Nephrology

Assessment and management of portal hypertension in patients with MASLD: advances and caveats.

INTRODUCTION: Metabolic dysfunction-associated steatotic liver disease (MASLD) is increasingly gaining relevance both as a public health issue and a clinical challenge. The development of portal hypertension in MASLD challenges traditional paradigm that it arises only in the context of cirrhosis.

Identification and validation of epithelial‑mesenchymal transition‑related genes for diabetic nephropathy by WGCNA and machine learning.

Diabetic nephropathy (DN) is the main cause of end‑stage renal disease, with epithelial‑mesenchymal transition (EMT) serving a key role in its initiation and progression. Nevertheless, the precise mechanisms involved remain unidentified. The present study aimed to identify the involvement of EMT‑related genes in the advancement of DN. Using the Gene Expression Omnibus database and the dbEMT 2.0 da...

Current state of AI for shockwave lithotripsy: a systematic review from YAU and EAU endourology.

PURPOSE: To consolidate the current evidence of artificial intelligence (AI) for management of nephrolithiasis using extracorporeal shock-wave lithotr...

Advancing fungal phylogenetics: integrating modern sequencing, dark taxa discovery, and machine learning.

The study of fungal genetics has undergone transformative advancements in recent decades, profoundly reshaping our understanding of fungal diversity, ...

Development and validation of personalized risk prediction models for patients with IgA nephropathy: a nationwide multicenter cohort study.

BACKGROUND: Effective prediction of immunoglobulin A nephropathy (IgAN) progression is crucial for early intervention and management. We aimed to deve...

Picoeukaryote-based biohybrid microrobots for active delivery in the kidney.

Confined spaces in the human body pose substantial challenges for biomedical procedures. Navigating these ultrasmall environments is essential for pre...

Machine learning-assisted assessment of extracellular vesicles can monitor cellular rejection after heart transplant.

BACKGROUND: Heart transplant rejection, particularly acute cellular rejection (ACR), remains a critical post-operative concern, despite declining inci...

Diagnostic immune-related markers for diabetic kidney disease: a bioinformatics and machine learning approach.

OBJECTIVE: Diabetic kidney disease (DKD) is a leading cause of chronic kidney disease, with chronic inflammation driving its progression. This study a...

Non-invasive identification of TKI-resistant NSCLC: a multi-model AI approach for predicting EGFR/TP53 co-mutations.

OBJECTIVES: To investigate the value of multi-model based on preoperative CT scans in predicting EGFR/TP53 co-mutation status.

A holistic framework for intradialytic hypotension prediction using generative adversarial networks-based data balancing.

BACKGROUND: Intradialytic Hypotension (IDH) is a frequent complication in hemodialysis, yet predictive modeling is challenged by class imbalance. Trad...

Atomistic Simulations of Thermal and Chemical Expansions of PrNiCoO Accelerated by Machine Learning Potentials.

The electrodes and solid-state electrolytes in protonic ceramic electrochemical cells (PCECs) experience significant lattice expansions when exposed t...

Real-world deployment of a fine-tuned pathology foundation model for lung cancer biomarker detection.

Artificial intelligence models using digital histopathology slides stained with hematoxylin and eosin offer promising, tissue-preserving diagnostic to...

Validation of the Toronto recurrence inference using machine-learning for post-transplant hepatocellular carcinoma model.

BACKGROUND: Organ shortages require prioritizing hepatocellular carcinoma (HCC) patients with the highest survival benefit for allografts. While tradi...

A clinicians' guide to non-invasive ventilation for exacerbated chronic obstructive pulmonary disease.

INTRODUCTION: Chronic Obstructive Pulmonary Disease (COPD) is a debilitating condition marked by persistent airflow limitation, leading to increased m...

Unsupervised learning using EHR and census data to identify distinct subphenotypes of newly diagnosed hypertension patients.

BACKGROUND: Hypertension (HTN) is a complex condition with significant heterogeneity in presentation and treatment response. Identifying distinct subp...

Drp1 Proteins Released from Hydrolysis-Driven Scaffold Disassembly Trigger Nucleotide-Dependent Membrane Remodeling to Promote Scission.

Dynamin-related protein (Drp1) drives mitochondrial fission, dysregulation of which leads to neurodegenerative, metabolic, and apoptotic disorders. Th...

Machine learning models using non-invasive tests & B-mode ultrasound to predict liver-related outcomes in metabolic dysfunction-associated steatotic liver disease.

Advanced metabolic-dysfunction-associated steatotic liver disease (MASLD) fibrosis (F3-4) predicts liver-related outcomes. Serum and elastography-base...

A novel method to predict the haemoglobin concentration after kidney transplantation based on machine learning: prediction model establishment and method optimization.

BACKGROUND: Anaemia is a common complication after kidney transplantation, and the haemoglobin concentration is one of the main criteria for identifyi...

A practical guide for nephrologist peer reviewers: evaluating artificial intelligence and machine learning research in nephrology.

Artificial intelligence (AI) and machine learning (ML) are transforming nephrology by enhancing diagnosis, risk prediction, and treatment optimization...

Cellular senescence in renal ischemia-reperfusion injury.

Acute kidney injury (AKI) affects more than 20% of hospitalized patients and is a significant contributor to morbidity and mortality, primarily due to...