超极化(13)C代谢物核磁共振实验的数学建模和数据分析。

Magnetic resonance insights Pub Date : 2013-02-24 eCollection Date: 2013-01-01 DOI:10.4137/MRI.S11084
Guilhem Pagès, Philip W Kuchel
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引用次数: 15

摘要

快速溶解动态核极化(DNP)对几种疾病在亚分钟时间尺度上发生的代谢的表征和理解产生了重大影响。虽然在开发应用和设计快速成像射频(RF)和磁场梯度脉冲序列方面已经做出了重大努力,但很少有小组致力于实现现实的数学/动力学/松弛模型来适应紧急数据。DNP实验建模时要考虑的关键方面取决于核磁共振(NMR)和(生物)化学动力学。前一种约束是由于核磁共振信号的松弛和“读”射频脉冲的应用,而动力学约束包括存在的每个分子物种的总量。我们描述了我们用来拟合和解释DNP结果的模型设计策略。据我们所知,这是第一份对DNP数据进行系统分析的报告。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Mathematical Modeling and Data Analysis of NMR Experiments using Hyperpolarized (13)C Metabolites.

Rapid-dissolution dynamic nuclear polarization (DNP) has made significant impact in the characterization and understanding of metabolism that occurs on the sub-minute timescale in several diseases. While significant efforts have been made in developing applications, and in designing rapid-imaging radiofrequency (RF) and magnetic field gradient pulse sequences, very few groups have worked on implementing realistic mathematical/kinetic/relaxation models to fit the emergent data. The critical aspects to consider when modeling DNP experiments depend on both nuclear magnetic resonance (NMR) and (bio)chemical kinetics. The former constraints are due to the relaxation of the NMR signal and the application of 'read' RF pulses, while the kinetic constraints include the total amount of each molecular species present. We describe the model-design strategy we have used to fit and interpret our DNP results. To our knowledge, this is the first report on a systematic analysis of DNP data.

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