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| Serum Metabolomics Study of CCI Model Rats Based on UHPLC-QE-MS |
| BAI Feng-yuan1, 2, ZHAO Dong-mei1, 2, CAI Ren-jun1, 2, SONG Su-fei1, 2, LIU Tao1, 2*, XU Qiu-ling1, 2* |
1. The First Affiliated Hospital of Hainan Medical University, Haikou 571199, China
2. School of Traditional Chinese Medicine, Hainan Medical University, Haikou 571199, China
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Abstract In this study, ultra-high performance liquid chromatography-quadrupole electrostatic field orbital trap mass spectrometry ( UHPLC-QE-MS ) non-targeted metabolomics method was used to observe the changes of endogenous metabolites in serum of CCI rats, screen out the serum differential metabolites of chronic sciatica rats, and analyze the effect of chronic pain on differential metabolites. Twelve SPF SD male rats were randomly divided into the normal control group and a chronic constriction injury ( CCI ) group, with 6 rats in each group. A chronic compression injury model of the left sciatic nerve was established in the CCI group. The normal control group had the same steps except no sciatic nerve ligation. After 14 days, abdominal aorta blood was collected, and serum was separated, and then the metabolites in rat serum were detected by metabolomics. The differential metabolites were screened by UHPLC-QE-MS combined with PCA ( principal component analysis ), and the enrichment analysis of differential metabolites was performed by Metabolic Analyst 5.0. The enrichment analysis results showed that compared with the normal control group, the serum organic acids, organic heterocyclic compounds, fatty acyl, carbohydrates, nucleic acids, organic nitrogen compounds, hydrocarbons and other nine metabolites of CCI model rats were statistically different. The serum metabolomics method based on UHPLC-QE-MS can effectively distinguish the normal group and the CCI group, and the screened differential metabolites are helpful in studying the mechanism of chronic pain and drug targets.
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Received: 2021-07-09
Accepted: 2021-09-28
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Corresponding Authors:
LIU Tao, XU Qiu-ling
E-mail: xql7809@163.com；13647549720@163.com
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