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Photodynamic priming (PDP), a fallout of photodynamic therapy, transiently modulates the tumor microenvironment (TME), enhances therapeutic susceptibility, and promotes immunogenic cell death through the release of damage-associated molecular patterns (DAMPs). Pancreatic ductal adenocarcinoma (PDAC) remains non-responsive to current therapies with a desmoplastic and immunosuppressive TME that limits drug delivery and blunts responses to immune checkpoint blockade. We investigated whether PDP could enhance anti-PD1 therapy responses in PDAC using patient-derived organoids (PDOs). PDOs were treated with Visudyne and red light (25, 75, and 100 J/cm²), followed by assessment of cytotoxicity, DAMP expression (HSP60, calreticulin, HMGB1), and transcriptomic changes. Monocyte-derived dendritic cells (mDCs) from healthy donors were cocultured with PDP-treated (25 J/cm 2 ) PDOs, then with matched naïve T cells. mDC and T cell activation markers were analyzed. Pembrolizumab (anti-PD1) was added to PDO-mDC-T cell cocultures to evaluate combined effects on PDO viability and T cell activation. PDP induced dose-dependent cytotoxicity and upregulated DAMPs. Gene profiling in PDOs showed increased IFN-γ , TNF-α , and CXCL12 , with reduced PD-L1 , TGF-β1 , and FOXP1 expression. mDCs exposed to PDP-treated PDOs upregulated CD40, CD86, and MHC-II, driving activation of CD4 + and CD8 + T cells, evidenced by elevated PD1 expression. Addition of pembrolizumab further decreased PDO viability and amplified effector cytokines ( IFN-γ , TNF-α , FASLG , granzyme B, IL-2 , IL-21 ). PDP was associated with modulation of the PDAC TME toward a more immunogenic phenotype by enhancing tumor immunogenicity, activating dendritic cells and T cells, and potentiating PD1 blockade. These findings provide mechanistic support for further preclinical and clinical evaluation of PDP combined with checkpoint inhibition in PDAC.

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: Whether robot-assisted cholecystectomy reduces bile duct injury compared with laparoscopic cholecystectomy remains uncertain because prior studies have inadequately accounted for disease severity and have rarely classified injury severity using standardized criteria. This study compared perioperative outcomes after robot-assisted and laparoscopic cholecystectomy across a large healthcare system while adjusting for operative complexity. Study Design: Adults undergoing robot-assisted or laparoscopic cholecystectomy within the Mayo Clinic Enterprise (2014–2025) were retrospectively evaluated. Propensity score weighting adjusted for demographics, surgeon case volume, learning curve, and disease severity using the Tokyo Guidelines and Parkland grading system in patients with acute cholecystitis. The primary outcome was bile duct injury; secondary outcomes included general and procedure-specific complications. Results: Among 23,513 patients (19,998 laparoscopic; 3,515 robotic), robot-assisted cholecystectomy was used more frequently for Parkland grade ≥3 disease. Overall, 227 bile duct injuries occurred (204 laparoscopic; 23 robotic), corresponding to absolute risks of 1.02% and 0.65%, respectively (absolute risk difference −0.37%, 95% CI −0.72% to −0.02%; number needed to treat, 273). Robot-assisted cholecystectomy was associated with lower odds of conversion to open surgery, 30-day readmission, and mortality, shorter hospital stay (β −0.56, 95% CI −0.66 to −0.45; P<0.001), and a 5-minute longer median operative time. In acute cholecystitis, robot-assisted cholecystectomy was associated with lower adjusted odds of bile duct injury (aOR 0.29, 95% CI 0.07–0.78; P=0.011). Conclusions: After adjustment for disease severity and surgeon-related factors, robot-assisted cholecystectomy was associated with lower odds of bile duct injury in acute cholecystitis and improved perioperative outcomes, including shorter hospitalization and lower conversion rates, despite greater use in more complex cases.

Abstract Introduction As the incidence of metastatic spine disease (MSD) increases, treatments to manage refractory pain, pathologic vertebral body fractures, and spinal cord compression are becoming increasingly common. Given the palliative nature of surgical intervention used to achieve tumor control and thus mitigate loss of neurologic function and compromised ambulatory function, it is essential to mitigate the risk of such procedures. Methods The AO Spine Knowledge Forum Tumor’s Metastatic Tumor Research and Outcomes Network (MTRON), an international, prospective registry for patients with spinal metastases, was used for this query. Prospective collection included baseline health and demographic information, oncologic data (including Spinal Instability Neoplastic Score (SINS) score and Bilksy epidural compression classification), and baseline functional status (preoperative American Spinal Injury Association (ASIA) and ECOG scores). Health related quality of life (HRQoL) data included Spine Oncology Study Group Outcomes Questionnaire (SOSGOQ2.0) and Euro-QoL measures. Surgery related adverse events (AE’s) were collected using the Spine Adverse Events Severity (SAVES V2) framework. Kaplan-Meir curves were used to assess survival. Results The cohort consisted of 1267 patients, 701 male (55.3%). A total of 245 (19.3%) experienced at least one postoperative AE, the majority of which were considered minor (grade 3 or less). Among the most common were deep wound infections (3.2%), wound dehiscence (2.5%), and urinary infections (2.4%). A multivariate analysis demonstrated that age, smoking status, ECOG performance, prior radiotherapy, presence of multiple metastases at other sites, and multiple spine metastases were significant risk factors for a postoperative AE. Postoperative AE’s (p = 0.049) and major postoperative AE’s (p = 0.0038) were found to be related to survival as well as a significant change in HRQoL scores (p &lt; 0.001). Conclusion Postoperative AE’s are extremely relevant to the care of patients with MSD and impact both HRQoL and survival.

Abstract Introduction Postoperative radiotherapy is an adjuvant therapy for brain metastases(BrMs) that improves local recurrence(LR). The radiosensitivity index(RSI) is a 10-gene index of pan-cancer molecular radiosensitivity previously validated for predicting radiotherapy response in clinical datasets. In this external validation study, we evaluate RSI as a predictor of local recurrence(LR) after radiotherapy in resected BrM. Methods Patients from University Health Network Toronto(UHN) and McGill University who had a resected BrM and subsequently underwent whole brain radiation(WBRT) or stereotactic radiosurgery(SRS). RSI was calculated using a ranked linear regression model from the weighted expression of 10 radiosensitivity genes, with higher values corresponding to radioresistance. Radiophenotype was determined using a previously validated RSI cutoff of &lt; 0.375 to identify radiosensitive tumors. LR was defined as recurrence in the resection cavity and overall survival(OS) was measured from time of BrM diagnosis. Results 106 BrM patients were included, comprising 29 breast, 37 GI, 33 lung, and 7 melanoma primary sources. Mean age at surgery was 59.2 years, 31.1%(n = 33) were male, 67.9%(n = 72) had WBRT, 23.6%(n = 25) had a subtotal resection, and 30.2%(n = 32) had postoperative chemotherapy. Overall, 34.0%(n = 36) patients had LR. Patients with breast BrMs had median RSI 0.70(IQR:0.55-0.75, 10.3% radiosensitive) with 48.3% LR(n = 14); gastrointestinal BrMs had median RSI 0.43(IQR: 0.35-0.46, 29.7% radiosensitive) and 24.3% LR(n = 9); lung BrMs had median RSI of 0.67(IQR:0.66-0.71, 9% radiosensitive) and 33.3% LR(n = 11); melanoma BrMs had median RSI of 0.72(IQR:0.53-0.92, 0% radiosensitive) and 28.6% LR(n = 2). After adjusting for demographics, primary organ, radiotherapy, resection extent, among others, RSI did not predict LR(p = 0.56) or OS(p = 0.61). Discussion RSI did not predict either LR or OS in patients with surgically resected BrMs status post radiotherapy, further establishing the need for improved predictive scores in this population.

Objective To compare perioperative outcomes, complications, imaging utilization, and device management following posterior vault distraction osteogenesis (PVDO) and spring-mediated cranioplasty (SMC) for multisutural craniosynostosis. Design Retrospective cohort study. Setting Single pediatric tertiary care center. Patients, Participants Twenty-three patients with multisutural craniosynostosis treated between 2017 and 2025 (PVDO, n = 18; SMC, n = 5). Interventions PVDO or SMC. Main Outcome Measure(s) Time to device removal, imaging utilization, reoperations, readmissions, device-related complications, revision surgeries, wound infections, and absolute intracranial volume change. Results PVDO was associated with earlier device removal than SMC (78.7 ± 22.1 vs. 133.0 ± 27.4 days; P = .0015) but greater postoperative imaging utilization during the first year (5.33 ± 1.28 vs. 2.80 ± 1.64 studies; P = .01). Rates of reoperation (22.2% vs. 0%), readmission (22.2% vs. 40.0%), device-related complications (11.1% vs. 0%), revision surgery (16.7% vs. 0%), and wound infection (22.2% vs. 20.0%) did not differ significantly (all P ≥ .50). Preoperative imaging utilization and postoperative intracranial volume gain were comparable between groups. Conclusions PVDO and SMC demonstrated similar safety profiles and intracranial volume expansion in patients with multisutural craniosynostosis. Compared with SMC, PVDO enabled earlier device removal but required increased postoperative imaging. These findings may inform operative planning, postoperative surveillance, and family counseling. Larger, multicenter studies with longer follow-up are needed to evaluate long-term outcomes.

Ascites development in cirrhosis reduces 5-year survival from 80% to 30%, yet substantial heterogeneity exists among patients with comparable ascites severity. This multicenter retrospective cohort study included adult liver transplant candidates with ascites at 4 United States centers (2015–2024). Latent class analysis was performed using 7 clinical variables: ascites grade, bilirubin, albumin, platelet count, estimated glomerular filtration rate, systolic blood pressure, and portal vein thrombosis. The derivation cohort (n=625) from the University of California San Francisco and Columbia University was randomly split 80/20 for model development and internal validation. External validation was performed at the University of Southern California (n=59) and Mayo Clinic (n=93). Primary outcomes were acute kidney injury (AKI) and waitlist mortality over 365 days. Three phenotypes emerged: “CKD-Metabolic” (30.4%, lowest eGFR 76.5 mL/min/1.73 m 2 ), “Vasodilatory-Synthetic Dysfunction” (38.9%, highest bilirubin 7.03 mg/dL, lowest blood pressure 117.5 mmHg), and “PVT-Intermediate” (30.7%, severe thrombocytopenia 68.1×10 3 /μL, 24.0% PVT). In validation cohorts (n=305), phenotypes demonstrated robust classification (mean posterior probability 0.823–0.855). Vasodilatory-Synthetic Dysfunction showed increased AKI risk versus CKD-Metabolic in derivation (MELD 3.0-adjusted HR 2.95, 95% CI 2.07–4.22, p <0.001) and validation cohorts (HR 3.39, 95% CI 1.93–5.94, p <0.001). Competing risk analysis revealed no mortality differences, but Vasodilatory-Synthetic Dysfunction was associated with higher transplantation rates (validation: HR 1.63, 95% CI 1.19–2.22, p =0.002). Three reproducible clinical phenotypes of ascites were identified with distinct risk profiles. The Vasodilatory-Synthetic Dysfunction phenotype was associated with a 3-fold increase in the risk of AKI that persisted after adjustment for MELD 3.0. No differences in waitlist mortality were observed, likely reflecting effective MELD-based transplant allocation that preferentially removes the highest-acuity patients from the waitlist.

Cardio-oncology has emerged as a critical discipline in modern medicine due to the growing population of cancer survivors and the increasing recognition of cardiovascular disease as a major cause of morbidity and mortality in this population. While there have been significant advances in chemotherapy such as advances in chemotherapy, targeted therapies, immunotherapies, and radiation therapy, these treatments are linked to a wide range of cardiovascular toxicities such as myocarditis, arrhythmias, and progressive fibrotic remodeling. These toxicities tend to be caused by interrelated and multifactorial cellular processes including endothelial damage, immunological dysregulation and mitochondrial dysfunction. Therefore, early diagnosis of subclinical harm using multimodal surveillance strategies integrating clinical risk assessment, specialized clinical imaging, and circulating biomarkers has replaced reactive care of overt cardiotoxicity in modern cardio-oncology. Echocardiographic techniques such as longitudinal strain, with the help of biomarker-guided surveillance of natriuretic peptides and cardiac troponins, have made the early detection of cardiac dysfunction more effective. However, the current prediction risk models are still constrained and limited by their dependence on static clinical variables and their partial integration of biological mechanisms. This review examines the current methods for risk stratification and surveillance throughout the cancer care continuum, including baseline assessment, monitoring during active therapy, and long-term survivorship surveillance. Future approaches for tailored cardiovascular care are also highlighted, including new advances in precision cardio-oncology such as multi-omics profiling, molecular biomarkers, artificial intelligence, and mechanism-guided preventative strategies. Therefore, advancing biologically informed and risk-adapted monitoring frameworks may enhance early diagnosis, maximize cardioprotective measures, and lower long-term cardiovascular consequences.

Abstract Objective Epilepsy duration is a modifiable risk factor in the outcome of definitive epilepsy surgery; however, an analogous effect in palliative procedures has not been shown. We reviewed the Pediatric Epilepsy Surgery Database data for an association between epilepsy duration and seizure reduction in palliative procedures. Methods Patients enrolled between January 2018 and April 2025 who underwent their first epilepsy surgery with palliative intent with 6 months of follow‐up were included. Procedures included neuromodulation, corpus callosotomy, hemispherotomy, lesionectomy, and lobectomy where surgical intent was not seizure freedom. Outcomes of seizure freedom, 90% seizure reduction, and 50% seizure reduction were considered at 6–12 months and >12 months from surgery. Duration from epilepsy onset to surgery was compared for patients above and below each outcome threshold at each time point. Logistic regression analysis for the association between epilepsy duration and seizure reduction adjusted for potential confounders including procedure type, etiology, and other clinical factors. Logistic regression analysis was performed on the overall cohort and subgroups of patients with each procedure. Results A total of 588 patients were included. Initial univariate analysis suggested that epilepsy duration at time of surgery was significantly associated with seizure freedom and 90% seizure reduction at both 6–12 months and >12 months. After adjusting for confounders, only seizure freedom at >12 months was significantly associated with duration of epilepsy. When individual procedures were considered, only lobectomy was sensitive to duration of epilepsy in multivariate analysis, with significant impacts on >50% and >90% seizure reduction at >12 months. Lesional epilepsy predicted seizure freedom at >12 months. Neuromodulation and corpus callosotomy were less likely to achieve seizure reduction than other procedures. Significance We did not find an association between early epilepsy surgery and seizure reduction. This reflects the heterogeneity of our population, including different types of surgical procedures and lesional and nonlesional epilepsies.

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.