Metabolic changes in rat urine after acute paraquat poisoning and discriminated by support vector machine. (11th November 2015)

• Record Type: Journal Article
• Authors: Wen, Congcong; Wang, Zhiyi; Zhang, Meiling; Wang, Shuanghu; Geng, Peiwu; Sun, Fa; Chen, Mengchun; Lin, Guanyang; Hu, Lufeng; Ma, Jianshe; Wang, Xianqin
• Is Part Of: Biomedical chromatography. Volume 30:Number 1(2016:Jan.)
• Page Start: 75
• Page End: 80
• Publication Date: 2015-11-11
• Subjects: metabolomics -- GC‐MS -- paraquat -- poisoning -- rat; Chromatographic analysis -- Periodicals; Biology -- Periodicals; Medicine -- Periodicals; Biology -- Periodicals; Chromatography -- methods -- Periodicals; Medicine -- Periodicals; 543.089
• DOI: 10.1002/bmc.3627
• Languages: English
• ISSNs: 0269-3879

Abstract

Abstract: Paraquat is quick‐acting and non‐selective, killing green plant tissue on contact; it is also toxic to human beings and animals. In this study, we developed a urine metabonomic method by gas chromatography–mass spectrometry to evaluate the effect of acute paraquat poisoning on rats. Pattern recognition analysis, including both partial least squares discriminate analysis and principal component analysis revealed that acute paraquat poisoning induced metabolic perturbations. Compared with the control group, the levels of benzeneacetic acid and hexadecanoic acid of the acute paraquat poisoning group (intragastric administration 36 mg/kg) increased, while the levels of butanedioic acid, pentanedioic acid, altronic acid decreased. Based on these urinary metabolomics data, support vector machine was applied to discriminate the metabolomic change of paraquat groups from the control group, which achieved 100% classification accuracy. In conclusion, metabonomic method combined with support vector machine can be used as a useful diagnostic tool in paraquat‐poisoned rats. Copyright © 2015 John Wiley & Sons, Ltd.