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                            Library & Multimedia
 Metabolite monitoring concept for the biometric identification of individuals from the skin surface
NCJ Number
              308293
Journal

*Analyst* Volume: 149 Dated: 2024 Pages: 350-356
Author(s)
          Mindy Greco;
                        Morgan Eldridge;
                        Emilynn Banks;
                        Lenka Halámková;
                        Jan Halámek
Date Published

2024
Length
              7 pages
Annotation
              This study explores a metabolite monitoring concept for the biometric identification of individuals from the skin surface.
Abstract
              This study aims at proof of concept that constant monitoring of the concentrations of metabolites in three individuals’ sweat over time can differentiate one from another at any given time, providing investigators and analysts with increased ability and means to individualize this bountiful biological sample. A technique was developed to collect and extract authentic sweat samples from three female volunteers for the analysis of lactate, urea, and L-alanine levels. These samples were collected 21 times over a 40-day period and quantified using a series of bioaffinity-based enzymatic assays with UV-vis spectrophotometric detection. Sweat samples were simultaneously dried, derivatized, and analyzed by a GC-MS technique for comparison. Both UV-vis and GC-MS analysis methods provided a statistically significant MANOVA result, demonstrating that the sum of the three metabolites could differentiate each individual at any given day of the time interval. Expanding upon previous studies, this experiment aims to establish a method of metabolite monitoring as opposed to single-point analyses for application to biometric identification from the skin surface. (Published Abstract Provided)
      
  
          Additional Details
Grant Number(s)
        2016-DN-BX-0188


  
  
        
  Agencies
        NIJ-Sponsored


  
  
        
  Publication Type
        Research (Applied/Empirical)


  
  
        
  Award
        Novel concept for fingerprint analysis
    
  
  
Date Published: January 1, 2024
    
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