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 AbstractN(epsilon)-(carboxymethyl)lysine Concentration in Debris from Carotid Artery Stenting Correlates Independently with Signal Intensity on T1-Weighted Black-Blood Magnetic Resonance Images    Next AbstractElucidating the transformation pattern of the cereal allelochemical 6-methoxy-2-benzoxazolinone (MBOA) and the trideuteriomethoxy analogue [D3]-MBOA in soil »

J Breath Res


Title:"Detecting multiple sclerosis via breath analysis using an eNose, a pilot study"
Author(s):Ettema AR; Lenders M; Vliegen J; Slettenaar A; Tjepkema-Cloostermans MC; de Vos CC;
Address:"Department of Neurology and Neurosurgery, Medisch Spectrum Twente, Enschede, The Netherlands. Department of Clinical Neurophysiology, University of Twente, Enschede, The Netherlands. Department of Anesthesiology, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands"
Journal Title:J Breath Res
Year:2021
Volume:20210111
Issue:2
Page Number: -
DOI: 10.1088/1752-7163/abd080
ISSN/ISBN:1752-7163 (Electronic) 1752-7155 (Linking)
Abstract:"In the present study we investigated whether multiple sclerosis (MS) can be detected via exhaled breath analysis using an electronic nose (eNose). The Aeonose(TM)(an eNose, The eNose Company, Zutphen, the Netherlands) is a diagnostic test device to detect patterns of volatile organic compounds in exhaled breath. We evaluated whether the Aeonose(TM)can make a distinction between the breath patterns of patients with MS and healthy control subjects. In this mono-center, prospective, non-invasive study, 124 subjects with a confirmed diagnosis of MS and 129 control subjects each breathed into the Aeonose(TM)for 5 min. Exhaled breath data was used to train an artificial neural network (ANN) predictive model. To investigate the influence of medication intake we created a second predictive model with a subgroup of MS patients without medication prescribed for MS. The ANN model based on the entire dataset was able to distinguish MS patients from healthy controls with a sensitivity of 0.75 (95% CI: 0.66-0.82) and specificity of 0.60 (0.51-0.69). The model created with the subgroup of MS patients not using medication and the healthy control subjects had a sensitivity of 0.93 (0.82-0.98) and a specificity of 0.74 (0.65-0.81). The study showed that the Aeonose(TM)is able to make a distinction between MS patients and healthy control subjects, and could potentially provide a quick screening test to assist in diagnosing MS. Further research is needed to determine whether the Aeonose(TM)is able to differentiate new MS patients from subjects who will not get the diagnosis"
Keywords:Breath Tests Electronic Nose Humans *Multiple Sclerosis Pilot Projects Prospective Studies *Volatile Organic Compounds exhaled breath analysis multiple sclerosis (MS) volatile organic compounds (VOCs);
Notes:"MedlineEttema, A R Lenders, M W P M Vliegen, J Slettenaar, A Tjepkema-Cloostermans, M C de Vos, C C eng England 2020/12/04 J Breath Res. 2021 Jan 11; 15(2). doi: 10.1088/1752-7163/abd080"

 
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 22-11-2024