Division of Psychology, Faculty of Natural Sciences, University of Stirling, Stirling FK9 4LA, UK.
Department of Civil, Architectural and Environmental Engineering, The University of Texas at Austin, Austin, TX 78712, USA.
Philos Trans R Soc Lond B Biol Sci. 2020 Jun 8;375(1800):20190259. doi: 10.1098/rstb.2019.0259. Epub 2020 Apr 20.
Odours can have a significant influence on the outcome of social interactions. However, we have yet to characterize the chemical signature of any specific social cue in human body odour, and we know little about how changes in social context influence odour chemistry. Here, we argue that adoption of emerging analytical techniques from other disciplines, such as atmospheric chemistry, might become game-changing tools in this endeavour. First, we describe the use of online chemical ionization time-of-flight mass spectrometry to sensitively measure many hundreds of gas-phase volatile organic compounds in real time. By analysing ambient air emanating from undisturbed individuals or groups, the technique enables a continuous recording of an instantaneous odour change in response to external stimuli and changing social context. This has considerable advantages over the traditional approach of periodic sampling for analysis by gas chromatography. We also discuss multivariate statistical approaches, such as positive matrix factorization, that can effectively sift through this complex datastream to identify linked groups of compounds that probably underpin functional chemosignals. In combination, these innovations offer new avenues for addressing outstanding questions concerning olfactory communication in humans and other species, as well as in related fields using odour, such as biometrics and disease diagnostics. This article is part of the Theo Murphy meeting issue 'Olfactory communication in humans'.
气味对社交互动的结果有重大影响。然而,我们还没有描述人类体臭中任何特定社交线索的化学特征,也不太了解社交环境的变化如何影响气味化学。在这里,我们认为采用来自其他学科的新兴分析技术,如大气化学,可能成为这一努力中的变革性工具。首先,我们描述了使用在线化学电离飞行时间质谱实时灵敏地测量数百种气相挥发性有机化合物的方法。通过分析来自未受干扰的个体或群体的环境空气,该技术能够连续记录对外界刺激和不断变化的社会环境的即时气味变化。这与通过气相色谱法定期采样进行分析的传统方法相比具有很大的优势。我们还讨论了多元统计方法,如正矩阵因子分解,该方法可以有效地筛选这种复杂的数据流,以识别可能构成功能化学生信号基础的相关化合物组。这些创新结合在一起,为解决有关人类和其他物种嗅觉交流以及使用气味(如生物识别和疾病诊断)的相关领域的悬而未决的问题提供了新的途径。本文是 Theo Murphy 会议议题“人类嗅觉交流”的一部分。