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Smartphone-based low light detection for bioluminescence application
We report a smartphone-based device and associated imaging-processing algorithm to maximize the sensitivity of standard smartphone cameras, that can detect the presence of single-digit pW of radiant flux intensity. The proposed hardware and software, called bioluminescent-based analyte quantitation...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5220360/ https://www.ncbi.nlm.nih.gov/pubmed/28067287 http://dx.doi.org/10.1038/srep40203 |
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author | Kim, Huisung Jung, Youngkee Doh, Iyll-Joon Lozano-Mahecha, Roxana Andrea Applegate, Bruce Bae, Euiwon |
author_facet | Kim, Huisung Jung, Youngkee Doh, Iyll-Joon Lozano-Mahecha, Roxana Andrea Applegate, Bruce Bae, Euiwon |
author_sort | Kim, Huisung |
collection | PubMed |
description | We report a smartphone-based device and associated imaging-processing algorithm to maximize the sensitivity of standard smartphone cameras, that can detect the presence of single-digit pW of radiant flux intensity. The proposed hardware and software, called bioluminescent-based analyte quantitation by smartphone (BAQS), provides an opportunity for onsite analysis and quantitation of luminescent signals from biological and non-biological sensing elements which emit photons in response to an analyte. A simple cradle that houses the smartphone, sample tube, and collection lens supports the measuring platform, while noise reduction by ensemble averaging simultaneously lowers the background and enhances the signal from emitted photons. Five different types of smartphones, both Android and iOS devices, were tested, and the top two candidates were used to evaluate luminescence from the bioluminescent reporter Pseudomonas fluorescens M3A. The best results were achieved by OnePlus One (android), which was able to detect luminescence from ~10(6) CFU/mL of the bio-reporter, which corresponds to ~10(7) photons/s with 180 seconds of integration time. |
format | Online Article Text |
id | pubmed-5220360 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-52203602017-01-11 Smartphone-based low light detection for bioluminescence application Kim, Huisung Jung, Youngkee Doh, Iyll-Joon Lozano-Mahecha, Roxana Andrea Applegate, Bruce Bae, Euiwon Sci Rep Article We report a smartphone-based device and associated imaging-processing algorithm to maximize the sensitivity of standard smartphone cameras, that can detect the presence of single-digit pW of radiant flux intensity. The proposed hardware and software, called bioluminescent-based analyte quantitation by smartphone (BAQS), provides an opportunity for onsite analysis and quantitation of luminescent signals from biological and non-biological sensing elements which emit photons in response to an analyte. A simple cradle that houses the smartphone, sample tube, and collection lens supports the measuring platform, while noise reduction by ensemble averaging simultaneously lowers the background and enhances the signal from emitted photons. Five different types of smartphones, both Android and iOS devices, were tested, and the top two candidates were used to evaluate luminescence from the bioluminescent reporter Pseudomonas fluorescens M3A. The best results were achieved by OnePlus One (android), which was able to detect luminescence from ~10(6) CFU/mL of the bio-reporter, which corresponds to ~10(7) photons/s with 180 seconds of integration time. Nature Publishing Group 2017-01-09 /pmc/articles/PMC5220360/ /pubmed/28067287 http://dx.doi.org/10.1038/srep40203 Text en Copyright © 2017, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Kim, Huisung Jung, Youngkee Doh, Iyll-Joon Lozano-Mahecha, Roxana Andrea Applegate, Bruce Bae, Euiwon Smartphone-based low light detection for bioluminescence application |
title | Smartphone-based low light detection for bioluminescence application |
title_full | Smartphone-based low light detection for bioluminescence application |
title_fullStr | Smartphone-based low light detection for bioluminescence application |
title_full_unstemmed | Smartphone-based low light detection for bioluminescence application |
title_short | Smartphone-based low light detection for bioluminescence application |
title_sort | smartphone-based low light detection for bioluminescence application |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5220360/ https://www.ncbi.nlm.nih.gov/pubmed/28067287 http://dx.doi.org/10.1038/srep40203 |
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