Estimation Of Postmortem Interval Research Articles

Analysis of Changes in Electrolytes Level in Serum After Death and Its Correlation With Postmortem Interval.

Background Apropos estimation of postmortem interval is an important and difficult task for forensic pathologists. In routine practice, postmortem interval is deduced by conventional or physical methods such as early and late postmortem changes, which are subjective methods and prone to errors. Estimating time since death by thanatochemistry is a more objective method as compared to routine conventional or physical methods. The present study is an attempt to analyze the changes in electrolytes level in serum after death and its correlation with postmortem interval. Materials and methods Blood samples were taken from the deceased who were brought for amedicolegal autopsy. The concentration of electrolytes, mainly sodium, potassium, calcium, and phosphate, was evaluated in the serum. The deceased were grouped on the basis of time since death. Log-transferred regression analysis was done to establish the correlation of the concentration ofelectrolytes with time since death and regression formulas were derived for each parameter. Results Sodium concentration in serum showed a negative correlation with time since death. Potassium, calcium, and phosphate showed a positive correlation with time since death. No statistically significant difference exists in the concentration of electrolytes between males and females. No significant difference was observed in the electrolytes concentration between the age groups. Conclusion Considering the findings of this study, we infer that the concentration of electrolytes, primarily sodium, potassium, and phosphates, in the blood can be used to approximate the amount of time that has passed since death. Nonetheless, until 48 hours after death, electrolyte levels in the blood can be considered for the calculation of the postmortem interval.

Influence of the ear temperature range on the measurement bias between an infrared thermometer and a reference probe for post-mortem interval determination

The aim of this study was to assess the influence of the post-mortem outer ear temperature (OET) on the measurement bias previously observed for short post-mortem intervals (PMI) between a commercially available infrared thermometer and a reference metal probe thermometer. To that end, 100 refrigerated bodies were added to our initial cohort to investigate lower OET. In contrast to our previous findings, a very good concordance was noted between both methods. There was still an overall underestimation of ear temperatures with the infrared thermometer, but the average bias was significantly reduced compared to that observed in the initial cohort (1.47 °C for the right ear and 1.32 °C for the left ear). Most importantly, this bias progressively decreased as the OET decreased, becoming negligible for OET lower than 20 °C. These results are in agreement with literature data regarding these temperature ranges. The discrepancy observed with our previous observations may be due to the technical characteristics of the infrared thermometers. The lower the temperatures measured, the more the measurements approach the lower limit of the measuring range of the device and tend to give constant values, resulting in a smaller underestimation of the measurements. Further research is needed to assess the interest of integrating in the already validated OET-based formulae a variable dependent on the temperature measured with the infrared thermometer, to eventually allow infrared thermometry to be used for PMI estimation in forensic practice.

Post-mortem interval estimation using miRNAs of road traffic accident cases: A forensic molecular approach

In forensic examination accurate estimation of post-mortem interval (PMI) is a challenging task, particularly in the advanced stages of decomposition. The existing methods (algor mortis, livor mortis, rigor mortis, putrefaction etc) used for estimating PMI rely on analyzing the physical, biochemical, and metabolic changes that occur in the corpse after death. While these methods have shown some level of effectiveness in estimating PMI during the early stages of decomposition, accurate estimation becomes increasingly challenging during the later stages of putrefaction when the body undergoes significant changes. Recently, microRNA (miRNA) profiling due to its relatively small size and stability has emerged as a promising tool in several areas of forensics. This study demonstrates the potential of miRNA for PMI estimation in advanced stages of death. In this study, miRNA-195, miRNA-206, and miRNA-378 were selected as target miRNAs and miRNA-1 as reference miRNA. Left ventricle tissue (5 g) of the heart from 20 forensic autopsies of traffic accident victims (18–32 years) were collected and processed. The samples were held at room temperature for eight different time intervals (12, 24, 48, 72, 96, 120, 168 and 196 h), and RNA was extracted from all the samples using Trizol-based RNA isolation protocol, followed by cDNA synthesis and amplification with commercially available specific miRNA probes in Real-Time PCR (RT-PCR), Ct was calculated. The result showed that miRNAs were associated with PMI. Over time, there were substantial changes in the Ct values of all three miRNAs, with significant reductions observed at 196 h compared to 12 h. miRNA-206 demonstrated significant changes at multiple time intervals, while miRNA-1 remained stable for up to 196 h and thus holds caas an endogenous marker. In conclusion, miRNA has the potential to serve as a valuable tool for estimating PMI, especially during the advanced stages of decomposition, when used in conjunction with established techniques. However, further validation of the study is required to obtain more accurate estimates of PMI.

New application of ATR-FTIR spectroscopy for postmortem interval estimation based on puparia of the sarcosaprophagous fly Chrysomya megacephala (Diptera: Calliphoridae)

Postmortem interval (PMI) estimation remains a challenge in forensic science due to the lack of efficient methods. In recent years, the preadult development of sarcosaprophagous flies has been recognized as a reliable method to estimate the minimum postmortem interval (PMImin). However, this method may fail once the PMI exceeds the duration of preadult development (i.e. after eclosion), leaving puparia of sarcosaprophagous flies as the only evidence for the estimation of the PMI at the crime scene. Fourier transform infrared (FTIR) spectroscopy with attenuated total reflectance (ATR) accessory was used in this study to collect comprehensive biochemical information from puparia of the sarcosaprophagous fly Chrysomya megacephala (Fabricius) (Diptera, Calliphoridae) at different time after eclosion (TAE). We established the partial least square (PLS) regression model using the acquired spectral dataset. The prediction results of the PLS regression model showed that R2CV of the internal cross-validation (calibration dataset) was 0.864 with RMSECV = 3.711 d and R2P of the prediction dataset was 0.909 with RMSEP = 3.045 d. The RMSEP/RMSECV value was 0.82 in our PLS regression model. Our results indicate that the TAE of puparia are highly predictable, which is valuable for the estimation of long-term PMImin.

Morphological changes and protein degradation during the decomposition process of pig cadavers placed outdoors or in tents—a pilot study

The delimitation of the postmortem interval (PMI) is of utmost importance in forensic science. It is especially difficult to determine the PMI in advanced decomposition stages and/or when dead bodies are found under uncommon circumstances, such as tents, or other (semi-) enclosed environments. In such cases, especially when insect access is restricted, morphological assessment of body decomposition is one of the remaining approaches for delimitation of the PMI. However, as this method allows only vague statements/indications about the PMI, it is required to develop new and more reliable methods. One of the most important candidates is the biochemical analysis of protein degradation. In this regard, it has been demonstrated that specific skeletal muscle protein degradation patterns characterize certain time points postmortem and thus can be used as markers for PMI estimation. In order to test this method in different micro-environments, a pilot study using ten pig carcasses was conducted in summer in Northern Germany. The cadavers were openly placed outside (freely accessible for insects), as well as enclosed in tents nearby, and left to decompose to investigate decomposition processes over a time course of 10 days. Muscle samples of the M. biceps femoris were collected on a regular basis and processed via SDS-PAGE and degradation patterns of selected proteins identified by Western blotting. In addition, morphological changes of the cadavers during decomposition were assessed using the total body score (TBS). Results showed that postmortem protein degradation patterns are largely consistent between treatment groups (open field versus tents) despite major morphological differences in the decomposition rate. This field study provides evidence that muscle protein degradation is mostly unaffected by different levels of exposure, making it a sufficient candidate for PMI delimitation under various circumstances.

Postmortem Interval Estimation Using Protein Chip Technology Combined with Multivariate Analysis Methods.

To estimate postmortem interval (PMI) by analyzing the protein changes in skeletal muscle tissues with the protein chip technology combined with multivariate analysis methods. Rats were sacrificed for cervical dislocation and placed at 16 ℃. Water-soluble proteins in skeletal muscles were extracted at 10 time points (0 d, 1 d, 2 d, 3 d, 4 d, 5 d, 6 d, 7 d, 8 d and 9 d) after death. Protein expression profile data with relative molecular mass of 14 000-230 000 were obtained. Principal component analysis (PCA) and orthogonal partial least squares (OPLS) were used for data analysis. Fisher discriminant model and back propagation (BP) neural network model were constructed to classify and preliminarily estimate the PMI. In addition, the protein expression profiles data of human skeletal muscles at different time points after death were collected, and the relationship between them and PMI was analyzed by heat map and cluster analysis. The protein peak of rat skeletal muscle changed with PMI. The result of PCA combined with OPLS discriminant analysis showed statistical significance in groups with different time points (P<0.05) except 6 d, 7 d and 8 d after death. By Fisher discriminant analysis, the accuracy of internal cross-validation was 71.4% and the accuracy of external validation was 66.7%. The BP neural network model classification and preliminary estimation results showed the accuracy of internal cross-validation was 98.2%, and the accuracy of external validation was 95.8%. There was a significant difference in protein expression between 4 d and 25 h after death by the cluster analysis of the human skeletal muscle samples. The protein chip technology can quickly, accurately and repeatedly obtain water-soluble protein expression profiles in rats' and human skeletal muscles with the relative molecular mass of 14 000-230 000 at different time points postmortem. The establishment of multiple PMI estimation models based on multivariate analysis can provide a new idea and method for PMI estimation.

Evidence of two mitochondrial lineages and genetic variability in forensically important Lucilia eximia (Diptera: Calliphoridae) in Colombia.

Lucilia eximia (Wiedemann, 1819) (Diptera: Calliphoridae) is a blowfly with medical and forensic importance that shows genetic and color variation, however, these variations have not justified the description of new species. But in forensic entomology an accurate identification of species and subpopulations is crucial. We explored the genetic variation of L. eximia from eight localities, in five natural regions in Colombia using two mitochondrial fragments, including the standard locus for insect identification COI and the Cytb-tRNA-Ser-ND1 region. We found significant differentiation at COI and Cytb-tRNA-Ser-ND1 level, characterizing two lineages and revealing a deep and significant genetic split. High values of FST and genetic distances supported the two lineages. The origin of the divergence of L. eximia remains to discover. Examining whether the lineages have diverse ecological and biological behaviors could be a significant impact on the use of L. eximia in forensic and medical science. Our results could have relevant implications for the use of post-mortem interval estimation based on insect evidence, as well as our sequences improve the database used in DNA-based methods for identifying forensically important flies.

Partners in Postmortem Interval Estimation: X-ray Diffraction and Fourier Transform Spectroscopy.

The postmortem interval (PMI) is difficult to estimate in later stages of decomposition. There is therefore a need to develop reliable methodologies to estimate late PMI. This study aims to assess whether there is a correlation between changes in the mineral composition of human teeth and the estimation of PMI. X-ray diffraction (XRD) and attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy techniques were performed to address this challenge. Forty healthy human teeth obtained from odontological clinics were stored at different times (0, 10, 25, 50 years; N = 10/group). XRD and ATR-FTIR parameters related to the structure and composition of teeth were studied. Our results showed that the crystallinity index, crystal size index, mineral-to-organic matrix ratio (M/M) and carbonate/phosphate ratio (C/P) had the strongest association with PMI. For larger PMIs, there was a significant increase in crystallinity, crystal size and M/M ratio, while the C/P ratio showed a specific decrease with increasing PMI. According to our results, the parameters of crystallinity, crystal size, M/M ratio and C/P ratio can be considered highly accurate in determining a PMI of 10 years of data; crystallinity and mineral maturity can be considered useful in determining a PMI of 25 years; and crystallinity and mineral maturity can be considered highly accurate in determining a PMI of 50 years. A particular XRD index was identified as the most suitable parameter to estimate PMI: crystallinity. The joint use of XRD and ATR-FTIR analyses could be a promising alternative for dating human teeth.

Quantifying microcracks on fractured bone surfaces – Potential use in forensic anthropology

Bone fracture surface morphology (FSM) can provide valuable information on the cause of failure in forensic and archaeological applications and it depends primarily on three factors, the loading conditions (like strain rate), the ambient conditions (wet or dry bone material) and the quality of bone material itself. The quality of bone material evidently changes in taphonomy as a result of the decomposition process and that in turn is expected to affect FSM. Porcine bones were fractured by a standardised impact during the course of soft tissue decomposition, at 28-day intervals, over 140 days (equivalent to 638 cooling degree days). Measurements of the associated microcracks on the fractured cortical bone surfaces indicated a progressive increase in mean length during decomposition from around 180 μm–375 μm. The morphology of these microcracks also altered, from multiple intersecting microcracks emanating from a central point at 0–28 cumulative cooling degree days, to longer linear cracks appearing to track lamellae as soft tissue decomposition progressed. The implications of these findings are that taphonomic changes of bone may offer the real possibility of distinguishing perimortem and taphonomic damage and also provide a new surrogate parameter for estimation of post-mortem interval (PMI) in forensics.

Trends in forensic microbiology: From classical methods to deep learning.

Forensic microbiology has been widely used in the diagnosis of causes and manner of death, identification of individuals, detection of crime locations, and estimation of postmortem interval. However, the traditional method, microbial culture, has low efficiency, high consumption, and a low degree of quantitative analysis. With the development of high-throughput sequencing technology, advanced bioinformatics, and fast-evolving artificial intelligence, numerous machine learning models, such as RF, SVM, ANN, DNN, regression, PLS, ANOSIM, and ANOVA, have been established with the advancement of the microbiome and metagenomic studies. Recently, deep learning models, including the convolutional neural network (CNN) model and CNN-derived models, improve the accuracy of forensic prognosis using object detection techniques in microorganism image analysis. This review summarizes the application and development of forensic microbiology, as well as the research progress of machine learning (ML) and deep learning (DL) based on microbial genome sequencing and microbial images, and provided a future outlook on forensic microbiology.

Estimating the intra-puparial period of Hydrotaea spinigera (Stein,1910) (Diptera: Muscidae) with morphological and gene expression changes

Hydrotaea spinigera (Stein, 1910) (Diptera: Muscidae) is a forensically important sarcosaprophagous species widely distributed throughout the Oriental and Australasian regions. At the advanced decomposition stage or the skeletonize stage, the immature stages of H. spinigera, especially the pupae, can still be found in large quantities and could be used as important indicators to estimate the minimum postmortem interval (PMImin). However, there have been no studies on the intra-puparial period of this species. Herein, we studied morphological and differential gene expression changes during the intra-puparial development of H. spinigera, aiming to accurately estimate the intra-puparial age of H. spinigera. The intra-puparial morphological changes of H. spinigera were observed at seven constant temperatures ranging from 16 °C to 34 °C and divided into 12 sub-stages. Structures that could be used to estimate the intra-puparial age, such as compound eyes, mouthparts, antennae, thorax, legs, wings, and abdomen, were observed in detail, and the developmental process of each structure was divided into 5 to 10 stages. The time range of each sub-stage, or when a structure appeared, was recorded. For the gene expression section, the most suitable reference genes were screened by geNorm, NormFinder, BestKeeper, and ΔCt methods. Based on the selected reference genes, real-time quantitative PCR (RT qPCR) was used to detect the expression changes of the white and hsp90 genes with developmental time at 19 °C, 25 °C, and 31 °C. Results showed that the trend of hsp90 gene expression under different temperatures was not consistent, while white genes exhibited regular changes during development, and could thus be used for age estimation of H. spinigera. This study provides an important basis for forensic entomology to use morphological and differential gene expression for estimating the age of H. spinigera during the intra-puparial period. Moreover, the combination of the two methods can produce a more accurate minimum postmortem interval (PMImin) estimate compared to when each method is used separately.

Mummification in a forensic context: an observational study of taphonomic changes and the post-mortem interval in an indoor setting

The objective of this study was to evaluate the presence of mummification in an indoor setting, with an emphasis on the forensic perspective. A dataset of 102 forensic autopsy cases was assessed for distribution of desiccation of skin and soft tissue (i.e., subcutaneous fat and musculature) and for moist decompositional (i.e., putrefactive) changes. Further, possible correlation with the post-mortem interval (PMI) was evaluated, as well as the effects of clothing coverage of the body. The results indicated that yellow to orange parchment-like desiccated skin was found at significantly shorter PMIs than reddish brown to black leathery desiccated skin, even when soft tissue desiccation was included in the comparative analysis. Clothing appeared to have a significant decelerating effect on the extent of desiccation on the legs, but findings in regard to whole body or torso/arms were inconclusive. A large variation in PMIs was evident as regards fully desiccated skin (PMI 18–217 days), indicating difficulties in PMI estimation due to a variable repressive effect on the decompositional process per se in an indoor setting. For the specific case in forensic practice, no definite conclusion can be drawn from the observed desiccation changes to the PMI. One way forward might be creating a systematic and standardized method for describing different desiccation types, as well as other cooccurring decompositional changes and how they relate to the PMI, as a foundation for a future quantification model.

Temperature-Dependent Development of Nitidula rufipes (Linnaeus, 1767) (Coleoptera: Nitidulidae) and Its Significance in Estimating Minimum Postmortem Interval.

Coleoptera, including the family Nitidulidae, are valuable for estimating long-term postmortem intervals in the late stage of body decomposition. This study showed that, under seven constant temperatures of 16, 19, 22, 25, 28, 31, and 34 °C, the developmental durations of Nitidula rufipes (Linnaeus, 1767) from oviposition to eclosion were 71.0 ± 4.4, 52.9 ± 4.1, 40.1 ± 3.4, 30.1 ± 2.1, 24.2 ± 2.0, 21.0 ±2.3, and 20.8 ± 2.4 days, respectively. The morphological indexes of body length, the widths of the head capsules, and the distance between the urogomphi of the larvae were measured in vivo. The regression model between larval body length and developmental durations was simulated for larval aging, and the head capsule width and the distance between the urogomphi at different instars were cluster-analyzed for instar discrimination. Based on the developmental durations, larval body length and thermal summation data were obtained, and the isomorphen diagram, isomegalen diagram, linear thermal summation models, and curvilinear Optim SSI models were established. The lower developmental threshold and thermal summation constant of N. rufipes evaluated by the linear thermal summation models were 9.65 ± 0.62 °C and 471.40 ± 25.46 degree days, respectively. The lower developmental thresholds, intrinsic optimum temperature, and upper lethal developmental threshold obtained by Optim SSI models were 10.12, 24.15, and 36.00 °C, respectively. The study of the immature stages of N. rufipes can provide preliminary basic developmental data for the estimation of minimum postmortem interval (PMImin). However, more extensive studies are needed on the effects of constant and fluctuating temperatures on the development of N. rufipes.

Oral Microbial Identity: A Potential Tool for Forensic Science

Microbial forensics is a feld that uses scientifc methods to analyze the evidence of bioterrorism, bio crimes, hoaxes, or the unintentional release of a biological agent or microbial toxin to determine who is to blame. It is now possible to characterize microorganisms for various human forensic applications, including human identifcation, body fluid characterization, postmortem interval estimation, and bio crimes involving the tracking of infectious agents. Big applause to technological advancements, remarkably massively parallel sequencing and bioinformatics. The oral microbiome contains microbiota markers that vary between individuals, emphasizing the possibility that it is highly individualized and perhaps even particular to each person. As a result, the oral microbial evidence found at crime scenes may lead to new information. This comprehensive review will discuss the state of the art of using the oral microbiome as a signature to conclude in the forensics sector.

Precision of the Abaxis VetScan VS2 for postmortem biochemical analysis of delphinid vitreous humor

AbstractBiochemical analysis of vitreous humor has several forensic applications, including toxicology, estimation of the postmortem interval, and as proxy for select antemortem serum analytes. Estimation of postmortem interval from vitreous humor analytes such as potassium has potential to be a valuable forensic tool for marine mammal strandings, as time of death is essential to provide spatial and temporal context for anthropogenic interactions. The Abaxis VetScan VS2 (VetScan) chemistry analyzer is inexpensive, compact, and requires low sample volume (100 μl), making it ideal for organizations with limited resources and limited samples. This pilot study compared accuracy of the Vetscan on delphinid serum/plasma (n = 7) to the Beckman Coulter AU480, validated the precision of the Vetscan for biochemical analysis of delphinid vitreous humor using the described sample processing protocol, and assessed analyte stability at room temperature in delphinid vitreous humor. Pooled samples (n = 12) of delphinid vitreous humor were serially analyzed and the between‐run and within‐run coefficient of variation of the VetScan was acceptable for most analytes tested but was not for creatinine, total bilirubin, amylase, and alanine aminotransferase. These results demonstrated the precision of the VetScan for the analysis of glucose, albumin, globulin, total protein, urea nitrogen, sodium, potassium, calcium, and phosphorus in delphinid vitreous humor.

Next generation forensic taphonomy: Automation for experimental, field-based research

Determining the post-mortem interval (PMI) is often a critical goal in forensic casework. Consequently, the discipline of forensic taphonomy has involved considerable research efforts towards achieving this goal, with substantial strides made in the past 40 years. Importantly, quantification of decompositional data (and the models derived from them) and standardisation in experimental protocols are being increasingly recognised as key components of this drive. However, despite the discipline’s best efforts, significant challenges remain. Still lacking are standardisation of many core components of experimental design, forensic realism in experimental design, true quantitative measures of the progression of decay, and high-resolution data. Without these critical elements, large-scale, synthesised multi-biogeographically representative datasets – necessary for building comprehensive models of decay to precisely estimate PMI – remain elusive. To address these limitations, we propose the automation of taphonomic data collection. We present the world’s first reported fully automated, remotely operable forensic taphonomic data collection system, inclusive of technical design details. Through laboratory testing and field deployments, the apparatus substantially reduced the cost of actualistic (field-based) forensic taphonomic data collection, improved data resolution, and provided for more forensically realistic experimental deployments and simultaneous multi-biogeographic experiments. We argue that this device represents a quantum leap in experimental methodology in this field, paving the way for the next generation of forensic taphonomic research and, we hope, attainment of the elusive goal of precise estimation of PMI.

Initial laboratory validation of temperature development models for Necrodes littoralis L. (Staphylinidae: Silphinae)

Development models of necrophagous insects are applied in forensic entomology for post-mortem interval estimation. Such estimates may be used as scientific evidence in legal investigations. For this reason, it is important that the models are valid and that the expert witness is aware of their limitations. Necrodes littoralis L. (Staphylinidae: Silphinae) is a necrophagous beetle species that frequently colonizes human cadavers. Temperature models of development for the Central European population of these beetles were recently published. In this article, we present results of the laboratory validation study for these models. Errors of beetle age estimation differed significantly between the models. Thermal summation models yielded the most accurate estimates, and the isomegalen diagram least accurate estimates. Errors of the beetle age estimation varied across beetle developmental stages and rearing temperatures. In general, most development models of N. littoralis were satisfactorily accurate in estimating beetle age under laboratory conditions; therefore, the study provides initial evidence to support their validity in forensic cases.

PMI estimation through metabolomics and potassium analysis on animal vitreous humour

IntroductionThe estimation of post-mortem interval (PMI) remains a major challenge in forensic science. Most of the proposed approaches lack the reliability required to meet the rigorous forensic standards.ObjectivesWe applied 1H NMR metabolomics to estimate PMI on ovine vitreous humour comparing the results with the actual scientific gold standard, namely vitreous potassium concentrations.MethodsVitreous humour samples were collected in a time frame ranging from 6 to 86 h after death. Experiments were performed by using 1H NMR metabolomics and ion capillary analysis. Data were submitted to multivariate statistical data analysis.ResultsA multivariate calibration model was built to estimate PMI based on 47 vitreous humour samples. The model was validated with an independent test set of 24 samples, obtaining a prediction error on the entire range of 6.9 h for PMI < 24 h, 7.4 h for PMI between 24 and 48 h, and 10.3 h for PMI > 48 h. Time-related modifications of the 1H NMR vitreous metabolomic profile could predict PMI better than potassium up to 48 h after death, whilst a combination of the two is better than the single approach for higher PMI estimation.ConclusionThe present study, although in a proof-of-concept animal model, shows that vitreous metabolomics can be a powerful tool to predict PMI providing a more accurate estimation compared to the widely studied approach based on vitreous potassium concentrations.

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.

Combining with lab-on-chip technology and multi-organ fusion strategy to estimate post-mortem interval of rat.

The estimation of post-mortem interval (PMI) is one of the most important problems in forensic pathology all the time. Although many classical methods can be used to estimate time since death, accurate and rapid estimation of PMI is still a difficult task in forensic practice, so the estimation of PMI requires a faster, more accurate, and more convenient method. In this study, an experimental method, lab-on-chip, is used to analyze the characterizations of polypeptide fragments of the lung, liver, kidney, and skeletal muscle of rats at defined time points after death (0, 1, 2, 3, 5, 7, 9, 12, 15, 18, 21, 24, 27, and 30 days). Then, machine learning algorithms (base model: LR, SVM, RF, GBDT, and MLPC; ensemble model: stacking, soft voting, and soft-weighted voting) are applied to predict PMI with single organ. Multi-organ fusion strategy is designed to predict PMI based on multiple organs. Then, the ensemble pruning algorithm determines the best combination of multi-organ. The kidney is the best single organ for predicting the time of death, and its internal and external accuracy is 0.808 and 0.714, respectively. Multi-organ fusion strategy dramatically improves the performance of PMI estimation, and its internal and external accuracy is 0.962 and 0.893, respectively. Finally, the best organ combination determined by the ensemble pruning algorithm is all organs, such as lung, liver, kidney, and skeletal muscle. Lab-on-chip is feasible to detect polypeptide fragments and multi-organ fusion is more accurate than single organ for PMI estimation.