Multi-odor discrimination by rat sniffing for potential monitoring of lung cancer and diabetes

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dc.contributor.authorYunkwang Oh-
dc.contributor.authorOhseok Kwon-
dc.contributor.authorS S Min-
dc.contributor.authorYong-Beom Shin-
dc.contributor.authorM K Oh-
dc.contributor.authorMoonil Kim-
dc.description.abstractThe discrimination learning of multiple odors, in which multi-odor can be associated with different responses, is important for responding quickly and accurately to changes in the external environment. However, very few studies have been done on multi-odor discrimination by animal sniffing. Herein, we report a novel multi-odor discrimination system by detection rats based on the combination of 2-Choice and Go/No-Go (GNG) tasks into a single paradigm, in which the Go response of GNG was replaced by 2-Choice, for detection of toluene and acetone, which are odor indicators of lung cancer and diabetes, respectively. Three of six trained rats reached performance criterion, in 12 consecutive successful tests within a given set or over 12 sets with a success rate of over 90%. Through a total of 1300 tests, the trained animals (N = 3) showed multi-odor sensing performance with 88% accuracy, 87% sensitivity and 90% specificity. In addition, a dependence of behavior response time on odor concentrations under given concentration conditions was observed, suggesting that the system could be used for quantitative measurements. Furthermore, the animals’ multi-odor sensing performance has lasted for 45 days, indicating long-term stability of the learned multi-odor discrimination. These findings demonstrate that multi-odor discrimination can be achieved by rat sniffing, potentially providing insight into the rapid, accurate and cost-effective multi-odor monitoring in the lung cancer and diabetes.-
dc.titleMulti-odor discrimination by rat sniffing for potential monitoring of lung cancer and diabetes-
dc.title.alternativeMulti-odor discrimination by rat sniffing for potential monitoring of lung cancer and diabetes-
dc.contributor.affiliatedAuthorYunkwang Oh-
dc.contributor.affiliatedAuthorOhseok Kwon-
dc.contributor.affiliatedAuthorYong-Beom Shin-
dc.contributor.affiliatedAuthorMoonil Kim-
dc.identifier.bibliographicCitationSensors, vol. 21, no. 11, pp. 3696-3696-
dc.subject.keywordMulti-odor discrimination-
dc.subject.keywordAnimal biosensor-
dc.subject.keywordOlfactory behavior-
dc.subject.localAnimal biosensor-
Appears in Collections:
Division of Research on National Challenges > Infectious Disease Research Center > 1. Journal Articles
Division of Biomaterials Research > Bionanotechnology Research Center > 1. Journal Articles
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