College of Forensic Medicine, Kunming Medical University, Kunming 650500, China.
Institute of Criminal Science and Technology, Yunnan Provincial Public Security Department, Kunming 650228, China.
Fa Yi Xue Za Zhi. 2023 Aug 25;39(4):399-405. doi: 10.12116/j.issn.1004-5619.2022.420606.
The postmortem interval (PMI) estimation is a key and difficult point in the practice of forensic medicine, and forensic scientists at home and abroad have been searching for objective, quantifiable and accurate methods of PMI estimation. With the development and combination of high-throughput sequencing technology and artificial intelligence technology, the establishment of PMI model based on the succession of the microbial community on corpses has become a research focus in the field of forensic medicine. This paper reviews the technical methods, research applications and influencing factors of microbial community in PMI estimation explored by using high-throughput sequencing technology, to provide a reference for the related research on the use of microbial community to estimate PMI.
死后间隔时间（PMI）估计是法医学实践中的一个关键和难点，国内外法医科学家一直在寻找客观、可量化和准确的 PMI 估计方法。随着高通量测序技术和人工智能技术的发展和结合，基于尸体上微生物群落演替建立 PMI 模型已成为法医学领域的研究热点。本文综述了高通量测序技术在 PMI 估计中探索微生物群落的技术方法、研究应用及影响因素，为利用微生物群落估计 PMI 的相关研究提供参考。
