Sleep Stages Research Articles

Effects and mechanisms of electroacupuncture on fear extinction and sleep phase in single prolonged stress mice

To observe the effects of electroacupuncture (EA) on fear extinction and sleep phase in single prolonged stress (SPS) mice, and explore its mechanism in view of the expression of relevant synaptic proteins. Thirty-two C57BL/6J male mice were randomly divided into a control group, a model group, an EA group and a paroxetine (PRX) group, with 8 mice in each one. Modified SPS method was used to establish PTSD model in the model group, the EA group and the PRX group. Seven days after modeling completion, in the EA group, the intervention was delivered at "Baihui" (GV 20) and bilateral "Zusanli" (ST 36), with disperse-dense wave, 3 Hz/15 Hz in frequency and 1 mA in current intensity, for 30 min. In the PRX group, paroxetine solution (2.5 g/L) was administered intragastrically (10 mg/kg). The intervention was given once daily and for consecutive 10 days in the above two groups. The fear conditioning task and the elevated plus-maze test were adopted to evaluate the fear extinction and anxiety of the mice in each group. Using Medusa electroencephalogram (EEG) and electromyography (EMG) recording system from rats and mice, the sleep phase was determined in the mice. With Western blot method adopted, the protein expression of the postsynaptic density protein 95 (PSD95), activity-regulated cytoskeleton-associated protein (ARC), brain-derived neurotrophic factor (BDNF), N-methyl-D-aspartic acid receptor 2A (GluN2A), N-methyl-D-aspartic acid receptor 2B (GluN2B) and alpha-amino-3-hydroxy-5-methyl-4-isoxazole-propionic acid receptor 1 (GluA1) in the hippocampus was detected in the mice. Compared with the control group, the freezing time for the fear re-exposure in 3 min to 15 min and the fear extinction in 0 min to 3 min were prolonged (P<0.05), the fear extinction index decreased (P<0.05), and the open arm time (OT) of the elevated plus-maze was shortened (P<0.05) in the model group. When compared with the model group, in the EA group and the PRX group, the freezing time for the fear re-exposure in 3 min to 6 min and 12 min to 15 min, as well as the fear extinction in 0 min to 3 min was shortened (P<0.05), the fear extinction index increased (P<0.05); the OT in elevated plus-maze was longer in the mice of the EA group (P<0.05). The period of wake (Wake) was prolonged (P<0.05), the non-rapid eye movement period (NREM) and the total sleep time (Sleep) were reduced in the model group (P<0.05) in comparison with the control group. Compared with the model group, the Wake was declined (P<0.05), and the NREM and Sleep increased in the EA group and the PRX group (P<0.05). When compared with the control group, the protein expression of PSD95, ARC, BDNF, GluN2A and GluA1 in the hippocampus decreased (P<0.05), and that of GluN2B increased (P<0.05) in the model group. In the EA group and the PRX group, the protein expression of PSD95, ARC, BDNF, GluN2A and GluA1 in the hippocampus was elevated (P<0.05), and that of GluN2B reduced (P<0.05) when compared with the model group. Electroacupuncture at "Baihui" (GV 29) and "Zusanli" (ST 36) can ameliorate anxiety-like behavior, fear extinction disorder and abnormal sleep phase in SPS mice, which may be related to the regulation of synaptic transmission and synaptic plasticity expression in the hippocampus.

Cerebral Gray Matter May Not Explain Sleep Slow-Wave Characteristics after Severe Brain Injury.

Sleep slow waves are the hallmark of deeper non-rapid eye movement sleep. It is generally assumed that gray matter properties predict slow-wave density, morphology, and spectral power in healthy adults. Here, we tested the association between gray matter volume (GMV) and slow-wave characteristics in 27 patients with moderate-to-severe traumatic brain injury (TBI, 32.0 ± 12.2 years old, eight women) and compared that with 32 healthy controls (29.2 ± 11.5 years old, nine women). Participants underwent overnight polysomnography and cerebral MRI with a 3 Tesla scanner. A whole-brain voxel-wise analysis was performed to compare GMV between groups. Slow-wave density, morphology, and spectral power (0.4-6 Hz) were computed, and GMV was extracted from the thalamus, cingulate, insula, precuneus, and orbitofrontal cortex to test the relationship between slow waves and gray matter in regions implicated in the generation and/or propagation of slow waves. Compared with controls, TBI patients had significantly lower frontal and temporal GMV and exhibited a subtle decrease in slow-wave frequency. Moreover, higher GMV in the orbitofrontal cortex, insula, cingulate cortex, and precuneus was associated with higher slow-wave frequency and slope, but only in healthy controls. Higher orbitofrontal GMV was also associated with higher slow-wave density in healthy participants. While we observed the expected associations between GMV and slow-wave characteristics in healthy controls, no such associations were observed in the TBI group despite lower GMV. This finding challenges the presumed role of GMV in slow-wave generation and morphology.

Automated remote sleep monitoring needs uncertainty quantification.

Wearable electroencephalography devices emerge as a cost-effective and ergonomic alternative to gold-standard polysomnography, paving the way for better health monitoring and sleep disorder screening. Machine learning allows to automate sleep stage classification, but trust and reliability issues have hampered its adoption in clinical applications. Estimating uncertainty is a crucial factor in enhancing reliability by identifying regions of heightened and diminished confidence. In this study, we used an uncertainty-centred machine learning pipeline, U-PASS, to automate sleep staging in a challenging real-world dataset of single-channel electroencephalography and accelerometry collected with a wearable device from an elderly population. We were able to effectively limit the uncertainty of our machine learning model and to reliably inform clinical experts of which predictions were uncertain to improve the machine learning model's reliability. This increased the five-stage sleep-scoring accuracy of a state-of-the-art machine learning model from 63.9% to 71.2% on our dataset. Remarkably, the machine learning approach outperformed the human expert in interpreting these wearable data. Manual review by sleep specialists, without specific training for sleep staging on wearable electroencephalography, proved ineffective. The clinical utility of this automated remote monitoring system was also demonstrated, establishing a strong correlation between the predicted sleep parameters and the reference polysomnography parameters, and reproducing known correlations with the apnea-hypopnea index. In essence, this work presents a promising avenue to revolutionize remote patient care through the power of machine learning by the use of an automated data-processing pipeline enhanced with uncertainty estimation.

Effect of Physical Exercise on Sleep Quality in College Athletes in Malaysia

Purpose: The aim of the study was to analyze the effect of physical exercise on sleep quality in college athletes in Malaysia. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: Research on college athletes in Malaysia reveals that regular physical exercise significantly improves sleep quality by increasing sleep duration and efficiency. Exercise reduces sleep latency, helping athletes fall asleep faster, and enhances deep sleep stages crucial for recovery. Additionally, physical activity aids in managing stress and anxiety, which are linked to poor sleep. However, the impact of exercise can vary depending on its intensity and timing. Unique Contribution to Theory, Practice and Policy: The theory of exercise and sleep interactions, the cognitive behavioral theory of insomnia (CBT-I) &amp; the circadian rhythm theory may be used to anchor future studies on the effect of physical exercise on sleep quality in college athletes in Malaysia. Athletic trainers and coaches should design personalized exercise regimens that include a mix of aerobic, resistance, and flexibility exercises tailored to individual athletes' needs. Sports organizations and educational institutions should establish policies that recommend optimal timing for workouts. Research indicates that morning sessions are less disruptive to sleep than evening sessions, and such guidelines can help in scheduling training sessions to promote better sleep quality.

Relationship between Sports Participation and Academic Discipline in Middle School Students in Egypt

Purpose: The aim of the study was to analyze the relationship between sports participation and academic discipline in middle school students in Egypt. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: Research on college athletes in Malaysia reveals that regular physical exercise significantly improves sleep quality by increasing sleep duration and efficiency. Exercise reduces sleep latency, helping athletes fall asleep faster, and enhances deep sleep stages crucial for recovery. Additionally, physical activity aids in managing stress and anxiety, which are linked to poor sleep. However, the impact of exercise can vary depending on its intensity and timing. Unique Contribution to Theory, Practice and Policy: Self-determination theory (SDT), social cognitive theory (SCT) &amp; achievement goal theory (AGT) may be used to anchor future studies on the relationship between sports participation and academic discipline in middle school students in Egypt. Schools should implement structured sports programs that emphasize not only physical skills but also the development of discipline, teamwork, and time management. Schools should adopt policies that promote the integration of sports and academics, ensuring that sports participation is not viewed as a distraction but as a complementary activity that enhances academic discipline.

Scheduled feeding improves sleep in a mouse model of Huntington’s disease

Sleep disturbances are common features of neurodegenerative disorders including Huntington’s disease (HD). Sleep and circadian disruptions are recapitulated in animal models, providing the opportunity to evaluate the effectiveness of circadian interventions as countermeasures for neurodegenerative disease. For instance, time restricted feeding (TRF) successfully improved activity rhythms, sleep behavior and motor performance in mouse models of HD. Seeking to determine if these benefits extend to physiological measures of sleep, electroencephalography (EEG) was used to measure sleep/wake states and polysomnographic patterns in male and female wild-type (WT) and bacterial artificial chromosome transgenic (BACHD) adult mice, under TRF and ad lib feeding (ALF). Our findings show that male, but not female, BACHD mice exhibited significant changes in the temporal patterning of wake and non-rapid eye movement (NREM) sleep. The TRF intervention reduced the inappropriate early morning activity by increasing NREM sleep in the male BACHD mice. In addition, the scheduled feeding reduced sleep fragmentation (# bouts) in the male BACHD mice. The phase of the rhythm in rapid-eye movement (REM) sleep was significantly altered by the scheduled feeding in a sex-dependent manner. The treatment did impact the power spectral curves during the day in male but not female mice regardless of the genotype. Sleep homeostasis, as measured by the response to six hours of gentle handling, was not altered by the diet. Thus, TRF improves the temporal patterning and fragmentation of NREM sleep without impacting sleep homeostasis. This work adds critical support to the view that sleep is a modifiable risk factor in neurodegenerative diseases.

The Impact of Lunch Timing on Nap Quality

Purpose: Previous research has established that food intake is a biological regulator of the human sleep–wake cycle. As such, the timing of eating relative to sleep may influence the quality of sleep, including daytime naps. Here, we examine whether the timing of lunch (1 h vs. 2 h interval between lunch and a napping opportunity) impacts the quality of an afternoon nap. Methods: Using a randomized within-subject design over two separate experimental sessions (7 days apart), participants (n = 40, mean age = 25.8 years) consumed lunch 1 h and 2 h prior to an afternoon nap opportunity. Polysomnography and subjective self-reports were used to assess sleep architecture, sleepiness levels, and nap quality. Results: Results revealed no significant differences in subjective ratings of sleep quality and sleepiness, or in sleep architecture (total sleep time, sleep efficiency, sleep onset latency, sleep stages) between the 1 h and 2-h lunch conditions. Conclusions: All sleep measures were similar when napping followed eating by either 1 h or 2 h, suggesting that eating closer to nap onset may not negatively impact sleep architecture and quality. Future research should continue to identify conditions that improve nap quality, given the well-documented benefits of naps to reduce sleep pressure and improve human performance.

The Interactions between Smoking and Sleep

Smoking a cigarette before bed or first thing in the morning is a common habit. In this review, the relationship between smoking and sleep is investigated based on the existing literature. Out of 6504 unique items that were identified via a PubMed search related to smoking and sleep, 151 were included in this review. Tobacco smoking disrupts sleep architecture by reducing slow wave and rapid eye movement (REM) sleep and undermining sleep quality. Furthermore, smoking affects sleep-related co-morbidities, such as obstructive sleep apnea–hypopnea syndrome (OSAHS), insomnia, parasomnias, arousals, bruxism, and restless legs, as well as non-sleep-related conditions such as cardiovascular, metabolic, respiratory, neurologic, psychiatric, inflammatory, gynecologic and pediatric issues, while poor sleep quality also seems to worsen the chances of successful smoking cessation. In conclusion, the existing literature suggests that there is a wicked relation between smoking and sleep.

GBA-AAV mitigates sleep disruptions and motor deficits in mice with REM sleep behavior disorder

Sleep disturbances, including rapid eye movement sleep behavior disorder (RBD), excessive daytime sleepiness, and insomnia, are common non-motor manifestations of Parkinson’s disease (PD). Little is known about the underlying mechanisms, partly due to the inability of current rodent models to adequately mimic the human PD sleep phenotype. Clinically, increasing studies have reported that variants of the glucocerebrosidase gene (GBA) increase the risk of PD. Here, we developed a mouse model characterized by sleep–wakefulness by injecting α-synuclein preformed fibronectin (PFF) into the sublaterodorsal tegmental nucleus (SLD) of GBA L444P mutant mice and investigated the role of the GBA L444P variant in the transition from rapid eye movement sleep behavior disorder to PD. Initially, we analyzed spectral correlates of REM and NREM sleep in GBA L444P mutant mice. Importantly, EEG power spectral analysis revealed that GBA L444P mutation mice exhibited reduced delta power during non-rapid eye movement (NREM) sleep and increased theta power (8.2–10 Hz) in active rapid eye movement (REM) sleep phases. Our study revealed that GBA L444P-mutant mice, after receiving PFF injections, exhibited increased sleep fragmentation, significant motor and cognitive dysfunctions, and loss of dopaminergic neurons in the substantia nigra. Furthermore, the over-expression of GBA-AAV partially improved these sleep disturbances and motor and cognitive impairments. In conclusion, we present the initial evidence that the GBA L444P mutant mouse serves as an essential tool in understanding the complex sleep disturbances associated with PD. This model further provides insights into potential therapeutic approaches, particularly concerning α-synuclein accumulation and its subsequent pathological consequences.

GRU-powered sleep stage classification with permutation-based EEG channel selection

We present a new approach to classifying the sleep stage that incorporates a computationally inexpensive method based on permutations for channel selection and takes advantage of deep learning power, specifically the gated recurrent unit (GRU) model, along with other deep learning methods. By systematically permuting the electroencephalographic (EEG) channels, different combinations of EEG channels are evaluated to identify the most informative subset for the classification of the 5-class sleep stage. For analysis, we used an EEG dataset that was collected at the International Institute for Integrative Sleep Medicine (WPI-IIIS) at the University of Tsukuba in Japan. The results of these explorations provide many new insights such as the (1) drastic decrease in performance when channels are fewer than 3, (2) 3-random channels selected by permutation provide the same or better prediction than the 3 channels recommended by the American Academy of Sleep Medicine (AASM), (3) N1 class suffers the most in prediction accuracy as the channels drop from 128 to 3 random or 3 AASM, and (4) no single channel provides acceptable levels of accuracy in the prediction of 5 classes. The results obtained show the GRU’s ability to retain essential temporal information from EEG data, which allows capturing the underlying patterns associated with each sleep stage effectively. Using permutation-based channel selection, we enhance or at least maintain as high model efficiency as when using high-density EEG, incorporating only the most informative EEG channels.

Effects of repeated cryostimulation exposures on sleep and wellness in healthy young adults

The aim of this study was to evaluate the effects of daily whole-body cryostimulation (WBC) sessions during 5 consecutive days on wellness and sleep parameters in healthy young men and women. Twenty healthy subjects (9 women; 11 men) aged 23.1 ± 2.6 years old participated in this randomized protocol, with 5 consecutive days with (CRYO) or without WBC (CONT) exposure. Sleep was analyzed over the 5 nights in each condition. Sleep quality and quantity were assessed via actimetry, cerebral activity and questionnaires. Nocturnal heart rate variability (HRV) was also recorded and questionnaires were given to assess wellness and mood. Repeated WBC exposures had a beneficial impact on mood and anxiety. It also improved subjective sleep quality (scored from 3.6 ± 0.5 pre to 3.9 ± 0.3), especially in women. Also, repeated WBC sessions modulated sleep architecture by increasing slow wave sleep duration (+7.3 ± 16.8 min) during the nights without impacting other sleep parameters, nor nocturnal HRV. In conclusion, repeated WBC seems to be an effective strategy to improve slow wave sleep duration in healthy young subjects. The reported psychological improvements may better benefit women than men.

Sleep stages detection based on analysis and optimisation of non-linear brain signal parameters

The analysis and detection of sleep stages continue to preoccupy researchers, particularly bioinformaticians and neurologists aiming to understand various aspects and functioning of the brain during sleep cycles. This understanding is crucial for developing systems capable of early diagnosis of sleep disorders and adapting these systems for use in operating rooms to monitor the brain activity of patients under sedation or anesthesia. In this study, we apply a set of methods to process and decompose the single-channel EEG neural signal into different brain waves such as beta, alpha, theta, and delta. We then focus on the analysis and optimization of the extracted non-linear features using Principal Component Analysis (PCA) to improve the performance and robustness of the classification of six sleep stages. Classifier validation is performed using the cross-validation method. The results show that when the dimensions of the combined non-linear features are reduced, the RF-PCA model achieves an accuracy of 95.2%, outperforming other models such as MLP, SVM, DT, and GB, as well as recent studies. These findings validate the effectiveness of the system, indicating its potential for embedded implementation in practical applications for sleep disorder diagnosis and monitoring.

The effect of central sleep apnea on sleep architecture in children with obstructive sleep apnea

ObjectiveThis study aimed to investigate how central sleep apnea (CSA) impacts sleep patterns in children with obstructive sleep apnea (OSA). MethodsChildren undergoing polysomnography (PSG) were enrolled and sorted into two groups: those with OSA alone (Group A) and those with both OSA and CSA (CAI < 1 nd: children with 10% CSA or more and less than 50%, Group B). Statistical analysis was conducted to compare sleep structure and clinical features between Group A and Group B. ResultsGroup B exhibited significantly higher respiratory events,apnea hypoventilation index,apnea index and oxygen desaturation index (ODI) compared toGroup A (p < 0.05). Group B also showed higher total sleep time and arousal index than Group A (P < 0.05). The proportion of time spent in stage N3 was lower in Group B than in Group A (P < 0.05). Moreover, mean heart rate and minimum heart rate were higher in Group B compared to Group A (P < 0.05).Minimum oxygenation levels( including non-rapid eye movement (NREM) stages) were lowe in Group B than in Group A (P < 0.05). Additionally, the prevalence of positional obstructive sleep apnea (P-OSA) was greater in Group B than in Group A (P < 0.05). ConclusionIn comparison to those with OSA alone, children with OSA and concurrent CSA exhibited distinct sleep patterns, including reduced N3uration, higher arousal index, longer respiratory events, higher ODI, and lower oxygen saturation,higher heart rate

Efficacy of hyperbaric oxygen therapy as an adjunct therapy in the treatment of sleep disorders among patients with Parkinson’s disease: a meta-analysis

ObjectiveTo systematically evaluate the efficacy of hyperbaric oxygen therapy (HBOT) as an adjunct therapy for treating sleep disorders in patients with Parkinson’s disease (PD).MethodsWe conducted comprehensive searches in eight databases from inception through September 2023, including PubMed, Cochrane Library, Embase, Web of Science, SinoMed, China National Knowledge Infrastructure (CNKI), China Science and Technology Periodical Database (VIP), and Wanfang Database. The objective was to identify randomized controlled trials (RCTs) evaluating HBOT’s effectiveness in alleviating sleep disorder symptoms in PD patients as an adjunct therapy. Literature screening and data extraction were independently executed by the authors. Meta-analyses were performed using Review Manager 5.3 software, and publication bias and sensitivity analyses were assessed using Stata 17.0 software.ResultsSeven RCTs involving 461 participants were included. The findings revealed that the addition of HBOT significantly enhanced sleep efficiency (MD = 15.26, 95% CI [10.89, 19.63], p &amp;lt; 0.00001), increased time in bed (MD = 69.65, 95% CI [43.01, 96.30], p &amp;lt; 0.00001), total sleep time (MD = 75.87, 95% CI [25.42, 126.31], p = 0.003), slow-wave sleep (SWS) time (MD = 6.14, 95% CI [3.95, 8.34], p &amp;lt; 0.00001), and rapid eye movement sleep (REM) time (MD = 4.07, 95% CI [2.05, 6.08], p &amp;lt; 0.0001), and reduced awakening frequency (MD = −11.55, 95% CI [−15.42, −7.68], p &amp;lt; 0.00001) and sleep latency (MD = −6.60, 95% CI [−9.43, −3.89], p &amp;lt; 0.00001). Additionally, significant improvements were observed in the Pittsburgh Sleep Quality Index (PSQI) (MD = −2.52, 95% CI [−2.85, −2.18], p &amp;lt; 0.00001), Epworth Sleepiness Scale (ESS) (MD = −2.90, 95% CI [−3.34, −2.47], p &amp;lt; 0.00001), Unified Parkinson’s Disease Rating Scale Part III (UPDRS III) (MD = −1.32, 95% CI [−2.16, −0.47], p = 0.002), and Hoehn and Yahr grading (H-Y grading) (MD = −0.15, 95% CI [−0.28, −0.01], p = 0.03).ConclusionThe current meta-analysis supports the efficacy of HBOT as an adjunct therapy in managing sleep disorders in PD patients. It is recommended for PD patients experiencing sleep disturbances.Systematic review registration:https://www.crd.york.ac.uk/, identifier: CRD42023462201.

Sleep stages and brain oscillations: An in-depth analysis using quantitative and mathematical models

Sleep stages and brain oscillations: An in-depth analysis using quantitative and mathematical models

Prognostic Factors Related to Sleep Quality in Patients With Obstructive Sleep Apnea After Positive Airway Pressure Therapy

Background and Objectives: This study aimed to evaluate the factors that influence deep sleep restoration in patients with obstructive sleep apnea (OSA) following positive airway pressure (PAP) therapy.Methods: In total, 363 patients diagnosed with OSA who received PAP therapy over at least 3 months were enrolled in the study. Polysomnographic parameters, anatomical characteristics, and subjective sleep-related parameters were evaluated according to the presence of daytime sleepiness and morning headache before and after 3 months of PAP treatment.Results: Age was significantly different according to whether excessive daytime sleepiness (EDS) was alleviated (average: 49.35 years) or persisted (average: 52.82 years) (p=0.001). Age was also significantly associated with morning headache (p=0.037). Body mass index (BMI) was higher in the alleviated EDS group (28.70 kg/m&lt;sup&gt;2&lt;/sup&gt;) than in the persistent EDS group (27.13 kg/m&lt;sup&gt;2&lt;/sup&gt;; p=0.002). The apnea-hypopnea index (AHI) was correlated with the EDS outcome (p=0.011). The group with alleviated EDS had a longer mandibular plane to hyoid distance (MPH) than the group with persistent EDS (17.95 mm vs. 15.38 mm; p&lt;0.001). However, BMI, AHI, and MPH showed no significant associations with morning headache. Epworth Sleepiness Scale scores were higher in the alleviated EDS and alleviated morning headache groups (EDS: p&lt;0.001, morning headache: p=0.001). Self-Efficacy Measure for Sleep Apnea (SEMSA) values differed significantly between the EDS groups (p&lt;0.001), but not between the morning headache groups (p=0.122). After 3 months of PAP therapy, the MPH was negatively correlated with EDS in univariate (odds ratio [OR]=0.921, p&lt;0.001) and multivariate analyses (OR=0.937, p=0.028). The SEMSA score was also negatively correlated with EDS in univariate (OR=0.961, p&lt;0.001) and multivariate (OR=0.973, p=0.019) analyses.Conclusion: Age, polysomnographic metrics, and anatomical considerations were important for sleep quality-associated daytime symptoms. In addition, anatomical characteristics and the patient’s self-efficacy were significantly associated with the effect of PAP treatment on sleep quality.

Melatonin targets the paraventricular thalamus to promote non-rapid eye movement sleep in C3H/HeJ mice.

Melatonin (MLT) is an important circadian signal for sleep regulation, but the neural circuitries underlying the sleep-promoting effects of MLT are poorly understood. The paraventricular thalamus (PVT) is a critical thalamic area for wakefulness control and expresses MLT receptors, raising a possibility that PVT neurons may mediate the sleep-promoting effects of MLT. Here, we found that MLT receptors were densely expressed on PVT neurons and exhibited circadian-dependent variations in C3H/HeJ mice. Application of exogenous MLT decreased the excitability of PVT neurons, resulting in hyperpolarization of membrane potential and reduction of action potential firing. MLT also inhibited the spontaneous activity of PVT neurons at both population and single-neuron levels in freely behaving mice. Furthermore, pharmacological manipulations revealed that local infusion of exogeneous MLT into the PVT promoted non-rapid eye movement (NREM) sleep and increased NREM sleep duration, whereas MLT receptor antagonists decreased NREM sleep. Moreover, we found that selectively knocking down endogenous MLT receptors in the PVT decreased NREM sleep and correspondingly increased wakefulness, with particular changes shortly after the onset of the dark or light phase. Taken together, these results demonstrate that PVT is an important target of MLT for promoting NREM sleep.

Dexmedetomidine Promotes NREM Sleep by Depressing Oxytocin Neurons in the Paraventricular Nucleus in Mice.

Dexmedetomidine (DEX) is a highly selective α2-adrenoceptor agonist with sedative effects on sleep homeostasis. Oxytocin-expressing (OXT) neurons in the paraventricular nucleus (PVN) of the hypothalamus (PVNOXT) regulate sexual reproduction, drinking, sleep-wakefulness, and other instinctive behaviors. To investigate the effect of DEX on the activity and signal transmission of PVNOXT in regulating the sleep-wakefulness cycle. Here, we employed OXT-cre mice to selectively target and express the designer receptors exclusively activated by designer drugs (DREADD)-based chemogenetic tool hM3D(Gq) in PVNOXT neurons. Combining chemogenetic methods with electroencephalogram (EEG) /electromyogram (EMG) recordings, we found that cannula injection of DEX in PVN significantly increased the duration of non-rapid eye movement (NREM) sleep in mice. Furthermore, the chemogenetic activation of PVNOXT neurons using i.p. injection of clozapine N-oxide (CNO) after cannula injection of DEX to PVN led to a substantial increase in wakefulness. Electrophysiological results showed that DEX decreased the frequency of action potential (AP) and the spontaneous excitatory postsynaptic current (sEPSC) of PVNOXT neurons through α2-adrenoceptors. Therefore, these results identify that DEX promotes sleep and maintains sleep homeostasis by inhibiting PVNOXT neurons through the α2-adrenoceptor.

Assessment of Sleep Stages in Unconscious Patients with Acute Severe Traumatic Brain Injury

Abstract Background The existence of a sleep cycle in deeply unconscious patients with severe traumatic brain injury (TBI) remains unknown. Evaluating the sleep patterns of these patients may provide insights into their consciousness and help predict functional recovery. Aims and Objectives This prospective observational study aimed to assess the usefulness of monitoring the sleep cycle in the prognostication of unconscious TBI patients. Materials and Methods A purposive sampling technique was employed to include 39 patients with severe TBI (Glasgow Coma Scale [GCS] ≤ 8). The average GCS score at admission was (5.76 ± 1.65). Sleep was monitored using an actigraphy smartwatch for 4 consecutive days, (3.15 ± 2.49) days postbrain injury. Sleep cycle monitoring tool and unconscious patient outcome monitoring tool were employed. An outcome assessment was done based on the GCS score. Results Severe TBI patients exhibit intact sleep cycle (i.e., deep sleep, light sleep, and rapid eye movement sleep) despite being deeply unconscious, even in the acute stage. Total sleep duration was found to be significantly higher at a mean of 19.97 hours as compared to the mean of 8 hours as per the smartwatch reference value for normal individuals. Patients with improved sleep cycles had a higher likelihood of GCS improvement (p &lt; 0.05). Conclusion This study is the first of its kind to demonstrate that the sleep cycle is a reliable prognostic factor for the recovery of consciousness in the acute phase of severe TBI among unconscious patients, with improvement in the sleep cycle mirroring neurological improvement.

Habitual rapid eye movementsleep predicts changes in test-anxiety levels weeks in advance.

Previous research has linked rapid eye movement sleep to emotional processing, particularly stress. Lab studies indicate that rapid eye movement sleep deprivation and fragmentation heighten emotional reactivity and stress response. This relationship extends to natural settings, where poor-quality sleep among college students correlates with increased academic stress and lower academic performance. However, there is a lack of research into how specific sleep stages, like rapid eye movement, affect real-life stress development. This study investigated whether habitual rapid eye movement sleep in college students can predict the future development of real-life stress symptoms associated with final exams. Fifty-two participants (mean age = 19 years, 62% females) monitored their sleep for a week during the academic semester using a mobile electroencephalogram device, and then completed self-evaluations measuring test anxiety and other relevant factors. They completed the same evaluations again just prior to final exams. We found that rapid eye movement sleep was the most dominant factor predicting changes in participants' test anxiety. However, contrasting with our predictions, habitual rapid eye movement sleep was associated with an increase rather than decrease in anxiety. We discuss these results in terms of the rapid eye movement recalibration hypothesis, which suggests rapid eye movement sleep modulates activity in stress-encoding areas in the brain, leading to both decreased sensitivity and increased selectivity of stress responses.