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Optimal Reaction Coordinate as a Biomarker for the Dynamics of Recovery from Kidney Transplant
The evolution of disease or the progress of recovery of a patient is a complex process, which depends on many factors. A quantitative description of this process in real-time by a single, clinically measurable parameter (biomarker) would be helpful for early, informed and targeted treatment. Organ t...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4072519/ https://www.ncbi.nlm.nih.gov/pubmed/24967678 http://dx.doi.org/10.1371/journal.pcbi.1003685 |
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author | Krivov, Sergei V. Fenton, Hayley Goldsmith, Paul J. Prasad, Rajendra K. Fisher, Julie Paci, Emanuele |
author_facet | Krivov, Sergei V. Fenton, Hayley Goldsmith, Paul J. Prasad, Rajendra K. Fisher, Julie Paci, Emanuele |
author_sort | Krivov, Sergei V. |
collection | PubMed |
description | The evolution of disease or the progress of recovery of a patient is a complex process, which depends on many factors. A quantitative description of this process in real-time by a single, clinically measurable parameter (biomarker) would be helpful for early, informed and targeted treatment. Organ transplantation is an eminent case in which the evolution of the post-operative clinical condition is highly dependent on the individual case. The quality of management and monitoring of patients after kidney transplant often determines the long-term outcome of the graft. Using NMR spectra of blood samples, taken at different time points from just before to a week after surgery, we have shown that a biomarker can be found that quantitatively monitors the evolution of a clinical condition. We demonstrate that this is possible if the dynamics of the process is considered explicitly: the biomarker is defined and determined as an optimal reaction coordinate that provides a quantitatively accurate description of the stochastic recovery dynamics. The method, originally developed for the analysis of protein folding dynamics, is rigorous, robust and general, i.e., it can be applied in principle to analyze any type of biological dynamics. Such predictive biomarkers will promote improvement of long-term graft survival after renal transplantation, and have potentially unlimited applications as diagnostic tools. |
format | Online Article Text |
id | pubmed-4072519 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-40725192014-07-02 Optimal Reaction Coordinate as a Biomarker for the Dynamics of Recovery from Kidney Transplant Krivov, Sergei V. Fenton, Hayley Goldsmith, Paul J. Prasad, Rajendra K. Fisher, Julie Paci, Emanuele PLoS Comput Biol Research Article The evolution of disease or the progress of recovery of a patient is a complex process, which depends on many factors. A quantitative description of this process in real-time by a single, clinically measurable parameter (biomarker) would be helpful for early, informed and targeted treatment. Organ transplantation is an eminent case in which the evolution of the post-operative clinical condition is highly dependent on the individual case. The quality of management and monitoring of patients after kidney transplant often determines the long-term outcome of the graft. Using NMR spectra of blood samples, taken at different time points from just before to a week after surgery, we have shown that a biomarker can be found that quantitatively monitors the evolution of a clinical condition. We demonstrate that this is possible if the dynamics of the process is considered explicitly: the biomarker is defined and determined as an optimal reaction coordinate that provides a quantitatively accurate description of the stochastic recovery dynamics. The method, originally developed for the analysis of protein folding dynamics, is rigorous, robust and general, i.e., it can be applied in principle to analyze any type of biological dynamics. Such predictive biomarkers will promote improvement of long-term graft survival after renal transplantation, and have potentially unlimited applications as diagnostic tools. Public Library of Science 2014-06-26 /pmc/articles/PMC4072519/ /pubmed/24967678 http://dx.doi.org/10.1371/journal.pcbi.1003685 Text en © 2014 Krivov et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Krivov, Sergei V. Fenton, Hayley Goldsmith, Paul J. Prasad, Rajendra K. Fisher, Julie Paci, Emanuele Optimal Reaction Coordinate as a Biomarker for the Dynamics of Recovery from Kidney Transplant |
title | Optimal Reaction Coordinate as a Biomarker for the Dynamics of Recovery from Kidney Transplant |
title_full | Optimal Reaction Coordinate as a Biomarker for the Dynamics of Recovery from Kidney Transplant |
title_fullStr | Optimal Reaction Coordinate as a Biomarker for the Dynamics of Recovery from Kidney Transplant |
title_full_unstemmed | Optimal Reaction Coordinate as a Biomarker for the Dynamics of Recovery from Kidney Transplant |
title_short | Optimal Reaction Coordinate as a Biomarker for the Dynamics of Recovery from Kidney Transplant |
title_sort | optimal reaction coordinate as a biomarker for the dynamics of recovery from kidney transplant |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4072519/ https://www.ncbi.nlm.nih.gov/pubmed/24967678 http://dx.doi.org/10.1371/journal.pcbi.1003685 |
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