Journal of Biological Rhythms

Background: KCNH2 encodes Kv11.1 channel proteins that conduct the rapidly activating delayed-rectifier K+ current (IKr), which is critical for cardiac repolarization. KCNH2 encodes two functional isoforms, Kv11.1a and Kv11.1b, via alternative transcription start sites. Kv11.1a is the principal determinant of cardiac IKr and ventricular repolarization. The circadian clock, a transcriptional-translational feedback loop that cycles with a period of ~24 hours and drives the circadian expression of many genes, including Kcnh2 in the mouse heart. Because daily body temperature rhythms provide a systemic signal that synchronizes cardiac circadian clocks, we tested whether physiological temperature cycles drive the circadian promoter activity of the cloned human KCNH2 (hKCNH2) promoter. Hypothesis: hKCNH2 is a direct transcriptional target of the circadian clock, with temperature driving its promoter activity through BMAL1:CLOCK acting at a conserved tandem E-box. Methods: We cloned the conserved proximal promoter of KCNH2 (-1631 bp upstream of Kv11.1a exon 1) to generate hKCNH2 promoter luciferase reporter constructs. Constructs were transfected into C2C12 myotubes and synchronized by serum shock (static 37{degrees}C) or temperature cycling (36.5-38.5{degrees}C). Bioluminescence was recorded and assessed for period, phase, and amplitude. BMAL1:CLOCK dependence was tested via dominant-negative CLOCK{Delta}19 co-expression. Results: Temperature cycling did not exhibit the rapid damping characteristic of serum-shock-synchronized oscillations, consistent with continuous entrainment by an external zeitgeber rather than a free-running oscillator. Deletion analysis identified a conserved tandem E-box required for oscillation under both serum shock and temperature cycling, and for BMAL1:CLOCK-dependent transactivation (1.75 {+/-} 0.21 vs. 0.86 {+/-} 0.06 RLU, p = 0.0038). CLOCK{Delta}19 reduced hKCNH2 promoter amplitude under temperature cycling without altering period. Conclusion: The circadian clock regulates KCNH2 promoter activity through daily temperature rhythms.

Light influences mood in both clinical and experimental settings, yet it remains unclear how ambient light exposure relates to mood in daily life, which dimensions of mood are most sensitive to light and over what timescales these associations emerge. Here, we combined continuous personal light monitoring using wearable light sensors with repeated assessments of multiple dimensions of mood and affect, including self-reported mood ratings and cognitive measures of affective bias, alongside physiological monitoring in 49 healthy adults living under naturalistic conditions. Brighter light was consistently associated with more positive self-reported mood. Associations emerged over distinct temporal windows, with greater melanopic irradiance during the preceding 30 min associated with increased feelings of energy. Importantly, this association remained significant after accounting for alertness, physical activity and sleep-related covariates, suggesting that it is not solely explained by the established alerting effects of light. In contrast, several positive mood dimensions, including happiness, feeling accompanied, enjoyment, motivation and relaxation, were associated with light accumulated over longer periods (60-240 min). Furthermore, happiness, feeling accompanied, enjoyment and relaxation, but not energy, were also associated with greater cumulative daily exposure to light above 250 lux melanopic equivalent daylight illuminance (EDI), a threshold proposed to support healthy daytime light exposure. Behavioural measures of affective bias showed no robust associations with light exposure. Together, these findings indicate that everyday light exposure is associated with distinct dimensions of mood over different timescales, highlighting a complex relationship between light and affect in daily life. Significance StatementLight is a promising target for improving mental health, yet little is known about how everyday light exposure relates to mood outside laboratory and clinical settings. Using wearable light sensors and repeated mood assessments in healthy adults living under naturalistic conditions, we show that different dimensions of mood are linked to light exposure over distinct timescales, from recent exposure to cumulative light history. Importantly, the association between recent light exposure and feelings of energy remained independent of physical activity and sleep-related factors. These findings demonstrate that effects of light on mood are dynamic and multidimensional, highlighting the need to move beyond simple measures of total light exposure and informing future efforts to design healthier light environments that support emotional wellbeing.

At-home collected salivary Dim Light Melatonin (DLMO) assessments have demonstrated agreement with laboratory-determined DLMO estimates, but key translational gaps remain. We compiled 32 at home salivary DLMO assessments obtained over four years from a healthy adult male (38 to 42 years) with stable sleep-wake patterns to characterize the magnitude of behavioral, environmental, and pharmacologic influences on DLMO and melatonin profile morphology at the individual level. The series included 10 assessments conducted under standardized dim light conditions to establish a baseline pattern, 21 assessments following controlled contextual manipulations (including exogenous melatonin, ambient and bright-light exposures, blue-blocking glasses, diazepam, behaviorally delayed bedtime scheduling, melatonin-rich foods, magnesium, caffeine, alcohol, late-evening anaerobic exercise), and one seasonal photoperiod comparison. Across a series of 10 baseline assessments, DLMO timing demonstrated high intra-individual stability (range: 7:13 PM to 8:43 PM; SD = 28 min), and peak melatonin levels were highly consistent (M = 13.26 pg/mL, SE = 0.46 pg/mL). Within this individual, 5-day magnesium supplementation (3.6 mg/kg per day), caffeine (300 mg), alcohol (6oz of 80-proof), melatonin-rich foods, or intense anaerobic exercise during the DLMO assessment window produced negligible deviation in DLMO timing or changes in peak concentrations. In contrast, continuous bright light (~1500 lux) during the established pre-onset interval suppressed melatonin production and obscured central circadian phase estimation, while bright light exposure after melatonin onset also produced steep declines in melatonin levels. Diazepam (0.12 mg/kg per day, over a 5-day period) delayed melatonin timing and attenuated melatonin levels. In contrast, Escitalopram (0.24 mg/kg per day, over a 60-day period) elevated baseline melatonin concentrations without obvious alteration of the underlying onset of melatonin secretion at the dosage evaluated. A behaviorally delayed sleep-wake time (i.e., 5 hours for 10 days) resulted in a corresponding delay in melatonin onset consistent with entrainment to the altered bedtime. Exogenous melatonin (0.06 mg/kg) produced supraphysiologic concentrations, which precluded interpretation of the endogenous circadian phase. These findings demonstrate that contextual influence on at-home DLMO assessment may differ substantially in effect magnitude at the individual level of analysis. Discussion focuses on the distinction between higher impact, first order threats and low negligible impact second order threats to at-home DLMO measurement validity.

Circadian clocks are evolutionarily conserved systems that orchestrate daily rhythms in human physiology, tissue behavior, and cellular function. In circadian research, the NanoString nCounter platform has emerged as a robust alternative to microarray and RNA sequencing. However, raw instrument output requires specialized preprocessing to handle technical noise. Furthermore, while harmonic regression is widely used to detect periodic signals in biological time-series data, evaluating rhythmicity remains highly challenging in clinical studies characterized by sparse sampling and small sample sizes. To address these limitations, we developed rhythmCI, an easy-to-use R package that integrates established normalization methods with a complete workflow for circadian data analysis. The package incorporates a bootstrapping procedure to estimate confidence intervals for harmonic regression amplitudes, offering a statistically transparent way to quantify rhythmicity in small-cohort studies. rhythmCI provides an end-to-end workflow for NanoString nCounter data, including automated preprocessing, normalization, and visualization. We evaluated the utility and accuracy of the package using synthetic time-series data generated with the Simphony framework, demonstrating that rhythmCI produces interpretable and reliable rhythmicity classifications under controlled simulation conditions. rhythmCI bridges a critical gap in circadian bioinformatics by offering a reliable method to characterize periodicity under challenging experimental designs typical of clinical research. By streamlining NanoString workflows and improving the statistical rigor of rhythm detection in small datasets, rhythmCI enhances the accessibility and reliability of circadian biology analysis.

Circadian clocks enable mosquitoes to anticipate recurring environmental variations and coordinate behaviors critical for survival and disease transmission, such as locomotion, reproduction, host-seeking, and blood-feeding, with times of day when performance is maximal. In Aedes aegypti, locomotor activity follows a robust diurnal rhythm shaped by endogenous circadian clocks and environmental cues, among which light has been shown to be the primary source of temporal information. While early studies established the role of light in regulating locomotor activity, behavior, oviposition and pupation, it remains unclear which features of a light cycle drive changes in circadian rhythms. This question is increasingly relevant as Ae. aegypti is frequently exposed to artificial and dynamic lighting conditions in urban environments. Here, we investigated how transient changes in light schedules influence circadian rhythms in locomotor activity by systematically manipulating the timing, duration, and direction of light exposure. Using a high-throughput assay, we tested over 1900 individuals, including wild-type and timeless knockout mutants, and showed that a single day of al tered lighting is sufficient to induce robust phase shifts, with no evidence of masking effects. A 6-hour light pulse was sufficient to re-entrain mosquitoes regardless of the timing of the pulse, and phase shifts were primarily driven by the offset time of the light pulse, indicating that light-offset acts as a major zeitgeber. Together, these findings challenge conventional assumptions about the timescale of circadian synchronization and highlight the remarkable plasticity of mosquito behavior in response to anthropogenic light. Eventually, these effects could explain the rapid adaptation of the species to urban environments and have potential consequences for disease transmission dynamics.

Passive physical activity is increasingly used as a digital-phenotyping proxy for mood, assuming a stable relationship across people and time. We tested this assumption using daily mood and activity data from 1,072 individuals (121 women, 951 men; 13,909 person-days) in the Juli app. The within-person activity-mood association was stronger in women than men (slope difference -0.194, p = 0.019). Within women, it varied across the menstrual cycle (p = 0.022): absent in the early luteal phase, significant in all other phases, and largest in the late luteal phase (+0.46). A male pseudo-cycle control showed no such modulation (p = 0.974), confirming the effect is cycle-specific rather than a general temporal pattern. Accounting for cycle phase improved out-of-sample mood prediction in women in 75% of cross-validation splits. Digital phenotyping should account for sex and menstrual cycle phase to avoid biased predictions and enable personalized recommendations for women.

Wearable light loggers are increasingly used to assess light exposure in everyday environments in studies of circadian physiology and sleep, yet their accuracy under diverse lighting conditions remains insufficiently understood. This study evaluated three commonly used wearable light loggers (ActLumus, Lido and OcuWEAR) by comparing measurements of photopic illuminance, melanopic equivalent daylight illuminance (m-EDI), and correlated colour temperature (CCT) against a reference spectroradiometer under controlled laboratory conditions and in the field. Measurements were conducted across fluorescent, incandescent, and multiple LED sources, as well as under dynamic daylight exposure. Device performance depended strongly on both light source characteristics and metric type. Illuminance exhibited lower variability, whereas m-EDI and CCT showed substantial device- and condition-specific biases, particularly under spectrally atypical illumination conditions. These differences were consistent with spectral mismatch effects arising from standard photometric calibration practices. Importantly, the impact of measurement bias varied by exposure context: under dim light conditions, small absolute deviations led to substantial misclassification relative to currently recommended thresholds, whereas brighter electric light and daylight conditions were more robust. These findings highlight that device- and context-dependent biases can influence the interpretation of light exposure in circadian and sleep research, underscoring the need for careful device selection and data interpretation.

Over the course of evolution, many species have adapted to the environmental conditions found at higher latitudes. This is likely also true of the circadian system, which regulates daily behavior and helps measure day length to facilitate adaptation to the seasons, though how the circadian clock adapts to latitude remains largely unknown. Here, we investigated daily activity patterns under long photoperiods and in constant darkness, as well as the underlying circadian clock network, in 52 Drosophila species from around the world. We found a strong, significant positive correlation between the clock's plasticity, measured as the phase difference between morning and evening activity, and the average geographical latitude from which the species originate. The mechanisms underpinning this increase in plasticity differed between species: in the subgenus Siphlodora, the clock weakened with increasing latitude, accompanied by a reduction of the neuropeptide Pigment-Dispersing Factor in the small ventrolateral clock neurons (s-LNv), whereas in the subgenus Drosophila the opposite was true. The subgenus Sophophora, by contrast, showed a negative correlation between circadian plasticity and PDF levels in the s-LNv axons. These results suggest that Drosophila species have evolved diverse, independent strategies to adapt their circadian clock to higher latitudes.

The circadian clock allows living systems to anticipate environmental daily variations by scheduling cellular mechanisms according to the time of the day. The reciprocal interplay between metabolism and circadian clock is essential for energy homeostasis, and the disruption of metabolic clock inputs contributes to dysfunction of clocks in peripheral tissues. However, the molecular mechanisms through which the feeding/fasting cycle entrains peripheral clocks remain incompletely understood. Here, we investigate experimentally and theoretically the role of AMP-dependent kinase (AMPK), a key fasting sensor, in metabolic regulation of the circadian clock. Using a luciferase reporter driven by the Bmal1 promoter to monitor molecular clock activity in human U2OS cells, and thanks to a signal processing method based on the Hilbert transform to retrieve the instantaneous phase and period of circadian signals, we show that pharmacological activation of AMPK by AICAR significantly elevates Bmal1 promoter activity and markedly lengthens the clock period in a dose-dependent manner. Conversely, the clock period is shortened by the pharmacological inhibition by SR18292 of Peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC-1-alpha). Importantly, the action of AICAR is abolished by FK866, a nicotinamide phosphoribosyltransferase (NAMPT) inhibitor, demonstrating that AMPK-dependent modulation of Bmal1 promoter activity requires NAD+ availability. These experimental results are recapitulated by numerical simulations of our previously published mathematical model, where PGC-1-alpha plays a key role in mediating AMPK activity to the clock. Moreover, the comparison of experimentally measured and theoretically predicted phase response curves, following AMPK activation at different circadian phases, provides an additional validation of the model. By integrating biological experiments with mathematical modeling, our results identify a key mechanism through which metabolic factors can entrain and regulate the circadian clock via NAD+-dependent AMPK-mediated regulation of Bmal1 promoter activity.

Light history leaves persistent changes in circadian period, but where this history is stored remains unresolved. Suprachiasmatic nucleus (SCN) network models have often approached photoperiodic encoding through phase organization or coupling strength. We computationally tested slow adaptation of subregion-specific intrinsic periods as an alternative memory mechanism. The model asymmetrically couples dorsal (D) and ventral (V) SCN oscillators and adds a systemic oscillator (X) representing putative circadian feedback present in vivo but lost ex vivo. With a single parameter set, period adaptation captured the direction and approximate magnitude of behavioral aftereffects across photoperiod and T-cycle conditions. Adapting coupling strength instead of period failed to reproduce the V-leading-D phase order reported after T22. Removing systemic feedback preserved the photoperiod-dependent period ordering but inverted the T22 and T26 aftereffects, an inversion that matched SCN explant observations. The model also yielded distinct D-V phase organization for each of 18:6 LD, T23, and T25. These results suggest that subregion-specific period plasticity provides a parsimonious substrate for encoding light history, while the dependence on systemic feedback indicates that behavioral period may not be a readout of the SCN alone. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=160 SRC="FIGDIR/small/743784v1_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@d48266org.highwire.dtl.DTLVardef@1bd15bdorg.highwire.dtl.DTLVardef@de3d9forg.highwire.dtl.DTLVardef@9fbc39_HPS_FORMAT_FIGEXP M_FIG C_FIG A model with dorsal period adaptation and phenomenological systemic feedback accounts for behavioral and explanted SCN aftereffects. (A) During T22 entrainment, dorsal (D), ventral (V), and systemic (X) oscillators remain phase-locked. After release into constant darkness, systemic coupling maintains a unified in vivo rhythm, whereas removing X feedback in the explant simulation allows the D-V network to express a distinct ex vivo period aftereffect. (B) The SCN model is modeled as an asymmetrically coupled attractive-repulsive oscillator network with stronger photic input to V. Light history is encoded via plasticity of the intrinsic period in D, while X represents putative systemic circadian feedback available in vivo and lacking direct photic input. (C) The model reproduces concordant period changes in behavior and SCN explants across photoperiods, but opposing period changes following T-cycle entrainment.

Mammalian circadian rhythms are primarily entrained by light, but nonphotic cues can also reorganize behavioral timing through mechanisms that remain poorly understood. Nocturnal foot shocks delivered to rodents while they forage away from the safety of their nesting area have been shown to entrain circadian behavioral rhythms and shift foraging and feeding to the daytime. To identify the neural circuits underlying this nonphotic fear entrainment, we optogenetically stimulated tachykinin 1-expressing neurons in the parabrachial nucleus (Tac1PBN) during the subjective night while the animals foraged outside of their nest, which recapitulated the total activity-rest phase switch in circadian behaviors induced by foot shocks. Furthermore, selective stimulation of Tac1PBN projections to the central amygdala (CeA) produced a significant but reduced phase shift compared to direct stimulation of Tac1PBN cell bodies. When Bmal1, a core clock gene, was conditionally deleted from the CeA, mice failed to fear-entrain, implicating the CeA molecular clock as a necessary component for fear entrainment. Together, these experiments demonstrate that activation of a defined neuronal population outside of the suprachiasmatic nucleus (SCN) can reorganize circadian behavior by engaging a non-SCN circadian oscillator network that requires an intact CeA molecular clock.

Analysis of circadian patterns in time-series data requires computational methods that can accommodate several factors, including variable sampling resolution, replicate number, and missing values. Most existing tools simplify rhythmicity to a strict dichotomy based solely on a single p-value threshold. This leads to a level of uncertainty that affects many biological targets. We developed CODAC (Circadian Oscillation Detection Analysis and Comparison), a framework that integrates nonlinear constrained optimization with a multicriteria rhythmicity classification scheme to evaluate rhythmic patterns without relying on a single statistical cutoff. This approach allows CODAC to identify and exclude medium-confidence rhythms rather than force them into a rhythmic/arrhythmic dichotomy. CODAC comprises four modules: (i) CODAC_single estimates rhythmicity within a single group; (ii) CODAC_flex extends this to identify distinct waveform types within one group; (iii) CODAC_compare performs pairwise comparisons across two or more groups to detect rhythmic or arrhythmic changes; and (iv) CODAC_multi handles more complex designs involving multiple-group comparisons. Using in silico simulations and public transcriptomic datasets, we show that CODAC performs comparably to established methods while providing additional flexibility for rhythm classification and comparison. Taken together, CODAC provides a flexible and open-source package for circadian timeseries analysis with automated visualization tools.

Background Sleep, mood, and affective states are mutually connected. There is a paucity of studies, however, that have considered bidirectional relationships between daily sleep-affective dyads in naturalistic settings, particularly for shift workers. Objective To evaluate the dynamic and temporal interplay of daily smartphone-based self-reported sleep measurements, dimensions of affective experience and cognitive processing in UK shift working nurses. Methods The EClocker Study prospectively monitored 102 National Health Service (NHS) nurses (aged 25-61 years, 83.3% female) working standard (day shift) and non-standard (fast rotating shifts) schedules over a two-week period. Smartphone-based Experience Sampling Methodology (ESM) recorded daily sleep, mood, momentary affect and cognitive attentional functioning. Self-reported burnout, emotional dysregulation, emotion reactivity and affective dimensions (positive and negative) were also collected. Findings Overall, NHS nurses reported a high prevalence of depressive symptoms, stress, burnout and sleep-circadian rhythm disturbances. Generalised Additive Modelling (GAMs) revealed that NHS nurses higher perceived sleep quality predicted better next-day mood state, while better daytime mood was associated with reduced sleep onset latency, such that participants reported falling asleep faster. In contrast, daytime mood or affect (positive and negative) had no substantial, direct impact on nurses subjective sleep parameters (sleep quality, sleep duration, sleep efficiency). Exposure to fast rotating night shifts across the two-week study was associated with more frequent response errors on a Choice Reaction Time (CRT) cognitive task, while daytime somnolence did not adversely influence nurses momentary reaction time speeds or attentional function. Conclusions Clinically relevant sleep impairments, insomnia-related symptoms, elevated stress, and poor mood were pervasive in a sample of UK NHS nurses, regardless of shift type. Sleep quality impacted next-day mood and daytime mood impacted sleep latency, while rotating shifts led to an increase in cognitive errors. Recognising the impact of shiftwork and designing interventions to promote better sleep quality offer potential to enhance mood and performance in healthcare professionals. Clinical implications We need to implement and evaluate interventions that regularise sleep patterns and promote sleep quality to alleviate mood symptoms among frontline NHS shift workers.

Study Objectives: Poor maternal sleep is associated with adverse health outcomes for women and their offspring, and perturbations to tryptophan metabolism through the kynurenine pathway (KP) may contribute. Kynurenic acid (KYNA), a neuroactive KP metabolite and endogenous modulator of glutamatergic and cholinergic neurotransmission, is of particular interest because elevated KYNA has been linked to altered sleep-wake behavior and neurodevelopmental outcomes. Because sleep patterns and KP metabolism change during pregnancy, we tested whether pregnancy modifies the effects of kynurenine supplementation on sleep-wake architecture. Methods: To model enhanced KP metabolism, we used the embryonic kynurenine (EKyn) model, in which the maternal diet is supplemented with kynurenine, the initial KP metabolite, during the last week of gestation. Using a within-subject design, we evaluated sleep-wake parameters in pregnant and non-pregnant female rats and assessed KYNA in brain and saliva. Results: Pregnancy increased dark phase NREM and REM sleep in control-fed (ECon) dams, a pattern largely maintained in EKyn dams. However, near parturition, EKyn dams exhibited reduced light phase REM sleep that was not observed in controls. In non-pregnant females, kynurenine supplementation produced a stronger phenotype, consistently reducing light phase REM sleep across treatment days. During pregnancy, kynurenine-associated sleep effects were detectable only when compared to within-subject non-pregnant baseline. Salivary KYNA distinguished kynurenine-fed females from matched controls and correlated with brain KYNA levels. Conclusion: These findings show that pregnancy reshapes sleep-wake architecture and attenuates, but does not eliminate, kynurenine-associated REM sleep disruption, implicating KP metabolism and potentially elevated brain KYNA in maternal sleep regulation.

Circadian rhythms in transcription are facilitated by well-defined genetic circuits, but how molecular clocks drive daily rhythms in mammalian physiology is poorly understood. The mechanistic target-of-rapamycin (mTOR) complex integrates daily systemic and circadian intracellular timing cues for input into the cellular timekeeping machinery. Here we demonstrate that mTOR is a major clock output pathway whose activity is required for most daily variation in cellular and organismal physiology, with PERIOD2 shown to interact directly with mTORC1. Acute mTOR inhibition abolishes functional rhythms in cells and most daily variation in mouse liver physiology. mTOR activity is not required for clock protein or locomotor rhythms, indicating that mTOR is not part of the cellular or central circadian timekeeping mechanism. In the forebrain, mTOR activity is required for most detectable daily rhythms in protein abundance and phosphorylation; however, the daily architecture of the sleep/wake cycle is remarkably preserved in mice and zebrafish under mTOR blockade, with a significant increase in wakefulness. Clock outputs in Arabidopsis (plant) and Neurospora (fungus) are also more sensitive to mTOR inhibition than core clock mechanisms indicating evolutionary conservation of mTOR as a circadian effector. We conclude that most but not all daily physiological rhythms in mammalian cells and tissues depend on rhythmic regulation by the mTOR pathway.

The prevalence of shift work-centric industries and the rise of flexible working render it crucial to investigate the health risks posed by unnatural patterns of work and sleep. Shift working in healthcare has been linked to emotional dysregulation, reduced alertness, and cognitive impacts, with Shift Work Disorder (SWD) classified as a circadian rhythm sleep-wake disorder in the DSM-5. These impacts have historically been attributed to schedule-related sleep disturbances; however certain individuals appear more acutely affected. One measure of individual inflexibility to altered routines is chronotype distinctness, an amplitude dimension of the Caen Chronotype Questionnaire (CCQ). Here, we use Structural Equation Modelling (SEM) to unravel the mechanisms by which sleep and chronotype distinctness govern the neuropsychiatric symptom profiles of a cohort of National Health Service (NHS) shift workers (n=102). We constructed a measurement model, extracting latent constructs from questionnaires for sleep disturbances (PSQI), chronotype distinctness (CCQ), mood disorder (MDQ), depression (PHQ8) and emotional reactivity (ERS), and cognitive assessments. Correlations were identified between constructs, then translated into two SEMs - day and rotating shifts respectively - with sleep and distinctness as predictors of detrimental effects. Models were tested for direct effects, significant paths, and overall model fit. We found that, whilst sleep governed fatigue-based symptoms in day-shift workers, chronotype distinctness determined the severity of adverse effects in rotating-shift workers, including mood disorders and cognitive impairments. We surmise that high chronotype distinctness should be considered a risk factor for adverse effects surrounding night and rotating-shift work, and that interventions should incorporate chronotype-specific remediation.

Circadian rhythms are critical for maintaining homeostasis and regulating physiological functions, and consequentially impact disease progression; yet, they remain largely overlooked in in vitro models used in preclinical research. One major barrier to rigorously testing the role of circadian rhythms in these models is the lack of accessible tools that seamlessly integrate into standard culture setups and are capable of sustainably delivering time cues to cells and tissues in long term experiments. Here, we present the ThermoClock, a low-cost, Arduino-based automated temperature control system capable of delivering independent temperature programs to multiple cultures simultaneously. Using circadian reporter U2OS cell lines (Bmal1:Luc and Per2:Luc), we demonstrated that ThermoClock-driven temperature cycles (36{degrees}C/38.5{degrees}C, 12h:12h) produced significantly higher amplitude entrainment than a programmable incubator delivering identical temperature trajectories, suggesting that the ramp time to setpoint is a critical determinant of entrainment strength. We further applied ThermoClock to skin explants from keratinocyte-specific Dbp:Luc reporter mice, showing that circadian temperature cycles (T24: 12h:12h and T25: 12.5h:12.5h) extended synchronized circadian rhythms ex vivo, while a shortened T-cycle (T20: 10h:10h) induced rhythm disruptions. We also observed reduced cell migration in T20 temperature-entrained explants wounded ex vivo, closely recapitulating attenuated wound healing observed in T20 light-cycle-disrupted mice in vivo. Finally, we show that wounding can act as a phase-resetting cue but its efficacy depends on pre-injury entrainment state, with circadian entrained tissues (T25) resisting reset, while disrupted (T20) and unentrained tissues showed resetting sensitivity. These findings establish ThermoClock as a versatile platform for incorporating circadian regulation and, for the first time, disruption into 2D and 3D in vitro systems and demonstrate that peripheral clock disruption and its functional consequences can be modeled ex vivo.

RationaleThe -opioid receptor (MOR) is widely expressed across tissues and plays crucial roles in pain and stress responses, social behaviour, and immune regulation. Recent evidence indicates seasonal variation in in vivo MOR signalling; for example, short photoperiods are associated with reduced central MOR availability, increased MOR expression in brown adipose tissue (BAT), and strengthened brain-BAT interactions. However, despite this coupling with photoperiod, it remains unclear whether static daylength and dynamically changing photoperiods exert distinct effects, as adaptation to photoperiod transitions may itself induce stress-related modulation of the MOR system. Elucidating how seasonal, stress-related adaptations influence MOR signalling is essential for advancing our understanding of seasonal fluctuations in mood and stress regulation. MethodsWe compared rats housed under seasonal photoperiod cycling with those maintained under constant photoperiod conditions, using ex vivo radioligand binding to directly assess MOR density in central and peripheral tissues. ResultsRats exposed to seasonal photoperiod cycling showed markedly reduced inter-individual variability in MOR density in both the brain (including the cerebellum and striatum) and peripheral tissues (adrenal glands), whereas no tissues exhibited substantially increased variability. ConclusionsThese findings demonstrate that seasonal photoperiod cycling stabilizes MOR dynamics at the population level, suggesting stress-related synchronization of MOR signalling. The findings deepen our understanding of seasonal effects on endogenous MOR signalling, and further underscore the role of seasonal light variation in modulating mood-related processes.

Sleep expression in wild animals is regulated by their ecological context. Yet, how populations of a species differ in their sleep in response to environmental challenges such as urbanization, remains to be fully understood. Robust quantification of sleep in small animals, such as lizards, has so far been methodologically difficult, limiting population-level assessments. Using recently developed miniature loggers, we recorded sleep in 19 wild-caught individuals of the Peninsular rock agama lizard (Psammophilus dorsalis). We compared individuals from urban and rural environments and measured electro-oculogram (EOG)-derived sleep parameters: sleep duration, bout frequency, bout duration, and interval between bouts. We then subjected all individuals to an acute stressor (handling-restraint) and examined changes in sleep expression. We found that this species slept mostly at night, with an average total sleep time of 11h 10min. EOG-derived sleep characteristics did not differ substantially between populations, although daytime sleep bouts were more consolidated (shorter interval between bouts) in urban lizards. Contrary to evidence from mammals, acute restraint stress did not impact sleep, overall or for either population. To complement these measures, we also measured the latency to arousal after exposure to vibration stimuli in a separate set of urban and rural lizards (n = 12 each), and found that urban individuals responded marginally quicker at night compared rural individuals, demonstrating greater vigilance and/or more fragmented sleep. Overall, we show that sleep characteristics of wild animals in a common garden condition can be conserved within a species, with limited context-dependent variation between populations.

Chronic social isolation induces persistent behavioral and physiological changes across species. In humans, prolonged social isolation is associated with insomnia and increased risks of cognitive decline, cardiovascular disease, compromised immunity, and premature mortality. Yet whether these consequences are modified by the environment in which social isolation is experienced remains unclear. In particular, can access to social sensory information from conspecifics alleviate the effects of isolation and can various ambient environmental settings modify them? A related question arises during behavioral measurement because behavioral assays themselves impose a new environmental context. Whether these assays simply capture the enduring effects of prior social experience or further modify those effects remains unknown. Using social isolation-induced sleep loss in Drosophila as a model, we systematically examined how the social, spatial, and photoperiodic environments during isolation and behavioral monitoring influence the isolation phenotype. Providing isolated flies with visual, olfactory, or tactile social cues from conspecifics living behind a divider, either individually or in combination, was insufficient to alleviate sleep loss. Spatial confinement exacerbated isolation-induced sleep loss, while winter-like photoperiod in spatially confined Drosophila Activity Monitor assays revealed the clearest progressive decline in sleep during sleep monitoring. Together, these findings demonstrate that social isolation-induced sleep loss is both enduring and dynamic: it persists despite exposure to social cues yet remains sensitive to the environmental context in which isolation is experienced and behavior is measured. More broadly, our study establishes a tractable framework for investigating the environmental modulation of chronic social isolation.