Citations

Abstract The intestinal epithelium harbors a large population of microbiota-dependent CD8αβ + T cells whose antigen specificity and regulation are ill-defined. By identifying MHCIa-restricted TCRs and generating tetramers against the gut commensal Segmented Filamentous Bacteria, we demonstrate that a single commensal species drives a clonally expanded, antigen-specific CD8αβ + T cell within the intraepithelial lymphocyte compartment. Mechanistically, the intestinal epithelium coordinates coincident signals governing this population: peptide:MHC-dependent TCR engagement drives pIEL accumulation, while αvβ6-mediated TGFβ activation restraints effector cell differentiation. Perturbation of epithelial cell-mediated TGFβ activation diverts commensal-specific CD8 + T cells toward inflammatory differentiation states transcriptionally convergent with those observed in ulcerative colitis. The intestinal epithelium thus functions as a dual-signal organizer of commensal-specific CD8 + T cell responses, coupling differentiation to restraint through spatially coincident molecular cues.

Background Resuming anticoagulation in patients with mechanical heart valves after intracranial hemorrhage presents a clinical dilemma. The optimal timing must balance the risk of thromboembolism against hemorrhagic expansion. Prior studies have addressed this issue, but most were limited by small sample sizes. This systematic review and meta‐analysis aimed to determine the optimal timing for anticoagulation resumption in this population. Methods We conducted a systematic review and meta‐analysis using PubMed, Embase, Web of Science, and Scopus from database inception to August 23, 2024. The target population included adults with intracranial hemorrhage who required anticoagulation for mechanical heart valves. Results Thirteen studies involving 788 patients were included: 12 retrospective and 1 prospective observational study. While off anticoagulation, 32 patients developed ischemic stroke, with a pooled event rate of 5.23% (95% CI, 3.80–7.20%) and negligible heterogeneity ( I 2 = 0%). The pooled average time to stroke was 8.08 days (95% CI, 1.99–14.18). After anticoagulation resumption, 73 patients experienced hemorrhagic recurrence, corresponding to a pooled event rate of 10.95%, with nonsignificant heterogeneity ( I 2 = 40.4%). Conclusions Withholding anticoagulation for up to 7 days after intracranial hemorrhage in patients with mechanical heart valves appears relatively safe. Hemorrhagic recurrence after resumption was more common than ischemic stroke during interruption. However, the included studies were observational and carried serious or critical risk of bias. Prospective multicenter studies, and ideally randomized trials, are needed to provide more definitive evidence.

Abstract Background Estimating bacterial load in clinical samples has important applications in tuberculosis (TB) management, including assessment of disease severity, treatment response, and baseline genome copies required for sequencing. However, rapid and affordable tools for quantifying Mycobacterium tuberculosis ( M. tuberculosis ) remain limited. Methods We developed a high-resolution melt (HRM) based quantitative PCR assay using molecular beacon chemistry targeting the single-copy RD9 region of M. tuberculosis . Analytical performance was assessed using 10-fold serial dilutions of H37Rv DNA. Clinical validation included DNA from 100 M. tuberculosis culture isolates and 40 sputum samples from Xpert MTB/RIF- and culture-positive pulmonary TB patients. To evaluate specificity, we tested 30 non-tuberculous mycobacterium (NTM) culture isolates from patients infected with Mycobacterium abscessus (n=25) and Mycobacterium fortuitum (n=5) and DNA from saliva samples of 10 healthy controls. Results The HRM-qPCR assay showed a linear dynamic range from 10 1 to 10 6 genome copies per reaction, with a lower limit of detection of 10 copies. Standardized melt-curve analysis yielded a single target-specific peak at 73.7±0.12°C across dilutions, confirming specific amplification. Sensitivity for M. tuberculosis detection was 100% in culture isolates and 95.0% (38/40) in sputum, with no false positives among M. tuberculosis -negative controls. Assay specificity was 100% in both culture isolates and sputum, with no additional melt peaks. We did not observe any peaks indicative of non-specific binding in NTMs. Amplification was observed in two NTM samples whose Tm matched M. tuberculosis RD9 (median M. tuberculosis copies=678.5), suggesting possible co-infection or contamination. No amplification or specific melt peaks were observed in saliva samples, indicating high probe specificity. Conclusions Molecular beacon-based HRM-qPCR assay enables rapid, highly specific quantification of M. tuberculosis genome copies in clinical samples and has potential utility for treatment monitoring, triaging specimens for sequencing, and assessing transmission risk in high-burden settings.

Kidney dysfunction after heart transplantation (HT) is associated with significant morbidity and mortality. Recipient and perioperative factors may all influence the risk of kidney injury. Furthermore, data suggest that the incidence of kidney dysfunction, both acute and chronic, is increasing after the implementation of the United States’ 2018 allocation system due to increasing use of temporary mechanical circulatory support and changing recipient characteristics. While data are robust regarding nephroprotective therapies such as renin-angiotensin-aldosterone system inhibition and SGLT2i (sodium-glucose cotransporter 2 inhibitors) to minimize the progression of chronic kidney disease in patients with heart failure, data in HT recipients are beginning to emerge. This state-of-the-art review will critically examine the existing literature regarding the epidemiology of kidney dysfunction after HT, mitigation strategies for acute kidney injury and chronic kidney disease, including pharmacotherapeutics, the need for kidney transplantation after HT, and practical next steps for the larger HT community.

Abstract Background The prevalence of heart failure with preserved ejection fraction (HFpEF) increases with age, and older adults with HFpEF have worse physical function, quality of life, and clinical outcomes. Semaglutide demonstrated efficacy in the treatment of obesity-related HFpEF in the STEP-HFpEF trials. Some have speculated that older patients may have less to gain from incretin therapies (and perhaps more to lose) than younger patients. Aims In this pre-specified pooled subanalysis of the STEP-HFpEF trials, we evaluated the efficacy of semaglutide across the age spectrum. Methods The STEP-HFpEF and STEP-HFpEF DM trials enrolled participants with obesity-related HFpEF and randomized them to semaglutide 2.4 mg once weekly (n = 573) or placebo (n = 572) for 52 weeks. Dual primary outcomes (change in Kansas City Cardiomyopathy Questionnaire clinical summary score [KCCQ-CSS] and change in body weight) and secondary outcome measures (6-minute walk distance [6MWD], C-reactive protein, hierarchical composite endpoint containing all-cause death, heart failure events, changes in KCCQ-CSS and 6MWD) were compared across specific age groups; <55 years, 55–64 years, 65–74 years and ≥75 years. Results Among 1145 randomized participants, 8.8% (N = 101) were <55, 23.3% (N = 267) were aged between 55–64, 42.4% (N = 485) were between 65–74, and 25.5% (N = 292) were 75 years or over. The efficacy of semaglutide on the dual primary endpoints was consistent across the age spectrum, KCCQ-CSS (p-interaction = 0.80), and body weight (p-interaction = 0.41). Similar benefits were observed for the key secondary endpoints, with no treatment effect heterogeneity across age groups. Moreover, the safety of semaglutide was consistent across age groups. Conclusion In patients with HFpEF enrolled across the STEP-HFpEF and STEP-HFpEF DM trials, treatment with semaglutide improved disease-specific symptoms, physical function and reduced body weight across the age spectrum. The safety profile of semaglutide was consistent in older and younger patients.

Abstract INTRODUCTION Alzheimer's disease (AD) is a progressive neurodegenerative disorder that needs better predictive tools. Using the National Alzheimer's Coordinating Center Uniform Data Set, this study developed machine learning (ML) models and a practical clinical tool for AD prediction. METHODS Data from 52,537 individuals (22,371 with AD) and more than 200 variables were processed with MissForest imputation and genetic algorithm‐based selection. Multiple ML models were trained, and interpretability was performed using SHAP and permutation importance. A LightGBM model was refined through iterative backward feature elimination (IBFE) followed by manual refinement. RESULTS LightGBM performed best (receiver operating characteristic‐area under the curve [ROC‐AUC] 0.91, accuracy 82.0%). Key predictors included arthritis, age, body mass index, and heart rate. A 19‐feature model retained accuracy (81.2%) and ROC‐AUC (0.90). DISCUSSION This lightweight tool predicts AD using mostly routine variables. Limitations include its cross‐sectional nature, and would need external validation. An interactive web app and GitHub resource are available. Highlights Developed a lightweight ML based tool using 19 routinely available features. The lightweight model achieved an ROC-AUC of 0.90 for Alzheimer's disease prediction on NACC multicenter data. Genetic algorithm, IBFE, and manual refinement enabled optimal feature selection. Tool hosted on an open‐access platform for clinical and research use. SHAP analysis provided model interpretability and feature‐level insights.

Importance Primary brain and central nervous system cancer (collectively referred to as CNS cancer) comprises 2% of all human cancers and poses significant health and economic challenges in the United States. Objective To analyze CNS cancer burden in the US, stratified by time, location (state and division), sex, age group, and Sociodemographic Index (SDI). Design, Setting, and Participants This cross-sectional study involved a repeated analysis of Global Burden of Disease Study (GBD) 2021 data in 2024. Using data from 183 sources, CNS cancer metrics in the US were estimated across states and years. US CNS cancer metrics across all sexes and age groups were included in the GBD. Exposure CNS cancer diagnosis. Main Outcomes and Measures Overall and age-standardized estimates of the incidence, prevalence, mortality, disability-adjusted life-years (DALYs), years of life lost, and years lived with disability per 100 000 population, including 95% uncertainty intervals (UIs), and time trends. Results In 2021, for all age groups and sexes across the US, there were 31 780 incident cases (95% UI, 29971.1 to 32843.9). Age-standardized incidence, DALYs, and mortality rates per 100 000 population were 6.91 (95% UI, 6.58 to 7.12), 134.38 (95% UI, 129.83 to 137.95), and 4.1 (95% UI, 3.87 to 4.22), respectively. Despite no significant change observed in the overall incidence between 1990 and 2021, DALY and mortality rates decreased by 15.77% (95% UI, −17.75% to −13.68%) and 8.41% (95% UI, −11.09% to −6.22%), respectively. Substantial geographic variability was noted. Mississippi, Alabama, Kentucky, and Kansas (West North Central and East South Central divisions) and West Virginia faced persistently high burdens over the past 30 years. Sex differences were evident; disease burden was consistently higher in males compared with females. Age-specific estimates showed a bimodal distribution: the youngest group (<5 years) showed a significant decrease in incidence rate (−34.42% to −11.56%), whereas older age groups (>70 years) experienced increasing trends. DALYs and mortality rates were negatively correlated with SDI (ρ = −0.6860 and ρ = −0.6391; P < .001). Conclusions and Relevance These findings provide valuable insights into the CNS cancer burden across the US by age, sex, location, and SDI, enabling better public health status assessments, health care policy restructuring, and resource redistribution for improved care.

PURPOSE Gender bias against girls may affect health-seeking behavior and outcomes of childhood cancer. This study aimed to study the nature and extent of gender bias in health care among caregivers of childhood patients with cancer and also in community. METHODS This cross-sectional mixed-methods study was conducted in a tertiary cancer hospital and an urban community between July 2021 and July 2023. Qualitative component included 26 in-depth interviews (IDI) and four focus group discussions (FGDs) with caregivers of children with cancer. IDIs and FGDs were conducted by a psychologist and continued until thematic saturation was reached. For quantitative part, a gender-bias questionnaire was finalized which was administered to 230 caregivers in hospital and 311 participants from the community, with children in family. RESULTS Most participants did not perceive personal gender bias; however, many acknowledged noticing gender bias in others. This bias was linked to girls being considered financial burdens and having reduced marital prospects due to illness. Reducing treatment costs, improving access, and education targeting societal mindsets were suggested measures to mitigate bias. In community, no significant difference was observed among the respondents based on sex of youngest child in family. However, in hospital, caregivers of male children were less likely to offer similar care to a child of opposite sex than that reported by caregivers of female children ( P = .01) for ailments like fever/diarrhea. Similar difference was not observed for other health care scenarios. CONCLUSION Gender bias against girls, including that in health care access, is influenced by societal norms. Even with little personal perception of bias, there was a significant perceived bias observed in others by the participants. This study identified the existence of gender bias affecting health care choices, including cancer care.

ABSTRACTBackgroundComplementary and alternative medicine (CAM) usage among childhood cancer patients remains understudied. Factors associated with CAM use and motivations of caregivers for using CAM remain poorly understood.MethodsThis cross‐sectional mixed‐methods study was conducted among caregivers of patients aged ≤18 years with confirmed cancer diagnoses. Caregivers were interviewed regarding CAM use, reasons for using/non‐using CAM, and views on CAM. Logistic regression identified factors associated with CAM use, whereas qualitative interviews explored motivations and barriers. The impact of CAM usage on 2‐year overall survival was explored.ResultsOut of 450 respondents, CAM usage was reported by 35.78% (n = 161), with home remedies (28.44%, n = 128) and AYUSH (Ayurveda, Unani, Siddha, Yoga, Homeopathy) therapies (13.56%, n = 61) being most common. CAM use was associated with symptom duration ≥30 days (adjusted odds ratio [aOR]: 1.71; 95% CI: 1.09–2.67; p = 0·019) and hematological malignancies (aOR: 2.05; 95% CI: 1.33–3.17; p = 0·001). Major motivations for CAM use included belief in effectiveness (44.72%, n = 72) and family recommendations (34.16%, n = 55). Qualitative interviews highlighted cost, accessibility issues, and diagnostic delays as key drivers of CAM adoption. The 2‐year survival probabilities of CAM users and nonusers were comparable (0.88 [95% CI: 0.83–0.94] vs. 0.87 [95% CI: 0.83–0.92], log‐rank p = 0.75).ConclusionCAM is frequently used by pediatric cancer patients, driven by caregiver beliefs, family influence, and access barriers. Addressing caregiver practices and integrating CAM discussions into care may enhance supportive strategies without impacting survival outcomes.