Clocks & Sleep

Circadian rhythms (CRs) are a key biological system regulating physiological processes such as metabolism, cell growth, DNA repair, and immunity, adapting to environmental changes like the light/dark cycle. Governed by internal clocks, it modulates gene expression through feedback loops involving Clock Genes (CGs), with the cycle initiated by CLOCK–BMAL1 and NPAS2–BMAL1 heterodimers. Disruptions in circadian rhythms have been linked to diseases including metabolic disorders, neurodegeneration, and cancer. CIPC (CLOCK-interacting pacemaker) has been studied as a negative regulator of the CLOCK–BMAL1 complex, focusing on its role in cancer, particularly leukemias. Public datasets and bioinformatics tools were used to examine CIPC gene expression in healthy patients and acute myeloid leukemia (AML) samples. Our analysis revealed significant overexpression of CIPC in AML compared to healthy tissues (p < 0.0001 ****). Additionally, survival analysis indicated significant differences in overall survival based on CIPC expression, with a log-rank test p-value = 0.014, suggesting that CIPC expression may affect overall patient survival. Altered CIPC expression may contribute to leukemogenesis by inhibiting circadian genes, which are often disrupted in leukemia. Furthermore, CIPC interacts with oncogenic pathways, including the MAPK/ERK pathway, which is essential for cell proliferation. Additional studies are needed to validate these findings and explore the detailed role of CIPC in cancer development. Full article

Background. Sleep disorders are a group of conditions that disrupt normal sleep patterns and are among the most common clinical challenges faced today. An innovative device that employs nanotechnology to deliver beneficial effects on the human body is the Taopatch^® (Tao Technologies, Vedelago, Italy). This study aims to assess the effectiveness of such nanotechnology-based devices in improving sleep quality. Methods. This study included only female participants, as a review of the literature indicated that sleep disorders are more prevalent in women than in men. A total of 30 subjects (with a mean age of 44.8 ± 3.44 years) were randomly divided into two groups: an experimental group and a control group. Sleep quality was evaluated three times throughout the study for each participant using the Pittsburgh Sleep Quality Index (PSQI). The Taopatch^® devices were applied using a specialized pillow. Results. The experimental group showed significantly better sleep quality (p < 0.001) compared to the control group. Conclusions. Our findings suggest that the application of the Taopatch^® has a positive impact on sleep quality by optimizing posture, aligning the cervical spine, and promoting muscle relaxation. This device uses advanced nanotechnology to enhance various physiological functions, contributing to better overall well-being. Full article

Introduction: For patients in intensive care units, the Richards–Campbell Sleep Questionnaire (RCSQ) seems to be a useful tool for assessing sleep quality. However, its application in the Moroccan medical context could be limited due to the lack of a dialectal Arabic version for Morocco. This study’s objective was to translate and validate the RCSQ into Arabic for Moroccan speakers. Patients and methods: For this investigation, a cross-sectional design was adopted. The RCSQ was translated and validated into Arabic for Morocco in accordance with the recommendations. For every scale, psychometric properties were computed. The Cronbach’s α coefficient was utilized to evaluate the internal consistency of multi-item measures. Results: The study involved 224 patients, whose mean age was 47 ± 18.3 years. The RCSQ’s internal consistency, or Cronbach’s alpha, was computed, and all dimensions showed good reliability over the 0.92 (0.894–0.983) level. The items demonstrated good reliability and validity, with correlation values larger than 0.4, according to the data. Conclusion: The RCSQ translated into Arabic for Morocco appears to have good psychometric qualities, making it useful for assessing the quality of sleep of patients in intensive care units within Moroccan healthcare settings. Full article

Chronobiotics represent a pharmacologically diverse group of substances, encompassing both experimental compounds and those utilized in clinical practice, which possess the capacity to modulate the parameters of circadian rhythms. These substances influence fluctuations in various physiological and biochemical processes, including the expression of core “clock” genes in model organisms and cell cultures, as well as the expression of clock-controlled genes. Despite their chemical heterogeneity, chronobiotics share the common ability to alter circadian dynamics. The concept of chronobiotic drugs has been recognized for over five decades, dating back to the discovery and detailed clinical characterization of the hormone melatonin. However, the field remains fragmented, lacking a unified classification system for these pharmacological agents. The current categorizations include natural chrononutrients, synthetic targeted circadian rhythm modulators, hypnotics, and chronobiotic hormones, yet no comprehensive repository of knowledge on chronobiotics exists. Addressing this gap, the development of the world’s first curated and continuously updated database of chronobiotic drugs—circadian rhythm modulators—accessible via the global Internet, represents a critical and timely objective for the fields of chronobiology, chronomedicine, and pharmacoinformatics/bioinformatics. The primary objective of this study is to construct a relational database, ChronobioticsDB, utilizing the Django framework and PostGreSQL as the database management system. The database will be accessible through a dedicated web interface and will be filled in with data on chronobiotics extracted and manually annotated from PubMed, Google Scholar, Scopus, and Web of Science articles. Each entry in the database will comprise a detailed compound card, featuring links to primary data sources, a molecular structure image, the compound’s chemical formula in machine-readable SMILES format, and its name according to IUPAC nomenclature. To enhance the depth and accuracy of the information, the database will be synchronized with external repositories such as ChemSpider, DrugBank, Chembl, ChEBI, Engage, UniProt, and PubChem. This integration will ensure the inclusion of up-to-date and comprehensive data on each chronobiotic. Furthermore, the biological and pharmacological relevance of the database will be augmented through synchronization with additional resources, including the FDA. In cases of overlapping data, compound cards will highlight the unique properties of each chronobiotic, thereby providing a robust and multifaceted resource for researchers and practitioners in the field. Full article

Sleep is an essential part of everyday life and disturbed sleep can produce numerous deleterious effects on the body. An especially prevalent and detrimental subset of sleep disturbances are sleep disturbances that occur in patients during the postoperative period. To better understand these disorders and how to treat them, a literature search was conducted to identify and consolidate recent advancements in this field. This narrative review discusses the structure of a typical night of sleep and the causes, effects, and treatment strategies of Postoperative Sleep Disturbances (PSDs). Factors that contribute to the development of PSDs have been identified at all stages of the surgical process, including the preoperative, intraoperative, and postoperative timepoints. Exposure to these factors can accumulate during each step and may decrease the quality of sleep postoperatively. The development of PSDs has been found to affect multiple systems throughout the body and can ultimately lead to poorer recovery times and increased postoperative mortality. As a result, multiple therapeutic approaches are being investigated for their role in reducing the prevalence of these disorders. This has revealed promising interventions throughout the surgical process, such as preoperative nerve blocks, intraoperative infusions, and postoperative behavioral interventions. However, despite these successful findings, work still needs to be completed to optimize these techniques and generalize intervention strategies. Full article

Measurement of respiratory patterns during sleep plays a critical role in assessing sleep quality and diagnosing sleep disorders such as sleep apnea syndrome, which is associated with many adverse health outcomes, including cardiovascular disease, diabetes, and cognitive impairments. Traditional methods for measuring breathing often rely on expensive and complex sensors, such as polysomnography equipment, which can be cumbersome and costly and are typically confined to clinical settings. These factors limit the performance of respiratory monitoring in routine settings and prevent convenient and extensive screening. Recognizing the need for accessible and cost-effective solutions, we developed a portable sleep sensor that uses an electret condenser microphone (ECM), which is inexpensive and easy to obtain, to measure nasal airflows. Constant current circuits that bias the ECM and circuit constants suitable for measurement enable special uses of the ECM. Furthermore, data transmission through the XBee wireless communication module, which employs the ZigBee short-range wireless communication standard, enables highly portable measurements. This customized configuration allows the ECM to detect subtle changes in airflow associated with breathing patterns, enabling the monitoring of respiratory activity with minimal invasiveness and complexity. Furthermore, the wireless module not only reduces the size and weight of the device, but also facilitates continuous data collection during sleep without disturbing user comfort. This portable wireless sensor runs on batteries, providing approximately 50 h of uptime, a ±50 Pa pressure range, and 20 Hz real-time sampling. Our portable sleep sensor is a practical and efficient solution for respiratory monitoring outside of the traditional clinical setting. Full article

This study explored whether sleep duration, insomnia, social jetlag, and circadian preference predicted adolescents’ risk of anxiety and depression two years later. High school students initially aged 16–17 years were, in 2019 and 2021, invited to a web-based survey assessing sleep patterns, insomnia, circadian preference, anxiety, and depression. Sleep duration, insomnia, circadian preference, depression, and anxiety were assessed using the Munich ChronoType Questionnaire, the Bergen Insomnia Scale, the reduced Morningness–Eveningness Questionnaire, the Patient Health Questionnaire-9, and the Generalized Anxiety-Disorder 7, respectively. Analyses were conducted using logistic regression analyses. The analytic longitudinal sample comprised 1456 students (initial mean age 16.4 years; 61.4% girls). Short school night sleep duration, chronic insomnia, and more severe insomnia symptoms at baseline predicted greater risk of anxiety and depression at follow-up when controlled for anxiety and depression at baseline. Neither free night sleep duration nor social jetlag at baseline were related to the risk of anxiety and depression at follow-up. When circadian preference was investigated continuously, greater morningness at baseline predicted lower risk of anxiety and depression at follow-up. When circadian preference was investigated categorically, evening preference type was associated with higher risk of depression at follow-up than intermediate preference type, while the prospective risk of anxiety and depression otherwise did not differ in relation to circadian preference. The results attest to prospective associations between adolescent sleep problems at baseline and later risk of anxiety and depression. Full article

This study explored the impact of lifestyle habits and sensory processing patterns on sleep quality by analyzing body movements (BMs) during the first and last 3 h of sleep in toddlers. We collected cross-sectional data about sleep-related habits from 58 toddlers using a mobile application. Actigraphy measured BMs during nighttime sleep and 1 h before bedtime, as well as sleep latency, over 8 consecutive days. The Infant/Toddler Sensory Profile was used to assess the toddlers’ sensory processing patterns. The participants had a mean age of 22.0 ± 2.0 months. BMs were significantly lower during the first 3 h of sleep. Longer sleep latency was significantly associated with media use and higher activity levels before bedtime. Ending a nap earlier and consuming a substantial breakfast were correlated with lower BMs during the first 3 h of sleep. Auditory and oral sensory scores were positively correlated with BMs during the first 3 h of sleep. However, no specific factors related to lifestyle habits or sensory processing patterns were found to correlate with BMs during the last 3 h of sleep. Lifestyle habits and sensory processing patterns have a significant impact on toddlers’ sleep quality, emphasizing the importance of appropriate routines and environments. Full article

Shift workers are at increased risk of insomnia. The standard treatment (cognitive behavioral therapy for insomnia) poses significant challenges for this demographic due to irregular work and sleep schedules. New approaches are still considered insufficient due to high attrition or insufficient effectiveness. Our preliminary study identified sleep-relevant state and trait factors (see secondary outcomes) for incorporation into an innovative manual that addresses sleep in an implicit manner. The objective was to reduce the focus on insomnia and to replace regularity-based interventions. With a sample of 55 insomniacs (67.74% male, mean age 41.62 years), standard and customized treatments were compared using pre-treatment, post-treatment, and three-month follow-up measurements (RCT, self-assessment data). Our linear mixed models revealed the main significant effects of the measurement point for the primary (insomnia severity, sleep quality, sleep onset latency, total sleep time, daytime sleepiness) and the secondary outcomes (selection: anxiety/depression, dysfunctional beliefs, arousal, emotional stability, concern). No main effects of the condition or interaction effects were identified. Non-inferiority and equivalence tests demonstrated that the customized treatment is equivalent to standard therapy, which is a favorable outcome in light of the implicit approach. Consequently, this innovative approach warrants further exploration, incorporating the present results. Full article

It remains unclear how sleep health has developed in the general population after the COVID-19 pandemic. This study aimed to (1) investigate the prevalence of sleep problems and poor sleep quality and (2) explore the associated sociodemographic and health-related factors in South Tyrol, Italy. A cross-sectional, population-based survey was conducted with a stratified probabilistic sample of 4000 adults aged ≥ 18 years. Sleep quality was assessed using the brief version of the Pittsburgh Sleep Quality Index. Descriptive and logistic regression analyses were performed to analyze the data. A total of 2090 adults (53%) completed the survey. Poor sleep quality was reported by 17.8%, with 28.2% of participants reporting insufficient sleep duration (i.e., six hours or less), 12.7% having problems staying asleep (i.e., waking up to 3–4 times a week and unable to fall asleep again), and 8.7% having problems falling asleep (i.e., >30 min). Sleep problems and poor sleep quality were associated with sociodemographic and health-related factors, including gender, age, mother tongue, chronic disease, and sleep hygiene. Notably, Italian-speaking participants reported poorer sleep quality and greater difficulty staying asleep compared to German-speaking participants, highlighting potential sociocultural influences on sleep health. This study contributes to understanding the unique sleep health challenges in a multilingual region, highlighting the role of sociocultural factors in sleep quality differences between language groups. Full article

Considering the frequent co-occurrence of major depressive disorder and excessive daytime sleepiness in apneic individuals, this study aimed to explore the relationship between excessive daytime sleepiness and the risk of developing major depressive disorder in this specific subpopulation. Demographic and polysomnographic data were retrospectively extracted from the clinical database of 1849 apneic individuals at the Sleep Unit. Excessive daytime sleepiness was considered present when the Epworth Sleepiness Scale score was >10 and major depressive episodes were diagnosed according to DSM criteria. Logistic regression analyses were performed to assess the risk of major depressive disorder associated with excessive daytime sleepiness in apneic individuals. The prevalence of major depressive disorder was 26.3% in apneic individuals. After controlling for major confounding variables, multivariate logistic regression analyses revealed that apneic individuals with complaints of excessive daytime sleepiness had a higher likelihood of developing major depressive disorder compared to those without complaint of excessive daytime sleepiness. This study highlights the strong association between excessive daytime sleepiness and major depressive disorder in apneic individuals, underlining the importance of systematically assessing and adequately treating excessive daytime sleepiness to better manage depressive symptoms and improve overall treatment outcomes in this specific subpopulation. Full article

Sleep is essential for maintaining both mental and physical well-being. It plays a critical role in the health and development of children. This study investigates sleep patterns and habits of First Nations children, the prevalence of sleep disturbances, and excessive daytime sleepiness (EDS), along with the factors associated with EDS. Our 2024 First Nations Children Sleep Health Study assessed the sleep health of children aged 6 to 17 years living in a First Nation in Canada. Statistical analyses were performed using comparison tests and logistic regression models. A total of 78 children participated; 57.7% were boys. The average age of the participants was 10.49 years (SD = 3.53 years). On school days, children aged 6 to 9 years slept an average of one additional hour, while on weekends, they slept an extra 40 min compared to adolescents aged 10 to 17 years. Only 39.7% of the children (ages 6 to 17) slept alone in a room, with more than 80% of the children sharing a bed every night. Only 30.6% of the children aged 6 to 9 years and 7.2% of the adolescents aged 10 to 17 years adhered to the recommended maximum screen time of 2 h on school days. More than two-thirds of the children reported experiencing sleep disturbances. The prevalence of EDS was 19.7%. After adjusting for age and sex, it was determined that the children who snored loudly and those who did not sleep in their own beds were more likely to experience abnormally high levels of daytime sleepiness. A high proportion of children exceeded the recommended screen time, an important public health issue. Further, identifying sleep patterns among children will facilitate the diagnosis and treatment of disordered sleep. Full article

Trail running has seen a surge in participants, including individuals with disabilities, particularly in ultratrail running (UTRs). Sleep–wake patterns are crucial for optimal performances in UTRs, which present unique physiological and behavioral challenges. This case study evaluated the sleep–wake cycle of a blind trail ultramarathoner (BTR) and his guide (GTR) before, during, and after an 80 km UTR. Two male participants (BTR: 54 years, BMI: 26.1 kg/m²; GTR: 48 years, BMI: 24.2 kg/m²) were assessed using validated questionnaires (MEQ, ESS, ISI, and PSQI) and actigraphy over 35 days. The BTR exhibited a morning chronotype (MEQ = 63), mild insomnia (ISI = 11), poor sleep quality (PSQI = 5), and prolonged sleep latency (>60 min), while the GTR showed an indifferent chronotype (MEQ = 52), good sleep quality (PSQI = 3), and shorter latency (10 min). Post-competition, both athletes experienced an increased total sleep time (TST): the BTR by 17.8% (05:32:00 vs. 04:25:00) and the GTR by 5.5% (07:01:00 vs. 06:39:00). The BTR demonstrated a greater Wakefulness after sleep onset (WASO 01:00:00 vs. 00:49:00) and awakenings (15.4 vs. 6.1). A time series analysis revealed greater variability in the BTR’s post-competition sleep efficiency and TST, while the GTR exhibited a greater stability of the circadian phase. These findings highlight the intricate sleep challenges faced by blind athletes, informing strategies to optimize recovery and performance. Full article

Isolated rapid eye movement (REM) sleep behavior disorder (iRBD) is recognized as a precursor to neurodegenerative diseases. This study aimed to develop predictive models for the timing and subtype of phenoconversion in iRBD. We analyzed comprehensive clinical data from 178 individuals with iRBD over a median follow-up of 3.6 years and applied machine learning models to predict when phenoconversion would occur and whether progression would present with motor- or cognition-first symptoms. During follow-up, 30 patients developed a neurodegenerative disorder, and the extreme gradient boosting survival embeddings–Kaplan neighbors (XGBSE-KN) model demonstrated the best performance for timing (concordance index: 0.823; integrated Brier score: 0.123). Age, antidepressant use, and Movement Disorder Society–Unified Parkinson’s Disease Rating Scale Part III scores correlated with higher phenoconversion risk, while coffee consumption was protective. For subtype classification, the RandomForestClassifier achieved the highest performance (Matthews correlation coefficient: 0.697), indicating that higher Montreal Cognitive Assessment scores and younger age predicted motor-first progression, whereas longer total sleep time was associated with cognition-first outcomes. These findings highlight the utility of machine learning in guiding prognosis and tailored interventions for iRBD. Future research should include additional biomarkers, extend follow-up, and validate these models in external cohorts to ensure generalizability. Full article

This narrative review explores the intricate relationship between circadian regulation and exercise performance, emphasizing the importance of aligning training strategies with the body’s natural physiological fluctuations. The three key mechanisms investigated are temperature, hormonal fluctuations, and diurnal chronotype—an individuals’ exhibition of enhanced physical or cognitive performance at specific times of day. Core body temperature variations impact exercise performance, suggesting strategic workout timing and intensity adjustments. Hormonal patterns (i.e., insulin, cortisol, testosterone) influence energy metabolism and muscle growth, informing tailored training plans. Diurnal chronotypes significantly affect performance, advocating for personalized training sessions based on individual preferences and entrained awakening. Integrating circadian mechanisms into training offers strategic advantages, guiding practitioners to design effective, personalized regimens, though we acknowledge relevant challenges and the need for further research. Full article

Ageing is associated with alterations in circadian rhythms and thermoregulation, contributing to a fragmentation of the sleep–wake cycle and possibly age-related changes in cognitive performance. In this study, we investigated the relationship between visuo-spatial working memory (vsWM) performance and thermoregulation in young (18–34 years) and old (64–84 years) healthy human adults. Variations in the distal–proximal skin temperature gradient (DPG) were continuously monitored over the 24 h cycle in a field setting. vsWM was assessed during morning (09:00) and evening sessions (17:00) using an object–location binding task. As expected, a reduced circadian DPG amplitude was observed in old as compared to young participants. Likewise, old participants produced more errors than the young ones in object identification and location, suggesting reduced vsWM ability. Notwithstanding this, no significant association was found between circadian DPG modulation and vsWM performance, nor between testing time-of-day and cognitive performance. Further research is needed to explore environmental factors and the timing of peak circadian rhythms to better understand the interplay between circadian biology and cognitive ageing. Full article

The aim of this study was to examine sleep timing across the lifespan of Australian adults. A cross-sectional design was used to collect information on subjective sleep timing from 1225 participants (52.3% female) during a telephone interview. The participants were aged from 18 to over 80 and were grouped according to their age using 10-year increments (e.g., 18–29 y, 30–39 y, etc.). There was a diverse distribution across the lifespans, with the largest proportion of participants being from the 60–69 age group (22.8%). Participants were predominantly from New South Wales, Queensland, and Victoria. Younger adults reported going to bed later (p < 0.001) and waking up later than other age groups (p < 0.001). Wake times were earliest during middle adulthood (p < 0.001). There was no significant age effect on the minimum sleep required for good health (p = 0.159) and only a marginal decrease with age in the amount of sleep required to maintain a good mood (p = 0.041). In conclusion, these findings highlight significant variations in sleep timing across younger, middle-aged, and older Australian adults. The current findings could inform future Australian sleep health campaigns, in which the goal is to provide targeted strategies for age groups across their lifespans. Full article

The regularity of sleep–wake cycles is a defining characteristic of normative sleep patterns that are typically associated with proper circadian rhythmicity. The previous literature indicates that consistent patterns of sleep and wake are associated with improved sleep quality and cognitive functioning. Conversely, sleep irregularity has been associated with reduced well-being and inefficiency in resting-state neural networks. This study investigated the relationship between specific sleep regularity measures and outcomes, including emotional affect, sleep quality, and resting-state functional connectivity. We found that variability in wake onset predicted poorer sleep quality and reduced positive affect. Furthermore, sleep regularity measures were associated with altered functional connectivity between the posterior cingulate cortex and regions involved in emotional processing. We propose that alterations in default mode network (DMN) connectivity linked to sleep irregularity reflect disruptions in emotional processing and sleep quality. Full article