Your browser doesn't support javascript.
loading
Metabolomics characteristics in a rat model of myocardial infarction based on bibiometrics analyses / 中国组织工程研究
Chinese Journal of Tissue Engineering Research ; (53): 633-640, 2017.
Article in Chinese | WPRIM | ID: wpr-510571
ABSTRACT

BACKGROUND:

Metabonomics has been proved to analyze and observe the pathological process of rat myocardial infarction and the underlying mechanism.

OBJECTIVE:

To further analyze the metabolomic pathways of bioinformatics in rat models of myocardial infarction.

METHODS:

The experimental studies about rat myocardial infarction were retrieved from CNKI, WanFang, CqVip, PubMed and Embase databases. The metabolic products described in the literatures were col ected and summarized. Signaling pathways were analyzed using KEGG database molecular function annotation, the enzymes, translocators and their properties were analyzed by HMDB database. Metabolites pathway were visualized with MetPA. RESULTS AND CONSLUSIONA total of 26 metabolic products were identified in the included literatures and mainly participated in 29 metabolic pathways. Through topology analysis, 5 of the 10 metabolic pathways were selected and regarded as the metabolic pathways of myocardial infarction in rats, including aminoacyl-tRNA biosynthesis;glycine, serine and threonine metabolism;valine, leucine and isoleucine biosynthesis;biosynthesis of unsaturated fatty acids;phenylalanine, tyrosine and tryptophan biosynthesis. In conclusion, the bioinformatics analysis of metabolites in rats with myocardial infarction show that myocardial infarction is related to the metabolism and metabolic pathways of carbohydrates, proteins, fat and RNA.
Full text: Available Index: WPRIM (Western Pacific) Type of study: Prognostic study Language: Chinese Journal: Chinese Journal of Tissue Engineering Research Year: 2017 Type: Article

Similar

MEDLINE

...
LILACS

LIS

Full text: Available Index: WPRIM (Western Pacific) Type of study: Prognostic study Language: Chinese Journal: Chinese Journal of Tissue Engineering Research Year: 2017 Type: Article