Discrimination of menstrual and peripheral blood traces using attenuated total reflection Fourier transform-infrared (ATR FT-IR) spectroscopy and chemometrics for forensic purposes

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.

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.

Forensic analysis of biological fluid stains on substrates by spectroscopic approaches and chemometrics: A review

BACKGROUND

Bodily fluid stains are one of the most relevant evidence that can be found at the crime scene as it provides a wealth of information to the investigators. They help to report on the individuals involved in the crime, to check alibis, or to determine the type of crime that has been committed. They appear as stains in different types of substrates, some of them porous, which can interfere in the analysis. The spectroscopy techniques combined with chemometrics are showing increasing potential for their use in the analysis of such samples due to them being fast, sensitive, and non-destructive.

FINDINGS

This is a comprehensive review of the studies that used different spectroscopic techniques followed by chemometrics for analysing biological fluid stains on several surfaces, and under various conditions. It focuses on the bodily fluid stains and the most suitable spectroscopic techniques to study forensic scientific problems such as the substrate's characteristics, the influence of ambient conditions, the aging process of the bodily fluids, the presence of animal bodily fluids and non-biological fluids (interfering substances), and the bodily fluid mixtures. The most widely used techniques were Raman spectroscopy and attenuated total reflection Fourier transform infrared spectroscopy (ATR FTIR). Nonetheless, other non-destructive techniques have been also used, like near infrared hyperspectral imaging (HSI-NIR) or surface enhanced Raman spectroscopy (SERS), among others. This work provides the criteria for the selection of the most promising non-destructive techniques for the effective in situ detection of biological fluid stains at crime scene investigations.

SIGNIFICANCE AND NOVELTY

The use of the proper spectroscopic and chemometric approaches on the crime scene is expected to improve the support of forensic sciences to criminal investigations. Evidence may be analysed in a non-destructive manner and kept intact for further analysis. They will also speed up forensic investigations by allowing the selection of relevant samples from occupational ones.

Latent bloodstain detection using a selective turn-on NIR fluorescence dye responsive to serum albumin

Bloodstain detection can provide crucial information and evidence at a crime scene; however, the ability to selectively detect bloodstains in a non-destructive manner with high sensitivity and low background is limited. This study reports a fluorescent dye (sulfonate indolizine squaraine, SO3SQ) for bloodstain visualization under near-infrared (NIR) irradiation. While the dye itself is minimally fluorescent in aqueous solution, it exhibits a "turn-on" mechanism upon binding with human serum albumin (HSA) as the fluorescence intensity increases over 160 times with strong absorption and emission at 693 nm and 758 nm, respectively. Bloodstains can be visualized on a surface even after being diluted 1000 times, and washed latent bloodstains can be detected with high sensitivity. Further, the turn-on fluorescent emission lasts for a minimum of seven days, allowing adequate time for detection. This study also indicates that the SO3SQ can sensitively detect bloodstain after the bloodstain aged for one week. Furthermore, the detection of latent blood fingerprint patterns from colorful backgrounds is demonstrated using this non-destructive method. The selective turn-on fluorescent dye with NIR excitation and emission is highly suitable in forensic science for bloodstain visualization.

Differentiation of blood and environmental interfering stains on substrates by Chemometrics-Assisted ATR FTIR spectroscopy

Blood is the most common and relevant bodily fluid that can be found in crime scenes. It is critical to correctly identify it, and to be able to differentiate it from other substances that may also appear at the crime scene. In this work, several stains of blood, chocolate, ketchup, and tomato sauce on five different substrates (plywood, metal, gauze, denim, and glass) were analysed by ATR FTIR spectroscopy assisted with orthogonal partial least square-discriminant analysis (OPLS-DA) models. It was possible to differentiate blood from the environmental interfering substances independently of the substrate they were on, and to differentiate bloodstains according to the substrate they were deposited on. These results represent a proof-of-concept that open new horizons to differentiate bloodstains from other interfering substances on common substrates present in crime scenes.

Rapid and accurate screening of cystic echinococcosis in sheep based on serum Fourier-transform infrared spectroscopy combined with machine learning algorithms

Cystic echinococcosis (CE) in sheep is a serious zoonotic parasitic disease caused by Echinococcus granulosus sensu stricto (s.s.). Presently, the screening technology for CE in sheep is time-consuming and inaccurate, and novel screening technology is urgently needed. In this work, we combined machine-learning algorithms with Fourier transform infrared (FT-IR) spectroscopy of serum to establish a quick and accurate screening approach for CE in sheep. Serum samples from 77 E. granulosus s.s.-infected sheep to 121 healthy control sheep were measured by FT-IR spectrometer. To optimize the classification accuracy of the serum FI-TR method for the E. granulosus s.s.-infected sheep and healthy control sheep, principal component analysis (PCA), linear discriminant analysis, and support vector machine (SVM) algorithms were used to analyze the data. Among all the bands, 1500-1700 cm^-1 band has the best classification effect; its diagnostic sensitivity, specificity, and accuracy of PCA-SVM were 100%, 95.74%, and 96.66%, respectively. The study showed that serum FT-IR spectroscopy combined with machine learning algorithms has great potential for rapid and accurate screening methods for the CE in sheep.

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.

Breast cancer early detection by using Fourier-transform infrared spectroscopy combined with different classification algorithms

Early detection of breast cancer is of great value in improving the prognosis. The current detection methods of breast cancer have their own limitations. In this study, we investigated the feasibility of Fourier Transform Infrared (FT-IR) spectroscopy combined with different classification algorithms for the early detection of breast cancer in a large sample of 526 patients, including 308 invasive breast cancer, 101 ductal carcinoma in situ, and 117 healthy controls. The serum was measured with FT-IR spectroscopy. Kennard-Stone (KS) algorithm was used to divide the data into the training set and testing set. Support vector machine (SVM) model and back propagation neural network (BPNN) model were used to distinguish ductal carcinoma in situ, invasive breast cancer from healthy controls. The accuracies of the SVM model and BPNN model were 92.9% and 94.2%. To determine the effect of different material absorption bands on early detection, the band was divided into four parts including 900-1425 cm^-1, 1475-1710 cm^-1, 2800-3000 cm^-1, and 3090-3700 cm^-1, to be modeled and detected respectively. The final results showed that the ranges 900-1425 cm^-1 and 1475-1710 cm^-1 had superior classification accuracies. The region 900-1425 cm^-1 corresponded to the lipids, proteins, sugar, and nucleic acids, and the region 1475-1710 cm^-1 corresponded to the proteins. The biochemical substances in other bands also contributed some unique potential to the classification, so the classification accuracy was the best in the full band. The study indicates that serum FT-IR spectroscopy combined with SVM and BPNN models is an effective tool for the early detection of breast cancer.

An Emerging Strategy for Muscle Evanescent Trauma Discrimination by Spectroscopy and Chemometrics

Trauma is one of the most common conditions in the biomedical field. It is important to identify it quickly and accurately. However, when evanescent trauma occurs, it presents a great challenge to professionals. There are few reports on the establishment of a rapid and accurate trauma identification and prediction model. In this study, Fourier transform infrared spectroscopy (FTIR) and microscopic spectroscopy (micro-IR) combined with chemometrics were used to establish prediction models for the rapid identification of muscle trauma in humans and rats. The results of the average spectrum, principal component analysis (PCA) and loading maps showed that the differences between the rat muscle trauma group and the rat control group were mainly related to biological macromolecules, such as proteins, nucleic acids and carbohydrates. The differences between the human muscle trauma group and the human control group were mainly related to proteins, polysaccharides, phospholipids and phosphates. Then, a partial least squares discriminant analysis (PLS-DA) was used to evaluate the classification ability of the training and test datasets. The classification accuracies were 99.10% and 93.69%, respectively. Moreover, a trauma classification and recognition model of human muscle tissue was constructed, and a good classification effect was obtained. The classification accuracies were 99.52% and 91.95%. In conclusion, spectroscopy and stoichiometry have the advantages of being rapid, accurate and objective and of having high resolution and a strong recognition ability, and they are emerging strategies for the identification of evanescent trauma. In addition, the combination of spectroscopy and stoichiometry has great potential in the application of medicine and criminal law under practical conditions.

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.

Detection and identification of drug traces in latent fingermarks using Raman spectroscopy

Recent advancements in analytical techniques have greatly contributed to the analysis of latent fingermarks' (LFMs) "touch chemistry" and identification of materials that a suspect might have come into contact with. This type of information about the FM donor is valuable for criminal investigations because it narrows the pool of suspects. It is estimated that at least 30 million people around the world take over-the-counter and prescription nonsteroidal anti-inflammatory drugs (NSAIDs) for pain relief, headaches and arthritis every day. The daily use of such drugs can lead to an increased risk of their abuse. In the present study, Raman spectroscopy combined with multivariate statistical analysis was used for the detection and identification of drug traces in LFMs when NSAID tablets of aspirin, ibuprofen, diclofenac, ketoprofen and naproxen have been touched. Partial least squares discriminant analysis of Raman spectra showed an excellent separation between natural FMs and all NSAID-contaminated FMs. The developed classification model was externally validated using FMs deposited by a new donor and showed 100% accuracy on a FM level. This proof-of-concept study demonstrated the great potential of Raman spectroscopy in the chemical analysis of LFMs and the detection and identification of drug traces in particular.

On the Identification of Body Fluids and Tissues: A Crucial Link in the Investigation and Solution of Crime

Body fluid and body tissue identification are important in forensic science as they can provide key evidence in a criminal investigation and may assist the court in reaching conclusions. Establishing a link between identifying the fluid or tissue and the DNA profile adds further weight to this evidence. Many forensic laboratories retain techniques for the identification of biological fluids that have been widely used for some time. More recently, many different biomarkers and technologies have been proposed for identification of body fluids and tissues of forensic relevance some of which are now used in forensic casework. Here, we summarize the role of body fluid/ tissue identification in the evaluation of forensic evidence, describe how such evidence is detected at the crime scene and in the laboratory, elaborate different technologies available to do this, and reflect real life experiences. We explain how, by including this information, crucial links can be made to aid in the investigation and solution of crime.

Surface enhanced Raman scattering specificity for detection and identification of dried bloodstains

Surface enhanced Raman spectroscopy (SERS) provides highly specific vibrational signatures identifying dried blood for a variety of forensic applications. SERS spectra on Au nanoparticle substrates excited at 785 nm are found to identify dried stains of human and nonhuman blood from seven animals, and distinguish stains due to menstrual and peripheral blood. In addition, the unique SERS bloodstain spectrum is distinct from the SERS spectra of thirty red-brown stains of potential household substances that could be visually mistaken for bloodstains and from food stains that have been shown to give positive results with presumptive colorimetric blood tests. Finally, a SERS swab procedure has been developed and demonstrates that the substrates that a blood sample dried on does not offer any Raman or fluorescence interference for the SERS identification of dried blood. Such bloodstains on porous and nonporous materials are all identical and exclusively due to the heme moiety of hemoglobin. Optimized selection of the extraction solvent is found to control the chemical composition of molecular components appearing in the SERS spectrum of complex, multicomponent biological mixtures, such as body fluids.

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.