Nephrology

A four-gene signature for diagnosis of acute kidney injury following kidney transplantation.

Acute kidney injury (AKI) is a common and severe complication following renal transplantation, large...

Polycystin-1 and Cardiac Remodeling: From Mechanotransduction to Clinical Consequences.

PC1 (polycystin-1), traditionally viewed through the lens of renal pathophysiology in autosomal domi...

Sweat-based electrochemical wearable biosensors for sports performance and fatigue monitoring: from laboratory prototypes to field deployment.

Wearable biosensing technologies are advancing sports performance monitoring by enabling the continu...

A validated custom pipeline for three-dimensional kidney stone renderings tocreate an open access repository.

Three-dimensional (3D) rendering of urologic pathology plays an important role in simulation-based e...

Continuous predictive mortality risk monitoring after allogeneic hematopoietic stem cell transplantation.

Allogeneic hematopoietic stem cell transplantation remains critical for treating high-risk hematolog...

Multifaceted role of histopathology in liver transplantation for hepatocellular carcinoma: A narrative review towards precision prognosis.

Hepatocellular carcinoma is a leading cause of cancer mortality globally. Liver transplantation is c...

Immunologic clustering of donor-specific antibodies and clinical outcomes in kidney transplant recipients.

BACKGROUND: Donor-specific antibodies (DSA) against human leukocyte antigens (HLA) are associated wi...

Risk stratification for in-hospital mortality in sepsis-associated acute kidney injury patients receiving continuous renal replacement therapy: an interpretable, externally validated machine learning study.

Patients with sepsis-associated acute kidney injury (SA-AKI) requiring continuous renal replacement ...

Mechanism-Based Multitarget Modeling for Pathway-Level Prediction of PI3K/Akt Signaling Perturbation Induced by Liquid Crystal Monomers.

Liquid crystal monomers (LCMs) are emerging contaminants whose system-level toxicity mechanisms rema...

From donor to recipient: Interpretable machine learning refocuses the prediction of post-transplant MASLD.

Rational design of high-loading electrocatalytic electrodes: from static multiscale integration to dynamic intelligent systems.

In the field of electrocatalysis, the industrial application of high-loading electrodes faces a fund...

Exploration of the mechanism of Xinjiang Rosa laxa Retz.Fruit extract on IgA nephropathy by bioinformatics and machine learning methods.

This study aimed to elucidate the core therapeutic targets and mechanisms of action of rosehip extra...

Single-cell transcriptomic analysis reveals the T lymphocyte microenvironment and identifies HOPX as a hub gene in membranous nephropathy.

BACKGROUND: Membranous nephropathy (MN) is an autoimmune disease characterized by immune complex dep...

Radiomics using contrast-enhanced T1-weighted imaging and clinical features for predicting response to EGFR-TKIs in EGFR-mutated non-small cell lung cancer patients with brain metastases.

OBJECTIVES: To construct and validate a model based on clinical characteristics and magnetic resonan...

Validation of latent health behaviour subtypes in young and middle-aged adults with hypertension: a machine learning-augmented LCA approach with external cohort replication.

AIMS: To validate behavioural subtypes among young and middle-aged hypertensive patients using laten...

[Construction and validation of a prognostic prediction model for children-onset initial steroid-resistant nephrotic syndrome].

Objective: To analyze the risk factors for poor prognosis in children with steroid-resistant nephrot...

Systematic Multi-Target QSAR Benchmarking: Machine Learning Algorithms, Molecular Descriptors, and Validation.

Quantitative structure-activity relationship (QSAR) modeling underpins computational drug discovery,...

Compositionally-informed machine learning for solid-state electrolyte design: a structure-free approach.

Next-generation energy storage demands high-performance solid-state electrolytes (SSEs), where machi...

nnU-Net-based CT segmentation of perigastric varices in sinistral portal hypertension: a multicenter study.

PURPOSE: To develop a deep learning model based on nnU-Net for automated segmentation of all perigas...

Machine learning to identify novel bleeding and residual thromboembolic risks in patients on anticoagulation.

Balancing thromboembolic prevention against bleeding risk remains a key challenge during oral antico...

The potential utility of in-silico approach in identifying phytochemicals against various targets for the management of lung cancer.

Research on novel treatment approaches is crucial for lung cancer, because it is one of the most com...