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Phenotypic profiling based on body fluid traces discovered at the scene of crime: Raman spectroscopy of urine stains for race differentiation.
Vyas, Bhavik; Halámková, Lenka; Lednev, Igor K.
Afiliação
  • Vyas B; Department of Chemistry, University at Albany, State University of New York, Albany, NY 12222, USA. ilednev@albany.edu.
  • Halámková L; Department of Environmental Toxicology, Texas Tech University, Lubbock, TX 79409, USA.
  • Lednev IK; Department of Chemistry, University at Albany, State University of New York, Albany, NY 12222, USA. ilednev@albany.edu.
Analyst ; 2024 Sep 02.
Article em En | MEDLINE | ID: mdl-39221568
ABSTRACT
Modern criminal investigations heavily rely on trace bodily fluid evidence as a rich source of DNA. DNA profiling of such evidence can result in the identification of an individual if a matching DNA profile is available. Alternatively, phenotypic profiling based on the analysis of body fluid traces can significantly narrow down the pool of suspects in a criminal investigation. Urine stain is a frequently encountered specimen at the scene of crime. Raman spectroscopy offers great potential as a universal confirmatory method for the identification of all main body fluids, including urine. In this proof-of-concept study, Raman spectroscopy combined with advanced statistics was used for race differentiation based on the analysis of urine stains. Specifically, a Random Forest (RF) model was built, which allowed for differentiating Caucasian (CA) and African American (AA) descent donors with 90% accuracy based on Raman spectra of dried urine samples. Raman spectra were collected from samples of 28 donors varying in age and sex. This novel technology offers great potential as a universal forensic tool for phenotypic profiling of a potential suspect immediately at the scene of a crime, providing invaluable information for a criminal investigation.

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article