APL Bioengineering

Tissue mechanics influence diverse biological processes, yet directly linking stiffness measurements to spatially resolved molecular states in intact tissues remains challenging. Here we developed a paired-surface spatial mechanomics approach to map Young's modulus by nanoindentation on a fresh tissue surface and co-register the stiffness grid with 10x Genomics Visium HD spatial transcriptome bins from the immediately adjacent, parallel surface. Applied to the mouse ovary, which has spatially distinct compartments and undergoes extracellular matrix remodeling with cycle and age, the workflow generated >2,900 matched measurements across 21 regions of interest. Nanoindentation at 50-m grid spacing enabled millimeter-scale stiffness maps while balancing acquisition time in fresh tissues, with ~92 4-m transcriptome bins assigned to each stiffness value. Global and compartment-specific analyses associated stiffer regions with lower elastic fiber programs and higher inflammatory signaling, with age-dependent differences. This correlative strategy integrates experimentally measured mechanics with spatial omics in fresh tissues.

Neurodegenerative diseases are increasingly associated with vascular dysfunction beyond progressive neuronal degeneration, yet how vascular pathology contributes to disease progression remains poorly understood, largely due to the lack of a neurodegenerative disease model capable of capturing neuronal pathology alongside associated vascular dysfunction. Here, we developed a microengineered 3D vascularized brain tissue model that integrates neurospheroids with a self-assembled, perfusable vascular network to recapitulate key features of the neurovascular interface. Using this model, we investigated the vascular contribution to Parkinson's disease pathology by introducing -synuclein preformed fibrils into the engineered vasculature. Intravascular -syn fibril exposure induced endothelial barrier disruption, vascular leakage, inflammation, and vascular regression. Notably, this vascular insult was accompanied by intraneuronal -synuclein aggregation within neurospheroids, suggesting that vascular dysfunction may facilitate the exposure of neural tissue to pathogenic -synuclein. Our neurodegenerative disease modeling approach establishes a versatile and tractable platform for investigating vascular contributions to neurodegenerative disease progression.

Decellularized extracellular matrices (ECMs) are widely used in regenerative medicine, yet current evaluation criteria prioritize cellular removal rather than preservation of the ECM characteristics that govern tissue behavior. Here, we demonstrate that efficient decellularization is achieved across a broad range of chemical conditions, whereas preservation of structurally and biologically relevant ECM components is confined to narrow, tissue-specific windows defined by coupled detergent interactions. Quantitative proteomics revealed that intrinsic ECM composition is strongly associated with tissue-specific susceptibility to decellularization-induced damage and provided molecular context for the distinct preservation responses between tissues. Optimized matrices retained major structural ECM components and supported tissue-specific cellular organization and cell-mediated mechanical reinforcement following cellular repopulation despite uniformly low residual DNA across protocols. Together, these findings support a shift in decellularization quality assessment from DNA-based evaluation toward preservation of biologically relevant ECM and establish a composition-driven strategy for the rational design of regenerative biomaterials with tissue-relevant biological and mechanical properties.

The immune checkpoint protein PD-L1 plays a pivotal role in tumor immune evasion by binding to PD-1 on immune cells, including T lymphocytes. While the expression and function of PD-L1 have been well studied, the importance of its spatial organization on the cell surface of tumor cells remains poorly understood. In this study, we used super-resolution microscopy combined with biochemical perturbations to investigate the factors regulating PD-L1 clustering and its effects on PD-1 binding and T cell inhibition. We found that PD-L1 is organized into nanoscale clusters at the plasma membrane, with distinct regulatory roles for the actin cytoskeleton, galectin-3, and cholesterol. Disruption of cortical actin increased PD-L1 cluster size, while galectin-3 promoted smaller, denser clusters and increased PD-L1 lateral mobility. Cholesterol depletion reduced PD-L1 cluster size and number and impaired PD-1 binding. These findings indicate that PD-L1 surface organization is collectively regulated by the actin cytoskeleton, galectin-3, and membrane cholesterol within the plasma membrane of tumour cells. Our results provide new insights into the dynamic regulation of PD-L1 and its potential as a therapeutic target in cancer immunotherapy.

Investigating the neural mechanisms of social group interactions and other naturalistic behaviors in small animals remains limited by current technology. Tethered neural recording systems are incompatible with many of these behaviors, while existing wireless devices for small animals are constrained by weight, bandwidth, recording duration, and the lack of closed-loop modulation capabilities. To overcome these limitations, we developed a Wireless, Interactive, Lightweight Datalogger (WILD) with integrated flexible neural probes, optogenetics, an inertial measurement unit, an ultrasonic microphone, and a head-mounted camera. This platform enables simultaneous, long-term recording of neural activity, locomotor variables, vocalizations, and eye movements from groups of freely moving mice in both laboratory and outdoor settings. Model-based real-time signal processing detects specific neural events and behavioral motifs to trigger closed-loop neural interventions. By combining multimodal recordings with advanced onboard signal-processing capabilities in a compact device, WILD enables the investigation of neural mechanisms underlying a broad range of natural behaviors in small animals.

Embedded extrusion printing can process collagen-rich bioinks, but their low viscosity and slow fibrillogenesis compromise print fidelity and post-deposition stability. Here, we developed a collagen fibril-inducing support bath (FIB) that combines mechanical support for embedded printing with biochemical induction of collagen assembly. Microfibrillated or nanofibrillated cellulose was incorporated into a fibril-inducing buffer, and formulations were screened at 37 degrees Celsius for rheological behaviour and optical transparency. The selected FIB was evaluated by printing 1% and 5% (w/v) articular cartilage-derived extracellular matrix (ECM) inks at 10-20 mm/s and compared with a cellulose-only control bath. FIB exhibited yield-stress, shear-thinning and rapid recovery behaviour that supported reproducible filament deposition. Unlike the control bath, FIB enabled intact construct retrieval following stabilisation and promoted the formation of fibrillar collagen within the printed strands. Scanning electron microscopy revealed D-banded collagen fibrils preferentially oriented along the deposition direction, with dominant orientation peaks within +/- 10-15 degrees. The platform supported the fabrication of 15 x 15 x 1.5 mm sheets and 6 x 6 x 6 mm scaffolds whose macroscopic dimensions were retained after processing. Constructs produced from 5% ECM inks exhibited approximately fourfold higher ramp and relaxation moduli than those produced from 1% ECM inks. Extracts from both formulations caused no detectable reduction in cell metabolic activity after 24 h or 72 h. Mesenchymal stem/stromal cells (MSCs) seeded onto printed sheets became markedly elongated and aligned by day 3, with approximately 80% of cells having an aspect ratio exceeding 1.5, significantly greater than cells seeded onto casted ECM controls, with a mean deviation of ~9 degrees from the filament print direction. These findings establish FIB as a bioactive support bath that couples embedded printability with collagen fibrillogenesis, enabling recoverable collagen-rich constructs with aligned fibrillar architecture that directs early cellular organisation.

Osteochondral repair requires restoration of zonally organised articular cartilage and subchondral bone, yet translatable implants rarely reproduce this spatial complexity. Here, we developed an off-the-shelf, cell-free multilayer scaffold comprising a superficial 2% (w/v) articular cartilage extracellular matrix (AC-ECM) phase, an intermediate 5% AC-ECM phase and a basal 6% bone ECM (BN-ECM) phase. The scaffold formed continuous interfaces, displayed regionally distinct pore sizes and resisted permanent deformation during cyclic compression. In vitro, constructs seeded with caprine mesenchymal stromal and articular cartilage progenitor cells supported cell expansion and the accumulation of sulfated glycosaminoglycan- and collagen-rich matrix, with regional differences in collagen I, II and X deposition. Following eight weeks of subcutaneous implantation, cell-seeded scaffolds contained more collagenous matrix than unseeded controls, while vascularisation preferentially localised to the BN-ECM phase. The scaffold was then evaluated against empty defects in a caprine osteochondral model for six months. Scaffold treatment significantly improved macroscopic and histological repair, increased chondral tissue fill (~60% versus ~40%), limited cartilage-like tissue extension into the subchondral region and generated a more native-like superficial collagen organisation. Repair tissue further exhibited greater collagen II immunoreactivity, increased ACAN and COL2A1 expression and reduced COL1A2 expression relative to empty defects, although deeper bone repair was not significantly improved. These findings demonstrate that tissue-specific ECM layering can spatially guide endogenous repair and substantially improve cartilage restoration without exogenous cells or growth factors in a clinically relevant large-animal model, while identifying subchondral bone regeneration as the remaining design challenge for complete osteochondral repair.

Focal adhesions maintain force-bearing attachment between cells and the extracellular matrix but can also undergo dynamic remodeling. Their assembly and actomyosin tension are coupled through mechanochemical feedback. The processes underlying this feedback are not instantaneous and therefore involve a time delay. However, how this delayed feedback gives rise to stable adhesion maintenance or dynamic remodeling remains unclear. Here, paired time-lapse measurements of vinculin fluorescence and traction stress revealed distinct local adhesion-force dynamics, including low-fluctuation and recurrent fluctuation patterns. To examine how these patterns could arise, we formulated a minimal mechanochemical model coupling focal adhesion assembly and actomyosin force through delayed reciprocal feedback. The model exhibited stable and oscillatory modes depending on feedback strength, the balance of opposing feedback effects, and the effective feedback delay. Bistability and hysteretic switching also occurred in a subset of parameter space, and the oscillation period followed a power-law relation with the delay. These results suggest that stable adhesion maintenance and dynamic remodeling can emerge from a common mechanochemical feedback architecture.

Background: In Denmark, perioperative high-dose glucocorticoid treatment were step-wisely implemented for total hip arthroplasty (THA), total knee arthroplasty (TKA), and unicompartmental knee arthroplasty (UKA). We aimed to estimate the effect of a single high dose of glucocorticoids on opioid consumption following primary THA, TKA, and UKA. Methods: This was a prespecified analysis of a multicenter natural experiment using electronic health record data. We included elective THA, TKA, or UKA surgeries performed in Eastern Denmark from 2017-2025. At each center, surgeries before implementation of high-dose glucocorticoids served as controls, whereas surgeries after implementation comprised the intervention group. The primary outcome was the between-group difference in cumulative 0-24h opioid consumption, which included preemptive end-of-surgery doses. The predefined minimal important difference was set at 5 mg IV morphine equivalents. Secondary outcomes were maximum 0-10 numerical rating scale (NRS) pain score and incidence of opioid-related adverse events within 24 hours, hospital length of stay, and days alive and out of hospital at 30 days. Results: A total of 47,317 surgeries performed at nine centers were analyzed: 13,010 controls and 34,307 in the intervention group. During the study period, five centers implemented high-dose glucocorticoids for THA patients, two for TKA/UKA patients. High-dose glucocorticoids were administered to 6% of patients before implementation versus 92% after. High-dose glucocorticoids resulted in a mean reduction of 3.8 mg intravenous (IV) morphine equivalents (95% CI 3.3;4.3). The intervention also reduced the maximum 0-24h NRS pain score by 0.8 points (99% CI 0.7;0.9), but there was no difference in adverse events, length of stay, or days alive and out of hospital. Conclusions: Implementation of high-dose glucocorticoids reduced 0-24-hour opioid consumption by 3.8 mg IV morphine equivalents after elective hip and knee arthroplasty. This difference was below the prespecified minimal important difference threshold. Online registration: https://doi.org/10.1101/2025.11.11.25339982

Introduction: Risk of recurrent opioid use during buprenorphine-naloxone (bup-nx) treatment is dynamic and remains elevated after initiation, with vulnerability shaped in part by treatment intensity and gaps between visits, yet routine outpatient care relies on episodic encounters and retrospective data. This mismatch can delay recognition of emerging instability and limit timely treatment adjustments. This paper reports the development and specification of an intervention strategy to address this mismatch. Methods: We used a structured, multi-phase design process to specify and configure a measurement-based care (MBC) strategy for bup-nx treatment (Bup-MBC) in outpatient addiction clinics through three phases: (1) a systematic review of patient-reported outcome measures (PROMs) for substance use treatment; (2) a qualitative needs assessment using the Theoretical Domains Framework and COM-B (Capability, Opportunity, Motivation-Behavior) model to identify gaps in risk monitoring, agency, and trust; and (3) iterative co-design with multidisciplinary clinicians to refine workflow fit and trust-preserving use of data. Patients informed item and feedback content during the needs assessment but did not participate in the co-design cycles. Results: Bup-MBC integrates (1) brief between-visit PROMs (e.g., withdrawal, craving, adherence); (2) immediate non-punitive patient feedback; (3) clinician-facing summaries and non-directive prompts in the electronic health record (EHR); and (4) an opt-in between-visit outreach pathway with predefined safety triggers, all configured within existing EHR and patient portal infrastructure. It targets patient and clinician capability to recognize changes in risk, opportunity for action through structured monitoring and visit preparation, and trust and agency through non-punitive communication, without adding substantial burden. The full measure set, severity bands, and question-to-action map are provided as supplementary material. Key trade-offs included prioritizing single-item measures for feasibility, balancing opt-in outreach with safety overrides, and assuming routine clinician use of summaries. Conclusion: This development study specifies an EHR-integrated MBC strategy for outpatient bup-nx treatment. As single-center design work with co-design limited to clinicians and delivery contingent on portal or text-message access, its outputs are hypotheses about mechanism and fit rather than demonstrated effects. Feasibility studies are needed to evaluate uptake, acceptability, workflow fit, and effects on treatment.

We propose two new tests to detect drug effects (DE) in trials of one to very few patients followed during two periods (before and after initiation of a treatment). Both methods use longitudinal natural history data to inform the estimation of each patient's DE. The first method uses a non linear mixed effect model (NLMEM) reflecting an expected natural history with a hypothetical drug effect, to estimate the Conditional Distribution of the Drug Effect (CDDE). The second method trains a Pareto Depth Analysis (PDA) algorithm, a machine learning based approach based on outlier detection, that we implement using data simulated under the NLMEM. We evaluated the two tests with a simulation study. We used data from the PROSPAX study in Autosomal Recessive Cerebellar Ataxias (ARCAs, to derive a NLMEM for the Scale for the Assessment and Rating of Ataxia score. The CDDE method provided controlled type I error and, in some scenarios, adequate corrected power, though sensitivity analyses showed vulnerability to misspecification. The PDA method demonstrated lower statistical power except with high score precision. These results highlight different strategies for quantifying treatment effects in ultra rare, patient' specific trials. They can inform methodological design for future ARCA precision therapies.

The distribution of fat-soluble compounds (including antioxidants) in follicular fluid (FF) remains sparsely documented in relation to in vitro fertilization (IVF) outcomes and existing studies have reported diverging associations. This study aimed to describe plasma and FF concentrations of fat-soluble micronutrients in women undergoing IVF and to analyze their adjusted associations with ovarian function, embryo development and pregnancy outcomes. In 2021-2022, plasma and FF samples were collected from 82 women (first IVF cycle) at oocyte puncture, along with lifestyle data covering the three preceding months. Eleven compounds (two tocopherols, three xanthophylls, five carotenes and retinol) were quantified. All compounds were detected in both compartments (lowest in FF) except phytoene, undetectable in FF. Plasma and FF -tocopherol concentrations were positively associated with plasma estradiol levels before oocyte puncture (both p<0.01) while FF -carotene and lycopene were inversely associated with plasma progesterone concentrations (p=0.01 and 0.02, respectively). Plasma phytofluene and phytoene were positively associated with mature oocyte rate (p=0.03 and p=0.01, respectively), while FF retinol was negatively associated (p=0.03). Carotenes, tocopherols and retinol were inversely associated with later IVF outcomes: fertilization rate (p<0.001 for plasma g-tocopherol, 0.02 for FF retinol), top-quality embryo (p=0.02 for plasma phytofluene), biochemical pregnancy at day 7 post-embryo transfer (p=0.05 for plasma -tocopherol, 0.02 for plasma -carotene), clinical pregnancy (p=0.03 for plasma -tocopherol, 0.01 for plasma phytoene) and live birth (p=0.04 for plasma -tocopherol, 0.02 for plasma phytoene). Plasma and FF g-tocopherol were positively associated with embryo fragmentation (both p<0.05). Finally, among xanthophylls, only plasma {beta}-cryptoxanthin was positively associated with plasma progesterone concentrations (p=0.02). Our findings of heterogeneous associations between tocopherols, carotenes, retinol and IVF outcomes across the stages of IVF suggest a beneficial effect limited to early outcomes and support a complex and context-dependent role of these compounds in female reproduction. This manuscript has been submitted to PlosOne on August 19, 2026.

Objective: This study examined the prevalence of psychotic experiences (PE) and how early onset and persistence of PE contribute to risk and severity of mental disorders in adolescents at familial high-risk of schizophrenia (FHR-SZ) or bipolar disorder (FHR-BP) and adolescents from a population-based control group (PBC). Methods: This is the second follow-up of a nationwide cohort study including 522 children at FHR-SZ (N=202), FHR-BP (N=120), and PBC (N=200). Participants were assessed at ages 7, 11, and 15 using a semi-structured interview to evaluate PE and mental disorders. Results: At age 15, adolescents at FHR-SZ reported more PE than PBC over the past six months (current) and the past four years, while adolescents at FHR-BP only reported more current PE. PE reported at two or three timepoints (persistent PE) predicted any Axis I disorder in mid-adolescence, corresponding to three- (OR 2.9, 95% CI [1.5-5.7]) and 21-fold (OR 21.4, 95% CI [2.8-162.3]) increased risks, respectively. Persistent PE also predicted multimorbidity, with three- (OR 2.8, 95% CI [1.0-7.6]) and four-fold (OR 4.1, 95% CI [1.2-14.1]) increased risks, respectively. This was after adjustment for sex, early mental disorders, and familial risk. Conclusions: This study demonstrates a strong link between persistent PE and mid-adolescence mental disorders. Our findings emphasize PE as important risk markers for mental disorders during mid-adolescence and highlight the importance of monitoring children with PE before age 7 who develop persistent symptoms.

Introduction Continuous Glucose Monitoring (CGM) is considered standard care in high-income countries. There is, however, limited published evidence on CGM use in low- and middle-income countries. The purpose of this study was to assess the usability, acceptability, and feasibility of CGM use among people living with type 1 diabetes (T1D) and caregivers in a low-resource setting. Research Design and Methods This prospective study conducted at the Kenyatta National Hospital purposively enrolled persons aged 4-25 years who had been on management for T1D for at least six months, and caregivers of those under 18 years. Fourty youth living with T1D used CGM for three months in place of self monitoring of blood glucose (SMBG). The System Usability Scale (SUS), a Theoretical Framework of Acceptability-based questionnaire, the Diabetes Distress Scale (DDS), the Glucose Monitoring Satisfaction Survey (GMSS), and a feasibility survey were administered. Outcomes were summarized descriptively, including means, medians, and frequencies using R statistical software. Results The median SUS score was 98.8 (IQR 92.5-100.0). Acceptability was high, and the median total GMSS score improved from 3.73 to 4.73. Among adolescents and adults, the median overall DDS score reduced from 1.54 to 1.36, with reductions in scores in all domains, except for hypoglycemia distress which increased, and physician distress which remained low. Among caregivers, the median overall DDS score declined from 2.05 (moderate distress) to 1.90 (low distress), with modest reductions in teen management and parent-teen relationship distress and a slight increase in personal distress. Median CGM active wear time was 89%. Conclusion This study comprehensively evaluated CGM across usability, acceptability, and feasibility outcomes, with the findings supporting the integration of CGM into routine diabetes management in low-resource settings. The short follow-up period, however, may not capture changing perceptions or long-term adherence.

Background: The condition of a patient with acute stroke often changes within hours of ICU admission. Prognostic work here targets fixed endpoints predicted from admission data, and trajectory phenotyping assigns one label per patient. We used longitudinal ICU data to identify interpretable dynamic clinical states, characterize transitions between them, and relate the current state to later events. Methods: Retrospective cohort study of 6368 adults with acute stroke in MIMIC IV v3.1. The first 72 h were divided into twelve 6-hour windows, and a hidden Markov model was fitted to 21 neurological, physiological and organ support variables. State number was chosen against criteria fixed before fitting: statistical fit, restart stability, state occupancy and clinical interpretability. Generalized estimating equations related the current state to new mechanical ventilation and vasopressor use within 12 h, and to ICU death within 72 h. Eleven sensitivity analyses assessed the robustness of the state solution. Results: Four states were selected: neurologically preserved-low support, neurological impairment low support, impairment renal dysfunction and impairment-respiratory support (63.3%, 7.8%, 11.8% and 17.1% of windows). Within 72 h, 40.3% of patients changed state at least once, and transitions ran in both directions rather than along a single severity gradient. States were identified without outcome data, yet ICU mortality by last state ranged from 2.9% to 43.9%. Adjusted for age, sex, subtype and Charlson index, the current state remained associated with organ-support escalation and death. State prevalence differed by at most 1.1 percentage points between training and test sets, and 10 of 11 sensitivity analyses gave a stable four-state solution (ARI 0.754 0.955). Conclusions: The early ICU course of acute stroke can be represented as movement among a small number of clinically interpretable states. The representation was reproducible in a held out set and across admission eras, but requires validation in an independent database before any clinical use.

Objective and scalable approaches for detecting subtle motor impairment in isolated REM sleep behavior disorder (iRBD), a prodromal stage of Parkinson's disease, remain limited. We investigated whether markerless motion capture from single RGB-camera videos can identify gait abnormalities in people living with iRBD and provide interpretable digital biomarkers. We retrospectively analyzed 93 standardized walking videos from three clinical sites. Human pose estimation extracted 12 body markers and 14 kinematic time series. Thirty-five machine learning approaches classified healthy controls (HC) and people with iRBD. The Movement Disorder Society Unified Parkinson's Disease Rating Scale Part 3 (MDS-UPDRS III) served as the clinical baseline. The best-performing model (tsfresh+XGBoost) achieved an AUROC of 0.739, significantly outperforming the MDS-UPDRS III sum score when trained on data from all three sites. Harmonized multi-site training improved performance. SHAP identified hip-related temporal features as key contributors, which differed between groups and showed stronger associations with regional dopaminergic deficits than clinical scores. Single-camera gait analysis may provide scalable digital biomarkers for low-cost screening and monitoring of prodromal PD.

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

Predicting disease risk from prior diagnoses is fundamental to clinical decision-making, particularly during health emergencies such as the COVID-19 pandemic, when individuals with long-term conditions may be disproportionately vulnerable to adverse outcomes. Despite intense interest in developing models to predict disease risk from prior diagnoses (1-3), most prediction models do not estimate effects of each prior diagnosis on disease risk conditional on other diagnoses, limiting interpretability and clinical utility. We developed the Comorbidity Risk Score (CRS), trained on 13 million individuals (age 40-69) from linked electronic health record (EHR) datasets of the entire population of England, to predict COVID-19 hospitalisation and 87 other disease outcomes. CRS was trained at close to saturated sample size and precisely estimated the effects of 212 prior diagnoses on the 88 disease outcomes, conditional on all other prior diagnoses. Correlations of CRS effect sizes across outcomes (e.g. 0.76 for myocardial infarction vs. hyperlipidaemia) matched the corresponding genetic correlations (e.g. 0.79 for myocardial infarction vs. hyperlipidaemia), confirming that comorbidity architectures capture disease aetiology. On average, CRS identified 5% of the population with 3.4-fold higher disease risk, including myocardial infarction (4.4-fold), lung cancer (6.5-fold), and COVID-19 hospitalisation (6.3-fold). Using prior diagnoses alone, CRS outperformed state-of-the-art clinical COVID-19 models (4). Furthermore, CRS (N=13 million) substantially outperformed state-of-the-art AI (1) (N=0.5 million) and linear (3) (N=0.5 million) models in predicting disease risk, suggesting that training sample size outweighs model complexity. CRS attained near-perfect transferability across self-reported ethnicities (e.g., Black vs. White: AUROC ratio = 97.3%). Finally, CRS distinguished independently predictive comorbidities from indirect associations, e.g., lipid metabolism disorder was a strong predictor of myocardial infarction risk but not ischaemic stroke, after conditioning on other prior diagnoses. In conclusion, CRS provides a comprehensive resource for understanding the impact of comorbidities on COVID-19 and other future diseases, revealing disease aetiology while enabling powerful prediction of disease risk.

Improvements in data availability, sharing, and integration, together with the development of explainable artificial intelligence (XAI) techniques, are advancing precision medicine for pediatric cancer by facilitating diagnosis, biomarker discovery, and drug development. Data sharing commons and initiatives like the Childhood Cancer Data Initiative (CCDI) provide access to pediatric-specific genomic and clinical data cohorts and improve data availability for pediatric cancer research. Based on CCDI, a scalable AI platform, Graph Artificial Intelligence for Pediatric Oncology (GAIPO), integrates various data modalities from bulk and single-cell omics data to clinical information. Such multi-modal data facilitates the training and development of advanced XAI models for pediatric cancers. We then developed an end-to-end multi-modality framework, PCGS, for pediatric cancer by incorporating omics-specific representation learning via GNN models with cross-attention fusion and multi-objective learning for downstream tasks such as classification, clustering, and survival analysis. This framework outperforms previous supervised multi-omics integration baseline approaches based on glioma and Wilms tumor cohorts and enables GNN model explainability via Shapley value-based feature attribution approaches to explain the contributions of gene-level features across various biomedical tasks, including classification and survival. Given specific background samples (e.g., age groups, sex, grades) as baselines, this explainable GNN model estimates and ranks the importance scores for input features from each omics modality. It identifies background-specific key features for biomarker discovery, risk group identification, and survival analysis in glioma and Wilms tumor, with potential applicability to other pediatric cancers.

Abstract Background: Vaginal steaming has gained popularity among women for reasons known best to them. However, the effects of vaginal steaming on vaginal lactobacilli levels remain poorly understood and understudied. This study investigated the prevalence, assessed differences in the presence of bacterial vaginosis (BV) among women who practiced vaginal steaming and those who do not and determined the factors associated with vaginal steaming among women attending Mulago Sexually Transmitted Infections (STI) clinic in Uganda. Methods: This study utilized a cross-sectional design to enroll 181 women aged 18 to 49 years who were systematically sampled at Mulago STI clinic. Interviews were conducted to obtain the demographic characteristics of the participants. Vaginal swabbing and Gram staining were done to attain lactobacilli counts by microscopy which were categorized using the Nugent score. Data were analyzed using Stata. The potential confounding effects of other variables on the relation between vaginal steaming and the presence of bacterial vaginosis as well as factors associated with vaginal steaming were assessed using modified Poisson regression. Results: Prevalence of vaginal steaming was 40.3%, (95% confidence interval (CI) 33.0% - 48.0%). There were 41.1% women who practiced vaginal steaming occasionally, 53.4% who used hot water having herbs and 78.1% who practiced vaginal steaming for medical reasons. There was no difference in the presence of bacterial vaginosis when women who practiced vaginal steaming were compared to those who did not (p-value = 0.286). Factors that were significantly associated with vaginal steaming included having experienced vaginal issues (aPR = 0.07, 95% CI 0.01 - 0.12, p value = < 0.001) and contraceptive use (aPR= 0.52, 95% CI 0.37 - 0.72, p value = 0.001). Conclusions: About 2 in every 5 women at Mulago STI clinic reported to have indulged in vaginal steaming. There was no difference in the presence of bacterial vaginosis when women who practiced vaginal steaming were compared to those who did not. Having experienced vaginal issues and contraceptive use were significantly associated with vaginal steaming among women at Mulago STI clinic, Uganda. The Ministry of Health of Uganda should establish targeted screening and treatment for bacterial vaginosis alongside other sexually transmitted infections.