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Breath Analysis as a Potential and Non-Invasive Frontier in Disease Diagnosis: An Overview

期刊

METABOLITES
卷 5, 期 1, 页码 3-55

出版社

MDPI
DOI: 10.3390/metabo5010003

关键词

Exhaled Breath (EB) analysis; Disease diagnosis; volatile organic compounds (VOCs); volatile fingerprint; breath analysis based disease diagnosis (BADD)

资金

  1. Portuguese Foundation for Science and Technology (FCT) through the MS Portuguese Networks [REDE/1508/RNEM/2010]
  2. pluriannual base funding [PEst-OE/QUI/UI0674/2011]
  3. ERA-NET, FP 7 [New-INDIGO/0003/2012]
  4. BPD [66177/2009]
  5. Department of Biotechnology (DBT), Ministry of Science & Technology, Government of India (New Indigo project) [BT/IN/New Indigo/03/RS/2013]

向作者/读者索取更多资源

Currently, a small number of diseases, particularly cardiovascular (CVDs), oncologic (ODs), neurodegenerative (NDDs), chronic respiratory diseases, as well as diabetes, form a severe burden to most of the countries worldwide. Hence, there is an urgent need for development of efficient diagnostic tools, particularly those enabling reliable detection of diseases, at their early stages, preferably using non-invasive approaches. Breath analysis is a non-invasive approach relying only on the characterisation of volatile composition of the exhaled breath (EB) that in turn reflects the volatile composition of the bloodstream and airways and therefore the status and condition of the whole organism metabolism. Advanced sampling procedures (solid-phase and needle traps microextraction) coupled with modern analytical technologies (proton transfer reaction mass spectrometry, selected ion flow tube mass spectrometry, ion mobility spectrometry, e-noses, etc.) allow the characterisation of EB composition to an unprecedented level. However, a key challenge in EB analysis is the proper statistical analysis and interpretation of the large and heterogeneous datasets obtained from EB research. There is no standard statistical framework/protocol yet available in literature that can be used for EB data analysis towards discovery of biomarkers for use in a typical clinical setup. Nevertheless, EB analysis has immense potential towards development of biomarkers for the early disease diagnosis of diseases.

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