Estimation of the late postmortem interval using FTIR spectroscopy and chemometrics in human skeletal remains

A methodological approach to age estimation of the intra-puparial period of the forensically relevant blow fly Calliphora vicina via Fourier transform infrared spectroscopy

Estimating the age of immature blow flies is of great importance for forensic entomology. However, no gold-standard technique for an accurate determination of the intra-puparial age has yet been established. Fourier transform infrared (FTIR) spectroscopy is a method to (bio-)chemically characterise material based on the absorbance of electromagnetic energy by functional groups of molecules. In recent years, it also has become a powerful tool in forensic and life sciences, as it is a fast and cost-effective way to characterise all kinds of material and biological traces. This study is the first to collect developmental reference data on the changes in absorption spectra during the intra-puparial period of the forensically important blow fly Calliphora vicina Robineau-Desvoidy (Diptera: Calliphoridae). Calliphora vicina was reared at constant 20°C and 25°C and specimens were killed every other day throughout their intra-puparial development. In order to investigate which part yields the highest detectable differences in absorption spectra throughout the intra-puparial development, each specimen was divided into two different subsamples: the pupal body and the former cuticle of the third instar, that is, the puparium. Absorption spectra were collected with a FTIR spectrometer coupled to an attenuated total reflection (ATR) unit. Classification accuracies of different wavenumber regions with two machine learning models, i.e., random forests (RF) and support vector machines (SVMs), were tested. The best age predictions for both temperature settings and machine learning models were obtained by using the full spectral range from 3700 to 600 cm-1. While SVMs resulted in better accuracies for C. vicina reared at 20°C, RFs performed almost as good as SVMs for data obtained from 25°C. In terms of sample type, the pupal body gave smoother spectra and usually better classification accuracies than the puparia. This study shows that FTIR spectroscopy is a promising technique in forensic entomology to support the estimation of the minimum post-mortem interval (PMImin), by estimating the age of a given insect specimen.

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 time since deposition of semen stain on different fabric types using ATR-FTIR spectroscopy and chemometrics

Various body fluids such as blood, semen, vaginal secretions, and saliva are frequently encountered at crime scene. In cases of sexual assault, semen stains are one of the most reliable evidence of biological origin. In this study, our objective was to develop a method for estimating the time since deposition of semen stains on five different fabric types using Attenuated Total Reflectance-Fourier Transform Infrared (ATR-FTIR) Spectroscopy, with a focus on a time frame of up to 8 weeks. Semen samples from six different volunteers were dripped onto five distinct fabric materials, and ATR-FTIR measurements were obtained at 17 different time points. Principal component analysis (PCA) and partial least squares (PLS) methods were employed to differentiate semen stains on various fabric samples and estimate the age of semen stains. Models constructed using PCA and PLSR achieved high R2 values and low root-mean-square error (RMSE). While the performance varies depending on fabric types, it was observed that age estimation of semen stains can be made within following intervals: 0.39-0.76 days for 0-7 day range, 2.59-3.38 days for the 1-8 week range, and 3.98-8.1 days for the 0-56 day range. This study demonstrates the effectiveness of using ATR-FTIR spectroscopy in combination with chemometrics to estimate the age of human semen stains on various fabric types based on time-dependent spectral changes.

Raman spectroscopy for postmortem interval estimation of human skeletal remains: A scoping review

Estimating postmortem intervals (PMI) is crucial in forensic investigations, providing insights into criminal cases and determining the time of death. PMI estimation relies on expert experience and a combination of thanatological data and environmental factors but is prone to errors. The lack of reliable methods for assessing PMI in bones and soft tissues necessitates a better understanding of bone decomposition. Several research groups have shown promise in PMI estimation in skeletal remains but lack valid data for forensic cases. Current methods are costly, time-consuming, and unreliable for PMIs over 5 years. Raman spectroscopy (RS) can potentially estimate PMI by studying chemical modifications in bones and teeth correlated with burial time. This review summarizes RS applications, highlighting its potential as an innovative, nondestructive, and fast technique for PMI estimation in forensic medicine.

Comparison of DNA preservation and ATR-FTIR spectroscopy indices of cortical and trabecular bone of metacarpals and metatarsals

Shape, size, composition, and function of the bones in the human body vary on the macro, micro and nanoscale. This can influence changes caused by taphonomy and post-mortem preservation, including DNA. Highly mineralised compact bone is less susceptible to taphonomic factors than porous trabecular bone. Some studies imply that DNA can be better preserved in trabecular bone, due to remnants of the soft tissue or bacteria better digesting organic matter while not digesting DNA. The aim of this study was to understand the differences between compact (diaphyses) and trabecular (epiphyses) bone on a molecular level and thus the reasons for the better preservation of the DNA in the trabecular bone. The powder obtained from epiphyses and diaphyses of metacarpals and metatarsals was analysed using ATR-FTIR spectroscopy and compared. Samples with poorest DNA preservation originated from diaphyses, predominantly of metatarsals. They were characterised by higher concentrations of phosphates and crystallinity, while lower collagen quality in comparison to samples with the best DNA preservation. Epiphyses presented higher concentrations of better-preserved collagen while diaphyses had higher concentrations of carbonates and phosphates and higher crystallinity. Due to better-preserved collagen in the epiphyses, the soft tissue remnants hypothesis seems more likely than the bacteria hypothesis.

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.

Differentiating present-day from ancient bones by vibrational spectroscopy upon acetic acid treatment

Acetic acid treatment for an accurate differentiation between ancient and recent human bones was assessed using Raman and FTIR-ATR spectroscopies. Each set of skeletal samples was analysed by these techniques, prior and after chemical washing, in order to determine the variations in bone´s chemical composition and crystallinity. Bone samples were collected from several independent sources: recent bones burned under controlled experimental conditions or cremated, and archaeological (XVII century and Iron Age). The effect of acetic acid, expected to impact mostly on carbonates, was clearly evidenced in the spectra of all samples, particularly in FTIR-ATR, mainly through the bands typical of A- and B-carbonates. Furthermore, as seen for crematoria and archaeological samples, acetic acid was found to remove contaminants such as calcium hydroxide. Overall, acetic acid treatment can be an effective method for removing carbonates (exogenous but possibly also endogenous) and external contaminants from bone. However, these effects are dependent on the skeletal conditions (e.g. post-mortem interval and burning settings). In addition, this chemical washing was shown to be insufficient for an unequivocal discrimination between recent and archaeological skeletal remains. Based on the measured IR indexes, only cremated bones could be clearly distinguished.

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

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

Attenuated total reflection-Fourier transform infrared spectroscopy: a universal analytical technique with promising applications in forensic analyses

Contemporary criminal investigations are based on the statements made by the victim and the eyewitnesses. They also rely on the physical evidences found in the crime scene. These evidences, and more particularly biological ones, have a great judicial value in the courtroom. They are usually used to revoke the suspect’s allegations and confirm or refute the statements made by the victim and the witnesses. Stains of body fluids are biological evidences highly sought by forensic investigators. In many criminal cases, the success of the investigation relies on the correct identification and classification of these stains. Therefore, the adoption of reliable and accurate forensic analytical methods seems to be of vital importance to attain this objective. Attenuated total reflection-Fourier transform infrared spectroscopy (ATR-FTIR) is a modern and universal analytical technique capable of fingerprint recognition of the analyte using minimal amount of the test sample. The current systematic review aims to through light on the fundamentals of this technique and to illustrate its wide range of applications in forensic investigations. ATR-FTIR is a nondestructive technique which has demonstrated an exceptional efficiency in detecting, identifying and discriminating between stains of various types of body fluids usually encountered in crime scenes. The ATR-FTIR spectral data generated from bloodstains can be used to deduce a wealth of information related to the donor species, age, gender, and race. These data can also be exploited to discriminate between stains of different types of bloods including menstrual and peripheral bloods. In addition, ATR-FTIR has a great utility in the postmortem investigations. More particularly, in estimating the postmortem interval and diagnosing death caused by extreme weather conditions. It is also useful in diagnosing some ambiguous death causes such as fatal anaphylactic shock and diabetic ketoacidosis.

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.

Human Remains Identification Using Micro-CT, Chemometric and AI Methods in Forensic Experimental Reconstruction of Dental Patterns after Concentrated Sulphuric Acid Significant Impact

(1) Teeth, in humans, represent the most resilient tissues. However, exposure to concentrated acids might lead to their dissolving, thus making human identification difficult. Teeth often contain dental restorations from materials that are even more resilient to acid impact. This paper aims to introduce a novel method for the 3D reconstruction of dental patterns as a crucial step for the digital identification of dental records. (2) With a combination of modern methods, including micro-computed tomography, cone-beam computer tomography, and attenuated total reflection, in conjunction with Fourier transform infrared spectroscopy and artificial intelligence convolutional neural network algorithms, this paper presents a method for 3D-dental-pattern reconstruction, and human remains identification. Our research studies the morphology of teeth, bone, and dental materials (amalgam, composite, glass-ionomer cement) under different periods of exposure to 75% sulfuric acid. (3) Our results reveal a significant volume loss in bone, enamel, dentine, as well as glass-ionomer cement. The results also reveal a significant resistance by the composite and amalgam dental materials to the impact of sulfuric acid, thus serving as strong parts in the dental-pattern mosaic. This paper also probably introduces the first successful artificial intelligence application in automated-forensic-CBCT segmentation. (4) Interdisciplinary cooperation, utilizing the mentioned technologies, can solve the problem of human remains identification with a 3D reconstruction of dental patterns and their 2D projections over existing ante-mortem records.

Critical aspects of Raman spectroscopy as a tool for postmortem interval estimation

The estimation of the postmortem interval (PMI) from skeletal remains represents a challenging task in forensic science. PMI is often influenced by extrinsic factors (humidity, dryness, scavengers, etc.) and intrinsic factors (age, sex, pathology, way of life, medical treatments, etc.). Raman spectroscopy combined with multivariate data analysis represents a promising tool for forensic anthropologists. Despite all the advantages of the technique, Raman spectra of skeletal remains are influenced by these extrinsic and intrinsic factors, which impairs precision and reproducibility. Both parameters have to reach a high level of confidence when such spectroscopy is used as a way to predict PMI. As a consequence, advanced multivariate data analysis is necessary to quantify the effect of all factors to improve the estimation of the PMI. The objective of this work is to evaluate the effect of intrinsic and extrinsic factors on the Raman spectra of skeletal remains. We designed a protocol close to a real-world scenario. We used ANOVA-simultaneous component analysis (ASCA) to unmix and quantify the effect of 1 intrinsic (source body) and 1 extrinsic (burial time) factors on the Raman spectra. In our model, the burial time was found to generate the highest variability after the source body. ASCA showed that the variability due to the burial time has 2 mixed contributions. Seasonal variations are the first contribution. The second contribution is attributed to diagenesis. A decrease in the mineral bands and an increase in the organic bands are observed. The source body was also found to contribute to the variability in Raman spectra. ASCA showed that the source body induces variability related to the composition of bones. This quantification cannot be assessed by basic chemometrics methods such as PCA. The results of this study highlighted the need to use an advanced chemometric data analysis tool (like ASCA) combined with Raman spectroscopy to estimate the postmortem interval.

Recent advances of vibrational spectroscopy and chemometrics for forensic biological analysis

Biological materials found at a crime scene are crucially important evidence for forensic investigation because they provide contextual information about a crime and can be linked to the donor-individuals through combination with DNA analysis. Applications of vibrational spectroscopy to forensic biological analysis have been emerging because of its advantageous characteristics such as the non-destructivity, rapid measurement, and quantitative evaluation, compared to most current methods based on histological observation or biochemical techniques. This review presents an overview of recent developments in vibrational spectroscopy for forensic biological analysis. We also emphasize chemometric techniques, which can elicit reliable and advanced analytical outputs from highly complex spectral data from forensic biological materials. The analytical subjects addressed herein include body fluids, hair, soft tissue, bones, and bioagents. Promising applications for various analytical purposes in forensic biology are presented. Simultaneously, future avenues of study requiring further investigation are discussed.

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.

Estimation of the post-mortem interval in human bones by infrared spectroscopy

In forensic anthropology, there is an inherent difficulty in estimating the post-mortem interval (PMI). This study aimed to assess whether there is a correlation between changes in the bone mineral component and the PMI estimation. Samples of femur and humerus from 80 identified individuals with known post-mortem interval were analyzed. Infrared spectroscopy in attenuated total reflectance mode (FTIR-ATR) was applied for this analysis, several indices having been obtained from the infrared bands most representative of the bone's relative contents in carbonate and phosphate. Specific relationships between sex/age and PMI were attained: for larger PMIs, there was an increase in the amount of B-type carbonate (BPI), A-type carbonates (API), and in the carbonate/phosphate (C/P) ratio, and a decrease of the crystallinity index (CI) and in the carbonate ratio (C/C). Two particular infrared indices (CI and C/C) were identified as the most suitable for post-mortem interval estimation, especially in females, controlling the effects of sex and age (in the statistical analysis).

Fourier-transform infrared microspectroscopy of pulmonary edema fluid for postmortem diagnosis of diabetic ketoacidosis

Determination of the cause of death for diabetic ketoacidosis (DKA), a common and fatal acute complication of diabetes mellitus, is a challenging forensic task owing to the lack of characteristic morphological findings at autopsy. In this study, Fourier-transform infrared (FTIR) microspectroscopy coupled with chemometrics was employed to characterize biochemical differences in pulmonary edema fluid from different causes of death to supplement conventional methods and provide an efficient postmortem diagnosis of DKA. With this aim, FTIR spectra in three different situations (DKA-caused death, other causes of death with diabetes history, and other causes of death without diabetes history) were measured. The results of principal component analysis indicated different spectral profiles between these three groups, which mainly exhibited variations in proteins. Subsequently, two binary classification models were established using an algorithm of partial least squares discriminant analysis (PLS-DA) to determine whether decedents had diabetes and whether the diabetic patients died from DKA. Satisfactory prediction results of PLS-DA models demonstrated good differentiation among these three groups. Therefore, it is feasible to make a postmortem diagnosis of DKA and detect diabetes history via FTIR microspectroscopic analysis of the pulmonary edema fluid.

Chemometrics in forensic science: approaches and applications

Forensic investigations are often reliant on physical evidence to reconstruct events surrounding a crime. However, there remains a need for more objective approaches to evidential interpretation, along with rigorously validated procedures for handling, storage and analysis. Chemometrics has been recognised as a powerful tool within forensic science for interpretation and optimisation of analytical procedures. However, careful consideration must be given to factors such as sampling, validation and underpinning study design. This tutorial review aims to provide an accessible overview of chemometric methods within the context of forensic science. The review begins with an overview of selected chemometric techniques, followed by a broad review of studies demonstrating the utility of chemometrics across various forensic disciplines. The tutorial review ends with the discussion of the challenges and emerging trends in this rapidly growing field.

Predicting the postmortem interval of burial cadavers based on microbial community succession

Previous studies have demonstrated that microbial community succession during the decomposition of cadavers could be used to estimate the postmortem interval (PMI). However, the vast majority of the existing studies focused on exposed cadavers. In fact, burial cadavers are common scenarios for forensic investigations. In this study, the microbial communities from gravesoil, rectum and skin of burial SD rat cadavers during decomposition were characterized using 16S rRNA gene high-throughput sequencing. We predicted PMI based on the microbial community succession. Obvious differences in microbial community structures were observed between different stages of decomposition. Later decay stages had a lower alpha diversity compared to earlier decay stages. Significant linear relationships between similarities of the microbial communities and postmortem intervals were observed, manifesting regular succession over the course of decomposition. Furthermore, we combined random forest models with postmortem microbial features to predict PMI. The model explained 86.83%, 84.55% and 81.67% of the variation in the microbial community, with a mean absolute error of 1.82, 2.06 and 2.13 days within 60 days of decomposition for gravesoil, rectum and skin of burial cadavers, respectively. Overall, our results suggested that postmortem microbial community data could serve as a potential forensic tool to estimate accurate PMI of burial cadavers.

Age related changes of rib cortical bone matrix and the application to forensic age-at-death estimation

Forensic anthropology includes, amongst other applications, the positive identification of unknown human skeletal remains. The first step in this process is an assessment of the biological profile, that is: sex, age, stature and ancestry. In forensic contexts, age estimation is one of the main challenges in the process of identification. Recently established admissibility criteria are driving researchers towards standardisation of methodological procedures. Despite these changes, experience still plays a central role in anthropological examinations. In order to avoid this issue, age estimation procedures (i) must be presented to the scientific community and published in peer reviewed journals, (ii) accurately explained in terms of procedure and (iii) present clear information about the accuracy of the estimation and possible error rates. In order to fulfil all these requirements, a number of methods based on physiological processes which result in biochemical changes in various tissue structures at the molecular level, such as modifications in DNA-methylation and telomere shortening, racemization of proteins and stable isotopes analysis, have been developed. The current work proposes a new systematic approach in age estimation based on tracing physicochemical and mechanical degeneration of the rib cortical bone matrix. This study used autopsy material from 113 rib specimens. A set of 33 parameters were measured by standard bio-mechanical (nanoindentation and microindentation), physical (TGA/DSC, XRD and FTIR) and histomorphometry (porosity-ImageJ) methods. Stepwise regressions were used to create equations that would produce the best 'estimates of age at death' vs real age of the cadavers. Five equations were produced; in the best of cases an equation counting 7 parameters had an R² = 0.863 and mean absolute error of 4.64 years. The present method meets all the admissibility criteria previously described. Furthermore, the method is experience-independent and as such can be performed without previous expert knowledge of forensic anthropology and human anatomy.

Establishing a minimum PMI for bone sun bleaching in a UK environment with a controlled desert-simulated comparison

Microenvironments play a significant part in understanding the post-mortem interval in forensic taphonomy. Recently, the value of weathering factors in relation to obtaining a PMI has been investigated further. In this study, observations were made to calculate the length of time it takes for three different bone elements (femur, rib, and scapula) to bleach in a UK summer and winter. This research also investigated whether there were any physicochemical modifications to the bone caused by bleaching. Porcine femora, scapulae, and ribs were placed into open and shaded areas of an outdoor research facility located in Oxfordshire, UK, during summer (July-Sep) and winter months (Dec-Mar). The specimens were monitored at 3-week intervals using photography, and an observational scoring method was developed to quantify the extent of bleaching. As temperatures are typically much lower in the UK compared with warmer climates, a controlled indoor-simulated desert experiment was also undertaken to be used as a control. This allowed sun bleaching and changes to the bone chemistry to be monitored in a controlled, high-UV environment for comparison with the UK outdoor experiments. Fourier transform infrared spectroscopy (FTIR) was employed to analyze physicochemical modifications to both the mineral and organic components of the bone. The FTIR was used to calculate crystallinity index (CI), mineral to organic ratio, and the relative amount of carbonate concentrations. Weather data was collected and a positive correlation was found between both ultraviolet (UV) levels and accumulated degree days (ADD) when compared with observational bleaching scores. Bleaching (whitening) of the bone samples occurred in both seasons but at different rates, with the bleaching process occurring at a slower rate in winter. During summer, the initial bleaching process was evident at 6 weeks, and by 9 weeks, the bones were an off-white colour. During the winter period, whitening of the bone started at 9 weeks; however, only the scapula and rib samples displayed a similar off-white colour. This colouration was observed at 13 weeks rather than at 9 weeks. The desert simulation samples started bleaching in a similar pattern to the outdoor samples after 1 week but the bones did not fully bleach. The bone chemistry, based on physicochemical properties obtained from the FTIR, showed a significant statistical difference between the simulated desert and winter season when compared against a control sample. For the winter samples, the mineral to organic ratio was significantly higher than that in the control, suggesting a reduction in the proportion of organic. For the samples in the simulated desert environment, the crystallinity index was significantly higher than that in the control samples, suggesting an increase in crystallinity. The results of this experiment support the fact that it is possible to achieve bleaching in a UK environment and that the minimal time frame for this to occur differs in seasons.

Identification of antemortem, perimortem and postmortem fractures by FTIR spectroscopy based on a rabbit tibial fracture model

The identification of antemortem, perimortem and postmortem fractures is very important for forensic pathologists and anthropologists. However, traditional methods are subjective, time-consuming, and have low accuracy, which do not fundamentally solve the problem. In this study, we utilized Fourier transform infrared (FTIR) spectroscopy and chemometrics to identify antemortem, perimortem and postmortem fractures in a rabbit tibial fracture model. Based on the results of the principal component analysis (PCA), changes in the ante-perimortem fracture repair process are mainly associated with protein variations, while postmortem fractures are more likely to result in lipid changes during degradation. Then, a partial least squares discriminant analysis (PLS-DA) was performed to assess the classification ability of the training and predictive datasets, with classification accuracies of 88.9% and 86.7%, respectively. According to the latent variable 1 (LV1) loading plot, amide I and amide II (proteins) are mostly classified as ante-perimortem and postmortem fractures. In conclusion, FTIR spectroscopy is a reliable tool to identify antemortem, perimortem and postmortem fractures. FTIR has the advantages of rapid, objective and strong discrimination. and shows great potential for analyzing forensic cases under actual natural conditions.

Estimation of the post-mortem interval using microRNA in the bones

MicroRNAs (miRNAs) can be useful in forensic science because of their numerous characteristics, especially stability. Post-mortem interval (PMI) is crucial for death scene investigations. However, estimating PMI is challenging in cases involving significantly decomposed or destroyed bodies, such as those involving skeletonized remains. In this study, 71 bones (patella) were collected from the bodies during autopsies (PMI ranging from 1 day to 2 years). As the let-7e and miR-16 miRNAs were used as internal controls for the bone tissue in previous studies, these miRNAs were selected as targets to estimate PMI. The miRNA Ce_miR-39_1 was used as a spike-in internal control to normalize the target miRNA levels. Real-time quantitative reverse transcription polymerase chain reaction was performed to correlate the expression levels of let-7e and miR-16 with increasing PMI. A negative correlation was observed between miRNA expression and increasing PMI. The expression of both let-7e and miR-16 was observed to be significantly different between group A and the other PMI groups (group A < 1 month; 1 month < group B < 3 months; 3 months < group C < 6 months; group D > 6 months). In conclusion, these data suggest that the expression level of specific miRNAs (let-7e and miR-16) in the bone tissue could be used to estimate PMI. However, more studies using long-term PMI samples are required to further corroborate these findings.

Identifying muscle hemorrhage in rat cadavers with advanced decomposition by FT-IR microspectroscopy combined with chemometrics

The identification of muscle hemorrhage in a cadaver that is in an advanced stage of decomposition is an important but challenging task. Our study investigated whether Fourier transform infrared (FT-IR) microspectroscopy in conjunction with chemometrics could identify muscle hemorrhage using rat cadavers with advanced decomposition. In this study, an intramuscular blood injection method, instead of a mechanical injury method, was used to construct a muscle hemorrhage model, and the modeling idea of muscle hemorrhage identification was to discriminate and classify hemoglobin-leaking myofibrils from negative myofibrils. First, the optical images of hematoxylin/eosin (H&E) stained hemorrhagic muscle at different postmortem intervals (PMIs) were observed and showed that the morphological features of whole erythrocytes disappeared since the PMI of 4 d. Subsequently, principle component analysis (PCA) was performed and indicated that the biochemical differences in protein structures between fresh erythrocytes and myofibrils can be detected by the IR spectroscopic method. Ultimately, several classification models based on the partial least square discriminant analysis (PLS-DA) algorithm were successfully constructed for different PMIs and PMI ranges and achieved great prediction performances in external validations. This preliminary study demonstrates the feasibility of using FT-IR microspectroscopy combined with chemometrics as a potential approach for identifying muscle hemorrhage in cadavers with advanced decomposition for offering vital evidences in judicial process.

Predicting postmortem interval based on microbial community sequences and machine learning algorithms

Microbes play an essential role in the decomposition process but were poorly understood in their succession and behaviour. Previous researches have shown that microbes show predictable behaviour that starts at death and changes during the decomposition process. Research of such behaviour enhances the understanding of decomposition and benefits estimating the postmortem interval (PMI) in forensic investigations, which is critical but faces multiple challenges. In this study, we combined microbial community characterization, microbiome sequencing from different organs (i.e. brain, heart and cecum) and machine learning algorithms [random forest (RF), support vector machine (SVM) and artificial neural network (ANN)] to investigate microbial succession pattern during corpse decomposition and estimate PMI in a mouse corpse system. Microbial communities exhibited significant differences between the death point and advanced decay stages. Enterococcus faecalis, Anaerosalibacter bizertensis, Lactobacillus reuteri, and so forth were identified as the most informative species in the decomposition process. Furthermore, the ANN model combined with the postmortem microbial data set from the cecum, which was the best combination among all candidates, yielded a mean absolute error of 1.5 ± 0.8 h within 24-h decomposition and 14.5 ± 4.4 h within 15-day decomposition. This integrated model can serve as a reliable and accurate technology in PMI estimation.

Estimation of the age of human semen stains by attenuated total reflection Fourier transform infrared spectroscopy: a preliminary study

Semen stain is one of the most important biological evidence at sexual crime scenes. Age estimation of human semen stains plays an important role in forensic work, and it is rarely studied due to lack of well-established methods. In this study, the technique called attenuated total reflection Fourier transform infrared spectroscopy (ATR-FTIR) coupled with advanced chemometric methods was employed to determine the age of semen stains on three different substrates: glass slides, tissues and fabric made of regenerated cellulose fibres up to 6 d. Partial least squares regression (PLSR) was used in conjunction with spectral analysis for age estimation, and the results generated high R² values (cross-validation: 0.81, external validation: 0.74) but a narrow margin of error for root mean square error (RMSE) (RMSE of cross-validation: 0.77 d, RMSE of prediction: 1.02 d). Additionally, our results indicated the robustness of PLSR model was not weaken by the influence of different substrates in this study. Our results indicate that ATR-FTIR, combined with chemometric methods, shows great potential as a convenient and efficient tool for age estimation of semen stains. Moreover, the method could be applied to routine forensic investigations in the future.

Evaluating the effects of causes of death on postmortem interval estimation by ATR-FTIR spectroscopy

Estimating postmortem interval (PMI) is one of the most challenging tasks in forensic practice due to the effects of many factors. Here, attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy combined with chemometrics was utilized to evaluate the effects of causes of death when estimating PMI and to establish a partial least square (PLS) regression model, which can precisely predict PMI under different causes of death. First, the sensitivities to causes of death (brainstem injury, mechanical asphyxia, and hemorrhage shock) of seven kinds of organs were evaluated based on their degrees of cohesion and separation. Then, the liver was selected as the most sensitive organ to establish a PMI estimation model to compare the predicted deviations from different causes of death. It turns out that the cause of death has no significant effect on estimating PMI. Next, a PLS regression model was built with kidney tissues, which have the lowest sensitivity, and this model showed a satisfactory predictive ability and wide applicability. This study demonstrates the feasibility of using ATR-FTIR spectroscopy in conjunction with chemometrics as a powerful alternative for detecting changes in biochemistry and estimating PMI. A new perspective was also provided for evaluating the effect of causes of death when predicting PMI.

Heat-induced Bone Diagenesis Probed by Vibrational Spectroscopy

Complementary vibrational spectroscopic techniques - infrared, Raman and inelastic neutron scattering (INS) - were applied to the study of human bone burned under controlled conditions (400 to 1000 °C). This is an innovative way of tackling bone diagenesis upon burning, aiming at a quantitative evaluation of heat-induced dimensional changes allowing a reliable estimation of pre-burning skeletal dimensions. INS results allowed the concomitant observation of the hydroxyl libration (OHlibration), hydroxyl stretching (ν(OH)) and (OHlibration + ν(OH)) combination modes, leading to an unambiguous assignment of these INS features to bioapatite and confirming hydroxylation of bone's inorganic matrix. The OHlib, ν(OH) and ν4(PO43-) bands were identified as spectral biomarkers, which displayed clear quantitative relationships with temperature revealing heat-induced changes in bone's H-bonding pattern during the burning process. These results will enable the routine use of FTIR-ATR (Fourier Transform Infrared-Attenuated Total Reflectance) for the analysis of burned skeletal remains, which will be of the utmost significance in forensic, bioanthropological and archaeological contexts.

Human and non-human bone identification using FTIR spectroscopy

Human and non-human identification of unknown skeletal remains is of great importance in forensic and anthropologic contexts. However, the traditional morphological methods for bone species identification are subjective or time-consuming. Here, we utilized Fourier transform infrared (FTIR) spectroscopy and chemometric methods to determinate the spectral variances between human and non-human (i.e., pig, goat, and cow) bones. To simulate real forensic situations as much as possible, fresh, boiled, and decomposed bones were included in this study. Principal component analysis (PCA) results illustrated pig bones were more sensitive to the environmental and external factors than other species studied in this work. Thus, pig bone might not be a suitable proxy for human bone in the study of postmortem changes. More importantly, score plots of PCA results showed clear separation with a slight overlap between the human and non-human fresh bones, but it failed to distinguish the boiled and decomposed bones. Then, partial least squares discriminant analysis (PLS-DA) was employed, and both internal and external validations were conducted to assess its classification ability, which resulted in 99.72 and 99.53% accuracy, respectively. According to the loading plots of PCA and PLS-DA, the spectral diversity was mainly due to the inorganic portion (i.e., carbonates and phosphates), which can remain relatively stable under various conditions. As such, our results illustrate that FTIR spectroscopy could serve as a reliable tool to assist in bone species determination and also has great potential in real forensic cases with natural conditions.