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Poisson statistics-mediated particle/cell counting in microwell arrays
Precise determination of particle or cell numbers is of importance for a wide array of applications in environmental studies, medical and biological applications, or manufacturing and monitoring applications in industrial production processes. A number of techniques ranging from manual counting to s...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5799205/ https://www.ncbi.nlm.nih.gov/pubmed/29403088 http://dx.doi.org/10.1038/s41598-018-20913-0 |
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author | Ahrberg, Christian D. Lee, Jong Min Chung, Bong Geun |
author_facet | Ahrberg, Christian D. Lee, Jong Min Chung, Bong Geun |
author_sort | Ahrberg, Christian D. |
collection | PubMed |
description | Precise determination of particle or cell numbers is of importance for a wide array of applications in environmental studies, medical and biological applications, or manufacturing and monitoring applications in industrial production processes. A number of techniques ranging from manual counting to sophisticated equipment (e.g., flow cytometry) are available for this task. However, these methods are either labour intensive, prone to error, or require expensive equipment. Here, we present a fast, simple method for determining the number density of cells or microparticles using a microwell array. We analyze the light transmission of the microwells and categorize the microwells into two groups. As particles/cells contained in a microwell locally reduce the light transmission, these wells displayed a lower average transmission compared to unoccupied microwells. The number density of particles/cells can be calculated by Poisson statistics from the ratio of occupied to unoccupied microwells. Following this approach, the number densities of two different types of microparticles, as well as HeLa and E. Coli cells, ranging over four orders of magnitude were determined. Through the microwell array defined by microfabrication, a simple image recognition algorithm can be used with the formation of aggregates or irregular shaped samples providing no additional difficulty to the microwell recognition. Additionally, this method can be carried out using only simple equipment and data analysis automated by a computer program. |
format | Online Article Text |
id | pubmed-5799205 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-57992052018-02-14 Poisson statistics-mediated particle/cell counting in microwell arrays Ahrberg, Christian D. Lee, Jong Min Chung, Bong Geun Sci Rep Article Precise determination of particle or cell numbers is of importance for a wide array of applications in environmental studies, medical and biological applications, or manufacturing and monitoring applications in industrial production processes. A number of techniques ranging from manual counting to sophisticated equipment (e.g., flow cytometry) are available for this task. However, these methods are either labour intensive, prone to error, or require expensive equipment. Here, we present a fast, simple method for determining the number density of cells or microparticles using a microwell array. We analyze the light transmission of the microwells and categorize the microwells into two groups. As particles/cells contained in a microwell locally reduce the light transmission, these wells displayed a lower average transmission compared to unoccupied microwells. The number density of particles/cells can be calculated by Poisson statistics from the ratio of occupied to unoccupied microwells. Following this approach, the number densities of two different types of microparticles, as well as HeLa and E. Coli cells, ranging over four orders of magnitude were determined. Through the microwell array defined by microfabrication, a simple image recognition algorithm can be used with the formation of aggregates or irregular shaped samples providing no additional difficulty to the microwell recognition. Additionally, this method can be carried out using only simple equipment and data analysis automated by a computer program. Nature Publishing Group UK 2018-02-05 /pmc/articles/PMC5799205/ /pubmed/29403088 http://dx.doi.org/10.1038/s41598-018-20913-0 Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Ahrberg, Christian D. Lee, Jong Min Chung, Bong Geun Poisson statistics-mediated particle/cell counting in microwell arrays |
title | Poisson statistics-mediated particle/cell counting in microwell arrays |
title_full | Poisson statistics-mediated particle/cell counting in microwell arrays |
title_fullStr | Poisson statistics-mediated particle/cell counting in microwell arrays |
title_full_unstemmed | Poisson statistics-mediated particle/cell counting in microwell arrays |
title_short | Poisson statistics-mediated particle/cell counting in microwell arrays |
title_sort | poisson statistics-mediated particle/cell counting in microwell arrays |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5799205/ https://www.ncbi.nlm.nih.gov/pubmed/29403088 http://dx.doi.org/10.1038/s41598-018-20913-0 |
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