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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 ra...

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Detalles Bibliográficos
Autores principales: Pagès, Guilhem, Kuchel, Philip W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Libertas Academica 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4089703/
https://www.ncbi.nlm.nih.gov/pubmed/25114541
http://dx.doi.org/10.4137/MRI.S11084
Descripción
Sumario: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.