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Continuous Metabolic Monitoring Based on Multi-Analyte Biomarkers to Predict Exhaustion
This work introduces the concept of multi-analyte biomarkers for continuous metabolic monitoring. The importance of using more than one marker lies in the ability to obtain a holistic understanding of the metabolism. This is showcased for the detection and prediction of exhaustion during intense phy...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4450587/ https://www.ncbi.nlm.nih.gov/pubmed/26028477 http://dx.doi.org/10.1038/srep10603 |
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author | Kastellorizios, Michail Burgess, Diane J. |
author_facet | Kastellorizios, Michail Burgess, Diane J. |
author_sort | Kastellorizios, Michail |
collection | PubMed |
description | This work introduces the concept of multi-analyte biomarkers for continuous metabolic monitoring. The importance of using more than one marker lies in the ability to obtain a holistic understanding of the metabolism. This is showcased for the detection and prediction of exhaustion during intense physical exercise. The findings presented here indicate that when glucose and lactate changes over time are combined into multi-analyte biomarkers, their monitoring trends are more sensitive in the subcutaneous tissue, an implantation-friendly peripheral tissue, compared to the blood. This unexpected observation was confirmed in normal as well as type 1 diabetic rats. This study was designed to be of direct value to continuous monitoring biosensor research, where single analytes are typically monitored. These findings can be implemented in new multi-analyte continuous monitoring technologies for more accurate insulin dosing, as well as for exhaustion prediction studies based on objective data rather than the subject’s perception. |
format | Online Article Text |
id | pubmed-4450587 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-44505872015-06-10 Continuous Metabolic Monitoring Based on Multi-Analyte Biomarkers to Predict Exhaustion Kastellorizios, Michail Burgess, Diane J. Sci Rep Article This work introduces the concept of multi-analyte biomarkers for continuous metabolic monitoring. The importance of using more than one marker lies in the ability to obtain a holistic understanding of the metabolism. This is showcased for the detection and prediction of exhaustion during intense physical exercise. The findings presented here indicate that when glucose and lactate changes over time are combined into multi-analyte biomarkers, their monitoring trends are more sensitive in the subcutaneous tissue, an implantation-friendly peripheral tissue, compared to the blood. This unexpected observation was confirmed in normal as well as type 1 diabetic rats. This study was designed to be of direct value to continuous monitoring biosensor research, where single analytes are typically monitored. These findings can be implemented in new multi-analyte continuous monitoring technologies for more accurate insulin dosing, as well as for exhaustion prediction studies based on objective data rather than the subject’s perception. Nature Publishing Group 2015-06-01 /pmc/articles/PMC4450587/ /pubmed/26028477 http://dx.doi.org/10.1038/srep10603 Text en Copyright © 2015, Macmillan Publishers Limited 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 Kastellorizios, Michail Burgess, Diane J. Continuous Metabolic Monitoring Based on Multi-Analyte Biomarkers to Predict Exhaustion |
title | Continuous Metabolic Monitoring Based on Multi-Analyte Biomarkers to Predict Exhaustion |
title_full | Continuous Metabolic Monitoring Based on Multi-Analyte Biomarkers to Predict Exhaustion |
title_fullStr | Continuous Metabolic Monitoring Based on Multi-Analyte Biomarkers to Predict Exhaustion |
title_full_unstemmed | Continuous Metabolic Monitoring Based on Multi-Analyte Biomarkers to Predict Exhaustion |
title_short | Continuous Metabolic Monitoring Based on Multi-Analyte Biomarkers to Predict Exhaustion |
title_sort | continuous metabolic monitoring based on multi-analyte biomarkers to predict exhaustion |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4450587/ https://www.ncbi.nlm.nih.gov/pubmed/26028477 http://dx.doi.org/10.1038/srep10603 |
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