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  4. Salivary volatile organic compound analysis: an optimised methodology and longitudinal assessment using direct injection mass spectrometry
 
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Salivary volatile organic compound analysis: an optimised methodology and longitudinal assessment using direct injection mass spectrometry
File(s)
applsci-13-04084.pdf (1.15 MB)
Published version
Author(s)
Vadhwana, Bhamini
James, Jack
Pelling, Melina
Belluomo, Ilaria
Boshier, Piers
more
Type
Journal Article
Abstract
Analysis of salivary volatile organic compounds (VOCs) may offer a novel noninvasive modality for disease detection. This study aims to optimise saliva headspace VOC analysis and assess longitudinal variation of salivary VOCs. Whole saliva from healthy participants was acquired in order to assess four methodological parameters: saliva collection, volume, dilution, and acidification. Saliva VOCs were analysed using untargeted proton transfer reaction time-of-flight mass spectrometry. Using the optimised method, five saliva samples collected over 3 weeks assessed the longitudinal VOC variability and reproducibility with targeted selected ion flow tube-mass spectrometry analysis. The method of saliva collection influenced VOC detection and was a source of contamination. An amount of 500 µL of whole saliva by passive drool yielded optimal VOCs. Longitudinal variation was negligible with target short chain fatty acids and aldehydes. However, certain compounds showed variability suggesting the influence of potential exogenous factors. Overall, there was an acceptable range of inter- and intraindividual VOC variability. Standardisation with morning sampling after a 6 h fast is recommended demonstrating minimal intersubject variability. Future studies should seek to establish salivary VOC levels in healthy and diseased populations.
Date Issued
2023-03-23
Date Acceptance
2023-03-21
Citation
Applied Sciences, 2023, 13 (7), pp.1-10
URI
http://hdl.handle.net/10044/1/103588
URL
https://www.mdpi.com/2076-3417/13/7/4084
DOI
https://www.dx.doi.org/10.3390/app13074084
ISSN
2076-3417
Publisher
MDPI AG
Start Page
1
End Page
10
Journal / Book Title
Applied Sciences
Volume
13
Issue
7
Copyright Statement
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
License URL
https://creativecommons.org/licenses/by/4.0/
Identifier
https://www.mdpi.com/2076-3417/13/7/4084
Publication Status
Published
Article Number
4084
Date Publish Online
2023-03-23
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