Nephrology

Advanced immunotherapy across diseases and the role of artificial intelligence: A review.

Immunotherapy, a therapeutic strategy aimed at modulating the host immune system, has undergone rapid evolution over recent decades, particularly in oncology. Advanced methodologies, including immune checkpoint inhibition, cytokine therapy, chimeric antigen receptor T-cell therapy (CAR-T), and tumor-infiltrating lymphocyte therapies, have significantly transformed cancer treatment. This review sum...

An Efficient 3D Latent Diffusion Model for T1-contrast Enhanced MRI Generation.

Gadolinium-based contrast agents (GBCAs) are commonly employed with T1-weighted (T1w) MRI to enhance lesion visualization but are restricted in patients at risk of nephrogenic systemic fibrosis and variations in GBCA administration can introduce imaging inconsistencies. This study develops an efficient 3D deep-learning framework to generate T1-contrast enhanced images (T1C) from pre-contrast multi...

Metabolic Syndrome and a Broken Heart: Trust Your Gut or Risk Your Heart.

Gut dysbiosis is increasingly recognized as a contributor to heart failure; however, its specific role in the development of metabolic syndrome-induce...

Development of a machine learning-based model for prediction of diabetes risk in patients with metabolic dysfunction-associated steatotic liver disease (MASLD).

BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) is a leading chronic liver disorder closely linked to diabetes mellitus (...

A comprehensive multi-task deep learning model for kidney cancer: histological subtyping, clinical staging, and anatomical complexity grading.

OBJECTIVES: To develop and validate a multi-task deep learning (MTDL) model using multiphase contrast-enhanced CT (CECT) for simultaneously assessing ...

Predicting and interpreting protein and phosphoprotein abundance from pan-cancer and single-cell transcriptomes.

Proteins that impact phenotype and disease are often approximated by RNA expression, which poorly infers protein abundance. We developed DeepGxP, a de...

Effect of frailty status and histopathological features on upstaging of non-muscle-invasive bladder cancer: a critical analysis based on machine learning.

AIM: This study aimed to develop a machine learning (ML)-assisted model to predict the risk of upstaging (subsequent higher stage on repeat pathology)...

Machine learning-based prediction of three-year mortality in elderly inpatients with coronary artery disease combined with heart failure.

OBJECTIVE: Accurate prediction of survival outcome is essential for early intervention and treatment optimization. This study aimed to develop a model...

Beyond the Chill: Emerging Electrolytes, Cathodes, and Air Electrodes for Cryogenic Aqueous Zn Batteries.

The burgeoning demand for energy storage in extreme cold environments has accelerated global research into low-temperature battery technologies. Aqueo...

Designing with Li2S in Lithium-Sulfur Batteries: From Fundamental Chemistry to Practical Architectures.

Lithium-sulfur (Li-S) batteries deliver gravimetric energy densities considerably higher than those of conventional lithium-ion systems while relying ...

Interpretable machine learning model for predicting refeeding syndrome after colorectal cancer surgery.

OBJECTIVE: Refeeding syndrome (RFS) is a common yet frequently overlooked complication during postoperative nutritional support in patients undergoing...

PHLDB1 and WDFY4 as dual-state biomarkers in SLE pathogenesis and lupus nephritis prediction.

OBJECTIVES: Our previous study confirmed systemic lupus erythematosus (SLE) associated with polymorphisms of PHLDB1 and WDFY4 genes. In this study, we...

Predicting kidney graft survival with a machine learning model based on for-cause biopsy transcriptomics.

Kidney transplantation significantly improves outcomes in end-stage renal disease, however, long-term graft survival remains suboptimal. Traditional p...

Diagnostic Accuracy of Artificial Intelligence-Enabled Retinal Biomarkers for Detecting Type 2 Diabetes and Prediabetes Among Asian Indians [DART Study].

PURPOSE: To identify retinal microvascular features that distinguish normoglycemia from diabetes mellitus (DM)[Study-1] and prediabetes (PreDM)[Study-...

Prediction of renal cell carcinoma: Development and validation of machine learning model.

Renal cell carcinoma (RCC) is the leading cause of urinary system morbidity and mortality. Early identification is crucial for improving RCC patient o...

An exploratory study on the relationship between renal cell carcinoma and CAFs infiltration by integrating Pathomics and collagen features.

OBJECTIVE: Cancer-associated fibroblasts (CAFs) are a critical component of the tumor microenvironment and play a significant role in renal cell carci...

Coriandrum sativum improves prognosis in clear cell renal cell carcinoma by targeting NEK6 to modulate the immune microenvironment: a predictive study based on network pharmacology and multi-omics analysis.

Coriandrum sativum L. (coriander) is a medicinal herb with diverse pharmacological properties, but its molecular mechanism in clear cell renal cell ca...

Chronic kidney disease detection using XceptionNet with Harmonic Addax Optimization.

Chronic Kidney Disease (CKD) refers to a persistent and progressive impairment of kidney function occurring over a prolonged duration. Impaired kidney...

Comment on Machine learning survival analysis for predicting kidney disease progression in patients with acute kidney injury undergoing continuous kidney replacement therapy: An analysis of the LINKA database.

Exploration Novel Therapeutic Targets for Periodontitis via Stress Granules Biomarkers.

BACKGROUND: Periodontitis (PD) is associated with stress granules (SGs), which are involved in cellular stress responses. Identifying biomarkers relat...