Sex discrimination from urine traces for forensic purposes using attenuated total reflectance Fourier transform infrared spectroscopy and multivariate data analysis

Sex and blood group determination from hair using ATR-FTIR spectroscopy and chemometrics

Examination of hair with its intact root is commonly used for DNA profiling of the donor. However, its use for gathering other types of information is less explored. Using attenuated total reflectance-Fourier transform infrared spectroscopy, the present study aims to explore other relevant aspects in a non-destructive manner for forensics. Determining the sex and blood group of human hair samples were the major goals of the study. Sex determination was accomplished by analyzing the differential vibrational intensities and stretching of various chemical groups associated with hair and its proteins. Statistical inference of spectral data was performed using chemometric algorithms such as PCA and PLS-DA. The PLS-DA model determined sex with 100% accuracy and blood grouping with an average accuracy of 95%. The present study is the first of its kind to determine sex and blood grouping from human scalp hair shafts, as far as the author knows. By acting as a preliminary screening test, this study could have significant implications for forensic analysis of crime scene samples. Human and synthetic hair were used in validation studies, resulting in 100% accuracy, specificity, and sensitivity, with 0% false positives and false negatives. The technique ATR FTIR spectroscopy could complement the currently used methods of hair analysis such as physical examination and mitochondrial or genomic DNA analysis.

Forensic Discrimination of condom lubricants using ATR-FTIR spectroscopy in combination with chemometrics- effect of matrices, pre-coital and post-coital conditions

The escalating rates of rape and sexual assault cases underscore the essential need to analyze associative evidence of sexual assault to ensure justice. The condom, when used during the act of sexual assault/rape, leaves behind traces of lubricant that could be instrumental in establishing the link between the victim and perpetrator. This leading evidence is crucial especially when the traditional DNA analysis is challenging owing to the lack of biological evidence. The present study employs the use of ATR FTIR spectroscopy coupled with the chemometric, to discern the chemical discrimination of condom lubricants. The study also aimed to investigate simulated real-case scenarios by analysing the effect of different matrices such as vaginal fluid, menstrual blood, and undergarment substrates (cotton, polyester and nylon) on condom traces. The difference in the spectral profile of pre-coitus and post-coitus samples was also investigated. The results of the present study are noteworthy, unveiling the efficacy of discriminating the condom lubricants of different brands and other frequently used household lubricants with 100% sensitivity, specificity, and accuracy. Condom lubricants are detected despite the presence of contaminants such as menstrual blood, and vaginal fluid, across different substrates and, in post-coital conditions. In conclusion, this study presents a comprehensive approach to analysing condom lubricants, offering a potential breakthrough in the investigation of sexual assault cases, coupled with the ability to counter false accusations.

Rapid discrimination of urine specific gravity using spectroscopy and a modified combination method based on SPA and spectral index

To achieve high-accuracy urine specific gravity discrimination and guide the design of four-waveband multispectral sensors. A modified combination strategy was attempted to be proposed based on the successive projections algorithm (SPA) and the spectral index (SI) in the present study. First, the SPA was used to select four spectral variables in the full spectra. Second, the four spectral variables were mathematically transformed by SI to obtain SI values. Then, SPA gradually fusions the SI values and establishes models to identify USG. The results showed that the SPA can screen out the four characteristic wavelengths related to the measured sample attributes. SIs can be used to improve the performance of constructed prediction models. The best model only involves four spectral variables and 1 SI value, with high accuracy (91.62%), sensitivity (0.9051), and specificity (0.9667). The results reveal that m-SPA-SI can effectively distinguish USG and provide design guidance for 4-wavelength multispectral sensors.