The biological clock in eukaryotes controls daily rhythms in physiology and behavior. It displays a complex organization that involves the molecular transcriptional clock and the redox oscillator which may coordinately work to control cellular rhythms. The redox oscillator has emerged very early in evolution in adaptation to the environmental changes in O2 levels and has been shown to regulate daily rhythms in glycerolipid (GL) metabolism in different eukaryotic cells. GLs are key components of lipid droplets (LDs), intracellular storage organelles, present in all living organisms, and essential for energy and lipid homeostasis regulation and survival; however, the cell bioenergetics status is not constant across time and depends on energy demands. Thus, the formation and degradation of LDs may reflect a time-dependent process following energy requirements. This work investigated the presence of metabolic rhythms in LD content along evolution by studying prokaryotic and eukaryotic cells and organisms. We found sustained temporal oscillations in LD content in Pseudomonas aeruginosa bacteria and Caenorhabditis elegans synchronized by temperature cycles, in serum-shock synchronized human embryonic kidney cells (HEK 293 cells) and brain tumor cells (T98G and GL26) after a dexamethasone pulse. Moreover, in synchronized T98G cells, LD oscillations were altered by glycogen synthase kinase-3 (GSK-3) inhibition that affects the cytosolic activity of the metabolic oscillator or by knocking down LIPIN-1, a key GL synthesizing enzyme. Overall, our findings reveal the existence of metabolic oscillations in terms of LD content highly conserved across evolutionary scales notwithstanding variations in complexity, regulation, and cell organization.

The phase of signals representing cyclic behavioural patterns provides valuable information for understanding the mechanisms driving the observed behaviours. Methods usually adopted to estimate the phase, which are based on projecting the signal onto the complex plane, have strict requirements on its frequency content, which limits their application. To overcome these limitations, input signals can be processed using band-pass filters or decomposition techniques. In this paper, we briefly review these approaches and propose a new one. Our approach is based on the principles of Empirical Mode Decomposition (EMD), but unlike EMD, it does not aim to decompose the input signal. This avoids the many problems that can occur when extracting a signal\'s components one by one. The proposed approach estimates the phase of experimental signals that have one main oscillatory component modulated by slower activity and perturbed by weak, sparse, or random activity at faster time scales. We illustrate how our approach works by estimating the phase dynamics of synthetic signals and real-world signals representing knee angles during flexion/extension activity, heel height during gait, and the activity of different organs involved in speech production.

Robust circadian rhythms are essential for optimal health. The central circadian clock controls temperature rhythms, which are known to organize the timing of peripheral circadian rhythms in rodents. In humans, however, it is unknown whether temperature rhythms relate to the organization of circadian rhythms throughout the body. We assessed core body temperature amplitude and the rhythmicity of 929 blood plasma metabolites across a 40-h constant routine protocol, controlling for behavioral and environmental factors that mask endogenous temperature rhythms, in 23 healthy individuals (mean [± SD] age = 25.4 ± 5.7 years, 5 women). Valid core body temperature data were available in 17/23 (mean [± SD] age = 25.6 ± 6.3 years, 1 woman). Individuals with higher core body temperature amplitude had a greater number of metabolites exhibiting circadian rhythms (R2 = 0.37, p = .009). Higher core body temperature amplitude was also associated with less variability in the free-fitted periods of metabolite rhythms within an individual (R2 = 0.47, p = .002). These findings indicate that a more robust central circadian clock is associated with greater organization of circadian metabolite rhythms in humans. Metabolite rhythms may therefore provide a window into the strength of the central circadian clock.

The study aimed to assess the regularity, intensity, frequency, and period of activities comprising social rhythm and associate them with the functionality of stroke patients. The sample consisted of 73 patients (41 men and 32 women) with a mean age of 60 years (±10). Social rhythm was assessed by Social Rhythm Metric (SRM) and Activity Level Index (ALI). The functionality was evaluated using the International Classification of Functioning, Disability, and Health (ICF). Data were analyzed using Student\'s t-test, ANOVA, and Chi-square test. The mean SRM was 5.1 ± 0.9, and ALI was 58.3 ± 14.9. Notably, 40% of the patients exhibited both low regularity and low intensity of activities. Six SRM activities, performed with low frequency (going outside, starting work, exercising, snacking, watching other TV programs, and going home), exhibited a tendency to have periods that deviated from the expected 24-hour daily cycle. ICF domains most associated with SRM were: d2-General tasks and demands, d3-Communication, d4-Mobility, d5-Self care, d8-Major life areas, and d9-Community, social and civic life. The results indicated changes in social rhythm with implications for patient functionality. Screening for disruptions in social rhythm could be part of the functional assessment during the rehabilitation process for post-stroke patients.

This study examined the psychometric properties and longitudinal changes of the self-reporting Traditional Chinese version of Biological Rhythms Interview for Assessment in Neuropsychiatry (C-BRIAN-SR) among healthy controls (HC) and patients with major depressive episode (MDE). Eighty patients with a current MDE and 80 HC were recruited. Assessments were repeated after two weeks in HC, and upon the discharge of MDE patients to examine the prospective changes upon remission of depression. The C-BRIAN-SR score was significantly higher in the MDE than HC group. The concurrent validity was supported by a positive correlation between scores of C-BRIAN-SR, Insomnia Severity Index and the Hospital Anxiety Depression Scale. C-BRIAN-SR negatively correlated MEQ in the MDE group (r = .30, p = 0.009), suggesting higher rhythm disturbances were associated with a tendency toward eveningness. A moderate test-retest reliability was found (r = .61, p < 0.001). A cut-off of 38.5 distinguished MDE subjects from HC with 82.9% of sensitivity and 81.0% of specificity. C-BRIAN-SR score normalized in remitted MDE patients but remained higher in the non-remitted. The C-BRIAN-SR is a valid and reliable scale for measuring the biological rhythms and may assist in the screening of patients with MDE.

BACKGROUND: Previous mobile health (mHealth) studies have revealed significant links between depression and circadian rhythm features measured via wearables. However, the comprehensive impact of seasonal variations was not fully considered in these studies, potentially biasing interpretations in real-world settings.
OBJECTIVE: This study aims to explore the associations between depression severity and wearable-measured circadian rhythms while accounting for seasonal impacts.
METHODS: Data were sourced from a large longitudinal mHealth study, wherein participants\' depression severity was assessed biweekly using the 8-item Patient Health Questionnaire (PHQ-8), and participants\' behaviors, including sleep, step count, and heart rate (HR), were tracked via Fitbit devices for up to 2 years. We extracted 12 circadian rhythm features from the 14-day Fitbit data preceding each PHQ-8 assessment, including cosinor variables, such as HR peak timing (HR acrophase), and nonparametric features, such as the onset of the most active continuous 10-hour period (M10 onset). To investigate the association between depression severity and circadian rhythms while also assessing the seasonal impacts, we used three nested linear mixed-effects models for each circadian rhythm feature: (1) incorporating the PHQ-8 score as an independent variable, (2) adding seasonality, and (3) adding an interaction term between season and the PHQ-8 score.
RESULTS: Analyzing 10,018 PHQ-8 records alongside Fitbit data from 543 participants (n=414, 76.2% female; median age 48, IQR 32-58 years), we found that after adjusting for seasonal effects, higher PHQ-8 scores were associated with reduced daily steps (β=-93.61, P<.001), increased sleep variability (β=0.96, P<.001), and delayed circadian rhythms (ie, sleep onset: β=0.55, P=.001; sleep offset: β=1.12, P<.001; M10 onset: β=0.73, P=.003; HR acrophase: β=0.71, P=.001). Notably, the negative association with daily steps was more pronounced in spring (β of PHQ-8 × spring = -31.51, P=.002) and summer (β of PHQ-8 × summer = -42.61, P<.001) compared with winter. Additionally, the significant correlation with delayed M10 onset was observed solely in summer (β of PHQ-8 × summer = 1.06, P=.008). Moreover, compared with winter, participants experienced a shorter sleep duration by 16.6 minutes, an increase in daily steps by 394.5, a delay in M10 onset by 20.5 minutes, and a delay in HR peak time by 67.9 minutes during summer.
CONCLUSIONS: Our findings highlight significant seasonal influences on human circadian rhythms and their associations with depression, underscoring the importance of considering seasonal variations in mHealth research for real-world applications. This study also indicates the potential of wearable-measured circadian rhythms as digital biomarkers for depression.

The biological rhythm is a fundamental aspect of an organism, regulating many physiological processes. This study focuses on the analysis of the molecular basis of circadian rhythms and its impact on the functioning of the liver. The regulation of biological rhythms is carried out by the clock system, which consists of the central clock and peripheral clocks. The central clock is located in the suprachiasmatic nucleus (SCN) of the hypothalamus and is regulated by signals received from the retinal pathway. The SCN regulates the circadian rhythm of the entire body through its indirect influence on the peripheral clocks. In turn, the peripheral clocks can maintain their own rhythm, independent of the SCN, by creating special feedback loops between transcriptional and translational factors. The main protein families involved in these processes are CLOCK, BMAL, PER and CRY. Disorders in the expression of these factors have a significant impact on the functioning of the liver. In such cases lipid metabolism, cholesterol metabolism, bile acid metabolism, alcohol metabolism, and xenobiotic detoxification can be significantly affected. Clock dysfunctions contribute to the pathogenesis of various disorders, including fatty liver disease, liver cirrhosis and different types of cancer. Therefore understanding circadian rhythm can have significant implications for the therapy of many liver diseases, as well as the development of new preventive and treatment strategies.

The origin of biological rhythms goes back to the very beginning of life. They are observed in the animal and plant world at all levels of organization, from cells to ecosystems. As early as the 18th century, plant scientists were the first to explain the relationship between flowering cycles and environmental cycles, emphasizing the importance of daily light-dark cycles and the seasons. Our temporal structure is controlled by external and internal rhythmic signals. Light is the main synchronizer of the circadian system, as daily exposure to light entrains our clock over 24 hours, the endogenous period of the circadian system being close to, but not exactly, 24 hours. In 1960, a seminal scientific meeting, the Cold Spring Harbor Symposium on Biological Rhythms, brought together all the biological rhythms scientists of the time, a number of whom are considered the founders of modern chronobiology. All aspects of biological rhythms were addressed, from the properties of circadian rhythms to their practical and ecological aspects. Birth of chronobiology dates from this period, with the definition of its vocabulary and specificities in metabolism, photoperiodism, animal physiology, etc. At around the same time, and right up to the present day, research has focused on melatonin, the circadian neurohormone of the pineal gland, with data on its pattern, metabolism, control by light and clinical applications. However, light has a double face, as it has positive effects as a circadian clock entraining agent, but also deleterious effects, as it can lead to chronodisruption when exposed chronically at night, which can increase the risk of cancer and other diseases. Finally, research over the past few decades has unraveled the anatomical location of circadian clocks and their cellular and molecular mechanisms. This recent research has in turn allowed us to explain how circadian rhythms control physiology and health.

BACKGROUND: Children with Down syndrome (DS) offer a compelling context within the fieldof human biology for examining potential lunar influences. While the exact mechanisms governing lunar effects are still under investigation, a growing body of scientific inquiry suggests possible connections between lunar phases and physiological, physical, and cognitive parameters. This investigation holds promise for uncovering the intricate interplay between lunar cycles (LCs) and the unique biology of children with DS. This study investigated the potential influence of the LC on physiological, physical, and cognitive parameters in children with DS, focusing on sleep patterns, physical performance, and cognitive abilities.
METHODS: Seventeen children with DS participated in this study. Sleep data, physical performance metrics, and cognitive test results were collected throughout the LC, including the new moon (NM), first quarter, full moon (FM), and third quarter. Statistical analyses were conducted to assess the differences in these parameters across lunar phases.
RESULTS: Significant differences were observed in sleep patterns, with reduced total sleep time (P < 0.01) and sleep efficiency (P < 0.001) during the FM phase. Heart rates (HRs) before (P < 0.001) and after (P < 0.01) exercise also displayed pronounced changes during LC. Additionally, the reaction time (RT) exhibited a significant difference (P < 0.01) across the lunar phases. However, physical performance metrics, including squat jump (SJ), sprint, and 6-minute walk distance (6MWD), did not show significant variations.
CONCLUSIONS: This study suggests that LC may have a moderating effect on sleep patterns, HR, and cognitive performance in children with DS. These findings have practical implications for caregivers and educators and highlight the importance of considering lunar-associated variations in planning schedules and interventions for children with DS.

BACKGROUND: Biological rhythms denote the cyclical patterns of life activities anchored to a 24-hour cycle. Research shows that depression exhibits disturbances in biological rhythms. Yet, the relationship between these biological rhythms and concomitant anxiety symptoms is insufficiently investigated in structured clinical assessments.
METHODS: This multicenter study, carried out in four Chinese hospitals, comprehensively examined the relationship between anxiety and disruptions in biological rhythms among patients with depression. The study encompassed 218 patients diagnosed with depression and 205 matched healthy controls. The Chinese version of the Biological Rhythms Interview of Assessment in Neuropsychiatry was utilized to evaluate the participants\' biological rhythms, focusing on four dimensions: sleep, activity, social, and diet.
RESULTS: In patients with depression, there is a significant positive correlation between the severity of anxiety symptoms and the disturbances in biological rhythms. The severity of anxiety and depression, along with the quality of life, are independently associated with disruptions in biological rhythms. The mediation model reveals that anxiety symptoms mediate the relationship between depressive symptoms and biological rhythms.
CONCLUSIONS: This research highlights the role of anxiety within the spectrum of depressive disorders and the associated disturbances in biological rhythms. Our findings shed light on potential pathways towards more targeted preventive strategies and therapeutic interventions for individuals battling depression and anxiety.