Nature Chemistry

Investigating the conformational dynamics of intrinsically disordered proteins (IDPs) is essential to understanding how their structural heterogeneity underlies function and how their dysregulation contributes to diseases. Here, we utilized an MspA nanopore-based approach for studying the conformational dynamics and interactions of IDPs at the single-molecule level. The platform was demonstrated using the intrinsically disordered transactivation domain of tumor suppressor p53 (p53-TAD), one of the important proteins in cancer biology. We showed that MspA can stably capture p53-TAD and resolve up to six distinct current states with frequent interconversions, revealing a rich conformational landscape. The nanopore also detected the effect of a cancer-associated double mutational variant, N29K/N30D. Combining experiments with steered molecular dynamics simulations, we showed that the mutant sampled compact conformational states more frequently than wild type, consistent with previous NMR studies. Importantly, the MspA platform enabled direct monitoring of E3 ligase MDM2 binding to p53-TAD and resolved how this interaction is inhibited by anti-cancer compound epigallocatechin gallate (EGCG). Notably, EGCG stabilizes one of the six states sampled by p53-TAD, providing a mechanistic explanation for its inhibitory effect. Together, these findings demonstrate the promise of the nanopore platform for label-free monitoring of IDP conformational dynamics, modulation, binding and inhibition at single-molecule resolution.

The rotary motor F1-ATPase has been extensively studied as a model molecular machine, yet rational engineering of its catalytic activity remains challenging because ATP hydrolysis is regulated by long-range intersubunit allostery and large conformational transitions. Here, we developed a homolog-guided engineering strategy to increase the maximum rotation rate of the thermophilic Bacillus PS3 F1-ATPase (TF1). Candidate mutation sites were first identified by comparing TF1 with the homologous enzymes bovine mitochondrial F1 (bMF1) and Paracoccus denitrificans F1 (PdF1), both of which exhibit higher maximum rotation rates than TF1. Systematic exploration of these sites identified four activity-enhancing hotspots, followed by focused hotspot exploration and machine-learning-assisted prioritization of combinatorial mutants. The best mutant, TF1({beta}Y313L/{beta}E332S), exhibited a 1.8-fold higher maximum rotation rate than TF1(WT) while retaining its functional thermostability. Interestingly, activity-enhancing substitutions were not limited to the residues conserved in both bMF1 and PdF1, indicating that the bMF1-PdF1 consensus substitutions effectively identify activity-enhancing hotspots rather than uniquely defining the optimal amino acid. Machine-learning-assisted exploration efficiently prioritized highly active mutants, although the predictive performance was limited by the relatively small training dataset and epistatic interactions among mutations. Kinetic and structural comparisons further provided mechanistic insights into the enhanced catalytic activity of the engineered mutant. Together, these results establish a practical strategy for engineering complex molecular motors by combining homolog-guided hotspot identification with focused hotspot exploration.

Accurate determination of kinase inhibitor binding modes could provide essential information for understanding resistance mechanisms and accelerating drug discovery. While conventional structural methods such as X-ray crystallography, cryo-EM and NMR provide high-resolution information but are low-throughput and capture largely static snapshots of dynamic protein-ligand interactions Here, we introduce a single-molecule nanopore tweezer platform that functionally subtypes ATP-competitive Abl kinase inhibitors by resolving distinct ionic current signatures of Abl-inhibitor complexes. This approach distinguishes Type I, Type IIA, and Type IIB inhibitors without structural determination. We further show how clinically relevant Abl variants (T315I and E255V) reshape inhibitor engagement and binding modes. By combining baseline probability features with wavelet-based time-frequency descriptors, ensemble machine-learning models achieved 97.5% classification accuracy across seven kinase inhibitor binding modes at sub-angstrom resolution and enabled deconvolution of mixed-inhibitor samples at nanomolar concentrations. These results establish nanopore tweezers as a label-free, super-resolution platform for profiling kinase conformational states and inhibitor binding modes, complementing structural approaches and supporting precision oncology.

Reflectin proteins drive dynamic structural coloration in cephalopods by organizing into dense intracellular lamellar structures that dictate local refractive index. While reconstituted reflectins readily undergo liquid-liquid phase separation in vitro, these assemblies frequently undergo dynamic arrest, vitrifying into non-dynamic condensates. Here, we investigate the primary sequence features, post-translational modifications, and heterotypic interactions that regulate the material properties of reflectin condensates within the crowded cellular environment of mammalian HeLa cells. Using confocal microscopy and fluorescence recovery after photobleaching (FRAP), we demonstrate that canonical block copolymeric A-type reflectins readily form dynamically arrested condensates, with the linker blocks primarily responsible for the observed arrest. In contrast, non-canonical B/C reflectin variants exhibit significantly greater fluidity and rapid recovery kinetics. We show that phosphomimetic substitutions progressively fluidize some reflectin condensates. Lastly, we find that heterotypic condensates composed of canonical and non-canonical reflectins in combinations associated with reversible iridescence in squid substantially enhance canonical mobility. Our findings establish a biophysical framework in which phosphorylation and heterotypic mixing cooperatively suppress dynamic arrest, enabling the reversible material transitions required for active cephalopod camouflage and communication.

Obtaining sufficient amounts of pure protein for downstream applications such as native mass spectrometry (nMS) is often challenging, especially when expression yields are low or proteins are unstable. In these cases, the commonly required buffer-exchange step is a major bottleneck, as it often leads to substantial protein loss and compromises biophysical characterization. These challenges are exacerbated in insect or eukaryotic expression systems, where protein yields are typically lower than in bacteria, making protein loss during purification particularly detrimental. Standard lysis and purification buffers contain non-volatile components such as Tris, phosphate, HEPES and sodium chloride, which form adducts during electrospray ionization (ESI) interfering with the signal and therefore must be re-moved prior to nMS. To address protein loss associated with this mandatory buffer-exchange, we evaluated an affinity-purification workflow, in which non-volatile salts are excluded throughout purification and proteins are directly eluted into nMS-compatible ammonium acetate-based buffers. This approach eliminates the need for a separate buffer exchange step and enables rapid nMS analysis immediately after affinity purification. We show that common eluents used in His- and Strep- based affinity purification, such as imidazole, biotin, and desthiobiotin, are well tolerated at relevant concentrations, allowing acquisition of high-quality spectra suitable for determining protein stoichiometry and for monitoring enzymatic or assembly processes. Together, this fast-track affinity workflow increases protein recovery, shortens sample preparation and complements online exchange protocols, which are less suited for monitoring processes. It hence expands the applicability of nMS to proteins and protein complexes that are difficult to obtain in sufficient quantity using conventional purification and buffer exchange strategies.

Nanodiscs and bicelles are widely used as membrane mimetics for structural studies of membrane-associated systems. Studies have reported that their magnetic alignment behavior and phase stability are highly sensitive to composition and temperature. In this study, we systematically investigate the effects of cholesterol on bicelle formation and magnetic alignment in DMPC + 0.2 glycyrrhizic acid (GA) systems using a combined 31P and 14N solid-state NMR experimental and simulation-based approach. Temperature dependent 31P NMR spectra reveal a clear transition from vesicle dominant to aligned bicelles/nanodsics phase, while 1N quadrupolar splitting and lineshape analysis provides quantitative insights into heterogeneous lipid bilayer populations, distinguishing large aligned nanodiscs (B(L)), small nanodiscs (B(S)), and isotropic/random components (B(R)). A strong correlation is observed between the 31P derived bicelle fraction and the 14N B(L) population, confirming that macroscopic alignment in the presence of an external magnetic field directly reflects the growth of large, well-ordered nanodiscs. Cholesterol is found to play a critical dual role by modulating membrane order and curvature. At low cholesterol concentration (0 to 5 mole percent), nanodiscs alignment occurs gradually with increasing temperature, while at higher cholesterol concentration (15 to 25 mole percent), the alignment is delayed and accompanied by broader spectral features, indicating structural heterogeneity. Notably, 10 mole percent cholesterol consistently provides the optimal balance, enabling efficient temperature dependent conversion to aligned bicelles while maintaining high B(L) populations (about 70-80 percentage) and minimal isotropic fractions. In contrast, higher cholesterol maintains significant B(S) and B(R) populations, even at elevated temperature. The 14N quadrupolar coupling (Cq is approximately 8.5 to 9.2 kHz for aligned nanodiscs) remains nearly invariant across compositions, showing that cholesterol does not change local headgroup dynamics but instead redistributes lipid populations. These findings establish a combined 31P and 14N solid -state NMR approach provides a valuable platform for quantitatively correlating membrane structure, dynamics, and alignment, offering practical guidelines for optimizing bicelle systems for high resolution solid-state NMR studies of membrane associated biomolecules.

Increased activity of leucine-rich repeat kinase 2 (LRRK2) confers Parkinson's disease risk. LRRK2 dynamically localizes to lysosomal membranes in response to various stresses, yet the mechanisms by which distinct lysosomal perturbations are communicated to LRRK2 remain unclear. Here, we show that inhibition of the lysosomal lipid kinase PIKfyve promotes LRRK2 recruitment and signaling through a pathway that requires the lysosomal chloride/proton antiporter ClC-7. ClC-7 in turn controls the accumulation of multiple Rab GTPases on lysosomes. LRRK2 signaling under these conditions requires its established Rab-binding surfaces, with Rab12 contributing significantly to this response. This pathway operates independently of CASM. In contrast, lysosomal stresses that induce CASM require both Rab-binding sites on LRRK2 and GABARAP for robust LRRK2 signaling. These findings identify ClC-7-dependent lysosomal remodeling and Rab accumulation as key features linking PIKfyve inhibition to LRRK2 signaling and reveal that distinct lysosomal stresses engage different combinations of Rab and GABARAP inputs to activate LRRK2.

Biomolecular condensates formed by intrinsically disordered proteins require molecular models that accurately describe proteins in both dilute solution and condensed phases. Explicit-solvent coarse-grained models offer an attractive balance between chemical resolution and computational efficiency. Yet, it remains unclear whether improving dilute-state properties is sufficient to obtain an accurate description of condensates. Here, we address this question by introducing minimal modifications to the Martini 3 force field that combine recent advances in bonded interactions with refined protein-water interactions and strengthened glycine self-interactions, while preserving the underlying chemical transferability of the model. The resulting model substantially improves the description of single-chain conformations across a diverse benchmark of disordered proteins. We then investigate phase separation of the well-characterized low-complexity domain of heterogeneous nuclear ribonucleoprotein A1 and its sequence variants. The model reproduces several key physicochemical properties of biomolecular condensates, including chain expansion in the dense phase, sequence-dependent intermolecular contacts, protein diffusion and its relation to single-chain dimensions, and hydration, while revealing quantitative limitations in condensate density, phase equilibria, and ion partitioning. Our results show that improving dilute-state behaviour translates into a better description of condensed-phase properties, including condensate density, but is not sufficient to quantitatively reproduce the equilibrium between the dilute and dense phases.

Next-generation sequencing (NGS) of the prokaryotic 16S rRNA gene revolutionized gut microbiome research two decades ago. However, short read lengths remain an inherent limitation of platforms such as the widely used Illumina platforms (2 x 150-300 bp). Recent advances in Oxford Nanopore Technologies (ONT) flow cell chemistry (R10.4.1) have substantially improved sequencing accuracy. Combined with a custom multiple-primer strategy that comprehensively targets 16S rRNA gene variants to generate near-full-length amplicons, this approach enables read-by-read taxonomic classification, a feature not feasible with short-read sequencing platforms. Although our multiple-primer strategy could enable parallel sequencing of more than 18,000 samples (192 x 96), current flow cell capacity offers sufficient sequencing depth for approximately 1,000-1,500 samples. To validate the scalability and our per-read classification pipeline, we show that more than a thousand human fecal microbiome samples spiked with two bacterial strains (Imtechella halotolerans and Allobacillus halotolerans), not otherwise present in human fecal samples, can be successfully sequenced on a single flow cell, achieving a per-molecule error rate sufficient for direct per-read classification and at an adequate read depth for downstream analysis. This level of scalability significantly reduces per-sample costs, making the approach more accessible to a broader research community. To embrace these advancements, we have developed RubyRed, a pipeline that processes raw sequencing data and assigns taxonomic classifications on a per-read basis. Using spike-in references (I. halotolerans and A. halotolerans), we demonstrate high mean single-read sequencing accuracy (99% and 98.9%, respectively), with the majority of reads exceeding the canonical threshold required for species-level taxonomic classification based on the 16S rRNA gene.

Microorganisms across all domains of life engage in molecular conflict, deploying toxins to inhibit competitors or respond to biological threats. Among these, ribonuclease toxins are particularly widespread and diverse. A substantial fraction is associated with the BECR fold, a compact /{beta} architecture that supports RNase activity despite extensive divergence. Although several canonical members are well characterized, many BECR-fold proteins remain difficult to identify because of low sequence similarity, variation in catalytic residues, and structural elaborations that obscure evolutionary relationships. The growing availability of high-confidence protein structure predictions provides an opportunity to reassess this deeply divergent protein landscape. Here, we integrate iterative profile-HMM searches, profile-similarity networks, structural analyses, active-site mapping, and genomic context to examine BECR proteins across the tree of life. Our analysis resolves an expanded BECR-fold landscape comprising canonical BECR and BECR-like superfamilies, refines the organization of canonical BECR proteins and identifies previously unrecognized families. We further validate BECR-Tox2 as a toxin neutralized by a cognate immunity protein and show that its homologs occur in both Menshen-like anti-phage systems and polymorphic toxin loci. Together, these findings expand and clarify the BECR-fold landscape and provide a framework for identifying and interpreting highly divergent proteins of this fold.

Background: Higher Body Mass Index (BMI) is an established risk factor of sleep disturbance. It is not known if the effect is homogeneous across the lifecourse or if there is a particular time point in life that might be best to target. Methods: Two-sample Mendelian randomization (MR) was used to investigated the effect of childhood adiposity (adjusting on adulthood adiposity and obstructive sleep apnea (OSA)) on insomnia, morning chronotype, sleep duration, daytime sleepiness and daytime napping. Similarly, total, and direct effect of adulthood adiposity on these outcomes was explored. We used summary statistics from a genome-wide association study (GWAS) of UK Biobank for childhood and adulthood adiposity (n=453,169) and large-scale consortia of OSA (Million Veteran Program) (n=410,268), insomnia, and chronotype (23andMe) (n=1,978,022 and n=248,1000, respectively). Results: Two-sample univariable MR analysis provided no evidence of an effect of genetically predicted childhood adiposity on later life insomnia (Odds ratio (OR)= 0.94, 95% Confidence interval (CI)= 0.87, 1.03). Whereas, multivariable MR (adjusted for adulthood adiposity) analysis provide strong evidence of direct protective effect of genetically predicted childhood adiposity on later life insomnia (OR= 0.70, CI= 0.64, 0.77). Further, both in univariable and multivariable MR, a strong positive effect of increased childhood body size on morning chronotype was observed (OR= 1.16, CI= 1.01, 1.33 and OR= 1.36, CI= 1.15, 1.62, respectively) after accounting for adulthood body size. In both analysis the estimate did not change considerably after aditionally adjusting for OSA. However, childhood and adulthood adiposity found to be associated with OSA and OSA with insomnia. In both univariable and multivariable analysis, increased body size in adulthood increased the risk of having insomnia and a morning chronotype. Conclusions: The findings suggest that higher body size in childhood is not a risk factor for later life insomnia, whereas higher body size in adulthood was. Further, if healthy body size is maintained in adulthood, high childhood adiposity may decrease the risk of insomnia and increase the risk of being a morning person in later life. Keywords: childhood, adulthood, obesity, insomnia, morning chronotype, medelian randomization

Background: Aerobic exercise is recommended during stroke rehabilitation to improve cardiorespiratory fitness and support recovery; however, participation rates remain low. While institutional and system-level barriers have been widely examined, less is known about how individual patient factors influence engagement in aerobic exercise during rehabilitation. Objectives: We aimed to determine whether depressive symptoms, apathy, self-efficacy and outcome expectations for exercise, perceived barriers, or past exercise history were associated with aerobic exercise participation in stroke rehabilitation. Methods: In this prospective cohort sub-study, adults admitted to in- or out-patient stroke rehabilitation at three urban hospitals completed validated questionnaires assessing depressive symptoms, apathy, exercise self-efficacy, outcome expectations for exercise, perceived barriers to being active, and premorbid exercise history. Participants were separated into two groups for analysis: those who completed aerobic exercise during rehabilitation and those who did not. Equivalence testing and between-group comparisons were performed. Results: Sixty-two participants were enrolled; 16 participated in aerobic exercise and 46 did not. Groups were not equivalent on any individual-level factors. Compared to non-participants, those who performed aerobic exercise had significantly higher depressive symptom scores (p=0.0025) and lower self-efficacy for exercise (p=0.0087). Non-participants demonstrated significantly higher apathy (p=0.0007). No significant differences were found for outcome expectations, perceived barriers, or exercise history. Conclusion: Depressive symptoms and lower self-efficacy did not impede aerobic exercise participation during rehabilitation. Increased apathy, however, was associated with non-participation. Findings highlight the need for individually tailored aerobic exercise prescriptions that consider motivational and affective factors to optimize engagement during stroke rehabilitation.

Background: In Tanzania, over 10,000 women aged 15-44 are diagnosed with cervical cancer annually, and more than 6525 die. The majority are diagnosed at an advanced stage, which contributes to delays in treatment enrollment and illness complications. Multiple factors can affect womens willingness and ability to access cervical pre-cancer screening. Purpose: To explore the barriers and facilitators to attending cervical pre-cancer screening among women living in a resource-constrained area of Southern Tanzania Methods: A qualitative study of 17 focus group discussions and 12 in-depth interviews was conducted from December 2023 to July 2024. Data collection took place in the community and health centers of a town and the surrounding rural areas in Kilombero district. The study used purposive sampling to recruit 112 women and 23 men aged 18- 50+ years. Results: Fear of death emerged as a central theme in the data, acting as both a barrier to and a facilitator of womens screening behavior. Women linked death with the screening procedure, receiving results and undergoing treatment. Participants mistrusted the speculum itself and linked it to pain, vaginal infection, and infertility. Conversely, fear of physical and social death motivated other women to attend the screening to learn about their health and prevent the consequences of a positive diagnosis. Public trust in the healthcare system and the role of health information sources were also identified as influencing women's decisions to undergo or not undergo screening. Conclusion: Our findings showed that cervical cancer screening uptake is influenced by fear of death and other co-factors. To improve early cervical cancer screening, programs and policy interventions are needed to raise awareness of the disease while also addressing womens specific concerns. Also, strengthening structural dimensions such as the availability of the healthcare workforce, healthcare facilities, and ensuring equitable service availability are essential to reducing cervical cancer complications and avoidable mortality.

Importance: Maternal vaccination and long-acting monoclonal antibodies are now available in the U.S. to prevent RSV. Long-acting monoclonal antibody administration in the U.S. commonly occurs after hospital discharge in outpatient settings, leaving some infants unprotected early in life when severe RSV risk is highest. Comparative effectiveness between the two interventions and whether delays affect effectiveness estimates have not been quantified. Objective: To evaluate the effectiveness of infant long-acting monoclonal antibody strategies and a maternal vaccination strategy, each compared to no intervention, and the comparative effectiveness of intervention strategies when accounting for real-world delays in monoclonal antibody receipt. Design: Cohort study using target trial emulation to compare four strategies for prevention of RSV-related outcomes. Setting: The U.S. between 2023 and 2025 using a nationwide database of employer-sponsored commercial insurance claims. Participants: 120,586 commercially insured mother-infants, whose infants were born in the U.S. during the 2023-2024 or 2024-2025 RSV season. Infants who could not be paired with their mother's record, did not enroll in commercial insurance within 75 days from birth, received palivizumab, and had an implausible birth date were excluded. Interventions: Comparison of four RSV prevention strategies: (i) maternal RSVpreF; (ii) long-acting monoclonal antibody given within the first week of life (mAb as intended); (iii) long-acting monoclonal antibody given within a six-month grace period from birth (mAb within grace period); and (iv) a control. Main outcomes and measures: Effectiveness against first RSV-associated hospitalization and medically-attended RSV illness was summarized using adjusted hazard ratios (aHR) and estimated using an inverse propensity weighting approach, with weights accounting for maternal age, maternal comorbidities affecting pregnancy, obstetric and newborn complications, season, region, and birth timing relative to October 1. A weighted Kaplan Meier estimator was used to estimate strategy-specific cumulative incidence of RSV outcomes over time. Results: In the first five weeks of life, the mAb within grace period strategy doubled the hazard of RSV hospitalization (aHR: 2.0 [95% CI: 1.0-4.9]) and increased the hazard of medically-attended RSV (aHR: 1.6 [95% CI: 1.0-2.7]) compared to the maternal RSVpreF strategy. The hazard for RSV hospitalization was similar for the mAb as intended strategy compared to the maternal RSVpreF strategy (aHR = 0.9 [95% CI: 0.3-1.9]). Conclusions and relevance: RSVpreF and monoclonal antibodies were similarly effective when monoclonal antibodies were administered close to birth, but when accounting for real-world delays in monoclonal antibody receipt, the maternal RSVpreF strategy was more effective than the mAb within grace period strategy.

Background Rural-urban disparities in SARS-CoV-2 infection epidemiology remain poorly quantified and understood in Zambia despite differences in healthcare access, services and preventive interventions. This study examined the geographical distribution and associated factors of SARS-CoV-2 cases across selected rural and urban districts of Zambia. Methods A convergent mixed-methods study comprised of quantitative survey and qualitative interviews was conducted in; Ndola (Urban), Kafue (Peri-urban) and Lufwanyama (Rural). The proximate determinant framework guided variable selection and interpretation. Quantitative combined (Hospital-surveillance data with community survey), while qualitative included In-depth interviews. Participants were sampled using multistage sampling technique. Quantitative data were analysed using STATA version 17, while qualitative data were analysed thematically. Findings were integrated through triangulation. Results A total of 528 participants were included, with a median age 31 years (15-71). Overall SARS-CoV-2 positivity was 12.6%, varying across rural (16.5%), peri-urban (14.9%), and urban (9.9%) settings, though residence was not associated with infection (P<0.132). Participants aged [&ge;]49 years had significantly higher odds of infection (aOR=8.78; 95% CI:1.15-66.99), whereas secondary education (aOR=0.37; 95% CI:0.16-0.86) and hospital-based testing (aOR=0.37; 95% CI:0.15-0.92) were associated with lower odds of infection. Vaccine uptake was highest in urban areas but was not independently associated with infection. Qualitative findings revealed marked rural-urban differences in perceived susceptibility, testing access, vaccine decision-making, and adherence to preventive measures, explaining several quantitative observations. Conclusion SARS-CoV-2 infection across rural and urban settings in Zambia was influenced by demographic, behavioral, and health-system factors rather than geographic residence alone. These findings highlight the need for context-specific prevention strategies, equitable access to testing, strengthened community surveillance, and targeted risk communication to improve preparedness and response for future respiratory disease outbreaks.

This study aimed to quantify the longitudinal tracking and cross-sectional construct validity of a single-item questionnaire measuring recreational physical activity frequency (RPAF) in the Womens Healthy Ageing Project. At baseline, 474 participants aged 45-55 reported RPAF from 1993 to 2014. Longitudinal tracking of the RPAF item was assessed as a consecutive-wave and baseline-referenced measure using linear weighted kappa (LWK), Spearman correlations, exact agreement and within-one-category agreement. Construct validity in the form of convergent and known-group validity was assessed using the International Physical Activity Questionnaire (IPAQ) leisure activity domains, Short Form 36 physical function (SF-36-PF) subscale, Timed Up and Go (TUG), hand grip strength (HGS) and waist-to-height ratio (WHtR). 474 participants provided baseline RPAF data. Pairwise longitudinal samples ranged from 176 to 459 across the study. Consecutive-wave LWK ranged from 0.38 to 0.49, and Spearman correlations ranged from 0.44 to 0.57. Exact and within-category agreement ranged from 41.4%-50.8% and 72.0%-79.0%. Baseline-referenced LWK ranged from 0.22 to 0.47, with Spearman correlations of 0.29 to 0.56. RPAF correlated with total IPAQ leisure score (rs = 0.60), IPAQ walking score (rs = 0.58), SF-36-PF (rs = 0.33) and TUG score (rs = -0.25). No significant correlation was identified between RPAF, HGS or WhTR. RPAF discriminated known groups for WHO guideline-sufficient activity, SF-36-PF, and TUG fall risk. The RPAF item demonstrated fair-to-moderate agreement in consecutive waves, with weaker baseline-referenced tracking. Cross-sectional validity was highest with total IPAQ leisure activity. The item may provide a pragmatic measure for RPAF in womens cohort studies.

Abstract Preventable neonatal deaths remain a major public health problem in Zimbabwe, where near-universal antenatal and facility-delivery coverage coexist with a rising neonatal mortality rate. This study evaluated whether institutionalising three core "vital signs" of the community health system (a trained village health worker (VHW) workforce, functional community governance structures, and modified women's and men's participatory learning and action groups) reduces preventable neonatal deaths in Mashonaland West Province. An embedded QUAN (qual) mixed-methods design was used, with a two-arm, parallel-group cluster-randomised controlled trial as the dominant strand. Fifty-two ward-level clusters were randomised 1:1 to the institutionalised community health system package or to standard Ministry of Health and Child Care community services, and 984 pregnant women were enrolled between 1 September 2020 and 31 October 2021, with each mother-infant pair followed to 28 days after delivery, yielding 973 mother-infant pairs for intention-to-treat analysis. The primary outcome was neonatal death within 28 days of life, expressed per 1,000 live births. The primary analysis used a three-level mixed-effects log-binomial regression model with cluster and community-health-worker random intercepts, adjusted for pre-specified covariates. Supervised machine-learning classifiers with leave-one-cluster-out cross-validation, Cox proportional-hazards regression, and multilevel logistic models were fitted as supplementary analyses. An embedded longitudinal process evaluation used key informant interviews and focus group discussions, which were analysed thematically and integrated with the quantitative findings. The neonatal mortality rate was 44.8 per 1,000 live births in the intervention arm versus 110.1 per 1,000 in the control arm. The adjusted risk ratio for neonatal death was 0.43 (95% CI 0.26-0.70; p < 0.001), a 57% relative reduction, with a number needed to treat of 16 mother-infant pairs (95% CI 11-29). Low birthweight (<2,500 g), birth interval under two years, and low community women's literacy were the strongest risk factors, while trained VHWs, functional community governance, early antenatal care, and sustained participatory group attendance were independently protective. The women's and men's groups were protective in a dose-dependent manner, becoming significant at four or more cycles (about 14 meetings) (adjusted odds ratio 0.71; 95% CI 0.60-0.85; p = 0.001). A random forest classifier discriminated against neonatal deaths with a cross-validated area under the curve of 0.842 and a sensitivity of 0.912. Qualitative findings converged with the trial results, identifying male engagement, earlier care-seeking, danger-sign literacy, social-network activation, and community death audits as the behavioural and structural mechanisms of change. Institutionalising the community health system package (trained VHWs, functional governance, early antenatal engagement, and sustained participatory groups) was associated with a substantial reduction in preventable neonatal deaths. The findings suggest that in high-coverage, high-mortality settings, the binding constraint is structural rather than clinical, and that scaling functional community governance and workforce infrastructure in the most disadvantaged communities may accelerate progress toward neonatal survival targets. The principal limitations are a one-year follow-up period, the rarity of neonatal death, and concurrent national programming that only partially reached the control clusters. Trial registration: Pan African Clinical Trials Registry, PACTR202607591142118 (https://pactr.samrc.ac.za/TrialDisplay.aspx?TrialID=PACTR202607591142118); registered retrospectively on 7 July 2026.

Biological aging occurs heterogeneously across individuals and organs. However, current measures of biological age incompletely capture organ-specific differences in health and disease risk. Because chest CT visualizes multiple thoracic organs, it offers an opportunity to quantify structural aging across organ systems. Here, we developed MOSAIC-Age, a framework characterizing eight organ-specific aging clocks on chest CT. The clocks were developed and validated using 9,971 CT scans from CT-RATE and MIDRC, and subsequently locked and applied to two independent prospective cohorts with 35,293 participants from the National Lung Screening Trial and Genetic Epidemiology of COPD study. CT-derived biological age gaps (BAGs) were examined in relation to lifestyle and socioeconomic factors, prevalent comorbidities, incident chronic diseases, and all-cause and cause-specific mortality. Higher BAGs, indicating organs that appeared older on CT than expected for their chronological age, were broadly associated with adverse health characteristics, chronic disease burden, and increased mortality risk. Multiple disease outcomes were associated with aging across several organs, whereas in multivariable analyses including all eight organ-specific BAGs, the remaining associations were more organ specific. A greater number of markedly older-appearing organs and a faster pace of aging were each associated with higher mortality. Together, these findings demonstrate that routine chest CT captures both shared and organ-specific patterns of biological aging and establish CT-derived organ aging as a quantitative imaging biomarker for assessing multi-organ health and long-term disease risk.

Stroke remains a leading cause of mortality and long-term disability worldwide, yet rapid diagnosis is often limited by the shortage of trained radiologists, particularly in resource-constrained settings. Automated analysis of CT imaging offers a potential solution, but existing methods often struggle to achieve clinically generalisable performance while jointly addressing multiple diagnostic tasks. Here we present the Intelligent Integrated Stroke Diagnosis System IISDS, an end-to-end deep learning framework built upon StrokeGNN, a graph-based architecture that integrates 3D contextual feature extraction with U-Net-based 2D lesion segmentation to enable comprehensive stroke analysis from non-contrast CT scans. IISDS performs stroke subtype classification, lesion segmentation and lesion volume estimation within a unified pipeline. To develop and validate the system, we collected and curated BGD-ISD through a collaboration between AI researchers, neurologists, radiologists and clinicians, resulting in a large multi-centre dataset comprising 1,507 CT scans from 597 stroke cases acquired across six hospitals and medical centres in Bangladesh. Across BGD-ISD and multiple publicly available datasets, IISDS achieves state-of-the-art performance on all tasks, improving segmentation accuracy by [&ge;]0.011 Dice score, reducing lesion volume estimation error by [&ge;]0.3 average symmetric surface distance (ASSD), and increasing classification performance by [&ge;]0.018 area under the receiver operating characteristic curve (AUC) compared with existing approaches. These results demonstrate the potential of graph-based deep learning to enable clinically generalisable, automated and scalable stroke diagnosis from CT imaging, supporting rapid clinical decision-making, particularly in healthcare environments with limited access to expert radiological interpretation.

Background and Objectives: Recurrence following burr-hole drainage of chronic subdural haematoma (cSDH) occurs in 10-25% of cases, sustained by neovascularisation of the subdural neomembrane supplied by the middle meningeal artery (MMA). MMA embolisation reduces recurrence; whether incidental burr-hole intersection of MMA branches during drainage confers similar benefit is unknown. Methods: We performed a multicentre retrospective cohort study of consecutive adults undergoing burr-hole drainage for cSDH at two UK tertiary neurosurgical centres. Postoperative thin-slice CT was used to classify burr-hole intersection of the underlying MMA groove (no hit, distal-branch hit or main-branch hit) and measure perpendicular burr-hole-to-MMA-groove distance. Co-primary outcomes were radiological recurrence and recurrence requiring intervention. Patient-clustered multivariable logistic regression adjusted for prespecified clinical covariates and treating site. Results: 227 patients (284 operated hemispheres) were included. Radiological recurrence decreased from 34.4% with no branch hit to 22.9% with main-branch intersection, with the gradient confined predominantly to unilateral cSDH. Main-branch intersection was associated with lower adjusted odds of radiological recurrence in unilateral cSDH (adjusted OR 0.30, 95% CI 0.11- 0.81; P = .018), with a similar but non-significant association in the overall cohort (adjusted OR 0.53, 95% CI 0.26-1.07; P = .075). Burr-hole-to-MMA-groove distance demonstrated a more consistent association: in the overall cohort, each 5-mm increase independently increased the odds of radiological recurrence (adjusted OR 1.38, 95% CI 1.04-1.82; P = .025). In unilateral cSDH, each 5-mm increase was independently associated with both radiological recurrence (adjusted OR 1.45, 95% CI 1.03-2.04; P = .034) and recurrence requiring intervention (adjusted OR 1.52, 95% CI 1.05-2.20; P = .027). Conclusion: Main-branch intersection of the middle meningeal artery during routine burr-hole surgery is associated with lower recurrence of unilateral cSDH, while the accompanying burr-hole-to-MMA-groove distance gradient provides biologically plausible support for a dose-response relationship. Together, these findings provide mechanistic rationale for prospective evaluation of intentional neuronavigation-guided MMA targeting (BURR-MMA; NCT07549893).