Multimodal forensic biomarkers of death: gene expression, enzyme kinetics, and histology for PMI estimation

Background: Postmortem interval estimation (PMI) is an important goal in forensic medicine.Aim: to estimate PMI using a scoring method for postmortem changes; hypostasis, rigidity and corneal turbidity in burn cases, potassium (K + ) in vitreous humor (VH) and serum and compare accuracy of thanatochemistry and scoring method for postmortem changes in estimation of PMI.Methods: The study was conducted from May 2017 to May 2018, 50 burn cases where autopsy confirmed the cause of death as severe burns and another 50 control cases.Physical postmortem changes were assessed and numerically scored.The VH (K + ) and serum levels were measured.Data were statistically analyzed and linear regression analysis was used to obtain equations for calculation of PMI.Results: All studied variables in the present study were significantly correlated with PMI; highest correlation coefficient in control and burn groups was for VH (K + ) level, followed by corneal turbidity and serum K + then rigidity in burn groups, but in control groups the highest correlation coefficient was for VH (K + ) and serum levels, followed by rigidity then corneal turbidity and lastly hypostasis.All equations obtained from the present study can predict PMI but with different levels of accuracy. Conclusion:The scoring method for physical postmortem changes was proved to be more valuable in PMI estimation than thanatochemistry.

Estimation of early postmortem intervals by a multiple regression analysis using rectal temperature and non-temperature based postmortem changes

Background: Estimation of postmortem interval is considered one of the most important issues in forensic medicine.It aids the police investigation and help to know the time of the crime and its relation to the assailant.It also important in some civil problems as inheritance.There are multiple methods that used for estimaton of PMI as: rate of cooling after death, detection of supravital reactions, rate of development of hypostasis, rigor mortis, life cycle of insect and the decomposition changes that occur after death.Also usage of body fluids as chemical method for estimation of time passed since death shows great advances.Recently application of DNA and RNA in this field has done aiming at more accurate estimation of PMI.Aim of the work: Introducing and establishing the basic knowledge about Postmortem Interval estimation and focusing on new approaches for postmortem interval estimation.Conclusion: PMI estimation is the time between time of death and time of identification of corpse.It has a role in forensic medicine specially in crimes.It helps to aid the police in their investigation and reduce the number of assailant.PMI estimation is still depend on early and late postmortem changes as algor mortis, rigor mortis, hypostasis and putrefaction.But recently there are new methods as detection of new biomarkers, using of microscopic changes that occur after death in multiple organs with success of these trials was noted and a correlation between them and PMI was found.DNA and RNA also participate in estimating time since death by detection the rate of degradation and its relation with PMI. Definition of postmortem interval (PMI):Postmortem interval (PMI) means the time passed since death.Estimation of PMI is done through information that depend on estimation of sets of time: Time A and Time B .Time A is the time when the decent was last known to be alive, while time B is the time when the decent was found dead.The time since death is presented certainly between these times (between death and examination of the dead body) based on different factors as algor mortis ,rigor mortis , postmortem lividity and decomposition (Prahlow, 2010).There are multiple early and late postmortem changes that may aid in PMI estimation: Early postmortem changes as: 1-Supra vitality: supravital reactions are defined as reactions of tissue that occur on postmortem excitation.2-Algor Mortis is a term utilized to describe postmortem cooling of the body. 3-Postmortem lividity:It is one of the early signs that occurred after death.Circulatory arrest with loss of hydro static pressure lead to settling of blood in lower parts of the body under the effect of gravity, with discolouration of these parts of body.4-Rigor mortis:it's a chemical change resulting in stiffening of the body muscles following death due to changes in myofibrils of the muscle tissues.5-Dryness of skin and visible mucosa with development of tache noire (Perper, 2006).Late post mortem changes as:PDF created with pdfFactory Pro trial version www.pdffactory.com

Background: The estimation of postmortem interval (PMI) is one of the most important topics in forensic medicine research. We speculate that with an increased PMI, the computed tomography (CT) values of different tissues may show regular changes. Purpose: To use postmortem computed tomography (PMCT) to measure the myocardial CT value (unit: Hounsfield Unit, HU) of the heart to explore its pattern in postmortem change, and to discuss whether it can serve as a new parameter for PMI estimation. Methods: A total of 10 healthy adult New Zealand rabbits were selected and then put into a 20°C incubator after being sacrificed. Within 0–156 h after death, CT scans were performed every 12 h to detect changes in the myocardial CT value of the heart over time. Regression analysis was used to determine the relationship between the myocardial CT value of the heart and PMI. At the same time, HE and Masson were used to stain the cardiac tissue sections detected by PMCT at 0h, 48h and 156h, respectively. Results: During 0–156 h, the overall myocardial CT value showed a trend of first rising and then decreasing with the increase of PMI. The fitting regression equation was y = −2873.193 + 143.866x − 1.728x2 (x: myocardial CT value, unit: Hu; y: PMI, unit: h, R2 = 0.466, P < 0.05). During 48–156 h, the overall myocardial CT value decreased gradually with the increase of PMI. The fitting regression equation was y = −93.038 + 18.700x − 0.321x2 (x: myocardial CT value, unit: Hu; y: PMI, unit: h, R2 = 0.963, P < 0.001). The results of the morphological changes of the myocardial tissue structure after death showed that the myocardial cell structure was relatively complete at 0−48 hours after death; and the myocardial cell structure disappeared at 156 hours after death. Conclusions: Our results revealed evident postmortem changes in the myocardial CT value of the heart. Accordingly, measuring the myocardial CT value through PMCT shows promise for being used as a parameter for PMI estimation in forensic medicine and is worthy of further studies. The morphological changes of the myocardial tissue structure after death provide morphological basis for postmortem changes of tissue density, and further prove the reasons for the changes of CT value.

Accurate post-mortem interval (PMI) estimation is essential in forensic investigations. Although various methods for PMI determination have been developed, only an approximate estimation is still achievable, and an accurate PMI indication is still challenging. Therefore, in this study, we employed gas chromatography-mass spectrometry (GC-MS)-based metabolomics to assess post-mortem changes in porcine blood samples collected with and without the addition of anticoagulant (EDTA). Our study aimed to identify metabolites dependent on the EDTA addition and time (taking into account the biodiversity of the studied organism) and those that are time-dependent but resistant to the addition of an anticoagulant. The experiment was performed on blood samples collected from 16 animals (domestic pig, breed: Polish Large White), 8 with and 8 without EDTA addition. The moment of death (time 0) and 15 additional time points (from 3 to 168 h after death) were selected to examine changes in metabolites' levels in specific time intervals. We employed linear mixed models to study the relationship between metabolite intensities, time and presence of EDTA while accounting for the effect of individual pigs. We confirmed that the intensity of 16 metabolites (mainly amino acids) significantly depends on PMI and the presence of EDTA. However, the intensity of the ideal biomarker(s) for PMI estimation should be determined only by the time after death and not by external factors such as the presence of the anticoagulant agent. Thus, we identified 41 metabolites with time-dependent intensities that were not susceptible to EDTA presence. Finally, we assessed the performance of these metabolites in a PMI predictive model. Citraconic acid yielded one of the lowest errors in general PMI estimation (32.82 h). Moreover, similar errors were observed for samples with and without EDTA (33.32 h and 32.34 h, respectively). Although the small sample size and information leak in predictive modelling prevent drawing definite conclusions, citraconic acid shows potential as a robust PMI estimator.

Implication of High-mobility group box-1 and skin post mortem changes in estimation of time passed since death: Animal and human study.

Estimation of postmortem interval using thanatochemistry and postmortem changes

Circular RNAs (circRNAs) are conserved, abundant, stable, and specifically expressed in mammals. The postmortem interval (PMI) estimation is crucial in forensic medicine, particularly for case investigation and civil action. CircRNAs may serve as ideal PMI biomarkers. However, no research has explored PMI estimation in the brain using circRNAs. The total RNA, including circRNA, was sampled from mouse brain tissues at multiple temperatures (4℃, 25℃, and 35℃). The semi-quantitative reverse transcription (RT)-PCR and real-time quantitative PCR (RT-qPCR) were used to test the postmortem degradation levels at different PMIs. As a result, we found circFat3 is highly and specifically expressed in mouse brain tissue, with postmortem levels significantly correlated with PMI across multiple temperatures. In addition, mt-co1 and 28 S rRNA demonstrated stability under various temperature conditions, supporting their use as reliable reference genes for PMI models. Moreover, the error rates showed that the circFat3/28S rRNA model was more accurate at 4℃. The circFat3/mt-co1 and circFat3/28S rRNA models provided slightly better predictions for short-term and long-term PMI, respectively at 25℃, while the circFat3/mt-co1 model was more accurate at 35℃. The combined application of the two reference genes was beneficial primarily for long-term PMI estimation. Furthermore, the validation results confirmed that these models were more accurate for long-term PMI estimation. Thus, our mathematical models were constructed at multiple temperatures based on circFat3 and these two reference genes. Taken together, this is the first study to identify circRNA circFat3 as a novel biomarker that may serve as a complementary tool for PMI estimation.

Serial estimation of gene expression of cardiac troponin I (cTnI) and autophagy gene HMGB1 to determine postmortem interval

Application of metabolomic methods to forensic studies may expand the limits of the post-mortem interval (PMI) estimation, and improve the accuracy of the estimation. To this end, it is important to determine which tissue is the most suitable for analysis, and which compounds are the most promising candidates for PMI estimation. This work is aimed at the comparison of human serum, aqueous humor (AH), and vitreous humor (VH) as perspective tissues for metabolomic-based PMI estimation, at the determination of most promising PMI biomarkers, and at the development of method of PMI estimation based on the measurement of concentrations of PMI biomarkers. Quantitative metabolomic profiling of samples of the human serum, AH, and VH taken at different PMIs has been performed with the use of NMR spectroscopy. It is found that the metabolomic changes in anatomically isolated ocular fluids are slower and smoother than that in blood. A good positive time correlation (Pearson coefficient r > 0.5) was observed for several metabolites, including hypoxanthine, choline, creatine, betaine, glutamate, and glycine. A model for PMI estimation based on concentrations of several metabolites in AH and VH is proposed. The obtained results demonstrate that the metabolomic analysis of AH and VH is more suitable for the PMI estimation than that of serum. The compounds with good positive time correlation can be considered as potential PMI biomarkers.

To present recent advances in forensic sciences with omics sciences and new biomarkers for postmortem interval (PMI) estimation. We conducted a narrative review screening PubMed and Scopus databases in the last 10 years (2015-2025) with the following keywords in the title and abstract: "postmortem interval" OR "post-mortem interval" AND "proteomics" OR "proteomic" OR "metabolomics" OR "metabolomic" OR "transcriptomic" OR transcriptomics" OR microRNA" OR "microRNAs" OR "lipidomic". Conventional methods of postmortem interval estimation are presented. Some of the most important studies and molecular techniques in genomics, transcriptomics, proteomics, metabolomics, lipidomics, old and new biomarkers for postmortem interval estimation are summarized. Single-omics or multi-omics, critical issues like data reproducibility and interpretation, judicial validity according to Daubert standard and ethical issues of PMI research are discussed. Postmortem interval estimation continues to be one of the most disputed issues of forensic medicine. Conventional methods for PMI estimation still offer a solid bench for practical means. As single-omics and multi-omics research continues to progress, we will likely discover new biomarkers and innovative techniques. Efforts will focus on identifying biomarkers that can deliver reliable and predictable outcomes, thereby facilitating their general acceptance and admissibility in legal proceedings.

Post-mortem interval (PMI) estimation is one of the most challenging tasks in forensic practice. Therefore, for PMI estimation, attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy coupled with chemometrics was utilized to monitor the biochemical changes in rat liver tissues with increasing PMI at 4°C, 20°C and 30°C. First, principal component analysis (PCA) revealed that the spectral points were distributed from right to left with increasing PMI along PC–1, and this trend was more obvious at the higher temperature (20°C and 30°C) groups. Second, a partial least squares (PLS) regression model was successfully constructed with the 30°C group, with a root mean square error of cross-validation (RMSECV) of 6.9 h (R2 = 0.92) and a root mean square error of prediction (RMSEP) of 4.6 h (R2 = 0.96). Lastly, a partial least squares-discriminant analysis (PLS-DA) classification model was established in the 20°C group and demonstrated a complete separation of the spectra among the three classes (0–24 h, 48–96 h and 120–168 h) with 90% accuracy (not-assigned rate: 11%). In conclusion, these results demonstrated that ATR-FTIR spectroscopy combined with chemometrics could serve as a convenient and reliable tool for studying PMI estimation.

Background and aim: Accurate estimation of the postmortem interval (PMI) remains a critical challenge in forensic investigations due to the complex interplay of decompositional processes. Histo-taphonomy, the microscopic examination of postmortem tissue changes, offers a potential approach for PMI determination. This study investigates the histological changes in porcine liver and kidney tissues over a controlled postmortem timeline to assess their forensic applicability. Methodology: A healthy female pig (Sus scrofa) was euthanized, and liver and kidney tissues were harvested immediately postmortem. Samples were collected at 0, 24, 36, 48, 60, 72, 84, and 96 hours postmortem. The tissues were fixed in 10% buffered formalin, processed using standard histological techniques, and stained with hematoxylin and eosin (H&E) for microscopic examination. Results: Histological analysis revealed progressive tissue degradation over time. Kidney tissues initially showed mild structural alterations, followed by significant nuclear changes and architectural disintegration. Liver tissues exhibited early-stage fibrosis and progressive hepatocyte necrosis. The observed cellular degeneration followed a time-dependent pattern, with both organs demonstrating severe autolysis by 96 hours postmortem. Conclusion: The findings suggest that histo-taphonomy provides a structured framework for PMI estimation based on organ-specific decomposition patterns. Given the anatomical and physiological similarities between porcine and human tissues, this model could serve as a valuable tool in forensic investigations. Future studies should incorporate environmental variables and molecular markers to enhance the accuracy and applicability of histological PMI estimation in forensic casework.

Purpose: The postmortem interval (PMI) evaluation is one of priorities while performing a forensic medical examination of corpse. To date, there is lack of information of morphological postmortem changes of some internal organs. Considering the persistent need to develop the method for a precise assessment of PMI, postmortem changes in these potentially informative organs were evaluated. The aim of study was to analyze morphological postmortem changes in prostate and uterus. Materials and Methods: histological samples of 40 prostate tissues and 40 uterus (n=80) from corpses of deceased aged 18-75 years. Only cases with known time of death were included to study, the time of death was taken from police reports. Exclusion criteria were cases of violent death, cases of death with massive blood loss, tumors of studied internal organs, cases when diagnosis was not made by a forensic medical examiner. The PMI of studied cases ranged from 1 to 6 days. Histological slides were made with a staining by hematoxylin and eosin, x200 magnification, using Olympus ВХ41 and Olympus ВХ46 microscopes, Olympus SC50 camera. Postmortem morphological changes were evaluated by a calculation of blank spaces percentage in microscopical structures using a JS-based program. Connection between PMI and morphological changes was calculated by the Spearman’s rank correlation. Results: the average percentage of blank spaces in uterus tissues was smaller than in prostate tissues (1,99 and 9,65 relatively). The slower growing of blank spaces was in uterus. In prostate samples, a notable increase of blank spaces was observed between 48 and 72 hours after the death. After this period, the increase slowed down and then an increase was observed again between 120 and 144 hours after the death. In uterus samples, a slight acceleration observed between 72 and 120 hours after the death and then slowing down between 120 and 144 hours after the death. Blank spaces in evaluated histological slides were increasing directly proportional to the PMI, a statistically significant interconnection was defined (p < 0.05). Conclusions: The morphological postmortem changes in prostate and uterus were developing at certain time frames. Blank spaces percentage, in studied histological slides, were increasing directly proportional to the PMI increase, a statistically significant interconnection was defined. Therefore, the results of study show the possibility of the evaluation of a postmortem time interval by assessing such morphological changes in these organs, which could be used in forensic medical cases.

The postmortem interval is estimated based on physical, biochemical, and morphologic changes in dead bodies, scene investigation findings, and judicial investigation findings. Many factors affect the onset and the course of the postmortem changes. There is no established method for accurate estimation of the postmortem interval, especially with regard to putrefied dead bodies. Aiming to determine the consistency and the variation of postmortem interval estimations in cases with various putrefaction degrees by forensic medicine assistants and specialists from different centers, a prospective study was undertaken. A form containing data about the time, environment, and geographical location where the cases were found, along with their postmortem changes was mailed to 110 forensic medicine assistants and specialists from different centers, who were also asked to note their postmortem interval estimations. About half of the forms were returned. Those postmortem interval estimations made based on the information included in the forms, showed great variability between the participants, and in only 6 cases a consistency exceeding 50% was found between the participants and the autopsy teams. It is not possible to estimate the postmortem interval in a standard way by using only the postmortem changes of putrefied bodies. Therefore, especially in the cases involving putrefied bodies, in addition to the postmortem changes, factors such as environmental conditions, the scene, and judicial investigation findings should be taken into consideration.