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DNP Data Analysis and Mathematical Modeling

Posted Mon, Feb, 25,2013

Published today in Magnetic Resonance Insights is a new review by Guilhem Pagès and Philip W. Kuchel.  Read more about this paper below:

Title

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

Abstract

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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