In the pursuit of the holy grail of forensic science – Spectroscopic studies on the estimation of time since deposition of bloodstains

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.

Raman Spectroscopy for the Time since Deposition Estimation of a Menstrual Bloodstain

Forensic chemistry plays a crucial role in aiding law enforcement investigations by applying analytical techniques for the analysis of evidence. While bloodstains are frequently encountered at crime scenes, distinguishing between peripheral and menstrual bloodstains presents a challenge. This is due to their similar appearance post-drying. Raman spectroscopy has emerged as a promising technique capable of discriminating between the two types of bloodstains, offering invaluable probative information. Moreover, estimating the time since deposition (TSD) of bloodstains aids in crime scene reconstruction and prioritizing what evidence to collect. Despite extensive research focusing on TSD estimations, primarily in peripheral bloodstains, a crucial gap exists in determining the TSD of menstrual bloodstains. This study demonstrates how Raman spectroscopy effectively analyzes biological samples like menstrual blood, showing similar aging patterns to those of peripheral blood and provides proof-of-concept models for determining the TSD of menstrual blood. While this work shows promising results for creating a universal model for bloodstain age determination, further testing with more donors needs to be conducted before the implementation of this method into forensic practice.

Alkaline Phosphatase for Estimating the Time since Deposition of Blood Fingerprints by Scanning Electrochemical Microscopy

Blood is one of the most frequent and valuable traces encountered at crime scenes, where knowing the time since deposition (TSD) of bloodstains tremendously assists forensic experts to screen out crime-related evidence and aids in the reconstruction of the event sequence. Although increasing proof-of-concept methodologies for investigating the TSD of bloodstains have been reported, there is still no accepted strategy in forensic practice as the aging mechanism involves complex components, leading to the inaccuracy of the estimation results. Herein, an endogenous biomarker of alkaline phosphatase (ALP) was chosen to investigate the TSD by scanning electrochemical microscopy (SECM). Results demonstrate that the ALP activity acquired via SECM lateral scan assay exhibited a clear decrease over time, and a similar trend was observed on both poly(vinylidene fluoride) (PVDF) membrane and glass, with the aging kinetics on PVDF membrane being faster than glass. By means of quantitatively calculating the flux of generated p-aminophenol (PAP), we established the aging curve and realized the TSD estimation of blood fingerprints (BFPs) that was unable to be distinguished via optical measurements. Intriguingly, the as-obtained estimation accuracy ranged from 74.6 to 93.7%, proving the possibility of using an ALP biomarker and SECM. More appealingly, the predicted TSDs were capable of accurately differentiating the deposition sequence of overlapping BFPs, which was hardly achieved by optical means. Therefore, this proof-of-concept strategy demonstrates the value of SECM as a forensic tool and opens possibilities for revealing multidimensional information about crime.

Untargeted Metabolomics Profiling for Determination of the Time since Deposition of Biofluids in a Forensic Context: A Proof-of-Concept for Urine, Saliva, and Semen in Addition to Blood

In a criminal trial, the reconstruction of a crime is one of the fundamental steps of the prosecution process. Common questions, such as what happened, where and how it happened, and who made it happen, need to be solved. Biological evidence at crime scenes can be crucial in the determination of these fundamental questions. One of the more challenging riddles to solve is the when? A trace left at a crime scene can prove a person's presence at the crime scene. Knowledge about when it was deposited there, the time since deposition (TsD), would allow linking the person in space and time to the site. This could fortify allegations against a suspect or discharge accusations if proven to be outside of the temporal boundaries where a suspected crime had occurred. Determining the TsD has yet to become routine forensic casework, despite recent research efforts, especially for blood traces. However, next to blood, other biological traces are also commonly encountered in crime scenes. We here present a study to profile the metabolomes of artificially aged dried body fluid spots of blood, semen, saliva, and urine over 4 weeks by liquid chromatography high-resolution mass spectrometry and data-dependent acquisition. All four body fluids (BFs) exhibited diverse time-dependent changes, and a large number of molecular features (MF) were associated with TsD. Still, significant differences between the BFs were observed, limiting universal interpretability independent of the BF and facilitating a need to further study time-dependent changes of different BFs individually toward the goal of TsD estimation.

Establishment of a random forest regression model to estimate the age of bloodstains based on temporal colorimetric analysis

Bloodstain age estimation is important in forensic science. Although several studies have used spectroscopy to estimate bloodstain ages, this method has not yet been practically applied due to the need for expensive equipment and low reproducibility. Thus, we aimed to develop a bloodstain age estimation model that can be easily performed using a spectrophotometric colorimeter. First, bloodstains were prepared by placing blood obtained from five healthy volunteers on a plastic plate. The bloodstains were kept on conditions with various brightness and temperatures. Then, each bloodstain was dissolved in saline every 24 h to a final concentration of 1%, measured with a spectrophotometric colorimeter, and subjected to machine learning to generate a random forest regression (RFR) model, and finally, the prediction accuracy of the bloodstain age was verified. We also elucidated the mechanism of the color changes utilizing aminoguanidine, which is an inhibitor of Maillard reaction. Finally, we measured the time-dependent color changes of the blood fluids obtained from healthy volunteers and examined if the method could be potentially applied to estimate postmortem interval (PMI). Our results showed that the RFR model estimated the bloodstain age with no substantial assessment, and it was applicable to bloodstains, regardless of the brightness or temperature. The color changes were affected by the addition of aminoguanidine. Furthermore, the method could be applied to blood fluids, suggesting its potential usefulness for PMI estimation. Considering its feasibility, the present method could potentially be introduced to practical forensic sciences in the near future.

Optical profilometry for forensic bloodstain imaging

Understanding the physical, chemical and biological changes that occur during the drying of a bloodstain is important in many aspects of forensic science including bloodstain pattern analysis and time since deposition estimation. This research assesses the use of optical profilometry to analyze changes in the surface morphology of degrading bloodstains created using three different volumes (4, 11, and 20 μL) up to 4 weeks after deposition. We analyzed six surface characteristics, including surface average roughness, kurtosis, skewness, maximum height, number of cracks and pits, and height distributions from the topographical scans obtained from bloodstains. Full and partial optical profiles were obtained to examine long-term (minimum of 1.5-h intervals) and short-term (5-min intervals) changes. The majority of the changes in surface characteristics occurred within the first 35 min after bloodstain deposition, in agreement with current research in bloodstain drying. Optical profilometry is a nondestructive and efficient method to obtain surface profiles of bloodstains, and can be integrated easily into additional research workflows including but not limited to time since deposition estimation. Optical profilometry is a non-contact tool to scan bloodstains in ambient conditions Drying phases are observable in small drip bloodstains Significant surface morphology changes occur within 35 min after deposition.

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.

Elemental and molecular characterization of degrading blood pools

Blood is a commonly encountered type of biological evidence and can provide critical information about the crime that occurred. The ability to accurately and precisely determine the time since deposition (TSD) of a bloodstain is highly sought after in the field of forensic science. Current spectral methods for determining TSD are typically developed using small volume bloodstains, we investigate the applicability to larger volume blood pools where drying and degradation mechanics are different. We explored the differences that exist between the surface and bulk of dried segments from fragments collected from 15 mL dried blood pools and identified heterogeneity using RGB colour analysis and hierarchical cluster analysis (HCA). The physical, molecular, and atomic differences between the layers were further investigated using scanning electron microscopy (SEM), X-Ray photoelectron spectroscopy (XPS), attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy, and Raman spectroscopy. SEM identified different morphology on the surface and the bulk indicative of density-dependant cellular settling. XPS revealed that iron was not present on the surface but rather was present in the bulk where the red blood cells had settled. The oxidation state of the iron was quantified over three weeks in which it transitioned from entirely Fe2+ to primarily Fe3+, as expected for ex vivo degradation of hemoglobin. Further, indications of amide saponification occurring at the blood-air interface were identified in the increased quantity of the C-O moiety relative to CO, and the formation of free amines and OC-ONa groups over time. ATR-FTIR and Raman spectroscopy provided insights into differences in the molecular composition of the layers, suggesting that the surface consists of more nucleic acids, lipids, and glycoproteins than the bulk, which was dominated by proteins (p < 0.001% using principal component analysis (PCA)). Additionally, spectral band trends previously reported to have applicability to the estimation of TSD were observed for the bulk portion of the blood pool as the Hb underwent predictable time dependant changes from oxyHb to metHb. PCA was performed based on all spectral data which demonstrated statistically significant differences between the surface and bulk, as well as proof-of-concept for linear TSD estimation models.

Quantitative PCR analysis of bloodstains of different ages

An accurate method to estimate the age of a stain or the time since deposition (TsD) would represent an important tool in police investigations for evaluating the true relevance of a stain. In this study, two laboratories reproduced an mRNA-based method for TsD estimation published by another group. The qPCR-based assay includes four transcripts (B2M, LGALS2, CLC, and S100A12) and showed preferential degradation of the 5' end over the 3' end. In this study, the blood-specific marker ALAS2 was added to examine whether it would show the same degradation pattern. Based on our qPCR data several elastic net models with different penalty combinations were created, using training data from the two laboratories separately and combined. Each model was then used to estimate the age of bloodstains from two independent test sets each laboratory had prepared. The elastic net model built on both datasets with training samples up to 320 days old displayed the best prediction performance across all test samples (MAD=18.9 days). There was a substantial difference in the prediction performance for the two laboratories: Restricting TsD to up to 100 days for test data, one laboratory obtained an MAD of 2.0 days when trained on its own data, whereas the other laboratory obtained an MAD of 15 days.

Discovery and validation of metabolite markers in bloodstains for bloodstain age estimation

Bloodstain age estimation involves measuring time-dependent changes in the levels of biomolecules in bloodstains. Although several studies have identified bloodstain metabolites as markers for estimating bloodstain age, none have considered sex, age-related metabolomic differences, or long-time bloodstain age. Therefore, we aimed to identify metabolite markers for estimating the age of bloodstains at weekly intervals within 28 days and validate them through multiple reaction monitoring. Adenosine 5'-monophosphate, choline, and pyroglutamic acid were selected as markers. Seven metabolites were validated, including five previously reported metabolites, ergothioneine, hypoxanthine, L-isoleucine, L-tryptophan, and pyroglutamic acid. Choline and hypoxanthine can be used to differentiate bloodstains between days 0 and 14 after deposition at weekly intervals, whereas L-isoleucine and L-tryptophan can help distinguish bloodstains between 7 days before and 14 days after deposition. Evaluation of the changes in metabolite levels according to sex and age revealed that the average levels of all seven metabolites were higher in women on day 0. Moreover, the level of ergothioneine was significantly higher in elderly individuals than in young individuals at all time points. In this study, we confirmed the potential effectiveness of metabolites in bloodstains as forensic markers and provided a new perspective on metabolomic approaches linked to forensic science.

Nucleic Acids Persistence-Benefits and Limitations in Forensic Genetics

The analysis of genetic material may be the only way to identify an unknown person or solve a criminal case. Often, the conditions in which the genetic material was found determine the choice of the analytical method. Hence, it is extremely important to understand the influence of various factors, both external and internal, on genetic material. The review presents information on DNA and RNA persistence, depending on the chemical and physical factors affecting the genetic material integrity. One of the factors taken into account is the time elapsing to genetic material recovery. Temperature can both preserve the genetic material or lead to its rapid degradation. Radiation, aquatic environments, and various types of chemical and physical factors also affect the genetic material quality. The substances used during the forensic process, i.e., for biological trace visualization or maceration, are also discussed. Proper analysis of genetic material degradation can help determine the post-mortem interval (PMI) or time since deposition (TsD), which may play a key role in criminal cases.

BloodNet: An attention-based deep network for accurate, efficient, and costless bloodstain time since deposition inference

The time since deposition (TSD) of a bloodstain, i.e., the time of a bloodstain formation is an essential piece of biological evidence in crime scene investigation. The practical usage of some existing microscopic methods (e.g., spectroscopy or RNA analysis technology) is limited, as their performance strongly relies on high-end instrumentation and/or rigorous laboratory conditions. This paper presents a practically applicable deep learning-based method (i.e., BloodNet) for efficient, accurate, and costless TSD inference from a macroscopic view, i.e., by using easily accessible bloodstain photos. To this end, we established a benchmark database containing around 50,000 photos of bloodstains with varying TSDs. Capitalizing on such a large-scale database, BloodNet adopted attention mechanisms to learn from relatively high-resolution input images the localized fine-grained feature representations that were highly discriminative between different TSD periods. Also, the visual analysis of the learned deep networks based on the Smooth Grad-CAM tool demonstrated that our BloodNet can stably capture the unique local patterns of bloodstains with specific TSDs, suggesting the efficacy of the utilized attention mechanism in learning fine-grained representations for TSD inference. As a paired study for BloodNet, we further conducted a microscopic analysis using Raman spectroscopic data and a machine learning method based on Bayesian optimization. Although the experimental results show that such a new microscopic-level approach outperformed the state-of-the-art by a large margin, its inference accuracy is significantly lower than BloodNet, which further justifies the efficacy of deep learning techniques in the challenging task of bloodstain TSD inference. Our code is publically accessible via https://github.com/shenxiaochenn/BloodNet. Our datasets and pre-trained models can be freely accessed via https://figshare.com/articles/dataset/21291825.

Internal standard metabolites for estimating origin blood volume of bloodstains

The volume of blood leaked from blood vessels may change due to evaporation of water under the natural influence of the external environment. Bloodstains and dried blood spots (DBS), which describes blood dried in the external environment, are similar in their production and their metabolite quantification profiles. In both bloodstain metabolite analysis in the forensic science field and DBS metabolite analysis in the clinical field, it is important to determine the volume of the origin blood as this affects metabolite quantification results. Therefore, the purpose of this study is to discover the internal standard metabolites that have quantitatively proportional relationships with origin blood volume and maintain constant concentrations even as the age of the bloodstain increases. As a result, the concentrations of L-isoleucine and L-phenylalanine increased in proportion to the origin blood volume of the bloodstain. The differences in concentration of L-isoleucine were significant in all volume comparisons except in the comparison between 65 μL and 85 μL. The differences in concentration of L-phenylalanine were significant in all volume comparisons except between 65 μL and 45 μL and between 65 μL and 85 μL. In addition, it was confirmed that both metabolites tended to maintain constant concentrations without being affected by bloodstain age as the volume became smaller. These internal standard metabolites can be used for estimating the origin blood volume of bloodstains during metabolite analysis of bloodstains and DBS and could provide a volume criterion for standardization when comparing metabolite quantification between samples.

Whole-genome sequencing of artificial single-nucleotide variants induced by DNA degradation in biological crime scene traces

The aim of this study was to identify artificial single-nucleotide variants (SNVs) in degraded trace DNA samples. In a preliminary study, blood samples were stored for up to 120 days and whole-genome sequencing was performed using the Snakemake workflow dna-seq-gatk-variant-calling to identify positions that vary between the time point 0 sample and the aged samples. In a follow-up study on blood and saliva samples stored under humid and dry conditions, potential marker candidates for the estimation of the age of a blood stain (= time since deposition) were identified. Both studies show that a general decrease in the mean fragment size of the libraries over time was observed, presumably due to the formation of abasic sites during DNA degradation which are more susceptible to strand breaks by mechanical shearing of DNA. Unsurprisingly, an increase in the number of failed genotype calls (no coverage) was detected over time. Both studies indicated the presence of artificial SNVs with the majority of changes happening at guanine and cytosine positions. This confirms previous studies and can be explained by depurination through hydrolytic attacks which more likely deplete guanine while deamination leads to cytosine to thymine variants. Even complete genotype switches from homozygote 0/0 genotypes to the opposite 1/1 genotypes were observed. While positions with such drastic changes might provide suitable candidate markers for estimating short-term time since deposition (TsD), 11 markers were identified which show a slower gradual change of the relative abundance of the artificial variant in both blood and saliva samples, irrespective of storage conditions.

Validation of the Metabolite Ergothioneine as a Forensic Marker in Bloodstains

Ergothioneine, which is a naturally occurring metabolite, generally accumulates in tissues and cells subjected to oxidative stress, owing to its structural stability at physiological pH; therefore, it has been attracting attention in various biomedical fields. Ergothioneine has also been suggested as a potential forensic marker, but its applicability has not yet been quantitatively validated. In this study, quantitative analysis of ergothioneine in bloodstains was conducted to estimate the age of bloodstains and that of bloodstain donors. Blood from youth and elderly participants was used to generate bloodstains. After extracting metabolites from the bloodstains under prevalent age conditions, ergothioneine levels were quantified by mass spectrometry via multiple reaction monitoring. The concentration of ergothioneine in day 0 bloodstains (fresh blood), was significantly higher in the elderly group than in the youth group, but it did not differ by sex. Statistically significant differences were observed between the samples from the two age groups on days 0, 5 and 7, and on days 2 and 3 compared with day 0. The findings suggest that ergothioneine can be used to estimate the age of bloodstains and of the donor; it could be useful as a potential marker in reconstructing crime scenes.

Bloodstain Metabolite Markers: Discovery and Validation for Estimating Age of Bloodstain within 7 Days

Metabolomic research using analytical chemistry methods has been carried out in a wide range of research fields. However, research combining forensic science and metabolomics is rare. Determining the age of bloodstains could provide key information regarding when a crime was committed. Currently, validated methods for estimating the age of bloodstains are unavailable. Metabolites are intermediate and final products of chemical reactions. Therefore, they are less likely to be degraded than other components of blood under field conditions. In this study, metabolites in bloodstains were analyzed using liquid chromatography-mass spectrometry to discover and validate metabolic markers for determining the age of bloodstains within a week post-bleeding. Nontargeted analysis of bloodstain metabolites revealed statistically significant differences over time. Quantitative analysis of identified candidates via multiple reaction monitoring confirmed the statistical significance according to the age of bloodstain. Pyroglutamic acid, l-glutamine, acetylcarnitine, and adenosine 5'-monophosphate were selected as the final markers. The content of each marker exhibited a statistically significant and consistent tendency to decrease with the age of bloodstain. Furthermore, the effect of hemolysis was considered according to the blood fraction spots of the four markers. This study is the first to identify and validate metabolite markers that may help determine the age of bloodstains within a week post-bleeding. If applied to crime scenes as indicators of the age of bloodstains, they can be used as innovative and important tools for reconstructing crime scenes, suggesting initial investigative direction. This study highlights the forensic utility of blood metabolites ex vivo.

Using total RNA quality metrics for time since deposition estimates in degrading bloodstains

The physicochemical changes occurring in biomolecules in degrading bloodstains can be used to approximate the time since deposition (TSD) of bloodstains. This would provide forensic scientists with critical information regarding the timeline of the events involving bloodshed. Our study aims to quantify the timewise degradation trends and temperature dependence found in total RNA from bloodstains without the use of amplification, expanding the scope of the RNA TSD research which has traditionally targeted mRNA and miRNA. Bovine blood with ACD-A anticoagulant was deposited and stored in plastic microcentrifuge tubes at 21 or 4°C and tested over different timepoints spanning 1 week. Total RNA was extracted from each sample and analyzed using automated high sensitivity gel electrophoresis. Nine RNA metrics were visually assessed and quantified using linear and mixed models. The RNA Integrity Number equivalent (RINe) and DV200 were not influenced by the addition of anticoagulant and demonstrated strong negative trends over time. The RINe model fit was high (R²  = 0.60), and while including the biological replicate as a random effect increased the fit for all RNA metrics, no significant differences were found between biological replicates stored at the same temperature for the RINe and DV200. This suggests that these standardized metrics can be directly compared between scenarios and individuals, with DV200 having an inflection point at approximately 28 h. This study provides a novel approach for blood TSD research, revealing metrics that are not affected by inter-individual variation, and improving our understanding of the rapid RNA degradation occurring in bloodstains.

Hierarchical classification models and Handheld NIR spectrometer to human blood stains identification on different floor tiles

One of the most important types of evidence in certain criminal investigations is traces of human blood. For a detailed investigation, blood samples must be identified and collected at the crime scene. The present study aimed to evaluate the potential of the identification of human blood in stains deposited on different types of floor tiles (five types of ceramics and four types of porcelain tiles) using a portable NIR instrument. Hierarchical models were developed by combining multivariate analysis techniques capable of identifying traces of human blood (HB), animal blood (AB) and common false positives (CFP). The spectra of the dried stains were obtained using a portable MicroNIR spectrometer (Viavi). The hierarchical models used two decision rules, the first to separate CFP and the second to discriminate HB from AB. The first decision rule, used to separate the CFP, was based on the Q-Residual criterion considering a PCA model. For the second rule, used to discriminate HB and AB, the Q-Residual criterion were tested as obtained from a PCA model, a One-Class SIMCA model, and a PLS-DA model. The best results of sensitivity and specificity, both equal to 100%, were obtained when a PLS-DA model was employed as the second decision rule. The hierarchical classification models built for these same training sets using a PCA or SIMCA model also obtained excellent sensitivity results for HB classification, with values above 94% and 78% of specificity. No CFP samples were misclassified. Hierarchical models represent a significant advance as a methodology for the identification of human blood stains at crime scenes.

Using the likelihood ratio in bloodstain pattern analysis

There is an apparent paradox that the likelihood ratio (LR) approach is an appropriate measure of the weight of evidence when forensic findings have to be evaluated in court, while it is typically not used by bloodstain pattern analysis (BPA) experts. This commentary evaluates how the scope and methods of BPA relate to several types of evaluative propositions and methods to which LRs are applicable. As a result of this evaluation, we show how specificities in scope (BPA being about activities rather than source identification), gaps in the underlying science base, and the reliance on a wide range of methods render the use of LRs in BPA more complex than in some other forensic disciplines. Three directions are identified for BPA research and training, which would facilitate and widen the use of LRs: research in the underlying physics; the development of a culture of data sharing; and the development of training material on the required statistical background. An example of how recent fluid dynamics research in BPA can lead to the use of LR is provided. We conclude that an LR framework is fully applicable to BPA, provided methodic efforts and significant developments occur along the three outlined directions.

Calcium-Alginate Tissue Gels (CATG): Proof-of-concept biomaterial development

Hydrogels are desirable materials to the field of forensic science and offer many advantages for use as tissue simulants in research and training scenarios. In this work, we demonstrate a proof-of-concept study for our biomaterial described as the Calcium-Alginate Tissue Gel (CATG). CATG biomaterials integrate functional DNA strands designed to amplify with known human primer sets for genetic profiling. Our range of CATG materials demonstrate successful DNA extraction, PCR amplification and genotyping when both fresh and aged for 21 days. The rheological properties of the CATGs were measured and the incorporation of DNA into the CATGs was assessed. Overall, the CATGs demonstrated increased viscoelastic behavior with the addition of DNA. In addition, two methods of sampling were considered, where it was found that cutting a sample of the dried CATG produced higher allele peak heights in the genotype compared to swabbing. Overall, our CATG biomaterials can be designed for multiple applications in forensic science with tunable properties for various training and research needs.

Short and Long Time Bloodstains Age Determination by Colorimetric Analysis: A Pilot Study

Bloodstains found at crime scenes represent a crucial source of information for investigative purposes. However, in forensic practice, no technique is currently used to estimate the time from deposition of bloodstains. This preliminary study focuses on the age estimation of bloodstains by exploiting the color variations over time due to the oxidation of the blood. For this purpose, we used a colorimetric methodology in order to easily obtain objective, univocal and reproducible results. We developed two bloodstain age prediction algorithms: a short-term and a long-term useful model for the first 24h and 60 days, respectively. Both models showed high levels of classification accuracy, particularly for the long-term model. Although a small-scale study, these results improve the potential application of colorimetric analysis in the time-line reconstruction of violent criminal events.

Comparison of photoacoustic imaging and histopathological examination in determining the dimensions of 52 human melanomas and nevi ex vivo

Surgical excision followed by histopathological examination is the gold standard for the diagnosis and staging of melanoma. Reoperations and unnecessary removal of healthy tissue could be reduced if non-invasive imaging techniques were available for presurgical tumor delineation. However, no technique has gained widespread clinical use to date due to shallow imaging depth or the absence of functional imaging capability. Photoacoustic (PA) imaging is a novel technology that combines the strengths of optical and ultrasound imaging to reveal the molecular composition of tissue at high resolution. Encouraging results have been obtained from previous animal and human studies on melanoma, but there is still a lack of clinical data. This is the largest study of its kind to date, including 52 melanomas and nevi. 3D multiwavelength PA scanning was performed ex vivo, using 59 excitation wavelengths from 680 nm to 970 nm. Spectral unmixing over this broad wavelength range, accounting for the absorption of several tissue chromophores, provided excellent contrast between healthy tissue and tumor. Combining the results of spectral analysis with spatially resolved information provided a map of the tumor borders in greater detail than previously reported. The tumor dimensions determined with PA imaging were strongly correlated with those determined by histopathological examination for both melanomas and nevi.

Post deposition aging of bloodstains probed by steady-state fluorescence spectroscopy

Blood is one of the most common body fluids discovered at crime scenes involving violent actions. It is one of the most important types of forensic evidence since it allows for the identification of the individual providing that there is a match with a known DNA profile. Determining the time since deposition (TSD) can assist investigators in establishing when the crime occurred or if a bloodstain present is actually related to the investigated event. To develop a forensically sound method for determining the TSD of a bloodstain, it is necessary to understand the underlying biochemical mechanisms occurring during aging. As biochemical processes occurring in blood are necessary for the continued survival of living organisms, they are important subjects of human biology and biomedicine and are well understood. However, the biochemistry of bloodstain aging ex vivo is primarily of interest to forensic scientists and has not yet been thoroughly researched. This preliminary study utilizes steady-state fluorescence spectroscopy to probe the changes in fluorescence properties of peripheral and menstrual blood up to 24-h post deposition. Peripheral and menstrual blood exhibited similar kinetic changes over time, assigned to the presence of the fluorophores: tryptophan, nicotinamide adenine dinucleotide (NADH), and flavins in both biological fluids. The biochemical mechanism of blood aging ex vivo is discussed.

Analysis of the ex-vivo transformation of semen, saliva and urine as they dry out using ATR-FTIR spectroscopy and chemometric approach

The ex-vivo biochemical changes of different body fluids also referred as aging of fluids are potential marker for the estimation of Time since deposition. Infrared spectroscopy has great potential to reveal the biochemical changes in these fluids as previously reported by several researchers. The present study is focused to analyze the spectral changes in the ATR-FTIR spectra of three body fluids, commonly encountered in violent crimes i.e., semen, saliva, and urine as they dry out. The whole analytical timeline is divided into relatively slow phase I due to the major contribution of water and faster Phase II due to significant evaporation of water. Two spectral regions i.e., 3200–3400 cm⁻¹ and 1600–1000 cm⁻¹ are the major contributors to the spectra of these fluids. Several peaks in the spectral region between 1600 and 1000 cm⁻¹ showed highly significant regression equation with a higher coefficient of determination values in Phase II in contrary to the slow passing Phase I. Principal component and Partial Least Square Regression analysis are the two chemometric tool used to estimate the time since deposition of the aforesaid fluids as they dry out. Additionally, this study potentially estimates the time since deposition of an offense from the aging of the body fluids at the early stages after its occurrence as well as works as the precursor for further studies on an extended timeframe.

A dataset for evaluating blood detection in hyperspectral images

The sensitivity of imaging spectroscopy to haemoglobin derivatives makes it a promising tool for detecting blood. However, due to complexity and high dimensionality of hyperspectral images, the development of hyperspectral blood detection algorithms is challenging. To facilitate their development, we present a new hyperspectral blood detection dataset. This dataset, published under an open access license, consists of multiple detection scenarios with varying levels of complexity. It allows to test the performance of Machine Learning methods in relation to different acquisition environments, types of background, age of blood and presence of other blood-like substances. We have explored the dataset with blood detection experiments, for which we have used a hyperspectral target detection algorithm based on the well-known Matched Filter detector. Our results and their discussion highlight the challenges of blood detection in hyperspectral data and form a reference for further works.

Dual-DMD hyperspectral spatial frequency domain imaging (SFDI) using dispersed broadband illumination with a demonstration of blood stain spectral monitoring

Spatial frequency domain imaging (SFDI) is a widefield diffuse optical measurement technique capable of generating 2D maps of sub-surface absorption and scattering in biological tissue. We developed a new hyperspectral SFDI instrument capable of collecting images at wavelengths from the visible to the near infrared. The system utilizes a custom-built monochromator with a digital micromirror device (DMD) that can dynamically select illumination wavelength bands from a broadband quartz tungsten halogen lamp, and a second DMD to provide spatially modulated sample illumination. The system is capable of imaging 10 wavelength bands in approximately 25 seconds. The spectral resolution can be varied from 12 to 30 nm by tuning the input slit width and the output DMD column width. We compared the optical property extraction accuracy between the new device and a commercial SFDI system and found an average error of 23% in absorption and 6% in scattering. The system was highly stable, with less than 5% variation in absorption and less than 0.2% variation in scattering across all wavelengths over two hours. The system was used to monitor hyperspectral changes in the optical absorption and reduced scattering spectra of blood exposed to air over 24 hours. This served as a general demonstration of the utility of this system, and points to a potential application for blood stain age estimation. We noted significant changes in both absorption and reduced scattering spectra over multiple discrete stages of aging. To our knowledge, these are the first measurement of changes in scattering of blood stains. This hyperspectral SFDI system holds promise for a multitude of applications in quantitative tissue and diffuse sample imaging.

Quantifying visible absorbance changes and DNA degradation in aging bloodstains under extreme temperatures

Physicochemical property changes observed in a degrading bloodstain can be used to estimate its time since deposition (TSD) and provide a timestamp to the sample's age. Many of the time-dependent processes that occur as a bloodstain degrades, such as DNA fragmentation and changes in hemoglobin structure, also exhibit temperature-dependent behaviours. Previous studies have demonstrated that pairing high-resolution automated gel electrophoresis and visible absorbance spectroscopy could be used to quantify the rate of degradation of a bloodstain in relation to time and storage substrate. Our study investigates such trends with an added factor, extreme temperatures. Passive drip stains were stored in either microcentrifuge tubes or on FTA cards at either -20°C, 21°C or 40°C and tested over 11 time points spanning 15 days. For both storage substrates, the wavelength at maximum absorbance for the Soret band and the maximum absorbance of the Alpha band showed a negative trend over time suggesting that spectral shifts are informative for TSD estimates. The ratio of the maximum peak height for DNA fragments lengths of 500-1000 base pairs to 1000-5000 base pairs was the most informative DNA variable in relation to time for both substrates. Cross-validation suggested the appropriate fit of the models with the data and reasonable predictive ability. We integrated both DNA concentration and hemoglobin visible absorbance metrics using principal component analysis (PCA) into a single model. Adding the random effect of the donor to the PCA model accounted for a large portion of the variation as did storage method and temperature. Additionally, canonical correspondence showed that temperature corresponded differently to the response variables for FTA card and microcentrifuge tube samples, suggesting a substrate specific effect. This study confirms that pairing DNA concentration and hemoglobin's visible absorbance can provide insight on the effect of different environmental and storage conditions on bloodstain degradation. While the level of uncertainty surrounding TSD estimates still precludes its use in the field, this study provides a valuable framework that improves our understanding of variation surrounding TSD estimates, which will be critical to any eventual application.

Blood Stain Classification with Hyperspectral Imaging and Deep Neural Networks

In recent years, growing interest in deep learning neural networks has raised a question on how they can be used for effective processing of high-dimensional datasets produced by hyperspectral imaging (HSI). HSI, traditionally viewed as being within the scope of remote sensing, is used in non-invasive substance classification. One of the areas of potential application is forensic science, where substance classification on the scenes is important. An example problem from that area-blood stain classification-is a case study for the evaluation of methods that process hyperspectral data. To investigate the deep learning classification performance for this problem we have performed experiments on a dataset which has not been previously tested using this kind of model. This dataset consists of several images with blood and blood-like substances like ketchup, tomato concentrate, artificial blood, etc. To test both the classic approach to hyperspectral classification and a more realistic application-oriented scenario, we have prepared two different sets of experiments. In the first one, Hyperspectral Transductive Classification (HTC), both a training and a test set come from the same image. In the second one, Hyperspectral Inductive Classification (HIC), a test set is derived from a different image, which is more challenging for classifiers but more useful from the point of view of forensic investigators. We conducted the study using several architectures like 1D, 2D and 3D convolutional neural networks (CNN), a recurrent neural network (RNN) and a multilayer perceptron (MLP). The performance of the models was compared with baseline results of Support Vector Machine (SVM). We have also presented a model evaluation method based on t-SNE and confusion matrix analysis that allows us to detect and eliminate some cases of model undertraining. Our results show that in the transductive case, all models, including the MLP and the SVM, have comparative performance, with no clear advantage of deep learning models. The Overall Accuracy range across all models is 98-100% for the easier image set, and 74-94% for the more difficult one. However, in a more challenging inductive case, selected deep learning architectures offer a significant advantage; their best Overall Accuracy is in the range of 57-71%, improving the baseline set by the non-deep models by up to 9 percentage points. We have presented a detailed analysis of results and a discussion, including a summary of conclusions for each tested architecture. An analysis of per-class errors shows that the score for each class is highly model-dependent. Considering this and the fact that the best performing models come from two different architecture families (3D CNN and RNN), our results suggest that tailoring the deep neural network architecture to hyperspectral data is still an open problem.

Feature Selection and Rapid Characterization of Bloodstains on Different Substrates

Establishing the precise timeline of a crime can be challenging as current analytical techniques used suffer from many limitations and are destructive to the body fluids encountered at crime scenes. Raman spectroscopy has demonstrated excellent potential in forensic science as it provides direct information about the structural and molecular changes without the need for processing or extracting samples. However, its current applicability is limited to pure body fluids, as signals from the substrate underlying these fluids greatly influence the current models used for age estimation. In this study, we utilized Raman spectroscopy to identify selective spectral markers that delineate the bloodstain age in the presence of interfering signals from the substrate. The pure bloodstains and the bloodstains on the substrate were aged for two weeks at 21 ± 2 ℃ in the dark. Least absolute shrinkage and selection operator (LASSO) regression was employed to guide the feature selection in the presence of interference from substrates to accurately predict the bloodstain age. Substrate-specific regression models guided by an automated feature selection algorithm yielded low values of predictive root mean square error (0.207, 0.204, 0.222 h in logarithmic scale) and high R² (0.924, 0.926, 0.913) on test data consisting of blood spectra on floor tile, facial tissue, and linoleum-polymer substrates, respectively. This framework for an automated feature selection algorithm relies entirely on pure bloodstain spectra to train substrate-specific models for estimating the age of composite (blood on substrate) spectra. The model can thus be easily applied to any new composite spectra and is highly scalable to new environments. This study demonstrates that Raman spectroscopy coupled with LASSO could serve as a reliable and nondestructive technique to determine the age of bloodstains on any surface while aiding forensic investigations in real-world scenarios.