in silico Plants

Mildew resistance Locus O (MLO) proteins have been originally identified as susceptibility factors for the fungal powdery mildew disease. Beyond immunity, they function in polarized secretion, including root and root hair elongation, trichome development, and fertilization. Moreover, MLO proteins mediate Ca{superscript 2} influx, either indirectly by recruiting Ca{superscript 2}-permeable channels to the plasma membrane or by acting as ion channels themselves. The latter raises the question of whether MLO proteins oligomerize to mediate ion transport across membranes. Here, we present an AlphaFold 3-based modeling pipeline for the reproducible assessment of MLO-containing protein complexes using AlphaFolds built-in confidence metrics together with structural and dynamic analyses. The resulting predictions for homo-oligomers of the prototypic barley Mlo support dimeric and trimeric assemblies, with the trimer forming a central membrane-spanning pore. Notably, AlphaFold 3 captured discrete conformational states of this trimer, as reflected by the clustering of confidence metrics. Computational structural analyses indicated that higher-confidence models adopt a closed pore conformation, whereas lower-confidence predictions reflect progressively expanding pore diameters. Molecular dynamics simulations further showed Ca{superscript 2} permeability of the putative open models. Our pipeline similarly predicts trimeric assemblies for MLO variants from Arabidopsis thaliana and Marchantia polymorpha, suggesting a conserved MLO structural scaffold within the land plant lineage. Additional Molecular Dynamics simulations revealed that closed models of barley Mlo and A. thaliana MLO2 open under simulated membrane tension, supporting the notion that MLO proteins are mechanosensitive ion channels. Moreover, predictions of MLO proteins with its known interactors, EF-hand proteins and exocyst complex subunit EXO70 proteins, suggest a mechanism for feedback inhibition of MLO-mediated ion flux and provide comprehensive experimental support for AlphaFold 3-predicted protein interfaces. Altogether, our results provide a structural framework for MLO channel architecture and regulation, while our prediction, modeling, and simulation pipeline should be useful beyond the study of this specific protein family. One-sentence summaryThis article describes AlphaFold 3-based analyses of MLO proteins, revealing the predicted structure of MLO membrane pores, their dynamic opening and closing, and their association with interacting proteins, including calmodulin and calmodulin-like calcium sensor proteins and exocyst complex subunit EXO70 proteins.

Predicting cellular behaviors, a central task in systems biology and metabolic engineering, can be enhanced through integrative modeling of processes such as gene regulation and metabolism. Information flow from gene regulation (modeled via a gene regulatory network) to metabolism (modeled via a genome-scale metabolic model) is well-studied, but the reciprocal regulation of genes by metabolites is less explored. We introduce CausalFlux, a method that models bidirectional feedback between genes and metabolites, in order to predict steady-state reaction fluxes under wild-type (WT) or perturbed (e.g., gene knockout/KO) conditions. CausalFlux does so by iteratively performing causal surgery on a Bayesian gene regulatory network and constraint-based analysis of a coupled metabolic model. CausalFlux enabled us to assess the impact of two-way feedback in several testbed models and real-world biological systems by comparing its predictions to those of TRIMER, a state-of-the-art model of gene-to-metabolite one-way feedback. Incorporating bidirectional feedback, as in CausalFlux, improved the Spearman correlation between actual and predicted fluxes in 92% of the 39 distinct simulation conditions relative to TRIMER. For predicting growth/no-growth phenotype following single-gene KOs in E. coli, CausalFlux achieved a balanced accuracy of 0.79 in identifying essential genes, and TRIMER achieved 0.71 for the same task, again highlighting the importance of modeling two-way feedback. In ablation studies that further dissect the role of specific metabolite[->]gene feedback edges in E. coli, the F1 scores of gene essentiality predictions decreased by 7.5% and 13% upon ablation of feedback edges from any metabolite to the crp gene and the 10 metabolic feedback genes with the highest influence on the KO genes, respectively. Finally, we highlight the application of CausalFlux to predict the essentiality of several hundred genes under different media conditions. Overall, our findings show that CausalFlux can crucially utilize information on feedback metabolites to predict trends in reaction fluxes and qualitative (growth/no-growth) outcomes; thereby encouraging future systems modeling efforts to carefully incorporate not only gene-to-metabolite but also metabolite-to-gene interactions. AvailabilityCode pertaining to the CausalFlux method, and its benchmarking and application is publicly available at: https://github.com/BIRDSgroup/CausalFlux. Author summaryThe myriad processes within a living cell, such as gene regulation or metabolism, are tightly interconnected. Modeling these interconnected processes can offer a deeper mechanistic understanding of cellular behaviors, as well as guide efforts that engineer the metabolic output of a cell. In this work, we develop a novel integrated model of gene regulation and metabolism that incorporates bidirectional feedback between these two processes, via the concept of metabolite-induced causal surgery on a gene regulatory network and gene-induced constraints on the fluxes of metabolic reactions. Our model, which we call CausalFlux, represents an advance over most existing models that capture just the one-way gene-to-metabolism feedback (i.e., genes coding for enzymes that control metabolic reactions). Our CausalFlux methodology opens up an unique opportunity to quantify the impact of two-way feedback in gene-metabolite systems, via comparison of CausalFluxs predictions to those of TRIMER, a published model incorporating one-way feedback alone. For predicting reaction fluxes in testbed models and essential genes in E. coli, quantitative comparison of the performance of CausalFlux vs. TRIMER showed that accounting for two-way feedback leads to more accurate and biologically meaningful predictions. CausalFlux also enabled us to quantify the effect of two-way feedback by comparing prediction performance before and after ablation of certain feedback edges from metabolites to genes. Overall, our findings highlight the importance of modeling gene regulation and metabolism as two-way interconnected systems within a living cell, and encourage future works to incorporate gene{leftrightarrow}metabolite feedback into their analyses.

Quantitative genetic approaches such as genome-wide association studies and genomic prediction are widely used to identify favourable genetic variation, but they have limited resolution due to linkage disequilibrium. Comparative genomics approaches, especially Protein Language Models (PLMs), have emerged as powerful alternatives, by detecting phylogenetic residue conservation (PRC) across evolutionary time scales. However, the extent to which these tools can guide the detection of impactful variants for field agronomic traits is still unclear. In this study, we used the pre-trained PLM ESM2 to predict PRC scores of nonsynonymous mutations segregating within a diverse panel of 387 accessions in sorghum (SAP). The distribution of fitness effects (DFE) of the same set of nonsynonymous mutations was inferred using unfolded site frequency spectra to assess whether the DFE distribution covaried with PRC scores. Furthermore, we estimated the load of putatively nonneutral mutations of SAP accessions and evaluated associations between this mutation load and phenotypic performance across multiple agronomic traits. Our results show that ESM2 can detect mutations associated with fitness-enhancing effects in SAP, as indicated by enrichments in positive selection signatures among the variants with positive PRC scores. Significant associations were also detected between phenotypic performance and mutation load for several agronomic traits, indicating that PLMs can identify functionally important genetic variation. However, these signals were not consistent across all traits in the SAP population. Altogether, our findings suggest that large language models may support breeding efforts, as PLM predictions covaried with fitness effects and captured agronomic performance for some traits in plant populations.

Diversity and composition of plant-associated microbiota are attributed to host and microbial genotype as well as the environment, yet our understanding of the causal factors driving these patterns remains incomplete. Elevated concentrations of the micronutrients zinc (Zn), manganese (Mn) and copper (Cu), and exposure to non-essential trace elements including cadmium (Cd) and arsenic (As), can be toxic. Here we explored whether differences in metal(loid) homeostasis between plants and bacteria shape microbial community composition in the phyllosphere. Among the biologically relevant metal(loid)s Cd, Cu, Mn, Zn, and As, we identified CdII as the most toxic, and AsV (arsenate) as the most harmless, by screening 224 representative Arabidopsis thaliana phyllosphere bacterial strains on metal(loid) concentration series in synthetic media. Comparing bacteriotoxicity profiles with our measurements of the leaf apoplastic fluid ionome indicated that Zn2+ and Cd2+ concentrations are the most likely to arrest growth of metal-sensitive strains in planta. Soil bacterial strains were several-fold more sensitive to both these metals than leaf strains, consistent with selection for increased bacterial Zn and Cd tolerance in the phyllosphere. Keystone strains, known to govern bacterial community structure, were highly metal-sensitive, with only few between-metal interactions and no between-strain interactions modulating single-metal(loid) toxicities. Overall, bacterial genus explained 63% of the variance in metal(loid)-related gene content and 42% of the metal(loid) tolerance phenotypic variance. Cd tolerance correlated with the presence and copy number of known Cd-related genes. In summary, our results support the hypothesis that plant metal homeostasis contributes to structuring bacterial communities in the leaf endosphere. One sentence summaryBased on the magnitude and variation of metal tolerances among bacterial strains of the Arabidopsis phyllosphere, we conclude that common leaf apoplastic cadmium and zinc concentrations can influence bacterial community structure. Highlights- Metal(loid) sensitivities of the Arabidopsis thaliana phyllosphere bacterial strain (At-LSPHERE) collection followed the order of toxicity Cd2+ >> Cu2+ > Zn2+ > arsenite (AsIII) > Mn2+ > arsenite (AsV), whereby the responses of individual strains were uncorrelated between metal(loids) and predicted the sensitivities of multi-strain synthetic communities. - Upon cultivation of Arabidopsis in unpolluted soil, total CdII and ZnII in leaf apoplastic fluid were equivalent to concentrations that arrested growth of up to 2.2% and 0.4% of phyllosphere bacterial strains on agar-solidified R2A medium, respectively, whereas apoplastic CuII and MnII were 10- to 100-fold below bacteriotoxic levels. - Phyllosphere bacteria known to strongly influence community composition mostly remained highly sensitive under combined metal(loid) exposure, and elevated tolerances to CdII and ZnII, but not to other metalloid(s), in phyllosphere compared to soil bacteria were consistent with divergent natural selection in the leaf and soil environments. - The degree of phyllosphere bacterial metal(loid) tolerances correlates with the presence and copy number of known tolerance genes, with genus accounting for 63% of the variation in gene content and 42% of the phenotypic variation in metal(loid) tolerance. - In summary, our data suggest that local Cd and Zn levels in the Arabidopsis leaf endosphere influence the composition of bacterial communities and have shaped their phenotypic metal(loid) tolerance properties as a result of natural selection.

Most eukaryotes reproduce using partial clonality, for which appropriate population genetic models remain limited. This gap constrains our ability to accurately reconstruct past population dynamics, predict future trajectories, and infer the evolutionary processes involved. We present a Wright-Fisher-like model tailored for tracking the mean and the variance of genotype frequencies over generations at one locus with multiple alleles in a same finite-sized population with mutation. Different initial conditions and rates of clonality generate unique mean trajectories of genotype frequencies. Partially clonal populations converge to the same unique stable equilibrium as exclusively sexual populations, that only depends on the reciprocal mutation rates between alleles. The dynamics unfold in two phases: First, genotype frequencies move towards Hardy-Weinberg proportions; Then iterate along the Hardy-Weinberg proportions until reaching the stable equilibrium. Mean allele frequencies and gene diversity remain unchanged by different rates of clonality along the trajectories. Instead, clonality influences the speed at which populations return to Hardy-Weinberg proportions and thus shapes the temporal sequence of genotype frequency distributions over generations. Variance around each mean trajectory depends only on parental genotype frequency distributions and population size, not on clonality. Taken together, these explain why both negative and positive Fis values are expected in partially clonal populations, and why variance of Fis across loci is a reliable proxy for inferring clonal rates. Our model will enable the analysis and prediction of changes in genotype frequencies within monitored populations, and will support future inference methods relying on time-series genotyping data from a target population. HighlightsO_LIOut of equilibrium, sexual and clonal populations share the same two-step dynamics. C_LIO_LIFirst, return to Hardy-Weinberg parabola impacted by rates of clonality; Then, iteration along this parabola until reaching equilibrium that only depends on mutation rates C_LIO_LIIncreasing clonality change the speed and direction of mean dynamics out of Hardy-Weinberg parabola without affecting mean allele frequencies C_LIO_LIVariance around mean dynamics depends on parental genotype frequencies and population size but not affected by clonality C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=98 SRC="FIGDIR/small/717696v1_ufig1.gif" ALT="Figure 1"> View larger version (13K): org.highwire.dtl.DTLVardef@3fe977org.highwire.dtl.DTLVardef@1f8a38eorg.highwire.dtl.DTLVardef@b9ebbaorg.highwire.dtl.DTLVardef@231c67_HPS_FORMAT_FIGEXP M_FIG C_FIG

Objective Cerebral palsy (CP) affects approximately 1 million Americans and 18 million individuals worldwide, yet contemporary US epidemiologic data remains limited. We aimed to use Cerebral Palsy Research Network (CPRN) clinical registry to describe demographics and clinical characteristics of individuals with CP across the US and determine associations with gross motor function and genetic etiology. Methods Registry subjects were included if they had clinician-confirmed CP and prospectively entered data for Gross Motor Function Classification System (GMFCS) Level, gestational age, genetic etiology, CP distribution, and tone/movement types. Logistic regression was used to determine which of these variables plus race, sex, ethnicity, and age were associated with GMFCS level and genetic etiology. Results A total of 9,756 children and adults with CP from 22 CPRN sites met inclusion criteria. Participants were predominantly White (73.0%), male (57.3%), non-Hispanic (87.8%), and younger than 18 years (73.7%). Most were classified as GMFCS levels I-III (55.6%), born preterm (52.8%), had spasticity (83.8%), and had quadriplegia (41.9%); 12.2% were identified as having a genetic etiology. Tone/movement types, CP distribution, and gestational age were significantly associated with both GMFCS level and genetic etiology (p<0.001). Compared to White individuals, Black individuals were more likely to have greater gross motor impairment (p<0.001). Conclusion In this large US cohort, clinical and demographic factors, including race, were associated with gross motor function and genetic etiology in CP. These findings highlight persistent disparities and demonstrate the value of a national clinical registry for informing prognostication, quality improvement efforts, and targeted genetic testing strategies.

Objectives: Acute gastroenteritis is a leading cause of pediatric emergency department (ED) visits. While ondansetron reduces vomiting, intravenous rehydration, and hospital admissions, its efficacy when initiated at triage remains unclear. We aimed to evaluate whether triage nurse-initiated administration of ondansetron in children with suspected gastroenteritis reduces the proportion of patients requiring observation following initial physician assessment. Methods: We conducted a randomized, double-blind, placebo-controlled trial in a tertiary pediatric ED in Canada. Children aged 6 months to 17 years presenting with morae than 3 episodes of vomiting in the preceding 24 hours (including 1 within 2 hours of arrival), were eligible. At triage, we randomized participants to receive liquid ondansetron or a color- and taste-matched placebo. The primary outcome was the proportion of patients requiring observation after the first physician evaluation. Secondary outcomes included post-intervention vomiting, ED length of stay, patient comfort, and 48-hour return visits. The trial was registered at ClinicalTrials.gov (NCT03052361). Results: Recruitment was stopped prematurely due to the COVID-19 pandemic. Ninety-one participants were randomized to ondansetron (n= 44) or placebo (n= 47). Overall, 40 patients (45%) were discharged immediately after the initial physician assessment, with no difference between the ondansetron and placebo groups (44% vs. 45%; absolute difference -1%, 95% CI: -20% to 19%). No significant differences were observed in all secondary outcomes. Conclusion: In this trial, triage nurse-initiated ondansetron administration did not reduce the need for ED observation in children with presumed gastroenteritis. While being underpowered, this study could inform researchers planning larger clinical trials.

Background: Preterm births contribute to approximately 35% of neonatal deaths globally, with an estimated 13.4 million infants born prematurely each year. Despite this substantial burden, limited evidence exists on time to discharge and its determinants among preterm neonates admitted to Neonatal Intensive Care Units (NICUs), particularly in rural Ugandan settings. This study aimed to investigate time to discharge and associated factors among preterm neonates admitted to Kiwoko Hospital in Nakaseke District, Uganda. Methods: A retrospective cohort study was conducted using secondary data from Kiwoko Hospital on preterm neonates admitted to the Neonatal Intensive Care Unit (NICU) between 2020 and 2021 (n = 847). The cumulative incidence function was used to estimate the probability of discharge within 28 days of admission, accounting for competing events. A Fine and Gray sub-distribution hazard regression model was fitted to identify factors associated with time to discharge. Results: Of the 847 preterm admissions, 70.1% were discharged alive within 28 days. The median time to discharge was 14 days. The cumulative incidence of discharge by 28 days was 68%, accounting for competing events. During follow-up, 165 neonates did not complete the 28-day period, including 88 deaths. Factors significantly associated with time to discharge included place of delivery (SHR: 0.62; 95% CI: 0.53-0.73; p<0.001), maternal residence in other districts (SHR: 0.69; 95% CI: 0.48-0.99; p=0.044), extreme preterm (SHR: 0.05; 95% CI: 0.03-0.09; p<0.001), very preterm (SHR: 0.18; 95% CI: 0.14-0.25; p<0.001), moderate preterm (SHR: 0.59; 95% CI: 0.46-0.76; p<0.001), triplet births (SHR: 0.40; 95% CI: 0.23-0.68; p=0.001), 2-4 ANC visits (SHR: 0.70; 95% CI: 0.56-0.87; p=0.002), <=1 ANC visit (SHR: 0.64; 95% CI: 0.49-0.85; p=0.002), respiratory distress syndrome (SHR: 0.64; 95% CI: 0.48-0.74; p<0.001), and birth trauma (SHR: 2.62; 95% CI: 1.60-4.29; p<0.001). Conclusions: Respiratory distress syndrome, fewer antenatal care visits, out-of-district residence, and higher degrees of prematurity were associated with prolonged time to discharge among preterm neonates. Strengthening antenatal care utilization and improving access to quality neonatal care in underserved areas may enhance discharge outcomes.

BackgroundMajor depressive disorder (MDD), a leading cause of disability worldwide, exhibits substantial heterogeneity in treatment outcomes. Patients who do not respond to standard antidepressant therapy account for the majority of MDDs disease burden. Risk factors have been implicated in treatment response, including genes impacting on how antidepressants are metabolised. Yet, despite its clinical importance, risk factors for treatment-resistant depression (TRD) remain unexplored in low- and middle-income countries (LMIC). We used data from the DIVERGE study on MDD to investigate the risk factors of TRD in Pakistan. MethodsDIVERGE is a genetic epidemiological study that recruited adult MDD patients ([&ge;]18 years) between Sep 27,2021 to Jun 30, 2025, from psychiatric care facilities across Pakistan. Detailed phenotypic information was collected by trained interviewers and blood samples taken. Infinium Global Diversity Array with Enhanced PGx-8 from Illumina was used for genotyping followed by DRAGEN calling to infer metaboliser phenotypes for Cytochrome P450 (CYP) enzyme genes. We defined TRD as minimal to no improvement after [&ge;]12 weeks of adherent antidepressant therapy. We conducted multi-level logistic regression to test the association of demographic, clinical and pharmacogenetic variables with TRD. FindingsAmong 3,677 eligible patients, polypharmacy was rampant; 86% were prescribed another psychotropic drug along with an antidepressant. Psychological therapies were uncommon (6%) while 49% of patients had previously visited to a religious leader/faith healer in relation to their mental health problems. TRD was experienced by 34% (95%CI: 32-36%) patients. The TRD group was characterised by more psychotic symptoms and suicidal behaviour (OR=1.39, 95%CI=1.04-1.84, p=0.02; OR=1.03, 95%CI=1.01-1.05, p=0.005). Social support (OR=0.55, 95%CI=0.44-0.69, p=1.4x10-7) and parents being first cousins (OR=0.81, 95%CI=0.69-0.96, p=0.01) were associated with lower odds of TRD. In 1,085 patients with CYP enzyme data, poor (OR=1.85, 95%CI=1.11-3.07, p=0.01) and ultra-rapid (OR=3.11, 95%CI=1.59-6.12, p=0.0009) metabolizers for CYP2C19 had increased risk of TRD compared with normal metabolisers. InterpretationThere was an excessive use of polypharmacy in the treatment of depression while psychological therapies were uncommon highlighting the need for more evidence-based practice. This first large study of MDD from Pakistan uncovered the importance of culture-specific forms of social support in preventing TRD, highlighting opportunities for interventions in low-income settings. Pharmacogenetic markers can be leveraged to predict TRD.

ImportanceGuideline-concordant care for young children with attention-deficit/hyperactivity disorder (ADHD) includes recommending parent training in behavior management (PTBM) as first-line treatment. However, assessing guideline adherence through manual chart review is time-consuming and costly, limiting scalable and timely quality-of-care measurement. ObjectiveTo evaluate the accuracy and explainability of large language models (LLMs) in identifying PTBM recommendations in pediatric electronic health record (EHR) notes as a scalable alternative to manual chart review. Design, Setting, and ParticipantsThis retrospective cohort study was conducted in a community-based pediatric healthcare network in California consisting of 27 primary care clinics. The study cohort included children aged 4-6 years with [&ge;] 2 primary care visits between 2020-2024 and ICD-10 diagnoses of ADHD or ADHD symptoms (n=542 patients). Clinical notes from the first ADHD-related visit were included. A stratified subset of 122 notes, including all cases with model disagreement, was manually annotated to assess model performance in identifying PTBM recommendations and rank model explanations. ExposuresAssessment and plan sections of clinical notes were analyzed using three generative large language models (Claude-3.5, GPT-4o, and LLaMA-3.3-70B) to identify the presence of PTBM recommendations and generate explanatory rationales and documentation evidence. Main Outcomes and MeasuresModel performance in identifying PTBM recommendations (measured by sensitivity, positive predictive value (PPV), and F1-score) and qualitative explainability ratings of model-generated rationales (based on the QUEST framework). ResultsAll three models demonstrated high performance compared to expert chart review. Claude-3.5 showed balanced performance (sensitivity=0.89, PPV=0.95, and F1-score=0.92) and ranked highest in explainability. LLaMA3.3-70B achieved sensitivity=0.91, PPV=0.89, and F1-score=0.90, ranking second for explainability. GPT-4o had the highest PPV [0.97] but lowest sensitivity [0.82], with an F1-score of 0.89 and the lowest explainability ranking. Based on classifications from the best-performing model, Claude-3.5, 26.4% (143/542) of patients had documented PTBM recommendations at their first ADHD-related visit. Conclusions and RelevanceLLMs can accurately extract guideline-concordant clinician recommendations for non-pharmacological ADHD treatment from unstructured clinical notes while providing clear explanations and supporting evidence. Evaluating model explainability as part of LLM implementation for medical chart review tasks can promote transparent and scalable solutions for quality-of-care measurement.

Importance: Suicide is a leading cause of death in the United States with risk strongly influenced by Interpersonal trauma, contributing to treatment resistance and clinical complexity. Objective: To assess clinical and genetic factors in individuals who died from suicide, with and without interpersonal trauma exposure. Design: Individuals who died from suicide with and without trauma were compared in a retrospective case-case design. Prevalence of 19 broad clinical categories was assessed between groups. Results directed selection of 42 clinical subcategories, and 40 polygenic scores (PGS) for further assessment. Multivariable logistic regression models, adjusted for critical covariates and multiple tests, were formulated. Models were also stratified by age group (<26yo and >=26yo), sex, and age/sex. Setting: A population-based evaluation of comorbidity and polygenic scoring in two suicide death subgroups. Participants: A total of 8 738 Utah Suicide Mortality Research Study individuals (23.9% female, average age = 42.6 yo) who died from suicide were evaluated, divided into trauma (N = 1 091) and non-trauma exposed (N = 7 647) individuals. A subset of unrelated European genotyped individuals was also assessed in PGS analyses (Trauma N = 491; Non-trauma N = 3 233). Exposures: Trauma is here defined as interpersonal trauma exposure, including abuse, assault, and neglect from International Classification of Disease coding. Main Outcomes and Measures: Prevalence of comorbid clinical sub/categories and PGS enrichment in trauma versus non-trauma exposed suicide deaths. Results: Overall, trauma-exposed individuals died from suicide earlier (mean age of 38.1 yo versus 43.3 yo; P <0.0001) and were disproportionately female (38% versus 21%, OR = 3.3, CI = 2.9-3.8). Prevalence of asphyxiation and overdose methods, prior suicidality, psychiatric diagnoses, and substance use (OR range = 1.3-3.7) were elevated in trauma exposed individuals who died from suicide. Genetic PGS were also elevated in trauma-exposed individuals who died from suicide for depression, bipolar disorder, cannabis use, PTSD, insomnia, and schizophrenia (OR range = 1.1-1.4) with ADHD and opioid use showing uniquely elevated PGS in trauma exposed males (OR range = 1.2-1.4). Conclusions and Relevance: Results demonstrated multiple convergent lines of age- and sex-specific evidence differentiating trauma-exposed from non-trauma exposed suicide death. Such findings suggest unique biological backgrounds and may refine identification and treatment of this high-risk group.

Introduction Access to safe water, sanitation, and hygiene (WASH) in schools is critical for child health, learning, and gender equity. In Kenya, the Kenya School Health Policy and the Basic Education Act outline standards for school WASH; however, implementation remains uneven due to inadequate infrastructure, weak inter-sectoral coordination, and limited financing. This study aimed to identify priority components for strengthening school WASH implementation and generate policy-relevant recommendations based on expert consensus in Uasin Gishu County, Kenya. Methods and Results A Delphi technique consisting of two iterative rounds was used to reach expert consensus. In Round 1, 20 purposively selected experts including head teachers, county education officials, public health officers, water and public works officers, and NGO representatives participated in key informant interviews. Emergent themes informed development of a structured Round 2 questionnaire administered through CommCare online app. Quantitative data were analyzed using descriptive statistics (means, standard deviations, percentage agreement), while qualitative responses underwent thematic coding using NVivo 12. Experts reached strong consensus on essential components required for strengthening school WASH implementation. Key priorities included clear governance structures, designated budget lines, inclusive infrastructure, menstrual hygiene management (MHM), curriculum integration, sustained capacity building, and systematic monitoring. Multi-sectoral collaboration and recognition of best-performing schools were also emphasized as important motivators for compliance and sustainability. Equity considerations particularly the need for disability-friendly facilities and school-community outreach were highlighted as critical. Agreement levels ranged from 74% to 100%, with most items scoring mean values between 4.5 and 4.8 on a 5-point Likert scale, indicating strong consensus among experts. Conclusion strengthening implementation of school WASH in Kenya requires coordinated governance, predictable funding, reliable water systems, inclusive sanitation, strengthened MHM, and consistent monitoring beyond infrastructure investment alone. Integrating these expert-validated priorities within existing national policies offers a practical pathway to improving learner health, reducing absenteeism especially among girls and promoting equitable educational outcomes.

Background: Large language models (LLMs) are increasingly used in mental health contexts, yet their detection of suicidal ideation is inconsistent, raising patient safety concerns. Objective: To evaluate whether an independent safety monitoring system improves detection of suicide risk compared with native LLM safeguards. Methods: We conducted a cross-sectional evaluation using 224 paired suicide-related clinical vignettes presented in a single-turn format under two conditions (with and without structured clinical information). Native LLM safeguard responses were compared with an independent supervisory safety architecture with asynchronous monitoring. The primary outcome was detection of suicide risk requiring intervention. Results: The supervisory system detected suicide risk in 205 of 224 evaluations (91.5%) versus 41 of 224 (18.3%) for native LLM safeguards. Among 168 discordant evaluations, 166 favored the supervisory system and 2 favored the LLM (matched odds ratio {approx}83.0). Both systems detected risk in 39 evaluations, and neither in 17. Detection was highest in scenarios with explicit suicidal ideation and lower in more ambiguous presentations. Conclusions: Native LLM safeguards frequently failed to detect suicide risk in this structured evaluation. An independent monitoring approach substantially improved detection, supporting the role of external safety systems in high-risk mental health applications of LLMs.

BackgroundProspective studies of pregnant adolescents are essencial to effectively address this global health priority. They help answer vital questions about their health, but such studies are uncommon due to the difficulty in retaining adolescents. This paper describes the successes and challenges of the research strategies used to ensure sufficient recruitment and retention of pregnant adolescents in a longitudinal study about adolescent childbearing in an under-resourced setting. MethodsThe Adolescence and Motherhood Research project was conducted in a rural region of Northeast Brazil in 2017-2019 and assessed 50 primigravids between 13-18 years (adolescents) and 50 primigravids between 23-28 years (young adults) during the first 16 weeks of pregnancy with two follow-ups (third trimester of pregnancy, and 4-6 weeks postpartum). Recruitment strategies involved engagement of health sector and community, as well as referrals from health care professionals and dissemination of the project in different locations. Retention strategies included maintaining contact with the participants between assessments and providing transportation for them to attend the follow-up procedures. ResultsRecruitment took 10 months to complete. A total of 78% of the participants were recruited from the primary health care units, mainly after referral from a health care provider. Retention reached 95% of the sample throughout the study (90%: adolescents; 98%: adults). ConclusionA combination of approaches is necessary to successfully recruit and retain youth in longitudinal studies and engaging local stakeholders may help to increase community-perceived legitimacy of the research. Working closely with front-line staff is essential when conducting research in rural low-income communities.

Background: HIV/AIDS remains a major public health challenge in Tanzania, where viral load suppression among adults on ART stands at 78% and HVL testing uptake among eligible patients is approximately 22%. Since the introduction of the National HVL Testing Guideline in 2015, little has been done to systematically evaluate its implementation. Objective: To evaluate adherence to the National HVL Testing Guideline across CTC clinics in Dar es Salaam Region, covering ART monitoring, documentation, turnaround time, and factors affecting implementation. Methods: A cross-sectional study was conducted in 2021 across 15 public health facilities with CTC clinics in all five Dar es Salaam districts. A total of 330 PLHIV on ART for more than six months were selected through systematic random sampling with proportional to size allocation, and 45 healthcare providers through convenient sampling. Data were collected via abstraction forms and self-administered questionnaires, and analysed using SPSS Version 23 with descriptive statistics, bivariate analysis, and binary logistic regression. Results: Only 25.1% of patients had their first HVL sample taken at six months as per guideline, with 68.8% delayed beyond six months. Second and third samples were similarly delayed. MoHCDGEC sample tracking forms were absent in 96.7% of facilities and incomplete in 99.1%, and no facility captured specimen acceptance or rejection as site feedback. Turnaround time exceeded the 14-day guideline threshold in 64.5%, 66.7%, and 69.4% of first, second, and third results respectively. Patient negligence (AOR=9.84; 95% CI: 1.83-52.77) and storage (AOR=5.72; 95% CI: 0.94-35.0) were independently associated with guideline adherence. Conclusion: Adherence to the National HVL Testing Guideline in Dar es Salaam is suboptimal across testing timelines, documentation, and turnaround time, with patient negligence and storage capacity as significant determinants. Targeted interventions are needed to strengthen patient education, improve storage infrastructure, enhance documentation systems, and support providers in adhering to guideline-specified timelines.

BackgroundPatent ductus arteriosus (PDA) is a common and potentially serious cardiovascular condition in preterm infants, particularly those with low gestational age and birth weight. Its management remains controversial due to variability in screening, diagnostic criteria, and treatment strategies. This study aimed to evaluate risk factors, outcomes, and management strategies for PDA in preterm infants, and to identify predictors of clinical and echocardiographic response to therapy. MethodsWe conducted a retrospective cohort study over a 4-year period (2016-2019) in the neonatal intensive care unit (NICU) of a tertiary care center. All consecutive preterm infants admitted during the study period were eligible. Infants with echocardiographically confirmed PDA who received pharmacological treatment with intravenous paracetamol or ibuprofen were included in the analysis. Missing data were minimal and handled using available-case analysis. Statistical analyses included descriptive statistics, Pearsons chi-square test, and multivariable logistic regression. ResultsAmong 2154 preterm infants admitted to the NICU, 60 were diagnosed with PDA (incidence : 2.8%). The mean gestational age was 29 {+/-} 2.6 weeks, and the median birth weight was 1200 g. Respiratory distress occurred in 95% of cases, mainly due to hyaline membrane disease (86.7%). PDA was symptomatic in 80% of infants. First-line treatment resulted in clinical improvement in 77% and ductal closure in 83.3% of cases, most within 3 days. Predictors of successful closure included gestational age [&ge;] 28 weeks (OR = 5.9; 95% CI : 1.7-20.2) and antenatal corticosteroid exposure (OR = 1.2; 95% CI : 1.0-1.6). Overall mortality was 35% and was significantly higher in infants < 28 weeks (OR = 5.0; 95% CI : 2.4-10.3). Clinical improvement (OR = 3.7) and echocardiographic closure (OR = 4.5) after first-line treatment were associated with reduced mortality. ConclusionsPDA in preterm infants is associated with substantial morbidity and mortality, particularly in those born before 28 weeks of gestation. Early diagnosis, antenatal corticosteroid exposure, and timely pharmacological treatment may improve outcomes. Systematic echocardiographic screening in high-risk neonates should be considered.

Female genital cutting (FGC) is identified within global health and human rights discourse as aligned with gender inequality and female disempowerment. The persistence of FGC in high-prevalence societies is assumed to reflect womens limited influence over decisions concerning their daughters. Yet anthropological research has questioned whether this interpretation adequately reflects how FGC is organized within practicing communities. Across two studies with 176,728 participants from 15 African and Asian countries, we examine whether mothers attitudes toward FGC predict daughters circumcision status and whether this relationship varies with regional FGC prevalence. Multilevel logistic regression models show that maternal attitudes strongly predict daughter circumcision status across both datasets. Contrary to expectations derived from disempowerment frameworks, the association between maternal attitudes and daughter outcomes is not weaker in high-prevalence contexts, it is stronger. These findings suggest that interpretations of FGC as reflecting female disempowerment may mischaracterize the social dynamics of societies in which FGC is common. Policy implications of the findings are discussed.

In the context of global health, the ability of frontline primary health providers to identify potential Drug-Drug Interactions (DDIs) is a critical component of patient safety. This is particularly true in settings like Tanzania, where drug dispensers often serve as the primary point of contact for healthcare. In this study, we establish a baseline for drug decision-making capabilities across multiple cadres of healthcare providers in Kibaha, Tanzania. We specifically distinguish between the ability to recognize safe drug combinations versus harmful ones. The findings reveal a critical asymmetry in provider performance: while professional training improves the recognition of safe combinations, it provides no advantage over lay intuition (and in some cases, a significant disadvantage) in detecting potentially harmful interactions.

Benzalkonium chloride (BAC) is widely used as a disinfectant in cleaning products and is frequently detected in indoor dust. In this study, we assessed dust samples, along with information on cleaning product use, from 24 pregnant participants. Dust samples were analyzed for BAC concentration and microbial tolerance. Different chain lengths of BAC (C12, C14, and C16) were quantified using LC-MS/MS, and bacterial isolates were tested for BAC tolerance using minimum inhibitory concentration (MIC) assays. BAC was ubiquitously detected, with C12 and C14 being dominant. Higher BAC concentrations were associated with reported disinfectant use and increased microbial tolerance. These findings suggest that indoor antimicrobial use may promote microbial resistance, highlighting potential exposure risks in indoor environments and the need for further investigation into health and ecological impacts.

Background: To investigate the safety and efficacy of CTguided lung nodule localization needles for the preoperative localization of small pulmonary nodules. Methods: A retrospective study was conducted on 102 patients with a total of 113 small pulmonary nodules who underwent preoperative localization at Jinan Fourth People's Hospital from January 2024 to December 2025. Nodule diameter and depth, localization time, the number of pleural punctures, the localization success rate, and postoperative complications (hook dislodgement, hemorrhage, and pneumothorax) were recorded. All patients underwent video assisted thoracoscopic surgery (VATS) after localization. Results: The mean nodule diameter was 0.97{+/-}0.36 cm, the mean depth was 1.26{+/-}0.48 cm, and the mean localization time was 9.8{+/-}3.65 minutes. The hook dislodgement rate was 0.98% (1/102), the intrapulmonary hemorrhage rate was 14.71% (15/102), and the pneumothorax rate was 16.67% (17/102). All pulmonary nodules were successfully resected by VATS at 73.82{+/-}13.83 minutes after localization, and no severe complications occurred. Conclusions: The use of a CTguided lung nodule localization needle for the preoperative localization of small pulmonary nodules decreases the time needed for intraoperative nodule detection and operation time. This strategy is a simple, safe, and accurate preoperative localization method that is worthy of increased clinical use.