Bedoukian   RussellIPM   RussellIPM   Piezoelectric Micro-Sprayer


Home
Animal Taxa
Plant Taxa
Semiochemicals
Floral Compounds
Semiochemical Detail
Semiochemicals & Taxa
Synthesis
Control
Invasive spp.
References

Abstract

Guide

Alphascents
Pherobio
InsectScience
E-Econex
Counterpart-Semiochemicals
Print
Email to a Friend
Kindly Donate for The Pherobase

« Previous AbstractAnalytical characterisation of Negroamaro red wines by 'Aroma Wheels'    Next AbstractFunctional analysis of expressed peptides that bind yeast STE proteins »

Biomed Chromatogr


Title:Chromatographic analysis of VOC patterns in exhaled breath from smokers and nonsmokers
Author(s):Capone S; Tufariello M; Forleo A; Longo V; Giampetruzzi L; Radogna AV; Casino F; Siciliano P;
Address:"National Research Council, Institute for Microelectronics and Microsystem, Lecce, Italy. National Research Council, Institute of Sciences of Food Production, Lecce, Italy"
Journal Title:Biomed Chromatogr
Year:2018
Volume:20171212
Issue:4
Page Number: -
DOI: 10.1002/bmc.4132
ISSN/ISBN:1099-0801 (Electronic) 0269-3879 (Linking)
Abstract:"Cigarette smoking harms nearly every organ of the body and causes many diseases. The analysis of exhaled breath for exogenous and endogenous volatile organic compounds (VOCs) can provide fundamental information on active smoking and insight into the health damage that smoke is creating. Various exhaled VOCs have been reported as typical of smoking habit and recent tobacco consumption, but to date, no eligible biomarkers have been identified. Aiming to identify such potential biomarkers, in this pilot study we analyzed the chemical patterns of exhaled breath from 26 volunteers divided into groups of nonsmokers and subgroups of smokers sampled at different periods of withdrawal from smoking. Solid-phase microextraction technique and gas chromatography/mass spectrometry methods were applied. Many breath VOCs were identified and quantified in very low concentrations (ppbv range), but only a few (toluene, pyridine, pyrrole, benzene, 2-butanone, 2-pentanone and 1-methyldecyclamine) were found to be statistically significant variables by Mann-Whitney test. In our analysis, we did not consider the predictive power of individual VOCs, as well as the criterion of uniqueness for biomarkers suggests, but we used the patterns of the only statistically significant compounds. Probit prediction model based on statistical relevant VOCs-patterns showed that assessment of smoking status is heavily time dependent. In a two-class classifier model, it is possible to predict with high specificity and sensitivity if a subject is a smoker who respected 1 hour of abstinence from smoking (short-term exposure to tobacco) or a smoker (labelled 'blank smoker') after a night out of smoking (long-term exposure to tobacco). On the other side, in our study 'blank smokers' are more like non-smokers so that the two classes cannot be well distinguished and the corresponding prediction results showed a good sensitivity but low selectivity"
Keywords:"Biomarkers/*analysis Breath Tests/*methods Gas Chromatography-Mass Spectrometry/*methods Humans Smokers/statistics & numerical data Smoking/*metabolism Solid Phase Microextraction Statistics, Nonparametric Volatile Organic Compounds/*analysis/isolation &;"
Notes:"MedlineCapone, Simonetta Tufariello, Maria Forleo, Angiola Longo, Valentina Giampetruzzi, Lucia Radogna, Antonio Vincenzo Casino, Flavio Siciliano, Pietro eng England 2017/11/14 Biomed Chromatogr. 2018 Apr; 32(4). doi: 10.1002/bmc.4132. Epub 2017 Dec 12"

 
Back to top
 
Citation: El-Sayed AM 2024. The Pherobase: Database of Pheromones and Semiochemicals. <http://www.pherobase.com>.
© 2003-2024 The Pherobase - Extensive Database of Pheromones and Semiochemicals. Ashraf M. El-Sayed.
Page created on 29-06-2024