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Assessing various Infrared (IR) microscopic imaging techniques for post-mortem interval evaluation of human skeletal remains.

ABSTRACT: 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.

SUBMITTER: Woess C

PROVIDER: S-EPMC5363948 | biostudies-literature |

REPOSITORIES: biostudies-literature

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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:OBJECTIVES:To test the applicability, accuracy, precision, and reproducibility of various 3D superimposition techniques for radiographic data, transformed to triangulated surface data. METHODS:Five superimposition techniques (3P: three-point registration; AC: anterior cranial base; AC + F: anterior cranial base + foramen magnum; BZ: both zygomatic arches; 1Z: one zygomatic arch) were tested using eight pairs of pre-existing CT data (pre- and post-treatment). These were obtained from non-growing orthodontic patients treated with rapid maxillary expansion. All datasets were superimposed by three operators independently, who repeated the whole procedure one month later. Accuracy was assessed by the distance (D) between superimposed datasets on three form-stable anatomical areas, located on the anterior cranial base and the foramen magnum. Precision and reproducibility were assessed using the distances between models at four specific landmarks. Non parametric multivariate models and Bland-Altman difference plots were used for analyses. RESULTS:There was no difference among operators or between time points on the accuracy of each superimposition technique (p>0.05). The AC + F technique was the most accurate (D<0.17 mm), as expected, followed by AC and BZ superimpositions that presented similar level of accuracy (D<0.5 mm). 3P and 1Z were the least accurate superimpositions (0.79<D<1.76 mm, p<0.005). Although there was no difference among operators or between time points on the precision of each superimposition technique (p>0.05), the detected structural changes differed significantly between different techniques (p<0.05). Bland-Altman difference plots showed that BZ superimposition was comparable to AC, though it presented slightly higher random error. CONCLUSIONS:Superimposition of 3D datasets using surface models created from voxel data can provide accurate, precise, and reproducible results, offering also high efficiency and increased post-processing capabilities. In the present study population, the BZ superimposition was comparable to AC, with the added advantage of being applicable to scans with a smaller field of view.

Project description:BackgroundThe post-mortem interval (PMI) is the time elapsed since the dead of an individual until the body is found, which is relevant for forensic purposes. The miRNAs regulate the expression of some genes; and due to their small size, they can better support degradation, which makes them suitable for forensic analysis. In the present work, we evaluated the gene expression of miR-381-3p, miR-23b-3p, and miR-144-3p in skeletal muscle in a murine model at the early PMI.MethodsWe designed a rat model to evaluate the early PMI under controlled conditions. This model consisted in 25 rats divided into five groups of rats, that correspond to the 0, 3, 6, 12 and 24 hours of PMI. The 0 h-PMI was considered as the control group. Muscle samples were taken from each rat to analyze the expression of miR-381-3p, miR-23b-3p, and miR-144-3p by quantitative RT-PCR. The gene expression of each miRNA was expressed as Fold Change (FC) and compared among groups. To find the targets of these miRNAs and the pathways where they participate, we performed an in-silico analysis. From the gene targets of miR-381-3p identified in the silico analysis, the EPC1 gene was selected for gene expression analysis by quantitative RT-PCR in these samples. Also, to evaluate if miR-381-3p could predict the early PMI, a mixed effects model was calculated using its gene expression.ResultsAn upregulation of miR-381-3p was found at 24 h-PMI compared with the control group of 0 h-PMI and (FC = 1.02 vs. FC = 1.96; p = 0.0079). This was the opposite for miR-23b-3p, which had a down-regulation at 24 h-PMI compared to 0 h-PMI (FC = 1.22 vs. FC = 0.13; p = 0.0079). Moreover, the gene expression of miR-381-3p increased throughout the first 24 h of PMI, contrary to miR-23b-3p. The targets of these two miRNAs, participate in biological pathways related to hypoxia, apoptosis, and RNA metabolism. The gene expression of EPC1 was found downregulated at 3 and 12 h of PMI, whereas it remained unchanged at 6 h and 24 h of PMI. Using a multivariate analysis, it was possible to predict the FC of miR-381-3p of all but 6 h-PMI analyzed PMIs.DiscussionThe present results suggest that miR-23b-3p and miR-381-3p participate at the early PMI, probably regulating the expression of some genes related to the autolysis process as EPC1 gene. Although the miR-381-3p gene expression is a potential estimator of PMI, further studies will be required to obtain better estimates.

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Assessing various Infrared (IR) microscopic imaging techniques for post-mortem interval evaluation of human skeletal remains.

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