Study of chemiluminescence measured by luminometry and its application in the estimation of postmortem interval of bone remains

Luminol and the postmortem interval estimation - influence of taphonomic factors

The estimation of the postmortem interval (PMI) is one of the key challenges for forensic anthropologists. Although there are several methods referenced for this purpose, none is sufficiently effective. One of the main reasons justifying the complexity of this task is the influence of several taphonomic factors.The study of the Luminol technique has stood out as a promising method for estimating PMI, complementing the existing methods, since it is an economic, easy and reproducible method that operates as a presumptive test. However, it is not known which taphonomic factors can influence the results obtained by this technique.The aim of this study is to test the influence of taphonomic factors, such as temperature, humidity, soil type and pH, on the estimation of the PMI by the Luminol technique.In order to test the influence of the referred factors, a sample consisting of 30 clavicles, with known and similar PMI, collected from autopsies, was distributed as evenly as possible by six vases and buried with different decomposition conditions for a period of 12 months. After the exhumation and sample preparation, the Luminol technique was applied.It was possible to clearly observe differences in the results. Thus, according to our research, it is possible to conclude that the results obtained by the application of Luminol are influenced by taphonomic factors. Therefore, the context in which a body is found should always be considered for applying this technique.

Handheld hyperspectral imaging as a tool for the post-mortem interval estimation of human skeletal remains

In forensic medicine, estimating human skeletal remains' post-mortem interval (PMI) can be challenging. Following death, bones undergo a series of chemical and physical transformations due to their interactions with the surrounding environment. Post-mortem changes have been assessed using various methods, but estimating the PMI of skeletal remains could still be improved. We propose a new methodology with handheld hyperspectral imaging (HSI) system based on the first results from 104 human skeletal remains with PMIs ranging between 1 day and 2000 years. To differentiate between forensic and archaeological bone material, the Convolutional Neural Network analyzed 65.000 distinct diagnostic spectra: the classification accuracy was 0.58, 0.62, 0.73, 0.81, and 0.98 for PMIs of 0 week-2 weeks, 2 weeks-6 months, 6 months-1 year, 1 year-10 years, and >100 years, respectively. In conclusion, HSI can be used in forensic medicine to distinguish bone materials >100 years old from those <10 years old with an accuracy of 98%. The model has adequate predictive performance, and handheld HSI could serve as a novel approach to objectively and accurately determine the PMI of human skeletal remains.

Estimation of Late Postmortem Interval: Where Do We Stand? A Literature Review

Estimating time since death can be challenging for forensic experts, and is one of the most challenging activities concerning the forensic world. Various methods have been assessed to calculate the postmortem interval on dead bodies in different stages of decomposition and are currently widely used. Nowadays, the only well-recognized dating technique is carbon-14 radioisotope measurement, whereas other methods have been tested throughout the years involving different disciplines with different and sometimes not univocal results. Today, there is no precise and secure method to precisely determine time since death, and late postmortem interval estimation remains one of the most debated topics in forensic pathology. Many proposed methods have shown promising results, and it is desirable that with further studies some of them might become acknowledged techniques to resolve such a difficult and important challenge. The present review aims at presenting studies about the different techniques that have been tested in order to find a valuable method for estimating time since death for skeletal remains. By providing a comprehensive overview, the purpose of this work is to offer readers new perspectives on postmortem interval estimation and to improve current practice in the management of skeletal remains and decomposed bodies.

Application of Micro-Computed Tomography for the Estimation of the Post-Mortem Interval of Human Skeletal Remains

It is challenging to estimate the post-mortem interval (PMI) of skeletal remains within a forensic context. As a result of their interactions with the environment, bones undergo several chemical and physical changes after death. So far, multiple methods have been used to follow up on post-mortem changes. There is, however, no definitive way to estimate the PMI of skeletal remains. This research aimed to propose a methodology capable of estimating the PMI using micro-computed tomography measurements of 104 human skeletal remains with PMIs between one day and 2000 years. The present study indicates that micro-computed tomography could be considered an objective and precise method of PMI evaluation in forensic medicine. The measured parameters show a significant difference regarding the PMI for Cort Porosity p < 0.001, BV/TV p > 0.001, Mean1 p > 0.001 and Mean2 p > 0.005. Using a machine learning approach, the neural network showed an accuracy of 99% for distinguishing between samples with a PMI of less than 100 years and archaeological samples.

Post-Mortem Interval of Human Skeletal Remains Estimated with Handheld NIR Spectrometry

Estimating the post-mortem interval (PMI) of human skeletal remains is a critical issue of forensic analysis, with important limitations such as sample preparation and practicability. In this work, NIR spectroscopy (NIRONE® Sensor X; Spectral Engines, 61449, Germany) was applied to estimate the PMI of 104 human bone samples between 1 day and 2000 years. Reflectance data were repeatedly collected from eight independent spectrometers between 1950 and 1550 nm with a spectral resolution of 14 nm and a step size of 2 nm, each from the external and internal bone. An Artificial Neural Network was used to analyze the 66,560 distinct diagnostic spectra, and clearly distinguished between forensic and archaeological bone material: the classification accuracies for PMIs of 0−2 weeks, 2 weeks−6 months, 6 months−1 year, 1 year−10 years, and >100 years were 0.90, 0.94, 0.94, 0.93, and 1.00, respectively. PMI of archaeological bones could be determined with an accuracy of 100%, demonstrating the adequate predictive performance of the model. Applying a handheld NIR spectrometer to estimate the PMI of human skeletal remains is rapid and extends the repertoire of forensic analyses as a distinct, novel approach.

Estimation of the post-mortem interval of human skeletal remains using Raman spectroscopy and chemometrics

An important demand exists in the field of forensic analysis to objectively determine the post-mortem interval (PMI) when human skeletal remains are discovered. It is widely known that bones undergo different chemical and physical processes after death, mainly due to their interaction with the environment in which they are found, although it is not known exactly what these processes consist of. Multiple techniques have been used so far to follow up these and other post-mortem changes and thus establish the time elapsed since the individual's death, but they present important drawbacks in terms of reliability and accuracy. The aim of this research was to propose an analytical methodology capable of determining the PMI by using non-destructive Raman spectroscopy measurements of human skeletal remains. The recorded Raman spectra provided valuable and potentially useful information from which a multivariate study was performed by means of orthogonal partial least squares regression (OPLSR) in order to correlate the PMI with the detected spectral modifications. A collection of 53 real human skeletal remains with known PMI (15 years ≤ PMI ≤ 87 years) was analysed and used for building and validating the OPLS model. The PMI of 10 out of 14 validation samples could be determined with an accuracy error of less than 30%, demonstrating the adequate predictive performance of the OPLS model even in spite of the large inter-individual variability it handled. This opens up the possibility of applying the OPLS model in combination with non-destructive techniques to the determination of the PMI of human skeletal remains that have been buried in conditions similar or equal to those of cemetery niches and in a geographic location with a Mediterranean climate, which is an important achievement for forensic medicine and anthropology.

Proteomics in Forensic Analysis: Applications for Human Samples

Proteomics, the large-scale study of all proteins of an organism or system, is a powerful tool for studying biological systems. It can provide a holistic view of the physiological and biochemical states of given samples through identification and quantification of large numbers of peptides and proteins. In forensic science, proteomics can be used as a confirmatory and orthogonal technique for well-built genomic analyses. Proteomics is highly valuable in cases where nucleic acids are absent or degraded, such as hair and bone samples. It can be used to identify body fluids, ethnic group, gender, individual, and estimate post-mortem interval using bone, muscle, and decomposition fluid samples. Compared to genomic analysis, proteomics can provide a better global picture of a sample. It has been used in forensic science for a wide range of sample types and applications. In this review, we briefly introduce proteomic methods, including sample preparation techniques, data acquisition using liquid chromatography-tandem mass spectrometry, and data analysis using database search, spectral library search, and de novo sequencing. We also summarize recent applications in the past decade of proteomics in forensic science with a special focus on human samples, including hair, bone, body fluids, fingernail, muscle, brain, and fingermark, and address the challenges, considerations, and future developments of forensic proteomics.

Human Bone Proteomes before and after Decomposition: Investigating the Effects of Biological Variation and Taphonomic Alteration on Bone Protein Profiles and the Implications for Forensic Proteomics

Bone proteomic studies using animal proxies and skeletonized human remains have delivered encouraging results in the search for potential biomarkers for precise and accurate post-mortem interval (PMI) and the age-at-death (AAD) estimation in medico-legal investigations. The development of forensic proteomics for PMI and AAD estimation is in critical need of research on human remains throughout decomposition, as currently the effects of both inter-individual biological differences and taphonomic alteration on the survival of human bone protein profiles are unclear. This study investigated the human bone proteome in four human body donors studied throughout decomposition outdoors. The effects of ageing phenomena (in vivo and post-mortem) and intrinsic and extrinsic variables on the variety and abundancy of the bone proteome were assessed. Results indicate that taphonomic and biological variables play a significant role in the survival of proteins in bone. Our findings suggest that inter-individual and inter-skeletal differences in bone mineral density (BMD) are important variables affecting the survival of proteins. Specific proteins survive better within the mineral matrix due to their mineral-binding properties. The mineral matrix likely also protects these proteins by restricting the movement of decomposer microbes. New potential biomarkers for PMI estimation and AAD estimation were identified. Future development of forensic bone proteomics should include standard measurement of BMD and target a combination of different biomarkers.

New contributions to the relationship between sequential changes of ATP-related metabolites and post-mortem interval in rats

In recent years, it has become a new research direction to post-mortem interval (PMI) estimation from the changes in metabolite content generated during the process of cadaver corruption, and lead to more and more attention has been paid to the biochemical changes of muscles after death. The ATP degradation process has long been accepted as a precise manner to estimate freshness of meat products in food science. ATP-related metabolites may also serve as an indicator for PMI estimation of corpses. The purpose of this study was to test this possibility. Firstly, this study optimized the detection method of ATP-related metabolites in skeletal muscles of rat. Moreover, in animal experiment, ATP-related metabolites (ATP, ADP, AMP, IMP, Ino, Hx) in lower hind limb skeletal muscles of sixty rats were measured by RP-HPLC at different PMI for 168 h at 20 °C ± 1 °C, the change of freshness indicators (K value, K1 value, K0 value, H value, P value, G value, IMP ratio) were carefully analyzed, and investigate the relationship between them and PMI. The overall results showed that IMP, AMP, Hx, Total metabolites, K value, K1 value, K0 value, H value, P value, G value, and IMP ratio in skeletal muscles changed significantly with PMI (R2 = 0.864-0.971, all P < 0.01) while ATP, ADP, Ino, IMP precursors and IMP degradants had minor changes during the same period (R2 = 0.171-0.706). Specifically, significant linear positive correlations between H value of skeletal muscles and PMI were found, and the coefficients of their regression functions were R2 = 0.971. The correlation between AMP and PMI was slightly lower (R2 = 0.864), but the scope of PMI estimation was the widest (168 h). It can be concluded that the determination of ATP-related metabolites in skeletal muscle may be a potential tool in the PMI estimation. However, more researches on its influencing factors are needed to facilitate its final use in practice.