Background & aim: Accurate assessment of glomerulosclerosis is essential for diagnosis, prognosis, and treatment of kidney diseases. Here, we developed a deep learning–based scoring method for glomerulosclerosis in PAS-stained kidney tissue. Additionally, we implemented an AI-based compartmental analysis to evaluate how…
Background & aim: Translational models are essential to identify improved treatment options for chronic kidney disease (CKD) patients. However, most preclinical CKD models do not demonstrate reduced glomerular filtration rate (GFR) or improvement by standard of care (SoC). The aim…
Background & aim: Glucagon influences kidney function through both direct intrarenal glucagon receptor (GCGR) signaling and indirect humoral pathways. Increasing evidence suggests that renal GCGR activity is impaired in chronic kidney disease (CKD). Survodutide is a novel, long-acting dual GCGR/GLP-1…
Background & aim: Translational rodent models of glomerulosclerosis are essential in drug discovery for chronic kidney disease (CKD). The anti-glomerular basement membrane (anti-GBM) model in mice represents a clinically relevant model as it exhibits key features of albuminuria and glomerulosclerosis.…
Background & aim: The current understanding of diabetic kidney disease (DKD) has significant gaps regarding the underlying pathogenesis. In this study, we aimed to characterize the temporal progression of DKD using a state-of-the-art mouse model of hypertension-accelerated disease, integrating kidney…
