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Voltammetric Electronic Tongue for the Simultaneous Determination of Three Benzodiazepines
The presented manuscript reports the simultaneous detection of a ternary mixture of the benzodiazepines diazepam, lorazepam, and flunitrazepam using an array of voltammetric sensors and the electronic tongue principle. The electrodes used in the array were selected from a set of differently modified...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6891414/ https://www.ncbi.nlm.nih.gov/pubmed/31744128 http://dx.doi.org/10.3390/s19225002 |
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author | Herrera-Chacón, Anna Torabi, Farzad Faridbod, Farnoush Ghasemi, Jahan B. González-Calabuig, Andreu del Valle, Manel |
author_facet | Herrera-Chacón, Anna Torabi, Farzad Faridbod, Farnoush Ghasemi, Jahan B. González-Calabuig, Andreu del Valle, Manel |
author_sort | Herrera-Chacón, Anna |
collection | PubMed |
description | The presented manuscript reports the simultaneous detection of a ternary mixture of the benzodiazepines diazepam, lorazepam, and flunitrazepam using an array of voltammetric sensors and the electronic tongue principle. The electrodes used in the array were selected from a set of differently modified graphite epoxy composite electrodes; specifically, six electrodes were used incorporating metallic nanoparticles of Cu and Pt, oxide nanoparticles of CuO and WO(3), plus pristine electrodes of epoxy-graphite and metallic Pt disk. Cyclic voltammetry was the technique used to obtain the voltammetric responses. Multivariate examination using Principal Component Analysis (PCA) justified the choice of sensors in order to get the proper discrimination of the benzodiazepines. Next, a quantitative model to predict the concentrations of mixtures of the three benzodiazepines was built employing the set of voltammograms, and was first processed with the Discrete Wavelet Transform, which fed an artificial neural network response model. The developed model successfully predicted the concentration of the three compounds with a normalized root mean square error (NRMSE) of 0.034 and 0.106 for the training and test subsets, respectively, and coefficient of correlation R ≥ 0.938 in the predicted vs. expected concentrations comparison graph. |
format | Online Article Text |
id | pubmed-6891414 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-68914142019-12-12 Voltammetric Electronic Tongue for the Simultaneous Determination of Three Benzodiazepines Herrera-Chacón, Anna Torabi, Farzad Faridbod, Farnoush Ghasemi, Jahan B. González-Calabuig, Andreu del Valle, Manel Sensors (Basel) Article The presented manuscript reports the simultaneous detection of a ternary mixture of the benzodiazepines diazepam, lorazepam, and flunitrazepam using an array of voltammetric sensors and the electronic tongue principle. The electrodes used in the array were selected from a set of differently modified graphite epoxy composite electrodes; specifically, six electrodes were used incorporating metallic nanoparticles of Cu and Pt, oxide nanoparticles of CuO and WO(3), plus pristine electrodes of epoxy-graphite and metallic Pt disk. Cyclic voltammetry was the technique used to obtain the voltammetric responses. Multivariate examination using Principal Component Analysis (PCA) justified the choice of sensors in order to get the proper discrimination of the benzodiazepines. Next, a quantitative model to predict the concentrations of mixtures of the three benzodiazepines was built employing the set of voltammograms, and was first processed with the Discrete Wavelet Transform, which fed an artificial neural network response model. The developed model successfully predicted the concentration of the three compounds with a normalized root mean square error (NRMSE) of 0.034 and 0.106 for the training and test subsets, respectively, and coefficient of correlation R ≥ 0.938 in the predicted vs. expected concentrations comparison graph. MDPI 2019-11-16 /pmc/articles/PMC6891414/ /pubmed/31744128 http://dx.doi.org/10.3390/s19225002 Text en © 2019 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 Herrera-Chacón, Anna Torabi, Farzad Faridbod, Farnoush Ghasemi, Jahan B. González-Calabuig, Andreu del Valle, Manel Voltammetric Electronic Tongue for the Simultaneous Determination of Three Benzodiazepines |
title | Voltammetric Electronic Tongue for the Simultaneous Determination of Three Benzodiazepines |
title_full | Voltammetric Electronic Tongue for the Simultaneous Determination of Three Benzodiazepines |
title_fullStr | Voltammetric Electronic Tongue for the Simultaneous Determination of Three Benzodiazepines |
title_full_unstemmed | Voltammetric Electronic Tongue for the Simultaneous Determination of Three Benzodiazepines |
title_short | Voltammetric Electronic Tongue for the Simultaneous Determination of Three Benzodiazepines |
title_sort | voltammetric electronic tongue for the simultaneous determination of three benzodiazepines |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6891414/ https://www.ncbi.nlm.nih.gov/pubmed/31744128 http://dx.doi.org/10.3390/s19225002 |
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