Kidney Transplantation

Artificial intelligence in pediatric nephrology: current applications and emerging frameworks for evidence generation.

Artificial intelligence (AI) is rapidly transforming many areas of medicine. Pediatric nephrology may be a field of particular relevance due to its data-rich environments, rarity of diseases, long-term follow-up needs, and persistent evidence gaps. Traditional clinical research methods, including randomized controlled trials, are often difficult to conduct in pediatric nephrology because of small ...

Phosphoenolpyruvate carboxykinase 2 as a prognostic biomarker: expression and clinical significance in Group 3 and Group 4 medulloblastoma.

PURPOSE: Despite Phosphoenolpyruvate carboxykinase 2 (PCK2) has attracted growing attention as a potential biomarker in cancer research, its role in medulloblastoma (MB) remains unclear. This research aims to evaluate PCK2 as a novel biomarker for groups 3 and 4 MB and to investigate its associations with prognosis and the tumor immune microenvironment. METHODS: Five cohorts were extracted to iden...

PAST, PRESENT and FUTURE OF LUPUS NEPHRITIS.

INTRODUCTION: Our objective is to delineate the evolution of lupus nephritis (LN) histological classifications and management, from their origins to t...

Machine learning derived proliferating T cell-related signature: a novel biomarker for prognosis and treatment efficacy in clear cell renal cell carcinoma.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) exhibits profound molecular heterogeneity, and reliable biomarkers for predicting clinical outcome...

CodeSafetyBench evaluating and improving ethical safety in large language model code generation.

As large language models transform software development, they introduce significant ethical and safety risks, with research revealing a 78.67% probabi...

Emerging trends and converging evidence in tumor evolution: A comprehensive review.

BACKGROUND: Tumor evolution is a spatiotemporal dynamic process orchestrated by the interplay of genetic mutations, epigenetic reprogramming, and bidi...

Single-cell transcriptomic analysis and machine learning identify ATAD3A as a key gene that stabilizes mitochondrial-endoplasmic reticulum membranes, promoting bladder cancer progression.

BACKGROUND: Mitochondria-associated endoplasmic reticulum membranes (MAM) play a critical regulatory role in cancer, yet their function in bladder can...

Vulnerability and short clinical outcomes in patients on the deceased-donor kidney transplant waiting list.

BACKGROUND: With prolonged waiting times for deceased-donor kidney transplantation (DDKT) in Japan, objective data on frailty among wait-listed patien...

Identification of clinical phenotypes and disease trajectories in SLE using AI through a natural language processing framework.

OBJECTIVES: Electronic Health Records (EHRs) contain a wealth of unstructured patient data that can be leveraged using Artificial Intelligence (AI). T...

Advancements and challenges in CAR-NK cell therapy for cancer treatment.

Chimeric antigen receptor natural killer (CAR-NK) cell therapy is an emerging cancer treatment offering advantages over CAR-T therapy, including reduc...

Artificial intelligence and machine learning applications in dialysis: Current applications, challenges, and future directions.

Artificial intelligence (AI) and machine learning (ML) applications have emerged as transformative technologies in nephrology, particularly in dialysi...

Interpretable prognostic modeling of glioblastoma using cross-cohort transcriptome integration and machine learning approaches.

Glioblastoma (GBM) is an aggressive brain tumor with highly variable patient outcomes due to pronounced molecular heterogeneity. Prognosis remains dis...

Hydrogel-enabled drug delivery for ulcerative colitis.

Ulcerative colitis (UC) represents a chronic, relapsing inflammatory condition primarily affecting the colonic and rectal mucosa, presenting substanti...

Research on the Application Value of Blood Plasma Autofluorescence Spectroscopy Model Constructed by Machine Learning Algorithms in Identifying the Types of Post-operative Kidney Transplantation Injury.

BACKGROUND: This study aimed to assess the value of blood plasma autofluorescence spectroscopy in classifying renal injury after renal transplantation...

Predicting Persistent Renal Failure Necessitating Dialysis in Patients Undergoing Elective, Open Thoracoabdominal Aortic Aneurysm Repair.

BACKGROUND: Acute renal failure remains a significant complication after open thoracoabdominal aortic aneurysm (TAAA) repair and is associated with hi...

Noninvasive Staging of Hepatic Fibrosis in Patients with Autoimmune Liver Disease Using Deep Learning.

RATIONALE AND OBJECTIVES: Accurate staging of hepatic fibrosis is essential for guiding immunosuppressive and antifibrotic therapies. However, percuta...

Exploring the toxicological mechanisms of Benzo[a]anthracene (BaA) exposure in lung adenocarcinoma (LUAD) via network toxicology, machine learning, and multi-dimensional bioinformatics analysis.

BACKGROUND: Lung adenocarcinoma (LUAD) is a major lung cancer subtype influenced by environmental factors. Benzo[a]anthracene (BaA), a common Group 2B...

Development and validation of a prognosis model for low-grade gliomas based on metabolic gene risk scoring and immune microenvironment interaction.

PURPOSE: Low-grade gliomas(LGGs) show significant clinical and molecular heterogeneity, complicating progression prediction with conventional indicato...

A novel integrative machine learning-based prognostic model reveals lactylation regulation in hepatocellular carcinoma progression.

BACKGROUND: Hepatocellular carcinoma (HCC) is one of the most common malignant liver tumor with poor clinical outcomes. Accumulated evidence has demon...

Updates on Kidney Transplantation From the World Transplant Congress 2025.

The World Transplant Congress 2025 showcased pivotal advances shaping the future of transplantation. Global efforts to expand access to transplantatio...