OBJECTIVE: To use an electronic nose to identify common upper respiratory bacterial pathogens. STUDY DESIGN: Controlled in vitro analysis. METHODS: Swabs of bacteria were obtained from in vitro samples. The specimens were vaporized and analyzed over the organic semiconductor-based electronic nose (Cyranose 320). Data from the 32-element sensor array were subjected to principal component analysis for depiction in two-dimensional space and differences in odorant patterns were assessed by calculating Mahalanobis distances. RESULTS: The electronic nose was able to distinguish between control swabs and bacterial samples. Furthermore, calculation of the Mahalanobis distances among the various bacteria demonstrated distinct odorant classes (Mahalanobis distance > or = 3). This demonstrates that the electronic nose could differentiate among various common bacterial pathogens of the upper respiratory tract, including Staphylococcus aureus, Streptococcus pneumoniae, Haemophilus influenza, and Pseudomonas aeruginosa. CONCLUSIONS: The electronic nose represents a novel method to identify potential upper respiratory infections and to discriminate among common upper respiratory bacterial pathogens. This technology could provide a rapid means to identify organisms causing upper respiratory infections.
OBJECTIVE: To use an electronic nose to identify common upper respiratory bacterial pathogens. STUDY DESIGN: Controlled in vitro analysis. METHODS: Swabs of bacteria were obtained from in vitro samples. The specimens were vaporized and analyzed over the organic semiconductor-based electronic nose (Cyranose 320). Data from the 32-element sensor array were subjected to principal component analysis for depiction in two-dimensional space and differences in odorant patterns were assessed by calculating Mahalanobis distances. RESULTS: The electronic nose was able to distinguish between control swabs and bacterial samples. Furthermore, calculation of the Mahalanobis distances among the various bacteria demonstrated distinct odorant classes (Mahalanobis distance > or = 3). This demonstrates that the electronic nose could differentiate among various common bacterial pathogens of the upper respiratory tract, including Staphylococcus aureus, Streptococcus pneumoniae, Haemophilus influenza, and Pseudomonas aeruginosa. CONCLUSIONS: The electronic nose represents a novel method to identify potential upper respiratory infections and to discriminate among common upper respiratory bacterial pathogens. This technology could provide a rapid means to identify organisms causing upper respiratory infections.
Authors: Roberto F Machado; Daniel Laskowski; Olivia Deffenderfer; Timothy Burch; Shuo Zheng; Peter J Mazzone; Tarek Mekhail; Constance Jennings; James K Stoller; Jacqueline Pyle; Jennifer Duncan; Raed A Dweik; Serpil C Erzurum Journal: Am J Respir Crit Care Med Date: 2005-03-04 Impact factor: 21.405
Authors: R Fend; R Geddes; S Lesellier; H-M Vordermeier; L A L Corner; E Gormley; E Costello; R G Hewinson; D J Marlin; A C Woodman; M A Chambers Journal: J Clin Microbiol Date: 2005-04 Impact factor: 5.948
Authors: Theodore R Mellors; Christiaan A Rees; Flavio A Franchina; Alison Burklund; Chaya Patel; Lucy J Hathaway; Jane E Hill Journal: J Chromatogr B Analyt Technol Biomed Life Sci Date: 2018-08-29 Impact factor: 3.205
Authors: Jussi Virtanen; Lauri Hokkinen; Markus Karjalainen; Anton Kontunen; Risto Vuento; Jura Numminen; Markus Rautiainen; Niku Oksala; Antti Roine; Ilkka Kivekäs Journal: Eur Arch Otorhinolaryngol Date: 2018-07-24 Impact factor: 2.503