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PubMed2026

Changes in sexual behavior among women in studies evaluating the dapivirine vaginal ring for HIV prevention.

BACKGROUND: Access to novel HIV prevention technologies often raise concerns of risk compensation. This analysis examined changes in the sexual behaviors of MTN 020/ASPIRE participants, a placebo controlled randomized control trial, who subsequently enrolled in MTN-025/HOPE, an open-label extension using the dapivirine vaginal ring. METHODS: Both studies enrolled healthy, sexually active, HIV-negative women from Malawi, South Africa, Uganda and Zimbabwe. Longitudinal data on participants' sexual behaviors, specifically sex with a nonprimary partner (past 3 months), and use of male or female condoms at the last vaginal sex act were compared between ASPIRE and HOPE. Conditional and mixed ordinal logistic regression models evaluated associations between study and sexual behaviors at enrollment, and quarterly over the first 12 months. RESULTS: Of the 2629 individuals enrolled in ASPIRE, 1456 (55%) participated in HOPE. At enrollment, the proportion of participants who reported sex with a nonprimary partner and condom use at last vaginal sex act did not differ by study. Across all quarterly follow-up visits, sex with a nonprimary partner was more common in HOPE (13.9-18.7%) than ASPIRE (10.7-12.6%); adjusted OR 1.47, 95% CI 1.24-1.75, P < 0.001. There was no difference in condom use at the last vaginal act across all quarterly follow-up visits between ASPIRE (36.5-42.7%) and HOPE (43.6-46.7%); adjusted OR 1.05, 95% CI 0.94-1.18. CONCLUSION: More women reported sex with nonprimary partners in HOPE, with little change in condom use over time between the two studies. Understanding behavior changes during PrEP use allows for tailored, holistic reproductive health programming.

Humans↗

PubMed2026

In silico identification of DNMT1 inhibitors from the PlantCyc database through computational approach to assess the anti-cancer potential of nutraceutical compounds in breast cancer.

Breast cancer accounts for a disproportionate share of global cancer-related deaths, with 670,000 fatalities and 2.3 million new diagnoses recorded in women during 2022 alone. Existing treatment modalities carry considerable toxicity burdens, and resistance to available agents remains an unresolved clinical problem. DNA methyltransferase 1 (DNMT1), the enzyme chiefly responsible for maintaining genome-wide methylation patterns during DNA replication, has been mapped out as a high-value target in breast cancer because its dysregulation silences tumour suppressor genes through promoter hypermethylation. The present work involves hierarchical in silico workflow to screen 4549 plant-derived compounds from the PlantCyc database (v16.0.3) against the human DNMT1 catalytic domain (PDB ID: 4WXX). Ten top-scoring compounds were taken forward for molecular docking via AutoDock Vina; Quercetin and Kaempferol both recorded the highest binding affinities at -9.5 kcal/mol, Wogonin (-9.3 kcal/mol) and Xanthohumol (-8.1 kcal/mol) also emerged as strong binders. Pharmacokinetic evaluation using ADMET-AI confirmed that all 10 compounds met Lipinski's rule of five, with human intestinal absorption values at or above 0.98. Wogonin and Xanthohumol were selected for a 100 ns all-atom molecular dynamics (MD) simulation in GROMACS due to their well-rounded ADMET profiles and limited existing data on their specific interactions with DNMT1 in breast cancer. Across all measured trajectory metrics, backbone RMSD, residue fluctuation, radius of gyration, solvent-accessible surface area, and intermolecular hydrogen bond count, Wogonin formed a more stable, compact complex. These findings suggest that Wogonin and Xanthohumol are non-toxic nutraceutical candidates suitable for DNMT1 targeted epigenetic therapy, with computational foundation strong enough to facilitate future in vitro and in vivo validation work.

Humans↗

PubMed2026

On-filter fractionation by empFASP improves identification of membrane peptides in proteomic experiments.

Membrane proteins remain among the most analytically challenging targets in bottom-up proteomics due to their limited solubility and low abundance of protease-accessible sites within transmembrane domains. In addition, hydrophobic peptides are frequently lost during detergent removal and the on-filter processing steps. Here, we present empFASP, a straightforward on-filter-fractionation-based modification of the enhanced filter-aided sample preparation (eFASP) workflow that enhances recovery of membrane-embedded peptides otherwise lost during digestion and cleanup. The method combines controlled on-filter inversion with sequential ethyl acetate extraction at defined pH values, enabling recovery of peptide material retained on the filter and redistributed into detergent micelles. Compared with SP3 and SP4 in HEK293T lysates, empFASP increased unique hydrophobic peptide identifications by up to 48% and increased the proportion of detected transmembrane peptides. Application to mouse mitochondrial membranes and phosphatidylethanolamine-deficient and PE-containing Escherichia coli membranes showed that the additional fractions of empFASP contribute complementary recovery of hydrophobic and membrane-associated peptides, with the strongest gains observed at the peptide level. Because empFASP requires no specialized reagents or instrumentation, it can be readily implemented in standard proteomics workflows to improve coverage of membrane-embedded regions. SIGNIFICANCE: The empFASP (enhanced membrane peptide) workflow offers a practical solution to one of the persistent limitations in membrane proteomics-the underrepresentation of hydrophobic and transmembrane peptides in standard digests. By integrating simple pH-controlled extractions into an on-filter format, empFASP recovers peptides otherwise lost through adsorption or detergent micelle retention, substantially improving coverage of the membrane proteome. This method expands the analytical reach of bottom-up proteomics without requiring specialized instrumentation, making it immediately applicable for studies of membrane topology, protein-lipid interactions, and the structural consequences of altered membrane composition.

Proteomics↗

PubMed2026

Comparison of the predictive performance of systemic immune-inflammation index and neutrophil-to-lymphocyte ratio for three-month poor functional outcome in ischemic stroke: a systematic review and meta-analysis.

INTRODUCTION: Ischemic stroke (IS) is a leading cause of global mortality and disability. Early and accurate prognosis is crucial for patient management. The neutrophil-to-lymphocyte ratio (NLR) and systemic immune-inflammation index (SII) are emerging inflammatory biomarkers; however, their relative predictive value for three-month poor functional outcome (modified Rankin Scale [mRS] > 2) remains uncertain. METHODS: We systematically searched PubMed, Embase, Web of Science, and the Cochrane Library up to 20 July 2025, adhering to PRISMA guidelines. Observational studies reporting the association of SII or NLR with three-month poor outcome were included. Study quality was evaluated using the Newcastle-Ottawa Scale. Area under the curve (AUC), odds ratios (OR), and standardized mean differences (SMD) were pooled using random-effects models in Stata 16.0. RESULTS: Twenty-one studies involving 7520 IS patients were analysed. NLR demonstrated marginally superior discriminative ability compared to SII (AUC 0.71, 95% CI: 0.67-0.76 vs. 0.68, 95% CI: 0.64-0.71), though this difference was not statistically significant. Elevated NLR was significantly associated with poor outcome (OR = 1.26, 95% CI: 1.17-1.37, p < .001), whereas SII was not (OR = 1.00, 95% CI: 1.00-1.00, p = .384). Both markers showed moderate effect sizes (SMD: NLR = 0.69, SII = 0.72; p < .001). NLR performed better in non-intervention and Chinese subgroups, while SII exhibited consistent AUC values across treatment and ethnic subgroups. CONCLUSION: NLR and SII are accessible prognostic markers in IS. NLR demonstrates superior accuracy and a significant association with poor outcome, while SII shows greater stability across patient subgroups. Both may assist in risk stratification, in resource-limited settings.

Humans↗

PubMed2026

BMT4me En Español: Multisite Feasibility and Usability Testing of a Spanish-Language mHealth Adherence Support App for Spanish-Speaking Caregivers of Children After Hematopoietic Stem Cell Transplantation and Cancer Treatment.

BACKGROUND: Medication nonadherence during the first 100 days after pediatric hematopoietic stem cell transplantation (HSCT) and during oncology treatment increases risk for complications. BMT4me is a caregiver-facing mobile health (mHealth) application providing medication reminders, symptom tracking, and note-taking features to support medication management. Spanish-speaking caregivers are frequently excluded from digital adherence interventions due to the lack of language-accessible tools. PROCEDURE: We conducted a multisite, mixed-methods usability testing of a Spanish-language version of BMT4me ("BMT4me en Español") with Spanish-speaking caregivers of children (ages 2-17 years) post-HSCT or with an oncology diagnosis on active treatment. Caregivers completed a facilitated, three-step usability session (unobtrusive observation, interactive observation, and debriefing), followed by a semi-structured interview, and then completed the system usability scale (SUS). Quantitative outcomes were summarized descriptively; qualitative data were analyzed using content analysis with constant comparison. RESULTS: Fifteen participants enrolled at each site for a total of 30 participants. Across both sites, the recruitment rate was 91%. All participants completed all parts of the study. The SUS score (M = 80.09; SD = 17.35) was above average (>68). Two key qualitative themes emerged: (1) the perceived positive impact of BMT4me on managing a serious illness and (2) the acceptance and sociocultural relevance of BMT4me for Spanish-speaking families. Caregivers also shared suggestions to add educational content and multiuser functionalities to BMT4me. CONCLUSIONS: The acceptance and perceived positive impact of the Spanish BMT4me app indicates that socioculturally relevant, Spanish mHealth interventions have strong potential to support Spanish-speaking caregivers in pediatric oncology and HSCT settings. CLINICAL TRIALS NCT: NCT06361173.

Adolescent↗

PubMed2026

Discrimination, chronic stress, and multimorbidity in cohort of Black and Latina transgender women with HIV: Longitudinal findings from the LITE Plus study.

Black and Latina transgender women with HIV (BLTWH) are exposed to repeated, intersecting discrimination based on race, gender, and serostatus. Minority stress theory conceptualizes discrimination as minority-specific stressors that drive health inequities. Allostatic load theory posits a pathway between discrimination and chronic disease through multisystem physiological dysregulation caused by chronic stress. To test this pathway, a longitudinal cohort of 108 BLTWH, enrolled December 2020 - June 2022 in Boston, New York City, and Washington, DC, were followed for 24 months, with biomarkers measured at baseline, 12, and 24 months. Questionnaires administered every 6 months assessed anticipated discrimination, everyday discrimination, perceived stress, and other psychosocial factors. Multimorbidity was measured via self-reported non-HIV chronic conditions. In mixed-effects mediation models, allostatic load did not mediate relationships between multimorbidity outcomes and anticipated discrimination (β: -0.0004 [95% CI: -0.004, 0.003]) nor everyday discrimination (β: -0.002 [95%CI: -0.009, 0.003]). Perceived stress demonstrated indirect effects on multimorbidity in unadjusted models of anticipated discrimination (β: 0.024, [95% CI: 0.015, 0.081]) and everyday discrimination (β: 0.021 [95%CI: 0.016, 0.077]). Indirect effects remained significant, with attenuated effects (β: 0.020 for anticipated discrimination; β: 0.017 for everyday discrimination) after adjusting for social support, community connection, and resilient coping. Total effects were only significant for the adjusted model of everyday discrimination (β: 0.056 [0.014, 0.099]). Findings suggest discrimination impacted health through specific psychosocial pathways. Alongside efforts to eliminate intersectional discrimination, stress-lowering interventions and increased access to social support and community connection may be effective approaches to reducing multimorbidity in this highly marginalized group.

Humans↗

PubMed2026

Latent profile analysis of pregnant exercise adherence and the relationship with demographic and socio-psychological factors: a multicentre cross-sectional study.

BACKGROUND: Pregnancy physical activity (PA) and exercise benefits both mothers and babies, but requires sustained adherence. Many pregnant women fail to meet recommended levels. The reasons for low adherence comprised fluctuating physiological and environmental factors. This study aims to identify discrete profiles of pregnant women based on exercise adherence and to examine differences in demographic and socio-psychological factors across these profiles. METHODS: A survey was conducted among 1,255 pregnant women in three hospitals in Shenzhen, Dongguan, and Shunde, China, using the Exercise Adherence Rating Scale (EARS), the Pregnancy Exercise Self-Efficacy Scale (P-ESES), and the Pregnancy Physical Activity Social Support Scale (P-PASSS). In the analysis, EARS items were scored higher, indicating a healthier state (e.g., sufficient time and energy). Latent profile analysis (LPA) was employed to classify adherence profiles, and multinomial logistic regression was used to examine differences in demographic, self-efficacy, and social support across four groups. RESULTS: Four profiles of exercise adherence were identified: (1) Profile 1 (16.97%), characterized by deficits in time and energy, (2) Profile 2 (15.22%), a group with sufficient time resources but the lowest self-efficacy, (3) Profile 3 (43.98%), characterized by high adherence despite moderate barriers, and (4) Profile 4 (23.83%), a group with optimal exercise adherence, confidence, and resources. Women with higher P-ESES (OR: 1.14-1.38) and P-PASSS (OR: 1.04-1.06) scores were more likely to be in Profiles 3 and 4. Additionally, women's partners who never or occasionally exercise were significantly more likely to be categorized into Profile 1 (OR = 0.18 for Profile 4 vs. Profile 1). Furthermore, the first trimester emerged as a significant risk period for lower exercise adherence, whereas overweight/obesity was independently associated with higher odds of membership in Profile 4. CONCLUSION: The study identified four distinct profiles of exercise adherence among pregnant women. 32.19% of participants were in the two lower exercise-adherence groups. Pregnant women in Profile 1 were characterized by challenges related to a lack of time and knowledge. Participants in Profile 2 showed the lowest exercise self-efficacy and social support among the four profiles. Furthermore, women in early pregnancy were more likely to have lower adherence profiles. Hence, targeted interventions addressing these specific groups are warranted to improve exercise adherence during pregnancy.

Humans↗

PubMed2026

Meta-PseU: A meta-classifier for robust prediction of RNA pseudouridine modification sites from long sequences.

BACKGROUND AND OBJECTIVES: Pseudouridine (Ψ) represents one of the most abundant and conserved RNA modifications. Ψ provides an additional hydrogen-bond donor that enhances RNA structural stability and modulates translation. It participates in diverse biological processes, including RNA-protein interactions, splicing, translational control, and stress responses. Aberrant pseudouridylation is implicated in cancer, neurodegenerative disorders, and autoimmune diseases. Despite its biological importance, experimental identification of Ψ sites remains time-consuming and costly, limiting the feasibility of transcriptome-wide profiling. Computational approaches have therefore become essential complements to experimental techniques. However, state-of-the-art machine-learning and deep-learning predictors often suffer from limited generalizability due to small training datasets. To overcome these issues, we aim at constructing new long-sequence datasets and developing a novel Ψ site predictor. METHODS: New long-sequence datasets were constructed as benchmarks for RNA Ψ-site prediction. The Ψ modification sites in RMBase 3.0 were mapped to the reference genomes across three species of human, mouse, and yeast, and the RNA sequences with a length of 201 were generated by extending the upstream and downstream from the mapped, central sites. To eliminate sequence redundancy, the sequences were clustered using CD-HIT with a 70% sequence identity threshold. We developed Meta-PseU, a logistic regression-based meta-classifier that considered 118 machine learning and deep learning classifiers. The datasets and programs are freely accessible at https://github.com/kuratahiroyuki/MetaPseU. RESULTS: By optimizing model configuration, we proposed the Meta-PseU model stacking 32 machine learning and deep learning classifiers out of 118 classifiers. Meta-PseU substantially improved model generalizability, overcoming a key limitation of existing approaches. It greatly outperformed state-of-the-art predictors and achieved increasing accuracy with increasing sequence length. CONCLUSIONS: Long-sequence datasets were newly constructed as benchmarks for RNA Ψ-site prediction. Meta-PseU offers a new framework for robust Ψ-site identification by using long sequences.

Pseudouridine↗

PubMed2026

Effect of knee and hip joint positions on passive stiffness of the rectus femoris and vastus lateralis in healthy individuals.

Passive muscle stiffness is a key determinant of musculoskeletal function and is influenced by structural components such as titin, connective tissue, and fascia. However, the effects of joint position, muscle depth, and sex on quadriceps passive stiffness remain unclear. To investigate the passive stiffness of the rectus femoris (RF) and vastus lateralis (VL) under different joint configurations, muscle depths, and between sexes using shear wave elastography (SWE). Thirty-six healthy young adults (18 men and 18 women) participated in this randomized crossover study. Passive stiffness was assessed in four positions of knee flexion: supine with 60° (SUP60), supine with 20° (SUP20), sitting with 60° (SIT60), and sitting with 20° (SIT20). SWE measurements (m/s) were obtained from 30 regions of interest (ROIs) per muscle, categorized into superficial, intermediate, and deep levels. Data were analyzed using Generalized Estimating Equations (GEE). A significant effect of position was observed, with higher stiffness values in the SUP60 condition for both RF and VL (p < 0.001). Superficial regions consistently exhibited greater stiffness compared to intermediate and deep regions across all positions (p < 0.001). Additionally, men demonstrated significantly higher stiffness values than women (p < 0.001). Significant interactions were found between position and muscle, as well as position and depth. Quadriceps passive stiffness is influenced by joint position, muscle depth, and sex. The SUP60 position elicits the highest stiffness, while superficial muscle regions are consistently stiffer. These findings highlight the non-uniform mechanical behavior of the quadriceps and may have implications for clinical assessment, rehabilitation, and exercise prescription. Clinical trial registration: This study was registered at Clinicaltrials.gov in June 06th, 2023. Register number NCT05905406. Link to access https//clinicaltrials.gov/study/NCT05905406.

Humans↗

PubMed2026

Integrated salivary proteomic and metabolomic analyses reveal molecular characterization and novel biomarker panels of chronic obstructive pulmonary disease.

Chronic obstructive pulmonary disease (COPD) is a respiratory disorder characterized by chronic inflammation, oxidative stress, and metabolic dysregulation. The lack of convenient and easily-accessible non-invasive diagnostic approaches remains a major clinical challenge. This study applied an integrated saliva-based proteomic and untargeted metabolomic strategy to identify potential biomarkers for COPD classification. Comprehensive multi-omics analyses identified 225 differentially abundant proteins and 60 differentially abundant metabolites between patients with COPD and healthy controls, including 24 biologically relevant endogenous metabolites. Functional enrichment analyses revealed pronounced dysregulation of mitochondrial energy metabolism, redox homeostasis, lipid remodeling, and inflammatory-related pathways in COPD. By integrating salivary proteomic and metabolomic biomarkers, a stepwise feature selection combined with LASSO logistic regression was used to construct diagnostic models, yielding an optimized biomarker panel consisting of 11 proteins and 2 endogenous metabolites. This integrated model achieved excellent diagnostic performance, with an area under the ROC curve of 0.96. Collectively, these findings demonstrate that integrated salivary proteomic and metabolomic profiling provides a robust, non-invasive approach for COPD classification and offers a promising foundation for the development of biosensor-based diagnostic platforms and early disease detection. SIGNIFICANCE: Chronic obstructive pulmonary disease (COPD) remains a major global health burden. Current diagnostic approaches rely largely on spirometry and clinical assessment, which are limited in sensitivity for early-stage disease and unsuitable for large-scale screening. This study employs an integrated saliva-based proteomic and metabolomic strategy to identify non-invasive biomarkers for COPD classification. Our findings reveal coordinated dysregulation of mitochondrial energy metabolism, redox homeostasis, and lipid remodeling in COPD, highlighting the interconnected roles of metabolic reprogramming, oxidative stress, and inflammation in disease pathophysiology. Notably, a robust diagnostic panel comprising 11 proteins and 2 endogenous metabolites was established, achieving excellent classification performance (AUC of 0.96). To our knowledge, the integrated application of salivary proteomics and metabolomics for COPD diagnosis remains largely unexplored, underscoring the significance and translational potential of our findings.

Humans↗

PubMed2026

Orchard netting impacts on biodiversity leading to cascading effects at the ecosystem level.

Agriculture must ensure food production without further compromising the ecosystem functions upon which it depends. Agricultural practices should therefore avoid harming farmland biodiversity, especially of taxa that supply the key ecosystem services (e.g. pollination, pest control and nutrient uptake) that ultimately support crop production. Orchards are among the largest permanent plantations worldwide and are increasingly characterised by the spread of plastic nets used to protect fruits/nuts from either abiotic (anti-hail, anti-rain, shade nets) or biotic (exclusion nets) hazards. Despite having received little attention to date, these nets may impact natural communities, acting both as physical barriers and as drivers of habitat changes to which biota must respond. Species-level responses to netting depend on the organism's ability to enter the netted environment and successfully exploit available resources. Net-mediated ecological filtering and plastic behavioural responses may alter species interactions, leading to cascading ecological impacts that may create species-poorer 'netted communities' with simplified ecological networks. Such changes may erode biological control potential, other ecosystem functions, and overall system stability. We conducted a systematic review on the effects of protection nets on biota, and reported novel empirical evidence on anti-hail nets' impacts on communities of orchard-dwelling birds, flower-visiting insects, and rodents. In total, we identified 48 studies from the literature, however this literature was strongly biased towards apple orchards, western countries, and pest taxa. Net deployment was highly effective in deterring target pest species, in some cases regardless of their original function, as even weather-protection nets limited pest populations. Side effects on non-target taxa were also often reported, such as decreases in pollinators and natural enemies, and/or increases in secondary pests or microbial diseases. However, most assessments largely disregarded non-pest taxa and the broader ecological consequences of netting. The few studies that addressed the effects of nets at the guild/community level, including our empirical study, confirmed that orchard netting resulted in species-poor assemblages, with possible ecosystem-level consequences. We propose that future assessments should pay more attention to the indirect effects of netting on non-target taxa, and on the supply of crop-supporting ecosystem services mediated by wild species occurring in agroecosystems. Due to the trade-offs between these services and net-mediated crop protection, integrated alternatives should be tested to improve the environmental sustainability of food production and biodiversity conservation in farmed landscapes.

Biodiversity↗

PubMed2026

A bimodal large language model reduces misalignment in patient education: A double-blinded randomized trial.

BACKGROUND: Effective patient education requires accurate communication aligned with patients' emotional and semantical needs. Text-based large language models (LLMs) lack access to non-verbal cues, which may contribute to misaligned responses. METHODS: We evaluated emotional and semantic misalignment in a text-based LLM using 64,200 utterances from 16,583 patient education cases across six departments and three centers. Dolphin was developed integrating text and audio cues and evaluated through emotion recognition, semantic consistency assessment, branch-level ablations, and a double-blinded randomized trial against a matched text-based LLM comparator (Chinese Clinical Trial Registry: (ChiCTR2500095933). FINDINGS: The text-based LLM showed emotional misalignment in 36.7% of responses and semantic misalignment in 28.3% of cases, with higher misalignment under greater burden. Dolphin outperformed the text-based LLM in emotion recognition accuracy (0.886 vs. 0.713) and semantic consistency (84.9% vs. 82.1%; both adjusted p < 0.001). Ablations supported contribution of audio branches. Dolphin received higher expert ratings than the text-based LLM and human educators (all p < 0.001). In 555 patients, Dolphin was associated with greater patient satisfaction (98.6% vs. 93.8%), suggestion acceptance (76.1% vs. 58.9%; p < 0.001), proactive disclosure (44.6% vs. 26.5%; p < 0.001), and fewer 7-day unplanned recontact (12.9% vs. 22.9%; p = 0.002). No unsafe recommendations or safety events were identified. CONCLUSIONS: Compared with text-based LLM, Dolphin improved emotional-semantic alignment and patient-education outcomes, supporting bimodal alignment as a strategy for reducing misalignment-driven communication failures. FUNDING: National Natural Science Foundation of China, State Key Laboratory Special Fund, and Chinese Academy of Medical Sciences Innovation Fund.

Humans↗

PubMed2026

Effectiveness of tobacco cessation interventions delivered in clinical settings in South Asia: a systematic review and meta-analysis.

BACKGROUND: Despite the burden of tobacco use, access to cessation support in South Asia remains scarce. OBJECTIVE: This review evaluates the effectiveness of tobacco cessation interventions delivered in clinical settings in South Asia. METHODS: Five relevant databases were searched from inception to February 2025. Eligibility criteria included randomized and non-randomized studies evaluating behavioral, pharmacotherapy, and multicomponent interventions delivered in clinical settings in South Asia. Data on study setting and design, participant information, intervention, comparator, and outcomes were extracted. Meta-analyses using random-effect models were conducted where possible. Certainty of evidence was assessed using GRADE. RESULTS: Thirty-seven studies were included (22 randomized and 15 non-randomized). Interventions involved pharmacotherapy (n = 6; 16.2%), nicotine replacement therapy (n = 7; 18.9%), behavioral counseling (n = 12; 32.4%), or combined/multicomponent interventions (n = 12; 32.4%). Most studies were conducted in India (n = 26; 70.3%), followed by Pakistan (n = 6; 16.2%), Nepal (n = 3; 8.1%), and two studies (5.4%) were multi-country in India, Pakistan, and Bangladesh. Pooled analyses demonstrated higher quit rates among intervention versus control for continuous abstinence at 0-3 months (RR: 1.21, 95%CI: 1.06 to 1.37) and >3 months (RR: 1.68, 95%CI: 1.1.4 to 2.47), and for point abstinence at >3 months post-intervention (RR: 2.03, 95%CI:1.35 to 3.08). Heterogeneity was high for all analyses (I2 range: 94% to 97%). Combined behavioral and pharmacotherapy interventions were most effective (RR: 1.70, 95%CI: 0.98 to 2.92), although not statistically significant (p = 0.06). CONCLUSION: Tobacco cessation interventions delivered in clinical settings in South Asia are effective, particularly when combining behavioral support with pharmacotherapy. However, evidence is limited by methodological weaknesses.

Humans↗

PubMed2026

How Following Medical Artificial Intelligence Advice Can Mitigate Malpractice Liability: Cross-National Insights from a Randomized Trial.

Artificial intelligence (AI) increasingly influences clinical decision-making, yet its recommendations may diverge from standard care. Although malpractice concerns are thought to discourage physicians from following AI advice, experimental evidence from the United States suggests the opposite: lay jurors are more likely to hold physicians liable when they reject AI recommendations. Whether this pattern extends to systems in which court-appointed experts, not lay jurors, determine liability remains unknown. Methods: To examine how physicians and laypeople in expert-based and lay-juror legal systems evaluate physicians' acceptance or rejection of AI recommendations, particularly when those recommendations deviate from standard care, we designed a randomized vignette study: a 2 × 2 factorial design varying the AI recommendation (standard vs. nonstandard care) and a fictional physician's decision (accept vs. reject). The study was conducted online in 2023 among nationally representative samples of U.S. and German adults and from 2023 to 2024 among German physicians. In total, 387 German physicians, 2291 U.S. adults, and 2283 German adults participated; those not completing the survey or failing attention checks were excluded per preregistered criteria. Participants were randomly assigned to 1 of 4 vignettes, varying the AI recommendation (standard vs. nonstandard care) and physician's decision (accept vs. reject). The reasonableness of the fictional physician's decision was measured, rated by participants on a Likert scale. Results: Analysis, following preregistered exclusion criteria, included 248 German physicians, 1202 U.S. adults, and 1358 German adults. Physicians accepting standard-care AI recommendations were rated more reasonable than those rejecting them (U.S. laypeople: t = 5.36; 95% CI, 0.45-0.97; P < 0.001; German physicians: t = 2.47; 95% CI, 0.14-1.30; P = 0.02; German laypeople: t = 4.14; 95% CI, 0.27-0.76; P < 0.001). Ratings of physicians accepting versus rejecting AI nonstandard-care recommendations were statistically equivalent. Equivalence was tested at an α-value of 0.05 using a two 1-sided tests procedure, reported with 90% CIs per standard convention (U.S. laypeople: t = -4.90; 90% CI, -0.1 to 0.36; P < 0.001; German physicians: t = -1.76; 90% CI, -0.12 to 0.67; P = 0.04; German laypeople: t = 5.35; 90% CI, -0.35 to 0.06; P < 0.001). Conclusion: Across the United States and Germany, samples representative of lay jurors and court-appointed experts viewed accepting standard-care AI advice as more reasonable, whereas accepting or rejecting nonstandard-care AI advice was judged similarly. Contrary to predictions, malpractice liability regimes do not necessarily pose a barrier to AI use in precision medicine.

Artificial Intelligence↗

PubMed2026

Survival by Race and Ethnicity in Children and Adolescents/Young Adults With Relapsed/Refractory Hodgkin Lymphoma: A Pooled Analysis of Children's Oncology Group Trials.

PURPOSE: Despite 5-year survival rates of over 90% among children and adolescents/young adults (CAYAs) with classic Hodgkin lymphoma (cHL), 15%-20% relapse after frontline therapy. Prior analysis of frontline Children's Oncology Group (COG) clinical trials demonstrated that, despite similar rates of relapse, non-Hispanic Black (NHB) and Hispanic (vs. non-Hispanic White [NHW]) patients experienced higher post-relapse mortality. It is unknown whether post-relapse disparities persist when second-line treatment is delivered in a cooperative group trial setting. We examined overall survival (OS) by race and ethnicity in CAYAs enrolled in COG trials for relapsed/refractory (r/r) cHL. METHODS: A pooled analysis of individual-level data from CAYAs (≤ 29 years) receiving therapy for r/r cHL on COG clinical trials (2001-2016) was conducted. The Kaplan-Meier method estimated 3-year OS by racial and ethnic groups. Cox regression models examined associations of race and ethnicity and OS, adjusted for age, insurance, first versus ≥2 relapse, and time from initial diagnosis to relapse trial enrollment. RESULTS: Among 175 CAYAs treated on COG trials for r/r cHL (5.7% Asian or Pacific Islander, 14.9% Hispanic, 14.3% NHB, 61.7% NHW, 3.4% other), at median follow-up of 4.9 years, 3-year OS was 82.1% (95% confidence interval [CI], 75.3%-87.1%) and did not differ by race and ethnicity (p = 0.36). In multivariable analyses, shorter time from diagnosis to relapse trial enrollment (p = 0.01) and ≥2 relapses (vs. first, p = 0.004) conferred worse OS, with no significant effect of race and ethnicity (p = 0.43). CONCLUSION: Post-relapse survival did not differ by race and ethnicity among CAYAs enrolled in COG trials for r/r cHL, suggesting access to clinical trials may mitigate OS disparities.

Humans↗

PubMed2026

Single-organ proteomics in Drosophila melanogaster larva.

The combination of genetic accessibility, organ complexity, evolutionary conservation, and cost-efficiency makes Drosophila melanogaster (Dm) a well-known model system for biomedical and fundamental biological research. Proteomic analysis of single organs enables the identification and quantification of proteins expressed in specific organs. This will help to uncover specific biological functions and unique protein profiles that are not detectable in whole-organism analyses. In this study we have isolated single organs form Dm larvae, and we have performed a deep proteomics mapping by following a minimal manipulation preparation procedure. The combined dataset across all organs comprised 9132 identified proteins. As anticipated, principal component analysis (PCA) revealed clear separation between the proteomes of most organs, confirming distinct protein profiles. These findings demonstrate the applicability of the sample preparation strategy for high-resolution proteomic characterization of individual organs in Drosophila. Given the extensive genetic tools available for this model organism, our approach has the potential to open new avenues for proteomic studies in Drosophila melanogaster and any other biological systems where the sample amount is limiting. SIGNIFICANCE STATEMENT: Drosophila melanogaster is a well-known model system for biomedical and fundamental biological research that serves as a valuable in vivo model organism due to its high degree of evolutionary conservation with higher vertebrates, tractable genetics, and logistical efficiency. However, the proteome of Drosophila at single organ level has been elusive to date, due to several factors like low sensitivity of previous generation mass spectrometers and sample preparation procedures, difficult isolation of some organs. In this study we have applied a compilation of advanced methods including minimal sample manipulation together with simple, straightforward and efficient protein extraction and digestion methods. Obtained peptides were minimally handled to be analyzed by applying specific and sensitive nLC methods coupled on-line to state-of-the-art MS/MS system. Altogether, the applied strategy allowed us to get the first single organ study to date for this animal. These datasets represent a significative resource for future genomic, transcriptomic and proteomic studies in Drosophila, as multi-omic integration requires deep proteomics to translate data into functional biochemistry, and serves as a critical bridge and an indispensable standalone resource across the genomic, transcriptomic, and proteomic landscapes.

Animals↗

PubMed2026

Effect of demographic characteristics on the outcome of prostate cancer salvage radiotherapy: Analysis from a randomized controlled trial.

BACKGROUND: This study investigated the impact of advanced molecular imaging, race, socioeconomic status, and metabolic dysregulation on the outcome of salvage radiotherapy (sRT) for prostate cancer recurrence in a clinical trial setting. METHODS: The authors randomized post-prostatectomy men with detectable prostate-specific antigen to sRT guided by conventional imaging (arm A) or 18F-fluciclovine-positron emission tomography/computed tomography (arm B) and followed them up for up to 48 months to determine failure-free survival (FFS). The authors computed socioeconomic status (SES) and allostatic load (AL) scores to quantify socioeconomic status and level of metabolic dysregulation. They stratified patients by race as African American men (AAM) versus men of other races (MOR) and compared FFS between them using the z-test. RESULTS: Eighty-one (AAM = 29, MOR = 52) and 76 (AAM = 26, MOR = 50) men completed per-protocol sRT in arms A and B, respectively. Across study arms, AAM showed a higher FFS rate than MOR (72.8% [95% CI, 53.8%-85.0%] vs. 58.7% [95% CI, 46.6%-68.9%]; p = .002). In arm A, FFS rate was better for AAM than MOR, (64.0% [95% CI, 34.4%-82.9%] vs. 45.3% [95% CI, 28.8%-60.4%]; p = .008). In arm B, FFS improved for both groups but less so for AAM, (81.5% [95% CI, 57.2%-92.7%] vs. 73.0% [95% CI, 56.3%-84.1%]; p = .131). The authors found lower SES scores and higher AL scores for AAM in both study arms than MOR. CONCLUSION: Despite lower socioeconomic status and higher burden of metabolic dysregulation, in a clinical trial setting that controls for disparities in health care access, AAM have a more favorable sRT outcome than MOR.

Humans↗

PubMed2026

Pricing Combination Therapies: A Systematic Review of Value Attribution, Cost-Sharing Mechanisms and Policy Frameworks.

BACKGROUND: Combination therapies are increasingly central to modern pharmacotherapy, particularly in oncology and other high-burden diseases. However, pharmaceutical pricing and reimbursement systems remain largely designed for single-product-single-indication interventions. When multiple patented medicines are used together, especially when owned by different manufacturers, conventional pricing frameworks may struggle to align prices with the value of the combination while preserving incentives for innovation and timely patient access. OBJECTIVE: To identify, describe, and critically assess the methods, models, and policy frameworks proposed in the literature to establish prices for combination therapies, with particular attention to value attribution mechanisms, cost-sharing arrangements between manufacturers, and budget impact considerations. METHODS: A systematic literature review was conducted in accordance with PRISMA guidelines and a pre-registered Open Science Framework protocol. Searches were performed in MEDLINE, Scopus, Web of Science, EconLit, CRD databases, and grey literature sources for publications up to July 2025. Eligible studies analysed pricing approaches, economic models, reimbursement mechanisms, or policy frameworks relevant to combination therapies, including more recent multi-indication pricing literature. Given the heterogeneity of the literature, findings were synthesized using a structured narrative and thematic approach. RESULTS: Sixty-nine studies met the inclusion criteria. The literature was dominated by conceptual and policy analyses, with relatively few empirical or implementation-oriented studies. Value attribution emerged as the central methodological challenge in pricing combination therapies. Several complementary approaches were proposed to operationalise value attribution, including adaptations of indication- or pathway-based pricing, manufacturer cost-sharing arrangements, managed entry agreements, and outcome-based reimbursement mechanisms. Empirical evidence suggests that health systems continue to rely primarily on pragmatic and often partial solutions rather than fully specified pricing frameworks. A complementary review of the multi-indication pricing literature indicates that, although the two fields address different pricing problems, they share important methodological and institutional lessons that can inform the development of pricing frameworks for combination therapies. CONCLUSIONS: The literature provides a growing repertoire of conceptual approaches for pricing combination therapies but limited empirical evidence on implementation. Pricing frameworks should place value attribution at their core while combining complementary policy mechanisms adapted to national pricing and reimbursement systems. Lessons from multi-indication pricing provide a valuable foundation but require additional governance mechanisms to address value attribution, multi-manufacturer negotiation, and implementation challenges specific to combination therapies.

Journal Article↗