YU TANG¹, WENXIAO HU^2,*, YAJUN PENG¹, XIANGDONG LING²

BIOCELL, Vol.48, No.10, pp. 1503-1516, 2024, DOI:10.32604/biocell.2024.052692 - 02 October 2024

Abstract Background: Podocyte injury is crucial in diabetic kidney disease (DKD) progression, and the mechanism remains unclear. The previous studies indicated Diosgenin played a key role in inhibiting podocyte injury progression. However, more research is needed to explore Diosgenin in inhibiting-molecular mechanisms in the process of podocyte injury. Methods: The content of Diosgenin in HeShenwan was detected by High-Performance Liquid Chromatography-mass spectrometry (HPLC-MS) method. The podocyte injury model was constructed by high glucose (HG)-induced mpc5 cells. The Cell Counting Kit-8 (CCK-8) assay was utilized to evaluate the activity of mpc5 cells. Pyroptosis in mpc5 cells was… More > Graphic Abstract

Sultan Mesfer Aldossary^*

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3387-3404, 2023, DOI:10.32604/iasc.2023.035249 - 15 March 2023

Abstract With the emergence of cloud technologies, the services of healthcare systems have grown. Simultaneously, machine learning systems have become important tools for developing matured and decision-making computer applications. Both cloud computing and machine learning technologies have contributed significantly to the success of healthcare services. However, in some areas, these technologies are needed to provide and decide the next course of action for patients suffering from diabetic kidney disease (DKD) while ensuring privacy preservation of the medical data. To address the cloud data privacy problem, we proposed a DKD prediction module in a framework using cloud… More >