当前位置: X-MOL 学术Proteome Sci. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
The proteomics analysis of the effects of Zhishi Rhubarb soup on ischaemic stroke
Proteome Science ( IF 2 ) Pub Date : 2021-11-10 , DOI: 10.1186/s12953-021-00181-z
Jing-Hua Zhang 1 , Yue-Jia Shao 1, 2 , Zhen Hui 1 , Su-Lei Wang 1 , Chi Huang 1 , Yang Zhao 1
Affiliation  

Stroke has always been a major threat worldwide but is most severe in China, with 2.5 million new stroke cases each year and 7.5 million stroke survivors, placing a heavy burden on the social and national health care systems. Zhishi Rhubarb Soup (ZRS) is a traditional Chinese medicine (TCM) that has been used clinically for many years in China. To explore the potential mechanism of ZRS in the treatment of stroke, liquid chromatography with mass spectrometry (LC–MS) was performed. In this study, a quantitative proteomic method with LC–MS was used to analyse the proteomic differences between MACO samples treated with ZRS and those without ZRS treatment. Liquid chromatography with mass spectrometry (LC–MS) analysis led to the identification of 35,006 peptides, with 5160.0 proteins identified and 4094.0 quantified. Significantly differentially expressed proteins were identified through data analysis, and the difference was found to be more than 1.2 times (P < 0.05). The Gene Ontology (GO) analysis provided a summary of the dysregulated protein expression in the biological process (BP), cell component (CC), and molecular function (MF) categories. Proteins related to brain repair, including BDNF, IL-10, IL-6, and TGF-β, were found to change significantly, partially demonstrating the effectiveness of ZRS to attenuate tissue injury. In this study, LC–MS/MS was performed to assess the effects of ZRS on differentially expressed proteins in rats with cerebral infarction. These promising results could help to improve the understanding of the effects of drugs on stroke.
更新日期:2021-11-10
down
wechat
bug