Tag: pubmed

Qual Manag Health Care. 2026 Aug 12. doi: 10.1097/QMH.0000000000000577. Online ahead of print.

ABSTRACT

Social risk strongly influence diabetes control and contribute to inequity in diabetes care. We aimed to improve and sustain health-related social needs (HRSNs) screening of patients with diabetes from 0 to >50% over a 2-year period at multiple clinic sites within a pediatric hospital center. Using a multidisciplinary team and quality improvement techniques, we implemented and maintained an intervention over a 2-year period to screen for HRSNs and connect those with positive screens to local resources. We used statistical process control to assess change over time. Screening for HRSNs increased from 0% to 68% within 3 months and was maintained at a mean of 62% for the subsequent 20 months. Overall, 9026 screens were completed, with 956 (11%) positive for HRSNs. Of those, 146 (15%) requested direct assistance with connecting to resources, 507 (47%) requested resources to self-navigate, and 305 (32%) declined wanting assistance. Less than 1% of screens (n = 48) required urgent intervention from clinical social workers. Implementation of universal HRSN screening within a pediatric diabetes clinic is feasible across multiple clinic locations.

PMID:42607105 | DOI:10.1097/QMH.0000000000000577

PLOS Glob Public Health. 2026 Aug 17;6(8):e0007096. doi: 10.1371/journal.pgph.0007096. eCollection 2026.

ABSTRACT

Understanding intention to test for HIV reflects readiness for action and provides an opportunity for intervention before behaviour is actualised. In sub-Saharan Africa (SSA), HIV testing remains low. While numerous studies have identified factors influencing HIV testing, less is understood about how these factors shape the intention to test. Guided by the Theory of Planned Behaviour (TPB), this study examined HIV testing intention among heterosexual males in Bolgatanga Municipality. A community-based cross-sectional survey included 480 heterosexual males. Data were collected using structured questionnaires and analysed with STATA 17 and IBM SPSS AMOS 29. Statistical procedures included descriptive statistics, chi-square tests, logistic regression, confirmatory factor analysis (CFA), and structural equation modelling (SEM). Model fit was assessed using the Adjusted Goodness-of-Fit Index (AGFI), Comparative Fit Index (CFI), Goodness-of-Fit Index (GFI), Incremental Fit Index (IFI), Normed Fit Index (NFI), and Root Mean Square Error of Approximation (RMSEA). Based on a predefined mean score of ≥3.0, only 13.3% (95% CI: 10.3 – 16.4) of participants expressed a strong intention to test for HIV; 46.5% had positive attitudes, 57.7% reported high subjective norms, and 2.1% had high perceived behavioural control (PBC). Multivariate analysis revealed that positive attitudes (AOR = 1.55), high subjective norms (AOR = 2.23), and high PBC (AOR = 2.97) increased the odds of strong intention. Younger age groups had lower odds of intention, while frequent media exposure predicted higher intention. Psychometric evaluation confirmed excellent internal reliability (ω ≥ 0.96), and SEM indicated good model fit (AGFI = 0.862; CFI = 0.926; RMSEA = 0.060). PBC emerged as the strongest direct predictor (β = 0.45). HIV testing intention was influenced by psychological, social, and structural factors. Improving HIV testing among heterosexual men requires interventions that strengthen PBC, leverage supportive social norms, and expand sustained media engagement to reduce barriers and normalise HIV testing.

PMID:42607102 | DOI:10.1371/journal.pgph.0007096

PLoS One. 2026 Aug 17;21(8):e0351164. doi: 10.1371/journal.pone.0351164. eCollection 2026.

ABSTRACT

OBJECTIVES: To estimate the prevalence of catastrophic costs incurred by households of people with tuberculosis (TB) in Guatemala, and to assess the potential wealth inequalities and the associated factors with the catastrophic costs, social consequences and coping strategies.

METHODS: A national representative survey, employing a clustered sampling based on health facilities, was conducted in 2023. The participants were people with TB and the data was collected by trained professionals using a standardized questionnaire. Catastrophic costs were defined as costs incurred by TB treatment that exceeds 20% of annual household income. We estimated the burden of catastrophic costs, social consequences and coping strategies. The primary analysis encompassed the output approach, while sensitivity analyses were conducted with the human capital approach and income loss adjustments. The associations were assessed using Poisson regression models with robust variance.

RESULTS: The First Guatemala National Tuberculosis Costs Survey had 530 participants enrolled in 42 clusters. The estimated catastrophic costs incurred by people with TB, through the output approach, was 36% (95% CI 29% – 43%). The prevalence among the poorest wealth quintile was 66%, while among the richest it was 50%, throughout the output approach adjusted for income loss (sensitivity analysis). Catastrophic costs were twice as high for 15-44-years old, but lower for people in the South West (PR 0.72; 95% CI 0.55-0.94), those in five-plus-person households (PR 0.73; 95% CI 0.57-0.93), and those treated in primary/secondary facilities (PR 0.69; 95% CI 0.49-0.97). Social effects were related with sociodemographic characteristics and catastrophic costs (PR 1.21; 95% CI 1.09-1.34). Coping strategies were associated with sociodemographic factors, presence of social support (PR 1.11; 95% CI 1.01-1.22), and TB type (PR 1.16; 95% CI 1.01-1.33).

CONCLUSION: In Guatemala, catastrophic costs were identified as a burden characterized by inequities, posing a challenge to the country in achieving zero to this indicator. However, the analyses revealed pathways that could be prioritized when formulating policies to effectively address this issue.

PMID:42607100 | DOI:10.1371/journal.pone.0351164

PLoS Comput Biol. 2026 Aug 17;22(8):e1013859. doi: 10.1371/journal.pcbi.1013859. eCollection 2026 Aug.

ABSTRACT

Pathogen-pathogen interactions occur when infection with one pathogen influences one’s chance of infection or disease due to another. Increasingly, evidence suggests that interactions are a common feature of infectious disease epidemiology. However, due to both the nonlinearities and stochasticity inherent to infectious disease transmission, and the frequency of confounding (e.g., by shared seasonal forcing), simple, correlative methods for characterizing interactions may be prone to failure. Here, we perform a simulation study to evaluate several more complex non-mechanistic approaches for inferring causality from time series data: generalized additive models (GAMs), Granger causality, transfer entropy, and convergent cross-mapping (CCM). Specifically, we use a two-pathogen mechanistic transmission model, calibrated to produce dynamics resembling outbreaks of influenza and respiratory syncytial virus (RSV), to generate synthetic datasets with a range of values for interaction strength and duration. We then apply each method to all synthetic datasets. We find that Granger causality, transfer entropy, and CCM all fail to consistently infer whether data contain signal of an interaction; in particular, methods tend to incorrectly identify interactions where none are modeled (average sensitivity = 80.6%, 92.1%, 72.1%, respectively; average specificity = 31.0%, 33.3%, 33.1%). Furthermore, we find little to no association between point estimates from each method and true interaction strength. In contrast, GAMs infer the existence of interactions more accurately than the other methods (sensitivity = 85.2%, specificity = 72.5%), and consistently yield larger point estimates for stronger interactions. However, their practical utility is limited by an inability to evaluate interaction asymmetry (i.e., whether the effect of pathogen A on pathogen B is identical to that of B on A). Overall performance patterns were similar when methods were applied to two real-world datasets from Hong Kong and Canada. We conclude that accurately and comprehensively characterizing pathogen-pathogen interactions based on outbreak data remains a significant challenge. For this reason, it is critical that any proposed methods be rigorously evaluated before being used to draw conclusions about interactions.

PMID:42607096 | DOI:10.1371/journal.pcbi.1013859

J Surg Oncol. 2026 Aug 17. doi: 10.1002/jso.70375. Online ahead of print.

ABSTRACT

INTRODUCTION: In liver transplantation (LT) with a caval sparing (CS) approach, the presence of complete encirclement of inferior vena cava (IVC-E) by hypertrophic segment 1 increases the technical complexity of hepatectomy. Thus, in LT for hepatocellular carcinoma (HCC), It may be suspected that the resulting greater liver manipulation and delayed vascular exclusion might increase the risk of intraoperative dissemination of tumor cells.

METHODS: A multicenter, retrospective study was performed to assess the association between IVC-E and the risk of post-transplant tumor recurrence in a cohort of 537 HCC patients treated with CS-LT, between 2010 and 2021. IVC-E was defined on preoperative imaging.

RESULTS: IVC-E (n = 150) and no-IVC-E (n = 387) groups were comparable in terms of severity of underlying liver disease, recipient characteristics, morphological and biological features of HCC. Recipient hepatectomy was significantly longer in IVC-E group (IVC-E vs. no-IVC-E, 144 min [110-180] versus 120 min [90-150], p < 0.001) and was associated with higher blood transfusion requirements (no transfusion cases, 15.3% vs. 25.8%, p = 0.034). The cumulative incidence of HCC recurrence at 1, 3, and 5-year, accounting for the competing risk of death unrelated to tumor recurrence, was significantly higher in IVC-E group (8.1%, 18.5%, and 20.1% vs. 3.9%, 8.4%, and 11.3%, p = 0.001, respectively).

CONCLUSIONS: The technical complexity associated with IVC-E during CS hepatectomy not only increases intraoperative morbidity but may also trigger the risk of post-transplant tumor recurrence in LT for HCC.

PMID:42607094 | DOI:10.1002/jso.70375

PLoS Negl Trop Dis. 2026 Aug 17;20(8):e0013519. doi: 10.1371/journal.pntd.0013519. Online ahead of print.

ABSTRACT

Schistosoma japonicum-associated liver fibrosis (SSLF) remains a major cause of long-term morbidity in schistosomiasis, even in post-control or low-transmission settings. While most vaccine development efforts have focused on reducing parasite burden, few approaches have incorporated host pathology related to liver fibrosis. This study developed an in silico strategy that combined host single-cell analysis with reverse vaccinology to guide the exploratory screening of parasite antigens with potential relevance to SSLF. Single-cell transcriptomics of fibrotic and control human liver tissues was used to identify immune-related molecular networks and host proteins associated with fibrosis-related pathology in the available dataset. In parallel, antigens were screened by functional annotation and established reverse-vaccinology criteria. Candidate antigens were further assessed by docking against selected host proteins. Docking of a known FYN inhibitor was included as a structural reference to interpret the strongest predicted antigen-host interaction. Single-cell analyses identified FYN, BCL2, and AKT3 as key nodes in fibrosis-associated immune networks. Among screened parasite antigens, DRE2_SCHJA, an Anamorsin homolog involved in iron-sulfur cluster assembly, emerged as a computational candidate for further validation. Docking predicted that DRE2_SCHJA may bind in an SH2-associated region of FYN, whereas the Saracatinib-FYN model was centered on the ATP-binding pocket of the kinase domain. This difference may suggest a distinct predicted binding mode rather than Saracatinib-like kinase inhibition. Overall, the vaccine-screening profile and predicted FYN-associated interaction may provide a computational rationale for further experimental evaluation of DRE2_SCHJA as a candidate antigen in the immune-fibrotic context of SSLF.

PMID:42607092 | DOI:10.1371/journal.pntd.0013519

PLoS Pathog. 2026 Aug 17;22(8):e1014521. doi: 10.1371/journal.ppat.1014521. Online ahead of print.

ABSTRACT

Microsporidia rely extensively on host resources, yet how parasite-derived microRNAs coordinate infection remains poorly understood. Here, we investigated the function of nce-miR-12220, a miRNA identified in Nosema ceranae spores, during infection of Apis mellifera workers. Target prediction, dual-luciferase assays, and fluorescence in situ hybridization were combined with RNA interference and miRNA gain- and loss-of-function experiments. nce-miR-12220 interacted sequence-specifically with binding regions in ATP-A and γ-tubulin and was detected in infected honeybee midgut epithelial cells. Silencing either target gene reduced expression of the N. ceranae virulence-associated gene NcRBL and improved worker survival relative to the scramble control. In infected workers, nce-miR-12220 overexpression increased endogenous ATP-A and γ-tubulin transcript abundance, whereas inhibition produced the opposite effect. Overexpression also reduced expression of the Toll pathway-associated genes Cactus and dorsal and the antimicrobial peptide genes Defensin and Hymenoptaecin, increased N. ceranae spore load and sucrose consumption, and decreased midgut ATP content. Inhibition of nce-miR-12220 reversed these responses and reduced parasite burden. Survival after nce-miR-12220 manipulation changed in the predicted direction but did not reach statistical significance. Together, these findings identify nce-miR-12220 as a parasite-derived regulator that promotes N. ceranae proliferation while reshaping host immune and energetic responses, and suggest that this microRNA and its target network may provide candidates for controlling bee nosemosis.

PMID:42607084 | DOI:10.1371/journal.ppat.1014521

PLoS Comput Biol. 2026 Aug 17;22(8):e1014640. doi: 10.1371/journal.pcbi.1014640. eCollection 2026 Aug.

ABSTRACT

Genetic contributions to complex traits are often mediated through coordinated gene-gene interaction networks, yet most existing association frameworks focus on marginal single-gene effects and overlook higher-order dependency structures. Direct modeling of interactions remains challenging due to combinatorial complexity and statistical instability. We introduce Interaction-Bridged Association Study (IBAS), a general framework that incorporates pathway-level interaction patterns into genotype-phenotype association analysis without explicitly enumerating interactions. IBAS leverages transcriptomic reference data to construct low-dimensional representations of pathway activity, which guide SNP-weighting and gene-level association testing within a kernel-based framework. In perturbation-based simulations, IBAS demonstrates improved stability and reproducibility compared to conventional TWAS and gene-based methods, while maintaining well-calibrated Type I error under phenotype permutation. Application to the WTCCC datasets identifies both known and novel genes across multiple complex diseases, including candidates with modest marginal effects missed by standard approaches. These findings are supported by replication in an independent cohort, and analyses across multiple reference tissues revealing both shared and tissue-specific signals. Overall, IBAS provides a statistically robust and computationally tractable framework for incorporating interaction effects into association mapping, extending beyond the single-gene paradigm and enabling more comprehensive characterization of complex trait. IBAS is available on GitHub at: https://github.com/QingrunZhangLab/IBAS.

PMID:42607076 | DOI:10.1371/journal.pcbi.1014640

Eur J Heart Fail. 2026 Aug 17:xuag209. doi: 10.1093/ejhf/xuag209. Online ahead of print.

ABSTRACT

AIMS: Apparent treatment-resistant hypertension (aTRH) is common and associated with adverse outcomes in individuals with heart failure (HF) with mildly reduced or preserved ejection fraction (HFmrEF/HFpEF). Whether finerenone improves blood pressure (BP) and clinical outcomes in individuals with HFmrEF/HFpEF and aTRH is uncertain.

METHODS: In this pre-specified analysis of the FINEARTS-HF trial, participants were categorized according to baseline BP, with aTRH defined as BP ≥140/90 mm Hg (≥130/80 mm Hg if diabetes) despite treatment with ≥3 BP-lowering medications, including a diuretic. Non-resistant hypertension was defined as BP above threshold but not meeting aTRH criteria. Controlled BP was defined as BP under the threshold. Incidence of clinical outcomes and safety events was assessed by baseline hypertension category.

RESULTS: Among 6001 participants, 3471 (57.8%) had controlled blood pressure, 1754 (29.2%) had non-resistant hypertension, and 776 (12.9%) had aTRH at baseline. Between baseline and 36 months, finerenone similarly reduced systolic BP across baseline BP categories (Pinteraction = 0.59). Rates of cardiovascular death and total HF events (per 100 person-years) were 17.0 in those with controlled BP, 16.0 in those with non-resistant hypertension, and 13.8 in those with aTRH (Pcomparison = 0.12). Relative treatment benefits of finerenone vs placebo on the primary outcome (Pinteraction = 0.32) and HF-related health status (Pinteraction = 0.22) were consistent across hypertension categories. The safety profile of finerenone vs placebo did not appear to be modified by baseline hypertension category.

CONCLUSION: aTRH was identified in 1-in-8 individuals with HFmrEF/HFpEF in FINEARTS-HF. Finerenone consistently improved clinical outcomes, health status, and blood pressure, including among those with aTRH.

PMID:42606500 | DOI:10.1093/ejhf/xuag209

Diabetes Care. 2026 Aug 17:dc260886. doi: 10.2337/dc26-0886. Online ahead of print.

ABSTRACT

OBJECTIVE: To identify and characterize daily and weekly patterns in glycemic management in longitudinal real-world continuous glucose monitoring (CGM) data from people with diabetes to enhance clinical interpretation and support more effective personalized diabetes management.

RESEARCH DESIGN AND METHODS: This observational, retrospective study used two independent, multiyear, real-world CGM cohorts (T1DiabetesGranada and Connected Pen), comprising 86,779 participants with diabetes. Their mean age (SD) was 40.3 (15.8) and 44.0 (15.9), respectively, and there was a total of 21,011,021 measurement days. Weekly variations in CGM metrics and bolus insulin dose were examined using linear mixed-effects models, and daily temporal patterns were assessed.

RESULTS: Weekly and daily glycemic patterns emerged. Mid-week time in range was consistently higher (e.g., Wednesday: +0.96 percentage points [%-points]; 95% CI 0.93-0.99; P < 0.001), with deterioration during weekends and Mondays (e.g., Sunday: -1.74%-points; 95% CI -1.77, -1.72; P < 0.001), mirrored by shifts in other CGM metrics. Bolus insulin dose increased on weekend days (e.g., Sunday: +0.69 units; 95% CI 0.64-0.74; P < 0.001). Daily analyses revealed distinct diurnal profiles, with the most favorable glycemic control during morning and midday hours on weekdays and consistently poorer control during evening and nighttime periods, particularly on weekends.

CONCLUSIONS: Daily and weekly glycemic patterns revealed statistically robust and consistent temporal variations in glycemic control across two large real-world cohorts. Although the magnitude of these differences was small, the findings provide novel population-level evidence and underscore the value of longer-term CGM perspectives in routine care.

PMID:42606498 | DOI:10.2337/dc26-0886