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                            Library & Multimedia
 A universal test for the forensic identification of all main body fluids including urine
NCJ Number
              303241
Journal

*Forensic Chemistry* Volume: 20 Dated: 2020
Author(s)
          B. Vyas;
                        et al
Date Published

2020
Annotation
              This article reports on a study that combined the Raman spectral dataset collected by Muro et al. with Raman spectral data collected from 27 urine samples from different donors to build calibration and validation datasets.
Abstract
              A critical aspect of forensic investigation is to detect and identify body fluid stains and preserve them for DNA extraction. The types of body fluid stains commonly found at a crime scene include blood, saliva, semen, sweat, vaginal fluid, and urine. Identification of a stain can be difficult as current methods are body fluid specific and mostly destructive. In an effort to develop a universal, confirmatory and nondestructive approach which can identify and differentiate body fluids Muro et al. (2016), combined Raman spectroscopy and chemometrics to build a statistical model which could differentiate peripheral blood, saliva, semen, sweat, and vaginal fluid. However, this model did not include urine. Urine can be vital evidence in cases of correctional officers being assaulted with urine bombs by prisoners, as well as in sexual assault cases. Recent studies have also shown that DNA can be extracted from a dried urine sample. The current study applied chemometrics to build an enhanced statistical model which can identify and differentiate all main body fluids, including peripheral blood, saliva, semen, sweat, vaginal fluid, and urine. This classification model offers a universal, single step, non-destructive, and robust technique with 100-percent accuracy for sample identification. (publisher abstract modified)
      
  
          Additional Details
Grant Number(s)
        2017-DN-BX-0135


  
  
        
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        Raman spectroscopy for analyzing body fluid traces: Universal method development
    
  
  
Date Published: January 1, 2020
    
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