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Identification of Potential Necroinflammation-associated Necroptosis-related Biomarkers for Delayed Graft Function and Renal Allograft Failure: a Machine Learning-based Exploration in the Framework of Predictive, Preventive, and Personalized Medicine by Qing Bi; Ji-Yue Wu; Xue-Meng Qiu; Yu-Qing Li; Yu-Yao Yan; Ze-Jia Sun; Wei Wang is a Medicine article available to read on EtoBox.

What is Identification of Potential Necroinflammation-associated Necroptosis-related Biomarkers for Delayed Graft Function and Renal Allograft Failure: a Machine Learning-based Exploration in the Framework of Predictive, Preventive, and Personalized Medicine about?

Delayed graft function (DGF) is one of the key post-operative challenges for a subset of kidney transplantation (KTx) patients. Graft survival is significantly lower in recipients who have experienced DGF than in those who have not. Assessing the risk of chronic graft injury, predicting graft rejection, providing personalized treatment, and improving graft survival are major strategies for predictive, preventive, and personalized medicine (PPPM/3PM) to promote the development of transplant medicine. However, since PPPM aims to accurately identify disease by integrating multiple omics, current methods to predict DGF and graft survival can still be improved. Renal ischemia/reperfusion injury (IRI) is a pathological process experienced by all KTx recipients that can result in varying occurrences of DGF, chronic rejection, and allograft failure depending on its severity. During this process, a necroinflammation-mediated necroptosis-dependent secondary wave of cell death significantly contributes to post-IRI tubular cell loss. In this article, we obtained the expression matrices and corresponding clinical data from the GEO database. Subsequently, nine differentially expressed necroinfla

Who reads Identification of Potential Necroinflammation-associated Necroptosis-related Biomarkers for Delayed Graft Function and Renal Allograft Failure: a Machine Learning-based Exploration in the Framework of Predictive, Preventive, and Personalized Medicine?

Author

Qing Bi; Ji-Yue Wu; Xue-Meng Qiu; Yu-Qing Li; Yu-Yao Yan; Ze-Jia Sun; Wei Wang

Publisher

Springer Science and Business Media LLC

Published

2023

Language

EN

Field

Medicine (Health Sciences)