Metabolite monitoring concept for the biometric identification of individuals from the skin surface

代谢物 汗水 色谱法 生物识别 代谢组学 化学 生物化学 计算机科学 医学 人工智能 内科学
作者
M Greco,Morgan Eldridge,Emilynn Banks,Lenka Halámková,Jan Halámek
出处
期刊:Analyst [Royal Society of Chemistry]
卷期号:149 (2): 350-356
标识
DOI:10.1039/d3an01605f
摘要

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.

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