Comprehensive two-dimensional gas chromatographic profiling and chemometric interpretation of the volatile profiles of sweat in knit fabrics

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• 作者：A. Paulina de la Mata ; Rachel H. McQueen…
• 关键词：Metabolomics ; Human body odor ; Solid ; phase microextraction (SPME) ; Comprehensive two ; dimensional gas chromatography time ; of ; flight mass spectrometry (GC×GC TOFMS) ; Variable selection ; Fisher ratio ; Textiles
• 刊名：Analytical and Bioanalytical Chemistry
• 出版年：2017
• 出版时间：March 2017
• 年：2017
• 卷：409
• 期：7
• 页码：1905-1913
• 全文大小：
• 刊物类别：Chemistry and Materials Science
• 刊物主题：Analytical Chemistry; Biochemistry, general; Laboratory Medicine; Characterization and Evaluation of Materials; Food Science; Monitoring/Environmental Analysis;
• 出版者：Springer Berlin Heidelberg
• ISSN：1618-2650
• 卷排序：409

文摘

Human axillary sweat is a poorly explored biofluid within the context of metabolomics when compared to other fluids such as blood and urine. In this paper, we explore the volatile organic compounds emitted from two different types of fabric samples (cotton and polyester) which had been worn repeatedly during exercise by participants. Headspace solid-phase microextraction (SPME) and comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC-TOFMS) were employed to profile the (semi)volatile compounds on the fabric. Principal component analysis models were applied to the data to aid in visualizing differences between types of fabrics, wash treatment, and the gender of the subject who had worn the fabric. Statistical tools included with commercial chromatography software (ChromaTOF) and a simple Fisher ratio threshold-based feature selection for model optimization are compared with a custom-written algorithm that uses cluster resolution as an objective function to maximize in a hybrid backward-elimination forward-selection approach for optimizing the chemometric models in an effort to identify some compounds that correlate to differences between fabric types. The custom algorithm is shown to generate better models than the simple Fisher ratio approach.