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Quantitative Point-of-Care Colorimetric Assay Modeling Using a Handheld Colorimeter
[Image: see text] Colorimetric assays typically offer a rapid and convenient method to assess analytes that span healthcare monitoring to water quality testing. However, such tests can only provide qualitative results when employed in resource-limited settings or require bulky and expensive equipmen...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8412955/ https://www.ncbi.nlm.nih.gov/pubmed/34497933 http://dx.doi.org/10.1021/acsomega.1c03460 |
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author | Abels, Kristen Salvo-Halloran, Elizabeth M. White, Dawn Ali, Monsur Agarwal, Nisha R. Leung, Vincent Ali, Muntakim Sidawi, Mariam Capretta, Alfredo Brennan, John D. Nease, Jake Filipe, Carlos D. M. |
author_facet | Abels, Kristen Salvo-Halloran, Elizabeth M. White, Dawn Ali, Monsur Agarwal, Nisha R. Leung, Vincent Ali, Muntakim Sidawi, Mariam Capretta, Alfredo Brennan, John D. Nease, Jake Filipe, Carlos D. M. |
author_sort | Abels, Kristen |
collection | PubMed |
description | [Image: see text] Colorimetric assays typically offer a rapid and convenient method to assess analytes that span healthcare monitoring to water quality testing. However, such tests can only provide qualitative results when employed in resource-limited settings or require bulky and expensive equipment such as lab spectrophotometers to allow quantitative measurements. In this paper, we report on the use of a handheld colorimeter to quantitatively determine the concentration of analytes in a manner that is independent of ambient lighting or initial sample color. The method combines the response of the sensor with first-principles modeling that better describes the nature of the assay compared to linear-in-parameters regression modeling that is typically performed in other studies. This method was successfully demonstrated using a number of colorimetric assays: (1) determination of solution pH using a universal indicator, (2) quantification of the DNase presence using a DNA-gold nanoparticle assay, and (3) quantification of the concentration of the antibiotic tetracycline using a cell-based assay. |
format | Online Article Text |
id | pubmed-8412955 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | American Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-84129552021-09-07 Quantitative Point-of-Care Colorimetric Assay Modeling Using a Handheld Colorimeter Abels, Kristen Salvo-Halloran, Elizabeth M. White, Dawn Ali, Monsur Agarwal, Nisha R. Leung, Vincent Ali, Muntakim Sidawi, Mariam Capretta, Alfredo Brennan, John D. Nease, Jake Filipe, Carlos D. M. ACS Omega [Image: see text] Colorimetric assays typically offer a rapid and convenient method to assess analytes that span healthcare monitoring to water quality testing. However, such tests can only provide qualitative results when employed in resource-limited settings or require bulky and expensive equipment such as lab spectrophotometers to allow quantitative measurements. In this paper, we report on the use of a handheld colorimeter to quantitatively determine the concentration of analytes in a manner that is independent of ambient lighting or initial sample color. The method combines the response of the sensor with first-principles modeling that better describes the nature of the assay compared to linear-in-parameters regression modeling that is typically performed in other studies. This method was successfully demonstrated using a number of colorimetric assays: (1) determination of solution pH using a universal indicator, (2) quantification of the DNase presence using a DNA-gold nanoparticle assay, and (3) quantification of the concentration of the antibiotic tetracycline using a cell-based assay. American Chemical Society 2021-08-17 /pmc/articles/PMC8412955/ /pubmed/34497933 http://dx.doi.org/10.1021/acsomega.1c03460 Text en © 2021 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by-nc-nd/4.0/Permits non-commercial access and re-use, provided that author attribution and integrity are maintained; but does not permit creation of adaptations or other derivative works (https://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Abels, Kristen Salvo-Halloran, Elizabeth M. White, Dawn Ali, Monsur Agarwal, Nisha R. Leung, Vincent Ali, Muntakim Sidawi, Mariam Capretta, Alfredo Brennan, John D. Nease, Jake Filipe, Carlos D. M. Quantitative Point-of-Care Colorimetric Assay Modeling Using a Handheld Colorimeter |
title | Quantitative Point-of-Care Colorimetric Assay Modeling
Using a Handheld Colorimeter |
title_full | Quantitative Point-of-Care Colorimetric Assay Modeling
Using a Handheld Colorimeter |
title_fullStr | Quantitative Point-of-Care Colorimetric Assay Modeling
Using a Handheld Colorimeter |
title_full_unstemmed | Quantitative Point-of-Care Colorimetric Assay Modeling
Using a Handheld Colorimeter |
title_short | Quantitative Point-of-Care Colorimetric Assay Modeling
Using a Handheld Colorimeter |
title_sort | quantitative point-of-care colorimetric assay modeling
using a handheld colorimeter |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8412955/ https://www.ncbi.nlm.nih.gov/pubmed/34497933 http://dx.doi.org/10.1021/acsomega.1c03460 |
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