4.7 Article

Spectroscopic molecular-fingerprint profiling of saliva

Journal

ANALYTICA CHIMICA ACTA
Volume 1185, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.aca.2021.339074

Keywords

Raman spectroscopy; Saliva profiling; Multivariate analysis; Diagnostic forensic biofluid

Funding

  1. Wellcome Trust [174ISSFPP, 213458/Z/18/Z]
  2. Royal Academy of Engineering [RF1415\14\28]
  3. EPSRC
  4. Wellcome Trust [213458/Z/18/Z] Funding Source: Wellcome Trust

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This study systematically investigated the molecular spectral fingerprint of saliva and developed a non-destructive molecular profiling approach using hybrid artificial neural network algorithms and Raman spectroscopy. The classification algorithm successfully identified gender and age information from saliva, laying the platform for applications in forensics and biosensing. The discernible spectral molecular 'barcodes' primarily stemmed from amino acid, protein, and lipid changes in saliva.
Saliva analysis has been gaining interest as a potential non-invasive source of disease indicative bio-markers due to being a complex biofluid correlating with blood-based constituents on a molecular level. For saliva to cement its usage for analytical applications, it is paramount to gain underpinning molecular knowledge and establish a 'baseline' of the salivary composition in healthy individuals as well as char-acterize how these factors are impacting its performance as potential analytical biofluid. Here, we have systematically studied the molecular spectral fingerprint of saliva, including the changes associated with gender, age, and time. Via hybrid artificial neural network algorithms and Raman spectroscopy, we have developed a non-destructive molecular profiling approach enabling the assessment of salivary spectral changes yielding the determination of gender and age of the biofluid source. Our classification algorithm successfully identified the gender and age from saliva with high classification accuracy. Discernible spectral molecular 'barcodes' were subsequently constructed for each class and found to primarily stem from amino acid, protein, and lipid changes in saliva. This unique combination of Raman spectroscopy and advanced machine learning techniques lays the platform for a variety of applications in forensics and biosensing. Crown Copyright (c) 2021 Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

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