Spectroscopic approach for dynamic bioanalyte tracking with minimal concentration information
Vibrational spectroscopy has emerged as a promising tool for non-invasive, multiplexed measurement of blood constituents - an outstanding problem in biophotonics. Here, we propose a novel analytical framework that enables spectroscopy-based longitudinal tracking of chemical concentration without nec...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | en_US |
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Nature Publishing Group
2014
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| Online Access: | http://hdl.handle.net/1721.1/92575 https://orcid.org/0000-0003-4975-3815 https://orcid.org/0000-0003-1190-3144 |
| _version_ | 1811083215951101952 |
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| author | Spegazzini, Nicolas Barman, Ishan Dingari, Narahara Chari Pandey, Rishikesh Soares, Jaqueline S. Ozaki, Yukihiro Dasari, Ramachandra Rao |
| author2 | Massachusetts Institute of Technology. Department of Chemistry |
| author_facet | Massachusetts Institute of Technology. Department of Chemistry Spegazzini, Nicolas Barman, Ishan Dingari, Narahara Chari Pandey, Rishikesh Soares, Jaqueline S. Ozaki, Yukihiro Dasari, Ramachandra Rao |
| author_sort | Spegazzini, Nicolas |
| collection | MIT |
| description | Vibrational spectroscopy has emerged as a promising tool for non-invasive, multiplexed measurement of blood constituents - an outstanding problem in biophotonics. Here, we propose a novel analytical framework that enables spectroscopy-based longitudinal tracking of chemical concentration without necessitating extensive a priori concentration information. The principal idea is to employ a concentration space transformation acquired from the spectral information, where these estimates are used together with the concentration profiles generated from the system kinetic model. Using blood glucose monitoring by Raman spectroscopy as an illustrative example, we demonstrate the efficacy of the proposed approach as compared to conventional calibration methods. Specifically, our approach exhibits a 35% reduction in error over partial least squares regression when applied to a dataset acquired from human subjects undergoing glucose tolerance tests. This method offers a new route at screening gestational diabetes and opens doors for continuous process monitoring without sample perturbation at intermediate time points. |
| first_indexed | 2024-09-23T12:28:41Z |
| format | Article |
| id | mit-1721.1/92575 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T12:28:41Z |
| publishDate | 2014 |
| publisher | Nature Publishing Group |
| record_format | dspace |
| spelling | mit-1721.1/925752022-10-01T09:15:59Z Spectroscopic approach for dynamic bioanalyte tracking with minimal concentration information Spegazzini, Nicolas Barman, Ishan Dingari, Narahara Chari Pandey, Rishikesh Soares, Jaqueline S. Ozaki, Yukihiro Dasari, Ramachandra Rao Massachusetts Institute of Technology. Department of Chemistry Massachusetts Institute of Technology. Laser Biomedical Research Center Spegazzini, Nicolas Dingari, Narahara Chari Pandey, Rishikesh Dasari, Ramachandra Rao Vibrational spectroscopy has emerged as a promising tool for non-invasive, multiplexed measurement of blood constituents - an outstanding problem in biophotonics. Here, we propose a novel analytical framework that enables spectroscopy-based longitudinal tracking of chemical concentration without necessitating extensive a priori concentration information. The principal idea is to employ a concentration space transformation acquired from the spectral information, where these estimates are used together with the concentration profiles generated from the system kinetic model. Using blood glucose monitoring by Raman spectroscopy as an illustrative example, we demonstrate the efficacy of the proposed approach as compared to conventional calibration methods. Specifically, our approach exhibits a 35% reduction in error over partial least squares regression when applied to a dataset acquired from human subjects undergoing glucose tolerance tests. This method offers a new route at screening gestational diabetes and opens doors for continuous process monitoring without sample perturbation at intermediate time points. National Institute for Biomedical Imaging and Bioengineering (U.S.) (9P41EB015871-27) Kwansei Gakuin University (Grant 126004) 2014-12-31T21:31:47Z 2014-12-31T21:31:47Z 2014-11 2014-07 Article http://purl.org/eprint/type/JournalArticle 2045-2322 http://hdl.handle.net/1721.1/92575 Spegazzini, Nicolas, Ishan Barman, Narahara Chari Dingari, Rishikesh Pandey, Jaqueline S. Soares, Yukihiro Ozaki, and Ramachandra Rao Dasari. “Spectroscopic Approach for Dynamic Bioanalyte Tracking with Minimal Concentration Information.” Sci. Rep. 4 (November 12, 2014): 7013. https://orcid.org/0000-0003-4975-3815 https://orcid.org/0000-0003-1190-3144 en_US http://dx.doi.org/10.1038/srep07013 Scientific Reports Creative Commons Attribution http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf Nature Publishing Group Nature Publishing Group |
| spellingShingle | Spegazzini, Nicolas Barman, Ishan Dingari, Narahara Chari Pandey, Rishikesh Soares, Jaqueline S. Ozaki, Yukihiro Dasari, Ramachandra Rao Spectroscopic approach for dynamic bioanalyte tracking with minimal concentration information |
| title | Spectroscopic approach for dynamic bioanalyte tracking with minimal concentration information |
| title_full | Spectroscopic approach for dynamic bioanalyte tracking with minimal concentration information |
| title_fullStr | Spectroscopic approach for dynamic bioanalyte tracking with minimal concentration information |
| title_full_unstemmed | Spectroscopic approach for dynamic bioanalyte tracking with minimal concentration information |
| title_short | Spectroscopic approach for dynamic bioanalyte tracking with minimal concentration information |
| title_sort | spectroscopic approach for dynamic bioanalyte tracking with minimal concentration information |
| url | http://hdl.handle.net/1721.1/92575 https://orcid.org/0000-0003-4975-3815 https://orcid.org/0000-0003-1190-3144 |
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