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Evaluation of Discrimination Performance in Case for Multiple Non-Discriminated Samples: Classification of Honeys by Fluorescent Fingerprinting
In this study we develop a variant of fluorescent sensor array technique based on addition of fluorophores to samples. A correct choice of fluorophores is critical for the successful application of the technique, which calls for the necessity of comparing different discrimination protocols. We used...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7570986/ https://www.ncbi.nlm.nih.gov/pubmed/32961995 http://dx.doi.org/10.3390/s20185351 |
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author | Rukosueva, Elizaveta A. Belikova, Valeria A. Krylov, Ivan N. Orekhov, Vladislav S. Skorobogatov, Evgenii V. Garmash, Andrei V. Beklemishev, Mikhail K. |
author_facet | Rukosueva, Elizaveta A. Belikova, Valeria A. Krylov, Ivan N. Orekhov, Vladislav S. Skorobogatov, Evgenii V. Garmash, Andrei V. Beklemishev, Mikhail K. |
author_sort | Rukosueva, Elizaveta A. |
collection | PubMed |
description | In this study we develop a variant of fluorescent sensor array technique based on addition of fluorophores to samples. A correct choice of fluorophores is critical for the successful application of the technique, which calls for the necessity of comparing different discrimination protocols. We used 36 honey samples from different sources to which various fluorophores were added (tris-(2,2′-bipyridyl) dichlororuthenium(II) (Ru(bpy)(3)(2+)), zinc(II) 8-hydroxyquinoline-5-sulfonate (8-Ox-Zn), and thiazole orange in the presence of two types of deoxyribonucleic acid). The fluorescence spectra were obtained within 400–600 nm and treated by principal component analysis (PCA). No fluorophore allowed for the discrimination of all samples. To evaluate the discrimination performance of fluorophores, we introduced crossing number (CrN) calculated as the number of mutual intersections of confidence ellipses in the PCA scores plots, and relative position (RP) characterized by the pairwise mutual location of group centers and their most distant points. CrN and RP parameters correlated with each other, with total sensitivity (TS) calculated by Mahalanobis distances, and with the overall rating based on all metrics, with coefficients of correlation over 0.7. Most of the considered parameters gave the first place in the discrimination performance to Ru(bpy)(3)(2+) fluorophore. |
format | Online Article Text |
id | pubmed-7570986 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-75709862020-10-28 Evaluation of Discrimination Performance in Case for Multiple Non-Discriminated Samples: Classification of Honeys by Fluorescent Fingerprinting Rukosueva, Elizaveta A. Belikova, Valeria A. Krylov, Ivan N. Orekhov, Vladislav S. Skorobogatov, Evgenii V. Garmash, Andrei V. Beklemishev, Mikhail K. Sensors (Basel) Article In this study we develop a variant of fluorescent sensor array technique based on addition of fluorophores to samples. A correct choice of fluorophores is critical for the successful application of the technique, which calls for the necessity of comparing different discrimination protocols. We used 36 honey samples from different sources to which various fluorophores were added (tris-(2,2′-bipyridyl) dichlororuthenium(II) (Ru(bpy)(3)(2+)), zinc(II) 8-hydroxyquinoline-5-sulfonate (8-Ox-Zn), and thiazole orange in the presence of two types of deoxyribonucleic acid). The fluorescence spectra were obtained within 400–600 nm and treated by principal component analysis (PCA). No fluorophore allowed for the discrimination of all samples. To evaluate the discrimination performance of fluorophores, we introduced crossing number (CrN) calculated as the number of mutual intersections of confidence ellipses in the PCA scores plots, and relative position (RP) characterized by the pairwise mutual location of group centers and their most distant points. CrN and RP parameters correlated with each other, with total sensitivity (TS) calculated by Mahalanobis distances, and with the overall rating based on all metrics, with coefficients of correlation over 0.7. Most of the considered parameters gave the first place in the discrimination performance to Ru(bpy)(3)(2+) fluorophore. MDPI 2020-09-18 /pmc/articles/PMC7570986/ /pubmed/32961995 http://dx.doi.org/10.3390/s20185351 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Rukosueva, Elizaveta A. Belikova, Valeria A. Krylov, Ivan N. Orekhov, Vladislav S. Skorobogatov, Evgenii V. Garmash, Andrei V. Beklemishev, Mikhail K. Evaluation of Discrimination Performance in Case for Multiple Non-Discriminated Samples: Classification of Honeys by Fluorescent Fingerprinting |
title | Evaluation of Discrimination Performance in Case for Multiple Non-Discriminated Samples: Classification of Honeys by Fluorescent Fingerprinting |
title_full | Evaluation of Discrimination Performance in Case for Multiple Non-Discriminated Samples: Classification of Honeys by Fluorescent Fingerprinting |
title_fullStr | Evaluation of Discrimination Performance in Case for Multiple Non-Discriminated Samples: Classification of Honeys by Fluorescent Fingerprinting |
title_full_unstemmed | Evaluation of Discrimination Performance in Case for Multiple Non-Discriminated Samples: Classification of Honeys by Fluorescent Fingerprinting |
title_short | Evaluation of Discrimination Performance in Case for Multiple Non-Discriminated Samples: Classification of Honeys by Fluorescent Fingerprinting |
title_sort | evaluation of discrimination performance in case for multiple non-discriminated samples: classification of honeys by fluorescent fingerprinting |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7570986/ https://www.ncbi.nlm.nih.gov/pubmed/32961995 http://dx.doi.org/10.3390/s20185351 |
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