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

NCJ Number
253477
Date Published
Unknown
Length
6 pages
Annotation
In this proof-of-concept study, Raman spectroscopy and chemometrics were used to analyze blood from human donors and differentiate between them based on their chronological age (CA) [i.e., newborns (CA of <1 year), adolescents (CA of 11-13 years), and adults (CA of 43-68 years)].
Abstract
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 the current study, a support vector machines discriminant analysis (SVMDA) model was constructed. It demonstrated high accuracy in correctly predicting blood donors' age groups, with the lowest cross-validated sensitivity and specificity values being 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 this project's suite of phenotype profiling methodologies, including the determination of sex and race. CA determination is important, since this characteristic cannot be determined through DNA profiling, unlike sex and race. When completed, the developed methodology should enable 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. (publisher abstract modified)
Date Created: January 28, 2021