Urology

GRU-based de novo design and in-silico prioritization of EZH2 inhibitors.

EZH2 (Enhancer-Homozygous Protein 2), as a key epigenetic regulator, is closely associated with multiple cancers. Consequently, the design of EZH2-targeting inhibitors has become a significant focus in drug development. The application of deep learning methods in the chemical field can accelerate the process of discovering new molecules. This study utilized the SMILES sequence information of 1,202...

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 the present histopathological framework and treatment strategies, and to consider prospective future directions.Areas covered. We describe the origins and progressive development of LN, particularly on histological classifications and pharmacological ...

Early detection of chronic kidney disease based on a SURD-enhanced machine learning model.

Chronic kidney disease (CKD) represents a major global health burden, and early, reliable risk prediction remains clinically challenging. This study p...

Retinal BioAge is associated with indicators of cardiovascular-kidney-metabolic syndrome in UK and US populations.

Accelerated biological aging, as well as cardiovascular, kidney, and metabolic (CKM) diseases, contribute to shortened healthspan. We studied a deep-l...

Integrated virtual screening, machine learning and molecular dynamics identify novel phytochemical FabI inhibitors against MRSA.

Methicillin-resistant Staphylococcus aureus (MRSA) infections pose a critical global health threat, necessitating the discovery of novel antibacterial...

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...

Dual Low-b-value-driven U-shaped fusion GAN for synthesizing high-b-value prostate DWI.

High-b-value (b = 2000 s/mm²) diffusion-weighted imaging (DWI) is vital for prostate disease detection and characterization due to superior tumor-to-b...

Machine Learning Phonon Spectra for Fast and Accurate Optical Lineshapes of Defects.

The optical properties of defects in solids produce rich physics, from gemstone coloration to single-photon emission for quantum networks. Essential t...

Toxicogenomic Characterization of Perfluorooctanoic Acid-Associated Bladder Carcinogenesis.

OBJECTIVE: This study aims to bridge toxicological target prediction and bladder cancer transcriptomics by systematically identifying molecular signat...

Enhancing prostate cancer diagnosis: a machine learning-based biomarker approach.

Dual selective gleason pattern-aware multiple instance learning with uncertainty regularization for grade group prediction in histopathology images.

Accurate prediction of Gleason Grade Group (GG) is of great importance for prostate cancer risk stratification and treatment planning. Although multip...

Correlation between the high-density lipoprotein-to-low-density lipoprotein ratio and contrast-induced acute kidney injury: an analysis based on the in-hospital AKI electronic monitoring system.

BACKGROUND: Contrast-induced acute kidney injury (CI-AKI) is a common and serious complication that can occur following angiography procedures. Consid...

Comparative Evaluation of Transfer Learning Models for Detecting Malignant Cells in Urinary Cytology.

AIMS AND OBJECTIVES: In the present paper, we compared the efficiency of six transfer learning models to detect malignant cells in urine cytology. We ...

End-to-end integrative segmentation and radiomics prognostic models for risk stratification of high-grade serous ovarian cancer: a retrospective multicohort study.

BACKGROUND: Valid stratification factors for patients with epithelial ovarian cancer are still lacking and individualisation of care remains an unmet ...

Bibliometric analysis of bone metastasis from prostate cancer research from 2007 to 2024.

BACKGROUND: Prostate cancer (PCa) is one of the most common cancer in men worldwide, while numerous scientific achievements have been made in research...

Evaluation of GPT-5 for Esophageal Cancer Staging Using Fluorodeoxyglucose Positron Emission Tomography Maximum-Intensity Projection Images: Comparative Pilot Study.

BACKGROUND: Accurate esophageal cancer staging relies on 18F fluorodeoxyglucose positron emission tomography (18F FDG-PET), but its interpretation is ...

Biomechanics-informed Non-rigid Medical Image Registration with Elasticity Theories.

Biomechanical modelling of soft tissue provides a method for constraining medical image registration, such that the estimated spatial transformation i...

The influence of age and the presence of prostate cancer on prostate volume, PSA and PSA density.

OBJECTIVE: To assess prostate volume (PV) changes with age in symptomatic and asymptomatic men with and without clinically significant prostate cancer...

Accelerating Screening of Phase Separation Agents for Carbon Dioxide Capture: A Machine-Learning Framework with Interpretable Quantum Chemical Insights.

Against the backdrop of addressing climate change and reducing carbon emissions, carbon dioxide capture technology has gained increasing significance ...

Artificial intelligence for the prediction of synchronous and metachronous liver metastasis in colorectal cancer patients: a systematic review and meta-analysis.

BACKGROUND: Colorectal cancer (CRC) is the third most common cancer and the second leading cause of cancer mortality in the world. Liver is the most c...