Matrix Biology

Postoperative resilience varies widely among older adults, yet the biological drivers of recovery remain unclear. We evaluated whether preoperative immune profiles, measured in plasma and through ex vivo whole blood stimulation, predict resilience to the acute stress of total knee arthroplasty. A total of 152 adults (greater or equal to 60 years) in the PRIME KNEE cohort underwent elective total knee arthroplasty and had available blood samples for measurement of 45 immune biomarkers, quantified in plasma and in whole blood stimulated ex vivo for 24 hours with lipopolysaccharide (LPS) or influenza antigen (FLU). Resilience was assessed using Expected Recovery Differential (ERD) and Resilience Trajectory (RT) across pain severity, pain interference, lower extremity physical activities of daily living (LE PADLs), and step counts. An exploratory stability selection framework using LASSO identified biomarker predictors of postoperative outcomes. Plasma and stimulated biomarkers showed broadly similar predictive performance. A shared set of biomarkers, including LBP, leptin, TNFR1, CD30, and LIF, was consistently selected across models. Immune predictors explained ~12-24% of the variance in resilience outcomes. Distinct immune signatures emerged for pain versus functional recovery: pain related predictors mapped to local inflammatory and neuroimmune pathways, whereas function related predictors reflected systemic inflammatory load and cytokine signaling. Preoperative immune biomarkers, whether measured in plasma or after ex vivo stimulation, capture meaningful variance in postoperative resilience. The divergence between pain related and function related immune signatures highlights biologically distinct pathways underlying different dimensions of recovery and supports further development of immune based perioperative risk assessment.

Biological systems evolve as continuous dynamical processes, but at organ-scale and across human lifespans they are rarely observed longitudinally--population data typically exist instead as sparse, cross-sectional snapshots. Inferring lifespan dynamics from such data requires methods distinct from those used at cellular and tissue scales where dense observations are accessible. We address this problem in the thoracic aorta, where surgical decisions currently rest on static, age- and sex-agnostic diameter thresholds that reduce three-dimensional morphology to a single scalar. Treating normal aortic morphology as a stochastic dynamical system, we pose a continuous-time drift-diffusion process in a two-coordinate state space of normalized surface area (A) and normalized fluctuation in integrated Gaussian curvature ({delta} K), and fit closed-form solutions of the Fokker-Planck equation by maximum likelihood to a sex-balanced, age-uniform cohort spanning infancy to age 99. Inter-individual variability is treated as a fitted diffusion parameter rather than as residual scatter, which is distinct from prior normative studies that report variability as scatter around a regression line. The framework identifies two growth regimes for aortic size (childhood expansion followed by persistent adult growth, with adult males growing approximately 70% faster than adult females) and a single dynamical regime for aortic shape, with heteroscedastic variability accumulating at a rate comparable to the mean drift over the lifespan. Applied to independent cohorts of acute and chronic thoracic aortic dissections, the multivariate model identifies over 95% as statistical outliers via Mahalanobis distance, consistently outperforming either coordinate alone. The same probabilistic envelope that describes normal aging thus defines a baseline against which disease can be detected, supporting a shift toward dynamic, age- and sex-aware assessment of thoracic aortic pathology.

Abstract (already in the PDF; paste if a box is required): Injury risk prediction in elite football relies almost exclusively on external load metrics derived from GPS tracking, overlooking the molecular state of the athlete. We monitored 26 male players from FC Barcelona's first team across the 2025 calendar year, integrating GPS-derived training load with longitudinal blood-based immune monitoring (systemic inflammation and TCR-derived immune age). Immune age acceleration and inflammation were elevated in the 14 days preceding musculoskeletal injuries. A logistic regression model combining external load, inflammation, immune age acceleration, and career injury history reached an overall AUC of 0.678 and a mean per-player AUC of 0.754 (SD 0.146), improving on a GPS-only baseline of 0.541. Applied to 2026 data, the frozen model ranked players who later sustained non-contact musculoskeletal injuries high in the risk distribution. Together, our data suggest multimodal immune monitoring in elite football to reveal the athlete's internal physiological state, which carries injury-relevant information that external load alone does not capture.

Bone remodeling is a tightly regulated physiological process that maintains bone health through coordinated action of bone-resorbing osteoclasts and bone-forming osteoblasts. Disruption of this balance, such as the one induced by estrogen decline after menopause, results in bone loss and osteoporosis. Genetic factors play an important role in determining bone mineral density (BMD) loss over time. However, translating genetic associations into individualized risk prediction remains challenging due to small effect size of individuals variants and non-linear interactions within the bone remodeling unit. Here, we present a bone cell population dynamics model that includes major regulatory pathways, such as the RANK/RANKL/OPG axis, Wnt signaling, and hormonal regulation by estrogen, parathyroid hormone, and TGF-{beta}. We calibrate the model on clinical data from healthy postmenopausal women, and women with reduced BMD undergoing anti-osteoporotic therapy. The calibrated model captures healthy BMD decline in postmenopausal women and therapeutic response to anti-osteoporotic medications. We mechanistically incorporate the effect of 22 variants across 8 genes involved in bone remodeling and simulate BMD trajectories in 1,000 virtual subjects differing by ancestry and genetic makeup. The median predicted 5-year BMD loss was 3.57% (95% prediction interval: 1.31-5.24), consistent with the values reported in the literature. The virtual individuals with African ancestry were predicted to experience the highest average 5-year BMD loss. The strongest genetic risk factors for bone loss were predicted to be CYP19A1 rs727479 and OPG rs3102735, while LRP5 rs11228240 emerged as a protective factor that could partially counteract the detrimental effects of other variants. Several epistatic effects were observed in the genetic interaction analysis. Mechanistically, our model suggested that estrogen exerts its effect on bone remodeling primarily by modulating osteoclast apoptosis. Overall, this framework demonstrates a proof-of-concept for integration of genetic risk factors into mechanistic models of disease and can be extended to other conditions with polygenic inheritance.

INTRODUCTION Severe acute brain injury (stroke, traumatic brain injury or hypoxic-ischemic encephalopathy; SABI) is increasingly recognized as a chronic condition with care and communication needs beyond the initial hospitalization. This study aimed to characterize post-acute care patterns among SABI survivors, focusing on healthcare utilization and outpatient communication. METHODS Data were collected from a prospective cohort of hospitalized SABI patients using surveys, chart reviews, and the ED Information Exchange database. Socioeconomic disadvantage was assessed using the Area Deprivation Index (ADI), and qualitative analysis of outpatient notes examined conversations around palliative care needs and goals-of-care. RESULTS Two-thirds of patients (140/222) survived until discharge, primarily to nursing facilities (39%) or inpatient rehabilitation (38%). Among 109 with one-year follow-up, there were 89 hospitalizations, 104 ED visits, and 28 deaths. Patients from the most disadvantaged neighborhoods had significantly higher odds of rehospitalization or ED use within 30 days (OR 3.37, p=0.036). ADI was not linked to one-year utilization. seen outpatient by primary care (40%), neurology/neurosurgery (57%), and palliative care (1%), but conversations rarely revisited prognosis or goals-of-care. CONCLUSIONS Our findings highlight the need for improved long-term care planning and communication, particularly for socioeconomically disadvantaged survivors of SABI.

Synapse loss is an early feature of neurodegeneration and may provide sensitive biomarkers for experimental medicine. Positron emission tomography (PET) with the synaptic vesicle glycoprotein 2A radioligand [11C]UCB-J shows widespread signal reduction across dementias. However, it remains unclear which aspects of synaptic integrity [11C]UCB-J PET measures. We developed a histological-imaging pipeline to quantify structurally intact synapses in post-mortem brain tissue. We applied it to six donors with the tauopathy progressive supranuclear palsy (PSP) who had ante-mortem [11C]UCB-J-PET, alongside six controls across 11 brain regions. Synapse loss in PSP was widespread but region-specific across cortical, subcortical, and brainstem regions. Greater synapse loss was associated with higher tau burden and pathology, and cortical synaptic density correlated with ante-mortem cognition. Post-mortem synaptic density correlated with in vivo [11C]UCB-J-PET signal. This study provides validation of SV2A PET as a biomarker of synaptic density and supports integration of imaging with histopathology in neurodegenerative disease research.

Background: Adults with severe mental health conditions (often referred to as severe mental illness, SMI) experience 15 to 20 year mortality gap relative to the general population, with lung cancer a significant contributor. National cancer policy targets earlier diagnosis but does not explicitly address how pathways function for this group. Aims: This study aimed to describe lung cancer risk, prevalence, screening eligibility, referral activity and diagnostic pathway performance for adults with SMI in South East London (SEL), and to examine where along the pathway inequalities arise. Methods: Co-designed with experts with lived experience and voluntary sector, this exploratory mixed-methods service evaluation combined quantitative analysis of routinely collected data from the Quality Outcomes Framework (QOF), SMI Register and Cancer Waiting Times Record (April 2023-March 2024) with semi-structured qualitative interviews (n=11 clinical staff) and focus groups (n=6 adults with lived experience of SMI). Quantitative and qualitative data were analysed using descriptive statistics and framework-based thematic analysis respectively, and findings were integrated using a joint display approach, organised by the Consolidated Framework for Implementation Research (CFIR). Results: Lung cancer prevalence was approximately double among adults with SMI (0.17% vs 0.09% in the general population). Despite Urgent Suspected Cancer (USC) referral rates being more than twice as high in the SMI population (63 vs 28 per 100,000), fewer cancers were detected via planned general practice (GP) routes (11% vs 20%), the 28-day Faster Diagnosis Standard was not met for any SMI patient diagnosed with lung cancer during the study period; overall FDS performance was 76% in the SMI population compared with 84% in the general population; and appointment non-attendance was more than double that in the general population (6% vs 3%). Qualitative findings identified individual, service and system-level mechanisms, including stigma, diagnostic overshadowing, fragmented coordination, and rigid pathway protocols, that compound disadvantage across lung cancer pathway stages. Conclusions: Inequality in lung cancer outcomes for adults with SMI accumulates across the pathway rather than arising at a single point of failure. Addressing this requires proportionate adaptations within existing cancer pathways, alongside routine reporting of cancer outcomes stratified by SMI population. Keywords: severe mental health conditions, lung cancer, health inequalities, cancer screening, diagnostic pathway, mixed methods

Background: Alpha-1 antitrypsin deficiency (AATD) caused by the PI*ZZ mutation (Glu342Lys) results in hepatic accumulation of misfolded AAT-Z protein and reduced circulating AAT levels, leading to progressive liver disease and emphysema. Gene correction therapy represents a potentially curative approach by directly correcting the underlying genetic defect. We report the first case of successful hepatic gene correction with early histological and functional assessment. Methods/Case presentation: We report the case of a 66-year-old male patient with PI*ZZ AATD who underwent gene correction therapy within the YOLT-202 phase I/Ia clinical trial (clinical trial.gov ID NCT07193615). Ten weeks post treatment a liver biopsy was performed to re-evaluate pre-existing F2 liver fibrosis as measured by elastography before entering the study. Serum samples allowed functional assessment of the AAT-mediated elastase inhibition. Results: Liver biopsy did not show signs of hepatic inflammation and demonstrated 54% (Sanger) and 57% (Illumina) gene correction rate of the PI*ZZ variant on the DNA level with no bystander edits or off-target effects. Following a transient elevation of transaminases during the early post-treatment period, liver enzymes normalized. Monthly serum AAT measurements demonstrated biologically active and stable therapeutic levels throughout follow-up. Conclusions: This case demonstrates efficient and precise hepatic gene correction without concerning histological alterations and with substantial improvement of functional parameters, supporting the feasibility and safety of gene editing approaches for AATD.

Background Continuous health monitoring enables early detection of diseases and improves therapeutic outcomes. Non-intrusive biosignal sensors, such as capacitive ECG (cECG), offer a practical solution for daily monitoring in private environments, such as smart homes and vehicles. However, artifacts reduce signal quality and compromise reliability. Methods Following a registered report protocol (Warnecke JM et al. Plos One. 2021; 16(7):e0254780), we record data of 44 subjects and develop an artifact index for cECG. We use three signal quality indices (SQIs): the correlation of QRS complexes (corSQI), the R-peak detection consistency (bSQI) and the absolute amplitude ratio (aSQI). Our index classifies overlapping 10s segments with a step-width of 2s into clean or artifact segments. We label a 2s interval as artifacts if all five overlapping segments indicate artifacts. We record cECGs using an armchair with integrated electrodes in a single-arm study involving 44 subjects performing two activities -- reading and watching television (TV); for 11 minutes each. We record a time-synchronized reference ECG with skin electrodes on the chest. To evaluate the artifact index, we compare it with manually generated ground truth. Moreover, we evaluate the clothing materials cotton, linen, jeans, and polyester in 5 subjects. Results Watching TV results in longer, continuously clean signal durations than reading. On average, 88.3% of the signal has a minimum continuous clean duration of 10s, versus 79.8% during reading. All clothing configurations achieve a clean signal duration exceeding 10s. Among the SQI metrics, bSQI performs best, achieving an accuracy of 90.7% and an F1 score of 79.9%. Combining the three SQI metrics in a voting approach improves accuracy to 92.0% and F1 score to 82.1%. Discussion Our artifact index automatically distinguishes clean from artifact cECG segments, promoting health monitoring in unsupervised real-world settings, earlier disease detection, and preventive health management. A limitation is the investigation of only two scenarios (reading and watching TV).

Whole-genome sequencing comprehensively captures coding, non-coding and structural variation in families with suspected inherited disorders, yet its clinical utility remains constrained by an interpretation bottleneck: selecting a handful of relevant variants from millions of candidates. Current rule-based pipelines, anchored in ACMG/AMP criteria, excel at identifying highly penetrant Mendelian alleles but frequently miss variants of low-to-moderate penetrance, non-coding alterations and germline-somatic interactions. Here we introduce PolyCLIP-T, a topology-guided multimodal framework that transforms variant selection from a classification problem into a geometric discovery task. By contrastively aligning DNA-sequence embeddings with functional annotations, PolyCLIP-T constructs a unified latent space in which the displacement between reference and alternate embeddings quantifies the molecular perturbation induced by each variant. Persistent homology then identifies stable topological components - coherent variant groups shared among affected relatives - that transcend single-variant scoring logic. Applied to six families with multi-morbid cancer, autoimmune and cardiovascular disease, PolyCLIP-T recovered non-coding and structural candidates overlooked by conventional pipelines and revealed pleiotropic networks spanning disease categories. This approach provides an interpretable, scalable solution for genome-first investigations of disorders driven by polygenic architectures that evade single-variant analysis. The framework was developed and benchmarked on deeply characterised familial cohorts selected for transgenerational multimorbidity; validation in larger, independent populations will be essential to establish its generalisability. An interactive web tool is freely available at https://www.polyclip-t.uma.es/.

Introduction: Early hospital presentation after stroke onset is necessary for rapid assessment and access to time-dependent acute management. This study examined the correlates of late presentation for stroke care among patients recorded at a tertiary hospital in Ondo State, Nigeria. Methods: A retrospective records review was conducted using secondary data from the Stroke Registry of the University of Medical Sciences Teaching Hospital, radiology department records, referral notes, and ambulance records. Records of stroke cases documented within the preceding 24 months were reviewed. Late presentation was defined as hospital presentation more than four hours after symptom onset. Frequencies, chi-square tests, and modified Poisson regression with robust standard errors were used to estimate adjusted prevalence ratios. Results: The analysis included 371 stroke cases. Of these, 317 (85.4%) presented after four hours, and the median time to presentation was 24 hours (interquartile range: 9-72 hours). Late presentation differed significantly by employment status, first-contact route, and pathway complexity at bivariate analysis. After adjustment, non-hospital first contact remained strongly associated with late presentation: patients whose first documented contact was non-hospital-based had almost 3 times the prevalence of delay compared with those whose first contact was hospital-based (adjusted prevalence ratio = 2.89; 95% confidence interval: 2.15-3.90; p < 0.001). Conclusion: Late presentation was pervasive in this tertiary hospital record cohort and was primarily associated with the initial direction of care-seeking. Stroke response interventions should emphasise immediate hospital presentation and strengthen urgent referral from non-hospital first-contact points.

Background Thalassemia is one of the most common monogenic disorders worldwide, current screening strategies combining hematological testing with molecular assays still carry a risk of missed diagnoses and undesirable efficiency, particularly for complex structural variants and rare mutations. Methods In this prospective double-blind, multicenter cohort study of 3,842 participants (3,362 pregnant women and 480 male partners), we conducted a head-to-head comparison to systematically evaluate the incremental clinical value and detection performance of single-molecule nanopore sequencing in thalassemia (SMITH) against conventional hematological testing and next-generation sequencing (NGS). Findings The overall concordance rate between NGS and SMITH was 98.6% (3789/3842). The discrepant cases (n=53) were directly attributed to the superior detection capabilities of SMITH, which successfully identified complex structural rearrangements-including 45 -globin gene triplications and four HK alleles-that were missed by NGS. Furthermore, SMITH accurately detected four rare variants (c.134_135insT/, c.-22(C>T)/, {beta}N/{beta}c.316-290delinsAGGGCAATAATTT and {beta}3.5 kb deletion/{beta}N ) and resolved ten trans and three cis configurations within the globin gene allele. Clinically, these technical advantages translated to a 9.3% (5/54) increase in the detection rate of high-risk prenatal couples, effectively preventing one birth affected by moderate-to-severe thalassemia. Additionally, SMITH corrected a diagnostic discrepancy in one case (HK vs. -3.7), sparing the couple from an unnecessary invasive procedure. Interpretation Our findings demonstrate that SMITH provides a powerful platform for resolving globin gene rearrangements, detecting rare variants, and enabling direct haplotype phasing. By effectively eliminating diagnostic blind spots, SMITH is expected to become an optimal method for thalassemia prevention programs. Funding This study was supported by Chinese National Natural Science Foundation Projects 81760037 and 82271894.

Background: Two-thirds of Dutch cardiovascular risk management (CVRM) for patients at risk of cardiovascular disease is delivered in primary care practices. While individual risk scores are increasingly used during consultation, a population-level structure for risk-based patient outreach is not currently available. We therefore developed the PROSPERA programme, a multilevel intervention comprising population-level risk stratification and individual-level support tools. Aim: To assess anticipated and experienced barriers and facilitators among healthcare professionals (HCPs) to inform implementation in primary care. Methods: We conducted four focus groups and six interviews with nine primary care HCPs to explore anticipated and experienced barriers and facilitators. Inductive codes were thematically analysed and assigned to corresponding domains of the Theoretical Domains Framework (TDF) and the related Capability, Opportunity, Motivation model of Behaviour. Results: Barriers and facilitators were identified in 11 TDF domains. Population-level barriers included altered professional roles and limitations in technological infrastructure. Individual-level barriers were limited skills in interpreting risk calculations and difficulty integrating tools into clinical routine. Facilitators were related to beliefs on the importance of providing proactive care (population level), the use of U-Prevent for risk communication (individual level) and positive patient responses to the Lifestylecheck questionnaire (individual level). Conclusion: Addressing barriers and facilitators identified at both the population and individual levels can support implementation of the PROSPERA programme. Opportunities exist in education and training of HCPs in risk communication, as well as support in restructuring the physical and digital environment.

Background: Cardiovascular-kidney-metabolic (CKM) syndrome is a leading driver of cardiovascular morbidity and mortality. Whole-body molecular imaging is well-positioned to phenotype such syndromes, yet no imaging biomarker quantifies cumulative CKM burden. Bone scintigraphy with 99mTc-labeled bisphosphonates is widely performed and expanding with transthyretin amyloidosis assessment, under which Perugini grade 0 (absent cardiac uptake) is considered clinically benign. Objective: We hypothesized that the soft tissue-to-bone ratio (STBR) on these scans captures CKM burden and is an independent prognostic biomarker. Methods: We retrospectively analyzed 8,769 consecutive patients without cardiac uptake on 99mTc-DPD whole-body planar scintigraphy. The primary endpoint was all-cause mortality. Secondary endpoints were major adverse cardiovascular events (MACE) and heart failure hospitalization. Cox models were adjusted for ten established cardiovascular risk factors. Imaging-phenotype association (IPA) analysis mapped STBR to 1,210 clinical traits. STBR distribution across CKM stages was assessed in four prespecified analyses, including a non-cancer subgroup. Results: During a median follow-up of 5.1 years (IQR 2.5-8.2), 2,418 deaths occurred. Patients with prespecified STBR >0.5 (n=772, 8.8%) had significantly higher mortality (adjHR 1.73, 95% CI 1.54-1.94, p<0.0001) with an adjHR of up to 3.42 at higher thresholds (95% CI 2.05-5.42, p<0.0001). Hazard increased monotonically with STBR. STBR >0.5 was independently associated with MACE (adjHR 1.51, 95% CI 1.11-2.05, p=0.008) and heart failure hospitalization (adjHR 1.31, 95% CI 1.02-1.67, p=0.03). The association was robust across all prespecified subgroups and sensitivity analyses, including continuous STBR and patients without renal insufficiency. IPA analysis identified significant associations with type 2 diabetes, chronic kidney disease, chronic ischaemic heart disease, heart failure, atrial fibrillation, liver disease, amyloidosis, and hypertension among binary traits, as well as with CRP, NT-proBNP, BUN, cholesterol (inverse), and hemoglobin (inverse) among continuous parameters. STBR increased monotonically across CKM stages in all sensitivity analyses (all p<0.0001). Conclusions: STBR derived from routine 99mTc-DPD bone scintigraphy in patients without cardiac uptake is an independent prognostic imaging biomarker associated with cumulative cardiovascular-kidney-metabolic burden. As an opportunistic measure from scans already acquired at scale, STBR could refine CKM risk stratification at no additional cost, radiation, or acquisition time.

Background Myocardial remodeling precedes symptomatic heart failure, which is important to detect early. We assessed feasibility and clinical correlates of a novel integrated assessment of myocardial remodeling in a large rural cohort in the Southeastern United States. Methods Echoes were obtained with AI assistance (Caption guidance) in 3100 adults in the NHLBI-funded RURAL cohort study. Of those, 1895 had quantifiable global longitudinal strain (GLS), left ventricular mass (LVM), and left atrial volume (LAV). LV-LA Health was based on a simple count of sex-specific abnormalities (0-3), indexed to body surface area (BSA) or height (Table 1). Relationships with demographics and risk factors were compared with Spearman correlation and Mantel-Haenszel tests, with moderate and severe results combined. Results Median (IQR) age was 49 (40-58). Impaired LV-LA Health is common even in a low PREVENT cardiovascular (CV) risk population (median 10-year risk 3.3%; 25th, 75th 1.2,7.2) with preserved ejection fraction (EF; 60%; 57,62). The prevalence of abnormalities differed greatly by indexing method: 18.2% with BSA (15.1% mild; 3.1% mod/severe) vs 51% with height (38.3% mild; 12.7% mod/severe) (Figure 1). LV-LA impairment increased with age, PREVENT CV risk score and cardiovascular risk factors (hypertension, diabetes, dyslipidemia, obesity); all p<0.001. Impairment was more common in Black vs White people (p<0.001) and differed by sex only with height indexation. Conclusions A novel LV-LA health composite of routinely acquired echocardiographic measures identifies substantial subclinical cardiac remodeling in a middle-aged rural community cohort, not detected by PREVENT score or ejection fraction. This is the first application of this framework in a large, unselected community sample. Indexation method affects prevalence, with BSA likely underestimating risk in adiposity-enriched populations. Findings suggest a high rural burden and longitudinal evaluation with future CV events is ongoing.

Background. Nascent findings suggest that people with attention-deficit/hyperactivity disorder (ADHD) experience higher rates of mortality. To date, study samples have been insufficiently well-characterized to examine the mechanisms via which this neurodevelopmental condition elevates mortality risk. Methods. We used data from the 2007 and 2011 waves of the US National Health Interview Survey, a general population-based cohort study comprising 52097 adults (28675 women) aged 18 years or older at baseline. ADHD diagnosis and an array of demographic, socioeconomic, lifestyle, and co-morbidity (somatic and psychiatric) covariates were self-reported. Findings. At baseline, compared with unaffected individuals, participants with ADHD were more likely to be socioeconomically disadvantaged, smoke cigarettes, consume alcohol, and report symptoms of psychological distress. A median 7.75 years of mortality surveillance (range: 7.25-12.25) gave rise to 6597 deaths from all-causes. After adjustment for age, sex, ethnicity, and survey year, ADHD was associated with a markedly elevated risk of death (hazard ratio [95% confidence interval]: 1.58 [1.20-2.09]). Statistical adjustment for socioeconomic circumstances (11% attenuation), physical co-morbidities (15%), and lifestyle factors (17%) had only a modest impact on the ADHD-death gradient, with the greatest explanatory power apparent for symptoms of depression and anxiety (58%). The magnitude of the association of ADHD with mortality was commensurate to that for several well-established risk factors such as poverty (1.66 [1.55-1.78]), hypertension (1.41 [1.32-1.51]), and diabetes (1.71 [1.59-1.85]) but somewhat lower than cigarette smoking (2.51 [2.29-2.76]) after controlling for age, sex, ethnicity, and survey year. Associations between ADHD and cause-specific mortality from cardiovascular disease, cancer, and chronic respiratory disease were inconclusive. Interpretation. In the present study, the influence of ADHD on total mortality appears to be largely embodied via a series of malleable characteristics, particularly mental illness. If confirmed elsewhere, these results raise the possibility that risk factor modification via standard pharmacological and behavioral interventions could help reduce rates of premature mortality in this patient group. Funding. This paper received no direct funding. GDB is supported by the UK Medical Research Council (MR/P023444/1) and the US National Institute on Aging (1R56AG052519-01, 1R01AG052519-01A1).

Background: Mass gathering events (MGEs) are associated with several public health challenges and may cause a strain on healthcare services. Literature findings on the impact of MGEs on emergency departments (EDs) are heterogeneous. Objectives: To examine shifts in ED attendance characteristics during a major sporting tournament, namely the UEFA European Football Championship 2024 held in Germany. Methods: We conducted a retrospective observational study using ED data from the Emergency Department Data Registry. We compared baseline ED attendance characteristics between the tournament and the reference period, defined as two weeks before and two weeks after the tournament, and between Germany game days and non-Germany game days. Hourly attendance patterns were analysed for all Germany games using a reference range. Results: We included data from 41 EDs, totalling 253,493 attendances during the study period. A 1.57% increase in attendance was observed during the tournament compared to the reference period, with baseline characteristics remaining similar. The median daily attendance within all EDs was slightly lower on Germany game days (4066) compared to non-Germany game days (4128). Modest changes were observed in the hourly attendance on Germany game days, most notable during the last Germany game where a decrease in attendance below the reference range extended over three hours. Conclusions: The observed shifts in ED attendance were minimal, suggesting that no major changes of public health relevance occurred in ED attendance during the tournament. We highlight the utility of using ED data for monitoring and for enhancing the understanding of the public health risks and challenges associated with MGEs.

Background: This study aimed to evaluate real-world adverse event (AE) signals of EV to provide evidence-based guidance for its safe clinical application. Methods: Data from the FDA Adverse Event Reporting System (FAERS) database from the period of 2019 Q1-2025 Q3 were analyzed. Disproportionality analysis algorithms, including the reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian confidence propagation neural network (BCPNN), and empirical Bayes geometric mean (EBGM), were utilized to mine safety signals.The time to onset (TTO) was evaluated using the Weibull distribution model. Results: Among 11,697,906 reports, 4,177 EV-treated patients experienced 14,511 AEs. The most common System Organ Classes (SOCs) were skin and subcutaneous tissue disorders (18.23%), general disorders and administration site conditions (13.17%).Multi-algorithm consensus identified 179 positive signals. Alongside known toxicities (rash, peripheral neuropathy, hyperglycemia), potential new signals emerged, including dysgeusia, atypical skin lesions, and myelosuppression. Median TTO was 14 days, with the Weibull {beta} of 0.736, confirming an "early failure" profile. Subgroup analysis revealed toxicity heterogeneity: patients aged [&ge;]65 and females exhibited stronger signals for fatal severe cutaneous adverse reactions, while patients aged < 65 and males showed higher susceptibility to neurological and metabolic toxicities. Conclusions: The real-world safety profile of EV confirms known toxicities, reveals new risks (e.g., dysgeusia), and shows toxicity concentrated in the first treatment cycle. Clinical practice requires proactive monitoring during the first two weeks using demographic-specific strategies: vigilance for fatal skin toxicity in elderly and female patients, and close follow-up of neurological and metabolic indicators in younger and male populations.

Electronic health record (EHR) prediction models often summarize longitudinal histories as static patient-level features, which may omit potentially informative event ordering. We developed a simplified spike-timing-dependent plasticity (STDP)-inspired framework that represents asynchronous EHR data as sparse, directional transition features. The approach encodes whether one clinical event precedes another within prespecified temporal windows, preserving event identity, directionality, and approximate timing while retaining feature-level interpretability. We evaluated this framework in two retrospective prediction tasks with different temporal scales: incident acute kidney injury (AKI) prediction in 17,351 MIMIC-IV ICU stays and early postoperative recurrence prediction in 713 CUMC patients with pancreatic ductal adenocarcinoma (PDAC). Models were compared with static burden features (demographics, comorbidities, raw lab measurements) and in addition with STDP transitional feature sets using patient-level cross-validation and rolling prediction horizons. In AKI, a calibrated STDP ensemble model showed higher discrimination than static burden alone at the 24-hour decision snapshot for AKI by 72 hours, with AUROC 0.838 versus 0.800, and at 48 hours for near-term AKI prediction, with AUROC 0.868 versus 0.827. In PDAC, STDP transition features modestly improved Day -30 preoperative recurrence prediction, with AUROC 0.611 versus 0.587 and AUPRC 0.323 versus 0.318 for static burden and showed similar performance at Day 0 (7 days before recorded surgery date), with AUROC 0.681 and AUPRC 0.363. Decision-curve and feature analyses suggested that selected temporal transitions were clinically interpretable across renal, inflammatory, hepatobiliary, hematologic, glycemic, and nutritional trajectories. These findings suggest that STDP-inspired transition features may provide a practical, interpretable way to incorporate temporal ordering into EHR-based risk prediction across both acute and longitudinal settings

Background Chronic pain is common in adults aged 85 years and older (85+) and is associated with detrimental outcomes. Chronic pain guidelines advise first line management with non-pharmacological measures; paracetamol and non-steroidal anti-inflammatory drugs are the preferred analgesics. Challenges in accessing non-pharmacological therapies for adults aged 85+, and the presence of multimorbidity and polypharmacy, mean that opioid medication is often prescribed for chronic pain despite the potential for opioid-related adverse effects and guidance identifying long-term opioids for chronic pain as a potentially inappropriate prescription. Aim This study aims to explore patient, caregiver, and healthcare professional perspectives on the prescription of opioid medications for pain management for chronic pain in adults aged 85+ to support development of resources for optimising opioid prescribing. Design and Setting In this qualitative study, participants were recruited through primary care, in the community or in care home settings. Method 36 semi-structured interviews were conducted with care home residents and community dwellers aged 85+ (n=12), caregivers (informal and care home staff) (n=12), and healthcare professionals (n=12). Interviews were transcribed and analysed using reflexive thematic analysis. Results Four themes were developed: contextual complexity, satellite influences, balancing act, and pragmatic prescribing. Using opioids in adults aged 85+ is a balancing act to support patients best possible quality of life within their unique circumstances whilst using the pain management tools available. Conclusion Opioids continue to have an important role in pain management in adults aged 85+ largely due to paucity of alternatives and the drive to support quality of life.