Subjective cognitive decline (SCD) is a well-recognized risk state for developing mild cognitive impairment (MCI) and dementia. Optimal risk stratification for early interventions and clinical trial selection remains challenging. This study evaluates progression risk across multimodal biomarker profiles in SCD. We conducted a longitudinal observational study including participants from the BioFINDER-1 and BioFINDER-2 cohorts with a baseline diagnosis of SCD, at least 1 follow-up visit, and available information on dementia progression. Baseline predictors included cognitive performance, APOE4 status, plasma phosphorylated tau (p-tau) 217, "AD-signature" cortical thickness, hippocampal volume, and white matter hyperintensities (WMHs) measured by the Fazekas scale. Missing data were handled using multiple imputation. Predictors were evaluated individually and then combined in progressively complex Cox regression models to predict progression to all-cause dementia, Alzheimer disease (AD) dementia, and MCI (BioFINDER-2 only). Model performance was assessed using the Harrell C-index, and Akaike information criterion was used for comparing model fit. A total of 469 participants with SCD (mean age 69.1 ± 7.1 years, 51.4% female) were included in the main sample. Eighty-four individuals progressed to dementia over 4.0 ± 2.1 years (66.7% AD dementia). Progressors were older and more frequently APOE4 carriers and showed worse baseline cognition, higher plasma p-tau217, and greater atrophy and WMH burden. Plasma p-tau217 was the strongest individual predictor for AD dementia (C-index = 0.86 ± 0.012), but multivariable models outperformed single-biomarker models. The best model for all-cause dementia included all variables and achieved a C-index of 0.89 ± 0.003. For AD dementia, a more parsimonious model combining plasma p-tau217, cognitive scores, and APOE4 status showed excellent predictive ability (C-index = 0.91 ± 0.009), with only marginal improvement when MRI markers were added. Among 249 individuals from BioFINDER-2, 84 progressed to MCI within 2.3 ± 1.2 years. For MCI prediction, model performance was generally lower and similar between the plasma model and the model including all variables (C-index = 0.83 ± 0.009). A clinically feasible multimodal approach combining cognitive assessment, plasma p-tau217, and APOE4 status accurately predicts AD dementia risk in individuals with SCD. Adding MRI measures of brain atrophy and WMHs further improves prediction for all-cause dementia. These findings underscore the clinical value of plasma p-tau217 in refining risk assessment in SCD and support its potential implementation in memory clinic settings alongside other widely available biomarkers.

BACKGROUND Insulin resistance (IR) plays a pivotal role in the pathogenesis of metabolic dysfunction-associated steatotic liver disease. While non-invasive imaging methods are increasingly used in pediatrics, the extent to which hepatic elastography reflects IR in children remains unclear. AIM To evaluate the association between ultrasound-based hepatic elastography parameters and clinical indices of IR in the pediatric population. METHODS A systematic search of PubMed, Scopus, and Web of Science databases was conducted through October 2025. Studies assessing correlations between elastography parameters - controlled attenuation parameter (CAP) and liver stiffness measurement (LSM) - and IR indices were included. Data were pooled using random-effects meta-analysis with correlation coefficients (r ) as the primary effect size. Subgroup and sensitivity analyses examined differences by IR index, cohort characteristics, and elastography modality. RESULTS Sixteen studies, encompassing 2,032 children and adolescents, were included. The pooled correlation between hepatic elastography (CAP/LSM) and IR indices was r = 0.44 (95% confidence interval: 0.38-0.50; I 2 = 72%), indicating a moderate positive association. The strongest correlations were observed for adipose tissue IR (r = 0.65) and the metabolic score for IR (r = 0.49), surpassing simpler indices such as homeostatic model assessment of IR. CAP correlated moderately with early steatosis (r = 0.30-0.40), whereas LSM showed stronger associations with advanced fibrosis and systemic IR (r = 0.50-0.65). Heterogeneity was mainly attributed to differences in disease severity and measurement methods. CONCLUSION Ultrasound-based hepatic elastography provides a reliable, non-invasive surrogate for systemic metabolic dysfunction in pediatric metabolic dysfunction-associated steatotic liver disease. CAP reflects early, reversible hepatic fat accumulation, while LSM reflects more advanced fibrosis and systemic IR, and identifies fibrotic progression driven by chronic IR. The strongest associations with adipose tissue-IR and metabolic score-IR highlight the systemic, multisite nature of pediatric IR. Elastography thus holds promise as an integrated biomarker for IR severity, early risk stratification, and therapeutic monitoring in children and adolescents with metabolic risk factors.

Adults older than age 55 years have the highest incidence rate and are the fastest-growing population among people with epilepsy. The aim of this study was to characterize the etiologies of new-onset seizures in older adults and to examine how seizure etiology varies across demographic groups. We used data from 7 US epilepsy centers from 2021 to 2025 and compared findings with those of previous population-based studies, providing an updated view and highlighting opportunities for prevention and improved risk stratification. We retrospectively reviewed medical charts of 2,052 patients aged ≥55 years at the time of a first seizure, who were evaluated at 7 epilepsy centers between 2021 and 2025. We categorized seizures by etiology as follows: ischemic stroke, hemorrhagic stroke, tumor, neurodegeneration, provoked seizures, traumatic brain injury, and unknown. We examined differences in etiology by demographic strata (age, sex, race, and primary language) using chi-square tests, Kruskal-Wallis tests, analysis of variance, and Cuzick tests. The most frequent seizure etiologies among older adults were unknown (29.9%), ischemic stroke (15.4%), and provoked seizures (14.9%). Neurodegenerative disease was the etiology for 5.3% of cases overall but increased in prevalence with age, accounting for 18.5% among patients aged 85-89 years. Seizure etiologies also differed by sex and race. Men more commonly had seizures caused by cerebrovascular disease and traumatic brain injury, while women more commonly had seizures due to neurodegenerative disease. Black patients had higher proportions of ischemic stroke and neurodegenerative disease, while unexplained epilepsy was more common among White patients. The causes of late-onset seizures vary based on age, sex, and race. Nearly one-third of cases of epilepsy in older adults remain unexplained despite advances in imaging techniques, underscoring the need for further research on the mechanisms and health implications of late-onset unexplained epilepsy. Improved prevention of cerebrovascular disease and optimized management of provoked seizures may reduce the growing burden of epilepsy in older adults.

Risk stratification of Ta high-grade non-muscle-invasive bladder cancer: Insights from a multicenter cohort study.

Admission clinical features associated with disease severity in psittacosis pneumonia: A retrospective study.

Integrative prognostic modeling and mediation analysis of recurrence risk in extremely early-stage oral squamous cell carcinoma.

Risk stratification across the three main clinical subsets of malignant peripheral nerve sheath tumor (MPNST), neurofibromatosis type I (NF1-related), sporadic, and prior radiation therapy (RT), is based mainly on clinicopathologic parameters, such as size, grade, stage, and NF1 status. Moreover, no prior study investigated the additional impact of genomic alterations in the prognosis of high-grade MPNST using clinically validated DNA targeted next-generation sequencing (NGS) panels. Our goal was to integrate clinicopathologic and genomic parameters using an elastic-net penalized Cox proportional hazards machine learning model using OncoCast for risk prediction. Herein we perform comprehensive mutational and copy number profiling using Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets (MSK-IMPACT) on 81 primary localized high-grade MPNSTs (51% NF1-related, 38% sporadic, 11% RT-associated). The most common genomic alterations included NF1 (51% germline, 59% somatic), CDKN2A/B (62%), PRC2 components (SUZ12, EED) (53%), and TP53 (25%). Variables selected by OncoCast as significantly associated with survival were used to construct a three-tier risk stratification model for progression-free survival (PFS) and disease-specific survival (DSS). For PFS, patients with chr16 deletion were classified as high-risk, those with concurrent germline and somatic NF1 alterations as low-risk, and the remainder was assigned to the intermediate-risk group. For DSS, cases with fraction genome altered (FGA) > 50% were defined as high-risk, those with PRC2 abnormalities, CDKN2A deletion, TERT promoter mutation, or chr16 deletion as intermediate-risk, and cases lacking all the aforementioned alterations as low-risk. The high-risk group showed significantly inferior survival compared to the low-risk group (both PFS and DSS p < 0.001). Subgroup analysis showed that among NF1-related MPNST, co-occurring somatic NF1 mutation or WT TP53 was associated with superior PFS. Collectively, genomic alterations detected by clinical NGS panels provide potential new biomarkers for risk stratification that can be integrated with conventional parameters to provide improved prognostication and guide therapeutic strategies. © 2026 The Pathological Society of Great Britain and Ireland.

Urine albumin-to-creatinine ratio for early diagnosis and risk stratification of acute kidney injury in high-risk critically ill ICU patients: A prospective cohort study.

Development and validation of a clinical risk stratification model for lumbar vertebral compression fractures in patients with lumbar disc herniation.

The study aimed to identify independent predictors associated with paravalvular regurgitation (PVR) after self-expanding transcatheter aortic valve replacement (SE-TAVR) and to develop a dual-parameter risk stratification model. This retrospective study enrolled 292 severe aortic stenosis patients underwent SE-TAVR. PVR severity was assessed pre-discharge. Multivariate logistic regression identified independent predictors of mild/moderate PVR, optimal cutoff values for significant anatomical parameters were determined using receiver operating characteristic (ROC) curve analysis. Patients were subsequently stratified into three risk groups based on these thresholds. Mild/moderate PVR occurred in 24.0 % of patients. Independent predictors included aortic annular perimeter (OR:1.067, P = 0.015), device landing zone calcific volume (OR:1.006 per 10 mm³, P = 0.025), and presence of sealing skirt (OR:0.412, P = 0.010). The combination of these predictors had a higher discriminative performance (AUC=0.779) than single predictors (P = 0.036, 0.007, and <0.001, respectively), with significant integrated discrimination improvement (integrated discrimination improvement=5.4-6.7 %, P < 0.001). ROC-derived thresholds (device landing zone calcific volume≥1240 mm³ and aortic annular perimeter≥77 mm) stratified patients into three risk groups with progressively increasing PVR incidence: Group A (neither elevate):8.4 %; Group B (either elevated):23.7 %; and Group C (both elevated):48.7 %. Pairwise comparisons confirming differences between Group A vs. B (P = 0.003) and Group B vs. C (P < 0.001). Sealing skirts significantly reduced PVR in Groups A (P = 0.042) but not in Group B and C (P = 0.082 and 0.342). The dual-parameter model based on device landing zone calcification and aortic annular perimeter significantly enhances PVR risk stratification after SE-TAVR. The dual-threshold model provides a clinically actionable tool for pre-procedural risk stratification and personalized valve selection.

Electrochemical biosensing of circulating MicroRNAs in endometrial Cancer.

Bilateral asymmetry of multifidus fat infiltration in cervical ossification of the posterior longitudinal ligament: A cross-sectional MRI analysis for risk stratification and clinical decision support.

Evaluating BCG response in primary and metachronous non-muscle invasive bladder cancer following prior upper tract urothelial cancer: A systematic review and meta-analysis.

Alcohol consumption is a modifiable, dose‑dependent risk factor that accelerates cancer initiation, progression, and therapy resistance across breast, liver, colorectal, esophageal, and melanoma cancers. Alcohol metabolism generates acetaldehyde, a genotoxic metabolite that induce DNA damage and impairs repair; drives oxidative stress, hormonal imbalance and promoting a tumor‑supportive microenvironment. These effects are amplified by obesity and insulin resistance, which heighten aggressiveness and blunt treatment response. Alcohol reshapes the tumor immune microenvironment (TIME) and undermines therapies, including immunotherapy. It impairs dendritic cell antigen presentation and co‑stimulation, limits CD4⁺/CD8⁺ priming, and expands immunosuppressive MDSCs and M2‑like TAMs that inhibit cytotoxic T cells and express checkpoint ligands. Concurrent cytokine shifts (TNFα, IL‑6), persistent ROS-NF‑κB signaling, and stromal/vascular remodeling promote immune exclusion and weaken responses to checkpoint blockade, targeted agents, and chemotherapy. Alcohol‑related gut dysbiosis is linked to ICB responsiveness-dampens antitumor immunity. Alcohol increases exosome biogenesis; circulating vesicles enriched in hepatocyte and inflammatory miRNAs (e.g., miR‑122, miR‑192) reprogram immune signaling and metastasis, forming a vesicular axis linking exposure to TIME dysfunction and resistance. Risk is synergistic with tobacco and worsens with aging as detoxification and DNA repair decline. Sex‑specific pharmacokinetics and composition confer vulnerability in women, while socioeconomic barriers delay diagnosis and care. Personalized prevention strategies that incorporate alcohol reduction, smoking cessation, and nutritional support, with emerging biomarkers such as exosomal miRNAs and alcohol‑related metabolites for early detection and risk stratification, are needed to mitigate alcohol‑related carcinogenesis, given the lack of definitive human evidence on alcohol's independent effects on immunotherapy and chemotherapy efficacy.

This article reviews the perioperative management of adults with heart valve disease undergoing noncardiac surgery. It focuses on aortic and mitral valve disease, as well as prosthetic heart valves, in the context of the substantial hemodynamic challenges imposed by anesthesia during major surgery. We aim to integrate guideline-based recommendations for preoperative evaluation and risk stratification with pathophysiological principles to support individualized intraoperative hemodynamic and anesthetic management. Current literature and guidelines converge on symptom status and echocardiographic severity as key determinants of perioperative risk. For stenotic lesions, maintaining sinus rhythm, avoiding tachycardia, preserving preload, and preventing abrupt afterload reduction are central intraoperative goals. For regurgitant lesions, strategies that support forward flow by avoiding bradycardia and excessive afterload are emphasized. In prosthetic valves, perioperative management is driven by valve type/position and thromboembolic risk, guiding anticoagulation interruption and bridging, while endocarditis prophylaxis is reserved for selected high-risk dental procedures. A practical approach integrates surgical urgency, valve severity, symptoms, ventricular function, and pulmonary pressures to determine whether to proceed with surgery, optimize medically, or to perform valve intervention first, and to tailor intraoperative monitoring and anticoagulation plans.

Iron deficiency anemia unmasking an endoscopically resectable GIST

Clinical assessment of abdominal aortic aneurysm (AAA) rupture risk relies on diameter criteria, which are often insufficient. Validating non-invasive biomarkers against experimental ground truth is a crucial prerequisite before conducting large-scale clinical trials. We hypothesize that Wall Motion Indices (WMI), derived from 4D ultrasound (4D-US) strain imaging, capture the functionally compromised mechanical state of the aneurysm wall. This study introduces a validation framework using patient-specific, experimental ground truth metrics. For nine AAA patients, the Normalized Experimental Rupture Potential (NERP) was established. The NERP, a normalized ratio of physiological loading to failure capacity, combined finite element analysis (FEA)-estimated wall tension with ex vivo rupture strength from harvested tissue. To ensure strict data separation, patient-specific ground truths (NERP and rupture strength) were correlated with pre-operative WMI exclusively at the documented harvest location. While maximum diameter showed no significant association with NERP or rupture strength, specific WMI quantifying kinematic anisotropy and local strain concentrations demonstrated notable correlations. Strain ratios, identifying local hotspots relative to background deformation, correlated with different structural integrity metrics. Principal strain ratio correlated significantly with intrinsic ex vivo rupture strength (r=-0.711,p=0.032), whereas the macroscopic anatomical strain ratio correlated with the computationally derived NERP (r=0.833,p=0.005). This study demonstrates an efficient validation framework for biomechanical biomarkers in small cohorts. The findings suggest that disparity-based WMI are promising, non-invasive indicators of AAA wall integrity that warrant further investigation. Statement of Significance This study addresses the critical need for reliable rupture risk assessment in abdominal aortic aneurysms (AAA), moving beyond simple diameter measurements. We introduce a multi-modal validation framework that serves as a crucial, mechanistically-informed precursor to large-scale clinical trials. By correlating non-invasive, 4D ultrasound-based wall motion biomarkers with patient-specific, experimental "ground truth" data (tissue strength and stress) from the exact same anatomical location, this approach establishes the necessary biomechanical plausibility of predictive metrics before clinical scaling. Our findings reveal that while traditional clinical parameters fail to predict wall integrity, disparity indices quantifying the mechanical disorganization (anisotropy of heterogeneity) of the aneurysm wall correlate strongly with structural vulnerability. This work establishes an efficient tool for evaluating biomechanical markers in small cohorts and highlights strain disparity-based Wall Motion Indices as promising candidates for a more refined, patient-specific risk stratification.

Urinary bladder cancer (UBC) is a leading cause of cancer-related morbidity and mortality worldwide, but current diagnostic methods are invasive and prone to false-negatives. This study aimed to evaluate the diagnostic and prognostic value of HMGB1 protein expression in urothelial carcinoma of the bladder using three distinct methods (serum ELISA, tissue IHC, and mRNA expression) via reverse transcription polymerase chain reaction (RT-PCR) and establishing their correlation. This single-center prospective observational study enrolled adults planned for transurethral resection of bladder tumor (TURBT) from March 2023 to April 2025 at Banaras Hindu University, India. The study enrolled 64 UBC patients and 21 control subject. For analysis, 5 ml of blood and cystoscopic guided tumor tissue were retrieved from UBC patients undergoing TURBT and normal bladder urothelium, and 5mL blood was retrieved from noncancerous subjects (controls) undergoing cystoscopy for various reasons. Clinicopathologic features including tumor stage (T), grade, risk group, and imaging data also were analyzed with respect to their correlation with HMGB1 expression. Levels of HMGB1 were significantly elevated in the UBC patients compared with the control patients (serum ELISA [p < 0.001], mRNA [p = 0.002], IHC [p = 0.013]). Expression of HMGB1 correlated significantly with tumor stage (T) and grade, with higher levels observed in muscle-invasive bladder cancer (MIBC) than in non-muscle-invasive bladder cancer (NMIBC). Notably, HMGB1 expression was highest in very-high-risk NMIBC patients. However, correlations with age, sex, MRI-VIRADS score, tumor size, and number of growths were statistically insignificant. Elevated levels of HMGB1 correlated with advanced tumor stage, high grade, and MIBC, suggesting its utility in early detection and risk stratification, making it a non-invasive diagnostic and prognostic biomarker for UBC.

CT Radiogenomics Provides a Novel Factor for cM0(i+) Risk Stratification in Localized Renal Cell Carcinoma: A Model Linked to a Circulating Tumor Cell-Related Gene Signature.

Non-coding RNAs as biomarkers and therapeutic targets in pancreatic cancer: Clinical implications and translational perspectives.