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最优反应坐标作为肾移植后恢复动力学的生物标志物。

Optimal reaction coordinate as a biomarker for the dynamics of recovery from kidney transplant.

机构信息

School of Molecular and Cellular Biology, University of Leeds, Leeds, United Kingdom; Astbury Centre for Structural Molecular Biology, University of Leeds, Leeds, United Kingdom.

School of Chemistry, University of Leeds, Leeds, United Kingdom.

出版信息

PLoS Comput Biol. 2014 Jun 26;10(6):e1003685. doi: 10.1371/journal.pcbi.1003685. eCollection 2014 Jun.

DOI:10.1371/journal.pcbi.1003685
PMID:24967678
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4072519/
Abstract

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.

摘要

疾病的演变或患者康复的进展是一个复杂的过程,取决于许多因素。通过单个临床可测量的参数(生物标志物)实时对该过程进行定量描述将有助于早期、知情和有针对性的治疗。器官移植就是一个突出的例子,术后临床状况的演变高度依赖于个体情况。对肾移植患者的管理和监测质量往往决定了移植物的长期预后。我们使用手术前后不同时间点采集的血液样本的 NMR 谱,表明可以找到一种生物标志物来定量监测临床状况的演变。我们证明,如果明确考虑到该过程的动力学,则可以实现这一点:生物标志物被定义并确定为最佳反应坐标,为随机恢复动力学提供定量准确的描述。该方法最初是为分析蛋白质折叠动力学而开发的,具有严格、稳健和通用的特点,即原则上可以应用于分析任何类型的生物学动力学。这种预测性生物标志物将促进肾移植后长期移植物存活的改善,并具有作为诊断工具的潜在无限应用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/428e/4072519/ddc6b9f4ce6a/pcbi.1003685.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/428e/4072519/d8e8371d0da9/pcbi.1003685.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/428e/4072519/321db8c1adf3/pcbi.1003685.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/428e/4072519/a131e161a467/pcbi.1003685.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/428e/4072519/ddc6b9f4ce6a/pcbi.1003685.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/428e/4072519/d8e8371d0da9/pcbi.1003685.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/428e/4072519/321db8c1adf3/pcbi.1003685.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/428e/4072519/a131e161a467/pcbi.1003685.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/428e/4072519/ddc6b9f4ce6a/pcbi.1003685.g004.jpg

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