Estimation of Early Postmortem Interval of Asphyxial Death Rats at Different Ambient Temperatures by GC-MS-Based Metabolomics

• Published in: Fa yi xue za zhi Vol. 36; no. 6; pp. 741 - 748
• Main Authors: Fang, S Y, Dai, X H, Xiao, L, Zou, J, Yang, L, Ye, Y, Liao, L C
• Format: Journal Article
• Language: Chinese
• Published: China Editorial Office of Journal of Forensic Medicine 01.12.2020
• Subjects: Animals; Autopsy; forensic pathology; metabolomics; gas chromatography-mass spectrometry; models, statistical; ambient temperature; metabolite; estimation of postmortem interval; rats; Gas Chromatography-Mass Spectrometry; Metabolomics; Postmortem Changes; Rats; Temperature; forensic pathology; metabolomics; gas chromatography-mass spectrometry; models, statistical; ambient temperature; metabolite; estimation of postmortem interval; rats
• ISSN: 1004-5619
• DOI: 10.12116/j.issn.1004-5619.2020.06.001

Objective To establish the orthogonal partial least square （OPLS） model for the estimation of early postmortem interval （PMI） of asphyxial death rats in four ambient temperatures based on gas chromatography-mass spectrometry （GC-MS） metabolomics. Methods The 96 rats were divided into four temperature groups （5 ℃, 15 ℃, 25 ℃ and 35 ℃）. Each temperature group was further divided into 3 h, 6 h, 12 h and 24 h after death, and 6 other rats were taken as the control group. The cardiac blood was collected at the set time points for the four temperature groups and 0 h after death for the control group for the metabolomics analysis by GC-MS. By OPLS analysis, the variable importance in projection （VIP）>1 and the result of Kruskal-Wallis test P<0.001 were used to screen out the differential metabolite related to PMIs in the cardiac blood of rats of different temperature groups. Then OPLS regression models of different temperature groups were established with these metabolites. At the same time, a prediction group for i