AIMC Topic: Diabetic Nephropathies

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Cross-talk between diabetic nephropathy and bone loss: PBMCs-guided discovery of NLRP3-inflammatory signalling.

Artificial cells, nanomedicine, and biotechnology
Diabetic nephropathy (DN), a major driver of end-stage kidney disease, elevates the risk for osteoporosis (OP) and its clinical precursor, low bone mineral density (low BMD), indicating broader systemic effects. While peripheral blood mononuclear cel...

Artificial intelligence-based diagnosis of diabetic kidney disease using urinary VOC biosensor data.

BMC nephrology
BACKGROUND: Diabetic kidney disease (DKD) remains a leading cause of chronic kidney disease worldwide. However, current diagnostic methods rely on indirect biomarkers or invasive renal biopsy. This study aimed to evaluate the feasibility of urinary v...

Reliable biomarkers for diabetic nephropathy using machine learning-assisted contrast-enhanced ultrasonography and clinical characteristics.

Clinical and experimental medicine
OBJECTIVE: To utilize machine learning techniques to screen contrast-enhanced ultrasound (CEUS) parameters and clinical characteristics, aiming to differentiate diabetic nephropathy (DN) from non-diabetic renal disease (NDRD) in patients with diabeti...

Multi-omics and machine learning identify FN1 and ALDH2 as diagnostic biomarkers and therapeutic targets in early and late diabetic kidney disease.

Renal failure
Diabetic kidney disease (DKD), the leading cause of end-stage kidney disease worldwide, demands deeper molecular characterization to improve clinical management. This study employed an integrated multi-omics approach to identify stage-specific biomar...

Interpretable Machine Learning Model for Predicting and Assessing the Risk of Diabetic Nephropathy: Prediction Model Study.

JMIR medical informatics
BACKGROUND: Diabetic nephropathy (DN), a severe complication of diabetes, is characterized by proteinuria, hypertension, and progressive renal function decline, potentially leading to end-stage renal disease. The International Diabetes Federation pro...

Integrative transcriptomic and genomic insights into diabetic kidney disease: evidence from multi-omics analysis and experimental validation.

Renal failure
Diabetic kidney disease (DKD) remains a critical challenge in diabetes management, necessitating a deep understanding of its molecular underpinnings for better diagnosis and treatment strategies. This study was conducted to identify and validate nove...

Multiple instance learning using pathology foundation models effectively predicts kidney disease diagnosis and clinical classification.

Scientific reports
Recently developed pathology foundation models, pretrained on large-scale pathology datasets, have demonstrated excellent performance in various downstream tasks. This study evaluated the utility of pathology foundation models combined with multiple ...

Finerenone Modulates PANoptosis to Improve Immune Microenvironment in Diabetic Nephropathy: A Machine Learning-Based Mechanistic Analysis.

Journal of molecular neuroscience : MN
Diabetic nephropathy (DN) is characterized by nephron degeneration induced by hyperglycemia, driven by complex interactions between glucose metabolism dysregulation and immune microenvironment dynamics. This study employed machine learning and bioinf...

Identification and experimental validation of mitochondrial and endoplasmic reticulum stress related gene in diabetic nephropathy.

Scientific reports
Diabetic nephropathy (DN) is a kidney disease. Mitochondrial and endoplasmic reticulum stress (ERS) significantly contribute to diabetic nephropathy (DN), although the precise mechanisms involved have not yet been fully understood. The objective of t...