86.5% (Sleep-EDF expanded database), and 2) the classification of 2 classes (S1 vs. REM) is made with an accuracy of 90.1% (Cap sleep database),88.9% (Sleep-EDF database), 90.1% (Sleep-EDF expanded database). The overall percentage of correct classification for 6 sleep stages are 88.13%, 84.3% and 86.1% for those databases, respectively. The other objective of this study is to present a new single-channel EEG sonification method, The classification accuracy obtained is higher or comparable to contemporary methods. This shows the efficiency of our proposed method.

Sleep disturbances and their correlation with memory impairment in patients with Alzheimer's disease and amnestic mild cognitive impairment

Background Episodic memory impairment is the core clinical feature of patients with typical Alzheimer's disease (AD) at an early stage. Since sleep plays a very important role in memory consolidation, the relationship between memory impairment and sleep disorders in AD patients is worthy of investigation. Objective To investigate sleep disturbances and their correlations with memory impairment in patients with AD and amnestic mild cognitive impairment (aMCI). Methods Forty-three patients with AD, 43 patients with aMCI, and 43 cognitively unimpaired controls (CUCs) were recruited and subjected to memory assessment via the Hopkins Verbal Learning Test–Revised and objective sleep evaluation via polysomnography (PSG). Results The total sleep time and the percentages of nonrapid eye movement (NREM) sleep stage 3 (N3) and the rapid eye movement (REM) were lower, while the percentages of NREM sleep stage 2 (N2) were greater in the AD and aMCI groups than in the CUC group (all p &lt; 0.01). Compared with the CUC group, the AD group also presented a longer sleep latency and higher NREM sleep stage 1 (N1) percentage, apnea-hypopnea index (AHI), periodic limb movements during sleep index (PLMSI), and arousal index (AI). Both total learning scores and delayed recall scores were positively correlated with the N3 sleep percentage and negatively correlated with the AHI and PLMSI (all p &lt; 0.01). Recognition scores were positively correlated with the N3 sleep percentage and negatively correlated with the AI (all p &lt; 0.01). Conclusions Our results suggest that sleep disturbance is correlated with learning and memory disability in AD and aMCI patients. PSG is useful for screening and monitoring AD.

Anti-IgLON5 Disease 10 Years Later: What We Know and What We Do Not Know.

Anti-IgLON5 disease was identified 10 years ago, thanks to the discovery of IgLON5 antibodies and the joint effort of specialists in sleep medicine, neuroimmunology, and neuropathology. Without this collaboration, it would have been impossible to untangle fundamental aspects of this disease. After the seminal description in 2014, today there is growing evidence that most patients present a chronic progressive course with gait instability, abnormal movements, bulbar dysfunction, and a sleep disorder characterized by nonrapid eye movement and REM parasomnias, and obstructive sleep apnea with stridor. Unlike other autoimmune encephalitides, the response to immunotherapy is suboptimal. Neuropathologic studies in patients with a prolonged clinical course showed a novel 3-repeat and 4-repeat neuronal tauopathy mainly involving the hypothalamus and tegmentum of the brainstem. The absence of tau deposits in the brain of patients who died early, the demonstration that IgLON5 antibodies cause an irreversible decrease in cell-surface levels of IgLON5, and a disorganization of the neuronal cytoskeleton suggest that the disease is primarily autoimmune and the tauopathy a secondary event. After a decade, we now know the disease much better, but important issues still need to be addressed. We have to gather more information on the natural course of the disease, develop better treatments, and identify robust predictors of outcome. More basic research is needed on the physiology of IgLON5, how antibodies disrupt its function, and the downstream effects leading to neurodegeneration. Finally, better designed passive transfer and active immunization models are needed to confirm the pathogenic effect of IgLON5 antibodies.

A thermodynamic model of the REM–NREM sleep cycle

Although many models explain the spontaneous alternation between two distinct sleep states, Rapid Eye Movement (REM) and Non-Rapid Eye Movement (NREM), new empirical evidence has accumulated regarding consistent temperature changes during sleep stage transitions in small animals. The temperature dependence of neuro-excitability and low-frequency (≤4 Hz) neuronal activity has also been investigated theoretically and experimentally. Based on these phenomena, we constructed a stochastic thermodynamic model of the ultradian sleep rhythm. The model was validated through simulation, demonstrating statistical properties that align with experimental data from rats. This model would provide new insights into the mechanisms behind the REM cycle and can be applied in new therapies for sleep disorders.

Evaluation of the sedative-hypnotic effects of Menyanthes trifoliata L. extract in mice.

Insomnia is a pervasive and prominent problem worldwide, afflicting approximately one-third of the population and profoundly affecting patients' quality of life. Efficient and safe sedative-hypnotic medications are required. Menyanthes trifoliata L. (Mt), a sleeping herb in China, is used as a hypnotic remedy in ethnomedicines; however, there are few studies on this herb. We systematically evaluated the potential of Mt as a sedative-hypnotic candidate. The chemical constituents of the Mt extract were analyzed by lLiquid chromatography with photodiode array detection and mass spectrometry (LC-PDA-MS). The sedative-hypnotic effects of Mt extract (0.5, 2, and 4g/kg) were investigated using the pentobarbital-induced sleep test (PIST), the caffeine-induced insomnia model (CIIM), and the open field test (OFT). Furthermore, the effect of Mt on sleep architecture was ‌investigated using electroencephalography/electromyography (EEG/EMG). The safety of the Mt extract was evaluated using the maximum tolerated dose method. Fifteen phenolic compounds were identified based on their UV absorption and MS fragmentation using LC-PDA-MS analysis. In the CIIM, PIST, and OFT, Mt extract exhibited a dose-dependent reduction in sleep latency, an extension of total sleep duration, and a decrease in locomotor activity. Moreover, it increased the duration of non-rapid eye movement (NREM) sleep and reduced wakefulness after one day's administration, according to EEG/EMG. Additionally, no signs of toxicity were observed at a dose of 30g/kg (equivalent to 316.46g/kg of crude drugs). This study supports the potential medicinal use of Mt extract for sleep promotion.

Norepinephrine-mediated slow vasomotion drives glymphatic clearance during sleep.

As the brain transitions from wakefulness to sleep, processing of external information diminishes while restorative processes, such as glymphatic removal of waste products, are activated. Yet, it is not known what drives brain clearance during sleep. We here employed an array of technologies and identified tightly synchronized oscillations in norepinephrine, cerebral blood volume, and cerebrospinal fluid (CSF) as the strongest predictors of glymphatic clearance during NREM sleep. Optogenetic stimulation of the locus coeruleus induced anti-correlated changes in vasomotion and CSF signal. Furthermore, stimulation of arterial oscillations enhanced CSF inflow, demonstrating that vasomotion acts as a pump driving CSF into the brain. On the contrary, the sleep aid zolpidem suppressed norepinephrine oscillations and glymphatic flow, highlighting the critical role of norepinephrine-driven vascular dynamics in brain clearance. Thus, the micro-architectural organization of NREM sleep, driven by norepinephrine fluctuations and vascular dynamics, is a key determinant for glymphatic clearance.

Predicting All-Cause Mortality in Patients With Obstructive Sleep Apnea Using Sleep-Related Features: A Machine-Learning Approach.

Obstructive sleep apnea (OSA) is associated with an increased risk of adverse outcomes, including mortality. Machine-learning algorithms have shown potential in predicting clinical outcomes in patients with OSA. This study aimed to develop and evaluate a machine-learning algorithm for predicting 10- and 15-year all-cause mortality in patients with OSA. Patients with OSA were stratified into deceased and alive groups based on mortality outcomes. Various sleep-related features were analyzed, including objective sleep measures and the heart-rate variability during various sleep stages. The light gradient-boosting machine (LGBM) algorithm was employed to construct a risk-stratification model. The predictive performance of the model was assessed using the area under the receiver operating characteristic curve (AUC) for predicting mortality over 10 and 15 years. Survival analysis was conducted using Kaplan-Meier plots and Cox proportional-hazards model. This study found that parasympathetic activity was higher in OSA patients with worse outcomes than in those with better outcomes. The LGBM-based prediction model with sleep-related features was moderately accurate, with a mean AUC of 0.806 for predicting 10- and 15-year mortality. Furthermore, survival analysis demonstrated that LGBM could significantly distinguish the high- and low-risk groups, as evidenced by Kaplan-Meier plots and Cox regression results. This study has confirmed the potential of sleep-related feature analysis and the LGBM algorithm for evaluating the mortality risk in OSA patients. The developed risk-stratification model offers an efficient and interpretable tool for clinicians that emphasizes the significance of patient-specific autonomic responses in mortality prediction. Incorporating survival analysis further validated the robustness of the model in predicting long-term outcomes.

Phase Angle Between Dim Light Melatonin Onset and Sleep Timing During Residential Treatment Prospectively Predicts Obsessive-Compulsive Symptoms

Phase Angle Between Dim Light Melatonin Onset and Sleep Timing During Residential Treatment Prospectively Predicts Obsessive-Compulsive Symptoms