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.

Estimating the Time Since Deposition of Saliva Stains With a Targeted Bacterial DNA Approach: A Proof-of-Principle Study

Information on the time when a stain was deposited at a crime scene can be valuable in forensic investigations. It can link a DNA-identified stain donor with a crime or provide a post-mortem interval estimation in cases with cadavers. The available methods for estimating stain deposition time have limitations of different types and magnitudes. In this proof-of-principle study we investigated for the first time the use of microbial DNA for this purpose in human saliva stains. First, we identified the most abundant and frequent bacterial species in saliva using publicly available 16S rRNA gene next generation sequencing (NGS) data from 1,848 samples. Next, we assessed time-dependent changes in 15 identified species using de-novo 16S rRNA gene NGS in the saliva stains of two individuals exposed to indoor conditions for up to 1 year. We selected four bacterial species, i.e., Fusobacterium periodonticum, Haemophilus parainfluenzae, Veillonella dispar, and Veillonella parvula showing significant time-dependent changes and developed a 4-plex qPCR assay for their targeted analysis. Then, we analyzed the saliva stains of 15 individuals exposed to indoor conditions for up to 1 month. Bacterial counts generally increased with time and explained 54.9% of the variation (p = <2.2E–16). Time since deposition explained ≥86.5% and ≥88.9% of the variation in each individual and species, respectively (p = <2.2E–16). Finally, based on sample duplicates we built and tested multiple linear regression models for predicting the stain deposition time at an individual level, resulting in an average mean absolute error (MAE) of 5 days (ranging 3.3–7.8 days). Overall, the deposition time of 181 (81.5%) stains was correctly predicted within 1 week. Prediction models were also assessed in stains exposed to similar conditions up to 1 month 7 months later, resulting in an average MAE of 8.8 days (ranging 3.9–16.9 days). Our proof-of-principle study suggests the potential of the DNA profiling of human commensal bacteria as a method of estimating saliva stains time since deposition in the forensic scenario, which may be expanded to other forensically relevant tissues. The study considers practical applications of this novel approach, but various forensic developmental validation and implementation criteria will need to be met in more dedicated studies in the future.

A diagnostic relationship between the RNA Integrity Number equivalent and Time Since Deposition of blood

Determining the age, or time since deposition (TSD), of bloodstains would provide forensic scientists with critical information regarding the timeline of the events of bloodshed during a crime. The physicochemical changes that occur to major biomolecules as a bloodstain dries can be used to estimate the TSD of bloodstains. For example, high-resolution automated gel electrophoresis can be used to quantify the timewise degradation of DNA present in bloodstains. Our study aims to analyze and quantify the timewise degradation trends found in total RNA from bloodstains, expanding the scope of the TSD research which has previously explored DNA and targeted mRNA molecules. Fifty bloodstains were stored in plastic microcentrifuge tubes at room temperature and tested over 10 different timepoints spanning one week. A total of eight RNA metrics were visually assessed and quantified using linear regression. RNA Integrity Number equivalent (RINe), total RNA concentration, and 28S/18S rRNA peak area ratios were retained for further analyses based on their relationship with time and limited correlations. RINe and total RNA concentration both exhibited negative trends over time, highlighting a decrease in quality and quantity. RINe was the RNA metric that demonstrated the greatest association with time (R2 = 0.696). Generalized linear mixed-effects models including donor (biological replicate) as a random effect increased the fit for all RNA metrics to varying degrees, but no significant differences were found between biological replicates for the RINe metric. Our results illustrated the presence of a significant decrease in the retained RNA metrics after 24 hours, suggesting that this method could be used to reliably differentiate day-old bloodstains from older bloodstains. Future work should focus on recreating this study in different environmental conditions, including testing on a variety of substrates.

Untargeted SPME–GC–MS Characterization of VOCs Released from Spray Paint

Paints are a common form of physical evidence encountered at crime scenes. This research presents an optimized method for the untargeted analysis of volatile organic compounds (VOCs) in spray paint using solid-phase microextraction–gas chromatography–mass spectrometry (SPME–GC–MS). The presence and persistence of VOCs were monitored in 30 minute intervals, over a 4 hour period, in a triplicate time study. As predicted, spray paint solvents are lost to the environment readily, whereas few VOCs remained present in the headspace in low concentrations beyond 4 hours. The VOCs that were observed to have the highest persistence in the headspace were aromatic compounds and those with longer hydrocarbon chains. We present this study in a forensic science context and suggest that the interpretation of the results may be useful for forensic applications in establishing a time since deposition of a spray-painted surface.