Short-term postmortem interval estimation by detection of apoptosis-related protein in skin.

Time-of-death extrapolation has always been one of the most important issues in forensic practice. For a complicated case in which a corpse is destroyed with little evidence, judging the time of death of the deceased is a major challenge, which also enables criminals to escape legal sanctions. To find a method to roughly judge the time of death of a corpse with only a small amount of skin tissue, in this study, we established an early death model by using mice; furthermore, the postmortem interval was estimated by determining the protein and mRNA levels of Bax and Bcl-2 in the skin. In this process, 0 h after death was used as the control group, and the expression levels of Bax and Caspase-3 reached the maximum value at 8-12 h, while Bcl-2, as an inhibitor of apoptosis protein, peaked after 24 h. The mRNA expression levels of related proteins in postmortem skin tissues were also different. The results of these data indicate that the protein and mRNA levels of Bax and Bcl-2 in the skin have potential application in early time-of-death estimation.

Changes in Microbial Communities Using Pigs as a Model for Postmortem Interval Estimation.

Microbial communities can undergo significant successional changes during decay and decomposition, potentially providing valuable insights for determining the postmortem interval (PMI). The microbiota produce various gases that cause cadaver bloating, and rupture releases nutrient-rich bodily fluids into the environment, altering the soil microbiota around the carcasses. In this study, we aimed to investigate the underlying principles governing the succession of microbial communities during the decomposition of pig carcasses and the soil beneath the carcasses. At early decay, the phylum Firmicutes and Bacteroidota were the most abundant in both the winter and summer pig rectum. However, Proteobacteria became the most abundant in the winter pig rectum in late decay. Using genus as a biomarker to estimate the PMI could get the MAE from 1.375 days to 2.478 days based on the RF model. The abundance of bacterial communities showed a decreasing trend with prolonged decomposition time. There were statistically significant differences in microbial diversity in the two periods (pre-rupture and post-rupture) of the four groups (WPG 0-8Dvs. WPG 16-40D, p < 0.0001; WPS 0-16Dvs. WPS 24-40D, p = 0.003; SPG 0D vs. SPG 8-40D, p = 0.0005; and SPS 0D vs. SPS 8-40D, p = 0.0208). Most of the biomarkers in the pre-rupture period belong to obligate anaerobes. In contrast, the biomarkers in the post-rupture period belong to aerobic bacteria. Furthermore, the genus Vagococcus shows a similar increase trend, whether in winter or summer. Together, these results suggest that microbial succession was predictable and can be developed into a forensic tool for estimating the PMI.

Research Progress on Microbial Community Succession in the Postmortem Interval Estimation.

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.

Estimation of Late Postmortem Interval: Where Do We Stand? A Literature Review.

Estimating time since death can be challenging for forensic experts, and is one of the most challenging activities concerning the forensic world. Various methods have been assessed to calculate the postmortem interval on dead bodies in different stages of decomposition and are currently widely used. Nowadays, the only well-recognized dating technique is carbon-14 radioisotope measurement, whereas other methods have been tested throughout the years involving different disciplines with different and sometimes not univocal results. Today, there is no precise and secure method to precisely determine time since death, and late postmortem interval estimation remains one of the most debated topics in forensic pathology. Many proposed methods have shown promising results, and it is desirable that with further studies some of them might become acknowledged techniques to resolve such a difficult and important challenge. The present review aims at presenting studies about the different techniques that have been tested in order to find a valuable method for estimating time since death for skeletal remains. By providing a comprehensive overview, the purpose of this work is to offer readers new perspectives on postmortem interval estimation and to improve current practice in the management of skeletal remains and decomposed bodies.

Exploring postmortem succession of rat intestinal microbiome for PMI based on machine learning algorithms and potential use for humans.

The microbial communities may undergo a meaningful successional change during the progress of decay and decomposition that could aid in determining the post-mortem interval (PMI). However, there are still challenges to applying microbiome-based evidence in law enforcement practice. In this study, we attempted to investigate the principles governing microbial community succession during decomposition of rat and human corpse, and explore their potential use for PMI of human cadavers. A controlled experiment was conducted to characterize temporal changes in microbial communities associated with rat corpses as they decomposed for 30 days. Obvious differences of microbial community structures were observed among different stages of decomposition, especially between decomposition of 0-7d and 9-30d. Thus, a two-layer model for PMI prediction was developed based on the succession of bacteria by combining classification and regression models using machine learning algorithms. Our results achieved 90.48% accuracy for discriminating groups of PMI 0-7d and 9-30d, and yielded a mean absolute error of 0.580d within 7d decomposition and 3.165d within 9-30d decomposition. Furthermore, samples from human cadavers were collected to gain the common succession of microbial community between rats and humans. Based on the 44 shared genera of rats and humans, a two-layer model of PMI was rebuilt to be applied for PMI prediction of human cadavers. Accurate estimates indicated a reproducible succession of gut microbes across rats and humans. Together these results suggest that microbial succession was predictable and can be developed into a forensic tool for estimating PMI.

Review of the current and potential use of biological and molecular methods for the estimation of the postmortem interval in animals and humans.

We provide here an overview of the state of applied techniques in the estimation of the early period of the postmortem interval (PMI). The biological methods included consist of body cooling, CSF potassium, body cooling combined with CSF potassium, and tissue autolysis. For each method, we present its application in human and veterinary medicine and provide current methodology, strengths, and weaknesses, as well as target areas for improvement. We examine current and future molecular methods as they pertain to DNA and primarily to messenger RNA degradation for the estimation of the PMI, as well as the use of RNA in aging wounds, aging blood stains, and the identification of body fluids. Various types of RNA have different lengths, structures, and functions in cells. These differences in RNAs determine various intrinsic properties, such as their half-lives in cells, and, hence, their decay rate as well as their unique use for specific forensic tests. Future applications and refinements of RNA-based techniques provide opportunities for the use of molecular methods in the estimation of PMI and other general forensic applications.

The Diversity of Forensic Entomofauna Associated With Decaying Chicken Liver in the Tropical Region of Kerala, India.

Forensic entomology To elucidate the time of death based on insect evidence, there are several studies on forensic entomology on life cycles, environmental factors, and feeding habitats of insects. However, there have not been any comprehensive studies on forensic entomology and its usage in forensic inquiry specific to the region, especially Kerala, India. The insect succession on decomposed animal matter plays an important role in estimating minimum postmortem intervals (mPMI). Objective The purpose of the study was to understand forensically important insect groups and their role in the decomposition process of dead decaying matter. The different decomposition stages of a corpse vary in attraction to necrophagous insects and the insect fauna depending on its prevailing conditions of decay. The decomposition is highly dependent on the exposition of animal matter and abiotic and biotic factors acting on it. The main objective of the present investigation was to identify the insect fauna associated with decaying chicken liver. The study also envisages comprising the diversity and abundance of insects between two different treatments of animal matter: in contact with soil and controlled conditions in a clean basin. Method The study was conducted for 45 days (until the total decomposition of the samples in both conditions) during the pre-monsoon months of April to May 2022 at Chalikadavu, Muvattupuzha, in the Ernakulam district, Kerala, India. The samples were however kept away from direct sunlight and rain to avoid the direct impact on the orienting fauna. The entomofauna found to be associated with the decaying animal matter was carefully collected from the site and stored in 70% isopropyl alcohol for preservation. The total number of insects was recorded along with the hours of maximum incidence, and samples were stored in plastic vials for further identification. Result In this study, we analyzed the activities of ants, mites, wasps, cockroaches, moths, beetles, and flies during the decomposition of decaying chicken liver. Among these insects, flies and beetles are two important arthropod communities associated with animal matter decomposition. We collected these foraging organisms for morpho-taxonomic identification. The decomposition stages among the two treatments could help to understand the variable factors in the decomposition of decaying corpse with special reference to the insect fauna acting on it. Conclusion We got 100 specimens comprising 28 species in 17 families from Blattidae, Coleoptera, Diptera, Hymenoptera, and Lepidoptera. Besides this, we identified two parasitic wasps with their host (dipteran pupa), which is helpful in postmortem interval (PMI) estimation. Our analysis showed an association between decay and the activity of carrion insects. The decomposition stages among the two treatments could help to understand the variable factors in the decomposition of a decaying corpse with special reference to the insect fauna acting upon it.

Research Progress on Microbial Community Succession in the Postmortem Interval Estimation / 法医学杂志

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.

Next-generation time of death estimation: combining surrogate model-based parameter optimization and numerical thermodynamics.

The postmortem interval (PMI), i.e. the time since death, plays a key role in forensic investigations, as it aids in the reconstruction of the timeline of events. Currently, the standard method for PMI estimation empirically correlates rectal temperatures and PMIs, frequently necessitating subjective correction factors. To address this shortcoming, numerical thermodynamic algorithms have recently been developed, providing rigorous methods to simulate postmortem body temperatures. Comparing these with measured body temperatures then allows non-subjective PMI determination. This approach, however, hinges on knowledge of two thermodynamic input parameters, which are often irretrievable in forensic practice: the ambient temperature prior to discovery of the body and the body temperature at the time of death (perimortem). Here, we overcome this critical limitation by combining numerical thermodynamic modelling with surrogate model-based parameter optimization. This hybrid computational framework predicts the two unknown parameters directly from the measured postmortem body temperatures. Moreover, by substantially reducing computation times (compared with conventional optimization algorithms), this powerful approach is uniquely suited for use directly at the crime scene. Crucially, we validated this method on deceased human bodies and achieved the lowest PMI estimation errors to date (0.18 h ± 0.77 h). Together, these aspects fundamentally expand the applicability of numerical thermodynamic PMI estimation.

Analysis of Postmortem Intestinal Microbiota Successional Patterns with Application in Postmortem Interval Estimation.

Microorganisms play a vital role in the decomposition of vertebrate remains in natural nutrient cycling, and the postmortem microbial succession patterns during decomposition remain unclear. The present study used hierarchical clustering based on Manhattan distances to analyze the similarities and differences among postmortem intestinal microbial succession patterns based on microbial 16S rDNA sequences in a mouse decomposition model. Based on the similarity, seven different classes of succession patterns were obtained. Generally, the normal intestinal flora in the cecum was gradually decreased with changes in the living conditions after death, while some facultative anaerobes and obligate anaerobes grew and multiplied upon oxygen consumption. Furthermore, a random forest regression model was developed to predict the postmortem interval based on the microbial succession trend dataset. The model demonstrated a mean absolute error of 20.01 h and a squared correlation coefficient of 0.95 during 15-day decomposition. Lactobacillus, Dubosiella, Enterococcus, and the Lachnospiraceae NK4A136 group were considered significant biomarkers for this model according to the ranked list. The present study explored microbial succession patterns in terms of relative abundances and variety, aiding in the prediction of postmortem intervals and offering some information on microbial behaviors in decomposition ecology.

Visualization of Literature Information on Postmortem Interval Estimation Indexed by CNKI Database from 1990 to 2020.

OBJECTIVES: To explore the development process of the postmortem interval (PMI) research in China from January 1990 to August 2020, research hotspots in different periods, authors and cooperation between institutions, and to provide a reference for the better development of PMI inference research through the visualization of the literature information of the PMI estimation research indexed in China National Knowledge Infrastructure (CNKI). METHODS: The information visualization analysis software CiteSpace 5.7.R1 was used to carry out big data analysis on hotspots, high-frequency keywords, authors, institutions and other information in the research literature on PMI inference from January 1990 to August 2020 indexed in CNKI. RESULTS: The peak time of publication of PMI was from 2006 to 2010 with 114 articles. In keyword co-occurrence network, the effective hot words were forensic entomology, DNA content analysis and some emerging words such as artificial intelligence and big data. In the cooperation network of institutions, the high-frequency institutions were mainly the scientific research institutions. The author cooperation network showed a trend of co-aggregation and multi-cooperation. CONCLUSIONS: With the development of science and technology, the research on PMI estimation based on traditional methods is mature and novel strategies are emerging. Big data and artificial intelligence combined with forensic science provide new research directions on PMI estimation.

New Advances, Challenges and Opportunities in Forensic Applications of Microbiomics.

The succession of microbiota is closely associated with several essential factors, including race, sex, health condition, lifestyle, postmortem interval, etc., and it has great potential application value in forensic medicine. This paper summarizes recent studies on the forensic applications of the microbiome, including individual identification, geographical feature identification, origin identification of the tissue or body fluid, and postmortem interval estimation, and introduces the current machine learning algorithms for microbiology research based on next-generation sequencing data. In addition, the current problems facing forensic microbiomics such as the extraction and preservation of samples, construction of standardization and database, ethical review and practical applicability are discussed. Future multi-omics studies are expected to explore micro ecosystems from a comprehensive and dynamic perspective, to promote the development of forensic microbiomics application.

New Advances, Challenges and Opportunities in Forensic Applications of Microbiomics / 法医学杂志

The succession of microbiota is closely associated with several essential factors, including race, sex, health condition, lifestyle, postmortem interval, etc., and it has great potential application value in forensic medicine. This paper summarizes recent studies on the forensic applications of the microbiome, including individual identification, geographical feature identification, origin identification of the tissue or body fluid, and postmortem interval estimation, and introduces the current machine learning algorithms for microbiology research based on next-generation sequencing data. In addition, the current problems facing forensic microbiomics such as the extraction and preservation of samples, construction of standardization and database, ethical review and practical applicability are discussed. Future multi-omics studies are expected to explore micro ecosystems from a comprehensive and dynamic perspective, to promote the development of forensic microbiomics application.

Visualization of Literature Information on Postmortem Interval Estimation Indexed by CNKI Database from 1990 to 2020 / 法医学杂志

OBJECTIVES@#To explore the development process of the postmortem interval (PMI) research in China from January 1990 to August 2020, research hotspots in different periods, authors and cooperation between institutions, and to provide a reference for the better development of PMI inference research through the visualization of the literature information of the PMI estimation research indexed in China National Knowledge Infrastructure (CNKI).@*METHODS@#The information visualization analysis software CiteSpace 5.7.R1 was used to carry out big data analysis on hotspots, high-frequency keywords, authors, institutions and other information in the research literature on PMI inference from January 1990 to August 2020 indexed in CNKI.@*RESULTS@#The peak time of publication of PMI was from 2006 to 2010 with 114 articles. In keyword co-occurrence network, the effective hot words were forensic entomology, DNA content analysis and some emerging words such as artificial intelligence and big data. In the cooperation network of institutions, the high-frequency institutions were mainly the scientific research institutions. The author cooperation network showed a trend of co-aggregation and multi-cooperation.@*CONCLUSIONS@#With the development of science and technology, the research on PMI estimation based on traditional methods is mature and novel strategies are emerging. Big data and artificial intelligence combined with forensic science provide new research directions on PMI estimation.

POSTMORTEM INTERVAL ESTIMATION BY THE METHOD OF WAVELET ANALYSIS OF STOKES-POLARIMETRIC MAPPING DATA OF HUMAN VITREOUS BODY LAYERS.

OBJECTIVE: The aim: To develop a set of forensic criteria for determining PMI on the basis of complex selective statistical data analysis of magnitude distributions of the wavelet-amplitude coefficients of VB polycrystalline films microscopic images. PATIENTS AND METHODS: Materials and methods: The object of study are polycrystalline films of VB, taken from 41 cadavers of both sexes aged from 37 to 79-year with pre-known time of death coming ranged from 3 to 36 h. Measuring the coordinate allocation meanings of parameters of polarization in the points of microscopic images was carried out at the location of the standard Stokes-polarimeter. RESULTS: Results: The magnitudes of statistical moments of the 1st-4th orders linearly vary within 36 hours. It was revealed that the data of time changes of the asymmetry and the excess are the most sensitive to necrotic changes in the polycrystalline structure of such samples. CONCLUSION: Conclusions: The scale-selective approach provides an increase in the range of sensitivity up to 36 h and increase the accuracy of the PMI estimation up to 45 min.

Life Cycle of Chrysomya rufifacies (Diptera: Calliphoridae) Under Semi-Controlled Laboratory Conditions.

Adult Calliphoridae flies, as well as their immature stages collected from carcasses, have been used as evidence in forensic investigations to estimate the postmortem interval (PMI), particularly those of the genus Chrysomya as it is one of the first genera to colonize a corpse. Chrysomya rufifacies (Macquart 1842), due to its appearance in cadaveric remains, plays a fundamental role in the study of forensic entomology. For this reason, we determined the biological cycle of C. rufifacies under semicontrolled laboratory conditions: uncontrolled average fluctuating temperature of 29. 76 ± 3. 22°C, uncontrolled average fluctuating humidity of 48. 91 ± 11.13%, and a controlled photoperiod of 12/12 (L/O). We established that the total development time from oviposition to adult emergence of C. rufifacies was 6. 5 d. The eggs took 12 h to hatch after oviposition. The complete larval stage took 60 h (instar 1 = 12 h, instar 2 = 12 h, instar 3 = 24 h, instar 3 post-feeding = 12 h). The pupa had a duration of 84 h. The species needed a total of 4642.8(±4.59) accumulated degree-hours (ADH) to complete its biological cycle.

Progress and Application of Entomological Evidence in Forensic Science.

ABSTRACT: Entomological evidence provides entry points and clues for cases detection, in terms of estimation of the postmortem interval （PMI）, and place and cause of death. In recent years, the feasibility of entomological evidence in practice has been proved by theories and cases. It especially plays an important role in the investigation of cases with unnatural death, no monitoring, and highly corrupt cadaver. However, there are still some key issues to be further studied and standardized before the application of entomological evidence to forensic practice, to improve the effect of entomological evidence in forensic investigation and trial. This paper retrospectively reviews key studies of the application of entomological evidence in forensic science, mainly including discussion of forensic entomology inspection standard, identification studies of sarcosaprophagous insect species, collection of sarcosaprophagous insect growth and succession data under different environments and forensic entomotoxicology. With the rapid development of information technology and biotechnology, applying artificial intelligence and whole genome sequencing technology in forensic entomology has become a new research direction, which can improve the application value and range of entomological evidence in forensic science.

Application of Sarcosaprophagous Insects to Estimate the Postmortem Interval in 11 Cases.

ABSTRACT: Objective To test the feasibility and accuracy of with sarcosaprophagous insects postmortem interval （PMI） estimation with sarcosaprophagous insects and provide references for estimation practice. Methods Eleven cases confirmed by the detection results, with complete entomological evidence were selected. The insect species, estimation results and true results involved in the cases were statistically analyzed and compared. Results Thirteen species of insects were found at the criminal scene, including Chrysomya megacephala （Fabricius）, Chrysomya rufifacies （Macquart）, Chrysomya nigripes （Aubertin）, Lucilia sericata （Meigen）, Hydrotaea spinigera Stein, Muscina stabulans （Fallén）, Sarcophagid （species were not identified）, Megaselia scalaris （Loew）, Hermetia illucens （Linnaeus）, Saprinus splendens （Paykull）, Creophilus maxillosus （Linnaeus）, Dermestes maculatus （De Geer） and Necrobia ruficollis （Fabricius）. The PMI of all eleven cases was within the range of estimated PMI. The estimated results of 72.73% cases were on the same day of the true results. Conclusion Sarcosaprophagous insects can estimate the PMI simply and conveniently. In cases where the PMI is within the time range of one generation of flies or beetles, the estimation results are relatively accurate. However, the estimation is less accurate when the PMI is beyond the time range.

Estimating Postmortem Interval Using Intestinal Microbiota Diversity Based on 16S rRNA High-throughput Sequencing Technology. / 基于16S rRNAé«˜é€šé‡æµ‹åºæŠ€æœ¯çš„è‚ é“èŒç¾¤å¤šæ ·æ€§æŽ¨æ–­æ­»äº¡æ—¶é—´.

OBJECTIVES: To explore the correlation between intestinal microbiota and postmortem interval(PMI) in rats by using 16S rRNA high-throughput sequencing technology. METHODS: Rats were killed by anesthesia and placed at 16 ℃, and DNA was extracted in caecum at 14 time points of 0, 1, 2, 3, 5, 7, 9, 12, 15, 18, 21, 24, 27 and 30 d after death. The 16S rRNA high-throughput sequencing technology was used to detect intestinal microbiota in rat cecal contents, and the results were used to analyze the rat intestinal microbiota diversity and differences. RESULTS: The total number of intestinal microbial communities did not change significantly within 30 days after death, but the diversity showed an upward trend. A total of 119 bacterial communities were significantly changed at 13 time points after death. The models for PMI estimation were established by using partial least squares (PLS) regression at all time points, before 9 days and after 12 days, reaching an R2 of 0.795, 0.767 and 0.445, respectively; and the root mean square errors (RMSEs) were 6.57, 1.96 and 5.37 d, respectively. CONCLUSIONS: Using 16S rRNA high-throughput sequencing technology, the composition and structure of intestinal microbiota changed significantly within 30 d after death. In addition, the established PLS regression model suggested that the PMI was highly correlated with intestinal microbiota composition, showing a certain time series change.

Application of Sarcosaprophagous Insects to Estimate the Postmortem Interval in 11 Cases / 法医学杂志

Objective To test the feasibility and accuracy of with sarcosaprophagous insects postmortem interval （PMI） estimation with sarcosaprophagous insects and provide references for estimation practice. Methods Eleven cases confirmed by the detection results, with complete entomological evidence were selected. The insect species, estimation results and true results involved in the cases were statistically analyzed and compared. Results Thirteen species of insects were found at the criminal scene, including Chrysomya megacephala （Fabricius）, Chrysomya rufifacies （Macquart）, Chrysomya nigripes （Aubertin）, Lucilia sericata （Meigen）, Hydrotaea spinigera Stein, Muscina stabulans （Fallén）, Sarcophagid （species were not identified）, Megaselia scalaris （Loew）, Hermetia illucens （Linnaeus）, Saprinus splendens （Paykull）, Creophilus maxillosus （Linnaeus）, Dermestes maculatus （De Geer） and Necrobia ruficollis （Fabricius）. The PMI of all eleven cases was within the range of estimated PMI. The estimated results of 72.73% cases were on the same day of the true results. Conclusion Sarcosaprophagous insects can estimate the PMI simply and conveniently. In cases where the PMI is within the time range of one generation of flies or beetles, the estimation results are relatively accurate. However, the estimation is less accurate when the PMI is beyond the time range.