Diabetic kidney disease (DKD) progression is not well understood. Using high-throughput proteomics, biostatistical, pathway and machine learning tools, we examine the urinary Complement proteome in two prospective cohorts with type 1 or 2 diabetes an...
Diabetic kidney disease (DKD) is a major cause of end-stage renal disease globally, with podocytes being implicated in its pathogenesis. However, the underlying mechanisms of podocyte involvement remain unclear. The aim of the present study was to id...
OBJECTIVE: Diabetic kidney disease (DKD) is a leading cause of chronic kidney disease, with chronic inflammation driving its progression. This study aimed to identify immune-related diagnostic biomarkers for DKD and explore their association with imm...
BACKGROUND: Diabetic kidney disease (DKD) is the major cause of chronic kidney failure, with tubulointerstitial fibrosis playing a crucial role in disease development. Identifying fibrosis-related genes is crucial for improving diagnosis and developi...
Diabetic kidney disease (DKD) is a serious complication of diabetes patients with long time duration, presenting with albuminuria and/or a reduced estimated glomerular filtration rate (eGFR), and without symptoms of other primary causes of kidney inj...
The role of genetic susceptibility in early warning and precise treatment of diabetic kidney disease (DKD) requires further investigation. A case-control study was conducted to evaluate the predictive effect of GSK3B genetic polymorphisms on the susc...
Anoikis and immune cell infiltration are pivotal factors in the pathophysiological mechanism of diabetic nephropathy (DN), yet a comprehensive understanding of the mechanism is lacking. This work aimed to pinpoint distinctive anoikis-related genes (A...
BACKGROUND: Diabetic kidney disease (DKD) is a common and serious complication of diabetes mellitus and has become the most important cause of end-stage renal disease (ESRD). In light of the rising prevalence of diabetes, there is a growing imperativ...
BACKGROUND: Machine learning (ML) models are being increasingly employed to predict the risk of developing and progressing diabetic kidney disease (DKD) in patients with type 2 diabetes mellitus (T2DM). However, the performance of these models still ...
OBJECTIVES: Diabetic kidney disease (DKD) is driven by mitochondrial dysfunction and immune dysregulation, yet the mechanistic interplay remains poorly defined. This study aimed to identify key molecular networks linking mitochondrial and immune path...
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