Weekly and seasonal variation in the circadian melatonin rhythm in humans:A response

We read with interest the commentary by Skeldon and Dijk about our article "Weekly, seasonal and chronotype-dependent variation of dim light melatonin onset." The discussion points raised by Skeldon and Dijk are currently among the most hotly debated in human circadian science. What external factors determine human phase of entrainment? How great is the contribution of natural versus artificial light and sun time versus social time? Our intra-individual data add to the still limited evidence from field studies in this matter. In their commentary, Skeldon and Dijk formulate two either-or hypotheses, postulating that humans entrain either solely to the natural light-dark cycle (sun time referenced by midday) (H1 ) or solely to the light selected by local clock time and social constraints (H2 ). Neither hypothesis accounts for the effect of season on human light exposure. We interpreted our findings along more complex lines, speculating that the 1-h earlier melatonin rise in summer found in our sample is likely the combined result of daylight saving time (DST)-induced behavioral advances and a stronger natural zeitgeber in summer (light exposure determined by social and seasonal factors, Horiginal ). Here, we show how the criticism by Skeldon and Dijk is based on two sentences quoted out of context (misrepresenting our hypothesis as H1 ) and that their hypothesis H2 leaves out important seasonal components in light exposure.</p

Sleep improvements on days with later school starts persist after 1 year in a flexible start system

Early school times fundamentally clash with the late sleep of teenagers. This mismatch results in chronic sleep deprivation posing acute and long-term health risks and impairing students' learning. Despite immediate short-term benefits for sleep, the long-term effects of later starts remain unresolved. In a pre-post design over 1 year, we studied a unique flexible school start system, in which 10–12th grade students chose daily between an 8:00 or 8:50AM-start. Missed study time (8:00–8:50) was compensated for during gap periods or after classes. Based on 2 waves (6–9 weeks of sleep diary each), we found that students maintained their ~ 1-h-sleep gain on later days, longitudinally (n = 28) and cross-sectionally (n = 79). This gain was independent of chronotype and frequency of later starts but attenuated for boys after 1 year. Students showed persistently better sleep quality and reduced alarm-driven waking and reported psychological benefits (n = 93) like improved motivation, concentration, and study quality on later days. Nonetheless, students chose later starts only infrequently (median 2 days/week), precluding detectable sleep extensions in the flexible system overall. Reasons for not choosing late starts were the need to make up lost study time, preference for extra study time and transport issues. Whether flexible systems constitute an appealing alternative to fixed delays given possible circadian and psychological advantages warrants further investigation

A 4-year longitudinal study investigating the relationship between flexible school starts and grades

The mismatch between teenagers’ late sleep phase and early school start times results in acute and chronic sleep reductions. This is not only harmful for learning but may reduce career prospects and widen social inequalities. Delaying school start times has been shown to improve sleep at least short-term but whether this translates to better achievement is unresolved. Here, we studied whether 0.5–1.5 years of exposure to a flexible school start system, with the daily choice of an 8 AM or 8:50 AM-start, allowed secondary school students (n = 63–157, 14–21 years) to improve their quarterly school grades in a 4-year longitudinal pre-post design. We investigated whether sleep, changes in sleep or frequency of later starts predicted grade improvements. Mixed model regressions with 5111–16,724 official grades as outcomes did not indicate grade improvements in the flexible system per se or with observed sleep variables nor their changes—the covariates academic quarter, discipline and grade level had a greater effect in our sample. Importantly, our finding that intermittent sleep benefits did not translate into detectable grade changes does not preclude improvements in learning and cognition in our sample. However, it highlights that grades are likely suboptimal to evaluate timetabling interventions despite their importance for future success

Validation of the Munich Actimetry Sleep Detection Algorithm for estimating sleep-wake patterns from activity recordings

© 2021 The Authors. Journal of Sleep Research published by John Wiley & Sons Ltd on behalf of European Sleep Research Society. This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.Periods of sleep and wakefulness can be estimated from wrist-locomotor activity recordings via algorithms that identify periods of relative activity and inactivity. Here, we evaluated the performance of our Munich Actimetry Sleep Detection Algorithm. The Munich Actimetry Sleep Detection Algorithm uses a moving 24-h threshold and correlation procedure estimating relatively consolidated periods of sleep and wake. The Munich Actimetry Sleep Detection Algorithm was validated against sleep logs and polysomnography. Sleep-log validation was performed on two field samples collected over 54 and 34 days (median) in 34 adolescents and 28 young adults. Polysomnographic validation was performed on a clinical sample of 23 individuals undergoing one night of polysomnography. Epoch-by-epoch analyses were conducted and comparisons of sleep measures carried out via Bland-Altman plots and correlations. Compared with sleep logs, the Munich Actimetry Sleep Detection Algorithm classified sleep with a median sensitivity of 80% (interquartile range [IQR] = 75%-86%) and specificity of 91% (87%-92%). Mean onset and offset times were highly correlated (r = .86-.91). Compared with polysomnography, the Munich Actimetry Sleep Detection Algorithm reached a median sensitivity of 92% (85%-100%) but low specificity of 33% (10%-98%), owing to the low frequency of wake episodes in the night-time polysomnographic recordings. The Munich Actimetry Sleep Detection Algorithm overestimated sleep onset (~21 min) and underestimated wake after sleep onset (~26 min), while not performing systematically differently from polysomnography in other sleep parameters. These results demonstrate the validity of the Munich Actimetry Sleep Detection Algorithm in faithfully estimating sleep-wake patterns in field studies. With its good performance across daytime and night-time, it enables analyses of sleep-wake patterns in long recordings performed to assess circadian and sleep regularity and is therefore an excellent objective alternative to sleep logs in field settings.ASL received a stipend from the Max‐Weber‐Programm (Studienstiftung), AMB received funding from the Graduate School of Systemic Neurosciences Munich, CR received funding from the Fundação para a Ciência e Tecnologia (FCT) PhD research grants (PDE/BDE/114584/2016), LKP received a fellowship from the Coordenação de Aperfeiçoamento Pessoal de Nível Superior (CAPES, Finance Code 001), and NG received research funding from the FoeFoLe program at LMU (registration No. 37/2013).info:eu-repo/semantics/publishedVersio

The genomes of two key bumblebee species with primitive eusocial organization

Background: The shift from solitary to social behavior is one of the major evolutionary transitions. Primitively eusocial bumblebees are uniquely placed to illuminate the evolution of highly eusocial insect societies. Bumblebees are also invaluable natural and agricultural pollinators, and there is widespread concern over recent population declines in some species. High-quality genomic data will inform key aspects of bumblebee biology, including susceptibility to implicated population viability threats. Results: We report the high quality draft genome sequences of Bombus terrestris and Bombus impatiens, two ecologically dominant bumblebees and widely utilized study species. Comparing these new genomes to those of the highly eusocial honeybee Apis mellifera and other Hymenoptera, we identify deeply conserved similarities, as well as novelties key to the biology of these organisms. Some honeybee genome features thought to underpin advanced eusociality are also present in bumblebees, indicating an earlier evolution in the bee lineage. Xenobiotic detoxification and immune genes are similarly depauperate in bumblebees and honeybees, and multiple categories of genes linked to social organization, including development and behavior, show high conservation. Key differences identified include a bias in bumblebee chemoreception towards gustation from olfaction, and striking differences in microRNAs, potentially responsible for gene regulation underlying social and other traits. Conclusions: These two bumblebee genomes provide a foundation for post-genomic research on these key pollinators and insect societies. Overall, gene repertoires suggest that the route to advanced eusociality in bees was mediated by many small changes in many genes and processes, and not by notable expansion or depauperation

Weekly, seasonal, and chronotype‐dependent variation of dim‐light melatonin onset

In humans, the most important zeitgeber for entrainment is light. Laboratory studies have shown that meaningful changes in light exposure lead to phase shifts in markers of the circadian clock. In natural settings, light is a complex signal varying with external conditions and individual behaviors; nonetheless, phase of entrainment is assumed to be fairly stable. Here, we investigated the influence of season and weekly schedule (as indicators of variation in light landscapes) on phase of entrainment. Using a within-subjects design (N = 33), we assessed dim-light melatonin onset (DLMO) as a circadian phase marker in humans, on workdays and work-free days, in summer (under daylight saving time) and in winter, while also estimating sleep times from actimetry. Our mixed-model regressions show that both season and weekly structure are linked with changes in phase of entrainment and sleep. In summer, both DLMO and sleep times were about 1 hour earlier compared to winter, and sleep duration was shorter. On work-free days, DLMO and sleep times were later, and their phase relationship differed more relative to workdays. All these effects were stronger in later chronotypes (those who habitually sleep late). Our results confirm that phase of entrainment is earlier when stronger zeitgebers are present (summer) and show that it relates to midday or midnight rather than sunrise or sunset. Additionally, they suggest that late chronotypes are capable of rapid phase shifts each week as they move between workdays and work-free days, stimulating interesting questions about the stability of circadian phase under natural conditions

Chronotype and social jetlag: a (self-) critical review

The Munich ChronoType Questionnaire (MCTQ) has now been available for more than 15 years and its original publication has been cited 1240 times (Google Scholar, May 2019). Additionally, its online version, which was available until July 2017, produced almost 300,000 entries from all over the world (MCTQ database). The MCTQ has gone through several versions, has been translated into 13 languages, and has been validated against other more objective measures of daily timing in several independent studies. Besides being used as a method to correlate circadian features of human biology with other factors&mdash;ranging from health issues to geographical factors&mdash;the MCTQ gave rise to the quantification of old wisdoms, like &ldquo;teenagers are late&rdquo;, and has produced new concepts, like social jetlag. Some like the MCTQ&rsquo;s simplicity and some view it critically. Therefore, it is time to present a self-critical view on the MCTQ, to address some misunderstandings, and give some definitions of the MCTQ-derived chronotype and the concept of social jetlag