Differentiating Donor Age Groups Based on Raman Spectroscopy of Bloodstains for Forensic Purposes

Developments in analytical chemistry technologies and portable instrumentation over the past decade have contributed significantly to a variety of applications ranging from point of care testing to industrial process control. In particular, Raman spectroscopy has advanced for analyzing various types of evidence for forensic purposes. Extracting phenotypic information (e.g., sex, race, age, etc.) from body fluid traces is highly desirable for criminal investigations. Identifying the chronological age (CA) of a blood donor can provide significant assistance to detectives. In this proof-of-concept study, Raman spectroscopy and chemometrics have been used to analyze blood from human donors, and differentiate between them based on their CA [i.e., newborns (CA of <1 year), adolescents (CA of 11-13 years), and adults (CA of 43-68 years)]. A support vector machines discriminant analysis (SVMDA) model was constructed, which demonstrated high accuracy in correctly predicting blood donors' age groups where the lowest cross-validated sensitivity and specificity values were 0.96 and 0.97, respectively. Overall, this preliminary study demonstrates the high selectivity of Raman spectroscopy for differentiating between blood donors based on their CA. The demonstrated capability completes our suite of phenotype profiling methodologies including the determination of sex and race. CA determination has particular importance since this characteristic cannot be determined through DNA profiling unlike sex and race. When completed, the developed methodology should allow for phenotype profiling based on dry traces of body fluids immediately at the scene of a crime. The availability of this information within the first few hours since the crime discovery could be invaluable for the investigation.

Forensic Hair Differentiation Using Attenuated Total Reflection Fourier Transform Infrared (ATR FT-IR) Spectroscopy

Hair and fibers are common forms of trace evidence found at crime scenes. The current methodology of microscopic examination of potential hair evidence is absent of statistical measures of performance, and examiner results for identification can be subjective. Here, attenuated total reflection (ATR) Fourier transform-infrared (FT-IR) spectroscopy was used to analyze synthetic fibers and natural hairs of human, cat, and dog origin. Chemometric analysis was used to differentiate hair spectra from the three different species, and to predict unknown hairs to their proper species class, with a high degree of certainty. A species-specific partial least squares discriminant analysis (PLSDA) model was constructed to discriminate human hair from cat and dog hairs. This model was successful in distinguishing between the three classes and, more importantly, all human samples were correctly predicted as human. An external validation resulted in zero false positive and false negative assignments for the human class. From a forensic perspective, this technique would be complementary to microscopic hair examination, and in no way replace it. As such, this methodology is able to provide a statistical measure of confidence to the identification of a sample of human, cat, and dog hair, which was called for in the 2009 National Academy of Sciences report. More importantly, this approach is non-destructive, rapid, can provide reliable results, and requires no sample preparation, making it of ample importance to the field of forensic science.

Race Differentiation by Raman Spectroscopy of a Bloodstain for Forensic Purposes

Bearing in mind forensic purposes, a nondestructive and rapid method was developed for race differentiation of peripheral blood donors. Blood is an extremely valuable form of evidence in forensic investigations so proper analysis is critical. Because potentially miniscule amounts of blood traces can be found at a crime scene, having a method that is nondestructive, and provides a substantial amount of information about the sample, is ideal. In this study Raman spectroscopy was applied with advanced statistical analysis to discriminate between Caucasian (CA) and African American (AA) donors based on dried peripheral blood traces. Spectra were collected from 20 donors varying in gender and age. Support vector machines-discriminant analysis (SVM-DA) was used for differentiation of the two races. An outer loop subject-wise cross-validation (CV) method evaluated the performance of the SVM classifier for each individual donor from the training data set. The performance of SVM-DA, evaluated by the area under the curve (AUC) metric, showed 83% probability of correct classification for both races, and a specificity and sensitivity of 80%. This preliminary study shows promise for distinguishing between different races of human blood. The method has great potential for real crime scene investigation, providing rapid and reliable results, with no sample preparation, destruction, or consumption.

A Raman "spectroscopic clock" for bloodstain age determination: the first week after deposition

Knowing the time since deposition (TSD) of an evidentiary bloodstain is highly desired in forensics, yet it can be extremely complicated to accurately determine in practice. Although there have been numerous attempts to solve this problem using a variety of different techniques, currently, no established, well-accepted method exists. Here, a Raman spectroscopic approach was developed for determining the age of bloodstains up to 1 week old. Raman spectroscopy, along with two-dimensional correlation spectroscopy (2D CoS) and statistical modeling, was used to analyze fresh bloodstains at ten time points under ambient conditions. The 2D CoS results indicate a high correlation between several Raman bands and the age of a bloodstain. A regression model was built to provide quantitative predictions of the TSD, with cross-validated root mean squared error and R (2) values of 0.13 and 0.97, respectively. It was determined that a "new" (1 h) bloodstain could be easily distinguished from older bloodstains, which is very important for forensic science in helping to establish the relevant association of multiple bloodstains. Additionally, all bloodstains were confirmatively identified as blood by comparing the experimentally measured spectra to multidimensional body fluid spectroscopic signatures of blood, saliva, semen, sweat, and vaginal fluid. These results demonstrate that Raman spectroscopy can be used as a nondestructive analytical tool for discriminating between bloodstains on the scale of hours to days. This approach shows promise for immediate practical use in the field to predict the TSD with a high degree of accuracy. Graphical Abstract Bloodstain aging over time illustrating naturally ocurring processes.