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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...

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Detalles Bibliográficos
Autores principales: Nummer, Stephanie A., Weeden, Alexandra J., Shaw, Chloe, Snyder, Brenda K., Bridgeman, Thomas B., Qian, Song S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2018
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.
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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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