Kyle C. Doty

Discrimination of human and animal blood traces via Raman spectroscopy

The characterization of suspected blood stains is an important aspect of forensic science. In particular, determining the origin of a blood stain is a critical, yet overlooked, step in establishing its relevance to the crime. Currently, assays for determining human origin for blood are time consuming and destructive to the sample. The research presented here demonstrates that Raman spectroscopy can be effectively applied as a non-destructive technique for differentiating human blood from a wide survey of animal blood. A Partial Least Squares-Discriminant Analysis (PLS-DA) model was built from a training set of the near infrared Raman spectra from 11 species. Various performance measures, including a blind test and external validation, confirm the discriminatory performance of the chemometric model. The model demonstrated 100% accuracy in its differentiation between human and nonhuman blood. These findings further demonstrate a great potential of Raman spectroscopy to the field of serology, especially for species identification of a suspected blood stain.

Raman spectroscopy of blood for species identification.

The species identification of a blood stain is an important and immediate challenge for forensic science, veterinary purposes, and wildlife preservation. The current methods used to identify the species of origin of a blood stain are limited in scope and destructive to the sample. We have previously demonstrated that Raman spectroscopy can reliably differentiate blood traces of human, cat, and dog (Virkler et al. Anal. Chem. 2009, 81, 7773 - 7777) and, most recently, built a binary model for differentiating human vs animal blood for 11 species integrated with human existence ( McLaughlin et al. Forensic Sci. Int. 2014, 238, 91 - 95). Here we report a satisfactory classification of blood obtained from 11 animal classes and human subjects by statistical analysis of Raman spectra. Classification of blood samples was achieved according to each samples species of origin, which enhanced previously observed discrimination ability. The developed approach does not require the knowledge of a specific (bio)chemical marker for each individual class but rather relies on a spectroscopic statistical differentiation of various components. This approach results in remarkable classification ability even with intrinsically heterogeneous classes and samples. In addition, the obtained spectroscopic characteristics could potentially provide information about specific changes in the (bio)chemical composition of samples, which are responsible for the differentiation.

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.

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.

Differentiation of human blood from animal blood using Raman spectroscopy: A survey of forensically relevant species

The identification of blood samples is a crucial facet of forensic investigations, particularly for violent crimes. One step in forensic serology (i.e., the analysis of bodily fluids) that is often skipped or overlooked is the determination that a bloodstain is of human or nonhuman origin. Typically, subsequent to identifying a stain as blood using a presumptive blood test, which have the propensity of providing false positive results, the stain is submitted for extraction of a DNA profile to compare with those in a database. It is extremely uncommon that evidentiary bloodstains are confirmed as being of human origin throughout the serological analysis. Therefore, time, money, and other resources can be wasted on obtaining a DNA profile from a bloodstain that may not be of human origin; if the intent was to obtain a human DNA profile and not that of an animal. This work demonstrates an important advancement of a previous study for nondestructive differentiation of human and animal blood using Raman spectroscopy coupled with partial least squares discriminant analysis (PLSDA). Raman spectra of blood from six species of animals, not previously accounted for, including chimpanzee, deer, elk, ferret, fish, and macaque were used to test a PLSDA classification method. These animal species are forensically relevant since they are (i) involved in wildlife crimes, (ii) consumed by humans, or (iii) known to produce a false positive result when their blood is tested with certain presumptive human blood tests. An external validation sensitivity of 1.00 and specificity of 0.93 for human class predictions was obtained from the PLSDA model constructed for this study. Using receiver operating characteristic (ROC) analysis of external human class predictions, the PLSDA model demonstrated 99% accuracy in being able to correctly classify any random blood sample as human or nonhuman. This is a significant advancement over the previous work and a very important finding as it demonstrates the superb selectivity of the developed method with high accuracy in being able to correctly predict the nonhuman origin of bloodstains from unknown animal species.

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.