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Population analysis to increase the robustness of molecular computational identification and its extension into the near-infrared for substantial numbers of small objects
The first population analysis is presented for submillimetric polymer beads which are tagged with five multi-valued logic gates, YES, 2YES + PASS 1, YES + PASS 1, YES + 2PASS 1 and PASS 1 with H(+) input, 700 nm near-infrared fluorescence output and 615 nm red excitation light as the power supply. T...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Royal Society of Chemistry
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6390691/ https://www.ncbi.nlm.nih.gov/pubmed/30881652 http://dx.doi.org/10.1039/c8sc05548c |
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author | Yao, Chaoyi Ling, Jue Chen, Linyihong de Silva, A. Prasanna |
author_facet | Yao, Chaoyi Ling, Jue Chen, Linyihong de Silva, A. Prasanna |
author_sort | Yao, Chaoyi |
collection | PubMed |
description | The first population analysis is presented for submillimetric polymer beads which are tagged with five multi-valued logic gates, YES, 2YES + PASS 1, YES + PASS 1, YES + 2PASS 1 and PASS 1 with H(+) input, 700 nm near-infrared fluorescence output and 615 nm red excitation light as the power supply. The gates carry an azaBODIPY fluorophore and an aliphatic tertiary amine as the H(+) receptor where necessary. Each logic tag has essentially identical emission characteristics except for the H(+)-induced fluorescence enhancement factors which consistently map onto the theoretical predictions, after allowing for bead-to-bead statistical variability for the first time. These enhancement factors are signatures which identify a given bead type within a mixed population when examined with a ‘wash and watch’ protocol under a fluorescence microscope. This delineates the scope of molecular computational identification (MCID) for encoding objects which are too small for radiofrequency identification (RFID) tagging. |
format | Online Article Text |
id | pubmed-6390691 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Royal Society of Chemistry |
record_format | MEDLINE/PubMed |
spelling | pubmed-63906912019-03-15 Population analysis to increase the robustness of molecular computational identification and its extension into the near-infrared for substantial numbers of small objects Yao, Chaoyi Ling, Jue Chen, Linyihong de Silva, A. Prasanna Chem Sci Chemistry The first population analysis is presented for submillimetric polymer beads which are tagged with five multi-valued logic gates, YES, 2YES + PASS 1, YES + PASS 1, YES + 2PASS 1 and PASS 1 with H(+) input, 700 nm near-infrared fluorescence output and 615 nm red excitation light as the power supply. The gates carry an azaBODIPY fluorophore and an aliphatic tertiary amine as the H(+) receptor where necessary. Each logic tag has essentially identical emission characteristics except for the H(+)-induced fluorescence enhancement factors which consistently map onto the theoretical predictions, after allowing for bead-to-bead statistical variability for the first time. These enhancement factors are signatures which identify a given bead type within a mixed population when examined with a ‘wash and watch’ protocol under a fluorescence microscope. This delineates the scope of molecular computational identification (MCID) for encoding objects which are too small for radiofrequency identification (RFID) tagging. Royal Society of Chemistry 2019-01-16 /pmc/articles/PMC6390691/ /pubmed/30881652 http://dx.doi.org/10.1039/c8sc05548c Text en This journal is © The Royal Society of Chemistry 2019 http://creativecommons.org/licenses/by-nc/3.0/ This article is freely available. This article is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported Licence (CC BY-NC 3.0) |
spellingShingle | Chemistry Yao, Chaoyi Ling, Jue Chen, Linyihong de Silva, A. Prasanna Population analysis to increase the robustness of molecular computational identification and its extension into the near-infrared for substantial numbers of small objects |
title | Population analysis to increase the robustness of molecular computational identification and its extension into the near-infrared for substantial numbers of small objects
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title_full | Population analysis to increase the robustness of molecular computational identification and its extension into the near-infrared for substantial numbers of small objects
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title_fullStr | Population analysis to increase the robustness of molecular computational identification and its extension into the near-infrared for substantial numbers of small objects
|
title_full_unstemmed | Population analysis to increase the robustness of molecular computational identification and its extension into the near-infrared for substantial numbers of small objects
|
title_short | Population analysis to increase the robustness of molecular computational identification and its extension into the near-infrared for substantial numbers of small objects
|
title_sort | population analysis to increase the robustness of molecular computational identification and its extension into the near-infrared for substantial numbers of small objects |
topic | Chemistry |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6390691/ https://www.ncbi.nlm.nih.gov/pubmed/30881652 http://dx.doi.org/10.1039/c8sc05548c |
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