Wellcome Open Research

Objectives To characterise COVID-19 inpatients with and without bacterial/fungal preceding, co- and secondary infections, and describe the distribution of organisms associated with COVID-19 and antibiotic use. Methods We linked ISARIC/WHO CCP-UK data from hospitals in England (admissions 01/01/2020-18/10/2021) with UK Health Security Agency infections datasets of COVID-19, and bacterial- and fungal-positive specimens using a multi-step hierarchical algorithm. We retained those aged >18 years and categorised COVID-19-associated infection as preceding (2-28 days prior to SARS-CoV-2 PCR positive date), co-infection ({+/-}1 day) or secondary (2-28 days after). Results During the study period, there were 173,947 hospitalised episodes of COVID-19; 5.8% (n=10,017) with a bacterial or fungal preceding, co- or secondary infection. Preceding and co-infections were rare (preceding: 0.7%; co-infection: 1.5%) while secondary infections were more common (3.5%). Escherichia coli (29.6%) and Staphylococcus aureus (15.2%) were the most identified organisms in blood specimens, while S. aureus (22.9%) and Pseudomonas aeruginosa (20.4%) were most common in lower respiratory tract specimens. The 28-day case fatality rate (CFR) remained static (36%) in those with secondary infection, whereas it decreased between early 2020 and mid-2021 in the other infection groups (37% to 27%). Of those with no positive microbiology, 72.8% received antibiotics, though this decreased between January-June 2020 (77.6%) and April-October 2021 (62.6%). Conclusion Bacterial and fungal infections complicated approximately 1-in-17 hospitalised episodes of COVID-19, with CFR of >25%. Antibiotic prescribing was common in those without firm evidence of bacterial infection. We recommend adhering to NICE guidance which discourages empirical antibiotic use for hospitalised COVID-19 patients.

Abstract Background. Enteric hyperoxaluria (EH) causes calcium oxalate kidney stones, oxalate nephropathy, and chronic kidney disease (CKD), and can progress to end-stage kidney disease. It occurs in Crohn's disease (CD), cystic fibrosis (CF), chronic pancreatitis, celiac disease, short bowel syndrome, and after bariatric surgery. Its prevalence in these populations has not been synthesized. Methods. PROSPERO CRD420261364424. PubMed and Embase were searched to 24 August 2026 for studies reporting 24-hour urinary oxalate. Prevalence was pooled using the Freeman-Tukey double arcsine transformation with a DerSimonian-Laird random-effects model; unweighted crude prevalence is also reported. Because heterogeneity was high, the narrative synthesis stratified by testing condition is the primary result. Prespecified subgroups addressed oxalate load before collection, diagnostic threshold, ileal resection, age, and urine collection format. Results. Forty-seven studies were included. In CD (17 studies, 471 patients; 204 with EH), crude prevalence was 43.3% and pooled prevalence 49.3% (95% CI 38.9-59.8; I^2 = 95.3%). With an oxalate load, prevalence was 64.7% (pooled 74.0%, 55.9-88.6) versus 38.6% without (pooled 39.1%, 28.7-50.0). Among CD patients, EH was more frequent with ileal resection (48.8% vs 31.7%; OR 1.62, 0.91-2.89) and with steatorrhea (62.5% vs 29.3%; OR 9.88, 3.81-25.61). In CF (7 studies, 348 patients; 179 with EH), pooled prevalence was 49.8% (40.5-59.1; I^2 = 91.9%). After bariatric surgery (15 studies, 849 patients; 474 with EH), pooled prevalence was 54.7% (45.4-63.9; I^2 = 96.7%). Conclusions. Roughly half of these patients have EH, but the proportion depends heavily on whether an oxalate load precedes urine collection (39% unprovoked vs 65%-74% provoked); because most studies do not state this condition, published prevalence estimates are not directly comparable. Ileal resection and steatorrhea identify those who should be screened.

Healthcare workers face substantial occupational demands and exposure to respiratory infections during winter, but evidence that probiotics improve their health and wellbeing remains limited. This exploratory, double-blind, randomised, placebo-controlled trial assessed whether daily Lab4 supplementation affected upper respiratory tract infection (URTI) frequency and supported wellbeing in 104 healthcare workers. Daily diaries recorded symptoms defining URTI episodes, general-practitioner visits, illness-related work absence and antibiotic use. Wellbeing was assessed at baseline and weeks 8 and 16, and faecal microbiota were assessed using 16S rRNA gene sequencing. Participants receiving Lab4 reported better wellbeing than those receiving placebo. For probiotic versus placebo, the risk ratio (RR) for URTI occurrence was 0.60 (95% confidence interval [CI]: 0.30-1.20; p=0.1477), the incidence rate ratio (IRR) for episodes was 0.58 (95% CI: 0.27-1.23; p=0.1581), and the mean ratio for episode duration was 0.98 (95% CI: 0.72-1.32; p=0.8776). For general-practitioner visits, the RR for at least one visit was 0.48 (95% CI: 0.21-1.07; p=0.0737) and the IRR was 0.44 (95% CI: 0.18-1.06; p=0.0677). For illness-related work absence, the RR for at least one day absent was 0.75 (95% CI: 0.18-3.22; p=0.6991) and the IRR for absence days was 0.74 (95% CI: 0.16-3.32; p=0.6914). For antibiotic use, the RR for any use was 0.48 (95% CI: 0.20-1.18; p=0.1111) and the IRR for antibiotic-use days was 0.42 (95% CI: 0.16-1.12; p=0.0820). No significant between-group differences in gut microbiota were detected in the subset providing faecal samples. Illness-related estimates generally favoured Lab4, although between-group differences were not statistically significant. These exploratory findings support evaluation in a larger, prospectively powered trial.

Objective Although numerous clinical prediction models (CPMs) have been developed to identify pregnancies at risk of serious adverse outcomes, most lack robust external validation, which restricts their reliability in clinical practice. This study aims to systematically review and externally validate existing clinical prediction models for Gestational Diabetes Mellitus (GDM), Pre-eclampsia (PE), Stillbirth, and Small-for-Gestational-Age (SGA) focusing on models for use in pre-conception or early pregnancy. The models were evaluated using a large, representative primary care cohort to assess their performance within a UK population. Method and Analysis A two-stage systematic review identified CPMs for GDM, PE, Stillbirth, and SGA. Eligible models used routinely collected maternal characteristics, fully reported the model equation, and included predictors commonly measured during the preconception or early pregnancy period. Validation was performed using the UK Clinical Practice Research Datalink (CPRD Aurum), including over 1.58 million pregnancies for women aged 14 - 49 between 2000 to 2020. Model performance was assessed through discrimination (C-statistic), calibration-in-the-large (CITL), calibration slope and calibration plot, with pooled estimates across 20 imputations. Results Of 30 studies included, 48 models were identified, comprising 47 binary outcome models and one continuous outcome model, and 23 models used UK cohorts. Models were developed in cohorts comprising 101 to 113,415 participants (median N=5,013). Whilst 29 models have been externally validated, only three have been validated in cohorts including UK population satisfying the requisite sample size. Across all outcomes, most models demonstrated limited generalisability in the UK population. The C-statistic for GDM ranged from 0.29 to 0.77, for PE from 0.42 to 0.71, whilst models for stillbirth and SGA showed weaker discrimination from 0.54 to 0.56 and 0.58 to 0.62, respectively. Models across all outcomes exhibited substantial miscalibration, with calibration-in-the-large ranging from -5.66 to 1.35, and calibration slope from -0.65 to 17.61. Conclusion Existing CPMs for pre-conception and early prediction of adverse pregnancy outcomes showed poor discrimination and frequent miscalibration in a large UK cohort. Whilst some models for SGA had excellent performance, most existing models for GDM, PE, and stillbirth demonstrated suboptimal generalisability, likely a result of differences in population characteristics and outcome prevalence. Therefore, most CPMs evaluated are not suitable for direct implementation in UK clinical practice and require further calibration, updating, even re-development using large, representative data before achieving clinical utility.

ObjectivesRespiratory Syncytial Virus (RSV) vaccine policies have varied globally since their approval in 2023. In the UK, policy has adapted in line with National evidence generation such that from Autumn 2026 at-risk persons [&ge;]65 years old will become eligible for vaccination. Immunosuppressed persons <65 years will still not be offered protection. The objective of this study is to investigate the relative burden of RSV infection by age and immunosuppressed status (IC). DesignRetrospective observational cohort study using routine healthcare data from North West London Integrated Care System. ParticipantsPatients with a confirmed diagnosis of a respiratory viral infection (RSV, Influenza A and B, SARS-CoV2) between October 2021 and July 2025. Main outcomes measuresPrevalence and severity of RSV infection in immunosuppressed persons <65 years old, and to provide a comparative analysis with Influenza and SARS-CoV2 in a sub-cohort tested using a 4-in-1 combined rapid PCR test. ResultsDuring the study period, 1226 patients were diagnosed with RSV of whom 596 (48.6%) were <65 years old. In 1091 patients with clinical data, 341 (31.3%) were IC. Fifty (9.9%) patients <65 years old had severe infection (ICU admission or death within 28 days of diagnosis), of whom 14 (28.0%) were IC. Proportionally, 16.7% of all RSV-associated deaths and 55.1% of all ICU RSV-admissions occurred in adult patients <65 years old. RSV accounted for 665 (10.1%) infections confirmed by 4-in-1 viral PCR testing. Eight-nine (13.4%), 172 (9.3%) and 448 (12.0%) patients with RSV, Influenza A and SARS-COV2 experienced severe infection, of whom 32 (36.0%), 82 (47.7%) and 156 (34.8%) were <65 years old respectively. Eight (25.0%), 20 (24.4%) and 52 (33.3%) of patients <65 years old with severe infection were IC. On adjusted analysis, having an immunosuppressive condition increased the odds of a severe SARS-CoV2 infection, OR (95% CI) 1.36 (1.08-1.71) but not a severe RSV or Influenza infection. ConclusionsSevere RSV infections occur in persons <65 years old, with a significant proportion of patients having an immunosuppressive condition. Urgent research is needed to investigate the potential benefit of extending the current UK RSV vaccine policy to protect younger immunosuppressed adults.

Background and objectives: Industrialisation is associated with lower gut microbial richness. The ecological insurance hypothesis proposes that richer communities buffer disturbance via overlapping functions, possibly affecting infection susceptibility. We state predictions, audit the evidence, and test the richness-infection relationship in Gambian children. Methodology: We analysed 452 children aged 6-35 months with Day 85 stool 16S profiles and dated infections over 113 days. Diversity used Hill numbers (q = 0, 1, 2); redundancy was inferred from reference-genome gene content. We examined associations with illness during follow-up and infections after Day 85, adjusting for earlier illness. Results: Richness was lower in children with any infection (93.9 vs 103.1; d = 0.36; adjusted odds ratio 0.989 per species, p = 0.019); abundance-weighted diversity was not. Most illness preceded sampling (295 of 315); the difference lay in common and intermediate-prevalence species. Richness was lowest around recent illness. Higher richness was associated with fewer later infections (rate ratio 0.69 per SD, 95% CI 0.51-0.93; q = 0.11). Redundancy correlated with richness at q = 0 (rho = 0.93); at q = 1-2 estimates indicated lower infection rates but none survived correction (smallest FDR q = 0.14). Conclusions and implications: Richness and infection were associated in both directions: children who had been ill had lower richness, and greater Day 85 diversity preceded fewer infections. Redundancy was directionally aligned with reduced infection at higher diversity orders, but FDR control and collinearity limit inference. Cohorts sampled before illness, with shotgun data, are needed.

Sepsis is a substantial contributor to neonatal mortality in Africa, with Klebsiella pneumoniae as the leading causative pathogen. Incorporating molecular tools such as whole genome sequencing (WGS) into routine surveillance of important bacterial pathogens, including those causing neonatal sepsis, can support targeted deployment of infection prevention and control measures and treatment interventions. This study aimed to understand the current practices and capacity for culture, identification and genomic analysis of bacterial pathogens in Africa, with a particular focus on K. pneumoniae, to support standardised genomic surveillance. A cross-sectional online survey was distributed to various clinician and scientist networks across Africa. All respondents completed a demographics section, while sections on laboratory test capacity, blood culture practices, WGS, and bioinformatics analysis were completed based on experience in these aspects. Responses were received from 52 institutions in 25 African countries. Among 51 institutions completing the laboratory test capacity section, 61% reported performing blood cultures, with the majority using manual commercial biochemical systems for species identification (71%) and manual disk diffusion for antibiotic susceptibility testing (82%). Participating institutions reported near-universal access to a -80{degrees}C freezer, centrifuge and thermocycler, but shaking incubators were less commonly available (67%). More than half of respondents (54%) indicated that they perform the entire WGS workflow (including DNA extraction, library preparation and WGS) internally, with most performing DNA extraction internally (88%) using column-based kits (70%). Outsourcing was progressively more common at later workflow stages. Infrastructure challenges that limit bioinformatics analysis capabilities were reported by all 23 respondents who completed this question, including limited access to high-performance computing and data storage space. This survey found sufficient capacity to support genomic surveillance of neonatal sepsis pathogens across participating African institutions. However, investments in blood culture, supply chains, sequencing, bioinformatics, and data dissemination capacity are needed to realise its full potential. These findings will support the development of standardised genomic surveillance protocols tailored to the diverse capacities of African laboratories.

Abstract Continuous glucose monitoring (CGM) is recommended for type 1 diabetes, but the supporting evidence derives almost entirely from high-income settings, and the technology is not routinely available in Kenya's public sector. This prospective study assessed the feasibility and sustainability of CGM implementation and changes in glycemic control after three months of use in a public-sector pediatric diabetes clinic in Nairobi. Forty patients aged 4 to 25 years, recruited by proportional quota sampling across age bands at Kenyatta National Hospital, used an intermittently scanned sensor system across five visits combining sensor data review, standardized diabetes education and insulin titration. Glycated hemoglobin (HbA1c) was measured at baseline and three months, alongside sensor-derived glucose metrics, wear time and diabetes-related admissions. Thirty-eight patients (95%) completed the study; median sensor wear time was 89.0%. Adjusted mean HbA1c fell from 10.82% to 9.42%, a difference of minus 1.40 percentage points (95% confidence interval minus 2.07 to minus 0.68). Time in target range (3.9 to 10.0 mmol/L) rose from 32.4% to 38.0%, and time above 10.0 mmol/L fell from 63.1% to 56.9%. Time below 3.9 mmol/L rose minimally, from 3.7% to 4.2%, while time below 3.0 mmol/L did not increase significantly, by 0.2%. Diabetes-related admissions fell from 7 of 40 in the three months before the study to 1 of 38 by its end. The uncontrolled design and small sample preclude an unbiased effect estimate. Since CGM efficacy is established internationally, these data add local evidence of transferability, which national guidelines and benefit-package decisions require.

Aims/hypothesis Higher body mass index (BMI) is associated with higher levels of HbA1c and glucose in conventional observational studies from sub-Saharan Africa, but its causal relationship in this population has not been explored. Mendelian randomization (MR) which leverages genetic variants can strengthen causal inference. However, its application in African ancestry populations is limited. The aim of this study was to determine whether causal effects of BMI on glycated haemoglobin (HbA1c) and random glucose differ between African and European populations. Methods We used two-sample MR to estimate the effects of BMI on HbA1c and random glucose in adults of African and European ancestries. We conducted a cross-ancestry BMI genome-wide association study (GWAS) from the Africa-Wits International Network for the Demographic Evaluation of Populations and Their Health (INDEPTH) Partnership for Genomic Studies (AWI-Gen) dataset of African adults (N=10,476) and the largest BMI GWAS in Europeans (N~700,000). From the cross-ancestry GWAS we identified 428 independent genome-wide significant variants and of those, 363 single nucleotide polymorphisms (SNPs) had consistent direction of effect in both Africans and Europeans. These variants were then used as genetic instruments to proxy BMI for both Africans and Europeans. Primary outcome data for African and European populations were obtained from UK Biobank summary statistics for HbA1c (5,790 Africans and 400,825 Europeans) and random glucose (5,750 Africans and 314,916 Europeans), with additional results for HbA1c from the MAGIC multi-ancestry GWAS comprised of Ugandan individuals (N=4,441), African Americans (N= 6,647), and Europeans (N=146,806). Main analyses used the inverse variance weighted (IVW) method, with sensitivity analyses conducted using MR-Egger, weighed median and weighted mode approaches. Results The main IVW analyses in UK Biobank provided support for higher BMI causally increasing HbA1c levels in both Africans (0.26 SD higher HbA1c per 1 SD BMI, 95% CI 0.07, 0.45) and Europeans (0.27 SD higher HbA1c per 1 SD BMI, 95% CI 0.22, 0.32). UK Biobank main analyses also supported higher BMI increasing random glucose in Africans (0.21 SD higher mean glucose per 1 SD BMI, 95%CI 0.03, 0.37) and Europeans (0.15 SD higher mean glucose per 1 SD BMI, 95%CI 0.12, 0.18). Sensitivity analyses suggested these results were not biased by unbalanced horizontal pleiotropy. Results from MAGIC also showed that higher BMI causally increased HbA1c in Europeans (0.04% higher HbA1c per 1 SD BMI, 95% CI 0.02, 0.05), though results for African Americans (0.01% higher HbA1c per 1 SD BMI, 95% CI -0.05, 0.07) and Ugandans (0.02% lower HbA1c per 1 SD BMI, 95% CI -0.10, 0.05) spanned the null. Conclusion/interpretation We have found broadly similar effects of BMI on HbA1c and random blood glucose in African and European populations. However, much larger GWAS of glycaemic traits in African and other non European populations are needed to strengthen causal inference and support equitable translation of these findings. The method that we have used to obtain identical strong genetic instrumental variables (IVs) for both European and African populations may have value for other MR studies interested in exploring differences in effects between different population groups.

Introduction: In temperate regions, influenza and respiratory syncytial virus (RSV) typically exhibit seasonal epidemics during the winter months, often concurrently with SARS-CoV-2 epidemics. Monitoring past and real-time trends in infection dynamics is important for informing public health situational awareness, including identifying and characterising unusual epidemic activity. However, data used to monitor these trends can exhibit substantial noise including strong day-of-the-week variation in reporting. In addition, case data for influenza can obscure distinct trends in influenza subtypes if not combined with virological data. Aim: By quantifying trends in respiratory virus activity using statistical methods, the Australia-Aotearoa Consortium for Epidemic Forecasting and Analytics (ACEFA) aims to provide government partners with comprehensive epidemic intelligence. Methods: Analyses were performed on daily case time series data for SARS-CoV-2, RSV and influenza across Australia's eight jurisdictions. Past and real-time trends were inferred for each pathogen and each influenza subtype using Bayesian p-spline models. Results: The 2025 Winter Situational Assessment Program provided weekly reports throughout the winter season and during the out-of-season influenza A H3N2 epidemic, driven by the emergence of the novel influenza subclade ('subclade K'). Despite limited subtyping data, our analysis provided an early signal of increasing influenza A H3N2 during a period in which overall influenza cases were decreasing; increases in influenza A H3N2 activity were first detected in July, and by mid-August, increasing H3N2 activity was estimated across all jurisdictions. Discussion: Our analysis highlights the benefits of incorporating statistical methods into real-time epidemic situational assessment and in consolidating reporting across jurisdictions.

Background Population-level administrative data cohorts hold huge potential for generating evidence to improve child health. Understanding the quality of these data is critical to enabling us to fully realise this potential. We aimed to evaluate linkage between children's health, education and social care administrative records (ECHILD) to identify possible sources of bias. Methods We created four cohorts to understand the drivers of inclusion/exclusion within ECHILD. For each cohort, we calculated the linkage rate by counting the total number of eligible individuals who appeared in the ECHILD linkage spine and any of the corresponding hospital/school component datasets. We then assessed whether linkage rates varied according to sociodemographic characteristics (year of birth, sex, ethnicity, region). Results ECHILD currently captures 34.2 million patients and 25.3 million pupils born between September 1984 and March 2023, aged 0-38 years. Over 90% of children with hospital birth records linked to a school record (rising to 93% for those born from 2014 onwards); 88% of children attending school in 2001/02 linked to a patient record (rising to 96% for those born in 2019/20), resulting in a total of 21 million linked individuals. Substantial variation existed between sociodemographic groups, with those living in London, residing in more deprived areas, or with recorded ethnicity other than White being less likely to be included. Conclusions Population-level datasets such as ECHILD often under-represent specific groups. Irrespective of the mechanisms by which individuals are excluded (e.g. opt outs, linkage errors or not interacting with services), those in minoritised ethnic groups and those living in more deprived areas are most affected. Linkage evaluations are critical for understanding who is and who is not included in analyses of these data so that researchers can account for potential sources of bias within analyses.

Background and aims. Inflammatory Bowel Disease (IBD) is a complex immune-mediated condition with a strong genetic contribution. The genetics of IBD are highly complex, with inflammation, autoimmunity, and mucosal immunity pathways involved in its pathogenicity. GenePy is a gene-level disease burden metric. The integration of clinical and genetic data and the application of machine learning methods can aid patient stratification for personalised care. Methods. Lists of consensus IBD pathway genes were curated. GenePy scores were computed from whole exome sequencing data. A K-Means algorithm was optimised using clustering quality and stability metrics on the GenePy scores of genes in each IBD pathway, and the results replicated in three independent IBD cohorts (SPARC IBD, MSCCR IBD, and Southampton IBD). Chi-square tests assessed the association between cluster assignment and phenotypic features, and were multiple test corrected via Benjamini-Hochberg FDR. Results. A strong association was replicated for NOD signalling genes driving IBD subtype, Crohns disease behaviour, and IBD surgery across all cohorts, as well as granuloma in Southampton IBD. This was mainly driven by NOD2. Similar genetic clustering patterns were observed across all cohorts, with additional phenotypic enrichment in clusters driven by NLRP1 (surgery in MSCCR IBD), and nominally significant enrichment for disease behaviour linked to BIRC2 (B2 in Southampton IBD and B2B3 in SPARC IBD). Conclusions. This analysis identified a common genetic architecture across NOD signalling genes across IBD cohorts, replicated a signal for NOD2 as a monogenic driver of disease with a strong phenotypic enrichment, and identified other putative genetic drivers of IBD, such as the NLRP1 gene.

Genetic ancestry composition has been used extensively as a predictor of clinical outcomes, multiomic biomarkers, and endophenotypes, but the models have most often used untransformed ancestry fractions as explanatory variables. Under a simplex constraint results from this type of model can be uninterpretable and misleading. We demonstrate the use of multiple transformed log ratio coordinates of ancestral proportions as predictors in a study of excreted myeloperoxidase (MPO), a neutrophilic enzyme used as a fecal biomarker to measure intestinal inflammation and enteropathy. We show how to convert these difficult-to-interpret effects into association results for shifts between two ancestries under an isoancestry constraint (holding an ancestry fraction constant) using post-estimation average marginal effects and explain their geometric interpretation. We found that increasing proportion of African ancestry was associated with increased levels of excreted MPO in low-income household infants in three Northeastern Brazil studies, with a smaller negative secondary association of European ancestry, all under a tri-continental ancestry composition (African, European, Amerindian). While the maximum log(MPO) outcome variance explained by differences in genetic ancestry was modest at a few percent, we show evidence that these differences in heritability were context-dependent on measurement of MPO under active enteric infection. The results were attenuated by socio-economic status, but a signal remained. Overall, we found that African genomes carry additional alleles that enable a more intensive neutrophil response to enteric infection relative to European and Amerindian genomes, illuminating a possible host genetic background role in modulating immune response to enteric diseases and pathogens.

Background: Genetic and observational studies have identified metabolic factors potentially contributing to the risk of Major Depression (MD). However, studies to date have concentrated on common genetic variants, many of which are in linkage disequilibrium. This makes it difficult to localise variants to a single gene. To overcome this, we used short read whole-genome sequenced datasets (srWGS) to conduct a targeted rare variant association analysis of the FADS region, which has previously been implicated in metabolic effects on MD. Methods: Using srWGS data from 740,373 individuals from All of Us (AoU) and the UK Biobank (UKB) we tested for associations between rare variants in the FADS region and MD. Additionally we conducted association tests between rare FADS variants and five blood-based metabolites implicated by previous studies of MD. Finally, we applied Mendelian randomisation to identify causal effects of metabolites on MD using rare-variants. Results: We found FADS rare variants were significantly associated with all tested metabolites, but not with MD. Using Wald-Ratio MR we found a putative causal effect of Docosahexaenoic acid (DHA) on MD using a rare-variant instrument in the FADS2 gene. Conclusion: Our study represents the largest rare-variant analysis of MD to date. However, the lack of associations between FADS rare-variants and MD suggests our analysis is underpowered, or that genetic effects on MD are conferred substantially by higher frequency variants. Rare-variant MR suggested a causal effect of DHA on MD, and implicates the FADS2 gene.

We used Scopus data on 243949 top-cited scientists to map scientific cosmopolitanism defined as having at least two different countries that contribute alone at least 10 percent of an author published record as indexed in Scopus. 20.4 percent of the top-cited authors were cosmopolitan based on this definition. Based on current author affiliation, rates varied widely from 9% to 76% across countries with at least 250 top-cited authors. Countries with few top-cited authors had almost always high rates of cosmopolitanism. The proportion of top-cited authors who are cosmopolitan has steadily increased over time in younger generations among those who started publishing after 1965 reaching 43% recently. Large differences were also seen across scientific subfields from 1% in General Psychology and Cognitive Sciences to 46% in Econometrics. Across the 30 country pairs that were most over-represented, countries shared borders, languages, most common religion pairs, or any of these features in 15, 19, 26, and 29 cases, respectively. The map of cosmopolitan authors reveals a large and increasing proportion of the most influential scientists who share two or more scientific homes that each has made a substantial contribution to their career. Cosmopolitanism among scientists requires better study to help facilitate its potential positive contributions not only to individual scientists but to science and society more broadly.

Background. Safely managed drinking-water monitoring under Sustainable Development Goal target 6.1 uses source-water quality, yet Escherichia coli is common in household drinking water in Bangladesh despite near-universal improved sources. We compared source and household point-of-use (POU) E. coli detection within households and estimated how the safely managed estimate changes if POU replaces source E. coli. Methods. Cross-sectional secondary analysis of the Bangladesh MICS 2025 water-quality subsample (February-June 2025; detection >=1 colony-forming unit/100 mL). We classified 5,944 households with readable paired results into four joint patterns and, exploratorily, examined POU detection among negative-source households and two-week diarrhoea in children under five with survey-weighted modified Poisson models. Results. E. coli was detected in 47.4% of source and 84.8% of POU samples; only 12.7% of households were negative at both. Among negative-source households, 75.8% had E. coli in household water, versus 94.7% with a detected source, persisting (33.3%) even direct from the source. The JMP-aligned safely managed estimate was 42.5% (95% CI 40.8-44.1); substituting POU for source E. coli gave 12.6% (11.4-13.8), not an SDG indicator estimate. The diarrhoea prevalence ratio for POU detection (1.04, 0.59-1.86) was too imprecise to interpret. In exploratory spatial analysis, POU detection clustered geographically (Moran's I 0.16 cluster level, 0.31 district level, both p<0.001) and was independently associated with lower elevation (odds ratio 0.62, 0.56-0.70) and longer travel time to healthcare (1.65, 1.29-2.12); five districts had complete detection among 84-94 households tested. Conclusions. Source and POU classifications differed substantially; the survey cannot show where or when contamination occurred. Contamination was spatially clustered, arguing against pure noise and pointing to districts for follow-up. The findings support evaluating standardised POU sampling as a complement to source-based monitoring, with targeted follow-up and cross-season, cross-country replication.

Homozygosity for the HBB codon 8/9 (+G) frameshift (c.27dup (p.Ser10ValfsTer14)) causes transfusion-dependent {beta}-thalassaemia and is common in South Asia. Prime editing can reverse this insertion without double-strand breaks or donor DNA, but its efficiency depends on pegRNA design. We derived Sendai-reprogrammed iPSCs from a homozygous patient, optimised PEmax editing (spacer, pegRNA extension, secondary nick, MLH1dn) and compared patient, PEmax-treated and control iPSC-derived erythroid cells by flow cytometry, colony assays, RT-qPCR, western blotting and cation-exchange HPLC. Patient iPSCs had a normal 46,XY karyotype, expressed pluripotency markers, formed all three germ layers and were Sendai-free by passage 15. A PAM-disrupting spacer with a +68 nicking sgRNA gave the highest intended-edit frequency 8.4%; MLH1dn added little. PEmax-treated cultures matured and formed colonies more like control than patient cultures, restored HBB transcript (about 4-fold control iPSC-derived cells) and detectable {beta}-globin protein, and contained an HPLC fraction consistent with HbA ( undetectable in patient cells). Fetal haemoglobin (about 80%) and embryonic globin remained predominant. Prime editing corrects HBB c.27dupG in patient iPSCs and restores {beta}-globin expression, with partial restoration of adult haemoglobin in a fetal/embryonic-type erythroid background. Validation in additional donors, haematopoietic stem cells and in vivo is required.

BackgroundHuman Mastadenovirus B (HAdV-B) causes ocular and respiratory infections and is capable of causing outbreaks in healthcare settings. HAdV-B114, a recombinant genotype only formally recognised in 2023, has been reported predominantly from Germany, the USA, China and Japan; genomic data from UK clinical settings remain limited. This study analysed 68 HAdV-B whole genomes from ocular and respiratory-associated samples collected at a Nottingham hospital across the pre- and post-COVID-19 restriction periods (2017-2023). MethodsClinical samples typed positive for HAdV-B by partial hexon Sanger sequencing were selected for whole-genome sequencing using a novel overlapping PCR amplicon strategy, sequenced on the Oxford Nanopore Technologies PromethION platform. Phylogenetic and pairwise difference analyses were used to characterise genotype composition and genomic relatedness. SimPlot and amino-acid comparison characterised divergence between sub-lineages. ResultsWhole-genome phylogenetics confirmed that two species B genotypes were detected in Nottingham University Hospitals between 2017-23: HAdV-B114 (n=56) and HAdV-B7 (n=12). HAdV-B114 was detected before and after COVID-19 restrictions, with an increase in 2022-2023, consistent with post-restriction expansion of a pre-existing lineage. Pairwise difference analysis identified 24 genomically identical B114 sequences; associated metadata argued against a single nosocomial transmission chain interpretation, with the pattern more consistent with repeated detection of a widely circulating community strain, with the possibility of localised onward transmission. Within the B114 clade, multiple monophyletic groups were identified by whole-genome phylogenetics. ConclusionsThis study adds whole-genome resolution to the existing UK HAdV-B114 data, demonstrates the utility of WGS for clinical adenovirus surveillance and shows the benefits of combining epidemiological data with genomic analysis.

OBJECTIVE: Sepsis-associated encephalopathy (SAE) and sepsis-associated delirium (SAD) lack confirmatory laboratory tests or biomarkers. We evaluated whether the Th17/interleukin (IL)-17 axis or neuroglial-injury biomarkers reflect acute brain dysfunction beyond systemic inflammation and whether biomarker profiles differ between these phenotypes. DATA SOURCES: EMBASE, MEDLINE/PubMed, and the Cochrane Library from inception to August 1, 2026, supplemented by backward and forward citation searching, following PRISMA 2020. STUDY SELECTION: Observational studies of adults with sepsis classified by SAE or SAD status and reporting circulating biomarker concentrations by neurological group or biomarker-outcome associations. Eighteen studies (2,388 participants; 1,863 with sepsis) were included. DATA EXTRACTION: Two reviewers independently extracted study, phenotype, assay, and outcome data. Risk of bias was assessed with the Newcastle-Ottawa Scale and certainty with GRADE. DATA SYNTHESIS: Random-effects models pooled standardized mean differences (SMDs) separately against non-septic and septic controls and odds ratios (ORs) for biomarker-outcome associations. IL-6 was the only mediator elevated in both comparative frameworks and associated with outcomes (non-septic controls: SMD, 0.54 [0.25-0.82]; septic controls: SMD, 1.05 [0.51-1.59]; OR, 1.85 [1.50-2.29]). S100B, neuron-specific enolase, IL-10, tumor necrosis factor; and interferon-gamma; were elevated versus septic controls, whereas IL-17 was modestly elevated only versus non-septic controls (SMD, 0.37 [0.01-0.73]). The IL-6 septic-control effect was concentrated in SAE (p<0.0001) and remained robust in leave-one-out and risk-of-bias sensitivity analyses. Certainty was low to very low, and all 14 computable prediction intervals included the null. CONCLUSIONS: IL-6 emerges as the leading circulating candidate biomarker of sepsis-associated brain dysfunction, while S100B and NSE capture neuroglial injury beyond sepsis. Current evidence does not establish a discriminating role for the Th17 axis. Future studies require standardized neurological phenotyping and appropriately matched septic controls to establish diagnostic value.

Background: Unpaid caregiving is a recognised social determinant of health, yet most research treats it as a fixed exposure measured at a single time point, and little is known about how patterns of caregiving transitions relate to health behaviours. Methods: Secondary analysis of the UK Household Longitudinal Study (waves 2 to 13, approximately 2010 to 2023; n=25,049). Latent class analysis was applied to binary caregiving status across 12 waves to identify caregiving trajectories. Associations between trajectories and four health behaviours (physical inactivity, fruit and vegetable consumption, problematic drinking, current smoking) at waves 7 to 13 were estimated using logistic and linear regression, adjusting for sociodemographic, health and baseline behavioural confounders. Results: An eight-class solution identified a non-caregiving class comprising 62.9% (n=15,760) of the sample. Among caregivers (n=9,289), trajectories were Temporary (20.0%), Former-short (20.2%), Former-long (10.9%), Emerging-short (15.4%), Emerging-long (11.6%), Long-term (15.7%) and Recurrent (6.3%). In fully adjusted models, Recurrent caregivers had higher odds of smoking (OR=1.67, 95%CI: 1.17 to 2.40) compared with non-caregivers but lower odds of physical inactivity (OR=0.65, 95%CI: 0.53 to 0.81) and problematic drinking (OR=0.75, 95%CI: 0.59 to 0.94). Associations for other trajectory classes were largely attenuated after adjustment. Conclusion: The pattern and timing of caregiving transitions are an under-explored dimension of the caregiving experience. Recurrent caregivers had a distinctive profile, with elevated smoking but lower physical inactivity and problematic drinking. Recurrent caregiving should be recognised alongside intensity and duration, and support systems better equipped for people who move into and out of care repeatedly.