Seasonal mouse cadaver microbial study: rupture time and postmortem interval estimation model construction

The estimation of postmortem interval (PMI) has long been a focal point in the field of forensic science. Following the death of an organism, microorganisms exhibit a clock-like proliferation pattern during the course of cadaver decomposition, forming the foundation for utilizing microbiology in PMI estimation. The establishment of PMI estimation models based on datasets from different seasons is of great practical significance. In this experiment, we conducted microbiota sequencing and analysis on gravesoil and mouse intestinal contents collected during both the winter and summer seasons and constructed a PMI estimation model using the Random Forest algorithm. The results showed that the MAE of the gut microbiota model in summer was 0.47 ± 0.26 d, R2 = 0.991, and the MAE of the gravesoil model in winter was 1.04 ± 0.22 d, R2 = 0.998. We propose that, in practical applications, it is advantageous to selectively build PMI estimation models based on seasonal variations. Additionally, through a combination of morphological observations, gravesoil microbiota sequencing results, and soil physicochemical data, we identified the time of cadaveric rupture for mouse cadavers, occurring at around days 24-27 in winter and days 6-9 in summer. This study not only confirms previous research findings but also introduces novel insights, contributing to the foundational knowledge necessary to advance the utilization of microbiota for PMI estimation.

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Publication Details

Journal
PeerJ
Published
2024-09-13
DOI
https://doi.org/10.7717/peerj.17932
Citations
4
Primary Topic
Forensic Entomology and Diptera Studies
Type
article
Field-Weighted Citation Impact
2.16

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article

Seasonal mouse cadaver microbial study: rupture time and postmortem interval estimation model construction

Peng Gui, Hao Nie, Fengqin Yang, Xingchun Zhao et al.
4 citations
PeerJ
Forensic Entomology and Diptera Studies
2.16
article

Seasonal mouse cadaver microbial study: rupture time and postmortem interval estimation model construction

Peng Gui, Hao Nie, Fengqin Yang, Xingchun Zhao, Fan Yang, Yadong Guo, Changquan Zhang, Sheng Hu
article en
4 citations

Abstract

The estimation of postmortem interval (PMI) has long been a focal point in the field of forensic science. Following the death of an organism, microorganisms exhibit a clock-like proliferation pattern during the course of cadaver decomposition, forming the foundation for utilizing microbiology in PMI estimation. The establishment of PMI estimation models based on datasets from different seasons is of great practical significance. In this experiment, we conducted microbiota sequencing and analysis on gravesoil and mouse intestinal contents collected during both the winter and summer seasons and constructed a PMI estimation model using the Random Forest algorithm. The results showed that the MAE of the gut microbiota model in summer was 0.47 ± 0.26 d, R2 = 0.991, and the MAE of the gravesoil model in winter was 1.04 ± 0.22 d, R2 = 0.998. We propose that, in practical applications, it is advantageous to selectively build PMI estimation models based on seasonal variations. Additionally, through a combination of morphological observations, gravesoil microbiota sequencing results, and soil physicochemical data, we identified the time of cadaveric rupture for mouse cadavers, occurring at around days 24-27 in winter and days 6-9 in summer. This study not only confirms previous research findings but also introduces novel insights, contributing to the foundational knowledge necessary to advance the utilization of microbiota for PMI estimation.

PeerJVol. 12
Nanjing Agricultural University (CN), Ministry of Public Security of the People's Republic of China (CN), Central South University (CN), Institute of Forensic Science (CN)
Central South University, Fundamental Research Funds for the Central Universities
Life in Land
Openalex Percentile: Top 14%
Forensic Entomology and Diptera Studies
2.16
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