Sleep Structure Research Articles

Sleep Disruption and Cancer: Chicken or the Egg?

Sleep is a nearly ubiquitous phenomenon across the phylogenetic tree, highlighting its essential role in ensuring fitness across evolutionary time. Consequently, chronic disruption of the duration, timing, or structure of sleep can cause widespread problems in multiple physiological systems, including those that regulate energy balance, immune function, and cognitive capacity, among others. Many, if not all these systems, become altered throughout the course of cancer initiation, growth, metastatic spread, treatment, and recurrence. Recent work has demonstrated how changes in sleep influence the development of chronic diseases, including cancer, in both humans and animal models. A common finding is that for some cancers (e.g., breast), chronic disruption of sleep/wake states prior to disease onset is associated with an increased risk for cancer development. Additionally, sleep disruption after cancer initiation is often associated with worse outcomes. Recently, evidence suggesting that cancer itself can affect neuronal circuits controlling sleep and wakefulness has accumulated. Patients with cancer often report difficulty falling asleep, difficulty staying asleep, and severe fatigue, during and even years after treatment. In addition to the psychological stress associated with cancer, cancer itself may alter sleep homeostasis through changes to host physiology and via currently undefined mechanisms. Moreover, cancer treatments (e.g., chemotherapy, radiation, hormonal, and surgical) may further worsen sleep problems through complex biological processes yet to be fully understood. This results in a “chicken or the egg” phenomenon, where it is unclear whether sleep disruption promotes cancer or cancer reciprocally disrupts sleep. This review will discuss existing evidence for both hypotheses and present a framework through which the interactions between sleep and cancer can be dissociated and causally investigated.

Sex-Specific Difference in the Effect of Altitude on Sleep and Nocturnal Breathing in Young Healthy Volunteers.

Importance: To date, there is no established evidence of sex-specific differences in altitude-induced sleep-disordered breathing (SDB) during polysomnography-confirmed sleep. Objective: The aim of this study was to investigate whether differences in sex play a pivotal role in incidences of SDB and acute mountain sickness (AMS) when staying overnight at high altitude. Design: This was a prospective cohort study. Setting: Participants underwent overnight polysomnography (PSG) and clinical assessment in a sleep laboratory at 500 m and two consecutive days at 3270 m. Participants: The participants comprised 28 (18 women) healthy, young, low-altitude residents with a median (interquartile range) age of 26.0 (25.0, 28.0) years. Exposures: Altitude exposure. Main outcomes and Measures: The primary outcome was altitude-induced change in the PSG-confirmed apnea–hypopnea index (AHI) at 3270 m compared to 500 m between men and women. Secondary outcomes included sex differences in other parameters related to SDB, sleep structure, AMS, psychomotor vigilance test reaction time and parameters from arterial and venous blood analyses. Results: The median (interquartile range) AHIs at 500 m and 3270 m on night 1 and on night 2 were 6.5/h (3.6, 9.1), 23.7/h (16.2, 42.5) and 15.2/h (11.8, 20.9) in men, respectively, and 2.2/h (1.0, 5.5), 8.0/h (5.3, 17.0) and 7.1/h (4.9, 11.5) in women, respectively (p < 0.05 nights 1 and 2 at 3270 m vs. 500 m in men and women). The median difference (95% CI) of altitude-induced change in AHI (3270 m night 1 compared to 500 m) between men and women was 11.2/h (1.9 to 19.6) (p < 0.05). Over the time course of 2 days at 3270 m, 9 out of 18 (50%) women and 1 out of 10 (10%) men developed AMS (p < 0.05 women versus men). Conclusions and Relevance: This prospective cohort study showed that men were more susceptible to altitude-induced SDB but that they had a lower AMS incidence when staying for 2 days at 3270 m than women. These findings indicate that sex-related prevention and intervention strategies against SDB and AMS are highly warranted. Trial Registration: This trial was registered at the Chinese Clinical Trial Registry; No. ChiCTR1800020155.

Can Daytime Transcranial Direct Current Stimulation Treatment Change the Sleep Electroencephalogram Complexity of REM Sleep in Depressed Patients? A Double-Blinded, Randomized, Placebo-Controlled Trial.

Study ObjectivesThe purpose of this study was to determine the effects of daytime transcranial direct current stimulation (tDCS) on sleep electroencephalogram (EEG) in patients with depression.MethodsThe study was a double-blinded, randomized, controlled clinical trial. A total of 37 patients diagnosed with a major depression were recruited; 19 patients (13 females and 6 males mean age 44.79 ± 15.25 years) received tDCS active stimulation and 18 patients (9 females and 9 males; mean age 43.61 ± 11.89 years) received sham stimulation. Ten sessions of daytime tDCS were administered with the anode over F3 and the cathode over F4. Each session delivered a 2 mA current for 30 min per 10 working days. Hamilton-24 and Montgomery scales were used to assess the severity of depression, and polysomnography (PSG) was used to assess sleep structure and EEG complexity. Eight intrinsic mode functions (IMFs) were computed from each EEG signal in a channel. The sample entropy of the cumulative sum of the IMFs were computed to acquire high-dimensional multi-scale complexity information of EEG signals.ResultsThe complexity of Rapid Eye Movement (REM) EEG signals significantly decreased intrinsic multi-scale entropy (iMSE) (1.732 ± 0.057 vs. 1.605 ± 0.046, P = 0.0004 in the case of the C4 channel, IMF 1:4 and scale 7) after tDCS active stimulation. The complexity of the REM EEG signals significantly increased iMSE (1.464 ± 0.101 vs. 1.611 ± 0.085, P = 0.001 for C4 channel, IMF 1:4 and scale 7) after tDCS sham stimulation. There was no significant difference in the Hamilton-24 (P = 0.988), Montgomery scale score (P = 0.726), and sleep structure (N1% P = 0.383; N2% P = 0.716; N3% P = 0.772) between the two groups after treatment.ConclusionDaytime tDCS changed the complexity of sleep in the REM stage, and presented as decreased intrinsic multi-scale entropy, while no changes in sleep structure occurred. This finding indicated that daytime tDCS may be an effective method to improve sleep quality in depressed patients. Trial registration This trial has been registered at the ClinicalTrials.gov (protocol ID: TCHIRB-10409114, in progress).

Pediatric sleep and pain: etiologies, consequences, and clinical considerations.

To examine current evidence of the relationship between sleep and pain from the neonatal period through adolescence. This review serves as a critical review of the literature and of the needs for future research on pediatric sleep and pain. The PubMed online database was queried from January 1, 1960, to March 1, 2020, producing 149 articles applicable to pain and sleep in the pediatric population. Of those, 97 articles were cited in this review with the key articles including over 3800 participants. The pediatric literature supports the relationship between poor sleep (both sleep efficiency and nighttime awakenings) and subsequent risk for pain, especially among children with chronic disease. The reverse effect of pain on sleep is not yet well delineated. The key moderating factors explored in the literature are pharmacologic and nonpharmacologic therapies, psychologic health, and the etiology of pain. There is evidence that both altered sleep and pain early in life impact neurodevelopment, as seen by changes in sleep structure in clinical studies and alterations in brain development in animal models. The complicated relationship between sleep and pain is critically important during pediatric development when alterations to a normal sleep structure can have a lifelong impact. It is becoming clear that sleep deprivation and poor sleep quality exacerbate pain. Further research is needed into the complex alterations of sleep in chronic pain conditions as well as treatments to improve sleep in pediatric care. Morris EE, Howell MJ, Pickup E, Iber C, Wang SG. Pediatric sleep and pain: etiologies, consequences, and clinical considerations. J Clin Sleep Med. 2022;18(9):2281-2289.

Sleep and epilepsy: A snapshot of knowledge and future research lines.

SummarySleep and epilepsy have a reciprocal relationship, and have been recognized as bedfellows since antiquity. However, research on this topic has made a big step forward only in recent years. In this narrative review we summarize the most stimulating discoveries and insights reached by the “European school.” In particular, different aspects concerning the sleep–epilepsy interactions are analysed: (a) the effects of sleep on epilepsy; (b) the effects of epilepsy on sleep structure; (c) the relationship between epilepsy, sleep and epileptogenesis; (d) the impact of epileptic activity during sleep on cognition; (e) the relationship between epilepsy and the circadian rhythm; (f) the history and features of sleep hypermotor epilepsy and its differential diagnosis; (g) the relationship between epilepsy and sleep disorders.

Sleep EEG-Based Approach to Detect Mild Cognitive Impairment.

Mild Cognitive Impairment (MCI) is an early stage of dementia, which may lead to Alzheimer’s disease (AD) in older adults. Therefore, early detection of MCI and implementation of treatment and intervention can effectively slow down or even inhibit the progression of the disease, thus minimizing the risk of AD. Currently, we know that published work relies on an analysis of awake EEG recordings. However, recent studies have suggested that changes in the structure of sleep may lead to cognitive decline. In this work, we propose a sleep EEG-based method for MCI detection, extracting specific features of sleep to characterize neuroregulatory deficit emergent with MCI. This study analyzed the EEGs of 40 subjects (20 MCI, 20 HC) with the developed algorithm. We extracted sleep slow waves and spindles features, combined with spectral and complexity features from sleep EEG, and used the SVM classifier and GRU network to identify MCI. In addition, the classification results of different feature sets (including with sleep features from sleep EEG and without sleep features from awake EEG) and different classification methods were evaluated. Finally, the MCI classification accuracy of the GRU network based on features extracted from sleep EEG was the highest, reaching 93.46%. Experimental results show that compared with the awake EEG, sleep EEG can provide more useful information to distinguish between MCI and HC. This method can not only improve the classification performance but also facilitate the early intervention of AD.

Effect of Fang's scalp acupuncture on perceived stress and sleep structure in insomnia patients: a randomized controlled trial

To compare the efficacy on insomnia between Fang 's scalp acupuncture combined with conventional acupuncture and the simple conventional acupuncture. A total of 66 patients with insomnia were randomly divided into an observation group (33 cases, 1 case dropped off) and a control group (33 cases, 2 cases dropped off). In the control group, the routine acupuncture therapy was applied to Shenmen (HT 7), Baihui (GV 20), Zhaohai (KI 6) and Sanyinjiao (SP 6), etc. Based on the treatment as the control group, Fang's scalp acupuncture therapy was supplemented at fuxiang tou, fuzang shangjiao, fuzang zhongjiao, siwei, etc. At these scalp points, the needles were inserted perpendicularly with flying needling technique and manipulated with trembling one. In either group, the treatment was given once daily, continuously for 2 weeks. Before and after treatment, separately, the score of Pittsburgh sleep quality index (PSQI) and the score of Chinese perceived stress scale (CPSS) were observed, as well as the parameters monitored by polysomnography, i.g. total sleep time (TST), sleep onset latency (SOL), wakefulness after the sleep onset (WASO), sleep efficiency (SE), the percentages of the time of rapid eye movement sleep phase (REM) and non-rapid eye movement sleep phase 1, 2, 3 and 4 in TST (REM%, N1%, N2%, N3%). The efficacy was compared between two groups. After treatment, the scores of each factor and the total scores of PSQI, as well as CPSS scores were all lower than those before treatment in the two groups (P<0.01, P<0.05); except the score for sleep quality, the score of each factor and the total score of PSQI, as well as CPSS score in the observation group were lower than those in the control group (P<0.01, P<0.05). After treatment, TST, SE%, REM% and N3% were increased and SOL, WASO, N1% were decreased as compared with before treatment in the two groups (P<0.01, P<0.05), and N2% in the observation group was decreased (P<0.01); SE%, REM% and N3% in the observation group were higher than the control group (P<0.05) and N1% and N2% were lower than the control group (P<0.05). The total effective rate was 93.8% (30/32) in the observation group, higher than 87.1% (27/31) in the control group (P<0.05). Fang 's scalp acupuncture, on the base of routine acupuncture, obviously improves the sleep quality and perceived stress and adjusts the sleep structure in the patients with insomnia.

The Effect of Bi-Level Positive Airway Pressure on Sleep Structure in Patients with Overlap Syndrome

Objective: The present study aimed to observe the effect of bi-level positive airway pressure on sleep structure in patients with overlap syndrome (OS). Method: Forty patients with OS were randomly divided into control and experimental groups, respectively, with 20 cases in each group. Patients in both the control and experimental groups were given anti-infection, dilating bronchi, expectoration, and oxygen inhalation treatment according to the conditions. Bi-level positive airway pressure was conducted in patients in the experimental group for approximately 10 hr a day over a one-week therapeutic course. Polysomnography, Sleep questionnaire survey was performed before treatment and after one week of treatment in both the control and experimental groups to measure sleep structure to investigate the drowsiness and quality of life of the patients. Results: (1) Prior to treatment, differences in the total sleep time, sleep latency, rapid eye movement (REM) latency, sleep efficiency, phase I, II, and III sleep, REM phase sleep and sleep questionnaire survey was not statistically significant between the two groups (P &gt; 0.05). (2) One week after treatment, compared with the control group, the REM latency in the experimental group was shortened, the percentage of REM sleep and Rem sleep in total sleep time was prolonged, the second stage sleep time and the percentage of second stage sleep in total sleep time were shortened, and the scores of Epworth drowsiness, fatigue, dizziness, lack of energy and anxiety decreased in the sleep questionnaire. There was no significant difference in other indexes (P &gt; 0.05). After treatment in the experimental group, REM latency was shortened, REM sleep time and the percentage of Rem sleep in total sleep time were prolonged, second-stage sleep time and second-stage sleep in total sleep time were shortened. Sleep questionnaire survey showed that Epworth drowsiness score, fatigue, dizziness, mental in concentration and anxiety symptoms decreased. There was no significant difference in other indexes (P &gt; 0.05). The sleep questionnaire in the control group after treatment showed that the score of fatigue symptoms decreased, and the difference was statistically significant (P &lt; 0.05). There was no significant difference in other indexes (P &gt; 0.05). Conclusion: Bi-level positive airway pressure can potentially shorten REM latency, prolong REM sleep, and shorten phase II sleep, alleviate the symptoms of drowsiness, fatigue, dizziness, distraction and anxiety, and improve the quality of life in patients with OS.

Literature Cases Summarized Based on Their Polysomnographic Findings in Rett Syndrome.

Rett syndrome (RTT) is a severe and rare neurodevelopmental disorder affecting mostly girls. In RTT, an impaired sleep pattern is a supportive criterion for the diagnosis, yet little is known regarding the sleep structure and sleep respiratory events. Aiming to delineate sleep by aggregating RTT case (series) data from published polysomnographic studies, seventy-four RTT cases were collected from eleven studies up until 6 February 2022 (PROSPERO: CRD 42020198099). We compared the polysomnographic data within RTT stratifications and to a typically developing population. MECP2 cases demonstrated shortened total sleep time (TST) with increased stage N3 and decreased REM sleep. In cases with CDKL5 mutations, TST was longer and they spent more time in stage N1 but less in stage N3 than those cases affected by MECP2 mutations and a typically developing population. Sleep-disordered breathing was confirmed by the abnormal apnea/hypopnea index of 11.92 ± 23.67/h TST in these aggregated cases. No association of sleep structure with chronological age was found. In RTT, the sleep macrostructure of MECP2 versus CDKL5 cases showed differences, particularly regarding sleep stage N3. A severe REM sleep propensity reduction was found. Aberrant sleep cycling, possibly characterized by a poor REM ‘on switch’ and preponderance in slow and high-voltage sleep, is proposed.

Pathogenetic links between ischemic stroke and sleep-disordered breathing

The paper reviews the pathophysiological links between ischemic stroke and sleep-disordered breathing. We discuss well-known mechanisms, such as intermittent hypoxemia, disturbed sleep structure and fluctuations in intrathoracic pressure, autonomic imbalance, oxidative stress, as well as genetic factors and the role of glymphatic system. The impact of sleep-disordered breathing on the development of various subtypes of stroke (according to the TOAST classification) and the so-called “wake-up stroke” is presented.

Sleep Disorders in Rett Syndrome and Rett-Related Disorders: A Narrative Review.

Rett Syndrome (RTT) is a rare and severe X-linked developmental brain disorder that occurs primarily in females, with a ratio of 1:10.000. De novo mutations in the Methyl-CpG Binding protein 2 (MECP2) gene on the long arm of X chromosome are responsible for more than 95% cases of classical Rett. In the remaining cases (atypical Rett), other genes are involved such as the cyclin-dependent kinase-like 5 (CDKL5) and the forkhead box G1 (FOXG1). Duplications of the MECP2 locus cause MECP2 duplication syndrome (MDS) which concerns about 1% of male patients with intellectual disability. Sleep disorders are common in individuals with intellectual disability, while the prevalence in children is between 16 and 42%. Over 80% of individuals affected by RTT show sleep problems, with a higher prevalence in the first 7 years of life and some degree of variability in correlation to age and genotype. Abnormalities in circadian rhythm and loss of glutamate homeostasis play a key role in the development of these disorders. Sleep disorders, epilepsy, gastrointestinal problems characterize CDKL5 Deficiency Disorder (CDD). Sleep impairment is an area of overlap between RTT and MECP2 duplication syndrome along with epilepsy, regression and others. Sleep dysfunction and epilepsy are deeply linked. Sleep deprivation could be an aggravating factor of epilepsy and anti-comitial therapy could interfere in sleep structure. Epilepsy prevalence in atypical Rett syndrome with severe clinical phenotype is higher than in classical Rett syndrome. However, RTT present a significant lifetime risk of epilepsy too. Sleep disturbances impact on child's development and patients' families and the evidence for its management is still limited. The aim of this review is to analyze pathophysiology, clinical features, the impact on other comorbidities and the management of sleep disorders in Rett syndrome and Rett-related syndrome.

Obstructive Sleep Apnea and Sleep Structure Assessed in Polysomnography and Right Ventricular Strain Parameters.

Our study aimed to assess functional, structural changes of the right ventricular using strain parameters and sleep structure using polysomnography in patients with obstructive sleep apnea (OSA). Our study group consisted of 43 patients, 29 men, 14 women. The mean age was 56.36 ± 14.77. All patients underwent full night polysomnography and transthoracic echocardiography. The right ventricular global longitudinal strain was measured by 2D speckle-tracking echocardiography. The prevalence of OSA (AHI ≥ 5) was 76.7% in the studied group. We observed a significant positive correlation between OAH and average free wall strain (r = 0.37), snore and mid-free wall strain (r = 0.34), average HR, and basal free wall strain (r = 0.34). Moreover, CSB was positively correlated with basal septal strain and mid septal strain (r = 0.36 and 0.42). In summary, among patients with sleep disorders, functional disorders of the right ventricle, assessed using the strain method, are partly observed.

Deep adaptation network for subject-specific sleep stage classification based on a single-lead ECG

Sleep plays a vital role in human physical and mental health. To accurately identify sleep structure under comfortable and convenient conditions, many machine-learning methods have been applied in the classification of sleep staging based on an Electrocardiogram (ECG); however, few works have solved the problem of generalization in the subject-specific sleep staging. The main reason for the problem is the difference of domain distribution across subjects. Most works are also classified based on ECG-derived signals and manual features. In this paper, we describe an end-to-end deep adaptation framework that classifies sleep stages into four classes based on a single-lead ECG to overcome the above problems. In particular, multi-class focal loss and a domain aligning layer based on the maximum mean discrepancy have been combined to solve data imbalances and domain shifts during three-step processing. We evaluate the method based on the three public datasets contained in SHHS2, SHHS1, and MESA. Compared to the performance of the model without domain aligning, the accuracy of the model for the public datasets has been improved by more than 20%, and the Kappa coefficient has also been improved by close to 0.4, which achieves state-of-the-art solutions compared to the baseline. In addition, the method has excellent performance for accuracy and Cohen’s Kappa in terms of cross datasets. The proposed method, which confuses the domain-variant features, makes important contributions to the prediction of different subjects’ sleep structures. The domain-adaptation setup, which varies across subjects and across environments, may provide a new approach to health monitoring.

Machine Learning‐Enabled Noncontact Sleep Structure Prediction

Automated, effective and efficient sleep‐stage monitoring and structure analysis is an essential enabling procedure for healthcare automation. Sleep diagnosis by polysomnography is a golden standard but expensive procedure involving huge effort from patients. There remain challenges for smart devices to precisely identify sleep stage and minimize intrusive effect on sleep progression. Herein, a novel noncontact sleep structure prediction system (NSSPS) using a single radar sensor is presented to analyze sleep structure without any tethered unit. The NSSPS is realized through training a convolutional recurrent neural network and neural conditional random fields using reflected radio frequency (RF) waves acquired by radar antennas. By capturing implicit temporal information in RF signals and transitions of sleep progression, high accuracy of sleep‐stage prediction is achieved and characteristics of sleep structure are extracted. The performance of the NSSPS is validated by transfer learning between radar signals with different frequency bands and crossvalidation among different subjects. Moreover, the NSSPS is demonstrated to estimate overnight parameters that are critical for sleep diagnosis. Benefiting from its low cost, convenient setup, and accurate prediction capability of sleep‐stage identification, the NSSPS can be widely deployed in “smart” homes and exploited to conduct daily sleep structure analysis.

Sleep-Induced Hypoxia under Flight Conditions: Implications and Countermeasures for Long-Haul Flight Crews and Passengers.

PurposeRecuperation during sleep on board of commercial long-haul flights is a safety issue of utmost importance for flight crews working extended duty periods. We intended to explore how sleep and blood oxygenation (in wake versus sleep) are affected by the conditions in an airliner at cruising altitude.MethodsHealthy participants’ sleep was compared between 4-h sleep opportunities in the sleep laboratory (n = 23; sleep lab, ie, 53 m above sea level) and in an altitude chamber (n = 20; flight level, ie, 753 hPa, corresponding to 2438 m above sea level). A subgroup of 12 participants underwent three additional conditions in the altitude chamber: 1) 4-h sleep at ground level, 2) 4-h sleep at flight level with oxygen partial pressure equivalent to ground level, 3) 4-h monitored wakefulness at flight level. Sleep structure and blood oxygenation were analysed with mixed ANOVAs.ResultsTotal sleep time at flight level compared to in the sleep laboratory was shorter (Δ mean ± standard error −11.1 ± 4.2 min) and included less N3 sleep (Δ −17.6 ± 5.4 min), while blood oxygenation was decreased. Participants spent 69.7% (± 8.3%) of the sleep period time but only 13.2% (± 3.0%) of monitored wakefulness in a hypoxic state (<90% oxygen saturation). Oxygen enrichment of the chamber prevented oxygen desaturation.ConclusionSleep – but not wakefulness – under flight conditions induces hypobaric hypoxia which may contribute to impaired sleep. The results caution against the assumption of equivalent crew recovery in-flight and on the ground but hold promise for oxygen enrichment as a countermeasure. The present results have implications for flight safety and possible long-term consequences for health in crews.

Research progress on the mechanism of comorbidities of vestibular migraine and sleep disorders

Vestibular migraine （VM） is one of the common vestibular diseases characterized by recurrent vertigo and migraine. Studies have shown that the sleep structure of VM patients is similar to that of migraine patients, and they have a common pathophysiological pathogenesis. There is a strong correlation between VM and the clinical symptoms of sleep disorders. Sleep disorders can trigger VM. On the contrary, VM can affect sleep regulatory centers and lead to structural sleep disorders. In addition, there is a common relationship between VM and sleep disorders in neuroanatomy, neurotransmitters and neural pathways. A correct understanding of the relationship between vestibular migraine and sleep disorders can provide some help for clinical diagnosis and treatment. This article reviews the relationship between vestibular migraine and the pathogenesis of sleep disorders.

Social jetlag and sleep debts are altered in different rosters of night shift work

Night and shift work are suspected to cause various adverse effects on health and sleep. Sleep deprivation through shift work is assumed to be compensated on free days. So far it is not clear how different shift systems and shift lengths affect sleep structure on work and free days. Especially working night shifts disrupts the circadian rhythm but also extended working hours (12h) might affect sleep characteristics. Hitherto, the magnitude of sleep debt, social jetlag, and Locomotor Inactivity During Sleep (LIDS) in different shift systems is unknown. Here, we investigated the impact of five different shift rosters on sleep in 129 industrial workers from Germany. Permanent night work with multiple shift systems with and without night shifts and with different shift lengths were compared. Wrist-activity was monitored over 28 days revealing sleep on- and offsets as well as LIDS as proxy for sleep quality. Overall, 3,865 sleep bouts comprising 22,310 hours of sleep were examined. The mean daily age-adjusted sleep duration (including naps) was 6:43h and did not differ between shift workers of different rosters. However, sleep duration on workdays was particularly low in rotational shift systems with 12h-shifts (5:00h), while overall sleep debt was highest. Shift workers showed a median absolute social jetlag of 3:03h, which differed considerably between shift types and rosters (p<0.0001). Permanent night workers had the highest social jetlag (5:08h) and latest mid-sleeps on workdays and free days. Sleep quality was reduced in permanent night shift workers compared with shift workers in other rosters and differed between daytime and nighttime sleep. Shift work leads to partial sleep deprivation, which particularly affects workers in 12h-shifts and permanent night shifts. Working these shifts resulted in higher sleep debts and larger absolute social jetlag whereas sleep quality was especially reduced in permanent night shift workers compared with shift workers of other rosters.

Metabolic rate and substrate oxidation of young males with obesity at the different sleep stages

ObjectiveInsufficient and poor-quality sleep among young adults is closely related to obesity and may impact metabolic processes. The mobilization and use of endogenous substrates during sleep, especially fat oxidation, is essential for energy metabolism. This study investigated whether there are differences in sleep structure, metabolic rate, substrate oxidation, and the respiratory quotient (RQ) between young males with normal weight and obesity according to sleep stages and overnight sleep. MethodsFifteen young males with normal weight and fifteen with obesity posited electrodes of polysomnography (PSG) and slept in the metabolic chamber for estimation of sleep structure, sleep metabolic rate (SMR), carbohydrate oxidation (CHOO), fat oxidation (FATO), and RQ. Fat-free mass (FFM) was measured by bioelectrical impedance analysis. ResultsThe sleep period time (p = 0.038) and total sleep time (p = 0.032) were significantly shorter in the obesity group than in the normal-weight group. The obesity group also had a longer sleep latency (p = 0.034) and more sleep-turning events (p = 0.018). CHOO/FFM and the RQ were higher in the obesity group while FATO/FFM was significantly higher in the normal-weight group. FATO/FFM was also higher in the normal-weight group in each sleep stage whereas the RQ was higher in the obesity group (p < 0.05). ConclusionsYoung males with obesity showed lower fat oxidation and more dominant carbohydrate-derived fuel oxidation than normal-weight during sleep and experienced shorter sleep periods and total sleep time.

Changes in the telomeres length in patients with obstructive sleep apnea after continuous positive airway pressure therapy: a pilot study

To evaluate a relative telomere length in patients with obstructive sleep apnea (OSA) before and after a 6-month course of continuous positive airway pressure (CPAP) therapy. Seventy-five men participated in the study, including 50 men with OSA (the main group 1) and 25 men without OSA (the control group). The average age in the total group was 53.4±3.6 years. Thirty-five men completed the study (the main group 2). According to the design, night polysomnography (PSG) was performed for all the subjects, blood sampling to assess the length of telomeres was carried out in the morning according to the standard method. The values of the relative telomere length were obtained using the difference between the values of the threshold cycles for telomeric DNA and the reference gene albumin (∆CCt). After clarifying the diagnosis, CPAP was applied for 6 months. Statistically significant indicators of PSG were revealed: a decrease in NREM 3 in patients with OSA compared to controls (89.3±15.8 versus 150±23.4 minutes), an increase in NREM1-2 in OSA (296.2±31.1 and 170.1±24.5, respectively), REM was 84.6±15.4 in the main group and 118.5±19.5 in the control group. CPAP therapy conducted for 6 months (at least 4-5 nights a week, lasting at least 5-6 hours of night sleep) demonstrated a significant improvement in the qualitative and quantitative parameters of sleep. In patients of the main group 1, there is a shortening of the telomere length compared with the control group (p<0.001). With the elimination of hypoxia and improvement of the structure of sleep after CPAP, there was an increase in the telomere lengths in the main group 1 from 0.28 [0.24-0.29] to 0.32 [0.30-0.34] in the main group 2 (p=0.03). The telomers length in the control group was 0.53 [0.50-0.55]. Intermittent hypoxia and fragmentation of sleep in OSA leads to shortening of telomeres. CPAP, by eliminating the pathophysiological triggers of OSA, contributes to an increase in telomeres lengths and can slow down the premature aging in OSA.

Alleviating Class Imbalance Problem in Automatic Sleep Stage Classification

For real-world automatic sleep stage classification tasks, various existing deep learning based models are biased towards the majority with high proportion. Because of the unique sleep structure, most of the current polysomnography datasets suffer an inherent class imbalance problem (CIP), in which the number of each sleep stage is severely unequal. In this study, we first define the class imbalance factor (CIF) to describe the level of CIP quantitatively. Afterwards, we propose two balancing methods to alleviate this problem from the dataset quantity and the relationship between the class distribution and the applied model respectively. The first one is to employ the data augmentation (DA) with the generative adversarial network (GAN) model and different intensities Gaussian white noise to balance samples, thereinto, Gaussian white noise addition is specifically tailored to deep learning based models, which can work on raw electroencephalogram (EEG) data while preserving their properties. In addition, we try to balance the relationship between the imbalanced class and biased network model to achieve a balanced state with the help of class distribution and neuroscience principles. We further propose an effective deep convolutional neural network (CNN) model utilizing bidirectional Long Short-Term Memory (Bi-LSTM) with single-channel EEG as the Baseline. It is used for evaluating the efficiency of two balancing approaches on three imbalanced polysomnography datasets (CCSHS, Sleep-EDF and Sleep-EDF-V1). The qualitative and quantitative evaluation of experimental results demonstrates that the proposed methods could not only show the superiority of class balancing through the confusion matrix and class-wise metrics, but also get better N1 stage and whole stages classification accuracies compared to other state-of-the-art approaches.