Species identification of bloodstains by ATR-FTIR spectroscopy: the effects of bloodstain age and the deposition environment

Determination of time since deposition of bloodstains through NIR and UV-Vis spectroscopy - A critical comparison

Time elapsed since bloodstain deposition is a crucial aspect in forensic investigations, where non-destructive spectroscopic methods play a pivotal role. While extensive research has been conducted by UV-Vis spectroscopy, showcasing its utility in specific cases, there is still a paucity of studies based on NIR spectroscopy, which has the potential to overcome the limitations of the UV-Vis-based methods. To compensate for this disequilibrium, the present study aimed to evaluate the NIR applicability for estimating the age of forensic bloodstains and develop a performance comparison with UV-Vis spectroscopy methods. Capillary blood was sampled and subjected to a 16-day aging, during which it was repeatedly analyzed using both spectroscopic methods. Subsequently, chemometric analysis was applied to process the spectral data and independently assess the methods' performance. Classical preprocessing transforms (i.e., Savitzky-Golay derivatives and SNV transform) were used together with more targeted strategies, such as class centering, whose benefit was highlighted by PCA. Lastly, PLS regression models were computed to evaluate the effectiveness of both spectroscopic methods in estimating the time elapsed since blood trace deposition. Comparable root mean square errors in prediction (RMSEP) - 40 and 55 h for UV-Vis and NIR spectroscopy, respectively - were observed for both techniques, featuring an improvement with respect to the existing literature for NIR spectroscopy. Data fusion strategies for a multi-instrumental platform were also explored, evaluating advantages and disadvantages of low-level and mid-level approaches. The results indicated that NIR spectroscopy integrated with adequate chemometric strategies deserves increased appreciation in forensic bloodstain dating.

Forensic significance of VOCs profiling in decayed ante- and post-mortem injuries by GC×GC-TOF/MS

Accurately identifying and differentiating the types of injuries in decomposed corpses is a major challenge in forensic identification. Forensic investigations involving decomposed cadavers pose challenges in determining the cause of death. Traditional methods often lack conclusive evidence. However, the implementation of advanced analytical techniques, such as comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC × GC-TOF/MS), shows promise in overcoming these limitations, but the potential in this area remains limited. Therefore, this study aims to bridge this gap by exploring the potential of GC × GC-TOF/MS in the analysis of volatile organic compounds (VOCs) changes within decaying ante- and post-mortem injuries.The research emphasizes the forensic significance of VOCs changes in decomposed cadavers. We used GC × GC-TOF/MS analysis to identify the specific volatile compounds in putrefied corpse tissue samples from mice. The GC × GC-TOF/MS analysis results showed that under winter conditions, PC1 explained 57.16% of the variance, and PC2 explained 25.23% of the variance; while under summer conditions, PC1 explained 71.89% of the variance, and PC2 explained 24.49% of the variance. This demonstrates the potential of GC × GC-TOF/MS in identifying specific VOCs present in tissue samples that can serve as potential biomarkers for distinguishing between antemortem and postmortem injury. GC × GC-TOF/MS analysis revealed distinct VOC patterns in both conditions. Comprehensive use of GC × GC-TOF/MS analysis enhances accuracy in identifying and characterizing ante- and post-mortem injuries in decomposed cadavers. This study can significantly contribute to the field of forensic medicine and improve the accuracy of forensic investigations.

Efficacy of chemical digestion methods to reveal undamaged microplastics from planktonic samples

Standardisation and validation of methods for microplastics research is essential. A major methodological challenge is the removal of planktonic organisms from marine water samples allowing for the identification of microplastics associated to planktonic communities. To improve the reproducibility and accuracy of digestion methods for the removal of planktonic biomass, we compared and modified existing chemical digestion methods. These digestion methods included an acidic digestion using nitric acid, alkaline digestions with potassium hydroxide (alkaline 1 digestion) and sodium hydroxide from drain cleaner (alkaline 2 digestion), an oxidative digestion using sodium dodecyl sulfate with hydrogen peroxide, and an enzymatic digestion using enzyme drain clean pellets. Chemical digestion of three densities of zooplankton communities (high, medium, and low) in the presence of five commonly found environmental microplastic pollutants (polyamide, polyethylene, polyethylene terephthalate, polypropylene, and polystyrene) were performed for each treatment. The chemical treatments were assessed for (i) their digestion efficiency of zooplankton communities by different biomass densities, and (ii) their impact on microplastic particles through the comparison of both chemical (Raman spectroscopy) and physical (length, width, and visual) changes, between the pre-treatment and post-treatment microplastic particles. The alkaline 1, alkaline 2 and oxidative methods demonstrated significantly better digestion efficiency (p < 0.05) than the modified enzymatic and acidic treatments. The acidic, alkaline 1, and alkaline 2, treatments caused the most damages to the microplastic particles. We suggest future studies to implement the oxidative digestion method with sodium dodecyl sulfate and hydrogen peroxide because of its high digestion efficiency, and low damage to microplastic particles. This method is similar to the wet peroxide oxidation digestion method used throughout the literature but can be implemented at a lower cost.

Discrimination of human and animal bloodstains using hyperspectral imaging

Blood is the most encountered type of biological evidence in violent crimes and contains pertinent information to a forensic investigation. The false presumption that blood encountered at a crime scene is human may not be realised until after costly and sample-consuming tests are performed. To address the question of blood origin, the novel application of visible-near infrared hyperspectral imaging (HSI) is used for the detection and discrimination of human and animal bloodstains. The HSI system used is a portable, non-contact, non-destructive method for the determination of blood origin. A support vector machine (SVM) binary classifier was trained for the discrimination of bloodstains of human (n = 20) and five animal species: pig (n = 20), mouse (n = 16), rat (n = 5), rabbit (n = 5), and cow (n = 20). On an independent test set, the SVM model achieved accuracy, precision, sensitivity, and specificity values of 96, 97, 95, and 96%, respectively. Segmented images of bloodstains aged over a period of two months were produced, allowing for the clear visualisation of the discrimination of human and animal bloodstains. The inclusion of such a system in a forensic investigation workflow not only removes ambiguity surrounding blood origin, but can potentially be used in tandem with HSI bloodstain age determination methods for rapid on-scene forensic analysis.

Enhancing forensic investigations: Identifying bloodstains on various substrates through ATR-FTIR spectroscopy combined with machine learning algorithms

The forensic analysis of bloodstains on various substrates plays a crucial role in criminal investigations. This study presents a novel approach for analyzing bloodstains using Attenuated Total Reflectance Fourier Transform Infrared spectroscopy (ATR-FTIR) in combination with machine learning. ATR-FTIR offers non-destructive and non-invasive advantages, requiring minimal sample preparation. By detecting specific chemical bonds in blood components, it enables the differentiation of various body fluids. However, the subjective interpretation of the spectra poses challenges in distinguishing different fluids. To address this, we employ machine learning techniques. Machine learning is extensively used in chemometrics to analyze chemical data, build models, and extract useful information. This includes both unsupervised learning and supervised learning methods, which provide objective characterization and differentiation. The focus of this study was to identify human and porcine blood on substrates using ATR-FTIR spectroscopy. The substrates included paper, plastic, cloth, and wood. Data preprocessing was performed using Principal Component Analysis (PCA) to reduce dimensionality and analyze latent variables. Subsequently, six machine learning algorithms were used to build classification models and compare their performance. These algorithms comprise Partial Least Squares Discriminant Analysis (PLS-DA), Decision Trees (DT), Logistic Regression (LR), Naive Bayes Classifier (NBC), Support Vector Machine (SVM), and Neural Network (NN). The results indicate that the PCA-NN model provides the optimal solution on most substrates. Although ATR-FTIR spectroscopy combined with machine learning effectively identifies bloodstains on substrates, the performance of different identification models still varies based on the type of substrate. The integration of these disciplines enables researchers to harness the power of data-driven approaches for solving complex forensic problems. The objective differentiation of bloodstains using machine learning holds significant implications for criminal investigations. This technique offers a non-destructive, simple, selective, and rapid approach for forensic analysis, thereby assisting forensic scientists and investigators in determining crucial evidence related to bloodstains.

Classification of bloodstains deposited at different times on floor tiles using hierarchical modelling and a handheld NIR spectrometer

Bloodstains are commonly encountered at crime scenes, especially on floor tiles, and can be deposited over different periods and intervals. Therefore, it is crucial to develop techniques that can accurately identify bloodstains deposited at different times. This study builds upon a previous investigation and aims to enhance the performance of three distinct hierarchical models (HMs) designed to differentiate and identify stains of human blood (HB), animal blood (AB), and common false positives (CFPs) on nine different types of floor tiles. Soft Independent Modeling Class Analogies (SIMCA), and Partial Least Squares-Discriminant Analysis (PLS-DA) were employed as decision rules in this process. The originally published model was constructed using a training set that included samples with a known time of deposit of six days. This model was then tested to predict samples with various deposition times, including human blood samples aged for 0, 1, 9, 20, 30, and 162 days, as well as animal blood samples aged for 0, 1, 10, 13, 20, 29, 105, and 176 days. To improve the identification of human blood, the models were modified by adding zero-day and one-day-old bloodstains to the original training set. All models showed improvement when fresher samples were included in the training set. The best results were achieved with the hierarchical model that used partial least squares-discriminant analysis as the second decision rule and incorporated one-day-old samples in the training set. This model yielded sensitivity values above 0.92 and specificity values above 0.7 for samples aged between zero and 30 days.

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.

Overcoming obstacles: Analysis of blood and semen stains washed with different chemicals with ATR-FTIR

INTRODUCTION

Blood and semen stains are the most common biological stains encountered at crime scenes. The washing of biological stains is a common application that perpetrators use to spoil the crime scene. With a structured experiment approach, this study aims to investigate the effects of washing with various chemicals on the ATR-FTIR detection of blood and semen stains on cotton.

MATERIALS AND METHODS

On cotton pieces, a total of 78 blood and 78 semen stains were applied, and each group of six stains was immersed or mechanically cleaned in water, 40% methanol, 5% sodium hypochlorite solution, 5% hypochlorous acid solution, 5 g/L soap dissolved pure water, and 5 g/L dishwashing detergent dissolved water. ATR-FTIR spectra gathered from all stains and analyzed with chemometric tools.

RESULTS AND DISCUSSION

According to performance parameters of developed models, PLS-DA is a powerful tool for discrimination of washing chemical for both washed blood and semen stains. Results from this study show that FTIR is promising for use in detecting blood and semen stains that have become invisible to the naked eye due to washing of the findings.

CONCLUSION

Our approach allows blood and semen to be detected on cotton pieces using FTIR combined with chemometrics, even though it is not visible to the naked eye. Washing chemicals also can be distinguished via FTIR spectra of stains.

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.

Correlated mechanochemical maps of Arabidopsis thaliana primary cell walls using atomic force microscope infrared spectroscopy

Spatial heterogeneity in composition and organisation of the primary cell wall affects the mechanics of cellular morphogenesis. However, directly correlating cell wall composition, organisation and mechanics has been challenging. To overcome this barrier, we applied atomic force microscopy coupled with infrared (AFM-IR) spectroscopy to generate spatially correlated maps of chemical and mechanical properties for paraformaldehyde-fixed, intact Arabidopsis thaliana epidermal cell walls. AFM-IR spectra were deconvoluted by non-negative matrix factorisation (NMF) into a linear combination of IR spectral factors representing sets of chemical groups comprising different cell wall components. This approach enables quantification of chemical composition from IR spectral signatures and visualisation of chemical heterogeneity at nanometer resolution. Cross-correlation analysis of the spatial distribution of NMFs and mechanical properties suggests that the carbohydrate composition of cell wall junctions correlates with increased local stiffness. Together, our work establishes new methodology to use AFM-IR for the mechanochemical analysis of intact plant primary cell walls.

Immobilized phytases: an overview of different strategies, support material, and their applications in improving food and feed nutrition

Phytases are the most widely used food and feed enzymes, which aid in nutritional improvement by reducing anti-nutritional factor. Despite the benefits, enzymes usage in the industry is restricted by several factors such as their short life-span and poor reusability, which result in high costs for large-scale utilization at commercial scale. Furthermore, under pelleting conditions such as high temperatures, pH, and other factors, the enzyme becomes inactive due to lesser stability. Immobilization of phytases has been suggested as a way to overcome these limitations with improved performance. Matrices used to immobilize phytases include inorganic (Hydroxypatite, zeolite, and silica), organic (Polyacrylamide, epoxy resins, alginate, chitosan, and starch agar), soluble matrix (Polyvinyl alcohol), and nanomaterials including nanoparticles, nanofibers, nanotubes. Several surface analysis methods, including thermal gravimetric analysis (TGA), differential scanning calorimetry (DSC), and FTIR analysis, have been used to characterize immobilized phytase. Immobilized phytases have been used in a broad range of biotechnological applications such as animal feed, biodegradation of food phytates, preparations of myo-inositol phosphates, and sulfoxidation by vanadate-substituted peroxidase. This article provides information on different matrices used for phytase immobilization from the last two decades, including the process of immobilization and support material, surface analysis techniques, and multifarious biotechnological applications of the immobilized phytases.

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.

Detection of bloodstains using attenuated total reflectance-Fourier transform infrared spectroscopy supported with PCA and PCA-LDA

The most important task in a criminal investigation is to detect and identify the recovered biological stains beyond reasonable scientific doubt and preserve the sample for further DNA analysis. In the light of this fact, many presumptive and confirmatory tests are routinely employed in the forensic laboratories to determine the type of body fluid. However, the currently used techniques are specific to one type of body fluid and hence it cannot be utilized to differentiate multiple body fluids. Moreover, these tests consume the samples in due process, and thus it becomes a great limitation especially considering the fact that samples are recovered in minute quantity in forensic cases. Therefore, such limitations necessitate the use of non-destructive techniques that can be applied simultaneously to all types of bodily fluids and allow sample preservation for further analysis. In the current work, attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy has been used to circumvent the aforementioned limitations. The important factors which could influence the detection of blood such as the effect of substrates, washing/chemical treatment, ageing, and dilution limits on the analysis of blood have been analysed. In addition, blood discrimination from non-blood substance (biological and non-biological in nature) has also been studied. Chemometric technique that is PCA-LDA has been used to discriminate blood from other body fluids and it resulted in 100% accurate classification. Furthermore, blood and non-blood substances including fake blood have also been classified into separate clusters with a 100% accuracy, sensitivity, and specificity. All-inclusive, this preliminary study substantiates the potential application of ATR-FTIR spectroscopy for the non-destructive identification of blood traces in simulated forensic casework conditions with 0% rate of false classification.

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.

The potential of FT-IR spectroscopy for improving healthcare in sepsis - An animal model study

Fourier Transform-Infrared (FT-IR) absorption spectroscopy has been used to investigate pathophysiological changes caused by sepsis. Sepsis has been defined as a potentially fatal organic dysfunction caused by a dysregulated host response to infection and can lead a patient to risk of death. This study used samples consisting of the blood plasma of mice which were induced to sepsis state, compared to a healthy group using FT-IR associated with attenuated total reflectance (ATR) spectroscopy. For statistical analysis, principal components analysis (PCA) and linear discriminant analysis (LDA) were applied, independently, to the second derivative spectra of both the fingerprint (900-1800 cm^-1) and the high wavenumber (2800-3100 cm^-1) regions. The technique efficiently differentiated the blood plasma of the two groups, sepsis and healthy mice, the analysis indicating that fatty acids and lipids in the blood samples could be an important biomarker of sepsis.

Discrimination between human and animal blood by attenuated total reflection Fourier transform-infrared spectroscopy

Forensic chemistry is an important area of analytical chemistry. This field has been rapidly growing over the last several decades. Confirmation of the human origins of bloodstains is important in practical forensics. Current serological blood tests are destructive and often provide false positive results. Here, we report on the development of a nondestructive method that could potentially be applied at the scene for differentiation of human and animal blood using attenuated total reflection Fourier transform-infrared (ATR FT-IR) spectroscopy and statistical analysis. The following species were used to build statistical models for binary human-animal blood differentiation: cat, dog, rabbit, horse, cow, pig, opossum, and raccoon. Three other species (deer, elk, and ferret) were used for external validation. A partial least squares discriminant analysis (PLSDA) was used for classification purposes and showed excellent performance in internal cross-validation (CV). The method was externally validated first using blood samples from new donors of species used in the training data set, and second using donors of new species that were not used to construct the model. Both validations showed excellent results demonstrating potential of the developed approach for nondestructive, rapid, and statistically confident discrimination between human and animal blood for forensic purposes.

Postmortem Diagnosis of Fatal Hypothermia by Fourier Transform Infrared Spectroscopic Analysis of Edema Fluid in Formalin-Fixed, Paraffin-Embedded Lung Tissues

The goal of this study was to investigate whether pulmonary edema could become a specific diagnostic marker for fatal hypothermia using Fourier transform infrared (FTIR) spectroscopy in combination with chemometrics. The spectral profile analysis indicated that hypothermia fatalities associated with pulmonary edema fluid contained more β-sheet protein conformational structures than the control causes of death, which included sudden cardiac death, brain injury, cerebrovascular disease, mechanical asphyxiation, intoxication, and drowning. Subsequently, the results of principal component analysis (PCA) further revealed that the content of β-sheet protein conformational structures in the pulmonary edema fluid was the main discriminatory marker between fatal hypothermia and the other causes of death. Ultimately, a robust postmortem diagnostic model for fatal hypothermia using a partial least-squares discriminant analysis (PLS-DA) algorithm was constructed. Pulmonary edema fluid spectra collected from eight new forensic autopsy cases that did not participate in the construction of the diagnostic model were predicted using the model. The results showed the causes of death of all these eight cases were correctly classified. In conclusion, this preliminary study demonstrates that FTIR spectroscopy in combination with chemometrics could be a promising approach for the postmortem diagnosis of fatal hypothermia.

Detection and discrimination of seminal fluid using attenuated total reflectance Fourier transform infrared (ATR FT-IR) spectroscopy combined with chemometrics

Semen is most frequently encountered body fluid in forensic cases apart from blood especially in sexual assault cases. The presence and absence of semen can help in conviction or exoneration of a suspect by either confirming or refuting the claims put forward by the suspect and the victim. However, in the wake of limited studies on non-destructive and rapid analysis of semen, it is fairly difficult. Therefore, it is an increasing demand to pioneer the application of available analytical methods in such manner that non-destructive, automated, rapid, and reliable identification and discrimination of body fluids can be established. In the present study, such a methodological application of attenuated total reflectance Fourier transform infrared (ATR FT-IR) spectroscopy has been put forward as one of the initial steps towards the identification and discrimination/classification of seminal fluid from vaginal fluid and other human biological as well as non-biological look-alike semen substances using chemometric tools which are principal component analysis (PCA), partial least square regression (PLSR), and linear discriminant analysis (LDA). Effect of other simulated factors such as substrate interference, mixing with other body fluids, dilutions, and washing and chemical treatments to the samples has been studied. PCA resulted in 98.8% of accuracy for the discrimination of seminal fluid from vaginal fluid whilst 100% accuracy was obtained using LDA method. One hundred percent discrimination was achieved to discriminate semen from other biological fluids using PLSR and LDA, and from non-biological substances using PCA-LDA models. Furthermore, results of the effect of substrates, chemical treatment, mixing with vaginal secretions, and dilution have also been described.

Forensic discrimination of menstrual blood and peripheral blood using attenuated total reflectance (ATR)-Fourier transform infrared (FT-IR) spectroscopy and chemometrics

Body fluids are one of the most important pieces of evidence encountered in forensic cases especially in cases of sexual assault. Analysis of such evidence can help to establish a link between the perpetrator, the victim, and the crime scene and thereby assist in crime reconstruction. However, one of the biggest challenges faced by the investigators in sexual assault cases is that of ascertaining the issue of consent of the victim. In this matter, differentiation of menstrual blood (either in dried or stained form) from traumatic peripheral blood can give a potential solution on this particular aspect. A number of studies have been attempted to differentiate these two body fluids using various biochemical and serological methods. However, the methods employed are limited by factors such as sample destructivity and non-specificity, and the methods are susceptible to false positive results. In the present study, the scope of attenuated total reflectance (ATR)-Fourier transform infrared (FT-IR) spectroscopy in discriminating samples of menstrual blood and peripheral blood has been investigated, in combination with chemometric tools such as principal component analysis (PCA), partial least square regression (PLSR), and linear discriminant analysis (LDA). PCA resulted in 93.3% accuracy, whereas PLSR and LDA resulted in 100% accuracy for the discrimination of peripheral blood from menstrual blood. Application of PCA for the discrimination of menstrual blood from vaginal fluid and seminal fluid delivered 100% classification. Similarly, 100% classification was achieved while differentiating between menstrual blood and blood look-alike substances. Furthermore, in the current study, the effect of substrates on the analysis of menstrual blood has also been studied and described. Graphical Abstract.

Postmortem diagnosis of fatal hypothermia/hyperthermia by spectrochemical analysis of plasma

Postmortem diagnosis of extreme-weather-related deaths is a challenging forensic task. Here, we present a state-of-the-art study that employed attenuated total reflection (ATR) Fourier transform infrared (FTIR) spectroscopy in combination with Chemometrics for postmortem diagnosis of fatal hypothermia/hyperthermia by biochemical investigation of plasma in rats. The results of principal component analysis (PCA) and spectral analysis revealed that plasma samples from the fatal hypothermia, fatal hyperthermia, and control groups, are substantially different from each other based on the spectral variations associated with the lipid, carbohydrate and nucleic acid components. Two partial least squares-discriminant analysis (PLS-DA) classification models (hypothermia-nonhypothermia and hyperthermia-nonhyperthermia binary models) with a 100% accuracy rate were constructed. Subsequently, internal cross-validation was performed to assess the robustness of these two models, which resulted in 98.1 and 100% accuracy. Ultimately, classification predictions of 42 unknown plasma samples were performed by these two models, and both models achieved 100% accuracy. Additionally, our results demonstrated that hemolysis and postmortem hypothermic/hyperthermic effects did not weaken the prediction ability of these two classification models. In summary, this work demonstrates ATR-FTIR spectroscopy's great potential for postmortem diagnosis of fatal hypothermia/hyperthermia.

Applicability of FTIR-ATR Method to Measure Carbonyls in Blood Plasma after Physical and Mental Stress

Introduction

Oxidative stress is a state of imbalance between the production of reactive oxygen species and antioxidant defenses. It results in the oxidation of all cellular elements and, to a large extent, proteins, causing inter alia the formation of carbonyl groups in their structures. The study focused on assessment of changes in the plasma protein-bound carbonyls in police horses after combat training and after rest and the applicability of infrared spectroscopy with a Fourier transform, utilizing the attenuated total reflectance (FTIR-ATR) in detecting plasma protein oxidation.

Methods

We evaluated the influence of both the different concentrations of hydrogen peroxide and combat training on protein carbonylation in horse blood plasma. The oxidation of plasma proteins was assessed using a spectrophotometric method based on the carbonyl groups derivatization with 2,4-dinitrophenylhydrazine (DNPH). The measured values were correlated with the carbonyl groups concentrations determined by means of the FTIR-ATR method.

Results

The linear correlation between the DNPH and FTIR-ATR methods was shown. The concentration of plasma protein-bound carbonyls significantly deceased in police horses after one-day rest when compared to the values measured directly after the combat training (a drop by 23%, p<0.05 and 29%, p<0.01 measured by DNPH and FTIR-ATR methods, respectively). These results were consistent with the proteins phosphorylation analysis.

Conclusion

The FTIR-ATR method may be applied to measure the level of plasma proteins peroxidation.

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.