Early Postmortem Interval Research Articles

Exploring the Post Mortem Interval (PMI) Estimation Model by circRNA circRnf169 in Mouse Liver Tissue

Estimating the post mortem interval (PMI) is a crucial and contentious issue in forensic research, particularly in criminal cases. Traditional methods for PMI estimation are limited by constraints and inaccuracies. Circular RNA (circRNA), formed through exon or intron looping to create a complete circular structure without a 5′ end cap and a 3′ poly(A) tail, exhibits exceptional stability, abundance, and tissue-specific characteristics that make it potentially valuable for PMI estimation. However, research on the exploration or application of circRNA in PMI estimation has been limited. This study aims to investigate the correlation between circRNA and PMI. In this study, liver tissue samples were collected from mice at six different time points at 4 °C, 18 °C, 25 °C, and 35 °C, respectively. The reference gene 28S rRNA and the biomarker circRnf169 were successfully screened. Quantitative PCR was employed to examine the correlation between circRnf169 levels and PMI. At 4 °C, the level of circRnf169 decreased with prolonged PMI, whereas at 18 °C, 25 °C, and 35 °C, the circRnf169 RNA was degraded rapidly, indicating that circRnf169 is suitable for PMI estimation at low temperatures or early PMI. These findings suggest the establishment of mathematical model for early PMI based on circRnf169 using liver tissue, which may serve as a reliable marker. Further research is required in order to develop more markers in mice and/or to validate these mathematical models in human samples.

An assessment of the Henssge method for forensic death time estimation in the early post-mortem interval

BackgroundTime-since-death (TSD) diagnostics are crucial in forensic medical casework. The compound method by Henssge and Madea, which combines temperature and non-temperature-based techniques, is widely used to estimate TSD. This study aims to validate the predictive ability of this method in a cohort of 76 deceased individuals with known times of death (TOD).MethodsA convenience sample of 76 deceased individuals was examined at the Institute of Legal Medicine, University Medical Center Hamburg-Eppendorf. The study included individuals who died at the hospital and those with sudden death in public. Exclusion criteria included age under 18, known infection or sepsis, polytrauma, bleeding, and hyperthermia. The TSD interval was calculated using the Deathtime software.ResultsThe overall agreement between the actual TOD and the 95% prediction interval for the TSD was 36.8% (95% CI: 26.1 to 48.7). Warm-stored corpses showed a higher agreement (61.9% [95% CI: 38.4 to 81.9]) compared to cold-stored corpses (27.3% [95% CI: 16.1 to 41.0]). Factors such as body mass index (BMI) and body surface area (BSA) were found to influence the odds of agreement. Assuming a plausible range of ambient temperatures between death and admission improved the agreement in cold-stored cases.ConclusionThe study found low to moderate agreement between the actual TOD and the 95% prediction interval using the Henssge method. Incorporating BMI and BSA could improve the predictive accuracy of TSD estimations. Further research with larger sample sizes and external validation is recommended to refine the model.

Post-mortem Interval estimate based on dental pulp: A histomorphology approach.

Estimating the post-mortem interval (PMI) of human remains based on the histomorphology of dental pulp parameters is promising, but available evidence is scarce and sometimes contradictory without a scientific model. The aim of the study is to characterise the histomorphological changes of dental pulp associated with the decomposition of human remains by a qualitative and quantitative approach. The main aim is to establish a correlation based on post-mortem (PM) dental pulp histomorphology and the PMI, and whether pulp degradation could be an available medico-legal tool for PMI estimation beyond the first week after death (late PMI). The eligible sample consisted of 27 sound teeth from 16 healthy patients aged 16 to 72 years due to orthodontic or oral surgery treatment, to create PMI's simulating the death of the subject as the time elapsed from tooth avulsion. Data collected from patients (sex, date of birth, tooth position, date and hour of the avulsion, date and hour of pulp extraction) were anonymised in accordance with the requirements of Faculty of Dental Medicine of the University of Lisbon. The sample was divided into 9 groups of 3 teeth according to different PMI sets from T0 (baseline) up to 2 weeks (T0, 7, 12, 24, 36, 48, and 72 hours, 1 and 2 weeks). All the dental samples were stored at room temperature up to the time of pulp extraction and then prepared with haematoxylin and eosin stain. High-resolution microscopy was performed to obtain histological images. An operator performed the qualitative evaluation of blood vessels, collagen fibres, and the extra-cellular matrix (ECM) in PM pulps and measured the variation in cells/nuclei density by counting 6 different ROIs (Regions of Interest) for each pulp manually and automatically (quantitative analysis). Qualitative results showed that the degeneration of dental pulp appears 7 hours after death but histological changes in vessels, fibres, and ECM in PM dental pulp are characterised by high variability, consequently it is not possible to generalise the results for early PMIs. Quantitative measurements proved that cell count cannot be standardised due to the presence of superimposed layers of cells and nuclei fragmentation. Odontoblasts did not demonstrate evidence of cellular or nuclear lysis up to 14 PM suggesting their applicability in late PMIs. Future research will focus on late PMIs and different techniques of tooth preparation.

An experimental study to estimate the early postmortem interval based on the degradation of lncRNAs in rat brain tissue

To study the degradation of lncRNAs in EPMI in rat brain tissue, this study provides a new direction for the estimation of EPMI. LncRNA high-throughput sequencing was performed on the brain tissues of hemorrhagic shock model rats at 0 h and 24 h, and the target lncRNAs were screened. Samples at 0, 1, 3, 6, 12, 18 and 24 h after death were collected, and miRNA-9 and miRNA-125b were used as reference genes. The relative expression levels of lncRNAs at each PMI were detected by RT–qPCR, and a functional model involving lncRNAs and EPMI was established. Samples were collected at 6, 9, 15, and 21 h after death for functional model verification. The expression of several lncRNAs decreased with the prolongation of EPMI, and the mathematical model established by several lncRNA indices exhibited good fit. The verification results of the multi-index joint function model are significantly better than those of the single-index function model, and the established model is more practical. There is a linear relationship between lncRNAs and EPMI, and the multi-index function model is significantly better than the single-index function model, which is important for EPMI inference in forensic pathology practice.

Proteomic Characterization of Changes in Mouse Brain Cortex Protein Expression at Different Post-Mortem Intervals: A Preliminary Study for Forensic Biomarker Identification.

Accuracy in the evaluation of death-induced tissue degradation for thanato-chronological purposes is strictly dependent on the condition of the biological source as well as on the precision of post-mortem interval (PMI) estimation. Thus, the optimization of tissue handling and identification of sensitive post-mortem biomarkers could help establish a timeline for post-mortem events. To this aim, we investigated the proteome changes in cortex samples of 6-week-old female SAMR1 mice over a post-mortem time course. After death, brain tissue was removed immediately (T0), and after 4, 8, 12, 24, and 32 h, four mice were used for each time period, and animals were maintained at 4 °C until brain removal. Dissected tissues were frozen at -80 °C until processed. Proteomic analysis, performed on samples related to early and late PMIs (<24 h and >24 h post-mortem, respectively) showed protein level changes as compared to T0 samples, with a remarkable increase in Calpain11 in the early PMI, as well as in Caspases 7 and 8 together with Gasdermin 3 in late PMI. These findings were confirmed by LIFT mass spectrometry technology and western blot analysis and, although requiring further investigation in other biological samples, suggest that these proteins could be considered as putative biomarkers of different PMIs.

Estimation of Post-mortem Interval Based on Livor Mortis using a Colorimeter in Thai Populations

OBJECTIVE Livor mortis is a helpful and widely used method of estimating postmortem interval (PMI) in Thailand. This study aimed to investigate the value of a colorimeter as a tool for estimating the PMI. METHODS The color of livor mortis and control skin in 80 cadavers whose PMI was within 12 hours was measured by a colorimeter. The L* (brightness), a*b* (chroma and hue), and ∆E* values were compared to the control skin values. Statistical analysis was performed to determine the relationship between PMI and skin color before and after application of a specific pressure. RESULTS The results showed that colorimetric parameters were only weakly correlated with the PMI. An univariable analysis of ∆E* values was performed and showed good discriminatory power, with an area under the ROC curve of 0.82. The recommended cut-off value of ∆E* was 14 for the discrimination between early PMI (less than 6 hours) and late PMI (6-12 hours), in which the sensitivity and specificity were 72.5% and 80%. CONCLUSIONS The findings in this study reinforce the utility of colorimetric measurements in PMI estimation. With additional study and a larger sample size, the estimation of PMI could be established for general use in forensic practice.

Integrating Temperature Data with Other Forensic Methods for Time Since Death Estimation

To reliably calculate the time since death is most important for investigating officers in all unnatural deathcases. Reliability of the study can be obtained only when potential influencing factors are considered during the calculation of time since death. One of the methods used for calculating the time since death is based on the cooling of the body. Cooling of the body is influenced by various internal as well as external factors. There are various body temperature-based methods in practice (Henssge’s rectal nomogram, Henssge’s brain nomogram, and Baccino’s both interval and global formulae based on ear temperature) to estimate the post-mortem interval (PMI). The rectum has been traditionally used to determine the central core temperature after death, though the external auditory canal has been proposed as an alternative site. According to published research, techniques based on ear temperature are just as trustworthy as those based on rectal temperature for determining the early PMI and may be employed as rapid, easy, and non-invasive procedures on the scene. It is vital to keep in mind that other aspects such as rigor mortis, lividity, and decomposition must also be taken into account to achieve a more accurate estimate, even if calculating the time since death based on the cooling of the corpse might be informative.Aim: The goal of this study is to thoroughly examine some of the available approaches, compare the accuracy of the results, and determine which method is more accurate (reliable) at estimating the time of death.Methods: It was decided to evaluate some of the earlier research’ published works from different publications and databases. A digital database was searched. Picks were made at random from the studies that were thought to be pertinent to the present goal.Result: Therefore, in addition to the body’s cooling rate, other factors like post-mortem lividity, rigor mortis,chemical changes in the body, and mechanical and electrical excitability of the skeletal muscles, are crucial for a more accurate prediction of the time of death.Conclusion: It is usually advisable to take into account additional factors in addition to the algor mortis-based one when determining the time since death so that a more exact and trustworthy time of death can assist the investigating officer in more precisely resolving medico-legal matters.

Post-mortem CT radiomics for the prediction of time since death.

Post-mortem interval (PMI) estimation has long been relying on sequential post-mortem changes on the body as a function of extrinsic, intrinsic, and environmental factors. Such factors are difficult to account for in complicated death scenes; thus, PMI estimation can be compromised. Herein, we aimed to evaluate the use of post-mortem CT (PMCT) radiomics for the differentiation between early and late PMI. Consecutive whole-body PMCT examinations performed between 2016 and 2021 were retrospectively included (n = 120), excluding corpses without an accurately reported PMI (n = 23). Radiomics data were extracted from liver and pancreas tissue and randomly split into training and validation sets (70:30%). Following data preprocessing, significant features were selected (Boruta selection) and three XGBoost classifiers were built (liver, pancreas, combined) to differentiate between early (< 12h) and late (> 12h) PMI. Classifier performance was assessed with receiver operating characteristics (ROC) curves and areas under the curves (AUC), which were compared by bootstrapping. A total of 97 PMCTs were included, representing individuals (23 females and 74 males) with a mean age of 47.1 ± 23.38years. The combined model achieved the highest AUC reaching 75% (95%CI 58.4-91.6%) (p = 0.03 compared to liver and p = 0.18 compared to pancreas). The liver-based and pancreas-based XGBoost models achieved AUCs of 53.6% (95%CI 34.8-72.3%) and 64.3% (95%CI 46.7-81.9%) respectively (p > 0.05 for the comparison between liver- and pancreas-based models). The use of radiomics analysis on PMCT examinations differentiated early from late PMI, unveiling a novel image-based method with important repercussions in forensic casework. This paper introduces the employment of radiomics in forensic diagnosis by presenting an effective automated alternative method of estimating post-mortem interval from targeted tissues, thus paving the way for improvement in speed and quality of forensic investigations. • A combined liver-pancreas radiomics model differentiated early from late post-mortem intervals (using a 12-h threshold) with an area under the curve of 75% (95%CI 58.4-91.6%). • XGBoost models based on liver-only or pancreas-only radiomics demonstrated inferior performance to the combined model in predicting the post-mortem interval.

A miRNome analysis at the early postmortem interval.

The postmortem interval (PMI) is the time elapsing since the death of an individual until the body is examined. Different molecules have been analyzed to better estimate the PMI with variable results. The miRNAs draw attention in the forensic field to estimate the PMI as they can better support degradation. In the present work, we analyzed the miRNome at early PMI in rats' skeletal muscle using the Affymetrix GeneChip™ miRNA 4.0 microarrays. We found 156 dysregulated miRNAs in rats' skeletal muscle at 24 h of PMI, out of which 84 were downregulated, and 72 upregulated. The miRNA most significantly downregulated was miR-139-5p (FC = -160, p = 9.97 × 10-11), while the most upregulated was rno-miR-92b-5p (FC = 241.18, p = 2.39 × 10-6). Regarding the targets of these dysregulated miRNAs, the rno-miR-125b-5p and rno-miR-138-5p were the miRNAs with more mRNA targets. The mRNA targets that we found in the present study participate in several biological processes such as interleukin secretion regulation, translation regulation, cell growth, or low oxygen response. In addition, we found a downregulation of SIRT1 mRNA and an upregulation of TGFBR2 mRNA at 24 h of PMI. These results suggest there is an active participation of miRNAs at early PMI which could be further explored to identify potential biomarkers for PMI estimation.

A pilot study investigating early postmortem interval of rats based on ambient temperature and postmortem interval-related metabolites in blood.

Estimation of the postmortem interval (PMI), especially the early PMI, plays a key role in forensic practice. Although several studies based on metabolomics approaches have presented significant findings for PMI estimation, most did not examine the effects of ambient temperature. In this study, gas chromatography-mass spectrometry (GC‒MS)‒based metabolomics was adopted to explore the changes in metabolites in the cardiac blood of suffocated rats at various ambient temperatures (5°C, 15°C, 25°C, and 35°C) from 0 to 24h after death. Isoleucine, alanine, proline, valine, glycerol, glycerol phosphate, xanthine, and hypoxanthine were found to contribute to PMI in all temperature groups. Hypoxanthine and isoleucine were chosen to establish estimation models (equations) with an interpolation function using PMI as the dependent variable (f(x, y)), relative intensity as the independent variable x, and temperature as the independent variable y. Thereafter, these two models were validated with predictive samples and shown to have potential predictive ability. The findings indicate that isoleucine, alanine, proline, valine, glycerol, glycerol phosphate, xanthine, and hypoxanthine may be significant for PMI estimation at various ambient temperatures. Furthermore, a method to determine PMI based on ambient temperature and PMI-related metabolites was explored, which may provide a basis for future studies and practical applications.

Do bone elasticity and postmortem interval affect forensic fractographic analyses?

Forensic fractographic features of bone reliably establish crack propagation in perimortem injuries. We investigated if similar fracture surface features characterize postmortem fractures. Experimentally induced peri- and postmortem fractures were used to assess if fractographic features vary as bone elasticity decreases during the postmortem interval (PMI). Thirty-seven unembalmed, defleshed human femoral shafts from males and females aged 33-81 years were fractured at varying PMIs with a drop test frame using a three-point bending setup and recorded with a high-speed camera. Vital statistics, cause of death, PMI length, temperature, humidity, collagen percentage, water loss, fracture energy, and fractography scores were recorded for each sample. Results showed that fractographic features associated with perimortem fractures were expressed in PMIs up to 40,600 accumulated degree hours (ADH), or 60 warm weather days. Hackle was the most consistently expressed feature, occurring in all fractures regardless of ADH. The most variable characteristics were wake features (78.4%) and arrest ridges (70.3%). Collagen percentage did not correlate strongly with ADH (r=-0.04, p=0.81); however, there was a strong significant correlation between ADH and water loss (r=0.74, p < 0.001). Multinomial logistic regression showed no association between fractographic feature expression and ADH or collagen percentage. In conclusion, forensic fractographic features reliably determine initiation and directionality of crack propagation in experimentally induced PMIs up to 40,600 ADH, demonstrating the utility of this method into the recent postmortem interval. This expression of reliable fractographic features throughout the early PMI intimates these characteristics may not be useful standalone features for discerning peri- versus postmortem fractures.

Estimation of Early Postmortem Interval from Long Noncoding RNA Gene Expression in the Incised Cutaneous Wound: An Experimental Study.

The assessment of alteration of postmortem RNA expression has forensic significance in estimating postmortem interval. To evaluate wound healing progression and the effect of different postmortem intervals, histopathological changes, immunohistochemical matrix metalloproteinase-9 (MMP-9) expression, and long noncoding fatty acid oxidation (lncFAO), RNA expression was assessed in the incised cutaneous wound model. A full-thickness cutaneous wound was inflicted on 75 rats. All 15 rats were sacrificed at different post-infliction intervals (0, 2, 4, 8 and 10 days), and the cutaneous wounds (n = 5) were excised at different postmortem intervals (0, 5, and 24 h after euthanasia). The maximal inflammatory healing stage was detected at day 4 post-infliction, while near complete healing, thick mature collagen deposition was detected at day 10 post-infliction. LncFAO expression was significantly over-expressed with increasing wound age. MMP-9 was detectable on injury day with continuous elevation until 8 days post-wounding, which later decreased. Although histopathological and immunohistochemical examinations within 24 h postmortem did not show any remarkable changes, lncFAO RNA expression showed a significant negative correlation with hours passed since death. The combined use of histopathological changes, immunohistochemical expression of MMP-9, and molecular expression of lncFAO could be appropriate in wound dating verification. Among these factors, lncFAO could be a reliable indicator in postmortem interval estimation.

The Influence of Eyelid Position and Environmental Conditions on the Corneal Changes in Early Postmortem Interval: A Prospective, Multicentric OCT Study.

In the current study, using portable optical coherence tomography, we evaluated 46 corneas of 23 individuals in a multicenter setting during the first 17 h after death. Twenty-three eyes were kept open, and twenty three were kept closed. Furthermore, the experiment was carried out for 12 samples in summer and 11 in winter. Our data show that postmortem corneal alterations largely depend on the phenomena of dehydration (in particular in open eyes) and swelling of the stroma in closed eyes, probably due in the first phase to hypoxia/anoxia and subsequently to the passage by osmosis of the aqueous humor from the anterior chamber to the corneal tissue. Our findings could have significant repercussions in forensic pathology for estimating the postmortem interval and transplantation to optimize the conservation of the tissue before the explant.

Correlation between Hounsfield Unit values of blood in CT on immediate postmortem CT after cardiopulmonary resuscitation and antemortem hemoglobin levels

The Hounsfield Unit (HU) values of blood in computed tomography (CT) on a live CT scan and hemoglobin levels have a positive linear correlation. The purpose of this study was to elucidate whether the same correlation could be observed on postmortem CT (PMCT) immediately after failed cardiopulmonary resuscitation (CPR) to determine its potential in diagnosing antemortem anemia. We enrolled 200 patients with nontraumatic cardiopulmonary arrest (103 men, 97 women) who could not be resuscitated after being transferred to our hospital. A blood count was taken at the start of the infusion, as well as an immediate PMCT. The CT values of regions of interest in the ascending aorta were measured at three levels. Pearson's correlation coefficient (R) between the HU values of blood in CT and hemoglobin was calculated. Results The maximum infusion volume during CPR was 500 ml in 169 cases and 1000 ml in 31 cases. There was a positive linear correlation between the HU values of blood in CT on immediate PMCT and hemoglobin at the time of initiation of infusion (R = 0.74). A strong correlation was observed between the HU values of blood in CT on immediate PMCT after CPR within the infusion range of 1000 ml and the antemortem hemoglobin levels, proposing the possibility of diagnosing antemortem anemia at least in a very early postmortem interval.

Systematic Review on Post-Mortem Protein Alterations: Analysis of Experimental Models and Evaluation of Potential Biomarkers of Time of Death.

Estimating the post-mortem interval (PMI) is a very complex issue due to numerous variables that may affect the calculation. Several authors have investigated the quantitative and qualitative variations of protein expression on post-mortem biological samples in certain time intervals, both in animals and in humans. However, the literature data are very numerous and often inhomogeneous, with different models, tissues and proteins evaluated, such that the practical application of these methods is limited to date. The aim of this paper was to offer an organic view of the state of the art about post-mortem protein alterations for the calculation of PMI through the analysis of the various experimental models proposed. The purpose was to investigate the validity of some proteins as “molecular clocks” candidates, focusing on the evidence obtained in the early, intermediate and late post-mortem interval. This study demonstrates how the study of post-mortem protein alterations may be useful for estimating the PMI, although there are still technical limits, especially in the experimental models performed on humans. We suggest a protocol to homogenize the study of future experimental models, with a view to the next concrete application of these methods also at the crime scene.

Postmortem Electrical Conductivity Changes of Dicentrarchus labrax Skeletal Muscle: Root Mean Square (RMS) Parameter in Estimating Time since Death.

Simple SummaryThe estimation of postmortem interval (PMI) still poses a major challenge for pathologists worldwide, making the search for new and more accurate technologies to assist in PMI estimation worthy of growing scientific interest. This study aimed to explore for the first time the use of an oscilloscope coupled with a signal generator, as innovative technology, to evaluate changes in the electrical conductivity of skeletal muscle of sea bass specimens during the early postmortem interval, to find an accurate, quantitative parameter useful in PMI estimation. The use of the oscilloscope, especially for the RMS measured parameter, has been shown here as a promising technology for studying dielectric muscle properties during the early postmortem interval, with the advantage of being a rapid, non-destructive, and inexpensive method.Electric impedance spectroscopy techniques have been widely employed to study basic biological processes, and recently explored to estimate postmortem interval (PMI). However, the most-relevant parameter to approximate PMI has not been recognized so far. This study investigated electrical conductivity changes in muscle of 18 sea bass specimens, maintained at different room temperatures (15.0 °C; 20.0 °C; 25.0 °C), during a 24 h postmortem period using an oscilloscope coupled with a signal generator, as innovative technology. The root mean square (RMS) was selected among all measured parameters, and recorded every 15 min for 24 h after death. The RMS(t) time series for each animal were collected and statistically analyzed using MATLAB®. A similar trend in RMS values was observed in all animals over the 24 h study period. After a short period, during which the RMS signal decreased, an increasing trend of the signal was recorded for all fish until it reached a peak. Subsequently, the RMS value gradually decreased over time. A strong linear correlation was observed among the time series, confirming that the above time-behaviour holds for all animals. The time at which maximum value is reached strongly depended on the room temperature during the experiments, ranging from 6 h in fish kept at 25.0 °C to 14 h in animals kept at 15.0 °C. The use of the oscilloscope has proven to be a promising technology in the study of electrical muscle properties during the early postmortem interval, with the advantage of being a fast, non-destructive, and inexpensive method, although more studies will be needed to validate this technology before moving to real-time field investigations.

Histobiochemical changes in early postmortem interval in liver, pancreas, skin and kidney of adult male albino rats

Histobiochemical changes in early postmortem interval in liver, pancreas, skin and kidney of adult male albino rats

Inferring Postmortem Submersion Interval in Rats Found in Water Based on Vitreous Humor Metabolites.

The metabolomics technique of LC-MS/MS combined with data analysis was used to detect changes and differences in metabolic profiles in the vitreous humor of early rat carcasses found in water, and to explore the feasibility of its use for early postmortem submersion interval (PMSI) estimation and the cause of death determination. The experimental model was established in natural lake water with 100 SD rats were randomly divided into a drowning group (n=50) and a postmortem (CO2 suffocation) immediately submersion group (n=50). Vitreous humor was extracted from 10 rats in each group at 0, 6, 12, 18 and 24 h postmortem for metabolomics analyses, of which 8 were used as the training set to build the model, and 2 were used as test set. PCA and PLS multivariate statistical analysis were performed to explore the differences in metabolic profiles among PMSI and causes of death in the training set samples. Then random forest (RF) algorithm was used to screen several biomarkers to establish a model. PCA and PLS analysis showed that the metabolic profiles had time regularity, but no differences were found among different causes of death. Thirteen small molecule biomarkers with good temporal correlation were selected by RF algorithm. A simple PMSI estimation model was constructed based on this indicator set, and the data of the test samples showed the mean absolute error (MAE) of the model was 0.847 h. The 13 metabolic markers screened in the vitreous humor of rat corpses in water had good correlations with the early PMSI. The simplified PMSI estimation model constructed by RF can be used to estimate the PMSI. Additionally, the metabolic profiles of vitreous humor cannot be used for early identification of cause of death in water carcasses.

A preliminary study on early postmortem submersion interval (PMSI) estimation and cause-of-death discrimination based on nontargeted metabolomics and machine learning algorithms.

Postmortem submersion interval (PMSI) estimation and cause-of-death discrimination of corpses in water have long been challenges in forensic practice. Recently, many studies have linked postmortem metabolic changes with PMI extension, providing a potential strategy for estimating PMSI using the metabolome. Additionally, there is a lack of potential indicators with high sensitivity and specificity for drowning identification. In the present study, we profiled the untargeted metabolome of blood samples from drowning and postmortem submersion rats at different PMSIs within 24 h by liquid chromatography-tandem mass spectrometry (LC-MS/MS). A total of 601 metabolites were detected. Four different machine learning algorithms, including random forest (RF), partial least squares (PLS), support vector machine (SVM), and neural network (NN), were used to compare the efficiency of the machine learning methods. Nineteen metabolites with obvious temporal regularity were selected as candidate biomarkers according to "IncNodePurity." Robust models were built with these biomarkers, which yielded a mean absolute error of 1.067 h. Additionally, 36 other metabolites were identified to build the classifier model for discriminating drowning and postmortem submersion (AUC = 1, accuracy = 95%). Our results demonstrated the potential application of metabolomics combined with machine learning in PMSI estimation and cause-of-death discrimination.

Estimation of time of death using brain parenchyma attenuation in post mortem computed tomography of brain – In malaysian setting

• Brain is first organ to undergo decomposition after death occurs and can be used to estimate early PMI. • Overall average attenuation of brain show linear positive correlation with early PMI. • Attenuation measurement at centrum semiovale, high convexity and parietal lobe can be grouped together and its average attenuation shows good correlation with early PMI. • In regards to one area of brain attenuation that corresponds best to PMI is at high convexity level. To measure brain attenuation of Post Mortem Computed Tomography (PMCT) of brain and to determine the correlation between the Post-Mortem Interval (PMI) and brain parenchymal attenuation value. This was a retrospective cross sectional study conducted at Institut Perubatan Forensik Negara (IPFN) of Hospital Kuala Lumpur from April 2019 to April 2020. Total of 160 PMCT brain samples that met inclusion criteria were examined. A measurement cursor with fixed size was used to measure the brain parenchymal attenuation in Hounsfield Unit (HU). The values were then averaged and plotted against the PMI to assess the correlation. Each brain location average attenuation as well as average attenuation of grouped locations were plotted against PMI to examine if any particular site of the brain had almost similar correlation or trend as the overall attenuation. There was positive linear correlation between the brain parenchymal attenuation changes and PMI, where there was progressive increase in HU values within the time limit of PMCT at our center, in which the longest stood at 31 hours. The best-fit model for the correlation involved the average attenuation of Centrum Semiovale-High Convexity-Parietal (CSHCP) levels. There was positive linear correlation between PMI and brain parenchymal attenuation and within the CSHCP levels, High Convexity was the single location that was most representative of this group, hence can be used to estimate PMI of a brain particularly in early decomposition state.