Estimating the Postmortem Interval of Carcasses in the Water Using the Carrion Insect, Brain Tissue RNA, Bacterial Biofilm, and Algae

Potential Role of mRNA in Estimating Postmortem Interval: A Systematic Review

Although the postmortem interval estimation still represents one of the main goals of forensic medicine, there are still several limitations that weigh on the methods most used for its determination: for this reason, even today, precisely estimating the postmortem interval remains one of the most important challenges in the forensic pathology field. To try to overcome these limitations, in recent years, numerous studies have been conducted on the potential use of the mRNA degradation time for reaching a more precise post mortem interval (PMI) estimation. An evidence-based systematic review of the literature has been conducted to evaluate the state of the art of the knowledge focusing on the potential correlation between mRNA degradation and PMI estimation. The research has been performed using the electronic databases PubMed and Scopus. The analysis conducted made it possible to confirm the potential applicability of mRNA for reaching a more precise PMI estimation. The analysis of the results highlighted the usefulness of some mRNAs, such as β-actin and glyceraldehyde-3-phosphate dehydrogenase (GAPDH) mRNA, especially in short time frames, within a few hours or days of death. The matrices on which these analyses were conducted were also analyzed, resulting in less exposure to the external environment, including the heart, brain, and dental pulp. The major limitations were also reported, including the short time intervals analyzed in most of the articles, the lack of mathematical models, and the failure to report the error rate between the mRNA degradation time and PMI. Given the still small number of published articles, the lack of globally recognized standardized methods, and the numerous techniques used to evaluate the mRNA degradation times, numerous and larger studies are still necessary to reach more solid and shared evidence.

Advances in artificial intelligence-based microbiome for PMI estimation

Postmortem interval (PMI) estimation has always been a major challenge in forensic science. Conventional methods for predicting PMI are based on postmortem phenomena, metabolite or biochemical changes, and insect succession. Because postmortem microbial succession follows a certain temporal regularity, the microbiome has been shown to be a potentially effective tool for PMI estimation in the last decade. Recently, artificial intelligence (AI) technologies shed new lights on forensic medicine through analyzing big data, establishing prediction models, assisting in decision-making, etc. With the application of next-generation sequencing (NGS) and AI techniques, it is possible for forensic practitioners to improve the dataset of microbial communities and obtain detailed information on the inventory of specific ecosystems, quantifications of community diversity, descriptions of their ecological function, and even their application in legal medicine. This review describes the postmortem succession of the microbiome in cadavers and their surroundings, and summarizes the application, advantages, problems, and future strategies of AI-based microbiome analysis for PMI estimation.