Brain, Behavior, & Immunity - Health

Compassion fatigue is a well-documented hazard among healthcare and veterinary professionals, yet the psychological toll on informal caregivers of feral cat colonies, likely numbering several tens of thousands in Portugal, remains largely unexplored. This cross-sectional study examines internal and external factors associated with the secondary traumatic stress component of compassion fatigue among 172 informal caregivers in Portugal. Secondary traumatic stress refers to work-related secondary exposure to individuals who have experienced extremely stressful or traumatic events. Structured telephone interviews assessed sociodemographics, colony management, compassion satisfaction, resilience, spiritual well-being, and perceived social support. Univariate and multivariable linear regression identified predictors of compassion fatigue. Results indicate that 47% of participants experienced moderate compassion fatigue, and 10% reported high levels. Multivariable analysis revealed that caring for large colonies (more than 25 cats) and being unemployed were significantly associated with higher fatigue. Conversely, older age, higher perceived family support, and the resilience dimension of serenity served as protective factors. Interestingly, finding meaning in life was positively correlated with fatigue, suggesting that caregivers who perceive their role as central to their life purpose may become more emotionally invested, increasing vulnerability to distress when unable to help animals. Official colony registration and formal institutional support did not significantly alleviate fatigue. These findings highlight that institutional support alone is insufficient to mitigate fatigue among informal caregivers, who experience significant distress driven by both practical burdens and profound emotional involvement. The most frequently reported concern among caregivers was the inability to cover the costs of feeding and veterinary care for the cats. Interventions must address both external needs (e.g., support to cover veterinary and feeding expenses for the cats) and internal coping mechanisms. Implementing psychosocial support alongside trap-neuter-return programs may also improve caregiver well-being and foster sustainable urban feral cat management. This underscores a One Health perspective, demonstrating that animal health is closely interconnected with human well-being and environmental health.

Introduction: Neurodegenerative diseases (NDDs) including Alzheimer's disease (AD), Parkinson's disease (PD), multiple sclerosis (MS), amyotrophic lateral sclerosis (ALS), and non-AD dementias share chronic neuroinflammatory mechanisms that contribute to neuronal injury and disease progression. While anti-inflammatory therapies (AITs) are associated with reduced neurodegenerative disease risk, knowledge regarding the impact of biological sex and treatment duration across multiple NDDs remains limited. Methods: We conducted a retrospective cohort analysis using a large propensity-score-matched population (n = 190,308; 95,154 treated vs 95,154 untreated) to evaluate associations between long-term AIT exposure and incidence of major NDDs. Disease-specific and combined outcomes were assessed across drug classes (NSAIDs, corticosteroids, immunomodulators), sex, age, and therapy duration. Results: AIT exposure was associated with a significantly lower risk of developing any NDD (RR = 0.47, 95% CI 0.43-0.48, p < .0001) and was equally effective in both sexes. Risk reduction was observed for each individual disease: AD (RR = 0.40), non-AD dementia (RR = 0.51), PD (RR = 0.43), MS (RR = 0.25), and ALS (RR = 0.48). Among drug classes, immunomodulators conferred the largest reduction (RR = 0.19), followed by corticosteroids (RR = 0.41) and NSAIDs (RR = 0.42). Duration analyses revealed a graded benefit, with RR declining from 0.94 (<1 year) to 0.25 (>6 years). Risk reduction was strongest in older participants (75-79 years). Discussion: Chronic use of anti-inflammatory or immunomodulatory therapies was associated with substantially reduced incidence of multiple neurodegenerative diseases in both sexes. The strongest effects were observed with immunomodulator use and prolonged therapy duration, suggesting that sustained modulation of systemic inflammation confers broad neuroprotective effects in both sexes. These findings highlight the potential of targeting immune-inflammatory pathways for neurodegenerative disease prevention and can inform prospective mechanistic and interventional studies.

Objective: Posttraumatic stress disorder (PTSD) after a traumatic birth is a serious but overlooked maternal morbidity, affecting ~20% of women following medically complicated deliveries. PTSD can undermine maternal caregiving. Rapid screening tools suited to busy obstetric settings are lacking. We developed and evaluated a brief screener, derived from the 20-item PTSD Checklist for DSM-5 (PCL-5), to identify PTSD related to childbirth. Study Design: We enrolled 107 women with traumatic childbirth. Participants completed the PCL-5 and the gold-standard clinician diagnostic interview for PTSD (CAPS-5); depression was measured with the Edinburgh Postnatal Depression Scale (EPDS). Bootstrap resampling with LASSO regression identified PCL-5 items most associated with PTSD. Firth logistic regression models estimated diagnostic accuracy. Sensitivity, specificity, area under the ROC curve (AUC), and Youden's J statistic determined performance and optimal cut-off. Results: A six-item version of the PCL-5 (PCL-5 R6), statistically derived from the full scale, showed excellent discrimination for PTSD compared with clinician evaluation (AUC = 0.95; 95% CI, 0.89-1.00). A cut-off score of 7 yielded high sensitivity (0.96) and good specificity (0.83), with an overall diagnostic efficiency of 0.86, detecting most PTSD cases while minimizing false positives. The PCL-5 R6 correlated moderately with the EPDS (rho = 0.53), showing that a depression screen alone cannot reliably detect PTSD. Conclusions: A short, 6-item PCL-5 provides a valid, efficient tool for detecting childbirth PTSD. Its brevity and accuracy make it practical for integration into routine postpartum care, enabling timely mental health screening.

Background and aims Iron deficiency (ID) and myocardial iron depletion (MID) are causally linked to heart failure (HF) in the general population and in preclinical models. ID is common amongst pregnant women, but its impact on cardiac adaptations to pregnancy is unknown. This study examines that impact, and its potential relevance to peripartum cardiomyopathy (PPCM). Methods. We provided female mice with iron-replete or iron-deficient diets, and monitored cardiac function and morphology longitudinally in pregnancy and postpartum. In women with no HF (n=64), we explored the associations between antenatal iron parameters and echocardiographic parameters in late pregnancy and at 6-12 months postpartum. We also performed a case (n=55), control (n=170) study comparing iron markers and assessing their association with PPCM risk. Results In mice, ID prevented postpartum reversal of pregnancy-induced hypertrophy, reduced postpartum LVEF, and caused profound MID. In women with no HF, low hepcidin, high transferrin and low serum iron were respectively associated with higher LVESV, lower LVEF and higher CMR T1-mapping (lower myocardial iron) in postpartum. In the PPCM study, serum iron, hepcidin and haemoglobin were significantly lower in cases than controls, and were independently associated with risk of PPCM. Mechanistically, myocardial proteomics revealed that ID caused sustained postpartum activation of pyruvate dehydrogenase kinase 4, a master cardiometabolic switch enzyme with a well-recognised role in HF. Conclusions This study links antenatal maternal ID to postpartum systolic dysfunction, and implicates MID and cardiometabolic switching as potential mechanisms. It suggests these links may potentially contribute to the pathophysiology of PPCM

Background At present, there are no approved pharmacological treatments for people at clinical high risk for psychosis (CHR-P). We sought to assess the acceptability of cannabidiol (CBD): a promising candidate treatment for this population. Methods CHR-P individuals completed a survey which assessed their views on the acceptability of CBD, its expected effectiveness and side effects, and on formulation preferences. Results The sample comprised 55 CHR-P individuals (24.3 years and 69% female). Most (91%) were familiar with CBD, and had previously used cannabis (64%), and around half (42%) had tried over-the-counter CBD. 75% were willing to take CBD as an intervention for mental health problems. Most participants anticipated fewer side effects with CBD than with existing medications, and preferred tablet or capsule formulations over liquids. Discussion CBD is perceived as a highly acceptable treatment among CHR-P individuals.

Abstract This protocol is reported in accordance with the SPIRIT 2025 guidelines for clinical trial protocols. Introduction: Young children, from birth to age 5 y are particularly vulnerable to indoor air pollutants and respiratory pathogens. Portable air purifiers (or filtration) and upper-room ultraviolet germicidal irradiation (UVGI) are two widely used interventions with the potential to improve indoor air quality (IAQ) and reduce sick-related absences. However, a review of the literature revealed no real-world randomized studies evaluating their effectiveness in reducing young children's sick-related absences in early care and education (ECE) classrooms. Methods and Analysis: The OK-AIR study is a longitudinal, cluster-randomized 2x2 factorial trial conducted in Head Start centers using two implementation cohorts: Cohort 1 (five Head Start centers and 20 classrooms from 2023 to 2024) and Cohort 2 (11 centers and 59 classrooms from 2025 to 2026), with expanded inclusion of rural areas. Cohort 1 enrolled 204 children, 48 teachers and 5 site directors, and Cohort 2 enrolled 462 children, 97 teachers and 11 site directors. Within each center, four classrooms are randomized to: (1) control; (2) portable filtration; (3) upper-room ultraviolet germicidal irradiation (UVGI); or (4) both interventions. Cohort 2 was initially planned as a second factorial trial but was amended to a purifier-only design due to funding changes; details are provided in the protocol amendments section. We collect continuous IAQ data, including particulate matter (PM) with aerodynamic diameters [&le;]1 m (PM1), [&le;]2.5 m (PM2.5), [&le;]4 m (PM4), and [&le;]10 m (PM10); total volatile organic compounds (TVOCs) index; nitrogen oxides (NOx) index; carbon monoxide (CO), noise; temperature; and relative humidity, alongside daily child absences. Seasonal environmental surface swabs (dining tables and toilet flooring) are tested by Reverse-Transcriptase quantitative Polymerase Chain Reaction (RT-qPCR) for Influenza A/B, Respiratory Syncytial Virus (RSV), Human Parainfluenza Virus Type 3 (HPIV3), Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), and Norovirus. IAQ monitoring is structured across Winter, Spring, Summer, and Fall, including designated baseline/off-period weeks to characterize temporal and seasonal variability in environmental measures across classrooms and centers. Multi-informant surveys (Director, Teacher, Parent) capture contextual factors, and children's social-emotional development is assessed using teacher ratings on the Devereux Early Childhood Assessment (DECA). The primary outcome is the sick-related absence rate, analyzed as cumulative absences over the attendance year while accounting for clustering by school and classroom using generalized mixed-effects models. Secondary outcomes include children's social-emotional ratings, IAQ metrics and pathogen detection rates; analyses of IAQ incorporate time/seasonal structure, and season-stratified absenteeism analyses will be treated as secondary/exploratory refinements. An economic evaluation will estimate incremental intervention costs and cost-effectiveness/cost-benefit (such as cost per sick-related absence day averted). Ethics and Dissemination: This study was approved by the Institutional Review Board (IRB) at the University of Oklahoma. Findings will be shared through peer-reviewed publications; presentations at local, state, and national conferences; research briefs developed for lay and policy audiences; and community briefings prioritizing the participating early childhood programs and communities. ISRCTN Trial Registration: ISRCTN78764448 Disclaimer: The views expressed are those of the authors and do not reflect the official views of the Uniformed Services University or the United States Department of War. Strengths and Limitations of This Study: {middle dot} Real-world longitudinal cluster RCT: The study uses a rigorous longitudinal cluster-randomized 2x2 factorial design in real-world ECE settings. {middle dot} Combined interventions: Interventions target both air filtration and disinfection, allowing for combined and comparative evaluation. {middle dot} Objective air quality monitoring: Continuous monitoring of IAQ metrics provides objective and reliable data on environmental change. {middle dot} Environmental pathogen surveillance: qPCR on surface swabs yields an objective biological outcome to triangulate with IAQ and absences. {middle dot} Comprehensive context and child measures: Multi-method and multi-reporter data collection includes Head Start attendance records, continuous air monitoring, pathogen detection, contextual surveys completed by center directors, teachers, and parents, and standardized social-emotional assessments (DECA) completed by classroom teachers. Head Start program records providing children's longer-term health data available through Health Insurance Portability and Accountability Act (HIPAA) authorization. {middle dot} Clustered/temporal complexity: Seasonal design accounts for variation over time but may introduce complexity in modeling temporal effects. {middle dot} Practical Implications: Study findings will have practical implications for Head Start and other ECE programs striving to maximize child attendance with cost effective strategies. Keywords: Early childhood; Head Start; indoor air quality (IAQ); air purifiers; filtration; ultraviolet germicidal irradiation; cluster randomized trial; absenteeism; environmental pathogens; DECA; cost-benefit analysis

Importance: Lung cancer mortality in the United States has fallen substantially in recent decades, yet the relative influence of behavioral, environmental, socioeconomic, and therapeutic factors and their sex specific contributions remains unclear. Understanding these drivers is essential to sustain progress and reduce persistent disparities. Objective: To quantify how behavioral, environmental, socioeconomic, and therapeutic determinants collectively shaped US lung cancer mortality from 1994 to 2020, assess sex specific differences, and forecast mortality trajectories through 2030 using an integrated machine learning framework. Design, Setting, and Participants: Ecological time series study using publicly available national data from 1994 to 2020. Sex stratified analyses were conducted integrating lung cancer mortality, smoking prevalence, fine particulate matter PM2.5 exposure, Human Development Index HDI, per capita healthcare expenditure, healthcare inflation, insurance coverage, income inequality, and annual drug approvals. Exposures: Behavioral smoking, environmental PM2.5, socioeconomic HDI health expenditure inflation, uninsurance inequality, and therapeutic drug approval indicators. Main Outcomes and Measures: Age-standardized lung cancer mortality per 100000 population. Temporal changes were modeled using Joinpoint regression. Concurrent associations were assessed using multivariable and elastic net regression, and forecasts were estimated with AutoRegressive Integrated Moving Average models with exogenous variables ARIMAX. Results: From 1994 to 2020, mortality declined by 59 percent in men, from 52.9 to 21.7 per 100000, and by 40 percent in women, from 26.7 to 15.9 per 100000, with faster declines after 2015. Smoking and PM2.5 decreased by more than 45 percent but remained strongly correlated with mortality. In elastic net models, PM2.5 was the strongest predictor for men, while smoking was the strongest predictor for women. Per capita expenditure and HDI ranked higher for men, while uninsurance and income inequality were strong predictors for women. Mortality declines occurred during periods of major approvals of lung cancer drugs. Forecasts suggest continued but slower declines through 2030, with projected rates of 20.2 and 14.9 deaths per 100000 in men and women, respectively. Conclusions and Relevance: Sex specific declines in lung cancer mortality reflect different dominant correlates, with air pollution more important in men and smoking more important in women, while socioeconomic conditions and therapeutic advances also influence trends. Continued tobacco control, improved air quality, and equitable access to screening and modern treatment are essential to sustain further reductions in mortality. Keywords: Lung Neoplasms, Sex Factors, Air Pollution, Smoking, Socioeconomic Factors, Machine Learning

Multiple sclerosis (MS) is a chronic neurodegenerative disease characterised by progressive neurological disability and heterogeneous symptom trajectories. Current clinical monitoring methods, including magnetic resonance imaging (MRI) and episodic neurological assessments, provide limited insight into subtle disease progression and functional changes. Digital health technologies integrating multimodal biosignals and behavioural assessments may enable continuous monitoring and personalised rehabilitation in patients with MS. This study aims to evaluate the clinical utility of the BodyMirror Clinical MS platform, a multimodal SaMD that combines wearable biosensors, neuroscience-based games, and machine learning to remotely monitor disease progression and deliver personalised neurorehabilitation for individuals with multiple sclerosis. This study is a prospective, randomised, double-blind, controlled, multisite clinical trial enrolling 400 participants (300 individuals with multiple sclerosis and 100 healthy controls). MS participants will be randomly assigned (1:1) to either an adaptive neurorehabilitation intervention group or a control group receiving non therapeutic digital activities matched for engagement and exposure. Participants will perform three 30-minute sessions per week over 24 months using the BodyMirror platform. The system integrates multiple biosignals, including electroencephalography (EEG), electromyography (EMG), inertial measurement unit (IMU) motion data, speech analysis, and behavioural performance metrics to generate digital biomarkers of neurological function. The primary endpoint is a change in Expanded Disability Status Scale (EDSS) score from baseline to 24 months. Secondary outcomes include changes in Multiple Sclerosis Functional Composite (MSFC), MRI brain volume, cognitive performance, patient-reported outcomes, adherence to digital rehabilitation, and health economic outcomes.

Protocadherin-12 (PCDH12), a cell-adhesion protein belonging to the non-clustered protocadherin family, plays a crucial role in the establishment and regulation of neuronal connections and communication. Bi-allelic loss-of-function (LoF) variants in the PCDH12 gene have been associated with several neurodevelopmental disorders (NDDs) such as diencephalic-mesencephalic junction dysplasia (DMJD) syndrome, cerebral palsy, and cerebellar ataxia, often accompanied by ocular abnormalities. However, genotypes exhibit variable expressivity. Affected individuals sharing the same PCDH12 variant presenting differing phenotypic severities have posed major challenges towards identification of the underlying pathogenic mechanisms. Here, we report three affected individuals from two families, each harbouring non-truncating pathogenic missense variants in PCDH12. The patients are compound heterozygous, with each individual carrying one extracellular [c.1742T>G (p.Val581Gly) and c.1861_2del/insCA (p.Ile621His)] and one intracellular variant [c.3370C>T (p.Arg1124Cys) and c.3445G>A (p.Asp1149Asn] on each allele. The children present with a range of phenotypes similar to those associated with LoF variants. One child exhibited microcephaly and seizures, while the two siblings displayed developmental delays and severe behavioral disorders. All three children experienced some degree of visual impairment. The missense variants provided new insights into the neurodevelopmental consequences of compromised PCDH12 function by distinguishing the specific consequences associated with dysfunction in the extracellular versus intracellular domains of PCDH12. All identified missense variants are predicted to be deleterious and destabilizing. The expression of PCDH12 in HEK293T and HeLa cells demonstrated that PCDH12 is expressed effectively, regardless of the presence of missense variants. However, the extracellular variants p.Val581Gly and p.Ile621His compromised the stability of PCDH12's homophilic adhesion. Additionally, we found evidence of an interaction between PCDH12 and the extracellular domain of the epilepsy-associated PCDH19 protein. PCDH12 extracellular missense variants also negatively impact this interaction. Our study provides evidence that PCDH12 mediates both homophilic and heterophilic interactions. Our findings also highlight the importance of stable PCDH12-mediated adhesion, emphasizing the need to further study the functional consequences of PCDH12 missense variants on brain and visual system development.

Background: Platform trials are an efficient trial design which enable testing of multiple interventions simultaneously. They could advance knowledge of treatments for intracerebral haemorrhage (ICH). We aimed to investigate the views of clinicians involved in stroke research on recruitment to a future platform trial for ICH. Methods: Between April and July 2025, we conducted a UK-wide online survey of clinicians actively involved in stroke research using convenience sampling through professional organisations. Participants considered factors related to the consent process and research environment and could provide optional free text responses about additional barriers or facilitators to recruitment. We used descriptive statistics for quantitative data and content analysis for qualitative data. Results: Among 73 respondents, 46 (63%) were female, 36 (50%) were stroke physicians, 24 (34%) nurses, 6 (8%) allied health professionals, and 7 (10%) were in other roles. 36 (49%) had >20 years of clinical experience, 45 (61%) reported spending <10% of their role in research. 66 (91%) thought that a platform trial would be a good option for testing interventions for patients with stroke due to ICH. Across 11 modifiable factors, clinicians most frequently rated perceived importance of the research question as a facilitator of recruitment (94%), while clinician preference for specific treatments was most frequently rated as a barrier (48%). Two themes emerged from free text responses: study design and infrastructure. Regarding study design respondents perceived consent procedures (n=9), study materials (n=8), study procedures (n=8), eligibility assessment (n=6), the research question (n=3) and randomization (n=3) as important for a future platform trial. Regarding infrastructure, emergent factors were staffing (n=17), local research culture and capacity (n=9), research governance and delivery (n=6), and training (n=6). Conclusion: The overwhelming majority of respondents from the UK clinical stroke community supported a platform trial for ICH, although the influence of survey responder bias is unknown.

Abstract Introduction Cardiovascular disease (CVD) is an important complication of type 2 diabetes (T2D). Current incident CVD-prediction models use single baseline measurements and achieve moderate performance in people with T2D, with C-indices around 0.7. Modern healthcare registries contain repeated measurements of HbA1c, LDL-cholesterol and eGFR, which could carry incremental predictive value. However, the added value of trajectory measures for CVD-risk prediction remains unclear. We aimed to investigate the utility of HbA1c, LDL-cholesterol and eGFR trajectory measures for incident CVD-risk prediction in people with T2D. Methods We studied 83,326 people with T2D from Danish nation-wide registers, who were without a CVD-history at baseline (January 1st 2015), and had [&ge;]2 recorded HbA1c, LDL-cholesterol and eGFR measurements between 2012-2014. Their last measurement was considered as baseline. Across 2012-2014, three types of paired trajectory measures were calculated for each participant (mean & standard deviation (SD), median & interquartile range (IQR), and intercept & slope from a fitted growth model), for HbA1c, LDL-cholesterol, and eGFR, respectively. Reference Cox-regression models for CVD-events (ICD-10 codes assessed prospectively from 2015- 2020) included only baseline measurements (age, sex , age at T2D onset, HbA1c, LDL-cholesterol, HDL-cholesterol, eGFR, and medication use). Next, the paired trajectory measures were sequentially added to the reference model, computing Hazard Ratios, C-indices and Net reclassification index (NRI) with 95% confidence intervals. Lastly, a combined model was fitted. Results At baseline, mean age was 65 (SD{+/-}12), median HbA1c was 48 (mmol/mol, IQR43-56), and 48% were female. During a median 6 years of follow-up 11,280 (14%) people had a CVD-event (ischemic heart disease: 40%; stroke: 32%; heart failure: 24%; CVD-mortality: 5%). Accounting for the reference model, trajectory measures of dispersion and change were associated with CVD-events, with hazard ratios {approx} 1.1 for HbA1c and eGFR, and >1.4 for LDL-cholesterol. Measures centrality did not show an association with CVD events. Addition of trajectory measures produced minimal gains in discrimination (C index {Delta} +0.001-+0.003) but modest improvements in net reclassification (continuous NRI {approx} +3-+9%). Conclusions Trajectory dispersion or change measures for HbA1c, eGFR and especially LDL-cholesterol, easily obtained from routine data, might moderately enhance incident CVD-risk prediction in people with T2D.

Deficits in inhibitory control are common across a wide range of psychiatric disorders and are closely linked to symptom severity, including emotional dysregulation, anxiety, substance misuse, and self-harm, making them an appealing target for intervention. Cognitive training offers a low-cost, scalable, and non-invasive strategy to strengthen inhibitory control; however, most existing paradigms target only a single facet of inhibition and rarely account for environmental influences, such as affective context. To address these gaps, we developed a computerized inhibitory control training paradigm to simultaneously engage three components of inhibition: preemptive, proactive, and reactive, while embedding trials within positive and negative affective contexts to assess the impact of emotional stimuli. Across two online experiments, participants completed the GAMBIT task in one session (Experiment 1, N = 300) or repeated over three sessions (Experiment 2, N = 65). The task included No-Go trials to train preemptive inhibition, stop-signal trials for reactive inhibition, and stop-signal anticipation trials to train proactive inhibition. Affective images of differing valence were presented as background stimuli to evaluate their impact on inhibitory performance. In Experiment 1, participants showed higher accuracy on No-Go versus reference Go trials ({beta}=1.45, SE=0.09, p<.001), confirming successful manipulation of preemptive inhibition. Reaction times were slower during anticipation trials across two different conditions ({beta}=0.16, SE=0.04, p<.001; {beta} = 0.07, SE = 0.04, p = 0.047), consistent with proactive slowing when anticipating a potential stop signal. Additionally, positive affective images ({beta} = 0.10, SE= 0.009, p < 0.001) further slowed RTs, indicating emotional interference with proactive control. In Experiment 2, the pattern of higher No-Go accuracy was replicated ({beta} = 0.91, SE = 0.11, p < .001) and accuracy generally improved over sessions ({beta} = 0.38, SE = 0.06, p < .001). In anticipation trials, RTs become shorter across sessions (session 2: {beta} = -0.25, SE = 0.06, p < .001; session 3: {beta} = -0.45, SE = 0.06, p < .001), reflecting practice-related gains, and SSRTs decreased over time (F(2,56) = 6.26, p = .004), consistent with enhanced reactive inhibition. Proactive inhibition was modulated by affective images, with both negative ({beta} = 0.04, SE = 0.02, p = .039) and positive ({beta} = 0.16, SE = 0.02, p < .001) affective images associated with slower RTs. Participants also reported reductions in self-assessed temper control by the last session (W = 25.5, p = .007, q = .037, d = -0.51) and usability ratings were high (all means [&ge;] 3.87/5). Together, these findings show that this paradigm recruits multiple forms of inhibitory control and yields training-related improvements in both performance and affective outcomes. This provides preliminary validation of a scalable, fully online inhibitory control training tool targeting multiple dissociable inhibitory processes within affective contexts. The approach holds promise as an accessible transdiagnostic intervention to support symptom improvement across psychiatric disorders, with future work needed to evaluate clinical efficacy in patient populations.

Purpose: The GIG-OSH cohort was established to investigate the impact of digital platform work on occupational safety and health (OSH), working and employment conditions, and health in seven countries in Europe. Participants: The cohort comprises 3,945 digital platform workers from seven European countries. The sample includes both web-based workers (e.g., micro-tasking, freelance design) and on-location workers (e.g., delivery, transport). Participants were recruited using non-probabilistic sampling strategies tailored to national contexts, including social media advertising, recruitment through micro-task platforms, and on-site field outreach. Multidimensional data have been collected through online surveys (implemented via REDCap) covering sociodemographic characteristics, working and employment conditions, psychosocial risks, algorithmic management, and physical and mental health indicators. Findings to date: Participants had a mean age of 32.6 years at baseline (SD 10.4), and the majority are male (58.8%), with a higher concentration of migrants in on-location tasks (62.2%) compared to web-based tasks (48.8%). Regarding educational attainment, 55.4% of the total cohort holds a tertiary degree, reaching 64.4% among web-based workers. Platform work intensity varies significantly: on-location workers averaged 85.4 hours of work in the last month, while web-based workers averaged 47.0 hours. Mean income from platform work as a percentage of the national median was 20.6% (SD 22.2). The mean WHO-5 Well-Being Index score was 58.7 (SD 20.3), which is notably lower than the European general population average (69.4), indicating poorer mental health outcomes among cohort members. Future plans: The GIG-OSH cohort represents the first large-scale, longitudinal study examining occupational safety and health among digital platform workers across multiple European countries. Future waves will prioritize developing precise tools to measure hourly earnings and unpaid waiting time. Future research should aim to include underrepresented subgroups, such as medical and domestic care workers, and explore potential linkage with administrative records to evaluate long-term health trajectories and the impact of new EU labour regulations.

A recent randomized clinical trial in non-small cell lung cancer1 confirms what numerous observational studies have reported time of day (ToD) may dramatically influence treatment outcomes in cancer patients. In this recent trial median overall survival (OS) decreased from 28 months in the early ToD arm to 16.8 months in the late ToD arm. We raise the concern that clinical trial outcomes may be influenced by seemingly minor biases in treatment time across arms. We also suggest that by measuring or randomizing treatment-time in clinical trials, we may identify beneficial ToD dependent treatments that would otherwise be overlooked.

Background and objectives STXBP1-related disorder (STXBP1-RD), caused by pathogenic variants in the STXBP1 gene, is a rare neurodevelopmental condition, characterized by early-onset seizures, developmental delay, intellectual disability (ID), and prominent motor dysfunction. Despite the high prevalence of motor symptoms, systematic gait characterization remains limited. We therefore aimed to quantitively assess gait in individuals with STXBP1-RD. Methods In this cross-sectional study, we included ambulatory patients aged 6 years or older with genetically confirmed STXBP1-RD. Instrumented 3D Gait Analysis (i3DGA) was performed to objectively quantify gait. Functional mobility was assessed with the Functional mobility scale (FMS) and Mobility Questionnaire 28 (MobQues28). Caregiver health-related quality of life was evaluated using the PedsQL-Family Impact Module (PedsQL-FIM). We explored associations between gait, functional mobility, STXBP1-variant type and clinical features (ID, age at seizure onset, seizure frequency, age at onset of independent walking). Correspondence between i3DGA and the Edinburgh Visual Gait Score (EVGS), an observational gait assessment, was investigated. Results Eighteen participants were included. Compared to typically developing peers, individuals with STXBP1-RD had significantly reduced walking speed, step and stride length. Gait patterns were highly variable, with the most frequent pattern being an externally rotated foot progression angle (FPA), present in 11/18 participants. At home, 93.75% of the participants (16/18) walked independently, yet community mobility was more variable: 11/16 (68.75%) walked independently, 2/16 (12.50%) with aid and 3/16 (18.75%) used a wheelchair, indicating increasing limitations with distance and environmental complexity. Earlier acquisition of independent walking strongly predicted later unassisted ambulation at community level (p<0.001). Median MobQues28 score was 57.14% and median PedsQL-FIM score was 60.42%, indicating a moderate level of mobility limitations and reduced health-related quality of life of caregivers. EVGS was highly positive correlated with i3DGA (p= 0.001). Discussion Quantitative gait analysis in individuals with STXBP1-RD demonstrates heterogenous kinematic deviations, with an externally rotated FPA emerging as the most common pattern. Age at independent walking was a clinically relevant predictor of later functional mobility. EVGS showed strong correspondence with i3DGA and may offer a more practical, semi-quantitative assessment for broader use. These findings inform clinical decision-making and guide the selection of scalable outcome measures for natural history studies and interventional trials.

Actigraphy is a popular behavioral sleep assessment tool in research and clinical practice. Hierarchical hand-scoring approaches remain the standard for actigraphy rest interval estimation, but can be impractical for large cohort studies and suffer from reproducibility problems. We developed a semi-automated pipeline (actiSleep) to set rest intervals consistent with best-practice hand-scoring algorithms incorporating event marker, diary, light, and activity data. To evaluate actiSleep performance, we used data from an observational study of 51 adolescents (14-19yr), with and without family history of bipolar disorder. Participants completed 2 weeks of wrist actigraphy and daily sleep diary. We first hand-scored records using a standardized hierarchical algorithm incorporating event marker, diary, light, and activity data. We then compared the hand-scored rest intervals to those from actiSleep and two automated activity-based algorithms (Activity-Merged, Activity-Only). Activity-Only used activity-based sleep estimation and Activity-Merged joined closely adjacent rest intervals. For rest onset, rest offset, and rest duration, all algorithms had strong mean agreement with hand-scoring: actiSleep estimates were within 1-3 minutes, Activity-Merged within 2-4 minutes, and Activity-Only within 7-14 minutes. However, actiSleep had notably better (narrower) margins of agreement with hand-scoring, as evidenced by Bland-Altman plots, and greater positive predictive value and true positive rates for rest detection, especially in the 60 minutes surrounding the onset and offset of the rest interval. The actiSleep algorithm successfully estimates actigraphy rest intervals comparable to hand-scoring while avoiding pitfalls of activity-only algorithms. actiSleep has potential to replace hand-scoring for research in adolescents but requires further testing and validation in other samples.

Background Persistent inequities in immunisation coverage, particularly among zero-dose and under-immunised children, continue to challenge Pakistan's Expanded Programme on Immunization. Weak feedback loop, inconsistent data quality, and limited real-time monitoring impede effective decision-making. This Implementation Research was conducted under the MAINSTREAM Initiative funded by Alliance for Health Policy and Systems Research (AHPSR) and supported by the Aga Khan Community Health Services Department and National Institutes of Health Pakistan to design, implement, and evaluate a digital monitoring and action planning tool to strengthen data-driven decision-making within routine immunisation systems. Methodology/Principal Findings A co-creation approach was employed to design a digital monitoring solution through inclusive consultations, key informant interviews, and focus group discussions with EPI Punjab at provincial and district levels. The solution included a customised mobile application for data collection and a Power BI visualisation dashboard to map low-coverage areas, identify drivers of dropouts and zero-dose children, and capture caregivers' information sources to inform targeted communication. The intervention was piloted in 60 households across six clusters of a Union Council of District Lahore. Advanced analytics identified reasons for non-vaccination and missed opportunities, generating tailored recommendations and practical plans for program managers. The analysis assessed acceptability, adoption, fidelity, and perceived scalability through field observations, system use, and stakeholder feedback. The co-developed digital tool enhanced visibility of coverage gaps through UC-level mapping, real-time dashboards, and structured action planning. Pilot testing in Lahore showed strong acceptability, ease of use, fidelity, and adaptability among managers, supervisors, and vaccinators. Scalability and sustainability potential were demonstrated, though barriers included leadership turnover, system fragmentation, workload pressures, and resource constraints. Conclusion The tool demonstrated feasibility to strengthen immunisation equity, accountability, and responsiveness. Co-creation with stakeholders enhanced ownership, operational relevance, and adoption, while complementing existing platforms. Sustainability will depend on effective integration, local ownership, capacity building, and accountability, while scalability requires interoperability, resource commitment, policy support, and alignment with existing workflows.

Understanding host susceptibility to Mycobacterium tuberculosis (Mtb) is critical for the development of new vaccines. Certain individuals "resist" becoming infected with Mtb despite intensive exposure; however, it is unknown whether there is a genetic basis for "resistance" to Mtb infection across populations. Here we conducted a genome-wide association study (GWAS) of resistance to Mtb infection by carefully characterizing exposure to TB patients among 4,058 close contacts in India, Brazil, and South Africa. 476 (12%) "resisters" remained free of Mtb infection despite substantial exposure to highly infectious TB patients. GWAS identified a novel chromosome 13 locus (rs1295104126) associated with resistance across the multi-ancestry meta-analysis. Comparing Mtb-infection to all uninfected contacts, irrespective of exposure, yielded a different locus on chromosome 6 (rs28752534), near the HLA-II region. These findings demonstrate a common genetic basis for resistance to Mtb infection across multi-ancestral cohorts with potential to elucidate novel mechanisms of protection from Mtb infection.

Background: Quadriceps weakness may reduce sagittal plane shock absorption during landing, shifting load toward the frontal plane and increasing knee abduction moment (KAM), a biomechanical risk factor for anterior cruciate ligament (ACL) injuries. Purpose: The purpose of this study was to evaluate the association between isokinetic quadriceps strength and peak KAM during drop vertical jump landing in adolescent athletes. Study Design: Secondary analysis of previously collected data. Methods: Healthy adolescent athletes completed quadriceps strength testing using an isokinetic dynamometer and a biomechanical assessment during a drop vertical jump task. Quadriceps strength was quantified as peak concentric torque and the peak external KAM was calculated during the landing phase on the dominant limb. Both strength and KAM were normalized to body mass. Linear regression was used to examine the association between normalized quadriceps strength and peak external KAM on the dominant limb. Results: The association between quadriceps strength and peak normalized KAM on the dominant limb was not statistically significant ({beta} = -0.053 (95% CI [-0.137 to 0.030]), F(1,119) = 1.62, R2 = 0.013, p = 0.206). Quadriceps strength explained only 1.3% of the variance in peak KAM, indicating a negligible association between these variables in this cohort. Discussion: Quadriceps strength was not associated with peak normalized KAM during landing, suggesting that frontal-plane knee loading during a drop vertical jump is not meaningfully explained by maximal concentric quadriceps strength alone. KAM appears to be driven more by multi-joint movement strategy and neuromuscular coordination than by the capacity of a single muscle group.

Objectives: Compare Anterior Cruciate Ligament (ACL) Return to Sport after Injury (ACL-RSI) scores over time following ACL reconstruction (ACLR) between male and female patients aged 15 to 25 years with primary ACL injuries and ACL reinjuries. Design: Retrospective cohort design. Setting: Sports physical therapy clinics. Participants: 332 patients aged 15-25 years who underwent ACLR following either primary ACL injury or ACL reinjury, either contralateral or ipsilateral graft reinjury, and had at least one observation of the ACL-RSI. Main Outcome Measures: ACL-RSI score. Results: ACL-RSI scores significantly increased over time post- ACLR (p < .001), males reported significantly higher scores compared to females (p < .001), and patients with contralateral ACL reinjury demonstrated higher scores than those with ipsilateral ACL graft reinjury (p = .006), though there was no difference in scores between patients with primary ACL injury and ACL reinjury. A significant interaction effect of sex and injury status was also observed (p = .009), generally demonstrating that females had lower psychological readiness compared to males across injury statuses. Conclusions: ACL-RSI following ACLR varies based on biological sex and time post-ACLR, though ACL reinjury, independent of the reinjured leg, does not appear to effect scores compared to primary ACL injury.