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Zhang FY, Wang LL, Zeng K, Dong WW, Yuan HY, Ma XY, Wang ZW, Zhao Y, Zhao R, Guan DW. A fundamental study on postmortem submersion interval estimation by metabolomics analyzing of gastrocnemius muscle from submersed rat models in freshwater. Int J Legal Med 2024; 138:2037-2047. [PMID: 38802694 DOI: 10.1007/s00414-024-03258-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Accepted: 05/16/2024] [Indexed: 05/29/2024]
Abstract
In forensic practice, determining the postmortem submersion interval (PMSI) and cause-of-death of cadavers in aquatic ecosystems has always been challenging task. Traditional approaches are not yet able to address these issues effectively and adequately. Our previous study proposed novel models to predict the PMSI and cause-of-death based on metabolites of blood from rats immersed in freshwater. However, with the advance of putrefaction, it is hardly to obtain blood samples beyond 3 days postmortem. To further assess the feasibility of PMSI estimation and drowning diagnosis in the later postmortem phase, gastrocnemius, the more degradation-resistant tissue, was collected from drowned rats and postmortem submersion model in freshwater immediately after death, and at 1 day, 3 days, 5 days, 7 days, and 10 days postmortem respectively. Then the samples were analyzed with liquid chromatography-tandem mass spectrometry (LC-MS/MS) to investigate the dynamic changes of the metabolites. A total of 924 metabolites were identified. Similar chronological changes of gastrocnemius metabolites were observed in the drowning and postmortem submersion groups. The difference in metabolic profiles between drowning and postmortem submersion groups was only evident in the initial 1 day postmortem, which was faded as the PMSI extension. Nineteen metabolites representing temporally-dynamic patterns were selected as biomarkers for PMSI estimation. A regression model was built based on these biomarkers with random forest algorithm, which yielded a mean absolute error (± SE) of 5.856 (± 1.296) h on validation samples from an independent experiment. These findings added to our knowledge of chronological changes in muscle metabolites from submerged vertebrate remains during decomposition, which provided a new perspective for PMSI estimation.
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Affiliation(s)
- Fu-Yuan Zhang
- Department of Forensic Pathology, China Medical University School of Forensic Medicine, Shenyang, China
- Liaoning Province Key Laboratory of Forensic Bio-evidence Science, Shenyang, China
- Collaborative Laboratory of Intelligentized Forensic Science, Shenyang, China
| | - Lin-Lin Wang
- Department of Forensic Pathology, China Medical University School of Forensic Medicine, Shenyang, China
- Liaoning Province Key Laboratory of Forensic Bio-evidence Science, Shenyang, China
- Collaborative Laboratory of Intelligentized Forensic Science, Shenyang, China
| | - Kuo Zeng
- Institute of Evidence Law and Forensic Science, China University of Political Science and Law, Beijing, China
| | - Wen-Wen Dong
- Department of Forensic Pathology, China Medical University School of Forensic Medicine, Shenyang, China
- Liaoning Province Key Laboratory of Forensic Bio-evidence Science, Shenyang, China
- Collaborative Laboratory of Intelligentized Forensic Science, Shenyang, China
| | - Hui-Ya Yuan
- Department of Forensic Pathology, China Medical University School of Forensic Medicine, Shenyang, China
- Liaoning Province Key Laboratory of Forensic Bio-evidence Science, Shenyang, China
- Collaborative Laboratory of Intelligentized Forensic Science, Shenyang, China
| | - Xing-Yu Ma
- Institute of Evidence Law and Forensic Science, China University of Political Science and Law, Beijing, China
| | - Zi-Wei Wang
- Department of Forensic Pathology, China Medical University School of Forensic Medicine, Shenyang, China
- Liaoning Province Key Laboratory of Forensic Bio-evidence Science, Shenyang, China
- Collaborative Laboratory of Intelligentized Forensic Science, Shenyang, China
| | - Yu Zhao
- Department of Forensic Pathology, China Medical University School of Forensic Medicine, Shenyang, China
| | - Rui Zhao
- Department of Forensic Pathology, China Medical University School of Forensic Medicine, Shenyang, China.
- PreventionKey Laboratory of Environmental Stress and Chronic Disease Control and Prevention, Ministry of Education, China Medical University, Shenyang, China.
- Liaoning Province Key Laboratory of Forensic Bio-evidence Science, Shenyang, China.
- Collaborative Laboratory of Intelligentized Forensic Science, Shenyang, China.
| | - Da-Wei Guan
- Department of Forensic Pathology, China Medical University School of Forensic Medicine, Shenyang, China.
- Liaoning Province Key Laboratory of Forensic Bio-evidence Science, Shenyang, China.
- Collaborative Laboratory of Intelligentized Forensic Science, Shenyang, China.
- Institute of Evidence Law and Forensic Science, China University of Political Science and Law, Beijing, China.
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Gelderman H, Kruiver C, Oostra R, Zeegers M, Duijst W. Estimation of the postmortem interval based on the human decomposition process. J Forensic Leg Med 2019; 61:122-127. [DOI: 10.1016/j.jflm.2018.12.004] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2018] [Revised: 12/09/2018] [Accepted: 12/10/2018] [Indexed: 10/27/2022]
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Sun T, Yang T, Zhang H, Zhuo L, Liu L. Interpolation function estimates post mortem interval under ambient temperature correlating with blood ATP level. Forensic Sci Int 2014; 238:47-52. [PMID: 24642264 DOI: 10.1016/j.forsciint.2014.02.014] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2013] [Revised: 02/10/2014] [Accepted: 02/16/2014] [Indexed: 11/17/2022]
Abstract
OBJECTIVE We developed a mathematical model using interpolation function, to characterize the correlation between blood ATP levels in the right ventricle of rabbit and post mortem interval (PMI) at different ambient temperatures. METHODS Forty-eight healthy rabbits were randomly divided into 6 groups of 8 each. The sacrificed rabbits were maintained in calorstats at 10°C, 15°C, 20°C, 25°C, 30°C and 35°C, respectively. Blood from the right ventricle was sampled every 4h until 72h after death. At different time points, ATP concentrations in the blood samples were measured using an ATP fluorescence rapid detector, and then displayed on the detector screen in the form of relative light units (RLU). Relationship between PMI and ATP degradation levels was investigated statistically by SPSS 17.0 and MATLAB 10.0 software. RESULTS We obtained six regression equations (Ra(2)=0.887-0.929) with RLU values at PMIs of 72h (10°C), 60h (15°C), 56h (20°C), 52h (25°C), 40h (30°C) and 32h (35°C), and an interpolation function (Ra(2)=0.930) was established with PMI as the dependent variable (z), RLU value as independent variable (x) and temperature as independent variable (y). CONCLUSION Interpolation function is an appropriate choice for PMI estimation by weakening influence of ambient temperature.
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Affiliation(s)
- Tingyi Sun
- Department of Forensic Medicine, Tongji Medical College of Huazhong University of Science and Technology, Wuhan 430030, China
| | - Tiantong Yang
- Collaborative Innovation Center of Judicial Civilization, Beijing 100040, China; Key Laboratory of Evidence Science, China University of Political Science and Law, Ministry of Education, Beijing 100040, China
| | - Haidong Zhang
- Collaborative Innovation Center of Judicial Civilization, Beijing 100040, China; Key Laboratory of Evidence Science, China University of Political Science and Law, Ministry of Education, Beijing 100040, China
| | - Luo Zhuo
- Department of Forensic Medicine, Tongji Medical College of Huazhong University of Science and Technology, Wuhan 430030, China
| | - Liang Liu
- Department of Forensic Medicine, Tongji Medical College of Huazhong University of Science and Technology, Wuhan 430030, China.
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