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Advisor(s)
Abstract(s)
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.
Description
Keywords
Exhaled Breath (EB) analysis Disease diagnosis Volatile organic compounds (VOCs) Volatile fingerprint Breath analysis based disease diagnosis (BADD) . Faculdade de Ciências Exatas e da Engenharia Centro de Química da Madeira
Citation
Pereira, J., Porto-Figueira, P., Cavaco, C., Taunk, K., Rapole, S., Dhakne, R., ... & Câmara, J. S. (2015). Breath analysis as a potential and non-invasive frontier in disease diagnosis: an overview. Metabolites, 5(1), 3-55. https://doi.org/10.3390/metabo5010003
Publisher
MDPI