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Diabetic Nephropathies

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Integrative analysis of potential diagnostic markers and therapeutic targets for glomerulus-associated diabetic nephropathy based on cellular senescence.

Frontiers in immunology
INTRODUCTION: Diabetic nephropathy (DN), distinguished by detrimental changes in the renal glomeruli, is regarded as the leading cause of death from end-stage renal disease among diabetics. Cellular senescence plays a paramount role, profoundly affec...

Study of Serum Fibroblast Growth Factor 23 as a Predictor of Endothelial Dysfunction among Egyptian Patients with Diabetic Kidney Disease.

Saudi journal of kidney diseases and transplantation : an official publication of the Saudi Center for Organ Transplantation, Saudi Arabia
Endothelial dysfunction in patients with diabetic nephropathy is caused by nontraditional factors in addition to common risk factors (e.g., hypertension) in people with normal kidney function. These nontraditional factors include factors involved in ...

Interpretable machine learning identifies metabolites associated with glomerular filtration rate in type 2 diabetes patients.

Frontiers in endocrinology
OBJECTIVE: The co-occurrence of kidney disease in patients with type 2 diabetes (T2D) is a major public health challenge. Although early detection and intervention can prevent or slow down the progression, the commonly used estimated glomerular filtr...

Integrated machine learning and deep learning for predicting diabetic nephropathy model construction, validation, and interpretability.

Endocrine
OBJECTIVE: To construct a risk prediction model for assisted diagnosis of Diabetic Nephropathy (DN) using machine learning algorithms, and to validate it internally and externally.

Integrating network pharmacology, molecular docking and simulation approaches with machine learning reveals the multi-target pharmacological mechanism of against diabetic nephropathy.

Journal of biomolecular structure & dynamics
Diabetic nephropathy (DN) is one of the most feared complications of diabetes and key cause of end-stage renal disease (ESRD). has been widely used to treat diabetic complications, but exact molecular mechanism is yet to be discovered. Data on activ...

Construction of Risk Prediction Model of Type 2 Diabetic Kidney Disease Based on Deep Learning.

Diabetes & metabolism journal
BACKGRUOUND: This study aimed to develop a diabetic kidney disease (DKD) prediction model using long short term memory (LSTM) neural network and evaluate its performance using accuracy, precision, recall, and area under the curve (AUC) of the receive...

Artificial intelligence assists identification and pathologic classification of glomerular lesions in patients with diabetic nephropathy.

Journal of translational medicine
BACKGROUND: Glomerular lesions are the main injuries of diabetic nephropathy (DN) and are used as a crucial index for pathologic classification. Manual quantification of these morphologic features currently used is semi-quantitative and time-consumin...

Research on disease diagnosis based on teacher-student network and Raman spectroscopy.

Lasers in medical science
Diabetic nephropathy is a serious complication of diabetes, and primary Sjögren's syndrome is a disease that poses a major threat to women's health. Therefore, studying these two diseases is of practical significance. In the field of spectral analysi...

Apoptosis and NETotic cell death affect diabetic nephropathy independently: An study integrative study encompassing bioinformatics, machine learning, and experimental validation.

Genomics
OBJECTIVE: Although programmed cell death (PCD) and diabetic nephropathy (DN) are intrinsically conneted, the interplay among various PCD forms remains elusive. In this study, We aimed at identifying independently DN-associated PCD pathways and bioma...