The 'ForensOMICS' approach for postmortem interval estimation from human bone by integrating metabolomics, lipidomics, and proteomics

DNA forensics at forty: the way forward

Forensic DNA analysis has transformed criminal investigations since its inception in 1985. Over four decades, this field has evolved through various phases-from the early stages of exploration to today's highly sophisticated methodologies. Key advancements such as the development of rapid DNA analysis techniques, microchip-based systems, and next-generation sequencing have improved the speed, reliability, and utility of DNA forensics. However, despite these technological advances, the field still faces considerable challenges, particularly with increasing case backlogs, limited population-specific databases, and the difficulties associated with analyzing degraded or challenging samples like bones and touch DNA. Emerging technologies such as single-cell genomic analysis, lineage markers, proteomics, and human microbiome analysis offer promising solutions to these challenges. Furthermore, the integration of artificial intelligence (AI) and machine learning (ML) in forensic workflows is enhancing the ability to analyze complex DNA samples efficiently, paving the way for faster and more accurate results. As forensic DNA analysis enters its next phase, the focus will be on expanding databases, refining quality control and assurance protocols, and standardizing training for forensic professionals worldwide. The journey of forensic DNA analysis over the past 40 years demonstrates a field in continuous development. Although significant progress has been made, there remain opportunities for further innovation, particularly in overcoming the current limitations and addressing ethical and legal concerns. By doing so, forensic DNA analysis will continue to play a pivotal role in the future of criminal justice.

Estimation of postmortem interval under different ambient temperatures based on multi-organ metabolomics and machine learning algorithm

In forensic practice, the estimation of postmortem interval has been a persistent challenge. Recently, there has been an increasing utilization of metabolomics techniques combined with machine learning methods for postmortem interval estimation. When examining metabolite changes from a global perspective, rather than relying on specific substance changes, estimating postmortem interval through machine learning methods is more precise and entails fewer errors. Prior studies have investigated the use of metabolomics to estimate postmortem interval. Nevertheless, most of them focused on analyzing the metabolomic properties of a single organ or biofluid concerning a specific temperature. In this study, we employ the GC-MS platform to identify metabolites in the liver, kidney, and quadriceps femoris muscle of mechanically suffocated Sprague Dawley rats at various temperatures. Multivariable statistical analysis was used to determine differential compounds from the original data. The machine learning method was used to establish models for the estimation of postmortem interval under various ambient temperatures. As indicated by the results, liver, kidney, and quadriceps femoris muscle samples were screened for 24, 18, and 19 differential metabolites respectively, associated with postmortem interval under various ambient temperatures. Based on the metabolites listed above, the support vector regression models were established by utilizing single-organ and multi-organ metabolomics data for postmortem interval estimation. The multi-organ model showed a higher estimation accuracy. Also, a comprehensive generalization postmortem interval estimation model was established with multi-organ metabolomics data and temperature variables, which can be used for the postmortem interval estimation within the temperature range of 5-35℃. These results demonstrate that a multi-organ model utilizing metabolomics techniques can accurately estimate the postmortem interval under various ambient temperatures. Meanwhile, this research establishes a strong foundation for the practical application of metabolomics in postmortem interval estimation.

Thanatochemistry and the role of hypoxanthine in the post-mortem interval estimation: a systematic literature review

The estimation of post-mortem interval (PMI) is of utmost importance for forensic pathologists due to its implication in medico-legal evaluations. Research over the last thirty years has sought new methods for estimating the time of death, particularly focused on human biomarkers whose concentration changes over time after death. Although most studies are based on potassium (K+) concentrations in blood and vitreous humor (VH), hypoxanthine (Hx) has shown great promise in assessing PMI. Following PRISMA guidelines, this systematic review addresses the PICO question: "In human cadavers, what is the role of hypoxanthine, where, and with what analytical techniques is it currently used for post-mortem interval estimation?". Twenty-four papers were retrieved. The results indicate that Hx concentration can be estimated in various biofluids, VH being the most commonly accounted for. Furthermore, different pre-analytical procedures are resorted to for sample preparation, such as several methodologies utilized to detect Hx concentration. The relationship between the so-obtained Hx levels and PMI is expressed quantitively (through regressions or correlation coefficients) or semi-quantitatively (by changes in nuclear magnetic resonance spectra). PMI estimation accuracy improves significantly when additional factors are considered (such as ambient and rectal temperature, urea concentration, body weight, and cause of death) or when new methodologies providing flexible regression models are applied. Despite the promising potential, many limitations remain. Notably, the heterogeneity of sample selection and pre-analytical/analytical phases leads to inconsistent results. Thus, much more should be done to lay procedural standards and optimize biochemistry and Hx utilization in PMI-related forensic investigations.

"Omics" and Postmortem Interval Estimation: A Systematic Review

Postmortem interval (PMI) estimation is a challenge of utmost importance in forensic daily practice. Traditional methods face limitations in accuracy and reliability, particularly for advanced decomposition stages. Recent advances in "omics" sciences, providing a holistic view of postmortem biochemical changes, offer promising avenues for overcoming these challenges. This systematic review aims at investigating the role of mass-spectrometry-based "omics" approaches in PMI estimation to elucidate molecular mechanisms underlying predictable time-dependent biochemical alterations occurring after death. A systematic search was performed, adhering to PRISMA guidelines, through "free-text" protocols in the databases PubMed, SCOPUS and Web of Science. The inclusion criteria were as follows: experimental studies analyzing, as investigated samples, animal or human corpses in toto or in parts and estimating PMI through MS-based untargeted omics approaches, with full texts in the English language. Quality assessment was performed using STROBE and ARRIVE critical appraisal checklists. A total of 1152 papers were screened and 26 included. Seventeen papers adopted a proteomic approach (65.4%), nine focused on metabolomics (34.6%) and two on lipidomics (7.7%). Most papers (57.7%) focused on short PMIs (<7 days), the remaining papers explored medium (7-120 days) (30.77%) and long PMIs (>120 days) (15.4%). Muscle tissue was the most frequently analyzed substrate (34.6% of papers), followed by liver (19.2%), bones (15.4%), cardiac blood and leaking fluids (11.5%), lung, kidney and serum (7.7%), and spleen, vitreous humor and heart (3.8%). Predictable time-dependent degradation patterns of macromolecules in different biological substrates have been discussed, with special attention to molecular insights into postmortem biochemical changes.

A multi-tissue longitudinal proteomics study to evaluate the suitability of post-mortem samples for pathophysiological research

Recent developments in mass spectrometry-based proteomics have established it as a robust tool for system-wide analyses essential for pathophysiological research. While post-mortem samples are a critical source for these studies, our understanding of how body decomposition influences the proteome remains limited. Here, we have revisited published data and conducted a clinically relevant time-course experiment in mice, revealing organ-specific proteome regulation after death, with only a fraction of these changes linked to protein autolysis. The liver and spleen exhibit significant proteomic alterations within hours post-mortem, whereas the heart displays only modest changes. Additionally, subcellular compartmentalization leads to an unexpected surge in proteome alterations at the earliest post-mortem interval (PMI). Additionally, we have conducted a comprehensive analysis of semi-tryptic peptides, revealing distinct consensus motifs for different organs, indicating organ-specific post-mortem protease activity. In conclusion, our findings emphasize the critical importance of considering PMI effects when designing proteomics studies, as these effects may significantly overshadow the impacts of diseases. Preferably, the samples should be taken in the operation room, especially for studies including subcellular compartmentalization or trans-organ comparison. In single-organ studies, the planning should involve careful control of PMI.

Comparative analysis of anticoagulant influence on PMI estimation based on porcine blood metabolomics profile measured using GC-MS

Introduction

Accurate post-mortem interval (PMI) estimation is essential in forensic investigations. Although various methods for PMI determination have been developed, only an approximate estimation is still achievable, and an accurate PMI indication is still challenging. Therefore, in this study, we employed gas chromatography-mass spectrometry (GC-MS)-based metabolomics to assess post-mortem changes in porcine blood samples collected with and without the addition of anticoagulant (EDTA). Our study aimed to identify metabolites dependent on the EDTA addition and time (taking into account the biodiversity of the studied organism) and those that are time-dependent but resistant to the addition of an anticoagulant.

Methods

The experiment was performed on blood samples collected from 16 animals (domestic pig, breed: Polish Large White), 8 with and 8 without EDTA addition. The moment of death (time 0) and 15 additional time points (from 3 to 168 h after death) were selected to examine changes in metabolites' levels in specific time intervals. We employed linear mixed models to study the relationship between metabolite intensities, time and presence of EDTA while accounting for the effect of individual pigs.

Results and Discussion

We confirmed that the intensity of 16 metabolites (mainly amino acids) significantly depends on PMI and the presence of EDTA. However, the intensity of the ideal biomarker(s) for PMI estimation should be determined only by the time after death and not by external factors such as the presence of the anticoagulant agent. Thus, we identified 41 metabolites with time-dependent intensities that were not susceptible to EDTA presence. Finally, we assessed the performance of these metabolites in a PMI predictive model. Citraconic acid yielded one of the lowest errors in general PMI estimation (32.82 h). Moreover, similar errors were observed for samples with and without EDTA (33.32 h and 32.34 h, respectively). Although the small sample size and information leak in predictive modelling prevent drawing definite conclusions, citraconic acid shows potential as a robust PMI estimator.

Lipidomics in forensic science: a comprehensive review of applications in drugs, alcohol, latent fingermarks, fire debris, and seafood authentication

Forensic science, an interdisciplinary field encompassing the collection, examination, and presentation of evidence in legal proceedings, has recently embraced lipidomics as a valuable tool. Lipidomics, a subfield of metabolomics, specializes in the analysis of lipid structures and functions, offering insights into biological processes that can aid forensic investigations. While not a substitute for DNA analysis in personal identification, lipidomics complements this technique by focusing on small biological molecules, with distinct sample requirements. This review comprehensively explores the current applications of lipidomics in forensic science. The review commences with an introduction to the concept and historical background of lipidomics, subsequently delving into its utilization in diverse areas such as drug analysis, ethyl alcohol and substitute assessment, latent fingermark detection, fire debris analysis, and seafood authentication. By showcasing the various biological materials and methods employed, this review underscores the potential of lipidomics as a powerful adjunct in forensic investigations.

Human Decomposition and Time Since Death: Persistent Challenges and Future Directions of Postmortem Interval Estimation in Forensic Anthropology

Estimating the time since death, or the postmortem interval (PMI), is a significant component of forensic anthropological analysis when human remains are discovered. Despite decades of research, methods for providing an estimate of the PMI with known error rates are still absent from applied medicolegal forensic work, which prompts the necessity for a critical examination of the state of the field. This review details the history of how forensic anthropology emerged from the broader discipline of biological anthropology, with a specific focus on how forensic anthropologists came to be understood as suitable experts for estimating the PMI. We describe existing PMI estimation methods and enduring barriers in advancing our knowledge. We provide an overview of the formative PMI research, then focus on a systematic review of 30 years (1993-2023) of human decomposition literature. Results of our synthesis demonstrate the two prevailing ways to estimate the PMI involve (1) the use of quantitative biomarkers and (2) macromorphoscopic observations. Results also highlight that PMI research continues to be limited by small, highly variable samples and a lack of standardized definitions of decomposition, which impedes replicability and the advancement of methods for PMI estimation. Forensic anthropologists can address these longstanding issues by ensuring the principles of Open Science are adhered to during the research and dissemination process including data sharing and transparency. Intentional research design that integrates comprehensive geospatial data and improved modeling techniques can contribute to devising methods capable of providing PMI estimates within applied medicolegal and humanitarian contexts.

Application of Metabolomics and Machine Learning for the Prediction of Postmortem Interval

Determining postmortem interval (PMI) during forensic investigations is essential and challenging. The traditional methods used to predict PMI, such as algor mortis, rigor mortis, livor mortis, and decomposition changes, involve large margins of error, particularly when the person's death has occurred more than 48 hours ago. Organs and tissues experience profound biochemical and metabolomic changes after death. As such, new approaches are required to enhance the prediction of PMI. Novel developments in forensic sciences are focusing on identifying and analyzing postmortem metabolomics, which are biomarkers found in different body fluids and tissues serving as a "fingerprint" of continuous processes affected by both external and internal factors. This variability complicates the dataset, making examination challenging. Hence, the application of machine learning technology offers the capability to navigate through the complexities of metabolomic data, uncover hidden correlations, and enhance the accuracy of PMI prediction in forensic science. This article explores and assesses the new methodology that has recently been used to enhance the prediction of PMI by analyzing postmortem metabolomics' changes and applying these data to machine learning models. This development provides a significantly more reliable process that could potentially decrease the margin of error compared to the traditional methods used for PMI prediction.

Multimodal Approaches Based on Microbial Data for Accurate Postmortem Interval Estimation

Accurate postmortem interval (PMI) estimation is critical for forensic investigations, aiding case classification and providing vital trial evidence. Early postmortem signs, such as body temperature and rigor mortis, are reliable for estimating PMI shortly after death. However, these indicators become less useful as decomposition progresses, making late-stage PMI estimation a significant challenge. Decomposition involves predictable microbial activity, which may serve as an objective criterion for PMI estimation. During decomposition, anaerobic microbes metabolize body tissues, producing gases and organic acids, leading to significant changes in skin and soil microbial communities. These shifts, especially the transition from anaerobic to aerobic microbiomes, can objectively segment decomposition into pre- and post-rupture stages according to rupture point. Microbial communities change markedly after death, with anaerobic bacteria dominating early stages and aerobic bacteria prevalent post-rupture. Different organs exhibit distinct microbial successions, providing valuable PMI insights. Alongside microbial changes, metabolic and volatile organic compound (VOC) profiles also shift, reflecting the body's biochemical environment. Due to insufficient information, unimodal models could not comprehensively reflect the PMI, so a muti-modal model should be used to estimate the PMI. Machine learning (ML) offers promising methods for integrating these multimodal data sources, enabling more accurate PMI predictions. Despite challenges such as data quality and ethical considerations, developing human-specific multimodal databases and exploring microbial-insect interactions can significantly enhance PMI estimation accuracy, advancing forensic science.

Enhancing late postmortem interval prediction: a pilot study integrating proteomics and machine learning to distinguish human bone remains over 15 years

BACKGROUND

Determining the postmortem interval (PMI) accurately remains a significant challenge in forensic sciences, especially for intervals greater than 5 years (late PMI). Traditional methods often fail due to the extensive degradation of soft tissues, necessitating reliance on bone material examinations. The precision in estimating PMIs diminishes with time, particularly for intervals between 1 and 5 years, dropping to about 50% accuracy. This study aims to address this issue by identifying key protein biomarkers through proteomics and machine learning, ultimately enhancing the accuracy of PMI estimation for intervals exceeding 15 years.

METHODS

Proteomic analysis was conducted using LC-MS/MS on skeletal remains, specifically focusing on the tibia and ribs. Protein identification was performed using two strategies: a tryptic-specific search and a semitryptic search, the latter being particularly beneficial in cases of natural protein degradation. The Random Forest algorithm was used to model protein abundance data, enabling the prediction of PMI. A thorough screening process, combining importance scores and SHAP values, was employed to identify the most informative proteins for model's training and accuracy.

RESULTS

A minimal set of three biomarkers-K1C13, PGS1, and CO3A1-was identified, significantly improving the prediction accuracy between PMIs of 15 and 20 years. The model, based on protein abundance data from semitryptic peptides in tibia samples, achieved sustained 100% accuracy across 100 iterations. In contrast, non-supervised methods like PCA and MCA did not yield comparable results. Additionally, the use of semitryptic peptides outperformed tryptic peptides, particularly in tibia proteomes, suggesting their potential reliability in late PMI prediction.

CONCLUSIONS

Despite limitations such as sample size and PMI range, this study demonstrates the feasibility of combining proteomics and machine learning for accurate late PMI predictions. Future research should focus on broader PMI ranges and various bone types to further refine and standardize forensic proteomic methodologies for PMI estimation.

Simultaneous multi-targeted forensic toxicological screening in biological matrices by MRM-IDA-EPI mode

The toxicologist ascertains drug assumptions in case of paediatric intoxications and death for overdose. The analytical approach consists of initially screening and consequently confirming drug positivity. We developed a toxicological screening method and validated its use comparing the results with a LC-MS/MS analysis. The method identifies 751 drugs and metabolites (704 in positive and 47 in negative mode). Chromatographic separation was achieved eluting mobile phase A (10 mM ammonium formate) and B (0.05% formic acid in methanol) in gradient on Kinetex Phenyl-Hexyl (50 × 4.6 mm, 2.6 μm) with 0.7 mL/min flow rate for 11 min. Multiple Reaction Monitoring (MRM) was adopted as survey scan and, after an Information-Dependent Analysis (IDA) (threshold of 30,000 for positive and 1000 cps for negative mode), the Enhanced Product Ion (scan range: 50-700 amu) was triggered. The MS/MS spectrum generated was compared with one of the libraries for identification. Data processing was optimised through creation of rules. Sample preparation, mainly consisting of deproteinization and enzymatic hydrolysis, was set up for different matrices (blood, urine, vitreous humor, synovial fluid, cadaveric tissues and larvae). Cut-off for most analytes resulted in the lowest concentration tested. When the results from the screening and LC-MS/MS analysis were compared, an optimal percentage of agreement (100%) was assessed for all matrices. Method applicability was evaluated on real paediatric intoxications and forensic cases. In conclusion, we proposed a multi-targeted, fast, sensitive and specific MRM-IDA-EPI screening having an extensive use in different toxicological fields.

Estimation of postmortem interval using histological and oxidative biomarkers in human bone marrow

In forensic medicine, estimating the postmortem interval (PMI) is of great importance for the timeline and the reconstruction of the events surrounding death. Bone marrow (BM) is one of the largest organs in the body, with good resistance to autolysis and contamination. Therefore, the present study aims to correlate different postmortem intervals and bone marrow antioxidant enzyme levels using an Enzyme-linked immunosorbent assay (ELISA). In addition, detection of the changes in the histological structure of human bone marrow in relation to the time passed since death. BM samples from 20 forensic autopsy cadavers were obtained from cases referred to the Department of Forensic Medicine in the Ministry of Justice, Dakahlia Governorate, processed for histopathological examination as well as estimation of reduced glutathione (GSH), glutathione peroxidase (GPX), and glutathione reductase (GRX) using ELISA. Results of ELISA analysis showed a significant decrease in the level of antioxidant enzymes with increasing PMI; regarding histopathological examination, from 6 to > 18 h PMI, the changes in morphology after death were gradual, progressive, and regular, indicating great value in PMI determination. Also, 18 h of PMI showed loss of cellular details, absence of fat cells, and necrosis of BM with the nucleus dispersed as eosinophilic debris. Estimation of antioxidant enzymes level in human bone marrow using ELISA and detection of the changes in the histological structure of human bone marrow in relation to time passed since the death, either separately or in combination, can be used to estimate PMI accurately.

Postmortem interval estimation of time since death: impact of non-histone binding proteins, immunohistochemical, and histopathological changes in vivo

The postmortem interval (PMI) is one of the primary objectives and challenging tasks proposed for determining the time of death. This study aimed to estimate the PMI using serum levels of high mobility group box 1 (HMGB1), a biomarker of pyroptotic cell death, along with desmin immunohistochemical and histological analyses of the gastrocnemius muscle in rats at various time intervals. Serum and gastrocnemius muscle samples were collected at zero, 24-, 48-, 72-, and 96 hours postmortem from 50 rats maintained at 22 ± 2°C. The results revealed that the HMGB1 level peaked at 48 hours and dropped in a time-dependent manner afterward. Immunohistochemical analysis revealed a progressive decrease in desmin expression, with severe immunoreactivity (38.19%) at 0 hours, dropping to a minimal level (1.09%) 96 hours after death. Histological analysis of the gastrocnemius muscle at 96 hours revealed significant vacuolation, loss of normal architecture, reduced nuclear visibility, and complete autolysis of all myocytes. In conclusion, HMGB1 levels, desmin immunoreactivity, and histopathological alterations seen in the gastrocnemius muscle could be helpful, valuable, and potential markers for accurately determining PMIs in humans in future studies.

Application and implications of radiocarbon dating in forensic case work: when medico-legal significance meets archaeological relevance

The estimation of the postmortem interval for skeletal remains is a crucial aspect of forensic anthropology. This paper illustrates the importance of radiocarbon analysis for establishing medico-legal significance and supporting forensic identification, through the analysis of three case studies for which the years of both birth and death were investigated. In Audresselles, Northern France, a partial skull was discovered with no contextual information or identity. Radiocarbon dating yielded an average calibrated calendar age of 4232 BCE (92.5% probability), indicating significant archaeological value but no forensic relevance. In the second case, skeletal remains were found in the flooded underground of a historical fort at Wimereux, Northern France, also with no identity. Radiocarbon dating based on the bomb-pulse curve indicated a calibrated date of death in 1962 CE (37.3% probability) or 1974-1975 CE (58.1% probability), both surpassing the French statute of limitations. Lastly, a skeleton with a suspected identity was discovered near Valenciennes, Northern France, and various biological tissues underwent radiocarbon dating. A bone sample suggested a calibrated date of death of 1998-2002 CE (84.6% probability), differing from a hair sample (2013-2018 CE, 83.3% probability) because of the slower bone tissue remodeling process. DNA analysis confirmed the person's identity, reported missing a decade prior to the discovery of the remains, following the alignment of the radiocarbon results with the individual's year of birth based on dental tissues and year of death. These case studies reveal that traditional radiocarbon dating and bomb-pulse dating are essential tools for estimating the postmortem interval, providing mutual benefits for archaeologists, forensic anthropologists, and the criminal justice system.

Key points

Traditional radiocarbon dating and bomb-pulse dating are essential tools to establish the archaeological relevance or medico-legal significance of human skeletal remains.Bomb-pulse dating enables assessment of an individual's years of birth and death.Bomb-pulse dating helps to narrow down the pool of candidates for identification.Radiocarbon analysis provides mutual benefits for archaeologists, forensic anthropologists, and the criminal justice system.

A fundamental study on postmortem submersion interval estimation by metabolomics analyzing of gastrocnemius muscle from submersed rat models in freshwater

In forensic practice, determining the postmortem submersion interval (PMSI) and cause-of-death of cadavers in aquatic ecosystems has always been challenging task. Traditional approaches are not yet able to address these issues effectively and adequately. Our previous study proposed novel models to predict the PMSI and cause-of-death based on metabolites of blood from rats immersed in freshwater. However, with the advance of putrefaction, it is hardly to obtain blood samples beyond 3 days postmortem. To further assess the feasibility of PMSI estimation and drowning diagnosis in the later postmortem phase, gastrocnemius, the more degradation-resistant tissue, was collected from drowned rats and postmortem submersion model in freshwater immediately after death, and at 1 day, 3 days, 5 days, 7 days, and 10 days postmortem respectively. Then the samples were analyzed with liquid chromatography-tandem mass spectrometry (LC-MS/MS) to investigate the dynamic changes of the metabolites. A total of 924 metabolites were identified. Similar chronological changes of gastrocnemius metabolites were observed in the drowning and postmortem submersion groups. The difference in metabolic profiles between drowning and postmortem submersion groups was only evident in the initial 1 day postmortem, which was faded as the PMSI extension. Nineteen metabolites representing temporally-dynamic patterns were selected as biomarkers for PMSI estimation. A regression model was built based on these biomarkers with random forest algorithm, which yielded a mean absolute error (± SE) of 5.856 (± 1.296) h on validation samples from an independent experiment. These findings added to our knowledge of chronological changes in muscle metabolites from submerged vertebrate remains during decomposition, which provided a new perspective for PMSI estimation.

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.

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.

Extraction and untargeted analysis of metabolome from undemineralised cortical bone matrix

Liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) untargeted metabolomics has become the gold standard for the profiling of low-molecular-weight compounds. Recently, this discipline has raised great interest in forensic sciences, especially in the field of toxicology and for post-mortem interval estimation. The current study aims at evaluating three extraction protocols and two LC-MS/MS assays run in both positive and negative modes, to identify the most suitable method to conduct post-mortem metabolomic profiling of bone tissue. A fragment of the anterior tibia of a 82 years-old male sampled from a human taphonomy facility was powdered via freeze-milling. The powdered sub-samples were extracted in five replicates per protocol. Methods tested were (I) a biphasic chloroform-methanol-water protocol, (II) a single phase methanol-water protocol, and (III) a single phase methanol-acetonitrile-water protocol. LC-MS/MS analyses were carried out via high performance liquid chromatography, either on hydrophilic interaction (HILIC) or on reversed-phase (C18) columns in both positive and negative ionisation modes, coupled with a Q-TOF mass spectrometer. Results suggest that the highest consistency between replicates and quality control samples was obtained with the single phase extractions (i.e., methanol-acetonitrile-water), whilst the ideal combination of instrumental set up HILIC chromatography in positive ionisation mode and of C18 chromatography in negative ionisation mode. For the purpose of forensic investigations, a combination of a single phase extraction and the two aforementioned chromatographic and mass spectrometry modes could represent an ideal set up for obtaining bone metabolomic profiles from taphonomically altered bones.

Bone finds and their medicolegal examination: a study from Hesse, Germany

Bones found by chance can be of great criminal or historical interest. The nature of their appraisal depends on the individual case, the locally effective legislation and the available resources. To assess whether a find is relevant with respect to criminal investigation, the circumstances of the find and the results of the forensic examination carried out by trained personnel must be considered. The aim of this study was to obtain an overview of the circumstances and nature of the finds as well as the results of the subsequent expert opinions by evaluating bone finds from the federal state of Hesse, Germany. For this purpose, over a 10-year period from 2011 to 2020, all bone finds examined at the Institutes of Legal Medicine in Gießen and Frankfurt am Main, Germany, were evaluated retrospectively with regard to the locations and circumstances of the finds, their nature (human or non-human), the postmortem interval, possible traces of violent impact and the results of further examinations. Of the 288 bone finds evaluated, 38.2% were found in forests, meadows and parks. In 50.7%, the finds contained human bones, of which 37.0% had a forensically relevant postmortem interval of 50 years or less. Evidence of trauma was described in 77.4% of the human bone cases: postmortem damage in 78.8%, peri-mortem injury in 9.7% and ante-mortem injury in 11.5%. DNA examinations were performed in 40.4% of the human bone finds. They yielded STR profiles in 81.3%, leading to a definite identification in 35.4%. Among the non-human bones sent in, the most common were bones from pigs (23.4%), deer (18.1%), cattle (16.4%), roe deer (11.7%) and sheep (11.7%). The macroscopic examination is the first step of the forensic-osteological evaluation and sets the course for further examinations or investigations. DNA examinations are of great importance for the reliable identification of human bones. They were responsible for 70.8% of successful identifications.

From flesh to bones: Multi-omics approaches in forensic science

Recent advancements in omics techniques have revolutionised the study of biological systems, enabling the generation of high-throughput biomolecular data. These innovations have found diverse applications, ranging from personalised medicine to forensic sciences. While the investigation of multiple aspects of cells, tissues or entire organisms through the integration of various omics approaches (such as genomics, epigenomics, metagenomics, transcriptomics, proteomics and metabolomics) has already been established in fields like biomedicine and cancer biology, its full potential in forensic sciences remains only partially explored. In this review, we have presented a comprehensive overview of state-of-the-art analytical platforms employed in omics research, with specific emphasis on their application in the forensic field for the identification of the cadaver and the cause of death. Moreover, we have conducted a critical analysis of the computational integration of omics approaches, and highlighted the latest advancements in employing multi-omics techniques for forensic investigations.

Carrion insects living within the bones of large mammals: insect conservation and forensic entomology implications

Succession patterns of carrion insects on large mammal's carrion has been widely studied, notably to estimate the post-mortem interval in forensic investigations as accurately as possible. However, little attention has been paid to the carrion insects living inside these bones once a carcass is skeletonized. One very recent study documented flies emerging from pig carcasses, and only scarce authors reported the presence of other carrion insects taking advantage of the bone marrow. We, thus, aimed to (1) estimate the frequency of inner-bone space colonization by carrion insects, with particular attention to bone-skipper flies; (2) identify the insects living inside the carrion bones; and (3) determine whether or not carrion insects found within the bones can successfully exit the bones and complete their development. We extensively sampled 185 large mammals' bones collected from twelve vulture feeding stations and four isolated carcasses in southwest France and northern Spain. Sampled bones were opened, and the insects found inside were identified. For two bones, foramen, i.e., the holes providing a natural entrance and exit to the bone's inner cavity, was monitored with a camera to assess the insect's putative exit. We describe the entomofauna, i.e., the set of insect species, living within the bones, and illustrate insects' ability to exit the bones for their subsequent development and maturity. These results are discussed in the framework of carrion insect conservation and forensic entomology perspectives.

Postmortem metabolomics as a high-throughput cause-of-death screening tool for human death investigations

Autopsy rates are declining globally, impacting cause-of-death (CoD) diagnoses and quality control. Postmortem metabolomics was evaluated for CoD screening using 4,282 human cases, encompassing CoD groups: acidosis, drug intoxication, hanging, ischemic heart disease (IHD), and pneumonia. Cases were split 3:1 into training and test sets. High-resolution mass spectrometry data from femoral blood were analyzed via orthogonal-partial least squares discriminant analysis (OPLS-DA) to discriminate CoD groups. OPLS-DA achieved an R2 = 0.52 and Q2 = 0.30, with true-positive prediction rates of 68% and 65% for training and test sets, respectively, across all groups. Specificity-optimized thresholds predicted 56% of test cases with a unique CoD, average 45% sensitivity, and average 96% specificity. Prediction accuracies varied: 98.7% for acidosis, 80.5% for drug intoxication, 81.6% for hanging, 73.1% for IHD, and 93.6% for pneumonia. This study demonstrates the potential of large-scale postmortem metabolomics for CoD screening, offering high specificity and enhancing throughput and decision-making in human death investigations.

Postmortem metabolomics: influence of time since death on the level of endogenous compounds in human femoral blood. Necessary to be considered in metabolome study planning?

INTRODUCTION

The (un)targeted analysis of endogenous compounds has gained interest in the field of forensic postmortem investigations. The blood metabolome is influenced by many factors, and postmortem specimens are considered particularly challenging due to unpredictable decomposition processes.

OBJECTIVES

This study aimed to systematically investigate the influence of the time since death on endogenous compounds and its relevance in designing postmortem metabolome studies.

METHODS

Femoral blood samples of 427 authentic postmortem cases, were collected at two time points after death (854 samples in total; t1: admission to the institute, 1.3-290 h; t2: autopsy, 11-478 h; median ∆t = 71 h). All samples were analyzed using an untargeted metabolome approach, and peak areas were determined for 38 compounds (acylcarnitines, amino acids, phospholipids, and others). Differences between t2 and t1 were assessed by Wilcoxon signed-ranked test (p < 0.05). Moreover, all samples (n = 854) were binned into time groups (6 h, 12 h, or 24 h intervals) and compared by Kruskal-Wallis/Dunn's multiple comparison tests (p < 0.05 each) to investigate the effect of the estimated time since death.

RESULTS

Except for serine, threonine, and PC 34:1, all tested analytes revealed statistically significant changes between t1 and t2 (highest median increase 166%). Unpaired analysis of all 854 blood samples in-between groups indicated similar results. Significant differences were typically observed between blood samples collected within the first and later than 48 h after death, respectively.

CONCLUSIONS

To improve the consistency of comprehensive data evaluation in postmortem metabolome studies, it seems advisable to only include specimens collected within the first 2 days after death.

Bone Proteomics Method Optimization for Forensic Investigations

The application of proteomic analysis to forensic skeletal remains has gained significant interest in improving biological and chronological estimations in medico-legal investigations. To enhance the applicability of these analyses to forensic casework, it is crucial to maximize throughput and proteome recovery while minimizing interoperator variability and laboratory-induced post-translational protein modifications (PTMs). This work compared different workflows for extracting, purifying, and analyzing bone proteins using liquid chromatography with tandem mass spectrometry (LC-MS)/MS including an in-StageTip protocol previously optimized for forensic applications and two protocols using novel suspension-trap technology (S-Trap) and different lysis solutions. This study also compared data-dependent acquisition (DDA) with data-independent acquisition (DIA). By testing all of the workflows on 30 human cortical tibiae samples, S-Trap workflows resulted in increased proteome recovery with both lysis solutions tested and in decreased levels of induced deamidations, and the DIA mode resulted in greater sensitivity and window of identification for the identification of lower-abundance proteins, especially when open-source software was utilized for data processing in both modes. The newly developed S-Trap protocol is, therefore, suitable for forensic bone proteomic workflows and, particularly when paired with DIA mode, can offer improved proteomic outcomes and increased reproducibility, showcasing its potential in forensic proteomics and contributing to achieving standardization in bone proteomic analyses for forensic applications.

Applicability of a Chemiluminescence Immunoassay to Screen Postmortem Bile Specimens and Its Agreement with Confirmation Analysis

Bile has emerged as an alternative matrix for toxicological investigation of drugs in suspected forensic cases of overdose in adults and intoxications in children. Toxicological investigation consists in screening and, subsequently, confirming the result with specific techniques, such as liquid chromatography with tandem mass spectrometry (LC-MS/MS). As there is no screening test on the market to test postmortem bile specimens, the novelty of this study was in investigating the applicability of a chemiluminescence immunoassay, designed for other matrices and available on the market, on bile and validate its use, testing the agreement with LC-MS/MS analysis. Bile specimens were obtained from 25 forensic cases of suspected death from overdose and intoxication. Sample preparation for bile screening consists simply in centrifugation and dilution. Confirmation analysis allows simultaneous identification of 108 drugs and was validated on bile. Kappa analysis assessed a perfect agreement (0.81-1) between the assays for benzodiazepines, methadone, opiates, cocaine, oxycodone, cannabinoids, buprenorphine and pregabalin; a substantial agreement (0.41-0.6) was reported for barbiturates. No agreement was assessed for amphetamines, due to an abundance of putrefactive amines in postmortem specimens. In conclusion, this fast and easy immunoassay could be used for initial screening of bile specimens, identifying presence of drugs, except amphetamines, with reliability.

Volabolomic Fingerprinting for Post-Mortem Interval Estimation: A Novel Physiological Approach

Death is a multifaceted process wherein each individual cell and tissue has a metabolic homeostasis and a time of functional cessation defined by the dying process as well as by intrinsic and extrinsic factors. Decomposition is physiologically associated with the release of different types of volatile organic compounds (VOCs), and these form volaboloma mortis. The main purpose of this study was to record the volabolomic fingerprint produced by volatile molecules during the physiological decomposition process of human tissue and muscle cells. The volatile chemical signature has important implications for an open issue in forensics and pathology, namely the estimation of the postmortem interval (PMI), which decreases in accuracy with the passage of time. Volatile metabolites emitted from human tissues and muscle cells at 0, 24, 48, and 72 h were recorded in real time with an electronic nose sensor device. The key findings were the continuous sampling of VOCs emitted from tissues and cells. These showed a common behavior as time progressed; particularly, after 48 h the distributions became dispersed, and after 72 h they became more variable. Volabolomic fingerprinting associated with time progression relevant to the study of PMIs was reconstructed. Additionally, there may be broader applications, such as in dog training procedures for detecting human remains, and perhaps even for studying scavenger and insect attractants.

Multi-omics integration strategy in the post-mortem interval of forensic science

Estimates of post-mortem interval (PMI), which often serve as pivotal evidence in forensic contexts, are fundamentally based on assessments of variability among diverse molecular markers (including proteins and metabolites), their correlations, and their temporal changes in post-mortem organisms. Nevertheless, the present approach to estimating the PMI is not comprehensive and exhibits poor performance. We developed an innovative approach that integrates multi-omics and artificial intelligence, using multimolecular, multimarker, and multidimensional information to accurately describe the intricate biological processes that occur after death, ultimately enabling inference of the PMI. Called the multi-omics stacking model (MOSM), it combines metabolomics, protein microarray electrophoresis, and fourier transform-infrared spectroscopy data. It shows improved prediction accuracy of the PMI, which is urgently needed in the forensic field. It achieved an accuracy of 0.93, generalized area under the receiver operating characteristic curve of 0.98, and minimum mean absolute error of 0.07. The MOSM integration framework not only considers multiple markers but also incorporates machine-learning models with distinct algorithmic principles. The diversity of biological mechanisms and algorithmic models further ensures the generalizability and robustness of PMI estimation.

Lipidomes in Cadaveric Decomposition and Determination of the Postmortem Interval: A Systematic Review

Lipids are a large group of natural compounds, together with proteins and carbohydrates, and are essential for various processes in the body. After death, the organism's tissues undergo a series of reactions that generate changes in some molecules, including lipids. This means that determining the lipid change profile can be beneficial in estimating the postmortem interval (PMI). These changes can also help determine burial sites and advance the localization of graves. The aim was to explore and analyze the decomposition process of corpses, focusing on the transformation of lipids, especially triglycerides (TGs) and fatty acids (FAs), and the possible application of these compounds as markers to estimate PMI and detect burial sites. A systematic review of 24 scientific articles from the last 23 years (2000-2023) was conducted. The results show that membrane glycerophospholipids (such as phosphatidylcholine and phosphatidylglycerol, among others) are the most studied, and the most promising results are obtained, with decreasing patterns as PMI varies. Fatty acids (FAs) are also identified as potential biomarkers owing to the variations in their postmortem concentration. An increase in saturated fatty acids (SFAs), such as stearic acid and palmitic acid, and a decrease in unsaturated fatty acids (UFAs), such as oleic acid and linoleic acid, were observed. The importance of intrinsic and extrinsic factors in decomposition is also observed. Finally, as for the burial sites, the presence of fatty acids and some sterols in burial areas of animal and human remains can be verified. In conclusion, glycerophospholipids and fatty acids are good markers for estimating PMI. It has been observed that there are still no equations for estimating the PMI that can be applied to forensic practice, as intrinsic and extrinsic factors are seen to play a vital role in the decomposition process. As for determining burial sites, the importance of soil and textile samples has been demonstrated, showing a direct relationship between saturated fatty acids, hydroxy fatty acids, and some sterols with decomposing remains.

Sr-Pb isotope differences in pre- and post-burial human bone, teeth, and hair keratin: implications for isotope forensics

The isotopic signatures of human tissues can provide valuable information on geographic origin for medicolegal investigations involving unidentified persons. It is important to understand the impact of diagenetic processes on isotopic signatures, as alterations could result in incorrect estimation of geographic origin. This study examines alterations in isotope signatures of different tissues of five human body donors studied throughout decomposition at the Forensic Anthropology Research Facility (FARF), San Marcos, TX. Two body donors were buried, two were placed in open pits, and one was first allowed to naturally mummify and then buried. Remains were recovered after a period of 7-34 months. The preplacement and post-recovery Sr-Pb isotope data of scalp hair, bone (iliac and tibia), and tooth enamel and dentine were compared. The hair samples record significant shifts in Sr-Pb isotope compositions, with hair keratin Pb isotope composition shifting towards the Pb signature of local soil samples. Hair keratin Sr isotope compositions were altered by the burial environment and possibly also by the lab sample cleaning method. The spongy iliac bone samples show inconsistencies in the recoverability of the preplacement Sr-Pb isotope signatures. The post-placement signatures of the buried donors show slight elevation over preplacement signatures. The post-placement signatures of donors placed in open pits are significantly elevated. The tibia and dental samples record the most consistent isotopic data with the least alteration. These more densely mineralised elements show good recoverability of the preplacement isotope signatures in burials and open pits and are thus deemed better targets for forensic investigative purposes.

Metabolomics investigation of post-mortem human pericardial fluid

INTRODUCTION

Due to its peculiar anatomy and physiology, the pericardial fluid is a biological matrix of particular interest in the forensic field. Despite this, the available literature has mainly focused on post-mortem biochemistry and forensic toxicology, while to the best of authors' knowledge post-mortem metabolomics has never been applied. Similarly, estimation of the time since death or post-mortem interval based on pericardial fluids has still rarely been attempted.

OBJECTIVES

We applied a metabolomic approach based on 1H nuclear magnetic resonance spectroscopy to ascertain the feasibility of monitoring post-mortem metabolite changes on human pericardial fluids with the aim of building a multivariate regression model for post-mortem interval estimation.

METHODS

Pericardial fluid samples were collected in 24 consecutive judicial autopsies, in a time frame ranging from 16 to 170 h after death. The only exclusion criterion was the quantitative and/or qualitative alteration of the sample. Two different extraction protocols were applied for low molecular weight metabolites selection, namely ultrafiltration and liquid-liquid extraction. Our metabolomic approach was based on the use of 1H nuclear magnetic resonance and multivariate statistical data analysis.

RESULTS

The pericardial fluid samples treated with the two experimental protocols did not show significant differences in the distribution of the metabolites detected. A post-mortem interval estimation model based on 18 pericardial fluid samples was validated with an independent set of 6 samples, giving a prediction error of 33-34 h depending on the experimental protocol used. By narrowing the window to post-mortem intervals below 100 h, the prediction power of the model was significantly improved with an error of 13-15 h depending on the extraction protocol. Choline, glycine, ethanolamine, and hypoxanthine were the most relevant metabolites in the prediction model.

CONCLUSION

The present study, although preliminary, shows that PF samples collected from a real forensic scenario represent a biofluid of interest for post-mortem metabolomics, with particular regard to the estimation of the time since death.

Estimating the time of human decomposition based on skeletal muscle biopsy samples utilizing an untargeted LC-MS/MS-based proteomics approach

Accurate estimation of the postmortem interval (PMI) is crucial in forensic medico-legal investigations to understand case circumstances (e.g. narrowing down list of missing persons or include/exclude suspects). Due to the complex decomposition chemistry, estimation of PMI remains challenging and currently often relies on the subjective visual assessment of gross morphological/taphonomic changes of a body during decomposition or entomological data. The aim of the current study was to investigate the human decomposition process up to 3 months after death and propose novel time-dependent biomarkers (peptide ratios) for the estimation of decomposition time. An untargeted liquid chromatography tandem mass spectrometry-based bottom-up proteomics workflow (ion mobility separated) was utilized to analyse skeletal muscle, collected repeatedly from nine body donors decomposing in an open eucalypt woodland environment in Australia. Additionally, general analytical considerations for large-scale proteomics studies for PMI determination are raised and discussed. Multiple peptide ratios (human origin) were successfully proposed (subgroups < 200 accumulated degree days (ADD), < 655 ADD and < 1535 ADD) as a first step towards generalised, objective biochemical estimation of decomposition time. Furthermore, peptide ratios for donor-specific intrinsic factors (sex and body mass) were found. Search of peptide data against a bacterial database did not yield any results most likely due to the low abundance of bacterial proteins within the collected human biopsy samples. For comprehensive time-dependent modelling, increased donor number would be necessary along with targeted confirmation of proposed peptides. Overall, the presented results provide valuable information that aid in the understanding and estimation of the human decomposition processes.

Proteomics: A New Research Frontier in Forensic Pathology

Proteomics, the study of proteins and their functions, has revolutionized the field of forensic science by providing a powerful approach to identify and characterize proteins for various aims [...].

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.