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Earlier human activity relative to sunrise and sunset, the very essence of daylight saving time, is linked with health and safety detriments in humans. A new study predicts that deer, at least, may benefit from earlier human activity through reduced deer-vehicle collisions.

Early school times clash with the late sleep of adolescents, leading to wide-spread sleep restriction in students. Evidence suggests that delaying school starts is beneficial for sleep and recent studies investigated whether this also translates into improved academic achievement. We thus conducted a systematic review of the literature on school start times, grades and test scores in middle and high-school students. We reviewed 21 studies following the PRISMA guidelines and assessed the evidence quality using a pre-defined risk of bias tool. Nine studies reported no association of later starts with achievement, while the remaining reported mixed (5), positive (5), negative (1) or unclear (1) results. Considering the heterogeneity in academic outcomes, study types, amount of delay and exposure, and the substantial risk of bias, a meta-analysis was not warranted - instead we provide grouped reviews and discussion. Overall, no generalisable improvements in achievement with later starts emerge beyond the level of single studies. This does not necessarily preclude improvements in students' learning but highlights shortcomings of the literature and the challenges of using grades and test scores to operationalise academic achievement. Given other previously reported positive outcomes, our results suggest that schools could start later while achievement is likely maintained.

Early school times fundamentally clash with the late sleep of teenagers. This mismatch results in chronic sleep deprivation, which poses acute and long-term health risks and impairs students’ learning. Despite conclusive evidence that delaying school times has immediate benefits for sleep, the long-term effects on sleep are unresolved due to a shortage of longitudinal data. Here, we studied whether a flexible school start system, with the daily choice of an 8AM or 08:50AM-start, allowed secondary school students to improve their sleep and psychological functioning in a longitudinal pre-post design over exactly 1 year. Based on 2 waves, each with 6-9 weeks of daily sleep diary, we found that students maintained their 1-hour-sleep gain on days with later starts, both longitudinally (n=28) and cross-sectionally (n=79). This sleep gain was independent of chronotype and frequency of later starts but differed between genders. Girls were more successful in keeping early sleep onsets despite later sleep offsets, whereas boys delayed their onsets and thus had reduced sleep gains after 1 year. Students also reported psychological benefits (n=93), increased sleep quality and reduced alarm-driven waking on later school days. Despite these benefits on later schooldays, overall sleep duration was not extended in the flexible system. This was likely due to the persistently low uptake of the late-start option. If uptake can be further promoted, the flexible system is an appealing alternative to a fixed delay of school starts owing to possible circadian advantages (speculatively through prevention of phase-delays) and psychological mechanisms (e.g. sense of control).Significance statementTeenage sleep becomes progressively later during adolescence but school starts do not accommodate this shifted sleep window. This mismatch results in chronic sleep deprivation in teenagers worldwide, which is a pervasive public health concern. Delaying school starts could counteract this misalignment if students keep sleep onsets stable. However, few studies have investigated long-term effects of delayed starts on sleep. We observed here that students slept persistently longer and better when school started later in a flexible start system. Girls were especially successful in keeping stable onsets. Students also benefitted psychologically and liked the flexible system despite only a modest uptake of later starts. The flexible system is an interesting alternative to a fixed delay and should receive more scientific attention.

School start times have been at the centre of many scientific and political debates given the accumulating evidence that bell times are generally too early, and thus lead to an epidemic of sleep restriction in the student population. Recent media attention has conveyed the message that later school starts not only improve sleep but also result in better academic achievement. Several studies have been recently published on this topic requiring a comprehensive review of the results to clarify the relationship between later school start times and academic achievement to inform the general public and policy makers.To this end, we conducted a systematic review of the current literature on school starting times and academic achievement in middle and high school students, considering grades and standardised test scores as achievement measures. We followed the PRISMA guidelines for searching, including, and reporting relevant literature and identified 21 studies for detailed analysis. Evidence quality of included studies was assessed with a pre-defined risk of bias assessment using modified items from the GRADE scheme and ROBINS-I tool.About half of the reviewed studies reported no (positive or negative) effect of delaying school times on grades and test scores, while the other half reported either mixed or positive results. Given the strong heterogeneity of included studies, we grouped them according to various characteristics, such as academic outcomes, dose of delay, evidence quality, or study design to identify potential hidden effects. Despite this, we could not identify any generalisable effect beyond single studies as to whether delaying school times has clear beneficial effects on academic performance.Given that grades and scores determine future career trajectories and predict future success, the question whether school start times contribute to academic achievement is of great interest for the general public and needs to be further clarified. Mechanistically, it is very likely that improved sleep leads to or mediates improved cognitive performance and learning, but definitive conclusions on whether this also translates into better grades and scores across all students requires better evidence at this stage. Importantly, this does not preclude other positive outcomes of later start times such as improved sleep (quality), motivation or learning but draws attention on current gaps and shortcomings. To this end, we also highlight critical methodological aspects and provide suggestions to increase the evidence-level and to guide the direction of research in future studies.

After a flight across multiple time zones, most people show a transient state of circadian misalignment causing temporary malaise known as jetlag disorder. The severity of the elicited symptoms is postulated to depend mostly on circadian factors such as the number of time zones crossed and the direction of travel. Here, we examined the influence of prior expectation on symptom severity, compared to said “classic” determinants, in order to gauge potential psychosocial effects in jetlag disorder.To this end, we monitored jetlag symptoms in travel-inexperienced individuals (n=90, 18-37y) via detailed questionnaires twice daily for one week before and after flights crossing >3 time zones. We found pronounced differences in individual symptom load that could be grouped into 4 basic symptom trajectories. Both traditional and newly devised metrics of jetlag symptom intensity and duration (accounting for individual symptom trajectories) recapitulated previous results of jetlag prevalence at about 50-60% as well as general symptom dynamics.Surprisingly, however, regression models showed very low predictive power for any of the jetlag outcomes. The classic circadian determinants, including number of time zones crossed and direction of travel, exhibited little to no link with jetlag symptom intensity and duration. Only expectation emerged as a parameter with systematic, albeit small, predictive value.These results suggest expectation as a relevant factor in jetlag experience - hinting at potential placebo effects and new treatment options. Our findings also caution against jetlag recommendations based on circadian principles but insufficient evidence linking circadian re-synchronization dynamics with ensuing symptom intensity and duration.Significance StatementJetlag disorder afflicts millions of travelers each year - a nuisance on holiday trips but also a danger in safety and performance-critical operations. For effective prevention and treatment, it is critical to understand what influences jetlag severity, i.e. jetlag symptom intensity and duration. In contrast to what guidelines state, in our study, we did not find that symptom severity could be explained by the number of time zones crossed or travel direction. Rather, travelers’ expectations about how long and strongly they will suffer from jetlag symptoms was the only factor systematically predicting jetlag severity. If this holds true not only for subjective but also objective symptoms, we need to revisit assumptions about how circadian desynchronization relates to experienced jetlag symptoms.

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.

With the emergence of big data science, the question how we can easily collect meaningful information about circadian clock phenotypes in large human cohorts imposes itself. Here, we describe potentials and limitations of using questionnaires, specifically the Munich ChronoType Questionnaire (MCTQ), to characterize such circadian phenotypes. We also discuss scenarios when alternative methods might be more appropriate.

With the emergence of big data science, the question how we can easily collect meaningful information about circadian clock phenotypes in large human cohorts imposes itself. Here, we describe potentials and limitations of using questionnaires, specifically the Munich ChronoType Questionnaire (MCTQ), to characterize such circadian phenotypes. We also discuss scenarios when alternative methods might be more appropriate.

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.

This chapter summarizes epidemiological insights into sleep and wake behaviour and covers the limited knowledge about its disorders, with special emphasis on psychiatry. The chapter systematically refers to the interdependencies of four different aspects in both sleep and wake: timing, duration, structure, and quality. It provides an overview of the current methods used in the field for studying this behaviour and predicts that long-term actimetry monitoring in everyday life will revolutionize research into both sleep and the circadian clock. The chapter argues that a stronger alliance between sleep research and circadian biology will help to better understand the different aetiologies of sleep disorders, as well as the relationships between sleep and disease. It is predicted that strengthening our consideration of sleep’s circadian regulation versus its societal constraints—together with improved light environments—will ameliorate many sleep problems. There is also a need to improve public education about sleep and the circadian clock to increase self-awareness of sleep, activity, and light behaviour on an individual level to prevent false self-diagnoses due to misconceptions about sleep.

Sleep deprivation in teenage students is pervasive and a public health concern, but evidence is accumulating that delaying school start times may be an effective countermeasure. Most studies so far assessed static changes in schools start time, using cross-sectional comparisons and one-off sleep measures. When a high school in Germany introduced flexible start times for their senior students—allowing them to choose daily between an 8 am or 9 am start (≥08:50)—we monitored students’ sleep longitudinally using subjective and objective measures. Students (10–12th grade, 14–19 y) were followed 3 weeks prior and 6 weeks into the flexible system via daily sleep diaries (n = 65) and a subcohort via continuous wrist-actimetry (n = 37). Satisfaction and perceived cognitive outcomes were surveyed at study end. Comparisons between 8 am and ≥9 am-starts within the flexible system demonstrated that students slept 1.1 h longer when starting school later—independent of gender, grade, chronotype, and frequency of later starts; sleep offsets were delayed but, importantly, onsets remained unchanged. Sleep quality was increased and alarm-driven waking reduced. However, overall sleep duration in the flexible system was not extended compared to baseline—likely because students did not start later frequently enough. Nonetheless, students were highly satisfied with the flexible system and reported cognitive and sleep improvements. Therefore, flexible systems may present a viable alternative for implementing later school starts to improve teenage sleep if students can be encouraged to use the late-option frequently enough. Flexibility may increase acceptance of school start changes and speculatively even prevent delays in sleep onsets through occasional early starts.

Individuals vary in how their circadian system synchronizes with the cyclic environment (zeitgeber). Assessing these differences in “phase of entrainment”—often referred to as chronotype—is an important procedure in laboratory experiments and epidemiological studies but is also increasingly applied in circadian medicine, both in diagnosis and therapy. While biochemical measurements (e.g., dim-light melatonin onset [DLMO]) of internal time are still the gold standard, they are laborious, expensive, and mostly rely on special conditions (e.g., dim light). Chronotype estimation in the form of questionnaires is useful in approximating the timing of an individual’s circadian clock. They are simple, inexpensive, and location independent (e.g., administrable on- and offline) and can therefore be easily administered to many individuals. The Munich ChronoType Questionnaire (MCTQ) is an established instrument to assess chronotype by asking subjects about their sleep-wake-behavior. Here we present a shortened version of the MCTQ, the µMCTQ, for use in situations in which instrument length is critical, such as in large cohort studies. The µMCTQ contains only the core chronotype module of the standard MCTQ (stdMCTQ), which was shortened and adapted from 17 to 6 essential questions, allowing for a quick assessment of chronotype and other related parameters such as social jetlag and sleep duration. µMCTQ results correspond well to the ones collected by the stdMCTQ and are externally validated by actimetry and DLMO, assessed at home (no measure of compliance). Sleep onset, midpoint of sleep, and the µMCTQ-derived marker of chronotype showed slight deviations toward earlier times in the µMCTQ when compared with the stdMCTQ (

Many regions and countries are reconsidering their use of Daylight Saving Time (DST) but their approaches differ. Some, like Japan, that have not used DST over the past decades are thinking about introducing this twice-a-year change in clock time, while others want to abolish the switch between DST and Standard Time, but don’t agree which to use: California has proposed keeping perennial DST (i.e., all year round) and the EU debates between keeping perennial Standard Time or perennial DST. Related to the discussion about DST is the discussion to which time zone a country, state or region should belong: the state of Massachusetts in the US is considering switching to Atlantic Standard Time, i.e., moving the timing of its social clock (local time) one hour further east (which is equivalent to perennial DST), and Spain is considering leaving the Central European Time to join Greenwich Mean Time (GMT), i.e., moving its social timing one hour further west. A wave of DST discussions seems to periodically sweep across the world. Although DST has always been a political issue, we also need to discuss the biology associated with these decisions because the circadian clock plays a crucial role in how the outcome of these discussions potentially impact our health and performance. Here we give the necessary background to understand how the circadian clock, the social clock, the sun clock, time zones and DST interact. We address numerous fallacies that are propagated by lay people, politicians, and scientists, and we make suggestions of how problems associated with DST and time-zones can be solved based on circadian biology.

Local and national governments around the world are currently considering the elimination of the annual switch to and from Daylight Saving Time (DST). As an international organization of scientists dedicated to studying circadian and other biological rhythms, the Society for Research on Biological Rhythms (SRBR) engaged experts in the field to write a Position Paper on the consequences of choosing to live on DST or Standard Time (ST). The authors take the position that, based on comparisons of large populations living in DST or ST or on western versus eastern edges of time zones, the advantages of permanent ST outweigh switching to DST annually or permanently. Four peer reviewers provided expert critiques of the initial submission, and the SRBR Executive Board approved the revised manuscript as a Position Paper to help educate the public in their evaluation of current legislative actions to end DST.

The temporal dynamics that characterize sleep are difficult to capture outside the sleep laboratory. Therefore, longitudinal studies and big-data approaches assessing sleep dynamics are lacking. Here, we present the first large-scale analysis of human sleep dynamics in real life by making use of longitudinal wrist movement recordings of >16,000 sleep bouts from 573 subjects. Through non-linear conversion of locomotor activity to "Locomotor Inactivity During Sleep" (LIDS), movement patterns are exposed that directly reflect ultradian sleep cycles and replicate the dynamics of laboratory sleep parameters. Our current analyses indicate no sex differences in LIDS-derived sleep dynamics, whereas especially age but also shift work have pronounced effects, specifically on decline rates and ultradian amplitude. In contrast, ultradian period and phase emerged as remarkably stable across the tested variables. Our approach and results provide the necessary quantitative sleep phenotypes for large field studies and outcome assessments in clinical trials.

Internal clocks driving rhythms of about a day (circadian) are ubiquitous in animals, allowing them to anticipate environmental changes. Genetic or environmental disturbances to circadian clocks or the rhythms they produce are commonly associated with illness, compromised performance or reduced survival. Nevertheless, some animals including Arctic mammals, open sea fish and social insects such as honeybees are active around-the-clock with no apparent ill effects. The mechanisms allowing this remarkable natural plasticity are unknown. We generated and validated a new and specific antibody against the clock protein PERIOD of the honeybee Apis mellifera (amPER) and used it to characterize the circadian network in the honeybee brain. We found many similarities to Drosophila melanogaster and other insects, suggesting common anatomical organization principles in the insect clock that have not been appreciated before. Time course analyses revealed strong daily oscillations in amPER levels in foragers, which show circadian rhythms, and also in nurses that do not, although the latter have attenuated oscillations in brain mRNA clock gene levels. The oscillations in nurses show that activity can be uncoupled from the circadian network and support the hypothesis that a ticking circadian clock is essential even in around-the-clock active animals in a constant physical environment.

Ob und wann wir schlafen, wird von zwei Faktoren beeinflusst: wie lange wir wach waren und ob es unsere „innere Uhr“ zulässt. Der erste Faktor ist trivial: Wir wissen aus Erfahrung, dass wir mit zunehmender Wachzeit immer müder werden. Den zweiten Faktor erleben wir, wenn wir todmüde sind, und dennoch nicht einschlafen können, oder wenn wir von selbst zu früh aufwachen, obwohl wir zu wenig geschlafen haben. Für beides gibt es natürlich viele Gründe, aber oft ist unsere innere Tagesuhr daran schuld.

Made available in DSpace on 2015-10-21T20:31:01Z (GMT). No. of bitstreams: 0 Previous issue date: 2015-04-24. Added 1 bitstream(s) on 2015-10-22T09:48:01Z : No. of bitstreams: 1 WOS000353676700001.pdf: 2518339 bytes, checksum: d1f8d18bd059b76504f3fcd9aa639a74 (MD5) National Institutes of Health (NIH) Agriculture and Food Research Initiative Competitive grant from the USDA National Institute of Food and Agriculture Research Council of Norway (NFR) PEW Charitable Trust University of East Anglia, UK Israel Science Foundation (ISF) Biotechnology and Biological Sciences Research Council, UK University of East Anglia University of Alabama College of Arts and Sciences Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Marie Curie International Outgoing Fellowship Swiss National Science Foundation New Faculty Initiative Grant (NFIG) from Illinois State University College of Arts and Sciences DFG Instituto Nacional de Bioinformatica (INB) from ISCIII in Spain 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. Illinois State Univ, Sch Biol Sci, Normal, IL 61790 USA ETH, Inst Integrat Biol, Expt Ecol, CH-8092 Zurich, Switzerland E Carolina Univ, Dept Biol, Greenville, NC 27858 USA Hebrew Univ Jerusalem, Alexander Silberman Inst Life Sci, Dept Ecol Evolut &Behav, Jerusalem, Israel Univ Ghent, Fac Sci, Lab Zoophysiol, B-9000 Ghent, Belgium Univ Otago, Dept Biochem, Labo Evolut &Dev Genet, Dunedin 9054, New Zealand Univ Otago, Dept Biochem, Natl Res Ctr Growth &Dev, Dunedin 9054, New Zealand Univ Missouri, Div Plant Sci, Div Anim Sci, Columbia, MO 65211 USA Univ Missouri, MU Informat Inst, Columbia, MO 65211 USA Georgetown Univ, Dept Biol, Washington, DC 20057 USA Arizona State Univ, Sch Life Sci, Tempe, AZ 85287 USA Univ Copenhagen, Dept Biol, Ctr Funct &Comparat Insect Gen, Copenhagen, Denmark Univ Hohenheim, Inst Anim Sci, D-70599 Stuttgart, Germany Univ Alabama, Dept Biol Sci, Tuscaloosa, AL 35487 USA Univ Illinois, Dept Entomol, Urbana, IL 61801 USA Univ Ghent, Fac Biosci Engn, Dept Crop Protect, Lab Agrozool, B-9000 Ghent, Belgium Univ Halle Wittenberg, Inst Biol, Wittenberg, Germany Univ Geneva, Sch Med, Dept Genet Med &Dev, CH-1211 Geneva, Switzerland Swiss Inst Bioinformat, CH-1211 Geneva, Switzerland MIT, Comp Sci &Artificial Intelligence Lab, Cambridge, MA 02139 USA MIT &Harvard, Broad Inst, Cambridge Ctr 7, Cambridge, MA 02142 USA Univ Munster, Inst Evolut &Biodivers, D-48149 Munster, Germany Ctr Genom Regulat CRG, Barcelona 08003, Spain UPF, Barcelona, Spain Ernst Moritz Arndt Univ Greifswald, Inst Math &Comp Sci, D-17487 Greifswald, Germany Univ Calif Berkeley, Lawrence Berkeley Natl Lab, Genom Div, Berkeley, CA 94720 USA Natl Lib Med, Natl Ctr Biotechnol Informat, Bethesda, MD 20894 USA Norwegian Univ Food Sci, Dept Chem Biotechnol &Food Sci, N-1432 As, Norway Univ E Anglia, Sch Comp Sci, Norwich NR4 7TJ, Norfolk, England Univ Dusseldorf, Inst Evolut Genet, D-40225 Dusseldorf, Germany Univ Cologne, Inst Genet, Cologne, Germany Univ Sao Paulo, Dept Biol, Fac Filosofia Ciencias &Letras Ribeirao Preto, BR-14040901 Ribeirao Preto, Brazil Univ Edinburgh, Ashworth Labs, Inst Evolutionary Biol &Edinburgh Gen, Edinburgh EH9 3FL, Midlothian, Scotland Univ E Anglia, Sch Biol Sci, Norwich NR4 7TJ, Norfolk, England Royal Holloway Univ London, Sch Biol Sci, London, England Maynooth Univ, Dept Biol, Co, Kildare, Ireland Univ Bristol, Sch Biol Sci, Bristol BS8 1TQ, Avon, England CSIRO, Land &Water Flagship, Canberra, ACT, Australia Trin Coll Dublin, Sch Nat Sci, Dept Zool, Dublin, Ireland Zool Soc London, Inst Zool, London NW1 4RY, England ETH, Inst Integrat Biol, Theoret Biol, CH-8092 Zurich, Switzerland Swiss Inst Bioinformat, Lausanne, Switzerland Swiss Fed Inst Technol, Dept Biosyst Sci &Engn, Computat Evolut, Basel, Switzerland USDA ARS, Bee Res Lab, Washington, DC 20250 USA Univ Sao Paulo, Dept Genet, Fac Med Ribeirao Preto, BR-14040900 Ribeirao Preto, Brazil N Carolina State Univ, Ctr Res Sci Computat, Raleigh, NC 27695 USA Kyoto Univ, Grad Sch Agr, Lab Insect Ecol, Kyoto, Japan Univ Sao Paulo, Dept Biol Celular &Mol &Bioagentes Patogen, Fac Med Ribeirao Preto, BR-14040900 Ribeirao Preto, Brazil Inst Fed Educ Ciencia &Tecnol Sao Paulo, BR-15991502 Matao, Brazil Ohio State Univ, Dept Entomol, Wooster, OH 44791 USA Oxford Brookes Univ, Fac Hlth &Life Sci, Dept Biol &Med Sci, Oxford OX3 0BP, England Xian Jiaotong Liverpool Univ, Dept Biol Sci, Suzhou, Peoples R China Univ Hosp Halle Saale, Dept Lab Med, Halle, Germany German Ctr Integrat Biodivers Res iDiv, Leipzig, Germany Univ Southampton, Southampton, Hants, England Univ Leicester, Dept Biol, Leicester, Leics, England Univ Fed Sao Carlos, Ctr Ciencias Biol &Saude, Dept Genet &Evolucao, BR-13565905 Sao Carlos, SP, Brazil Univ Estadual Paulista, Fac Ciencias Agr &Vet, Dept Tecnol, BR-14884900 Jaboticabal, Brazil Univ N Carolina, Dept Biol, Greensboro, NC 27403 USA Natl Ctr Sci Res Demokritos, Inst Biosci &Applicat, Athens, Greece Univ Munich, Munich, Germany Baylor Coll Med, Dept Mol &Human Genet, Human Genome Sequencing Ctr, Houston, TX 77030 USA Univ Illinois, Roy J Carver Biotechnol, Urbana, IL 61801 USA Univ Illinois, Dept Crop Sci, Urbana, IL 61801 USA Univ Illinois, Inst Genom Biol, Urbana, IL 61801 USA MD Anderson Canc Ctr, Sch Hlth Profess, Mol Genet Technol Program, Unit 2, Houston, TX 77025 USA Univ Chicago, Dept Human Genet, Chicago, IL 60637 USA Univ Ghent, Dept Biochem &Microbiol, Lab Prot Biochem &Biomol Engn, B-9000 Ghent, Belgium Queen Mary Univ London, Sch Biol &Chem Sci, Dept Biol &Expt Psychol, London E1 4NS, England Guangzhou Univ, Sch Life Sci, Guangzhou, Guangdong, Peoples R China Johns Hopkins Univ, McKusick Nathans Inst Genet Med, Ctr Computat Biol, Baltimore, MD 21205 USA Univ Illinois, Neurosci Program, Dept Entomol, Carl R Woese Inst Genom Biol, Urbana, IL 61801 USA Departamento de Tecnologia, Faculdade de Ciências Agrárias e Veterinárias, Universidade Estadual Paulista, Jaboticabal, 14884-900, Brazi National Institutes of Health (NIH): DP1 OD006416 National Institutes of Health (NIH): U54 HG003273 Agriculture and Food Research Initiative Competitive grant from the USDA National Institute of Food and Agriculture: 2010-65106-21301 FAPESP: 11/03171-5 Marie Curie International Outgoing Fellowship: PIOF-GA-2011-303312 Swiss National Science Foundation: 31003A-125350 Swiss National Science Foundation: 31003A-143936

Our lives are structured by the daily alternation of activity and rest, of wake and sleep. Despite significant advances in circadian and sleep research, we still lack answers to many of the most fundamental questions about this conspicuous behavioral pattern. We strongly believe that investigating this pattern in entrained conditions, real-life and daily contexts-in situ-will help the field to elucidate some of these central questions. Here, we present two common approaches for in situ investigation of human activity and rest: the Munich ChronoType Questionnaire (MCTQ) and actimetry. In the first half of this chapter, we provide detailed instructions on how to use and interpret the MCTQ. In addition, we give an overview of the main insights gained with this instrument over the past 10 years, including some new findings on the interaction of light and age on sleep timing. In the second half of this chapter, we introduce the reader to the method of actimetry and share our experience in basic analysis techniques, including visualization, smoothing, and cosine model fitting of in situ recorded data. Additionally, we describe our new approach to automatically detect sleep from activity recordings. Our vision is that the broad use of such easy techniques in real-life settings combined with automated analyses will lead to the creation of large databases. The resulting power of big numbers will promote our understanding of such fundamental biological phenomena as sleep.

Our lives are structured by the daily alternation of activity and rest, of wake and sleep. Despite significant advances in circadian and sleep research, we still lack answers to many of the most fundamental questions about this conspicuous behavioral pattern. We strongly believe that investigating this pattern in entrained conditions, real-life and daily contexts— in situ —will help the field to elucidate some of these central questions. Here, we present two common approaches for in situ investigation of human activity and rest: the Munich ChronoType Questionnaire (MCTQ) and actimetry. In the first half of this chapter, we provide detailed instructions on how to use and interpret the MCTQ. In addition, we give an overview of the main insights gained with this instrument over the past 10 years, including some new findings on the interaction of light and age on sleep timing. In the second half of this chapter, we introduce the reader to the method of actimetry and share our experience in basic analysis techniques, including visualization, smoothing, and cosine model fitting of in situ recorded data. Additionally, we describe our new approach to automatically detect sleep from activity recordings. Our vision is that the broad use of such easy techniques in real-life settings combined with automated analyses will lead to the creation of large databases. The resulting power of big numbers will promote our understanding of such fundamental biological phenomena as sleep.

Sleep and wake represent two profoundly different states of physiology that arise within the brain from a complex interaction between multiple neural circuits and neurotransmitter systems. These neural networks are, in turn, adjusted by three key drivers that collectively determine the duration, quality, and efficiency of sleep. Two of these drivers are endogenous, namely, the circadian system and a homeostatic hourglass oscillator, while the third is exogenous - our societal structure (social time). In this chapter, we outline the neuroscience of sleep and highlight the links between sleep, mood, cognition, and mental health. We emphasize that the complexity of sleep/wake generation and regulation makes this behavioral cycle very vulnerable to disruption and then explore this concept by examining sleep and circadian rhythm disruption (SCRD) when the exogenous and endogenous drivers of sleep are in conflict. SCRD can be particularly severe when social timing forces an abnormal pattern of sleep and wake upon our endogenous sleep biology. SCRD is also very common in mental illness, and although well known, this association is poorly understood or treated. Recent studies suggest that the generation of sleep and mental health shares overlapping neural mechanisms such that defects in these endogenous pathways result in pathologies to both behaviors. The evidence for this association is examined in some detail. We conclude this review by suggesting that the emerging understanding of the neurobiology of sleep/wake behavior, and of the health consequences of sleep disruption, will provide new ways to decrease the conflict between biological and societal timing in both the healthy and individuals with mental illness. © 2013 Elsevier Inc.

Following general anesthesia, people are often confused about the time of day and experience sleep disruption and fatigue. It has been hypothesized that these symptoms may be caused by general anesthesia affecting the circadian clock. The circadian clock is fundamental to our well-being because it regulates almost all aspects of our daily biochemistry, physiology, and behavior. Here, we investigated the effects of the most common general anesthetic, isoflurane, on time perception and the circadian clock using the honeybee ( Apis mellifera) as a model. A 6-h daytime anesthetic systematically altered the time-compensated sun compass orientation of the bees, with a mean anticlockwise shift in vanishing bearing of 87° in the Southern Hemisphere and a clockwise shift in flight direction of 58° in the Northern Hemisphere. Using the same 6-h anesthetic treatment, time-trained bees showed a delay in the start of foraging of 3.3 h, and whole-hive locomotor-activity rhythms were delayed by an average of 4.3 h. We show that these effects are all attributable to a phase delay in the core molecular clockwork. mRNA oscillations of the central clock genes cryptochrome -m and period were delayed by 4.9 and 4.3 h, respectively. However, this effect is dependent on the time of day of administration, as is common for clock effects, and nighttime anesthesia did not shift the clock. Taken together, our results suggest that general anesthesia during the day causes a persistent and marked shift of the clock effectively inducing “jet lag” and causing impaired time perception. Managing this effect in humans is likely to help expedite postoperative recovery.

The integrity of extracted ribonucleic acid (RNA) is commonly assessed by gel electrophoresis and subsequent analysis of the ribosomal RNA (rRNA) bands. Using the honey bee, Apis mellifera (Hymenoptera: Apidae), as an example, the electrophoretic rRNA profile of insects is explained. This profile differs significantly from the standard benchmark since the 28S rRNA of most insects contains an endogenous “hidden break.” Upon denaturation, the masking hydrogen bonds are disrupted, releasing two similar sized fragments that both migrate closely with 18S rRNA. The resulting rRNA profile thus reflects the endogenous composition of insect rRNA and should not be misinterpreted as degradation.