Journal of Biological Rhythms

Both active movement profiles and robust circadian rhythms are linked to improved health outcomes, yet the underlying mechanisms remain partially understood. We investigated this relationship in young adults (n = 169, aged 18-30 years) under real-world conditions using actigraphy data. We performed k-means clustering on 12 accelerometer-based features capturing magnitude, duration, frequency, and intensity distribution to derive movement behavior profiles. As a proxy of circadian rhythms integrity we computed the Circadian Function Index (CFI), which combines intradaily variability, interdaily stability, and relative amplitude. We also assessed circadian phase and sleep quality parameters. Additionally, we quantified light exposure and physical activity over 3-hour daily intervals. The unsupervised algorithm identified two non-overlapping profiles among participants, the More Active (MA) and the Less Active (LA) profiles. MA exhibited a higher CFI (0.81 {+/-} 0.06 vs. 0.69 {+/-} 0.06, p <0.001), which was also positively associated with early-evening physical activity, but not with light exposure. MA also showed an earlier circadian phase, estimated as the midpoint of the five least active hours (L5c, 04:30 {+/-} 01:03 vs. 04:59 {+/-} 01:15, p adj. = 0.04), which was inversely associated with early-morning physical activity and late-morning light exposure. We found no differences in sleep quality between MA and LA. Our results underscore the association between movement behavior and overall circadian rhythms integrity. Importantly, these findings reinforce actigraphy as a multidimensional tool for both health research and clinical applications.

Actigraphy is a non-invasive and cost-effective method for monitoring behavioral rhythms under real-world conditions by collecting time-resolved measurements of locomotor activity, light exposure, and temperature. Although several open-source packages support specific aspects of actigraphy analysis, aspects such as preprocessing, metric calculation, and mathematical modeling are often distributed across separate software packages, limiting interoperability and increasing programming overhead. Here we introduce circStudio, a Python package that unifies actigraphy data processing and mathematical modeling of circadian rhythms within a single framework. Built from the pyActigraphy codebase and integrating circadian models from the Arcascope circadian package, circStudio provides flexible preprocessing tools, support for multiple actigraphy file formats through adaptor classes, standalone functions for computing commonly used actigraphy metrics, and implementations of several mathematical models of circadian rhythms. The package enables users to move efficiently from raw wearable data to physiologically interpretable circadian outputs. Ultimately, circStudio aims to facilitate reproducible workflows and to provide a flexible foundation for research applications across circadian biology, sleep science, and digital health.

Abstract Background: While total physical activity is a recognized modifier of cancer risk, accelerometer-derived digital phenotyping enables high-resolution mapping of circadian behavior. Whether these multidimensional patterns comprising step counts, sleep, physical activity, circadian rhythmicity, and light exposure independently influence the risk of incident colorectal cancer (CRC) has not been comprehensively evaluated Methods: We performed an exposure-wide association study (ExWAS) of 224 accelerometer-derived metrics among 95,050 UK Biobank participants who were free of CRC at accelerometry. To comprehensively define circadian rhythm patterns, we systematically categorized these metrics into five core behavioral domains: step counts, sleep architecture, physical activity bouts, circadian rhythmicity, and light exposure. Hazard ratios (HRs) and 95% confidence intervals were estimated using Cox proportional hazards models with age as the underlying timescale. Results: During a median follow-up of 8.5 years, 775 participants developed CRC (503 colon; 269 rectal). In minimally adjusted models, 121 metrics showed nominal significance (31 for overall CRC, 89 for colon, and 1 for rectal cancer). Protective associations were predominantly observed for metrics characterizing activity intensity and bout structure; notably, higher mean acceleration during 5-10 minute bouts of moderate-to vigorous physical activity was associated with reduced CRC risk (HR 0.88 per SD). In contrast, no metrics within the defined sleep or light exposure domains reached nominal significance. These associations attenuated substantially following progressive adjustment for lifestyle and metabolic covariates, suggesting potential confounding or shared biological pathways. Conclusions: Our findings identified specific behavioral phenotypes within a multidimensional framework of circadian rhythm, including step counts, physical activity intensity, and bout structure, as being associated with CRC risk. However, the marked attenuation of signals after multivariable adjustment suggests these markers may not serve as independent predictors. These results underscore the complexity of multidimensional circadian digital biomarkers and necessitate independent replication to clarify their utility in cancer risk stratification.

The light-dark cycle shaped by Earths rotation provided the evolutionary conditions under which circadian rhythms emerged. Consistent with this, previous studies indicate that less than 40% of total blind individuals, who lack photic input, entrain to the 24-h cycle, further evidencing the critical role of light as the dominant zeitgeber for circadian alignment. However, this assumption has been tested almost exclusively in temperate, high-latitude regions, where environmental cues vary seasonally. Near the equator, by contrast, photoperiod and temperature cycles remain exceptionally stable. This highlights a fundamental gap: can circadian rhythms in humans remain synchronised without light when environmental temporal cues are highly regular? We addressed this question in 58 blind adults (21-77 years; 43.1% female) living near the equator in Rio Grande do Norte, Brazil ([~]5{degrees}S), who wore wrist actigraphy continuously for four weeks. Light sensitivity was assessed through the pupillary light reflex (PLR; 22 PLR-reactive, 36 non-reactive). Applying a semi-supervised machine learning approach to uncover multidimensional patterns without prior categorisation, we identified two distinct phenotypes: a Higher Circadian Stability (HCS; 72%, n = 42) and a Lower Circadian Stability group (LCS; 28%, n = 16). Notably, 64% of PLR-non-reactive individuals (23 of 36) were classified within the HCS group, a proportion approximately 1.6 times higher than previously reported for blind cohorts. These findings demonstrate that, under exceptionally regular equatorial conditions, non-photic cues can sustain a robust circadian entrainment even in the absence of photic input. We propose that environmental regularity promotes the synergy of non-photic timing signals, underscoring ecological context as a key determinant of human circadian temporal organisation.

BackgroundThe mechanisms underpinning associations between sleep and psychiatric conditions are poorly understood, partly due to challenges with longitudinal sleep studies outside the laboratory. Children and young people with rare genetic conditions caused by micro-deletions or -duplications (Copy Number Variants or CNVs) have increased risk of disrupted sleep and poorer neurodevelopmental (ND) outcomes. The Sleep Detectives study aims to investigate this by tracking behavioural and neurophysiological signatures of sleep health in young people with ND risk or ND-CNVs. To optimally achieve this, we have worked with families with ND-CNVs and charity partners to co-design our tools, methods, study protocol, and materials. MethodWe established a Lived Experience Advisory Group (LEAP) with nine parents and 13 children and young people with ND-CNVs, alongside representatives of UK charities Max Appeal and Unique. Together, the research team and LEAP co-designed two in-person family workshops in which we collected feedback on the acceptability of sleep monitoring devices, the design of bespoke cognitive tasks, and overall study protocol. Informal interviews and surveys were conducted with LEAP members and researchers, to enable the team to reflect and learn from their Patient/Public Involvement (PPI) experiences. ResultsKey outputs included pre-workshop invitation and briefing materials and insights that iteratively refined the main study design, including the need for flexibility to increase accessibility, selection of sleep devices, customisation of cognitive tasks, and choice of language in documents. The PPI process was highly valued by LEAP members, workshop attendees, and the research team. One investigator described the PPI work as "reinvigorating my love of research by helping me focus on science that matters". Participating families also established peer support networks. ConclusionsInvolving families affected by ND-CNVs in co-designing the Sleep Detectives study maximised opportunities for acceptability, accessibility and scalability. The research team gained inspiration and deeper understanding of the impact of ND-CNVs on families. Families gained awareness about research, established connections with each other and peer support, and were enthusiastic about future research involvement. This experience empowered families to engage more deeply with the research process and helped the PPI work to be more impactful and inclusive. Plain English summaryChildren and young people with rare genetic conditions caused by small deletion or duplication of genetic material are more likely to experience sleep difficulties such as insomnia, restless sleep, and tiredness. They also show an increased likelihood of neurodevelopmental conditions such as learning disability and autism, and mental health issues such as anxiety. The Sleep Detectives team wanted to explore how these genetic conditions affect childrens sleep, cognition and psychiatric health. To make sure that the project design was well suited to the children and young people that would be invited to participate, the team worked closely with families to design the study. Parents and caregivers of affected children and young people were invited to join a Lived Experience Advisory Panel (LEAP), together with charity representatives and Sleep Detective researchers, to co-design two hands-on workshops, and advise on study design. Children and young people and parents/caregivers attending the workshops tried out and provided feedback on tools and devices that the research team were developing. They also advised on the arrangements and support families might need whilst taking part, and on the study protocol. This collaborative approach helped ensure the study design was optimally suited for the recruitment and participation of children and young people and their families. This report documents our public involvement work for the Sleep Detectives study, illustrating the difference the partnership between researchers and families has made to the project, and the wider benefits for all concerned.

An increasing number of epidemiological and experimental studies have demonstrated a bidirectional relationship between mood disorders and the circadian system, with disrupted circadian rhythms contributing to depressive states, and their restoration playing a key role in antidepressants effects. In this context, we sought to examine whether key molecular targets of antidepressants exhibit diurnal regulatory patterns. Naive adult male and female C57BL/6 mice were euthanized at 3-hour intervals beginning at Zeitgeber Time 0 (ZT0), and hippocampal (HC) and medial prefrontal cortex (mPFC) tissues were collected for RT-qPCR and western blot analyses. We observed statistically significant diurnal rhythmicity in all analyzed transcripts (cFos, Arc, Nr4a1, Dusp1, Dusp5, and Dusp6) in both HC and mPFC samples, with peak expression occurring during the dark (active) phase (ZT15-18). Phosphorylation levels of TrkBY816 (tropomyosin-related kinase) and GSK3{beta}S9 (glycogen synthase kinase 3{beta}) also showed periodic rhythmicity, peaking during the light (inactive) phase. Levels of p-ERK2T185/Y187 (extracellular-signal regulated kinase) did not display rhythmicity, but peaked during the light phase in the HC, especially in males. Collectively, these findings demonstrate that antidepressant targets are subject to diurnal regulation, highlighting the importance of integrating circadian biology and time-of-day as relevant variables in the development of translationally relevant antidepressant research. HighlightsO_LIKey molecular targets of antidepressants exhibit diurnal regulation in adult mice C_LIO_LIDiurnal patterns were conserved across targets, sexes, and brain regions (HC&PFC) C_LIO_LIcFos, Arc, Nr4a1, Dusp1,5,6 mRNAs display peak expression during the dark phase C_LIO_LITrkBY816 and GSK3{beta}S9 phosphorylation peak during the light (inactive) phase C_LIO_LIAntidepressant mechanisms may be linked with circadian and sleep-wake dynamics C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=102 SRC="FIGDIR/small/716906v1_ufig1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@1e65e60org.highwire.dtl.DTLVardef@13e302corg.highwire.dtl.DTLVardef@1ccc25forg.highwire.dtl.DTLVardef@1ed10d3_HPS_FORMAT_FIGEXP M_FIG C_FIG

PurposeTo determine whether circadian timing defines critical molecular windows in myopia development and to assess the transferability of circadian gene programs across ocular tissues, disease stages, and species. MethodsPublicly available retinal and choroidal RNA-seq datasets from chick models of form-deprivation myopia were analyzed using unsupervised transcriptomic profiling and multistage machine-learning classification. Circadian windows were defined based on Zeitgeber time, and samples were grouped accordingly for downstream analyses. Classification model robustness was evaluated through cross-tissue and cross-stage validation and further assessed using external validation in an independent dataset. Functional translation to humans was examined using ortholog-based Gene Ontology enrichment analysis to identify conserved biological processes and higher-order regulatory pathways. ResultsA circadian critical window at ZT8-ZT12 exhibited the strongest transcriptional divergence during both myopia onset and progression. Gene signatures derived from this window generalized across retina and choroid and remained predictive across disease stages, supporting coordinated molecular regulation between ocular tissues. External validation confirmed the reproducibility of these signatures despite differences in experimental design and gene coverage. Functional mapping revealed that conserved molecular components in chicks are reorganized into more complex neuroendocrine and regulatory networks in humans, indicating cross-species conservation with increased functional complexity. ConclusionsCircadian timing strongly shapes myopia-related gene expression and underlies coordinated retina-choroid signaling. These findings highlight circadian biology as a key factor of refractive development and suggest that time-dependent mechanisms may influence myopia susceptibility, progression, and response to treatment.

BackgroundIn long-term care facilities (LTCFs), close-contact identification often relies on staff recall and monitoring records because residents may be unable to self-report reliably. How these different record-generation processes relate to proximity-based sensor measurements in routine LTCF workflow remain unclear, and how such differences may influence contact-based decision-making in outbreak response is not well understood. MethodsWe conducted a five-day observational study in a Japanese LTCF using ultra-wideband (UWB) indoor positioning. Twenty-seven participants wore UWB tags, including 16 residents and 11 staff members; 10 staff members completed questionnaires. We compared UWB-derived proximity with questionnaire-derived contacts from staff self-report and monitoring-based proxy records, and assessed directional discrepancies under multiple distance-time thresholds. ResultsQuestionnaire-based records and UWB-derived proximity showed different patterns of discrepancy across contact types. Within this facility, resident-related monitoring-based proxy records showed relatively small directional discrepancies, whereas staff self-reports tended to identify additional resident-staff contacts under the baseline threshold ([&le;]1.0 m for [&ge;]15 min). Several alternative thresholds were associated with discrepancies closer to zero than the baseline, although the apparent ranking varied by summary metric. ConclusionsIn this single-facility observational study, different contact-list generation processes were associated with different patterns of discrepancy relative to a proximity-based operational measure. These findings support interpretation in terms of workflow-specific contact-list generation rather than a single universally optimal threshold and may help inform facility-level review of contact identification practices in LTCFs. These findings support aligning contact identification strategies with facility-specific workflows to improve the feasibility and effectiveness of IPC practices in LTCFs.

Study ObjectivesTo evaluate wearable sleep staging across sleep apnea severity, including very severe sleep apnea defined as an apnea-hypopnea index (AHI)[&ge;] 50 events/h, and to assess how training-set composition affects performance in this subgroup. MethodsWe analyzed 552 overnight recordings, 318 from the Sleep Lab Dataset and 234 from the Hospital Dataset. In the Hospital Dataset, 26.5% had very severe sleep apnea. We developed a deep learning model for sleep staging using RR intervals from wrist-worn photoplethysmography and three-axis accelerometry. Baseline performance was assessed by cross-validation under 5-stage and 4-stage staging. We examined night-level associations with AHI severity. We also compared the baseline model with an ablation model trained on the same number of recordings but with more Sleep Lab Dataset and lower-AHI Hospital Dataset recordings, evaluating both models in the very severe subgroup. ResultsIn 5-stage classification, Cohens kappa was 0.586 in the Sleep Lab Dataset and 0.446 in the Hospital Dataset. Under 4-stage staging, the gap narrowed, with kappa values of 0.632 and 0.525, respectively. In the Hospital Dataset, performance declined with increasing AHI severity. Among 62 recordings with very severe sleep apnea, reducing high-AHI representation in training lowered kappa from 0.365 to 0.303. ConclusionsWearable sleep staging performance declined across greater sleep apnea severity in this clinical cohort. Clinical utility may benefit from training data that better represent the target severity spectrum and from selecting staging granularity to match the intended use case. Statement of SignificanceRepeated laboratory polysomnography is impractical for long-term sleep apnea management. Wearable sleep staging could support scalable monitoring, yet its reliability in clinically severe sleep apnea has remained unclear. This study developed and evaluated a wearable sleep staging approach in both sleep-laboratory and hospital cohorts. The hospital cohort included many severe and very severe cases. Performance was lower in the hospital cohort and declined with greater sleep apnea severity. A coarser staging scheme reduced the gap between cohorts, and models trained without representative very severe cases performed worse in this target population. These findings highlight the value of severity-aware model development and motivate future multi-night home validation with reliability cues.

High and low tides occur twice a day (every [~]12.4 hours), with the largest tidal ranges during spring tides around new and full moons (every [~]14.765 days). While these lunar cycles are known to influence many animal phenotypes, particularly the reproduction of coastal animals, the genetic basis of lunar-related rhythms remains unclear. Since phenotypic variation is a valuable resource for elucidating such mechanisms, we examined geographic variation in the lunar-regulated mass spawning of the grass puffer (Takifugu alboplumbeus) along the Japanese coast. We found that western populations spawn during the first half of the spring tides, whereas eastern populations spawn during the second half. Furthermore, although spawning typically occurs a few hours before high tide, this timing is restricted to a specific time window that is earlier in the western populations than in the eastern ones. Behavioral analysis of larvae also revealed a shorter free-running circadian period ({tau}) in the western population than in the eastern ones. As differences in {tau} affect individual variation in the timing of physiological functions and behaviors, we hypothesized that differences in {tau} could account for the different time windows and consequently the observed difference in spawning days. Population genomics analysis identified proline-rich transmembrane protein 1-like (prrt1l) as a candidate gene. Expression of prrt1l was observed in the circadian pacemaker suprachiasmatic nucleus, and triple CRISPR F0 knockout of prrt1l shortened the free-running period in larvae. These findings suggest a potential mechanism underlying the geographic variation in lunar-synchronized spawning behavior. HighlightsO_LIThe geographic variation exists in the lunar-regulated spawning of the grass puffer, with differences in spawning dates and times between western and eastern Japan. C_LIO_LIThe free-running period of western populations is shorter than that of eastern populations, which is consistent with their earlier spawning timing. C_LIO_LIPopulation genomics analysis identified prrt1l as a candidate gene harboring population-specific missense mutations, the knockout of which shortens the free-running period. C_LI

Cardiovascular age is a powerful risk-communication tool that translates complex physiological data into an intuitive number, yet traditional estimates require clinical testing. Consumer wearables now estimate cardiorespiratory fitness age from photoplethysmography-derived heart rate data, enabling continuous, passive health monitoring, but whether such estimates capture substantive lifestyle variation has not been examined. We characterized Cardio Age, a wearable-derived cardiorespiratory fitness age estimate, in 442 Ultrahuman Ring users across a 12-month window ending February 2026, separating independent lifestyle correlates from direct or indirect algorithmic inputs. The mean Cardio Age gap (CA gap; mean Cardio Age minus chronological age) was -1.84{+/-}2.97 years, with 82.6% of participants exhibiting younger estimated cardiovascular ages. Independent lifestyle metrics with no algorithmic link to Cardio Age showed significant associations: sleep efficiency (r = -0.194, p < 0.001), rapid eye movement (REM) sleep (r = -0.203, p < 0.001), sleep duration (r = -0.200, p < 0.001), and daily steps (r = -0.145, p = 0.003). A monotonic body mass index (BMI) dose-response was observed, with underweight participants showing a mean CA gap of -3.73 years versus -0.52 for obese participants. Extreme-group comparisons revealed that users with the youngest cardiovascular ages slept 37 minutes longer, achieved 22 more minutes of REM sleep, and had 1.8% higher sleep efficiency than those with the oldest cardiovascular ages (all p < 0.05). Sustained improvers over 12 months showed a mean CA reduction of 3.24 years, accompanied by decreased resting heart rate (-0.8 bpm, p < 0.001) and increased estimated VO2 max (+1.3 mL/kg/min, p < 0.001), indicating that Cardio Age tracks physiological changes over time.

Background Emerging evidence highlights the gut-brain axis as a key pathway linking diet and anxiety, yet the key determinants remain unclear. Most studies have focused on single components of diet and rarely integrate long- and short-term intake. Furthermore, prior gut-brain work has focused on microbiome composition, while functional features remain underexplored. In this study, we investigated associations between long- and short-term dietary intake, gut microbiome composition and functions, and anxiety in a subclinical cohort of 46 females (18-24 years) from the United Kingdom. Results Long-term diet quality was assessed using the Healthy Eating Index (HEI-2020) derived from a food frequency questionnaire, stratifying participants into lower and higher diet quality clusters. Short-term dietary intake was assessed via 24-hour recalls. Shotgun metagenomics of stool samples was used to assess differences in alpha and beta diversity indices, species abundances, and bacterial pathways putatively metabolizing gut-brain-axis-relevant molecules. Anxiety was measured using the State-Trait Anxiety Inventory (state subscale STAI-s). Regression models identified diet quality (HEI cluster) as the primary dietary feature of anxiety variation. The presence of Ruminococcus gnavus and Flavonifractor plautii and the abundances of Bilophila wadsworthia and Bacteroides thetaiotaomicron were positively associated with anxiety. The presence of Feacalibacterium prausnitzii and greater abundances of butyrate, propionate, and GABA synthesis pathways were inversely associated with anxiety. Non-linear models revealed a U-shaped relationship between inositol synthesis and STAI-s. Finally, we found that habitual diet quality may modulate anxiety-related responses to short-term dietary variation. Conclusions These findings reveal widespread links between long-term diet quality, microbiota composition and function, and anxiety symptoms. These results point towards several promising targets for prebiotic, probiotic, postbiotic, and dietary interventions aimed at reducing anxiety.

Loneliness--the perceived discrepancy between desired and actual social connection--is a common and aversive psychological state associated with a range of adverse health outcomes. Several theoretical models suggest that these associations may operate partly through health behaviors. In this preregistered study, we used data from the All of Us Research Program to evaluate associations of loneliness and functional rurality (FR), a study-specific contextual index of reduced neighborhood accessibility, with Fitbit-derived physical activity and sleep outcomes. Final samples included 16,912 participants for physical activity analyses and 13,937 for sleep analyses. In adjusted models, higher FR was associated with greater loneliness ({beta} = 0.061, 95% CI [0.045, 0.077], p = 9.63 x 10-14). FR and loneliness were independently associated with fewer daily steps and lower moderate-to-vigorous physical activity. Loneliness was also associated with shorter sleep duration, greater sleep duration variability, higher odds of short sleep, and higher odds of low sleep efficiency. FR was not associated with sleep duration or sleep duration variability but showed a small positive association with mean sleep efficiency and lower odds of low sleep efficiency. Interaction analyses provided little evidence that FR modified the associations of loneliness with most outcomes, although the FR x loneliness interaction was significant for sleep duration variability, indicating that loneliness was more strongly associated with irregular sleep duration in higher-FR contexts. Sensitivity analyses using stricter valid-day thresholds, winsorization, quartile-based exposure coding, and a backward 30-day window yielded directionally similar findings. These results suggest that FR and loneliness are independently associated with lower physical activity, whereas loneliness shows a more consistent relationship with adverse sleep patterns.

Wellbeing is commonly defined as the combination of feeling good and functioning well and typically conceptualized as two related but distinct components. Hedonic wellbeing emphasizes pleasure, happiness, and life satisfaction, while eudaimonic wellbeing focuses on meaning, personal growth, flourishing, and the realization of ones potential. The Mental Health Continuum-Short Form was developed as a comprehensive measure of wellbeing and includes three subscales assessing emotional, social, and psychological wellbeing. Although the Mental Health Continuum total score is often interpreted as an indicator of overall wellbeing, the underlying genetic structure of its three subscales and its genetic overlap with other commonly used wellbeing measures remains unclear. Using data from 5,212 individuals from the Netherlands Twin Register (72% female, mean age 36.4), we fitted multivariate twin models to examine the genetic architecture of the Mental Health Continuum and its associations with other wellbeing measures (quality of life, life satisfaction, subjective happiness, and flourishing). Results indicate that, at the genetic level, the Mental Health Continuum is best explained by its three distinct subscales rather than by a latent factor. When considering the Mental Health Continuum together with the other wellbeing measures, we found moderate to high genetic correlations (r = 0.52 - 0.83), indicating substantial overlap in the genetics underlying the wellbeing constructs. However, we did not find evidence for a single common genetic factor underlying all constructs. These findings highlight the multidimensional structure of wellbeing, but the moderate to high genetic correlations across measures suggest that it is important to align the level of measurement (phenotypic vs genetic) with the research question.

The causes of severe neuropsychiatric deteriorations among patients with previously stable autism spectrum disorder (ASD) are poorly understood and present substantial challenges for care. We aimed to characterize the prevalence of autoimmune and inflammatory conditions and markers, as well as musculoskeletal findings, among youth with ASD experiencing a suspected post-infectious neuropsychiatric deterioration. The Stanford Immune Behavioral Health (IBH) Clinic is a specialty program for youth with neuropsychiatric deteriorations that are suspected to be post-infectious (non-psychosocial). We report findings for 43 consecutive patients with ASD (70% male [30 of 43]) evaluated in the IBH Clinic. The average (SD) age at clinical presentation was 12.0 (4.0) years. Juvenile arthritis was diagnosed in 15 patients (35%), predominantly enthesitis-related arthritis (ERA) and psoriatic arthritis (PsA). Seven patients had ultrasonographic evidence of joint effusions and/or synovitis without meeting juvenile idiopathic arthritis (JIA) criteria. Autoimmune conditions other than arthritis were observed in 9 patients (21%). The mean (SD) age at arthritis and other autoimmune condition diagnoses were 16.2 (5.5) and 12.7 (4.9) years, respectively. We observe markers of immune activation during neuropsychiatric deteriorations in over half of patients (60% [26 of 43]), including markers of autoimmunity (33% [12 of 36]), complement activation (41% [13 of 32]), immune dysregulation/inflammation (11% [4 of 37]), and vasculopathy (30% [13 of 43]). One-third (37% [16 of 43]) demonstrated two or more markers. These data underscore the importance of targeted immune evaluation--including musculoskeletal imaging and inflammatory marker screening--in ASD patients who have had a suspected post-infectious behavioral regression. Lay SummaryIn this cohort study of 43 patients with autism spectrum disorder (ASD) and suspected post-infectious deteriorations, more than half had laboratory markers of immune activation (using a limited panel), one-third had joint inflammation (confirmed by ultrasound), and additional autoimmune conditions were observed in 21%. From this, we conclude that patients with ASD who experience a suspected post-infectious neuropsychiatric deterioration may have underlying inflammation which may contribute to neuropsychiatric and behavioral regressions, highlighting the importance of immunologic and rheumatologic evaluation in clinical assessment.

ObjectiveLong term monitoring of obstructive sleep apnea (OSA) severity may be relevant for several clinical applications. We developed a method for estimating the apnea-hypopnea index (AHI) using wrist-worn, reflective photoplethysmography (PPG). ApproachA neural network was developed to detect respiratory events using PPG and PPG-derived sleep stages as input. The development database encompassed retrospective data from three polysomnographic datasets (N=3111), including a dataset with concurrent reflective PPG recordings from a wrist-worn device (N=969). The model was pre-trained with (transmissive) finger-PPG signals from all overnight recordings and then fine-tuned to wrist-PPG characteristics using transfer learning. Validation was performed on the test portion of the development set and on a fourth, external hold-out dataset containing both wrist-PPG and PSG data (N=171). Performance was evaluated in terms of AHI estimation accuracy and OSA severity classification. Main ResultsThe fine-tuned wrist-PPG model demonstrated strong agreement with the PSG-derived gold-standard AHI, achieving intra-class correlation coefficients of 0.87 in the test portion of the development set and 0.91 in the external hold-out validation set. Diagnostic performance was high, with accuracies above 80% for all severity thresholds. SignificanceThe study highlights the potential of reflective PPG-based AHI estimation, achieving high estimation performance in comparison with PSG. These measurements can be performed with relatively comfortable sensors integrated in convenient wrist-worn wearables, enabling long-term assessment of sleep disordered breathing, both in a diagnostic phase, and during therapy follow-up.

Background: Digital health platforms can improve clinical efficiency and patient outcomes, but adoption in routine care remains limited due to workflow and integration challenges. Rheumatoid arthritis (RA) management relies on consistent capture of patient-reported and clinical data, which is often time-intensive and inconsistently documented. Objective: To assess the impact of the cliexa-RA digital platform on patient experience, physician workflow, and cost-related outcomes using the Quadruple Aim framework. Methods: A six-month pilot study was conducted at the Colorado Arthritis Center involving 300 RA patients. Patients completed a 16-question intake (RAPID3-based), followed by clinician-entered joint assessments. The platform generated five disease activity scores (DAS28-ESR, DAS28-CRP, SDAI, CDAI, RAPID3) and produced EMR-compatible outputs. Time metrics, patient satisfaction, and workflow efficiency were evaluated. Results: Mean patient intake time was 2.4 minutes, a 52% reduction compared to paper-based processes. Clinician time for calculation and documentation decreased by 77%, with near real-time EMR integration. Overall patient satisfaction was high (3.55/4), with 85% recommending the platform. Physicians reported improved documentation efficiency and workflow integration. Administrative cost reductions were observed through decreased reporting burden and improved compliance with quality reporting requirements. Conclusions: The cliexa-RA platform significantly improved efficiency and user experience in RA management. These findings support the role of integrated digital tools in reducing administrative burden and enabling scalable, data-driven care, with potential downstream benefits for cost and population health.

Heat Shock Protein 90 (HSP90) functions as an evolutionary capacitor, allowing populations to store cryptic genetic variation that can be released under stress. While former studies have described the release of morphological variation, its behavioural consequences remain unexplored. In the red flour beetle, Tribolium castaneum, HSP90 inhibition released a phenotype with much smaller, less defined eyes that confers fitness benefits in continuous light and was subsequently assimilated. We hypothesized that altered eye morphology affects light perception and thereby changes light-dependent behaviours. To test whether phenotypes released via evolutionary capacitance can beneficially alter behaviour, we examined locomotor activity rhythm entrainment to light-dark cycles as well as individual and group light choice behaviour. Males of the reduced-eye phenotype exhibited a diminished startle response to sudden light exposure in locomotor activity assays. We also found reduced negative phototaxis in groups of beetles with reduced eyes. This modified behaviour, indicating reduced light sensitivity, may stem from impaired light perception caused by altered eye morphology. Lower light sensitivity could be beneficial under stressful environmental conditions by promoting the exploration of alternative niches. Therefore, this study provides the first evidence for potentially beneficial behavioural changes in a HSP90-released phenotype, reinforcing HSP90s role as an evolutionary capacitor.

Study objectives Consumer sleep technologies (CSTs) enable low-burden longitudinal sleep monitoring, and their output measures are often interpreted as equivalent to polysomnography (PSG) measures. We applied a measurement reliability-aware approach to determine whether CST-derived 'sleep' measures (1) are interchangeable or device-specific, (2) can reliably assess trait-like sleep characteristics of an individual, (3) can be reduced to latent principal components of sleep, and (4) can be used for classification and biomarker discovery. Methods Data from 74 older adults (20 people living with dementia [PLWD]) were collected at-home (upto 14 nights; Total=752nights) using four tools simultaneously: research-grade actigraphy (Axivity), a wearable (Withings Watch), a nearable (Withings Sleep Analyzer) and Sleep Diary, followed by one in-lab PSG assessment. We used repeated-measures correlation analyses, intraclass correlation coefficients (ICC), principal component analysis (PCA) and binary classification models to address our objectives. Results Single-night between-device correlations and correlations with PSG were moderate (0.3[&le;]r<0.7) for some duration- and timing-related measures, but other associations were weak (r<0.3). Seventy-one percent of sleep measures reached acceptable reliability (ICC[&ge;]0.7) within seven nights of aggregation, but the required aggregation window varied across measures, tools and between PLWD and Controls. Reliability-filtered PCA yielded stable and interpretable principal components, but Duration was the only component showing moderate between-device association. Principal components were successfully used to classify PLWD vs Controls but feature importance varied across devices. Conclusions Aggregation of CST derived measures across 7-14 nights, yielded reliable measures, most of which were device-specific, with duration being the only essential aspect transferable between devices.

RationaleBronchopulmonary dysplasia (BPD), the lung disease associated with premature birth, is a significant health problem, often with long-term respiratory consequences. Recent research has highlighted the potential role of the lung and gut microbiome in the development and progression of BPD, yet it is unclear what aspects of the microbiome may contribute to BPD susceptibility. ObjectivesTo comprehensively characterize the lung and gut microbiomes of preterm infants and identify shared microbial taxa that are associated with BPD development. MethodsTracheal aspirate and stool samples were collected from 39 premature infants over the first month of life. To assess the taxonomic microbial composition of the lung and gut, samples were analyzed using shotgun metagenomic sequencing. BPD classification was determined using the National Institute of Child Health and Human Development severity-based definition at 36 weeks postmenstrual age. Measurements and Main ResultsMicrobial communities of the lung and gut were significantly different between infants who went on to develop BPD and those who did not, with an enrichment of skin-associated microbial genera such as Staphylococcus, Corynebacterium, and Cutibacterium in infants who developed BPD. Specifically, Staphylococcus epidermidis was enriched in premature infants who developed BPD and was the most prominent species shared between lung and gut communities. Temporal changes in gut microbial communities co-occurred with feeding practices and antibiotic exposure, suggesting an influence of external factors on microbiome composition. ConclusionsOur findings provide evidence that certain microbial colonization patterns among premature infants are closely associated with the pathogenesis and progression of BPD.