Nephrology

Transcriptomic analysis identifies novel ferroptosis-related biomarkers and therapeutic targets in pulmonary arterial hypertension.

BACKGROUND: Ferroptosis plays a significant role in pulmonary arterial hypertension (PAH), although its underlying mechanisms and key pathogenic genes remain unclear. METHODS: Transcriptomic data from human PAH and control lung tissue were obtained from the Gene Expression Omnibus (GEO) database, whereas ferroptosis-related genes (FRGs) were sourced from the MsigDb and FerrDb databases. Differenti...

Integrative single-cell and spatial transcriptomics with machine learning identify a Luminal-inflam malignant program and reveal an RPN1-PERK UPR vulnerability in triple-negative breast cancer.

Triple-negative breast cancer is marked by extensive cellular heterogeneity and limited availability of actionable targeted treatments, which contributes to an unfavorable prognosis. In this work, single-cell and spatial transcriptomic profiling was integrated with network-based analyses and machine-learning approaches to characterize malignant epithelial programs in TNBC and to pinpoint prognosti...

Transforming hemodialysis care: a tripartite collaboration model among medical staff, AI agents, and robots.

Hemodialysis demand is rising as populations age and the chronic kidney disease burden increases, yet dialysis units face persistent workforce constra...

Predicting long-term allograft outcomes in kidney transplant recipients using a machine learning approach: a 5-year retrospective cohort study.

Long-term outcomes of kidney allografts vary significantly among deceased donor kidney transplant recipients, and current prediction tools struggle to...

Shaping the future of endourology: role of education, simulation and uro-technology: a scoping review by the EAU Section of Endourology.

PURPOSE OF REVIEW: This scoping review synthesizes contemporary evidence on the role of simulation, uro-technology and structured training curricula i...

Machine learning-based prediction of mortality and hospitalization in diabetic patients with heart failure with preserved ejection fraction: the GUARDIAN-P risk score.

AIMS: Diabetes mellitus (DM) is a major contributor to adverse outcomes in patients with heart failure with preserved ejection fraction (HFpEF). We ai...

High-energy-density aqueous magnesium metal battery textiles enable ultrasensitive pressure sensing across -40° to 100°C.

Smart wearable sensing systems necessitate self-powered, high-sensitivity pressure sensors that can operate efficiently across a wide temperature rang...

Multi-Omics Integration Reveals the Genetic Mechanisms of Periodontitis and Predicts Therapeutic Drugs.

BACKGROUND: Periodontitis is a chronic inflammatory disease driven by host immune dysregulation. However, the specific genetic regulatory mechanisms u...

Integrating network toxicology, molecular docking and experimental validation reveals potential mechanisms of DEHP in osteoarthritis.

Di(2-ethylhexyl) phthalate (DEHP), a ubiquitous environmental endocrine disruptor, has been implicated in osteoarthritis (OA) pathogenesis, although t...

Preoperative Predictive Modeling of Recurrent Graft Failure: Development and Validation of a 12-Month Prognostic Tool in Kidney Transplant Recipients.

BACKGROUND: Kidney transplantation is among the most effective treatments for end-stage renal disease. However, kidney transplant (KT) recipients rema...

Computer-Interpretable Domain Knowledge for Drug-Induced Acute Kidney Injury: a Knowledge Graph Approach.

In this study, a Knowledge Graph (KG) for Drug-Induced Acute Kidney Injury (DAKI) was developed to provide structured and standardized knowledge about...

Deep-learning-based artificial intelligence approaches for grading and progression prediction of clear cell renal cell carcinoma.

The grading classification of clear cell renal cell carcinoma (CCRCC) is a crucial prognostic factor. However, manual observation can lead to subjecti...

Multiscale Prediction of Tumor Micronecrosis and Progression in Clear Cell Renal Cell Carcinoma Based on Artificial Intelligence: A Multicenter Cohort Study.

RATIONALE AND OBJECTIVES: Tumor micronecrosis (TM) represents a critical pathological feature influencing the prognosis and surgical management of cle...

Development and external validation of a machine learning model for predicting post-CABG acute kidney injury: insights from MIMIC database and real-world cardiac surgery cohort.

OBJECTIVE: Acute kidney injury (AKI) is a severe complication following coronary artery bypass grafting(CABG) While machine learning models trained on...

Ketone Body Metabolism and Sodium Glucose Cotransporter 2 Inhibitor Response in Heart Failure With Ischemic Cause: A Precision Medicine Approach Using Metabolomics Integration With Global Burden of Disease Population Data Across Diverse Genetic Backgrounds.

BACKGROUND: Heart failure with ischemic cause is associated with substantial cardiovascular mortality. SGLT2 (sodium glucose cotransporter 2) inhibito...

Age-stratified risk profiles for emergency colorectal cancer resection: A machine-learning analysis.

BACKGROUND: Emergency colorectal cancer resection (ECCR) is associated with worse perioperative and oncologic outcomes than elective surgery. As the i...

Decision tree with randomized grid search-based hyperparameter tuning and optimal feature scaling for diabetes diagnosis.

BACKGROUND: Diabetes is a chronic condition that arises when the body cannot effectively regulate blood glucose levels, either due to insufficient ins...

Progress of Non-Aqueous Liquid Electrolytes for High-Voltage Sodium-Ion Batteries.

Due to their significant resource-economic advantages, sodium-ion batteries are gradually becoming an important alternative to lithium-ion batteries i...

Updating CMV protocols in lung transplant patients: a single-center case study modeling use of generative AI for antimicrobial stewardship protocol development and economic impact analysis.

OBJECTIVE: Antimicrobial Stewardship Programs (ASPs) need healthcare economic analyses to support and inform ASP strategies. This work aimed to determ...

Machine learning-guided drug repurposing for EGFR inhibition using scaffold-split validation, docking, and molecular dynamics.

Aberrant epidermal growth factor receptor (EGFR) signaling drives multiple cancers, but the clinical effectiveness of EGFR inhibitors is limited by re...