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Updating the ELISA standard curve fitting process to reduce uncertainty in estimated microcystin concentrations
This study is aimed at exploring the optimal ELISA standard curve fitting process for reducing measurement uncertainty. Using an ELISA kit for measuring cyanobacterial toxin (microcystin), we show that uncertainty associated with the estimated microcystin concentrations can be reduced by defining th...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6050442/ https://www.ncbi.nlm.nih.gov/pubmed/30023312 http://dx.doi.org/10.1016/j.mex.2018.03.011 |
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author | Nummer, Stephanie A. Weeden, Alexandra J. Shaw, Chloe Snyder, Brenda K. Bridgeman, Thomas B. Qian, Song S. |
author_facet | Nummer, Stephanie A. Weeden, Alexandra J. Shaw, Chloe Snyder, Brenda K. Bridgeman, Thomas B. Qian, Song S. |
author_sort | Nummer, Stephanie A. |
collection | PubMed |
description | This study is aimed at exploring the optimal ELISA standard curve fitting process for reducing measurement uncertainty. Using an ELISA kit for measuring cyanobacterial toxin (microcystin), we show that uncertainty associated with the estimated microcystin concentrations can be reduced by defining the standard curve as a four-parameter logistic function on the natural log concentration scale, instead of the current approach of defining the curve on the concentration scale. The model comparison method is outlined in this paper, allowing it to be transferable to test different statistical models for other ELISA test kits. |
format | Online Article Text |
id | pubmed-6050442 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-60504422018-07-18 Updating the ELISA standard curve fitting process to reduce uncertainty in estimated microcystin concentrations Nummer, Stephanie A. Weeden, Alexandra J. Shaw, Chloe Snyder, Brenda K. Bridgeman, Thomas B. Qian, Song S. MethodsX Mathematics This study is aimed at exploring the optimal ELISA standard curve fitting process for reducing measurement uncertainty. Using an ELISA kit for measuring cyanobacterial toxin (microcystin), we show that uncertainty associated with the estimated microcystin concentrations can be reduced by defining the standard curve as a four-parameter logistic function on the natural log concentration scale, instead of the current approach of defining the curve on the concentration scale. The model comparison method is outlined in this paper, allowing it to be transferable to test different statistical models for other ELISA test kits. Elsevier 2018-04-12 /pmc/articles/PMC6050442/ /pubmed/30023312 http://dx.doi.org/10.1016/j.mex.2018.03.011 Text en © 2018 The Author(s) http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Mathematics Nummer, Stephanie A. Weeden, Alexandra J. Shaw, Chloe Snyder, Brenda K. Bridgeman, Thomas B. Qian, Song S. Updating the ELISA standard curve fitting process to reduce uncertainty in estimated microcystin concentrations |
title | Updating the ELISA standard curve fitting process to reduce uncertainty in estimated microcystin concentrations |
title_full | Updating the ELISA standard curve fitting process to reduce uncertainty in estimated microcystin concentrations |
title_fullStr | Updating the ELISA standard curve fitting process to reduce uncertainty in estimated microcystin concentrations |
title_full_unstemmed | Updating the ELISA standard curve fitting process to reduce uncertainty in estimated microcystin concentrations |
title_short | Updating the ELISA standard curve fitting process to reduce uncertainty in estimated microcystin concentrations |
title_sort | updating the elisa standard curve fitting process to reduce uncertainty in estimated microcystin concentrations |
topic | Mathematics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6050442/ https://www.ncbi.nlm.nih.gov/pubmed/30023312 http://dx.doi.org/10.1016/j.mex.2018.03.011 |
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