Jin Wenfang, Bi Jianli, Xu Sheng, Rao Mengfan, Wang Qi, Yuan Yan, Fan Baolei
Department of Medicine, Hubei University of Science and Technology, Xianning 437000, China.
Hubei Engineering Research Center of Traditional Chinese Medicine of South Hubei Province, Xianning 437000, China.
Chin Herb Med. 2022 Aug 23;14(4):602-611. doi: 10.1016/j.chmed.2022.07.002. eCollection 2022 Oct.
To establish a metabonomics research technique based on the combination of H-NMR and multivariate statistical analysis, so as to explore the metabolic regulation mechanism of extract (ARCE) in rat tissues and serum.
SD rats were randomly divided into blank group, female group and male group. The H-NMR technique was used to collect the information of rat tissues and serum samples in each group. The principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA) and other methods were used for data pattern recognition, so as to screen out potential differential metabolites and metabolic pathways, and then network analysis and KEGG database were used to analyze the relationship between metabolites, metabolic pathways and diseases.
The external features and H-NMR analysis showed that the sex of rats had no obvious effect on the drug action. A total of 15 potential differential metabolites and six metabolic pathways were screened out through data pattern recognition. Through network analysis and KEGG pathway analysis, three target diseases closely related to differential metabolites were found, and the metabolic pathway related to lung cancer was the central carbon metabolism of cancer.
This study shows that (ARC) may regulate the energy metabolism of the body by influencing arginine synthesis, so as to play the roles of anti-inflammation, analgesia, anti-tumor and immune regulation.
建立基于氢核磁共振（H-NMR）与多元统计分析相结合的代谢组学研究技术，以探讨提取物（ARCE）在大鼠组织和血清中的代谢调控机制。
将SD大鼠随机分为空白组、雌性组和雄性组。采用H-NMR技术收集各组大鼠组织和血清样本信息。运用主成分分析（PCA）、偏最小二乘判别分析（PLS-DA）等方法进行数据模式识别，筛选出潜在的差异代谢物和代谢途径，然后利用网络分析和KEGG数据库分析代谢物、代谢途径与疾病之间的关系。
外观特征及H-NMR分析表明，大鼠性别对药物作用无明显影响。通过数据模式识别共筛选出15种潜在差异代谢物和6条代谢途径。通过网络分析和KEGG通路分析，发现3种与差异代谢物密切相关的靶疾病，与肺癌相关的代谢途径为癌症的中心碳代谢。
本研究表明（ARC）可能通过影响精氨酸合成来调节机体能量代谢，从而发挥抗炎、镇痛、抗肿瘤及免疫调节作用。
