Nephrology

Multi-Omics and Machine Learning-Uncovered FLT1-Mediated Epithelial-Endothelial Crosstalk in Cellular Senescence Driving Clear Cell Renal Cell Carcinoma Malignancy.

Clear cell renal cell carcinoma (ccRCC) is distinguished by the absence of definitive diagnostic markers and efficacious treatment modalities, factors that collectively contribute to its unfavorable clinical prognosis. The targeting of senescent cells has recently emerged as a promising therapeutic strategy. Nevertheless, the precise role of cellular senescence in the pathophysiology of ccRCC has ...

Integrated cross-organ transcriptomic analysis uncovers conserved gene signatures predictive of allograft rejection.

Long-term transplant success is limited by allograft rejection, a complex process traditionally studied on an organ-specific basis. To establish a unified framework beyond organ-specific studies, we performed a network-based systems biology analysis of transcriptomic data from 672 liver, kidney, and heart transplant biopsies to identify a conserved, pan-organ molecular framework of rejection. By c...

In-hospital electronic monitoring system approaches to epidemiologic investigation and predictive modeling of contrast-induced acute kidney injury.

Contrast-induced acute kidney injury (CI-AKI), the third most common cause of hospital-acquired kidney injury, is associated with poor clinical outcom...

Self-supervised Deep Learning for Denoising in Ultrasound Microvascular Imaging.

Ultrasound microvascular imaging (UMI) has emerged as a powerful, noninvasive modality for visualizing the microvasculature, offering valuable insight...

Tracing the evolution of cardiology: Pioneering discoveries and paradigm shifts in cardiovascular care.

Cardiology has undergone an impressive transformation from the initial anatomical observations of William Harvey to the current data-driven precision ...

Retinal imaging and supervised learning predict hospitalizations, kidney, and heart-lung damage in sickle cell disease.

Sickle cell disease (SCD) is a single-gene illness which causes painful vaso-occlusion, debilitating organ damage, and early mortality. Its clinical c...

Development and validation of a machine learning-based early prediction model for fetal acidosis in vaginal deliveries.

Construction and validation of a glycosylation-related diagnostic model and immune characterization in lupus nephritis.

BACKGROUND: As a critical hallmark of systemic lupus erythematosus, lupus nephritis (LN) stands as a major organ-threatening condition driven by sophi...

A pilot study on the impact of large language model assistance on the evaluation of complex medical living kidney donor candidates.

BACKGROUND: Large language models (LLMs) are undergoing exploration as clinical decision support tools. However, their role in complex, high-stakes tr...

AI-driven Predictive Models in Endourological Treatment of Urolithiasis: A Systematic Review of Nomogram Applications from EAU Endourology.

BACKGROUND: Artificial intelligence (AI) is increasingly applied in endourology to enhance surgical planning, risk stratification, and outcome predict...

BA-UNet: A Boundary Augmented Segmentation Network for Cervical Cancer Radiotherapy.

Accurate segmentation of the Clinical Target Volume (CTV) and Organs At Risk (OARs) is a prerequisite for effective cervical cancer radiotherapy. Howe...

Concordance Analysis Between KDIGO Definition of Acute Kidney Injury and Its Coding in Clinical Practice.

RATIONALE & OBJECTIVE: Acute kidney injury (AKI) in research is typically identified using KDIGO criteria based on changes in serum creatinine (SCr) l...

Understanding the precipitation mechanism in pentavalent vanadium electrolytes through deep learning potential molecular dynamics.

Vanadium flow batteries (VFBs) represent one of the promising options for large-scale energy storage, yet the precipitation of pentavalent (V(v)) spec...

An optimized machine learning approach for reliable design of hybrid FRP-steel-concrete tubular columns.

This study develops and evaluates machine-learning models for predicting the confined ultimate strength (fcc, u) and ultimate strain (εcc, u) of a hyb...

nnLoGoNet: a hybrid local-global network for retinal vessel segmentation with Skeleton Recall Loss.

Retinal vessel segmentation is a fundamental task in ophthalmic image analysis, playing a critical role in disease screening and clinical diagnosis. H...

Predicting primary aldosteronism: risk stratification-based and machine learning-based models.

AIMS: Primary aldosteronism (PA) screening is difficult in an unselected population of hypertensive patients, as it can be challenging. We report new ...

Emerging multidimensional biomarker system for cardiovascular-kidney-metabolic syndrome: from multi-omics integration to clinical artificial intelligence.

Cardiovascular-kidney-metabolic (CKM) syndrome is an emerging clinical entity that highlights the complex, bidirectional interplay among cardiovascula...

Deep learning-based Wilms tumor segmentation to create 3D models for surgical planning: Implementation in the clinical workflow.

BACKGROUND AND AIM: Creating 3D models based on pre-operative MRI of patients with a Wilms tumor (WT) can aid surgical planning. However, creating the...

Increasing value in the Veterans Affairs Healthcare System (VA) with precision health: a continuing landmark collaboration with the Department of Energy.

OBJECTIVE: Phase II of MVP-CHAMPION, a federal collaboration between the Veterans Affairs Healthcare System (VA) and the Department of Energy (DoE), l...

An explainable clinical-radiomics machine learning model for preoperative prediction of WHO/ISUP nuclear grade in clear cell renal cell carcinoma.

BACKGROUND: Accurate preoperative assessment of the WHO/ISUP nuclear grade of clear cell renal cell carcinoma (ccRCC) is critical for guiding individu...