Citations

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.

Background : Hepatocellular carcinoma (HCC) remains a major cause of cancer-related mortality. Optimal treatment decisions are challenging, and existing treatment allocation frameworks may not fully reflect the evolving therapeutic landscape or contemporary clinical practices in North America. Methods : Using a modified Delphi process, a multidisciplinary panel of 20 North American experts in hepatology, medical oncology, surgery, radiology, and radiation oncology developed a consensus-based treatment framework for HCC, termed the BEACON-HCC system. The framework was informed by current evidence and expert opinion through iterative discussion and voting. In a pilot study using 29 real-world patient cases, we assessed concordance between external expert recommendations and BEACON-HCC recommendations and Barcelona Clinic Liver Cancer (BCLC) 2025 treatment recommendations. Results : The BEACON-HCC treatment allocation framework diverges from prior frameworks by incorporating nuanced clinical features such as degree of intrahepatic tumor burden and vascular invasion, and adverse tumor prognostic markers, to align treatment allocation with tumor biology and therapeutic potential. Key innovations include the incorporation of emerging modalities such as external beam radiation therapy (EBRT), transarterial radioembolization (TARE), and systemic-locoregional combination therapies. In the pilot exercise, expert treatment decisions showed 96.6% concordance with BEACON-HCC recommendations and 72.4% concordance with BCLC recommendations. Conclusions : BEACON-HCC is a consensus-based framework for treatment allocation that incorporates the expanding range of therapeutic options available to patients in the North American HCC population. Expert treatment decisions showed a high concordance with the BEACON-HCC system; further validation using empiric clinical data is planned through the HCC-Live Consortium.

Pediatric sarcomas are a heterogeneous group of rare mesodermal malignancies. These cancers, which affect children from infancy through adolescence and young adulthood, are in general challenging to treat with currently available therapies. Biologically, many are characterized by quiet genomes, fusion oncoproteins, immune “cold” microenvironments, and vast epigenetic deregulation that contributes to diverse and complex mechanistic drivers. Multifaceted advancements in research strategies, including high-throughput screening, new model systems, surfaceome profiling, and study of oncogenic fusion condensates have led to new opportunities for understanding the biology of pediatric sarcomas. To continue to make progress for these difficult to treat cancers, it will be critical to continue to improve access to bioinformatic data, approach patient care using innovative clinical trial frameworks, and foster interdisciplinary partnerships among medicinal chemists, scientists, clinicians, advocates, and industry partners.

Background With improvements in in vitro culture techniques, there has been a steady shift in practice to transfer in vitro fertilisation (IVF) embryos at the blastocyst-stage to increase pregnancy rates per embryo transfer (ET) and reduce the risk of multiple pregnancy. In patients with fewer embryos (≤5 zygotes), fresh cleavage-stage ET is still commonly performed to reduce the risk of cycle cancellation if no embryo survives to the blastocyst-stage in vitro. However, evidence for improved outcomes with cleavage-stage embryo transfer in this subgroup of patients is lacking. We will compare blastocyst-stage to cleavage-stage ET with regard to cumulative live birth rates (CLBR) per oocyte retrieval and other patient-centred cycle outcomes in patients with ≤5 zygotes. Methods and analysis Multicentre, randomised pragmatic comparative effectiveness trial with superiority design comparing blastocyst-stage to cleavage-stage ET in patients with ≤5 zygotes. This trial will enrol and randomise 1126 women aged 18–44 undergoing IVF to either fresh cleavage-stage or blastocyst-stage ET at eleven IVF centres. Surplus embryos will be vitrified at the blastocyst-stage. The primary outcome is the CLBR per oocyte retrieval. Secondary outcomes include: multiple pregnancy, pregnancy loss <20 weeks and cycle cancellation. Exploratory outcomes include: live birth per fresh ET, ectopic pregnancy, time to pregnancy, stillbirth, preterm birth, financial burden, patient distress and facilitators and barriers for patient involvement and implementation. All primary analyses will be conducted according to the intent-to-treat principle. We also will report per-protocol analyses as a sensitivity analysis. A multidisciplinary stakeholder team, including a 5-patient stakeholder panel, will participate in study design, conduct and oversight. Ethics and dissemination The Institutional Review Board at Beth Israel Deaconess Medical Center (BIDMC) provides central regulatory oversight. Results will inform timing of embryo transfer in patients with ≤5 zygotes and will be disseminated through academic publications, meeting presentations and communications to advocacy groups and patient participants. Trial registration number NCT06746129 .

ABSTRACT Background Higher time in sedentary behavior and insufficient physical activity are very common in bipolar disorder (BD). Whereas physical activity and exercise offer significant benefits across mental health, brain health, and heart health in BD. The International Society for Bipolar Disorders Nutrition and Exercise Task Force (NExT) synthesized evidence to evaluate the impacts of sedentary behavior, physical activity, and exercise on illness course, physical health, and treatment outcomes. Methods A best‐evidence synthesis was conducted using a question‐and‐answer format. We searched PsycINFO, SPORTDiscus, Embase, PubMed, and Web of Science from inception to March 1st, 2026, supplemented by reference lists and existing guidelines. Search terms included combinations of physical activity, exercise, sedentary behavior, and bipolar disorder‐related terms. Results Observational studies show that individuals with BD exhibit significantly higher sedentary behavior and lower physical activity compared to the general population, with notable discrepancies between self‐reported and objective measurements. Evidence on physical activity's protective role against BD onset is mixed, with some prospective and Mendelian randomization studies suggesting reduced risk, while others report bidirectional or null associations. Preliminary findings from clinical trials indicate that exercise improves overall functioning, reduces mood episode frequency and hospitalizations, and alleviates depressive symptoms, with one pilot study showing an 82% antidepressant response rate. Exercise also shows potential to reduce anxiety and improve sleep, though robust data are limited. Conclusions Despite limited high‐quality evidence, physical activity and exercise demonstrate promising physical and mental health benefits for individuals with BD. Future research should prioritize multicenter randomized controlled trials, enhanced assessment tools, and accessible, tailored programs to integrate physical activity into routine BD management.

Abstract Germinal center (GC)-derived lymphomas arise within a specialized immune ecosystem, yet whether malignant cells direct its remodeling remains unclear. Integrating genomic, transcriptomic, spatial, and functional analyses across follicular lymphoma and diffuse large B-cell lymphoma, we define a developmental framework linking malignant B-cell differentiation state to tumor microenvironment (TME) organization. Rather than segregating by histology, lymphomas align along a shared differentiation continuum in which proliferative dark zone (DZ) states associate with immune-depleted TMEs, whereas post-GC/memory B-cell (MBC) states drive inflamed but immunosuppressed TMEs. Spatial profiling reveals collapse of GC architecture and emergence of suppressive myeloid niches along this trajectory. Single-cell lineage reconstruction uncovers a DZ-to-MBC developmental axis underlying lymphoma evolution. Genetic reprogramming in vivo demonstrates that malignant differentiation state is sufficient to instruct TME remodeling. Collectively, these findings establish malignant differentiation state as a causal determinant of immune architecture across GC-derived lymphomas and identify lineage-directed immune reprogramming as a potential therapeutic strategy.

TRAIL is a TNF family ligand that trimerizes TRAIL-R1 (DR4) or TRAIL-R2 (DR5) to induce apoptosis, necroptosis, and/or NF-κB activation in receptor-bearing cells. We previously identified TRAILshort as a splice variant of TRAIL that lacks cysteine 230, cannot trimerize, and acts as a dominant-negative ligand that blocks TRAIL-mediated apoptosis. TRAILshort is expressed on cell surfaces and within extracellular vesicles, enabling it to confer TRAIL resistance to both producing and bystander cells. In this study, we showed that elevated TRAILshort levels were associated with chronic viral infections, cancer, and autoimmune diseases, suggesting a link to impaired immune regulation. Using unbiased phosphoproteomics and mechanistic studies, we demonstrated that TRAILshort binding to DR5 recruited and activated the phosphatase Src homology region 2 domain–containing phosphatase 1 (SHP-1), leading to zeta-chain-associated protein kinase 70 (ZAP-70) dephosphorylation, disruption of ZAP-70–CD3ζ interactions, and impaired T cell receptor signaling, thereby reducing T cell activation, proliferation, and cytokine production in response to antigen or CD3/CD28 ligation. Genetic or pharmacologic SHP-1 inhibition reverses these effects. In humanized mouse models, TRAILshort promoted the persistence of transformed mouse embryonic fibroblasts (MEFs) and L428 and antagonized CD19-directed CAR T cell activity, revealing TRAILshort as an immunomodulator of T cell function with therapeutic implications, including blocking TRAILshort to restore T cell immunity or delivering TRAILshort to enforce tolerance. TRAILshort, a variant of TRAIL, suppresses T cell function and immune responses in cancer and infectious diseases, highlighting its potential as a therapeutic target.

BMT CTN 1506 ("MORPHO") was a phase 3 study of post-hematopoietic cell transplantation (HCT) maintenance with gilteritinib versus placebo for patients with FLT3-ITD-mutated acute myeloid leukemia (AML) in first remission. Subgroup analysis indicated a significant benefit of post-HCT gilteritinib for participants in North America, but no benefit for those in Europe or Asia. We conducted a post-hoc analysis of the data focusing on days from AML diagnosis to HCT, pre-HCT FLT3 inhibitor use, and FLT3-ITD measurable residual disease (MRD). Participants transplanted &lt; 120 days from AML diagnosis and/or those treated with FLT3 inhibition pre-HCT were more likely to have improved survival from post-HCT gilteritinib. Pre-HCT MRD levels were higher (P = 0.001) in participants transplanted within 120 days from diagnosis and in those treated with a FLT3 inhibitor pre-HCT and transplanted within 120 days (P = 0.008). Pre-HCT MRD was dependent on both FLT3 inhibitor use and time to HCT, as participants treated with successive courses of chemotherapy + FLT3 inhibition had successively lower MRD by the time of HCT. Time from AML diagnosis to HCT and pre-HCT FLT3 inhibitor use both appeared to impact MRD levels immediately prior to HCT, and geographic differences in these two practice patterns likely accounted for the observed regional differences in benefit from post-HCT gilteritinib. Increasing the number of courses of treatment pre-HCT may lower MRD sufficiently to eliminate the need for post-HCT inhibition, but with a presumed risk of some patients experiencing early progression. This trial was registered at www.clinicaltrials.gov as #NCT02997202.

ABSTRACT Background and Aims It remains unclear whether different factors influence 30‐ and 90‐day readmission rates. We identified predictors of 90‐day mortality in a global cohort of hospitalised patients with cirrhosis. Methods Variables associated with 30‐ and 90‐day post‐discharge readmission, liver transplantation (LT), and mortality were compared in prospectively enrolled, non‐electively hospitalised adult patients with cirrhosis. Results We enrolled 4208 patients from 125 centres across 37 countries. Alcohol‐related liver disease was the most common aetiology of cirrhosis (40%), followed by hepatitis B virus infection (21%); 47% were readmitted, 8% received liver transplantation (LT), and 23% died within 90 days post‐discharge. In multivariable analysis, country income was significantly associated with both 30‐ and 90‐day readmission rates, the receipt of LT, and mortality within 30 and 90 days post‐discharge (all p ‐values < 0.001). Independent predictors of higher rates of 30‐ and 90‐day readmissions, respectively, were disease severity ( p < 0.001, p = 0.003), prior ascites ( p = 0.025, p = 0.016), prior hospitalisation ( p < 0.001), hyponatremia ( p < 0.001, p = 0.008), and in‐hospital vasopressor use ( p = 0.002, p = 0.011). Prior variceal bleeding independently predicted higher 90‐day readmission rates, whereas age, disease severity, mechanical ventilation, and in‐hospital vasopressor use (all, p < 0.001) increased odds of 30‐ and 90‐day post‐discharge death. Additionally, admission ( p = 0.011) and nosocomial ( p = 0.022) infections increased the odds of 90‐day post‐discharge death. Conclusion In a global cohort of hospitalised patients with cirrhosis, patients in high‐income countries exhibited the highest rates of 30‐ and 90‐day readmission, alongside lower mortality rates and a higher incidence of LT. Variables that predict 30‐day readmission also predicted 90‐day readmission. Understanding these disparities is essential for achieving health equity.

Abstract Introduction Microglia are the resident immune cells of the central nervous system, classically studied for neuroinflammation. A specialized subset, vessel-associated microglia (VAM), whose somata directly contact capillaries, constitutes ∼30% of microglia in the naïve brain. Only recently have VAM been recognized as regulators of brain circulation, influencing blood—brain barrier (BBB) integrity and cerebral blood flow, yet their role in pathological vascular remodeling remains unclear. To address this gap, we used glioma models in which peritumoral capillaries undergo extensive vascular remodeling and BBB dysfunction, providing an in vivo platform to probe capillary vulnerability and vascular stability. Methods We combined pharmacological microglial ablation via CSF1R inhibitors with longitudinal in vivo two-photon imaging to visualize microglia—capillary interactions. Behavioral testing, survival analysis, T2-weighted MRI, and immunostaining were performed in parallel. Results Over half of the microglia-depleted mice developed acute, lethal paralysis by 15 days, whereas control tumor-bearing mice remained asymptomatic and survived 30 days. MRI revealed large intracranial hemorrhages and severe edema, and two-photon imaging showed nodular, abnormal vasculature at paralysis onset. The peritumoral region contained dense capillary networks with a marked increase in VAMs (&gt;60%). Genetic lineage tracing confirmed these cells were microglia, exhibiting elongated, vessel-wrapping morphology, also observed following single-vessel photothrombosis and consistent with a response to capillary injury. Conclusion Our findings identify VAMs as critical neurovascular stabilizers that preserve peritumoral capillary integrity and prevent lethal hemorrhage in glioma, highlighting an essential immune role in brain vascular homeostasis. Notably, intracranial hemorrhage has repeatedly emerged across clinical trials of CSF1R inhibitors, raising important safety considerations for CSF1R-targeted therapies in the diseased brain. Funding Source AHA postdoc fellowship (26POST1560008) (J.Z.) Topic Categories Neuroimmunology (NEUR)