Journal of Sleep Research最新文献

As sleep restriction has negative effects on performance, ensuring sufficient sleep for shift workers is essential. Quick returns (< 11 h off between shifts) shorten sleep and are associated with increased fatigue and risk of accidents, but there is limited research on other aspects of cognitive performance and work performance. The aim of the present quasi-experimental field study was to investigate the effects of quick returns on objective and subjective measures of sleep, fatigue and cognitive performance. In total 36 newly graduated nurses were followed during two pre-scheduled work periods, with and without a quick return (evening-day-day vs. day-day-day). They kept diaries of sleep and work, wore actigraphy wristbands to record sleep and performed 3 × 3 min smartphone-based cognitive tests (simple reaction time, episodic memory and Stroop) several times daily. Quick returns were found to shorten sleep by 46 min on average, and participants felt less rested in the morning and sleepier throughout the day. Sleep fragmentation and sleep efficiency did not differ between conditions but participants reported poorer sleep quality. Although the nurses reported cognitive impairments after a quick return, the estimated effects on simple attention, episodic memory and Stroop were small and overlapped zero. There were also indications of lingering fatigue on the second day shift after a quick return, but estimates are uncertain. In sum, quick returns shorten sleep and decrease subjective alertness, which could contribute to increased fatigue-related risk at work, but people seem able to mobilise necessary resources to maintain performance on short cognitive tasks.

The mouse sleep is mostly recorded with only epidural electrodes and divided simply into NREM and REM stages. With the help of distributed intracerebral triplet electrodes, we searched for possible new electrophysiological signatures to characterise more specific sleep substages within the timeframe of seconds to tens of minutes. We implanted 17 C57BL/6J male mice with double or triple wire electrodes into the hippocampus, somatosensory cortex and olfactory bulb, conventional skull screw electrodes and neck EMG electrodes. Sessions with at least 1 h of sleep of the 3-h total recording time were included in the analysis. We could identify N1, N2 and N3 stages in the mouse NREM. N2 could be further divided into N2s with spindles and N2n without spindles. Furthermore, N3 following N2n vs. N2s showed different features and were therefore coined N3s and N3n, respectively. The REM could be divided into asynchronous (aREM), synchronous (sREM) and phasic (pREM) substages. The EEG power between 5 and 30 Hz showed quasi-periodic fluctuation at an infra-slow range (0.005-0.02 Hz). The sequence of sleep stages followed reliably this fluctuation, so that the onset of N2n co-occurred with a low power, N2s halfway on the rise, aREM or N3s near the peak and sREM on the descending phase. The infra-slow fluctuation was temporarily abolished by damaging the locus coeruleus noradrenergic axons with the selective neurotoxin DSP-4 or by administration of the alpha-2 adrenergic agonist medetomidine. As a result, the brain got locked in a continuous N3-like state and no REM was present.

Automatic sleep stage classification is essential for enabling non-invasive, at-home monitoring. However, current methods often rely on electroencephalogram (EEG) signals and ad-hoc development approaches that limit reproducibility. We present a reproducible engineering framework for a deep learning model based on the U-Net architecture that classifies sleep into five stages (Wake, N1, N2, N3 and REM) or four (Wake, Light Sleep, Deep Sleep and REM) using only three easily acquired physiological signals: oxygen saturation (SpO), heart rate (HR) and abdominal respiratory effort (AbdRes). In contrast to most previous studies, our model provides sleep stage predictions on a per-second basis, thus overcoming the limitations associated with fixed 30-s epochs. The model was trained on the Sleep Heart Health Study-Visit 2 (SHHS2) dataset and externally validated on the Multi-Ethnic Study of Atherosclerosis (MESA). Optimisation of the model was achieved via Keras Tuner with the Hyperband algorithm. The study achieved weighted F1-scores of 68% (five-stage) and 71% (four-stage) with Cohen's Kappa of 0.61 and 0.67 on SHHS2, with consistent performance on MESA. These results demonstrate strong generalisation and suggest that this lightweight, EEG-free approach offers a practical path towards scalable, clinically relevant sleep monitoring.

While previous research has identified emotional dysregulation and repetitive thinking as contributors to insomnia, the interplay between these factors remains unclear. Building upon data previously collected in our laboratory, this exploratory study extends prior findings by examining the mediating role of rumination, worry and rapid eye movement (REM) sleep instability in the relationship between emotional dysregulation and the functional impact of insomnia and depressive symptoms, aiming to generate hypotheses about the psychological and neurophysiological mechanisms linking these constructs. Using the same cohort of 23 patients with insomnia disorder and 23 matched healthy sleepers, participants underwent overnight polysomnography and completed validated questionnaires assessing emotional dysregulation, worry, rumination and the functional impact of insomnia. Novel mediation models were used to examine whether worry, rumination and REM sleep instability mediated the link between emotional dysregulation and daytime consequences of insomnia. Compared to controls, individuals with insomnia showed significantly greater emotional dysregulation, rumination and worry. Mediation analysis indicated that rumination, but not worry, significantly mediated the relationship between emotional dysregulation and daytime consequences of insomnia. Furthermore, higher scores on the dimension 'difficulties in distracting with emotions' were associated with increased REM sleep instability, which also mediated the effect of emotional dysregulation on daytime consequences of insomnia. These findings highlight the crucial role of rumination in sustaining the functional impact of insomnia and suggest that interventions targeting repetitive negative thinking and emotional regulation may improve sleep outcomes.

Sleep dysfunction can impair cognition and may play a causal role in the development of hallucinations. Deficits in cognitive control have been implicated in cognitive models of hallucinations. To better understand the underpinning role of cognition in the relationship between sleep and hallucinations, the current study aimed to investigate the impact of sleep deprivation on cognitive control mechanisms such as intentional inhibition and working memory, as well as auditory signal detection. Forty-five participants were allocated to either a sleep-deprivation condition (N = 15) or a rested control group condition (N = 30). Cognitive control assessments were applied at three timepoints for each condition: baseline (T1), post-sleep deprivation/post-habitual sleep (T2), and post-recovery sleep/post-habitual daily activity (T3). Results showed significant effects of sleep deprivation on intentional inhibition and working memory, but not auditory signal detection. Findings support current neurocognitive theories and suggest that sleep deprivation may lead to hallucinations through effects on intrusive thoughts and memories. Future research should continue to explore the potential mechanistic pathway between cognitive control and sleep, to inform future intervention work. The study pre-registration, open materials, data, and code are available on the Open Science Framework (doi.org/10.17605/OSF.IO/28SRW).

Central hypersomnia disorder (CHD) may result in a higher risk of injury/accident. The present study aims to investigate the real-world risk by tracing patients in a clinical cohort for 4 years. We tracked the injury/accident risk of CHD clinical cohort patients from Taiwan's National Health Insurance Research Database (NHIRD) and compared it with controls. Data were collected based on the International Classification of Diseases, Tenth Revision. Patients were categorised by diagnosis, gender and age, with each subgroup compared to age- and gender-matched controls. Group differences were analysed using the Chi-square test and t-test. Bonferroni correction was used for post hoc analysis. A total of 386 CHD clinical cohort patients were included. Narcolepsy type 1 patients had the highest subjective and objective symptom severity (p < 0.001). Compared to controls, CHD patients had a significantly higher risk of injury and accident of up to 61.92% and 7.51% during the 4-year follow-up, necessitating clinical visits. Narcolepsy type 2 patients have the highest risk of injury (p = 0.005). Age/gender differences were found. Males had a higher specific-site injury risk (p = 0.045) than females, while females had a higher transportation accident risk than controls (p = 0.048). Children/adolescents had a higher risk in total injury and multiple-site injury than controls (p = 0.024, p = 0.014), and adults had a higher risk in specific-site injury and transportation accident (p = 0.020, p = 0.004). In conclusion, CHD patients had a higher risk of injury/accident, even among those with milder symptoms. Gender and age differences in these risks were observed. Our findings highlight the importance of hypersomnia treatment and individualised considerations in clinical practice.

Multiple sclerosis is frequently associated with sleep disorders. This study aimed to evaluate subjective and objective sleep parameters in de novo relapsing-remitting multiple sclerosis patients compared to healthy controls and to explore correlations with cerebrospinal fluid cytokines. Twenty-one patients underwent CSF cytokine analysis, overnight polysomnography and sleep quality assessments; 21 HCs also participated in sleep evaluations. We analysed sleep macrostructure and the cyclic alternating pattern. Compared to controls, patients exhibited increased sleep period time, time in bed, REM sleep latency, N3 sleep percentage and wakefulness after sleep onset, along with reduced sleep efficiency and REM sleep percentage. These alterations were more pronounced in patients who also had obstructive sleep apnoea. Cyclic alternating pattern analysis revealed increased CAP time and rate-particularly higher A3 indices and duration of A phases-suggesting enhanced sleep fragmentation. A significant association was found between IL-1β and longer Phase B duration, and IL-15 showed a positive correlation with A3 mean duration in the cyclic alternating pattern, indicating inflammatory modulation of sleep architecture. Fatigue was negatively correlated with A1 mean duration and cycle mean duration. These findings demonstrate that de novo relapsing-remitting multiple sclerosis is associated with significant sleep fragmentation, particularly in patients with obstructive sleep apnoea and suggest that pro-inflammatory cytokines might influence sleep homeostasis through adaptive mechanisms. This underscores the importance of addressing sleep quality in multiple sclerosis management.

Three out of 10 older adults are admitted in US hospitals where they are at risk for a decline in physical function. Identifying factors related to sleep and recovery of physical function is key to facilitating independence after discharge. This study examined the association between sleep and functional recovery following an acute hospitalisation in community-dwelling older adults. Participants aged 65+ years (n = 52) were recruited during hospitalisation at the UTMB hospital in Galveston, Texas. Prior to discharge (baseline) and at 4-weeks post-discharge (follow-up), participants completed sleep questionnaires, including PROMIS Sleep-Related Impairment and Sleep Disturbance, as well as physical function testing and questionnaires, Short Physical Performance Battery (SPPB) and PROMIS Physical Function. A subset of participants (n = 24) wore an actigraphy device for 4 weeks post-discharge to record sleep continuity. Separate multivariate regression models were conducted to determine whether baseline sleep predicted physical functioning at follow-up as well as if pre-post hospital changes in sleep predicted pre-post changes in physical functioning. Baseline PROMIS Sleep-Related Impairment was inversely associated with SPPB Balance (p = 0.023), SPPB Chair Stand (p = 0.0406), SPPB Total (p = 0.01), and PROMIS Physical Function (p = 0.008). Change in PROMIS Sleep-Related Impairment between baseline and follow-up was inversely associated with change in SPPB Total (p = 0.03), SPPB Balance (p = 0.0102), and PROMIS Physical Function (p = 0.012). Additionally, change in PROMIS Sleep Disturbance was inversely correlated with change in PROMIS Physical Function (p = 0.04). These results showed that self-reported sleep disturbances and daytime sleep-related impairments during and after hospitalisation predicted physical functioning at 4-weeks post-discharge. Trail Registration: clinicaltrials.gov as NCT02990533.

Insomnia disorder (ID) frequently coexists with substantial psychiatric comorbidity, particularly anxiety and depression. The neurobiological mechanisms underlying the association between ID and emotional dysregulation remain incompletely understood. The locus coeruleus (LC), a pontine nucleus within the ascending reticular activating system, plays a crucial role in sleep-wake regulation and emotional processing. Here, we acquired simultaneous electroencephalography and functional magnetic resonance imaging (EEG-fMRI) data from 37 patients with ID and 30 healthy controls (HCs) during their nocturnal sleep. Group-by-stage interactions in LC-based functional connectivity (FC) were assessed using a linear mixed-effects model. Associations were evaluated between FC patterns and the Pittsburgh sleep quality index (PSQI), the self-rating depression scale (SDS) and the self-rating anxiety scale (SAS). Significant group-by-stage interactions were observed in multiple brain regions, including the cingulate cortex, right insular cortex, left temporal cortex and left insular cortex. Post hoc analyses revealed that patients with ID exhibited significantly enhanced FC between the LC and cingulate cortex during N2 sleep compared to HCs (p = 0.023). In the pooled sample, N2-specific LC-cingulate cortex connectivity strength demonstrated significant positive correlations with both SDS scores (r = 0.337, p = 0.018) and PSQI scores (r = 0.401, p = 0.003). In conclusion, the observed alterations in LC-cingulate cortex FC during N2 sleep suggest a distinct neural circuit that may underlie the dysregulation of emotional processing in ID. These findings may provide insights into neurobiological mechanisms in ID.

Sleep disorders such as obstructive sleep apnea (OSA) may be influenced by environmental exposures, yet the contribution of indoor microbial communities is not well understood. In this study, we examined whether the composition and load of airborne bacteria in bedrooms were associated with the Multivariable Apnea Prediction (MAP) index, a validated indicator of OSA risk. Bedroom air was sampled using electrostatic dust fall collectors in five Nordic centres participating in ECRHS III. Dust was analysed for bacterial load, endotoxin levels, and microbial composition using qPCR, LAL assay, and 16S rRNA sequencing. Associations between microbial exposures and MAP index were assessed using linear regression and categorical MAP cutoffs (≥ 0.5 and ≥ 0.7) adjusting for environmental factors. Bacterial community composition differed significantly between MAP groups, and participants with MAP ≥ 0.7 showed higher bacterial loads. However, alpha diversity and endotoxin levels did not vary by MAP category. A total of 35 bacterial genera were associated with MAP scores; taxa enriched in individuals with higher MAP values were primarily anaerobic and human-associated, whereas negatively associated genera were mostly aerobic and environmental. These findings suggest that the bedroom microbiome may carry a distinct microbial signature related to elevated OSA risk, potentially reflecting or contributing to sleep-disordered breathing.