Journal of Biological Rhythms

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.

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.

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.

Background: Shiftwork disrupts natural sleep-wake cycles, alters light exposure patterns, and contributes to circadian misalignment. Detrimental health consequences associated with shift work include elevated risk for metabolic disorders, cardiovascular disease, cancer and all-cause mortality. Healthcare workers have one of the highest rates of shift work exposure, yet there are relatively few non-pharmacological interventions (with good evidence) developed to improve sleep outcomes in this population. Objective: A pre-post pilot interventional study assessed the acceptability and perceived effectiveness of commercial noise-masking earbuds on improving subjective sleep characteristics among National Health Service (NHS) healthcare staff working fast rotating shifts. Methods: Noise-masking sleep earbuds (Kokoon NightBuds) were worn for a pilot six-week intervention by twenty-seven NHS nurses (aged 26-43 years, 88.9% female) working fast rotating shifts from the EClocker Study. Sensors inside the earbuds were paired with a smartphone app to monitor sleep. An audio library in the smartphone app delivered personalised relaxation exercises and sleep techniques drawn from cognitive behavioural therapy for insomnia (CBT-I). A pre-post two-week monitoring period with daily smartphone-based Experience Sampling Methods (ESM) captured perceived daily sleep patterns. Acceptability and perceived effectiveness of the earbuds in promoting better sleep outcomes was assessed. Results: Use of the noise-masking sleep earbuds over a six-week period was associated with positive sleep improvement trends and elicited promising acceptability. Almost two thirds of NHS fast rotating shift nurses (63%) subjectively reported reductions in general sleep disturbance symptoms (PSQI Global), one in four experienced perceived sleep quality improvements (SQ; 25.9%), one in five reported sleeping longer (TST; 22.2%), and a third perceived falling asleep faster (SOL; 33.3%), had better sleep efficiency (SE; 33.3%) and improved daytime dysfunction (33.3%) (PSQI subcomponent scores). Sleep diaries (CSD) collected daily using smartphone-based ESM also demonstrated small improvements post-sleep earbud use; nurses reported sleeping an average 18 minutes longer (TST) and fell asleep more easily, on average 11 minutes faster (SOL). Sleep earbuds were generally well tolerated; 56% of nurses reported the earbuds as (somewhat to very) helpful, 52% reported (somewhat to strongly) falling asleep more easily (SOL), 44% felt (somewhat to strongly) their sleep quality was improved (SQ) and 30% agreed (somewhat to strongly) they slept longer (TST) and had less disturbed sleep. Conclusions: To our knowledge, this is the first study in Europe to pilot noise-masking earbuds as a potential non-pharmacological aid to improve sleep-wake behaviours or mitigate fatigue for healthcare staff. Preliminary results showed promising acceptability and (small) perceived sleep improvement trends following a targeted six-week earbud intervention in NHS fast rotating shift nurses.

Intertidal mudflats are low hydrodynamic energy environments hosting microphytobenthic communities that experience strong spatiotemporal variability in light regimes, including changes in spectral quality and light intensity that can lead to cellular photooxidative stress. To cope with these fluctuations, autotrophs exhibit diverse and highly plastic adaptations that are often species-dependent and shaped by their ecological niches. This study investigates photophysiological responses and metabolic remodeling in a diatom assemblage originating from a natural winter microphytobenthic biofilm under contrasting red and blue light intensities. To this end, photosynthetic parameters were monitored alongside changes in lipophilic metabolites, including untargeted lipids and lipophilic pigments. While few metabolites showed temporal remodeling, rapid and contrasting changes were observed within 30 minutes in response to both spectral quality and light intensity. Red light treatments induced broader remodeling of lipophilic metabolites than blue light, whereas blue light appeared to have a greater impact on photosynthetic parameters. Moreover, red light induced xanthophyll-cycle responses comparable to those observed under blue light at equivalent incident intensity. We discuss these metabolic responses in relation to diatom photoadaptive strategies, placing these findings within the intertidal environmental framework. This work further underlines the importance of understanding rapid metabolic plasticity in coping with light fluctuations, providing new insights into the photoregulatory strategies of natural microphytobenthic communities.

Objectives To evaluate whether access to a certified large language model (LLM)-based clinical decision support system improves physician diagnostic performance in rheumatology compared with conventional diagnostic resources alone. Methods In this multicentre, open-label, randomised controlled trial, 82 physicians from seven hospitals in two countries were randomised 1:1 to conventional diagnostic resources plus Prof. Valmed or conventional resources alone. Participants assessed three rheumatology vignettes before and after assistance. The primary outcome was top-1 diagnostic accuracy. Secondary outcomes included top-3 accuracy, diagnostic reasoning, confidence, case-processing time and perceived support quality. Results Top-1 accuracy increased from 22.2% to 33.3% in the intervention group and from 23.3% to 35.0% in the control group, with no between-group difference in improvement (adjusted OR 0.99, 95% CI 0.45 to 2.19; p=0.979). Differences in top-3 accuracy, diagnostic reasoning and confidence were also not significant. Assisted case-processing time was substantially shorter with LLM support (94 vs 206 s; adjusted mean difference -112 s, 95% CI -141 to -83; p<0.001). Information timeliness and perceived diagnostic support quality were rated significantly higher in the intervention group. Exploratory analyses showed persistent overconfidence and substantial AI over-reliance. Conclusions Certified LLM-based diagnostic support did not improve diagnostic accuracy compared with conventional resources, but substantially reduced case-processing time and improved perceived support quality. These findings suggest potential workflow benefits while highlighting overconfidence and over-reliance as important safety considerations.

We identified Sleep Bursts (SBs), as a novel phenomenon of brief (1-2 sec), often periodic bursts in cranial forces occurring during human sleep. Our goal was to characterize SBs in normal subjects, then compare SB in a cohort of subjects with neurodegenerative disease (NDD). We recorded 32 cognitively healthy subjects (23 -87 years) and 13 subjects with NDD (51 - 84 years). SBs occurred in all 45 subjects. SBs occurred at 0.57 SB/min (once per 105 seconds) in controls and 0.40 SB/min (once per 150 seconds) in NDD (p = 0.0043). SB occurred with equal rates across all sleep stages in both groups. When occurring periodically, SBs had modal intervals (3.75 bursts/min (0.0625 Hz) - 2.67 bursts/min (0.044 Hz)). EEG power increased in the delta range 1-2 seconds before and following the SB. EEG delta power during a SB was significantly lower in all NDD subjects across sleep stages compared to controls. The relatively low frequency of SB events and synchronization with EEG power has no parallel in human sleep; we hypothesize that SBs may represent a brain-generated pulsatile component of brain glymphatic drainage.

This study investigated bidirectional associations between maternal sleep and depressive symptoms from preconception to postpartum, and whether infant sleep mediated or moderated these associations. We used data from the Generation R Next Study (N=2,294). Maternal sleep (specifically general sleep disturbance, latency, quality, duration, and midpoint) and depressive symptoms were prospectively assessed at five timepoints from preconception to 12-month postpartum. Sleep was self-assessed with the General Sleep Disturbance Scale and Munich Chronotype Questionnaire; depressive symptoms with the Adult Self Report depression/anxiety subscale and Edinburgh Postnatal Depression Scale. Infant sleep (specifically night awakenings, nocturnal sleep duration, and latency) was parent-reported at 1-month postpartum using the Brief Infant Sleep Questionnaire. Bidirectional associations were examined using Autoregressive Latent Trajectory Models with Structured Residuals. The role of infant sleep was examined using mediation and moderation analyses. We found that maternal sleep and depressive symptoms were both stable over time. For sleep quality and disturbance, bidirectional associations suggested slightly stronger effects from depression to sleep (sleep quality:{beta}depression[-&gt;]sleep quality=0.11, 95%CI:0.07 - 0.14; general sleep disturbance:{beta}depression[-&gt;]sleep disturbance=0.14, 95%CI:0.10 - 0.18) than from sleep to depression ({beta}sleep quality/disturbance[-&gt;]depression=0.07 for both, 95%CIs:0.03 - 0.11). For latency, effects were comparable in both directions ({beta}depression[-&gt;]sleep latency=0.06, 95%CI:0.03 - 0.09; {beta}sleep latency[-&gt;]depression=0.05, 95%CI:0.01 - 0.09). The association between depressive symptoms and sleep latency was both mediated (9.7%) and moderated (p<0.05) by infant sleep latency. In conclusion, general maternal sleep disturbance, sleep quality, and sleep latency showed bidirectional associations with depressive symptoms from preconception/early pregnancy onwards. Infant sleep latency may represent a potential modifiable factor within this cycle.

Polycystic Ovary Syndrome is a common endocrine disorder characterized by ovulatory dysfunction, hyperandrogenism, and/or polycystic ovarian morphology, with significant reproductive and metabolic consequences. Due to heterogeneous symptom profiles, Polycystic Ovary Syndrome is frequently underdiagnosed or diagnosed late. In this study, we develop machine learning models for early Polycystic Ovary Syndrome prediction using a structured clinical dataset with 42 features and 542 patient records. After data cleaning and normalization, correlation-based feature selection was applied to retain the most predictive variables. Multiple models were trained and evaluated, including Logistic Regression, Decision Tree, KNN, and Random Forest. Results demonstrate that Random Forest achieves the best overall performance (approximately 88% accuracy), suggesting that ensemble models can effectively capture non-linear feature interactions in clinical data. We also contextualize findings with international clinical guidance and recent work on explainable and clinically applicable Polycystic Ovary Syndrome prediction systems.

Background: Polymorphisms in the N-acetyltransferase 2 (NAT2) gene explain much of the interindividual variation in isoniazid (INH) metabolism and determine risk of toxicities. However, there is limited evidence to guide INH dose adjustment according to the NAT2 acetylator profile in weekly rifapentine-INH tuberculosis preventive therapy (TPT). Methods: In a prospective, multicenter, within-subject PK trial (NCT05413551), adults initiating 3HP in Brazil were assigned genotype-guided INH doses (slow: 5 mg/kg <=300 mg; intermediate: 15 mg/kg <=900 mg; rapid: 25 mg/kg <=1,500 mg) alongside a standard 900 mg flat dose on an alternate occasion. AUC0-24 and C24 were estimated from serial blood samples; a two-compartment Michaelis-Menten population PK model characterized NAT2 effects on clearance. Results: Among 228 participants, 47.4% (108/228) were intermediate, 43.4% (99/228) slow, and 9.2% (21/228) rapid acetylators. Genotype-guided dosing reduced AUC0-24 variability approximately two-fold versus standard dosing (CV 58.8% vs 76.8%) and increased exposure uniformity (median AUC0-24 27.2 [IQR 18.8-41.3] vs 43.2 [27.3-71.0] mg h/L). Among slow acetylators, C24 >0.15 ug/mL decreased from 27/42 (64%) with standard dosing to 1/42 (2%) with genotype-guided dosing (P<0.0001). In 104 participants with intensive PK sampling, rapid acetylators receiving guided doses had AUC0-24 similar to standard-dose intermediate acetylators (42.8 vs 39.5 mg h/L; P=.63). Monte Carlo simulations supported doses of 600, 900, and 1,200 mg for slow, intermediate, and rapid acetylators, respectively. Conclusions: NAT2-guided isoniazid dosing reduced variation in drug levels, averting very low and high AUC and C24. These findings inform genotype-stratified dosing of INH for TPT, which might reduce toxicities and improve outcomes.

Background. Urine-based testing offers a promising non-sputum approach for diagnosing paediatric tuberculosis. However, the currently available lipoarabinomannan (LAM) assay shows limited sensitivity in children and is primarily indicated for those living with HIV. Co-detection of LAM with Mycobacterium tuberculosis (Mtb) proteins in urine could provide complementary pathogen-derived biomarkers that improve diagnostic performance. Methods. We developed an ultrasensitive multiplex electrochemiluminescence (ECL) immunoassay to measure Ag85B, CFP-10, ESAT-6, MPT32, and MPT64 in urine. We determined the analytical limits of detection and evaluated the diagnostic performance of individual proteins and LAM using urine samples from children with Confirmed, Unconfirmed, and Unlikely pulmonary tuberculosis enrolled across five high-burden countries (The Gambia, India, Peru, South Africa, and Uganda). Performance was assessed overall, by HIV and nutritional status, and across biomarker combinations. Findings. Urine samples from 630 children were analysed (median age was 4 years [IQR 2-8]; 44% female, 15% living with HIV, 19% underweight, 24% with Confirmed tuberculosis). The ECL assay achieved femtomolar limits of detection (1.5 to 4.0 fM). The sensitivity and specificity of individual Mtb proteins were 12-33% and 98-100%, respectively. Ag85B had the highest sensitivity (33%, 95% CI 26-41) for Confirmed tuberculosis and was similar to LAM. A four-antigen signature (Ag85B, MPT64, MPT32, LAM) was 50% sensitive (95% CI 42-58) and 94% specific (95% CI 90-96), and was significantly more sensitive than LAM alone, in particular among those without HIV. An additional sixteen (10%) of children with Unconfirmed TB had at least one Mtb protein or LAM detected. Interpretation. Multiple Mtb proteins are detectable in paediatric urine with high specificity, and multi-antigen signatures can augment sensitivity versus LAM alone. These findings demonstrate the potential of multi-antigen urine detection for childhood TB and define analytical targets for the development of future point-of-care diagnostics. Funding. National Institutes of Health.

Light reaching the retina is a primary regulator of human circadian physiology, acting largely through melanopsin-expressing retinal ganglion cells with peak short-wavelength sensitivity. Delivering known, repeatable retinal doses outside the laboratory is difficult because conventional light sources leave viewing geometry, gaze, and ambient conditions uncontrolled. Consumer extended-reality (XR) glasses fix a bright binocular display in constant geometry relative to the eye, but their suitability as calibrated photic stimulators has not been established. Here we validate a commercial micro-OLED XR display (VITURE Luma Ultra) for controlled retinal photostimulation. A purpose-built host application renders exact 8-bit RGB stimuli while independently controlling hardware brightness and logging all intensity-determining state; spectral radiance was measured at the retinal position of a 3D-printed phantom head with an open-source miniature spectroradiometer, anchored to absolute units by a luminance transfer calibration. The blue primary peaks at 461 nm (FWHM 43 nm), is spectrally invariant across a >10-fold intensity range, and at maximum output delivers an estimated 299 lx melanopic equivalent daylight illuminance, above consensus daytime recommendations, while remaining roughly two orders of magnitude below photobiological safety limits. The red primary is visually effective with minimal melanopic drive (melanopic DER 0.10), enabling spectrally shifted evening stimulation. Unlike the immersive virtual-reality headsets previously used for calibrated light delivery, the see-through form factor preserves the wearer's view of the surroundings--relevant for clinical monitoring in supervised settings such as the intensive care unit. These results show that consumer XR glasses can serve as a dose-calibrated platform for wearable photostimulation using an open-source measurement chain, and provide groundwork for application-layer dose-response studies.

Conventional sleep electroencephalography (EEG) measures often rely on predefined bands, thresholds, and averages that incompletely capture transient oscillatory dynamics across an entire night. Here, we introduce the Dynamic Oscillation (DYNAM-O) Toolbox, an open-source, cross-platform (MATLAB, Python, and Rust) software package for data-driven characterization of individualized neural dynamics in sleep EEG. DYNAM-O identifies transient oscillations as time-frequency peaks on multitaper spectrograms using a novel multi-resolution procedure, computes intrinsic and sleep-state-dependent extrinsic features for each event, and represents the overnight distributions of tens of thousands of TF-peaks as feature histograms spanning oscillation frequency, slow oscillation power, and slow oscillation phase. This distributional representation preserves continuous brain-state variation that could be obscured by averaging within conventional sleep stages. The toolbox further provides Gaussian and spline basis-based dimensionality reduction, visualization, and whole-histogram statistical testing tools to support both exploratory and hypothesis-driven analyses. To demonstrate its use for group-level inference, we analyzed overnight C3-channel EEG from 133 adults (71 females, 72 males; ages 20-35 years) in the Cleveland Family Study. Whole-histogram and parameterized-mode analyses reproduced the established higher center frequency of fast-spindle activity in females and additionally revealed greater low-alpha transient oscillatory activity in females, a pattern outside the conventional sleep spindle range. By completing the analysis cycle from TF-peak extraction to statistical inference, DYNAM-O provides an accessible and interpretable framework for studying individualized sleep physiology and identifying subtle, reproducible electrophysiological patterns.

Background: Children spend more than 90% of their time indoors, and early childhood education settings (ECEs) are an understudied, high-occupant-density indoor microenvironment where exposure to volatile organic compounds, particulate matter, and other toxicants has been documented. Limited knowledge exists on ECE-specific exposures affecting young children and how they compare to exposures in the home. Methods: This prospective, repeated-measures pilot study targeted enrollment of 44 preschool-aged children and 8 ECE staff across two geographically and sociodemographically distinct ECEs in metropolitan Atlanta, Georgia. Paired silicone wristbands, one home-designated and one ECE-designated, were exchanged between settings across three consecutive days and nights beginning at enrollment to characterize microenvironment-specific exposure. A single spot urine sample was also collected from each child. Continuous indoor air quality monitoring was conducted in two classrooms per site. Caregivers and ECE staff completed structured questionnaires assessing home and ECE environmental characteristics, child respiratory risk, and protocol feasibility and acceptability. Feasibility was evaluated using eight pre-specified indicators spanning recruitment and enrollment, wristband wear duration and loss by microenvironment, urine sample collection completeness, and survey completion by instrument and respondent group. Conclusion: This pilot will establish feasibility and acceptability parameters for a paired, multi-matrix silicone wristband protocol across home and ECE microenvironments. Findings will inform the design, sample size, and power calculations for a subsequent study testing indoor air interventions and pediatric respiratory outcomes in ECEs. Feasibility outcomes are reported in a companion manuscript.

Human deep-space missions face bone-kidney risks that cannot be extrapolated from six-month ISS data. We built a 12-state Ca-bone-urine-stone mechanistic ODE model and jointly calibrated its 11 physiological parameters on eight ISS targets by Bayesian identification (M0 base = 19-D; M1 extension adds a GCR-bone coupling term for parsimony testing only), then propagated the M0 posterior to four environments (ISS, Lunar subsurface, Lunar surface, Mars). Lumbar-lower BMD loss increases with mission duration and partial-gravity unloading (ISS 180 d -4.83% -> Mars 730 d -12.15%; 2^3 factorial: duration 82.9%, gravity 12.5%, GCR main effect ~ 0), whereas stone rate follows the opposite gradient (ISS 16.1 vs Mars 13.1 per 1000 person-years), reflecting weakened partial-gravity bone resorption alongside residual urinary chemistry changes. The dominant pathway thus shifts from bone-centric on the ISS to kidney-centric on Mars, where residual urinary-chemistry changes-not bone resorption-drive stone risk. The direct GCR-bone coupling term is unidentifiable at current ISS doses (DeltaWAIC = +0.0076 +/- 0.126 SE), so M0 is retained as the main inference model. Bisphosphonates provide >=84% BMD protection but leave a urinary-chemistry residual, so bisphosphonate monotherapy would underestimate Mars stone risk; potassium-magnesium-citrate combinations (RRR_RSS 51%) should therefore be added to deep-space countermeasures. A Lunar-surface 365-day mission is the earliest environment on the NASA roadmap to cross a composite RED threshold. That profile differs from the regolith-shielded 180-day case in both cumulative GCR (~69x) and duration (2x), so a shielding-specific effect cannot be isolated here; forcing the GCR coupling terms to zero leaves all four composite tiers unchanged (0/4, Supp S24), and the shielded 180-day profile is YELLOW rather than GREEN. Independent hold-out validation (Culliton 2025 60-day HDT-bedrest RCT, n=8 control arm of n=24 total) supports the M0 posterior predictive distribution on the lumbar-BMD sub-scope.

Agentic workflows can coordinate modelling, but balancing predictive performance, measurement burden and reproducibility is unclear. We developed DXA Agent, an agentic workflow for dual-energy X-ray absorptiometry (DXA) outcomes integrating planning, feature-model refinement, tools, provenance and hypothesis-generating interpretation. Models were independently developed and tested in UK Biobank (5,318 participants) and the National Health and Nutrition Examination Survey (NHANES; 3,777 participants), using cost-efficient and no-limit strategies. Across 20 UK Biobank and three NHANES bone mineral density sites, cost-efficient models achieved lower RMSE and higher R2 than the best conventional comparator, with median relative RMSE reductions of 10.9% and 9.9%, respectively. Classification was task dependent: UK Biobank osteoporosis averaged AUROC 0.839 and PR-AUC 0.182, whereas NHANES performance was comparable with conventional models. Higher-burden features did not consistently improve prediction. These retrospective, cohort-internal findings position DXA Agent as an inspectable, measurement-burden-aware research workflow requiring independent prospective validation.

Introduction: Parkinson's disease (PD) and aging both disrupt hypothalamic-pituitary-adrenal (HPA) axis function and peripheral immune homeostasis. Whether aging or -synuclein (-syn) pathology alters glucocorticoid (GC) sensitivity of peripheral immune cells has not been investigated. Methods: Using an ex vivo GC sensitivity assay, we assessed the responsiveness of isolated and lipopolysaccharide (LPS)-stimulated splenocytes to the anti-inflammatory effects of increasing doses of corticosterone (CORT) in a wild-type (WT) aging cohort and in a PD -syn transgenic mouse model and respective age-matched controls. Results: Compared with splenocytes from 6-month-old WT mice, splenocytes from 20-month-old WT mice were less sensitive to 0.1 and 0.5 M CORT. Isolated splenocytes from PD vs. control mice were less sensitive to 0.05, 0.1, and 0.5 M CORT specifically at 16 months of age, but not at 6 or 20 months of age. As peripheral immune phenotyping revealed neither differences in HPA axis-related parameters nor in splenic GC receptor expression between PD and age-matched control mice at 6, 16, and 20 months, splenic GC resistance in PD mice at 16 months of age seems to be mediated by downstream GR signaling dysfunction. Conclusion: Together, our results support the hypothesis that -syn pathology accelerates an aging-associated decline in the peripheral sensitivity to anti-inflammatory GCs and may thereby sustain systemic and neuroinflammatory processes in PD.

BACKGROUND Generative AI (genAI) chart summarization tools embedded in electronic health records (EHRs) are being rapidly deployed across U.S. health systems. Although these tools represent a promising solution to alleviate cognitive burdens, their effects have not been examined in randomized-clinical trials (RCTs). METHODS In this pragmatic RCT at a single academic health system, 284 outpatient clinicians across forty-two specialties were assigned 1:1 to Epic's outpatient chart summarization tool or a usual-care control arm over 90 days, from February 23 to May 23, 2026. The primary outcome was physician task load (PTL) adapted for pre-charting. Prespecified exploratory outcomes included additional validated psychometrics as well as usability, safety, and time-based measures. Descriptive statistics included interaction and usage of the tool. RESULTS Of 74,474 AI chart summaries generated, 14.2% were interacted with by a clinician; the proportion of generated summaries interacted with declined from 21.5% in month 1 to 10.5% in month 3, and the proportion of clinicians using the tool at least once per month declined from 88.7% to 66.2%. The adjusted between-arm difference in PTL at follow-up favored the intervention arm (scale 0-400; -27.4; 95% CI, -49.4 to -5.3; P=0.02). Among the Professional Fulfillment Index (PFI; scale 0-4, lower=better) psychometrics, overall burnout (-0.20; 95% CI, -0.38 to -0.01) and work exhaustion (-0.24; 95% CI, -0.47 to -0.02) were lower in the intervention arm, with little difference in overall professional fulfillment (+0.04; 95% CI, -0.16 to 0.25). Charting time per encounter showed no significant between-arm difference during steady state (-1.2 seconds; 95% CI, -19.0 to 16.6). The net promoter score was -22, indicating that on average, clinicians did not recommend the tool. Among free-text respondents, 57.1% reported at least one concern, most commonly tool limitations or inaccurate information. No adverse patient safety events or near-misses were reported. CONCLUSION An EHR-integrated AI chart summarization tool modestly reduced physician task load and was associated with lower burnout, without time savings and against declining engagement. Sustained usage and oversight of reported inaccuracies remain open challenges.

The increasing incidence of H5N1 influenza virus transmission from animal species to humans has heightened concerns about an imminent H5N1 pandemic. Prior studies using recombinant hemagglutinin and neuraminidase proteins have reported age-dependent cross-reactivity to H5N1, attributed to immune imprinting from an individual's first influenza virus exposure. However, whether this pattern holds when using whole inactivated virus (WIV), capturing antibodies against diverse viral proteins, and is stable over time remains unknown. We therefore aimed to determine whether H5N1 cross-reactivity of pre-existing antibodies to whole virus follows an age-dependent or imprinting-specific pattern, and whether this pattern is stable over a five-year period. To this end, we measured serum antibody levels in adolescents, adults and seniors by ELISA using whole inactivated H5N1 virus as antigen rather than purified proteins. Detectable, albeit generally low, levels of H5N1-reactive antibodies were present in most individuals, irrespective of age. Comparison of antibody levels against H5N1 with those to five historical influenza virus strains revealed a consistent positive correlation between H5N1-reactive antibodies and responses to the H1N1pdm09 strain A/California/7/2009 (CA), across all age groups. Using unbiased clustering of antibody titers against H5N1, CA, and the H3N2 strain A/Perth/16/2009 (PE), we identified seven distinct age-transcending antibody profiles. These profiles covered individuals with varying titers to all three included viruses but also identified individuals with high anti-CA levels, yet low anti-H5N1 levels and vice versa. Moreover, despite stable antibody levels over a five-year interval in the study population, individual antibody levels and profiles fluctuated considerably over this period. Taken together, our results confirm the presence of H5N1-reactive antibodies in human sera and their association with previously circulating strains. However, they also caution against inferring antibody levels against a new strain based solely on responses to antigenically related strains and highlight the limitations of extrapolating immune status from single timepoint measurements.

In vertebrates, top-down visual attention is a cognitive process where internal goals modulate the tuning of peripheral sensory systems. This leads to increased perceived contrast to both goal-relevant objects and areas of the visual field that are attended. Such a system would also be beneficial to bees, enabling them to detect and recognise the most profitable flowers in their environment. We tested whether bumblebees possess a top-down attentional system resembling that seen in vertebrates. We trained two groups of bees to collect rewards under high contrast targets. To potentially induce a difference in attention while searching for the targets, one group received a higher concentration of sucrose rewards compared to the other. During tests, the targets were presented with a series of lower contrasts to measure the contrast sensitivity curves of the bees induced by the different learnt reward levels. We predicted a stronger effect of any attention-like process on contrast sensitivity in the high reward group. We also repeated this experiment with the neonicotinoid pesticide imidacloprid dissolved in the sucrose rewards to test whether this affects bee attention. Across all test contrasts, higher rewards significantly increased bee accuracy when locating targets, lowered contrast thresholds and reduced the latency to make first choices. Imidacloprid reduced bee accuracy but did not influence first choice latency. These results suggest that learnt floral rewards can influence bee behavioural contrast sensitivity in a manner resembling vertebrate top-down attention and that imidacloprid may modulate this through effects on their nervous system.