BMC Microbiology

Background: Metronidazole (MTZ) is a first-line antibiotic for several enteric infections. Its use is common in low-income countries, where most primary-care consultations are conducted by nurses. However, increasing resistance among some enteric pathogens is a growing concern. Using WHO guidelines, we conducted a register-based cross-sectional study to assess MTZ prescribing practices and their determinants in public and private primary healthcare facilities in South Benin. Methods: We performed a register-based cross-sectional study covering the year 2020 in 11 primary healthcare facilities (5 public and 6 private) in Abomey-Calavi, South Benin, following WHO recommendations. In total, 200 visits per facility were selected using systematic random sampling. The primary outcome was the prevalence of MTZ prescription. Determinants of MTZ prescription were identified using multivariable logistic regression analysis. Results: In total, 2,200 medical visits were analyzed. The median age of patients was 19 years, and 57% were female. Antimalarials were prescribed in 52% of visits. Antibacterial agents were prescribed in the majority of visits, with MTZ being the second most frequently prescribed antibiotic (18%), after aminopenicillins (27%). In multivariable analysis, digestive symptoms (adjusted odds ratio [aOR], 8.65; 95% confidence interval [CI], 6.49-11.6), genitourinary symptoms (aOR, 6.84; 95% CI, 3.18-15.0), and skin lesions (aOR, 2.39; 95% CI, 1.58-3.60) were independently associated with increased odds of MTZ prescription. In contrast, fever (aOR, 0.66; 95% CI, 0.49-0.87), respiratory symptoms (aOR, 0.44; 95% CI, 0.26-0.71), and malaria (aOR, 0.21; 95% CI, 0.15-0.28) were associated with decreased odds. Visits in the private sector were also associated with higher odds of MTZ prescription compared with the public sector (aOR, 2.31; 95% CI, 1.78-3.02). Conclusion: MTZ is the second most commonly prescribed antibiotic in primary care in the study area, with its use largely driven by digestive symptoms. Further studies are needed to assess the appropriateness of this prescription. Additionally, research is warranted to understand better the determinants of higher antimicrobial prescribing in the private healthcare sector.

Digital pathology, coupled with advanced image recognition algorithms, represents a transformative frontier in histopathological diagnosis. This sub-Saharan African laboratorys exploratory study investigates the application of a Convolutional Neural Network (CNN) model, specifically leveraging the VGG16 architecture with transfer learning, for automated analysis and classification of selected gastrointestinal (GIT) and liver tissue samples, incorporating both routine and specialized staining protocols. The study utilized a dataset comprising 114 samples (18 liver, 96 GIT images) derived from archival formalin-fixed paraffin-embedded tissue blocks at University College Hospital, Ibadan, Nigeria. Specialized staining techniques included Alcian Yellow for GIT mucin visualization and Massons Trichrome for liver fibrosis assessment, alongside conventional H&E staining. Model performance was evaluated using statistical methodologies including Wilson Score confidence intervals (CI), Bayesian probability assessment, and effect size analysis. Results reveal a striking dichotomy in model performance. The GIT tissue model achieved perfect classification accuracy (100% test accuracy) with exceptional statistical significance (Z=10.0, p<0.0001), Wilson CI [96.29%, 99.99%], Cohens h=1.571, and Bayesian probability >99.99%. Conversely, the liver tissue model demonstrated diagnostic failure (42.86% test accuracy), with Z=-1.428, p=0.9236, Wilson CI [33.59%, 52.65%], Cohens h=-0.144, and Bayesian probability of 7.64%. This performance divergence correlates with training data availability, as the liver dataset fell far below empirically established thresholds (>100-200 samples) for reliable classification. The liver models failure reveals limitations in transfer learning with insufficient data. These findings underscore critical implications for AI-enhanced digital pathology, demonstrating potential deployment of the GIT model as a promising one that supports tissue-specific model development.

Background: Chest tube infection is one of the complications of the tube thoracostomy. Infectious complications may develop in 2% to 25% of patients who undergo thoracotomy tube placement. The use of prophylactic antibiotics to prevent infections associated with thoracostomy tubes remains a subject of debate. Current practices in managing infections related to tube thoracostomy are hindered by the lack of comprehensive and localised data on the microbial profile and their resistance patterns. Objective: To determine the prevalence of thoracostomy tube infections and associated clinical characteristics among patients treated with a thoracostomy tube at KCMC Zonal Referral Hospital. Methodology: Prospective cohort study done at KCMC Zonal Referral Hospital. Include all patients undergoing thoracostomy tube insertion from September 2024 to April 2025. Results: A total of 84 patients underwent tube thoracostomy during the study time. Of these 22 (26.2%) developed SSI. Out of the 22 samples collected, 17 (77.3%) had positive culture results. The most commonly identified pathogens were Pseudomonas aeruginosa (41.2%) and Staphylococcus aureus (29.4%). The highest overall susceptibility was observed with amikacin, effective against 10 (58.8%) of the tested organisms. The most common resistance was observed against ceftazidime (56.3%) and piperacillin-tazobactam (50.0%). Prolonged chest tube duration (>7 days) was the strongest independent predictor of tube thoracostomy infection. Conclusion: This study revealed a high prevalence of tube thoracostomy infection. Prolonged tube duration and admission to a non-surgical ward care emerge as key risk factors for SSI. These findings underscore the importance of limiting chest tube duration when clinically feasible and ensuring optimal postoperative care environments to minimise the risk of infection.

Background: Ribavirin is a guanosine analogue with clinical antiviral activity against a range of RNA viruses including hepatitis C virus (HCV), respiratory syncytial virus and Lassa virus. Several potential mechanisms of action have been proposed, but there is limited data supporting them clinically. Methods: We studied 196 HCV-infected participants from a trial of short-course directly antiviral therapy (STOPHCV-1) which included a factorial randomisation to ribavirin versus no ribavirin. Deep sequencing of the HCV genome was performed on samples with detectable viremia from three time-points: baseline (n = 191), day 3 of treatment (n = 25) and post-treatment failure (n = 47). Results: Ribavirin exposure significantly increased total mutational load at treatment failure (P = 0.0065) and enriched classical ribavirin-associated transitions, including G->A (P = 0.026) and C[-&gt;]U (P = 0.004), along with other key changes including A->G (P = 0.005), U->C (P = 0.023), C->G (P = 0.010), and U->A (P = 0.026). The resulting mutational signature was broad, not dominated by G-related changes. Region-specific analyses demonstrated this increase was broadly distributed across the viral genome, without strong evidence for protection of specific regions. Non-synonymous to synonymous mutation ratios (dN/dS) rose at day 3 (P = 5.5e-5) before declining at failure (P = 8.5e-7), with trends toward higher dN/dS in the ribavirin group at day 3 (P = 0.06). Conclusions: Ribavirin acts as a potent in vivo mutagen, driving viral populations toward genome-wide diversity rather than selecting a few highly fit drug-resistant clones. These findings support an error-catastrophe model.

BackgroundDelayed tuberculosis (TB) treatment remains a major challenge to TB control and is associated with increased mortality, drug resistance, and onward transmission. Food insecurity may contribute to delayed TB treatment through economic, physical, and psychosocial pathways. Depression and anxiety are also associated with delayed TB treatment and may mediate the relationship between food insecurity and delayed TB treatment. This study examined the association between food insecurity and delayed TB treatment initiation and assessed the mediation roles of depression and anxiety for this relationship among people newly diagnosed with TB. MethodsWe recruited 180 participants newly diagnosed with TB in Gaborone, Botswana. Food insecurity, depression, and anxiety were measured using the Household Food Insecurity Access Scale, PHQ-9, and Zung Self-Rating Anxiety Scale, respectively. Delayed TB treatment was defined as > 2 months since first TB symptoms. Logistic regression was used to examine the association between food insecurity and delayed TB treatment. Causal mediation analysis was conducted to assess the mediating roles of depression and anxiety. ResultsAmong the 180 participants, 45 (25%) experienced delayed TB treatment initiation. Participants with delayed TB treatment had slightly higher median scores for food insecurity (2 vs. 1, p = 0.11), depression (9 vs. 6, p = 0.001), and anxiety (37 vs. 34, p = 0.05). There was insufficient evidence of an overall association between food insecurity and delayed TB treatment initiation (OR = 1.04, 95% CI 0.98-1.11, p = 0.20). Mediation analysis found insufficient evidence of total and direct effects through depression and anxiety. However, there was evidence of significant indirect effect through depression (OR = 1.04, 95% CI 1.01-1.08, p < 0.001) and a borderline indirect effect through anxiety (OR = 1.02, 95% CI 1.00-1.04, p = 0.05). ConclusionMediation analysis revealed associations between food insecurity and delayed TB treatment initiation mediated by depression and anxiety which were not evident in total effects analysis. These findings highlight the importance of considering both socioeconomic and psychological factors in addressing delayed TB treatment. Further studies are needed to confirm these pathways.

Mycetoma is a neglected tropical disease caused by various bacterial and fungal pathogens that has a significant health impact across a broad geographically defined "mycetoma belt" spanning South America, Africa and Asia. Histologically, mycetoma is characterised by invasive and destructive granuloma development in the skin, deep tissues and bone, leading to tissue destruction, deformities and high morbidity. The presence of macroscopic, highly compacted pathogen microcolonies, or "grains," is a key diagnostic feature, and the formation of grains supports pathogen persistence and disease chronicity. However, there is a paucity of information on immune responses in mycetoma patients and on the relative importance of phylogeny and/or grains in establishing the local immune landscape. Here, we used spatial proteomics to examine the distribution of 43 immune-related proteins in surgical biopsies from 11 patients with mycetoma of bacterial (Actinomycetoma; Actinomadura pelletierii and Streptomyces somaliensis; n=6) and fungal (Eumycetoma; Madurella mycetomatis; n=5) origin. Using mixed-effects modelling, an exploratory analysis across species and pathogen classes revealed few significant differences in immune marker expression. In contrast, and independently of pathogen class, the cellular infiltrate closest to grain boundaries had higher per-cell expression of CD66b+, ARG1, and VISTA. The preferential accumulation of CD66b+ARG1+VISTA+ cells at grain boundaries was confirmed by quantitative immunofluorescence analysis. Hence, the local tissue microenvironment surrounding the mycetoma grain represents a specialised immunosuppressive niche, with parallels to the tumour microenvironment.

Antimicrobial resistance (AMR) is a growing global public health threat that complicates the treatment and control of bacterial infections. Shigella spp., a leading cause of bacterial diarrhea worldwide, has increasingly exhibited resistance to multiple antimicrobial agents that are commonly recommended therapy for severe shigellosis. Although conventional antimicrobial susceptibility testing (AST) remains the reference standard, it is time-consuming and provides limited insight into the genetic mechanisms underlying resistance. Whole-genome sequencing (WGS) has emerged as a complementary approach for AMR detection by enabling direct identification of resistance genetic determinants encoded in bacterial genomes. Machine learning (ML) methods applied to genomic features such as k-mers have shown promise for predicting resistance phenotypes from WGS data; however, applications to Shigella remain limited. In this study, we developed and evaluated an interpretable ML framework for predicting ciprofloxacin resistance using k-mer features derived from WGS data of 1,424 Shigella isolates collected in Ontario, Canada, between 2018 and 2025. K-mers were extracted from known gene targets associated with ciprofloxacin resistance, including chromosomal quinoline resistance-determining regions (QRDRs: gyrA and parC) and plasmid-mediated determinants (qnr). Supervised ML approaches were trained and compared. We evaluated the influence of k-mer lengths (k=11, 15, 21 and 31) on predictive performance and model interpretability; and compared models based on chromosomal determinants alone and models incorporating both chromosomal and plasmid-mediated determinants. Randon Forest classifier achieved the most consistent performance across models. Inclusion of plasmid-mediated determinants improved predictive accuracy relative to chromosomal-only models. Although differences across k-mer lengths were modest, k = 11 produced the highest area under the receiver operating characteristic curve (AUC) and the lowest Brier score. SHAP analyses localized high-impact features within QRDRs of gyrA and parC, supporting biological interpretability. These findings demonstrate that biologically-informed k-mer-based ML models can accurately and transparently predict ciprofloxacin resistance in Shigella, supporting their potential integration into genomic AMR surveillance and digital public health frameworks. Author summaryIn this study, we used genome sequencing data to develop machine learning models that predict ciprofloxacin resistance for Shigella directly from bacterial DNA. We focused on small DNA fragments (k-mers) derived from known resistance genes and mutations. Among the approaches tested, a Random Forest model showed the most consistent performance. Combining chromosomal mutations with plasmid-mediated resistance genes improved prediction accuracy and helped identify key genetic regions associated with resistance. These findings demonstrate that machine learning applied to genomic data can accurately and interpretable predict antibiotic resistance, supporting its potential use in genomic surveillance and public health monitoring.

Standard in vitro antimicrobial susceptibility testing (AST) using Mueller-Hinton broth (MHB) does not reflect infection-site conditions, and its results often do not correlate with therapeutic outcomes. Here, we compared the antibiotic susceptibility of methicillin-resistant Staphylococcus aureus (MRSA), a common chronic wound pathogen, in simulated wound fluid (SWF) resembling wound exudate versus MHB, revealing discordant AST results across six of nine tested antibiotic classes. The most significant were 128-fold increased resistance to tetracyclines and 256-fold sensitization to {beta}-lactams in SWF. Tetracycline resistance was mediated by MntC, an extracellular manganese-binding protein, whereas {beta}-lactam sensitization was driven by cell envelope remodelling in SWF. Galleria mellonella wound infection results matched the SWF susceptibility phenotypes, suggesting SWF better predicts in vivo wound infection therapeutic outcomes. These comprehensive phenotypic and mechanistic insights into MRSA antibiotic responses under wound-infection-mimetic conditions with direct in vivo validation identify a potential new antibiotic adjuvant target and may guide improved antibiotic therapy for MRSA wound infections.

BackgroundTo date, accessible diagnostic tools to identify whether a patients pneumonia is a bacterial, or viral infection, are not accurate or timely enough to prevent preemptive antibiotic administration. Relying on single biomarkers or clinical presentations has been insufficient. We aimed to incorporate a wide range of novel biomarkers and clinical presentations in a multivariable model and validate its capacity to differentiate cases of bacterial and viral pneumonia. MethodsData from 457 children aged 2-59 months, admitted to Kilifi County Referral Hospital, Kenya, with bacterial (n = 229) and viral (n = 228) infections, were used to develop and validate a predictive multivariable Poisson regression model to differentiate pneumonia etiology. The Receiver Operating Characteristic curve was used to assess biomarker performance and validate the model internally. ResultsSixty-three percent (63%) of the children presented with severe pneumonia. 72% with viral pneumonia had severe pneumonia, compared to 54% with bacterial pneumonia who had severe pneumonia. In crude analyses, chest-wall indrawing, cough, convulsions, crackles, angiotensinogen, and Serpin Family A Member 1 were significantly associated with pneumonia etiology, controlling for age. However, only chest-wall indrawing remained significant in multivariable analyses after controlling for age. The model demonstrated fair, but inadequate, discrimination, with an Area Under the Curve of 0.61. ConclusionAmong the children admitted to hospital with WHO defined pneumonia, a wide range of biomarkers and clinical presentations still failed to distinguish bacterial from viral pneumonia.

Background: Reusable menstrual products provide sustainable and cost effective alternatives to disposable sanitary products; however, their adoption remains limited, even among healthcare professionals. Objectives: To assess awareness, knowledge, perceptions, and utilisation of reusable menstrual products among female medical students and healthcare professionals, and to identify predictors of willingness and use. Design: Cross sectional analytical study. Setting: An online survey was conducted among female medical students and healthcare professionals in Nigeria. Participants: A total of 203 female respondents aged 15 to 55 years. Intervention: Not applicable. Primary Outcome Measures: Utilisation of reusable menstrual products and willingness to adopt their use. Secondary Outcome Measures: Awareness, knowledge, perceptions, and barriers. Methods: Data were collected using a structured questionnaire and analysed using descriptive statistics, chi square tests, and logistic regression. Results: Awareness was high (96.06%), but utilisation was low, with 5.42% ever using and 4.43% currently using reusable products. About 31.53% were willing to use them. Respondent type was not associated with willingness (p = 0.735), although healthcare professionals had higher knowledge (p = 0.024). Positive perception predicted willingness (AOR = 7.58, 95% CI: 3.18 to 18.03, p < 0.001). Good knowledge (AOR = 14.96, p = 0.014) and increasing age (AOR = 1.28, p = 0.004) predicted utilisation. Conclusion: Despite high awareness, utilisation remains low. Perception influences willingness, while knowledge drives use. Targeted behavioural and educational interventions are needed. Keywords: Menstrual hygiene, reusable menstrual products, menstrual cup, sustainability, healthcare professionals

Background Five-biomarker-defined hypervirulent Klebsiella pneumoniae (hvKp) causes invasive infections, but its burden in bloodstream infections versus classical K. pneumoniae (cKp) is unclear. Methods This retrospective cohort study at a tertiary hospital in Japan included K. pneumoniae bloodstream infection episodes from January 2022-December 2024. hvKp was defined by the presence of all 5 genotypic biomarkers (rmpA, rmpA2, iucA, iroB, and peg-344). The primary outcome was abscess complications, and secondary outcomes were length of stay and antibiotic duration. Whole-genome sequencing was performed for 164 isolates. Results Among the 207 episodes, 28 (14%) were of hvKp. Abscess complication occurred in 17 (61%) hvKp versus 23 (13%) cKp episodes (adjusted odds ratio 10.7; 95% CI, 4.36-26.2). Median length of stay in hvKp versus cKp was 28 versus 14 days (adjusted ratio 1.60; 95% CI, 1.18-2.16) and median antibiotic duration was 43 versus 14 days (adjusted ratio 2.13; 95% CI, 1.64-2.77). These associations were attenuated after adjusting for abscess-related complications. No significant difference in 30-day mortality was observed, although the study was underpowered. Multidrug resistance was less frequent in hvKp strains than in cKp strains (11% vs. 30%; P = .040). Among the sequenced hvKp episodes, abscess rates varied across lineages, from 9 of 10 in ST23 to 1 of 4 in ST412. Conclusions Five biomarker-defined hvKp strains delineated a bloodstream infection subgroup with frequent abscess complications and prolonged care. hvKp and cKp present distinct clinical challenges; diagnostic tools distinguishing these subgroups may aid abscess evaluation and source control.

Orphan genes, lacking homologs in other species, are systematically found across genomes. Their presence may result from extensive divergence from pre-existing genes or from de novo gene birth, which occurs when a gene emerges from a previously non-genic region. In this study, we identified orphan genes in the genomes of globally distributed plant-parasitic nematodes of the genus Meloidogyne and investigated their origins, evolution, and characteristics. Using a comparative genomics framework across 85 nematode species, we found that 18% of Meloidogyne genes are genus-specific, transcriptionally supported orphans. By combining ancestral sequence reconstruction and synteny-based approaches, we inferred that 20% of these orphan genes originated through high divergence, while 18% likely emerged de novo. Proteomic and translatomic evidence confirmed the translation of a subset of these genes, and feature analyses revealed distinctive molecular signatures, including shorter length, signal peptide enrichment, and a tendency for extracellular localization. These findings highlight orphan genes as a substantial and previously underexplored component of the Meloidogyne genome, with potential roles in their worldwide parasitism.

In this work, the impact of outliers on the performance of machine learning and deep learning models is investigated, specifically for the case of histopathological images of colorectal cancer stained with Haematoxylin and Eosin. The evaluation of the impact is done through the systematic comparison of one machine learning model (Random Forests) and one deep learning model (ResNet-18). Both models were trained with the popular NCT-CRC-HE-VAL-100K dataset and tested on the CRC-HE-VAL-7K companion set. Then, a curation process was performed by analysing the divergence of patches based on chromatic, textural and topological features of the training set and removing outliers to repeat the training with a cleaned dataset. The results showed that machine learning models, can benefit more from improvements in the quality of data, than deep learning models. Further, the results suggest that deep learning models are more robust to outliers as, through the training process, the architectures can learn features other than those previously mentioned.

BackgroundEarly-life adversity (ELA) is a risk factor for enduring pain in youth and is associated with alterations in brain morphology and function. However, it remains unclear whether ELA-related neurobiological changes contribute to the development of enduring pain in early adolescence. MethodsUsing data from the Adolescent Brain Cognitive Development (ABCD) Study, we examined multimodal magnetic resonance imaging (MRI) markers in children assessed at baseline (ages 9-11 years) and at 2-year follow-up (ages 11-13 years). ELA exposure was defined at baseline to maximise temporal separation between early adversity and later enduring pain. Participants with enduring pain at follow-up (n = 322) were compared to matched pain-free controls (n = 644). Structural MRI, diffusion MRI (fractional anisotropy, mean diffusivity), and resting-state functional connectivity data were analysed. Linear models tested main effects of enduring pain, ELA, and their interaction on brain metrics, controlling for relevant covariates. ResultsELA exposure was associated with smaller caudate and nucleus accumbens volumes, and reduced surface area of the left rostral middle frontal gyrus. No significant effects of enduring pain or ELA-by-enduring pain interaction were observed across grey matter, white matter, or functional connectivity measures. ConclusionsELA was associated with alterations in fronto-striatal regions in late childhood, but these changes were not linked to enduring pain in early adolescence. These findings suggest that ELA-related neurobiological alterations may represent early markers of vulnerability rather than concurrent correlates of enduring pain. Longitudinal follow-up is needed to determine whether these alterations contribute to later chronic pain risk.

BackgroundNegative symptoms are core features of schizophrenia that relate strongly to functional impairment, yet interventions targeting these symptoms remain largely ineffective. Emerging theoretical work highlights how environmental factors may shape and maintain negative symptoms. Although racial disparities in schizophrenia diagnosis among Black Americans are well documented and linked to racial stress and psychosis, the impact of racial stress on negative symptoms has not been examined. This study provides an initial test of a novel theory proposing that racial stress - here measured by racial discrimination - influences negative symptom severity through exacerbation of negative cognitions about the self, particularly defeatist performance beliefs (DPB). Study DesignParticipants diagnosed with schizophrenia-spectrum disorder (SSD) (N = 208; 80 Black, 128 White) completed the Positive and Negative Syndrome Scale (PANSS), the Defeatist Beliefs Scale, and self-report measures of subjective racial and ethnic discrimination (Racial and Ethnic Minority Scale and General Ethnic Discrimination Scale). Relationships among variables were tested using linear regression and mediation analysis. Study ResultsBlack participants exhibited significantly greater total and experiential negative symptoms than White participants with no group difference in DPB. Racial discrimination explained 46% of the relationship between race and negative symptoms. Among Black participants, higher DPB were associated with greater negative symptom severity. Discrimination was positively related to both DPB and negative symptoms. DPB partially mediated the relationship between discrimination and negative symptoms. ConclusionsFindings suggest that racial stress contributes to negative symptom severity via defeatist beliefs among Black individuals, highlighting potential targets for culturally informed interventions.

Background During Nigeria's largest recorded diphtheria outbreak, hospital capacity in Kano State was rapidly overwhelmed. Medecins Sans Frontieres introduced home-based care (HBC) for patients with mild disease to prioritise facility-based care for severe cases. We assessed whether HBC was non-inferior to facility-based treatment in terms of mortality, sequelae, and household transmission. Methods We conducted a retrospective matched cohort study. Mild diphtheria cases treated between January 2023 and May 2024 were matched 1:1 by treatment modality (HBC or diphtheria treatment centre [DTC]) on sex, age group, vaccination status, and residence. Conditional logistic regression estimated the association between treatment modality and mortality, with robustness assessed through propensity score weighting, sensitivity analyses, and E-value computation. Findings Of 990 sampled patients, 678 (367 HBC, 311 DTC) were enrolled (68.5%). After adjustment, treatment modality was not independently associated with mortality (HBC vs. DTC: aOR 0.40, 95% CI 0.13-1.30), with similar estimates across sensitivity analyses (E-value 4.40). Clinical complications were the strongest predictor of death (aOR 23.1, 95% CI 1.73-307). Vaccination was protective (aOR 0.28, 95% CI 0.08-0.94) and treatment delay of four or more days increased mortality (aOR 4.15, 95% CI 1.23-14.0). HBC was not associated with increased household transmission or long-term sequelae. Interpretation Vaccination and early treatment, rather than care setting, were the main determinants of survival. When supported by clinical triage and structured follow-up, decentralised care can be used to manage mild cases during diphtheria epidemics in settings with constrained hospital capacity.

Background Higher levels of sedentary behaviour, such as leisure screen time (LST), and lower levels of physical activity are associated with diseases across multiple body systems which contribute to a large global health burden. Whether these associations are causal is unclear. The primary aim of this study is to investigate the causal effects of higher LST (given greater power) and, secondarily, lower moderate-to-vigorous intensity physical activity (MVPA), on a wide range of diseases in a hypothesis-free approach. Methods A two-sample Mendelian randomisation phenome-wide association study was conducted for the main analyses. Genetic single nucleotide polymorphisms (SNPs) were first selected as exposure genetic instruments for LST (hours of television watched per day; 117 SNPs) and MVPA (higher vs. lower; 18 SNPs) based on the genome-wide significant threshold (p < 5*10-8) from the largest relevant genome-wide association study (GWAS). For disease outcomes, we used summary results from FinnGen GWAS, including 1,719 diseases defined by hospital discharge International Classification of Diseases (ICD) codes in 453,733 European participants. For the main analyses, we used the inverse-variance weighting method with a Bonferroni corrected p-value of p [&le;] 3.47*10-4. Sensitivity analyses included Steiger filtering, MR-Egger and weighted median analyses, and data from UK Biobank were used to explore replication. Findings Genetically predicted higher LST was associated with increased risk of 87 (5.1% of the 1,719) diseases. Most of these diseases were in musculoskeletal and connective tissue (n=37), genitourinary (n=12) and respiratory (n=8) systems. Genetic liability to lower MVPA was associated with six diseases: three in musculoskeletal and connective tissue and genitourinary systems (with greater risk of these diseases also identified with higher LST), and three in respiratory and genitourinary systems. Sensitivity analyses largely supported the main analyses. Results replicated in UK Biobank, where data available. Conclusions Higher levels of sedentary behaviour, and lower levels of physical activity, causally increase the risk of diseases across multiple body systems, making them promising targets for reducing multimorbidity.

Objectives: Longer lifespans lead to longer time on retirement, despite the efforts to raise the retirement age. Therefore, it is important to study how the retirement years can be spent without diseases. This study examined socioeconomic and sociodemographic differences in healthy years spent on retirement. Methods: We followed a cohort of retired Finnish municipal employees (N=4231, average follow-up 15.4 years) on national administrative registers for major chronic diseases: cancer, coronary heart disease, cerebrovascular disease, diabetes, asthma or chronic obstructive pulmonary disease, dementia, mental disorders, and alcohol-related disorders. Median healthy years on retirement and age at first occurrence of illness (ICD-10 and ATC-based) in each combination of sex, occupational class, and age of retirement were predicted using Royston-Parmar models. Prevalence rates for each diagnostic group were calculated. Results: Most healthy years on retirement were spent by women having worked in semi-professional jobs who retired at age 60-62 (median predicted healthy years 11.6, 95% CI 10.4-12.7). The least healthy years on retirement were spent by men having worked in routine non-manual jobs who retired after age 62 (median predicted healthy years 6.5, 95% CI 4.4-9.5). Diabetes was slightly more common among lower occupational class women, and dementia among manual working women having retired at age 60-62. Discussion: Healthy years on retirement are not enjoyed equally by women and men and those who retire early or later. Policies aiming to increase the retirement age should consider the effects of these gaps on retirees and the equitability of those effects.

The global ambition to end the human immunodeficiency virus (HIV) epidemic requires understanding which system-level policy levers, enacted under the framework of Universal Health Coverage (UHC), are most effective in achieving both transmission reduction and diagnostic coverage. This study addresses an important evidence gap by quantifying the within-country association between measurable UHC policy indicators and the estimated rate of new HIV infections across nine Southeast Asian countries between 2013 and 2022. Employing a Fixed-Effects panel data methodology, the analysis controls for time-invariant national heterogeneity, ensuring reliable estimates of policy impact. We found that marginal changes in total current health expenditure (CHE) as a percentage of gross domestic product (GDP) were not statistically significantly associated with changes in HIV incidence. However, increases in the UHC Infectious Disease Service Coverage Index were statistically significantly associated with concurrent reductions in HIV incidence (p < 0.001), suggesting the efficacy of targeted service implementation as the principal driver of curbing new HIV infections. In addition, the UHC Reproductive, Maternal, Newborn, and Child Health Service Coverage Index exhibited a statistically significant positive association with changes in HIV incidence (p < 0.01), which is interpreted as a vital surveillance artefact resulting from expanded detection and reporting of previously undiagnosed HIV cases. Furthermore, out-of-pocket (OOP) health expenditure as a percentage of CHE showed a counter-intuitive negative association with changes in HIV incidence (p < 0.01), suggesting this metric primarily shows ongoing indirect cost burdens on the established patient cohort, or, alternatively, presents a diagnostic access barrier that results in lower case finding. These findings suggest that policymakers should prioritise investment in targeted infectious disease service efficacy over aggregate fiscal commitment and utilise integrated sexual health platforms for strengthened HIV surveillance and case identification.

Human papillomavirus (HPV) testing is the primary method for cervical cancer screening, and a negative HPV test is associated with a very low subsequent risk of invasive cancer. Nevertheless, a small number of cervical cancers are diagnosed following an HPV-negative testing result, posing challenges within HPV-based screening pathways. Using nationwide Swedish registry data of HPV testing, we identified women diagnosed with invasive cervical cancer between 2019 and 2024 and reconstructed HPV testing histories from the National Cervical Screening Registry (NKCx). The most recent HPV test prior to diagnosis was defined as the index test, and longitudinal HPV testing trajectories were classified among women with an HPV-negative index test. Of 3,000 women diagnosed with invasive cancer, 243 (8.1%) had an HPV-negative index test. These women were older at diagnosis and more frequently diagnosed at advanced stages compared with women with an HPV-positive index test. Most HPV-negative index tests (66.3%) were performed in the peri-diagnostic period (+/- 30 days). Among women with an HPV-negative index test, 52.7% (128/243) had no prior HPV testing recorded, while the remainder had consistently HPV-negative histories (33.3%, 83/243) or evidence of prior HPV positivity before the index negative test (14%, 32/243). Possible recurrent HPV positivity following an intervening negative test was rare (0.4%, 1/243). HPV-negative screening results preceding invasive cancer reflect heterogeneous screening histories and cannot be explained solely by test failure. Findings highlighting the importance of reaching women earlier in screening programs and show that fluctuating HPV detectability is rare.