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The development of a post-mortem interval estimation for human remains found on land in the Netherlands.

ABSTRACT: The decomposition process of human remains can be used to estimate the post-mortem interval (PMI), but decomposition varies due to many factors. Temperature is believed to be the most important and can be connected to decomposition by using the accumulated degree days (ADD). The aim of this research was to develop a decomposition scoring method and to develop a formula to estimate the PMI by using the developed decomposition scoring method and ADD.A decomposition scoring method and a Book of Reference (visual resource) were made. Ninety-one cases were used to develop a method to estimate the PMI. The photographs were scored using the decomposition scoring method. The temperature data was provided by the Royal Netherlands Meteorological Institute. The PMI was estimated using the total decomposition score (TDS) and using the TDS and ADD. The latter required an additional step, namely to calculate the ADD from the finding date back until the predicted day of death.The developed decomposition scoring method had a high interrater reliability. The TDS significantly estimates the PMI (R 2 = 0.67 and 0.80 for indoor and outdoor bodies, respectively). When using the ADD, the R 2 decreased to 0.66 and 0.56.The developed decomposition scoring method is a practical method to measure decomposition for human remains found on land. The PMI can be estimated using this method, but caution is advised in cases with a long PMI. The ADD does not account for all the heat present in a decomposing remain and is therefore a possible bias.

SUBMITTER: Gelderman HT

PROVIDER: S-EPMC5920129 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature

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The development of a post-mortem interval estimation for human remains found on land in the Netherlands.

Gelderman H T HT Boer L L Naujocks T T IJzermans A C M ACM Duijst W L J M WLJM

International journal of legal medicine 20171106 3

The decomposition process of human remains can be used to estimate the post-mortem interval (PMI), but decomposition varies due to many factors. Temperature is believed to be the most important and can be connected to decomposition by using the accumulated degree days (ADD). The aim of this research was to develop a decomposition scoring method and to develop a formula to estimate the PMI by using the developed decomposition scoring method and ADD.A decomposition scoring method and a Book of Ref ...[more]

PMID: 29110084

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Project description:Due to the influence of many environmental processes, a precise determination of the post-mortem interval (PMI) of skeletal remains is known to be very complicated. Although methods for the investigation of the PMI exist, there still remains much room for improvement. In this study the applicability of infrared (IR) microscopic imaging techniques such as reflection-, ATR- and Raman- microscopic imaging for the estimation of the PMI of human skeletal remains was tested. PMI specific features were identified and visualized by overlaying IR imaging data with morphological tissue structures obtained using light microscopy to differentiate between forensic and archaeological bone samples. ATR and reflection spectra revealed that a more prominent peak at 1042 cm-1 (an indicator for bone mineralization) was observable in archeological bone material when compared with forensic samples. Moreover, in the case of the archaeological bone material, a reduction in the levels of phospholipids, proteins, nucleic acid sugars, complex carbohydrates as well as amorphous or fully hydrated sugars was detectable at (reciprocal wavelengths/energies) between 3000 cm-1 to 2800 cm-1. Raman spectra illustrated a similar picture with less ν2PO43-at 450 cm-1 and ν4PO43- from 590 cm-1 to 584 cm-1, amide III at 1272 cm-1 and protein CH2 deformation at 1446 cm-1 in archeological bone material/samples/sources. A semi-quantitative determination of various distributions of biomolecules by chemi-maps of reflection- and ATR- methods revealed that there were less carbohydrates and complex carbohydrates as well as amorphous or fully hydrated sugars in archaeological samples compared with forensic bone samples. Raman- microscopic imaging data showed a reduction in B-type carbonate and protein α-helices after a PMI of 3 years. The calculated mineral content ratio and the organic to mineral ratio displayed that the mineral content ratio increases, while the organic to mineral ratio decreases with time. Cluster-analyses of data from Raman microscopic imaging reconstructed histo-anatomical features in comparison to the light microscopic image and finally, by application of principal component analyses (PCA), it was possible to see a clear distinction between forensic and archaeological bone samples. Hence, the spectral characterization of inorganic and organic compounds by the afore mentioned techniques, followed by analyses such as multivariate imaging analysis (MIAs) and principal component analyses (PCA), appear to be suitable for the post mortem interval (PMI) estimation of human skeletal remains.

Project description:The combined use of multiple omics methods to answer complex system biology questions is growing in biological and medical sciences, as the importance of studying interrelated biological processes in their entirety is increasingly recognized. We applied a combination of metabolomics, lipidomics and proteomics to human bone to investigate the potential of this multi-omics approach to estimate the time elapsed since death (i.e., the post-mortem interval, PMI). This “ForensOMICS” approach has the potential to improve accuracy and precision of PMI estimation of skeletonized human remains, thereby helping forensic investigators to establish the timeline of events surrounding death. Anterior midshaft tibial bone was collected from four female body donors in a fresh stage of decomposition before placement of the bodies to decompose outdoors at the human taphonomy facility managed by the Forensic Anthropological Center at Texas State (FACTS). Bone samples were again collected at selected PMIs (219, 790, 834 and 872 days). Liquid chromatography mass spectrometry (LC-MS) was used to obtain untargeted metabolomic, lipidomic and proteomic profiles from the pre- and post-placement bone samples. Multivariate analysis was used to investigate the three omics blocks by means of Data Integration Analysis for Biomarker discovery using Latent variable approaches for Omics studies (DIABLO), to identify the reduced number of markers that could effectively describe post-mortem changes and classify the individuals based on their PMI. The resulting model showed that pre-placement bone metabolome, lipidome and proteome profiles were clearly distinguishable from post-placement profiles. Metabolites associated with the pre-placement samples, suggested an extinction of the energetic metabolism and a switch towards another source of fuelling (e.g., structural proteins). We were able to identify certain biomolecules from the three groups that show excellent potential for estimation of the PMI, predominantly the biomolecules from the metabolomics block. Our findings suggest that, by targeting a combination of compounds with different post-mortem stability, in future studies we could be able to estimate both short PMIs, by using metabolites and lipids, and longer PMIs, by including more stable proteins.

Project description:BackgroundPerinatal mortality may vary between herds, but the cost of deaths are always higher than value of the calf. When diagnosing the cause of a calf's death it is important to determine when it occurred, before or after calving. Metabolomics is widely used to identify many human diseases, but quite rarely applied in veterinary science. The aim of this study was to compare the metabolic profiles of calves with different times of death and those of calves born alive. Into the study, twenty one healthy controls (singleton, normal assisted calving, born alive) and 75 stillborn (SB) calves (with a gestation length of ≥260 days, SB, or dead within 6 h of birth) were enrolled. Plasma and urine from SB and control calves were investigated by proton nuclear magnetic resonance based metabolomic methods. SB calves were divided into four PMI groups. One PMI group included calves that died after calving and the other groups - three comprised in utero deaths, based on pathophysiological changes (lung inflation, autolysis in internal organs, hemoglobin imbibition in the pleura and aortic arch). Partial Least Squares - Discriminant Analysis models based on plasma metabolites were calculated, reflecting assumed data clustering.ResultsTwenty six metabolites in plasma and 29 in urine changed significantly with PMI according to one way analysis of variance. Half the metabolites in plasma and the majority in urine increased with PMI. Six metabolites increased simultaneously in plasma and urine: acetate, sn-glycero-3-phosphocholine (GPC), leucine, valine, creatine, and alanine.ConclusionsPost-mortem changes in calves were associated with molecular variations in blood plasma and urine, showing the greatest differences for the group in which the post-mortem pathological changes were the most advanced. The results of the study show that evaluation of calf plasma or urine may be used as a diagnostic method for the determination of the PMI. Moreover, the metabolites, which unambiguously increased or decreased, can be used as potential biomarkers of PMI.

Dataset Information

The development of a post-mortem interval estimation for human remains found on land in the Netherlands.

Publications

The development of a post-mortem interval estimation for human remains found on land in the Netherlands.

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