Innovative Vibrational Spectroscopy Research for Forensic Application

Attenuated total reflection Fourier transform infrared spectroscopy (ATR-FTIR) analysis of human nails: Implications for age determination in forensics

A person's age estimation from biological evidence is a crucial aspect of forensic investigations, aiding in victim identification and criminal profiling. In this study, we present a novel approach of utilizing Attenuated Total Reflection Fourier Transform Infrared (ATR FT-IR) spectroscopy to predict the age of donors based on nail samples. A diverse dataset comprising nails from donors spanning different age groups was analyzed using ATR FT-IR, with subsequent multivariate analysis techniques used for age prediction. The developed partial least squares regression (PLS-R) model demonstrated promising accuracy in age estimation, with a root mean square error of prediction (RMSEP) equal to 11.1 during external validation. Additionally, a partial least squares discriminant analysis (PLS-DA) classification model achieved high accuracy of 88% in classifying donors into younger and older age groups during external validation. This proof-of-concept study highlights the potential of ATR FT-IR spectroscopy as a non-destructive and efficient tool for age estimation in forensic investigations, offering a new approach to forensic analysis with practical implications.

Phenotypic profiling based on body fluid traces discovered at the scene of crime: Raman spectroscopy of urine stains for race differentiation

Modern criminal investigations heavily rely on trace bodily fluid evidence as a rich source of DNA. DNA profiling of such evidence can result in the identification of an individual if a matching DNA profile is available. Alternatively, phenotypic profiling based on the analysis of body fluid traces can significantly narrow down the pool of suspects in a criminal investigation. Urine stain is a frequently encountered specimen at the scene of crime. Raman spectroscopy offers great potential as a universal confirmatory method for the identification of all main body fluids, including urine. In this proof-of-concept study, Raman spectroscopy combined with advanced statistics was used for race differentiation based on the analysis of urine stains. Specifically, a Random Forest (RF) model was built, which allowed for differentiating Caucasian (CA) and African American (AA) descent donors with 90% accuracy based on Raman spectra of dried urine samples. Raman spectra were collected from samples of 28 donors varying in age and sex. This novel technology offers great potential as a universal forensic tool for phenotypic profiling of a potential suspect immediately at the scene of a crime, providing invaluable information for a criminal investigation.

Near-infrared excitation Raman spectroscopy of colored fabric contaminated with body fluids

Confirmatory identification of dyes in the physical pieces of evidence, such as hair and fabric, is critically important in forensics. This information can be used to demonstrate the link between a person of interest and a crime scene. High performance liquid chromatography is broadly used for dye analysis. However, this technique is destructive and laborious. This problem can be overcome by near-Infrared excitation Raman spectroscopy (NIeRS), non-invasive and non-destructive technique that can be used to determine chemical structure of highly fluorescent dyes. Analyzed fabric materials often possess body fluid stains, which may obscure the accuracy of NIeRS-based identification of dyes. In this study, we investigate the extent to which fabric contamination with body fluids can alter the accuracy of NIeRS. Our results showed that NIeRS coupled with partial-least squared discriminant analysis (PLS-DA) enabled on average 97.6% accurate identification of dyes on fabric contaminated with dry blood, urine and semen. We also found that NIeRS could be used to identify blood, urine and semen on such fabric with 99.4% accuracy. Furthermore, NIeRS could be used to differentiate between wet and dry blood, as well as reveal the presence of blood on washed fabric. These results indicate that NIeRS coupled with PLS-DA could be used as a robust and reliable analytical approach in forensic analysis of fabric.

Evaluation of spectroscopic techniques for on-site drug testing of festival seizures

Despite the fact that drugs of abuse are illegal, a drug-free festival still remains an utopia in most settings. For law enforcement purposes, it is necessary to rapidly determine whether controlled substances are involved. On-site testing is a challenging task because drugs appear in different physical forms and concentrations. The aim of this study was to compare the performance of two spectroscopic techniques, Raman and Fourier transform-infrared (FT-IR), for the testing of drug seizures at a dance festival. First, samples were measured through packaging with Raman. Subsequently, homogenized samples were analysed with FT-IR. For MDMA tablets, a chemometric model was applied on the FT-IR spectra for the dose estimation. After the festival, results were confirmed in the forensic laboratory with gas chromatography coupled with mass spectrometry (GC-MS) and gas chromatography with flame ionization detection (GC-FID). In total, 166 samples of which 90 tablets, 53 powders, 16 crystals and 7 liquids were analysed. MDMA, cocaine and ketamine were the top three drugs seized. The Raman technique was suitable for powders and crystals (sensitivity of 100% and 81%, respectively). However, in comparison with FT-IR, Raman performance was lower for the analysis of liquids (sensitivity of 67%) and 'ecstasy'-like tablets (sensitivity of 41%). Overall, sensitivities above 95% were obtained with FT-IR. The MDMA doses of the tablets, determined on-site, ranged between 52 mg and 336 mg MDMA hydrochloride. For a quick identification of a variety of drugs on-site, the combination of Raman and FT-IR is recommended. It should be emphasized that optimized settings, in-house libraries and analysis by trained operators are essential to obtain correct results.

Machine Learning Discrimination and Ultrasensitive Detection of Fentanyl Using Gold Nanoparticle-Decorated Carbon Nanotube-Based Field-Effect Transistor Sensors

The opioid overdose crisis is a global health challenge. Fentanyl, an exceedingly potent synthetic opioid, has emerged as a leading contributor to the surge in opioid-related overdose deaths. The surge in overdose fatalities, particularly due to illicitly manufactured fentanyl and its contamination of street drugs, emphasizes the urgency for drug-testing technologies that can quickly and accurately identify fentanyl from other drugs and quantify trace amounts of fentanyl. In this paper, gold nanoparticle (AuNP)-decorated single-walled carbon nanotube (SWCNT)-based field-effect transistors (FETs) are utilized for machine learning-assisted identification of fentanyl from codeine, hydrocodone, and morphine. The unique sensing performance of fentanyl led to use machine learning approaches for accurate identification of fentanyl. Employing linear discriminant analysis (LDA) with a leave-one-out cross-validation approach, a validation accuracy of 91.2% is achieved. Meanwhile, density functional theory (DFT) calculations reveal the factors that contributed to the enhanced sensitivity of the Au-SWCNT FET sensor toward fentanyl as well as the underlying sensing mechanism. Finally, fentanyl antibodies are introduced to the Au-SWCNT FET sensor as specific receptors, expanding the linear range of the sensor in the lower concentration range, and enabling ultrasensitive detection of fentanyl with a limit of detection at 10.8 fg mL-1.

Combining spectrum and machine learning algorithms to predict the weathering time of empty puparia of Sarcophaga peregrine (Diptera: Sarcophagidae)

The weathering time of empty puparia could be important in predicting the minimum postmortem interval (PMImin). As corpse decomposition progresses to the skeletal stage, empty puparia often remain the sole evidence of fly activity at the scene. In this study, we used empty puparia of Sarcophaga peregrina (Diptera: Sarcophagidae) collected at ten different time points between January 2019 and February 2023 as our samples. Initially, we used the scanning electron microscope (SEM) to observe the surface of the empty puparia, but it was challenging to identify significant markers to estimate weathering time. We then utilized attenuated total internal reflectance Fourier transform infrared spectroscopy (ATR-FTIR) to detect the puparia spectrogram. Absorption peaks were observed at 1064 cm-1, 1236 cm-1, 1381 cm-1, 1538 cm-1, 1636 cm-1, 2852 cm-1, 2920 cm-1. Three machine learning models were used to regress the spectral data after dimensionality reduction using principal component analysis (PCA). Among them, eXtreme Gradient Boosting regression (XGBR) showed the best performance in the wavenumber range of 1800-600 cm-1, with a mean absolute error (MAE) of 1.20. This study highlights the value of refining these techniques for forensic applications involving entomological specimens and underscores the considerable potential of combining FTIR and machine learning in forensic practice.

Miniaturized Near-Infrared spectrophotometers in forensic analytical science - a critical review

The advent of miniaturized NIR instruments, also known as compact, portable, or handheld, is revolutionizing how technology can be employed in forensics. In-field analysis becomes feasible and affordable with these new instruments, and a series of methods has been developed to provide the police and official agents with objective, easy-to-use, tailored, and accurate qualitative and quantitative forensic results. This work discusses the main aspects and presents a comprehensive and critical review of compact NIR spectrophotometers associated with analytical protocols to produce information on forensic matters.

Chromatographic and spectroscopic methods for the detection of cocoa butter in cocoa and its derivatives: A review

Currently, there is fierce competition in the cocoa industry to develop products that possess distinctive sensory characteristics and flavours. This is because cocoa and its derivatives provide numerous health and functional advantages, which is essential to their economics. The fatty acid and triglyceride composition of cocoa determines its quality. This review emphasises the necessity of developing precise, adaptable analytical techniques to identify and quantify cocoa butter in cocoa and its derived products, from cocoa beans to chocolate bars. Key chromatographic and spectroscopic techniques play crucial roles in understanding the fundamental principles underlying the production of cocoa with desirable flavours. This significantly impacts the sustainability, traceability, and authenticity of cocoa products while also supporting the battle against adulteration.

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.

Extrapolation study for determining the time since injury in a rat subcutaneous hematoma model utilizing ATR-FTIR spectroscopy

The determination of the time of an injury has been a major problem in forensic science due to the lack of objective, reliable and portable methods. In this study, a subcutaneous hemorrhage model in rats was established over six days, and attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy coupled with chemometrics was used to determine the time since injury. Initial principal component analysis (PCA) showed variance among hematoma sites. Subsequently, spectral data were acquired to establish a dependable partial least square (PLS) regression model with predictive abilities. The root mean square error of cross-validation (RMSECV) and the root mean square error of prediction (RMSEP) values produced by a genetic algorithm (GA) were 0.64 d (R2 = 0.88) and 0.57 d (R2 = 0.90), respectively. Few variables were involved in the model, and significantly better results were obtained in comparison to the conventional full-spectrum PLS model. In combination with the results of variable importance in projection (VIP) scores, all components, including proteins, nucleic acids and phospholipids, provided inferences regarding the samples at different time points; additionally, amide I and II bands represented the secondary structure of proteins and provided the largest contribution. Based on our preliminary study, the combination of swift and nondamaging ATR-FTIR spectroscopy with chemometrics could prove to be an advantageous approach for gauging the age of an injury in the forensic field.

Spheroids as a 3D in vitro model to study bone and bone mineralization

Traumas, fractures, and diseases can severely influence bone tissue. Insight into bone mineralization is essential for the development of therapies and new strategies to enhance bone regeneration. 3D cell culture systems, in particular cellular spheroids, have gained a lot of interest as they can recapitulate crucial aspects of the in vivo tissue microenvironment, such as the extensive cell-cell and cell-extracellular matrix (ECM) interactions found in tissue. The potential of combining spheroids and various classes of biomaterials opens also new opportunities for research within bone tissue engineering. Characterizing cellular organization, ECM structure, and ECM mineralization is a fundamental step for understanding the biological processes involved in bone tissue formation in a spheroid-based model system. Still, many experimental techniques used in this field of research are optimized for use with monolayer cell cultures. There is thus a need to develop new and improving existing experimental techniques, for applications in 3D cell culture systems. In this review, bone composition and spheroids properties are described. This is followed by an insight into the techniques that are currently used in bone spheroids research and how these can be used to study bone mineralization. We discuss the application of staining techniques used with optical and confocal fluorescence microscopy, molecular biology techniques, second harmonic imaging microscopy, Raman spectroscopy and microscopy, as well as electron microscopy-based techniques, to evaluate osteogenic differentiation, collagen production and mineral deposition. Challenges in the applications of these methods in bone regeneration and bone tissue engineering are described. STATEMENT OF SIGNIFICANCE: 3D cell cultures have gained a lot of interest in the last decades as a possible technique that can be used to recreate in vitro in vivo biological process. The importance of 3D environment during bone mineralization led scientists to use this cell culture to study this biological process, to obtain a better understanding of the events involved. New and improved techniques are also required for a proper analysis of this cell model and the process under investigation. This review summarizes the state of the art of the techniques used to study bone mineralization and how 3D cell cultures, in particular spheroids, are tested and analysed to obtain better resolved results related to this complex biological process.

Fluorescence Spectroscopy: A Useful Method to Explore the Interactions of Small Molecule Ligands with DNA Structures

Small molecule ligands-DNA interactions have recently received a lot of attention in the fields of life sciences, medicine, and chemical sciences. To decode these interactions, many strategies have been developed. DNA is the primary target for a wide range of drugs that may interact with DNA in particular or non-specific ways and impact its activities. Fluorescence spectroscopy is a highly advanced and non-invasive technology for measuring the concentrations of substrates and products or identifying characteristic processing states. Small molecule ligands-DNA interaction studies are beneficial not only in comprehending the method of interaction, but also in synthesizing DNA-targeted particular drugs. Several small compounds that bind to DNA are clinically established therapeutic medicines, while their specific mechanism of action is unknown. Figuring out their molecular recognizing patterns is the only way to construct innovative compounds that can target specific DNA sequences with strong affinities. This book chapter will mostly explore several fluorescence spectroscopic methodologies used to investigate interactions between small molecule ligands and DNA. In addition, we provide many approaches for determining a drug's binding mode with DNA. These strategies produce data that is both trustworthy and easy to comprehend. All of the knowledge gained by studying these fluorescence spectroscopies are supposed to lead to the development of more efficient new pharmaceuticals that might aid in the treatment of diseases.

Combining surface-enhanced Raman spectroscopy and paper spray mass spectrometry for the identification and confirmation of psychotropic substances in alcoholic beverages

Criminal practices in which an individual becomes vulnerable and prone to sexual assault after ingesting drinks spiked with doping substances have become a social concern globally. As forensic protocols require a multi-tiered strategy for chemical evidentiary analysis, the backlog of evidence has become a significant problem in the community. Herein, a fast, sensible, and complementary dual analytical methodology was developed using a single commercial paper substrate for surface-enhanced Raman spectroscopy (SERS) and paper spray mass spectrometry (PS-MS) analysis to identify psychotropic substances added to alcoholic beverages irrefutably. To study and investigate this criminal practice, pharmaceutical formulations containing distinct psychotropic substances (zolpidem, clonazepam, diazepam, and ketamine) were added to drinks typically consumed at parties and festivals (Pilsen beer, açaí Catuaba®, gin tonic, and vodka mixed with Coca-Cola Zero®). A simple liquid-liquid extraction with a low-temperature partitioning (LLE-LTP) procedure was applied to the drinks and effectively minimized matrix effects. As a preliminary analysis, SERS spectra combined with Hierarchical Clustering Analysis (HCA) provided sufficient information to investigate the samples further. The presence of the protonated species for the psychotropic substances in the spiked drinks was readily verified in the mass spectra and confirmed by tandem mass spectrometry. Finally, the results demonstrate the potential of this methodology to be easily implemented into the routine of forensic laboratories and to be further employed at harm reduction tends at parties and festivals to detect contaminated beverages promptly and irrefutably as an efficient tool to prevent such crimes.

[Vibrational spectroscopy use for forensic purposes combined with machine learning]

Vibrational spectroscopy combined with machine learning has a great potential for forensic research. Portable Raman spectrometers are already being used by law-enforcement agencies to identify drugs. Several new technologies based on vibrational spectroscopy, that can be used in forensic science to analyze documents, gunshot traces, cloths, soil, hair, nails and lacquer, are being developed nowadays. The article considers the use of vibrational spectroscopy in forensic practice for conducting serological studies with an emphasis on the development of a universal method of identifying the main secretions of the body. The method allows to determine the time elapsed since the trace was made, as well as the phenotypic profile of host, including sex, race and age.

Spatially resolved multimodal vibrational spectroscopy under high pressures

In this perspective, we discuss the potential impact on in situ studies under controlled environments of a novel multimodal spectroscopic technique, optical photothermal infrared + Raman spectroscopy, which enables the simultaneous collection of infrared and Raman scattering spectra, along with hyperspectral imaging and chemical imaging with wavelength-independent sub-500 nm spatial resolution. A brief review of the current literature regarding the O-PTIR technique is presented along with recent work from our own lab on determining the crystallinity of soft and inorganic materials. The results highlight the possibility of resolving differences in the crystallinity of soft materials associated with changes in material processing. We also demonstrate the first reported use of a diamond anvil cell with simultaneous infrared and Raman measurements that showcases, using a high energy material as an example, the potential use of O-PTIR spectroscopy in diamond anvil cell techniques.

Applications of Fourier Transform-Infrared spectroscopy in microbial cell biology and environmental microbiology: advances, challenges, and future perspectives

Microorganisms play pivotal roles in shaping ecosystems and biogeochemical cycles. Their intricate interactions involve complex biochemical processes. Fourier Transform-Infrared (FT-IR) spectroscopy is a powerful tool for monitoring these interactions, revealing microorganism composition and responses to the environment. This review explores the diversity of applications of FT-IR spectroscopy within the field of microbiology, highlighting its specific utility in microbial cell biology and environmental microbiology. It emphasizes key applications such as microbial identification, process monitoring, cell wall analysis, biofilm examination, stress response assessment, and environmental interaction investigation, showcasing the crucial role of FT-IR in advancing our understanding of microbial systems. Furthermore, we address challenges including sample complexity, data interpretation nuances, and the need for integration with complementary techniques. Future prospects for FT-IR in environmental microbiology include a wide range of transformative applications and advancements. These include the development of comprehensive and standardized FT-IR libraries for precise microbial identification, the integration of advanced analytical techniques, the adoption of high-throughput and single-cell analysis, real-time environmental monitoring using portable FT-IR systems and the incorporation of FT-IR data into ecological modeling for predictive insights into microbial responses to environmental changes. These innovative avenues promise to significantly advance our understanding of microorganisms and their complex interactions within various ecosystems.

Field-portable detection of fentanyl and its analogs: A review

The need to detect fentanyl and its analogs in the field is an important capability to help prevent unintentional exposure or overdose on these substances, which may result in death. Many portable methods historically used in the field by first responders and other field users to detect and identify other chemical substances, such as hazardous materials, have been applied to the detection and identification of these synthetic opioids. This paper describes field portable spectroscopic methods used for the detection and identification of fentanyl and its analogs. The methods described are automated colorimetric tests including lateral flow assays; vibrational spectroscopy (mid-infrared and Raman); gas chromatography-mass spectrometry; ion mobility spectrometry, and high-pressure mass spectrometry. In each case the background and key details of these technologies are outlined, followed by a discussion of the application of the technology in the field. Attention is paid to the analysis of complex mixtures and limits of detection, including the required spectral databases and algorithms used to interrogate these types of samples. There is also an emphasis on providing actionable information to the (likely) non-scientist operators of these instruments in the field.

Raman Spectroscopy to Enhance Investigative Lead Information in Automotive Clearcoats

A new method to determine the make and model of a vehicle from an automotive paint sample recovered at the crime scene of a vehicle-related fatality such as a hit-and-run using Raman microscopy has been developed. Raman spectra were collected from 118 automotive paint samples from six General Motors (GM) vehicle assembly plants to investigate the discrimination power of Raman spectroscopy for automotive clearcoats using a genetic algorithm for pattern recognition that incorporates model inference and sample error in the variable selection process. Each vehicle assembly plant pertained to a specific vehicle model. The spectral region between 1802 and 697 cm-1 was found to be supportive of the discrimination of these six GM assembly plants. By comparison, only one of the six automotive assembly plants could be differentiated from the other five assembly plants using Fourier transform infrared spectroscopy (FT-IR), which is the most widely used analytical method for the examination of automotive paint) and the genetic algorithm for pattern recognition. The results of this study indicate that Raman spectroscopy in combination with pattern recognition methods offers distinct advantages over FT-IR for the identification and discrimination of automotive clearcoats.

Attenuated Total Reflection Fourier Transform Infrared Spectroscopy for Forensic Screening of Long-Term Alcohol Consumption from Human Nails

Fourier transform infrared (FT-IR) spectroscopy is used throughout forensic laboratories for many applications. FT-IR spectroscopy can be useful with ATR accessories in forensic analysis for several reasons. It provides excellent data quality combined with high reproducibility, with minimal user-induced variations and no sample preparation. Spectra from heterogeneous biological systems, including the integumentary system, can be associated with hundreds or thousands of biomolecules. The nail matrix of keratin possesses a complicated structure with captured circulating metabolites whose presence may vary in space and time depending on context and history. We developed a new approach by using machine-learning (ML) tools to leverage the potential and enhance the selectivity of the instrument, create classification models, and provide invaluable information saved in human nails with statistical confidence. Here, we report chemometric analysis of ATR FT-IR spectra for the classification and prediction of long-term alcohol consumption from nail clippings in 63 donors. A partial least squares discriminant analysis (PLS-DA) was used to create a classification model that was validated against an independent data set which resulted in 91% correctly classified spectra. However, when considering the prediction results at the donor level, 100% accuracy was achieved, and all donors were correctly classified. To the best of our knowledge, this proof-of-concept study demonstrates for the first time the ability of ATR FT-IR spectroscopy to discriminate donors who do not drink alcohol from those who drink alcohol on a regular basis.

Identification and highly selective differentiation of organic gunshot residues utilizing their elemental and molecular signatures

Firearm related evidence is of great significance to forensic science. In recent years, many researchers have focused on exploring the probative value of organic gunshot residue (OGSR) evidence, which is often bolstered by many factors including recoverability. In addition, OGSR analysis has shown the potential to achieve differentiation between OGSRs generated from various ammunition brands and/or calibers. Raman spectroscopy is a vibrational spectroscopic technique which has been used in the past for gunshot residue analysis-including OGSR specifically. Raman spectroscopy is a nondestructive, highly-selective, simple, and rapid technique which provides molecular information about samples. LIBS or Laser-Induced Breakdown Spectroscopy is a simple, robust, and rapid analytical method which requires minimal to no sample preparation and a small amount of sample for analysis. LIBS provides information on the elemental compositions of samples. In this study, Raman spectroscopy and LIBS were used together in sequence in an attempt to achieve the specific identification and characterization of OGSR particles from ammunition types which were closely related. The main goal was to determine if this method had the potential to differentiate between various ammunition types of the same caliber and produced by the same manufacturer, and generated under identical firing conditions. High-resolution optical microscopy documented the OGSR particles' morphologies and Raman spectroscopy was used to identify particles as OGSRs. Finally, LIBS analysis of the OGSR particles was carried out. Advanced chemometric techniques were shown to allow for very successful differentiation between the OGSR samples analyzed.