Inferring Postmortem Submersion Interval in Rats Found in Water Based on Vitreous Humor Metabolites.
10.12116/j.issn.1004-5619.2021.410613
- Author:
Fu-Yuan ZHANG
1
;
Lin-Lin WANG
1
;
Miao ZHANG
1
;
Wen-Wen DONG
1
;
Zhong-Duo ZHANG
1
;
Xin-Jie LI
1
;
Xing-Yu MA
1
;
Shu-Kui DU
1
;
Hao-Miao YUAN
1
;
Da-Wei GUAN
1
;
Rui ZHAO
1
Author Information
1. Center of Medico-legal Investigation, School of Forensic Medicine, China Medical University, Shenyang 110122, China.
- Publication Type:Journal Article
- Keywords:
forensic pathology;
liquid chromatography-tandem mass spectrometry;
metabolomics;
partial least square;
postmortem submersion interval;
principal components analysis;
rats;
vitreous humor
- MeSH:
Animals;
Biomarkers/metabolism*;
Cadaver;
Chromatography, Liquid;
Immersion;
Postmortem Changes;
Rats;
Rats, Sprague-Dawley;
Tandem Mass Spectrometry;
Vitreous Body/metabolism*;
Water/metabolism*
- From:
Journal of Forensic Medicine
2022;38(1):59-66
- CountryChina
- Language:English
-
Abstract:
OBJECTIVES:The metabolomics technique of LC-MS/MS combined with data analysis was used to detect changes and differences in metabolic profiles in the vitreous humor of early rat carcasses found in water, and to explore the feasibility of its use for early postmortem submersion interval (PMSI) estimation and the cause of death determination.
METHODS:The experimental model was established in natural lake water with 100 SD rats were randomly divided into a drowning group (n=50) and a postmortem (CO2 suffocation) immediately submersion group (n=50). Vitreous humor was extracted from 10 rats in each group at 0, 6, 12, 18 and 24 h postmortem for metabolomics analyses, of which 8 were used as the training set to build the model, and 2 were used as test set. PCA and PLS multivariate statistical analysis were performed to explore the differences in metabolic profiles among PMSI and causes of death in the training set samples. Then random forest (RF) algorithm was used to screen several biomarkers to establish a model.
RESULTS:PCA and PLS analysis showed that the metabolic profiles had time regularity, but no differences were found among different causes of death. Thirteen small molecule biomarkers with good temporal correlation were selected by RF algorithm. A simple PMSI estimation model was constructed based on this indicator set, and the data of the test samples showed the mean absolute error (MAE) of the model was 0.847 h.
CONCLUSIONS:The 13 metabolic markers screened in the vitreous humor of rat corpses in water had good correlations with the early PMSI. The simplified PMSI estimation model constructed by RF can be used to estimate the PMSI. Additionally, the metabolic profiles of vitreous humor cannot be used for early identification of cause of death in water carcasses.
