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Clinical Analysis of the Renal Protective Effect of GLP-1 on Diabetic Patients Based on Edge Detection

With the rapid development of IoT technology, it is a new trend to combine edge computing with smart medicine in order to better develop modern medicine, avoid the crisis of information “sibling,” and meet the requirements of timeliness and computational performance of the massive data generated by...

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Autores principales: Wang, Jing, Wang, Yang, Pang, Ping, Jia, Xiaomeng, Yan, Xu, Lv, Zhaohui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8964200/
https://www.ncbi.nlm.nih.gov/pubmed/35360475
http://dx.doi.org/10.1155/2022/6504006
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author Wang, Jing
Wang, Yang
Pang, Ping
Jia, Xiaomeng
Yan, Xu
Lv, Zhaohui
author_facet Wang, Jing
Wang, Yang
Pang, Ping
Jia, Xiaomeng
Yan, Xu
Lv, Zhaohui
author_sort Wang, Jing
collection PubMed
description With the rapid development of IoT technology, it is a new trend to combine edge computing with smart medicine in order to better develop modern medicine, avoid the crisis of information “sibling,” and meet the requirements of timeliness and computational performance of the massive data generated by edge devices. However, edge computing is somewhat open and prone to security risks, so the security and privacy protection of edge computing systems for smart healthcare is receiving increasing attention. The two groups were compared before and after treatment for blood glucose, blood lipids, blood pressure, renal function, serum advanced glycosylation end products (AGEs) and cyclic adenosine monophosphate (cAMP), serum oxidative stress indicators, and levels of cAMP/PKA signalling pathway-related proteins in peripheral blood mononuclear cells. The results of this study show that the reduction of AGEs, the improvement of oxidative stress, and the regulation of the cAMP/PKA signalling pathway may be associated with a protective effect against early DKD. By introducing the edge computing system and its architecture for smart healthcare, we describe the security risks encountered by smart healthcare in edge computing, introduce the solutions proposed by some scholars to address the security risks, and finally summarize the security protection framework and discuss the specific solutions for security and privacy protection under this framework, which will provide some help for the credible research of smart healthcare edge computing.
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spelling pubmed-89642002022-03-30 Clinical Analysis of the Renal Protective Effect of GLP-1 on Diabetic Patients Based on Edge Detection Wang, Jing Wang, Yang Pang, Ping Jia, Xiaomeng Yan, Xu Lv, Zhaohui J Healthc Eng Research Article With the rapid development of IoT technology, it is a new trend to combine edge computing with smart medicine in order to better develop modern medicine, avoid the crisis of information “sibling,” and meet the requirements of timeliness and computational performance of the massive data generated by edge devices. However, edge computing is somewhat open and prone to security risks, so the security and privacy protection of edge computing systems for smart healthcare is receiving increasing attention. The two groups were compared before and after treatment for blood glucose, blood lipids, blood pressure, renal function, serum advanced glycosylation end products (AGEs) and cyclic adenosine monophosphate (cAMP), serum oxidative stress indicators, and levels of cAMP/PKA signalling pathway-related proteins in peripheral blood mononuclear cells. The results of this study show that the reduction of AGEs, the improvement of oxidative stress, and the regulation of the cAMP/PKA signalling pathway may be associated with a protective effect against early DKD. By introducing the edge computing system and its architecture for smart healthcare, we describe the security risks encountered by smart healthcare in edge computing, introduce the solutions proposed by some scholars to address the security risks, and finally summarize the security protection framework and discuss the specific solutions for security and privacy protection under this framework, which will provide some help for the credible research of smart healthcare edge computing. Hindawi 2022-03-22 /pmc/articles/PMC8964200/ /pubmed/35360475 http://dx.doi.org/10.1155/2022/6504006 Text en Copyright © 2022 Jing Wang et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Wang, Jing
Wang, Yang
Pang, Ping
Jia, Xiaomeng
Yan, Xu
Lv, Zhaohui
Clinical Analysis of the Renal Protective Effect of GLP-1 on Diabetic Patients Based on Edge Detection
title Clinical Analysis of the Renal Protective Effect of GLP-1 on Diabetic Patients Based on Edge Detection
title_full Clinical Analysis of the Renal Protective Effect of GLP-1 on Diabetic Patients Based on Edge Detection
title_fullStr Clinical Analysis of the Renal Protective Effect of GLP-1 on Diabetic Patients Based on Edge Detection
title_full_unstemmed Clinical Analysis of the Renal Protective Effect of GLP-1 on Diabetic Patients Based on Edge Detection
title_short Clinical Analysis of the Renal Protective Effect of GLP-1 on Diabetic Patients Based on Edge Detection
title_sort clinical analysis of the renal protective effect of glp-1 on diabetic patients based on edge detection
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8964200/
https://www.ncbi.nlm.nih.gov/pubmed/35360475
http://dx.doi.org/10.1155/2022/6504006
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