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ABSTRACT Background While vaccination is a key strategy to mitigate the severity of coronavirus disease 2019 (COVID‐19) in children, the risk factors for symptomatic, medically attended (hereon referred to as “symptomatic”) COVID‐19 and the impact of vaccination are not well defined among pediatric solid organ transplant recipients (PSOTR). Methods PSOTR aged six months through 21 years at 11 centers in the Pediatric Infectious Diseases Transplant Network (PIDTRAN) were analyzed retrospectively for symptomatic COVID‐19 between July 2021 and May 2023. Using a Cox proportional hazards model, risk factors associated with COVID‐19‐associated hospitalization, in‐hospital oxygen use, mechanical ventilation, and the impact of COVID‐19 vaccination were analyzed. Results Of 1370 PSOTR, 410 (29%) had symptomatic COVID‐19 infection. Among those with symptomatic infection, 115 (28%) were hospitalized, 35 required in‐hospital oxygen, and three required mechanical ventilation. In the study, 45% were unvaccinated against COVID‐19. Compared to unvaccinated PSOTR, incompletely vaccinated PSOTR had 56% lower hazard (95% CI 0.26, 0.72, p = 0.001) of COVID‐19‐associated hospitalization whereas completely vaccinated did not have a statistically significant difference in hazard of hospitalization. Receipt of at least one dose of the bivalent vaccine was also associated with 92.5% lower hazard (95% CI 0.010, 0.55, p = 0.011) of hospitalization. Risk factors for hospitalization included chronic kidney disease, underlying heart disease, neurodevelopmental delay, and lymphocytopenia. Conclusions Most PSOTR with symptomatic COVID‐19 did not require hospitalization or respiratory support. Several comorbidities and lymphocytopenia are associated with severe COVID‐19 in PSOTR. COVID‐19 vaccination, mostly, protected PSOTR against COVID‐19‐associated hospitalization, but vaccine uptake among PSOTR was low. image

ABSTRACT Many real‐world patients with advanced biliary tract cancer (BTC) are excluded by TOPAZ‐1 criteria; this study assessed cisplatin and gemcitabine plus durvalumab (CGD) efficacy and safety in these patients. Data from 1358 patients with advanced BTC treated with first‐line CGD across 55 international centers were retrospectively analyzed. Patients were classified as TOPAZ‐1‐in (meeting all inclusion criteria) or TOPAZ‐1‐out (meeting ≥ 1 exclusion criterion). Primary endpoints were overall survival (OS) and progression‐free survival (PFS); secondary endpoints included objective response rate (ORR), disease control rate (DCR), and safety. Furthermore, OS and PFS of the TOPAZ‐1‐out cohort were compared with reconstructed survival data from the phase III trial. 912 (67.1%) patients were classified as TOPAZ‐1‐in , and 446 (32.9%) as TOPAZ‐1‐out . After a median follow‐up of 14.5 months (95% CI: 13.7–36.5), OS was 16.1 months in TOPAZ‐1‐in and 12.5 months in TOPAZ‐1‐out (HR 0.69, 95% CI: 14.6–16.5, p = 0.0001); PFS was 8.2 versus 6.5 months (HR 0.73, 95% CI: 7.1–8.1, p < 0.0001). Median OS in the TOPAZ‐1‐out cohort (12.5 months) was nearly identical to the phase III trial experimental arm (12.9 months; HR 1.15, p = 0.13); for PFS the HR was 1.12 (95% CI 0.93–1.42; p = 0.09). Among TOPAZ‐1‐out patients, active infection, elevated bilirubin, and ECOG PS > 1 were linked to poorer OS, while no detrimental impact emerged for ALT/AST abnormalities, corticosteroid use, renal or hematologic parameters, or prior surgery within 6 months, suggesting treatment effectiveness was broadly maintained across clinical subgroups. Furthermore, TOPAZ‐1‐out patients experienced no significant increase in adverse events compared with the TOPAZ‐1‐in group. Real‐world data suggest CGD may be effective in TOPAZ‐1‐out patients, with no evident increase in toxicity, supporting the potential expanded use of the regimen in clinical practice.

Amyloid-targeting therapies (ATTs), including donanemab and lecanemab, are FDA-approved disease-modifying therapies for Alzheimer’s disease in the mild cognitive impairment or mild dementia stages. Early initiation is important for optimal outcomes. This article summarizes practical strategies for implementing ATTs in clinical practice, focusing on leadership alignment and infrastructure development, as well as patient identification, diagnosis, and monitoring protocols. Key recommendations include establishing appropriate patient tracking systems, infusion and imaging protocols, and interprofessional collaboration. Approaches for systematic patient routing (e.g., hub-and-spoke models, fast-track mechanisms) and biomarker-integrated assessments are critical to facilitating timely diagnosis and treatment. Education for patients, care partners, and clinicians is crucial for managing the risks associated with amyloid-related imaging abnormalities. Successful ATT implementation requires coordinated systems, timely diagnosis, and robust safety monitoring. These measures can enable frameworks for ATT administration to optimize outcomes for patients, care partners, and health systems.

Summary Background Body composition is recognized as a major determinant of health outcomes, but its multidimensional nature makes clinical adoption challenging. We sought to develop and validate a body composition index (BCI) for all-cause mortality risk assessment, integrating variables of six body composition tissues. Methods We analyzed 28509 consecutive patients undergoing myocardial perfusion imaging with routine low-dose chest CT attenuation correction (CTAC) scans acquired during myocardial perfusion imaging (MPI) at 12 centers across four countries. An artificial intelligence-based BCI was developed in a cohort of 15037 patients’ CTACs by integrating the CT-derived metrics of bone, skeletal muscle, and four adipose tissue compartments, coronary artery calcium score, and basic demographic variables (age, sex, BMI). The performance of BCI for mortality prediction was validated in an internal cohort of 6444 patients and an external cohort of 7028 patients by prognosis, calibration, net benefit, and explainability. Model-based simulation of tissue metrics modification was performed to evaluate estimated mortality risk reduction. Findings During a median of 3.5 (IQR [1.9, 5.1]) years, 4697 (16%) patients died. In the external testing cohort, the BCI demonstrated excellent discrimination for mortality (area under receiver operating characteristic curve 0.78 (95% CI [0.76, 0.79]) and Harrell’s concordance index 0.75 [0.73, 0.76]), calibration, and net benefit overall and across pre-specified subgroups stratified by patient characteristics and imaging protocols. Visceral adipose tissue attenuation was the most influential body composition measure, followed by skeletal muscle volume. Simulated improvement in body composition was associated with significant mortality risk reduction. Interpretation An index combining six body composition measures obtained opportunistically from routine chest CT provides robust mortality risk stratification. By converting complex body composition information into a single interpretable score, the BCI can facilitate clinical implementation of opportunistic CT biomarkers and guide individualized preventive strategies. Funding National Institute of Health Research in context Evidence before this study We searched PubMed and Google Scholar on July 7, 2026 for English language studies using the terms (“mortality prediction” OR “death prediction”) AND (“integrated body composition analysis” OR “body composition metrics integration”) AND (“predictive model” OR “model development”), and identified 41 publications describing predictive models incorporating body composition metrics. Recent advances in artificial intelligence (AI) have enabled increasingly granular quantification of body composition from CT, with multiple tissues and tissue-specific metrics showing independent prognostic value for all-cause mortality (ACM) prediction. However, reported associations of body composition metrics with mortality risk were highly inconsistent or even contradictory across studies. This heterogeneity likely reflected the differences in study design or the inherent complexity of body composition analysis, such as the interaction among variables derived from multiple tissues. Thus, it is difficult to interpret body composition results reliably in clinical practice. We hypothesized that integrating multiple body composition metrics could achieve comprehensive and reliable prediction of mortality across patient populations. Added value of this study In this large international, multicenter longitudinal cohort study of 28509 consecutive patients with suspected or known coronary artery disease (CAD) undergoing myocardial perfusion imaging across 12 sites in four countries, we developed and externally validated an artificial intelligence-based body composition index (BCI) for all-cause mortality prediction. The BCI integrated chest CT-derived metrics of six body composition tissue compartments – bone, skeletal muscle (SM), subcutaneous adipose tissue (SAT), intramuscular adipose tissue (IMAT), visceral adipose tissue (VAT), and epicardial adipose tissue (EAT), together with demographics (age, sex, BMI) and CT-derived coronary artery calcium (CAC) score, all derived automatically from routine low-dose attenuation correction CT scans without additional imaging or laboratory tests. In an external validation cohort of 7028 patients, the BCI achieved robust discrimination for mortality prediction, substantially outperforming a baseline model using demographics and calcium score alone, and exceeded the discriminative performance of prior body composition models. Performance was consistent across subgroups defined by sex, age, body mass index, cardiometabolic risk factors, imaging modality, and acquisition protocol, supporting generalizability across clinical settings. The BCI demonstrated excellent calibration and net clinical benefit. Explainability analysis identified visceral adipose tissue attenuation and skeletal muscle volume as the dominant contributors to mortality risk, offering tissue-specific therapeutic targets that complement generic weight-based metrics. Model-based simulations suggested that improvements in these specific compartments could reduce estimated mortality risk more effectively than equivalent changes in BMI alone, pointing toward precision therapeutic targets beyond weight reduction. Our study improved over previous literatures on body composition-based predictive models in one or more of the following ways: (1) we considered six types of body composition tissues while existing studies considered only three or less tissues, thus significantly higher granularity and improved ability to capture refined tissue interactions; (2) our model was rigorously validated in external sites, showing cross-site generalizability while most previous work lacked external validation; (3) our model achieved significant prediction performance improvement over previous body composition predictive models, offering better clinical outcomes prediction and facilitating the suitability for widespread clinical adoption; (4) our study was conducted with a large multi-center cohort across multiple countries, achieving statistical power and demonstrating reliability towards patients characteristics and imaging acquisition protocols while previous studies involved small single-center cohorts; (5) our model required only CT scans and basic demographics which were widely available in clinical routine while the existing models required dedicated laboratory tests or specialized imaging modalities, enhancing the applicability in routine clinical practice. Implications of all the available evidence BCI offers an explainable and clinically deployable tool for improved prediction of mortality risk from existing chest CT scans. Its use could inform updates to existing risk models, guide precision preventive strategies, and support development of therapeutics targeting specific body composition phenotypes.

Abstract INTRODUCTION Associations of arterial stiffness, measured through pulse wave velocity (PWV), with incident dementia may be driven by age‐related structural changes to the arterial wall or by elevated blood pressure. METHODS Dementia‐free White or Black participants in the community‐based Atherosclerosis Risk in Communities (ARIC) cohort study with measures of PWV were examined. The associations of carotid‐femoral PWV (cfPWV) and total, structural, and load‐dependent PWV with dementia were estimated using Poisson regression models and Cox proportional hazards models. Dementia cases were defined by physician‐adjudicated review, telephone interviews, hospitalization records, and death certificates. RESULTS Of 4818 participants included in the study population (mean age: 75 years; 41% male, 21% Black), 1067 (22%) developed dementia over a median follow‐up of 9.0 years. Higher cfPWV, total PWV, structural PWV, and load‐dependent PWV were associated with greater dementia risk. DISCUSSION Both structural and pressure‐related arterial stiffness mechanisms may underlie the link between PWV and dementia.

The Impella 5.5 is an axillary mechanical circulatory support device used in patients with cardiogenic shock, but those with small left ventricular (LV) cavities may be at risk for suction events, hemolysis, malpositioning, hypoperfusion, and LV injury. Informally accepted guidelines, extrapolated from durable LVAD studies, suggest a minimum left ventricular internal dimension in diastole (LVIDd) of 58 mm, with some clinical practices using a more stringent ≤52 mm cutoff. We retrospectively analyzed 154 consecutive patients supported with Impella 5.5 between January 2020 and December 2024. Overall, 38 patients had an LVIDd ≤58 mm, and 116 had an LVIDd &gt;58 mm; a key subgroup of 21 patients presented with a very small LVIDd of ≤52 mm]. Baseline demographics, comorbidities, body mass index, and renal function were similar [across groups], although those with larger LVIDd had lower ejection fractions (16% vs. 24%, p = 0.001). Median support duration was 24 days in all groups, and pre- and post-implant hemodynamic and laboratory improvements were comparable. Rates of transplantation (79% vs. 90%, p = 0.088) and LVAD implantation (2% vs. 6%, p = 0.159) did not differ significantly in the ≤58 mm cohort. Notably, within the ≤52 mm subgroup, 90-day survival remained high at 90.5% ( p = 0.336), with significant improvements in right atrial pressure (17 to 10 mmHg, p = 0.041), mean pulmonary artery pressure (36 to 26 mmHg, p = 0.008), and eGFR (45 to 57 mL/min/1.73m 2 , p = 0.003). Remarkably, native cardiac recovery was observed exclusively in the smaller LV cohorts, occurring in 11% of the ≤58 mm group ( p = 0.003 vs. 0%, p = 0.003) and reaching 19% in the ≤52 mm group (vs. 0% in larger cavities, p &lt; 0.001), while durable LVAD escalation was entirely avoided in the ≤52 mm cohort (0% vs. 6%). Ninety-day event-free survival was excellent across all cohorts 92% vs. 96% in the primary analysis, with no major device-related complications, suction events, clinically significant hemolysis, bleeding, stroke, or escalation to Bi-VAD support. These findings strongly support the safety and feasibility of Impella 5.5 in extremely constrained, small LV cavities.

Breast cancer is the most common cancer in women, causing more than 600,000 deaths every year. The human microbiome is increasingly recognized as a key regulator of cancer initiation, progression, and therapeutic response. Postbiotics—defined as non-viable microbial cells and/or their structural components and metabolites that confer health benefits—are emerging as promising and safer alternatives to live probiotics in oncology. This review provides a comprehensive mechanistic overview of the potential role of postbiotics against cancer, with a specific focus on breast cancer. Preclinical evidence demonstrates that selected postbiotics exert dose- and time-dependent anticancer effects against multiple breast cancer subtypes by modulating key oncogenic pathways (such as PI3K/AKT and NF-κB) and inducing epigenetic regulation through histone deacetylase inhibition. Beyond direct effects on tumor cell proliferation and apoptosis, postbiotics influence the breast cancer microenvironment by reshaping cytokine networks, suppressing pro-metastatic inflammation, and enhancing antitumor immune responses through the activation of NK cells and T cells. We also provide emerging links between microbiome composition, estrobolome activity, and breast cancer subtype-specific biology. Despite these encouraging findings, the clinical translation of postbiotics in oncology remains limited. Currently, only one registered clinical trial investigates postbiotics in the oncology setting (melanoma), and no clinical trials have specifically evaluated postbiotics in breast cancer patients. This highlights a substantial translational gap between preclinical evidence and clinical application. Accordingly, well-designed, tumor-specific clinical trials are urgently needed to validate the safety, efficacy, and therapeutic potential of postbiotics as novel strategies in personalized breast cancer management.

Importance Elevated low-density lipoprotein cholesterol (LDL-C) is a modifiable risk factor for cardiovascular disease, the leading cause of premature death worldwide. Assessing the LDL-C–related burden is critical for guiding prevention and treatment strategies. Objectives To estimate the global, regional, and national burden of ischemic heart disease and ischemic stroke attributable to elevated LDL-C (relative to 35-54 mg/dL) from 1990 to 2023 and to quantify the contributions of population growth, aging, risk-deleted burden, and exposure changes to burden trends. Design, Setting, and Population This comparative risk assessment, part of the Global Burden of Disease Study 2023, estimated population-level LDL-C exposure and associated health loss in 204 countries and territories. Mean LDL-C levels were estimated using spatiotemporal gaussian process regression based on 806 studies across 161 countries. Relative risks were derived from meta-analyses of 38 randomized clinical trials. Population-attributable fractions for deaths and disability-adjusted life-years (DALYs) were estimated by age and sex for adults aged 25 years or older from 1990 to 2023, with 95% uncertainty intervals. Exposure Population-level LDL-C concentrations. Main Outcomes and Measures Population-attributable fractions, counts, and rates (all ages and age standardized per 100 000) of LDL-C–attributable deaths and DALYs from ischemic heart disease and ischemic stroke, with uncertainty intervals. Results In 2023, elevated LDL-C accounted for 3.6 million deaths (95% uncertainty interval, 2.2-5.4 million; 6.0% of global mortality) and 90.7 million DALYs (95% uncertainty interval, 58.9-123.3 million; 3.2% of DALYs). Although global all-ages rates remained stable, age-standardized death and DALY rates decreased by 45.6% and 39.5%, respectively, since 1990. In 2023, age-standardized LDL-C–attributable DALY rates were highest in Eastern Europe and lowest in high-income Asia-Pacific. One-third of the global LDL-C burden occurred in India and China. Population growth and aging drove the increasing burden, with notable regional disparities in LDL-C exposure and risk-deleted DALY rates shifting toward middle-sociodemographic settings. Conclusions and Relevance Despite declining age-standardized rates, the absolute LDL-C burden has increased since 1990 due to demographic changes and has shifted toward middle-sociodemographic countries. Measurement and surveillance gaps persist. Strengthened prevention, diagnosis, and treatment access strategies are essential to mitigate the health burden of LDL-C.

ABSTRACT Surgery after response to first‐line chemoimmunotherapy may offer a potential curative option for patients with locally advanced biliary tract cancer (BTC) initially considered unresectable. However, robust real‐world evidence in this setting remains limited. We retrospectively analyzed patients with locally advanced BTC treated with first‐line cisplatin, gemcitabine, and durvalumab (CGD) across 55 centers in 12 countries. Endpoints included overall survival (OS), progression‐free survival (PFS), disease‐free survival (DFS) among resected patients, objective response rate (ORR), and the prognostic impact of surgery. A multivariable logistic regression model was developed to predict surgical conversion using baseline clinical and laboratory variables. Among 1358 screened patients, 219 had locally advanced disease and were included in the analysis. Median follow‐up was 14.5 months. ORR was 34.6%, with median PFS and OS of 10.0 and 20.7 months, respectively. Twenty‐four patients (10.9%) underwent surgical resection after systemic therapy. Median OS was 22.5 months in resected patients versus 19.9 months in those who did not undergo surgery. Median DFS after resection was 15.8 months. Pathological lymph node involvement was independently associated with shorter DFS. Larger baseline tumor size correlated with higher odds of radiological response but not with OS. An exploratory elastic‐net model retained four baseline variables and showed moderate discriminative ability for surgical conversion, with an apparent AUC of 0.72 and an optimism‐corrected AUC of 0.65. First‐line CGD enabled secondary resection in approximately 11% of patients with locally advanced BTC. A simple baseline model may support patient selection for conversion surgery, although prospective validation is needed.

Stem cell-derived β (SC-β) cells are a promising therapy for type 1 diabetes (T1D), but their long-term efficacy is limited by immune-mediated graft rejection. Platelet-derived exosome product (PEP) has emerged as a novel immunomodulatory agent, although its effect on SC-β cell xenograft rejection remains unclear. Here, we evaluated PEP in stimulated human peripheral blood mononuclear cells (PBMCs) and in an immunocompetent mouse model of SC-β cell transplantation under the kidney capsule. Immune-related gene expression was assessed by quantitative PCR, immune cell infiltration by immunofluorescence, and graft function by circulating human insulin. In vitro, PEP reduced NK-cell-associated gene expression, including NK1.1, EOMES, and KLRK1, and increased IL-10 expression. In vivo, untreated SC-β cell xenografts showed progressive immune infiltration and loss of detectable human insulin by day 14, whereas PEP-treated grafts retained detectable insulin through day 14 across co-transplantation, pretreatment, and systemic administration strategies. PEP co-transplantation delayed, but did not prevent, xenograft rejection, with graft loss observed by day 21. This delay was associated with reduced NK1.1+ cell infiltration and lower expression of selected inflammatory and rejection-associated markers, including NK1.1, Nos2, and Nlrp3. These findings suggest that PEP modulates graft-associated immune responses and may serve as an adjunct immunomodulatory strategy for stem cell-based therapies for type 1 diabetes. Further studies are needed to evaluate sustained graft durability, safety, and translational efficacy.