Metabolic Modeling of Dynamic (13)C NMR Isotopomer Data in the Brain In Vivo: Fast Screening of Metabolic Models Using Automated Generation of Differential Equations.
Neurochem Res
; 40(12): 2482-92, 2015 Dec.
Article
em En
| MEDLINE
| ID: mdl-26553273
ABSTRACT
Most current brain metabolic models are not capable of taking into account the dynamic isotopomer information available from fine structure multiplets in (13)C spectra, due to the difficulty of implementing such models. Here we present a new approach that allows automatic implementation of multi-compartment metabolic models capable of fitting any number of (13)C isotopomer curves in the brain. The new automated approach also makes it possible to quickly modify and test new models to best describe the experimental data. We demonstrate the power of the new approach by testing the effect of adding separate pyruvate pools in astrocytes and neurons, and adding a vesicular neuronal glutamate pool. Including both changes reduced the global fit residual by half and pointed to dilution of label prior to entry into the astrocytic TCA cycle as the main source of glutamine dilution. The glutamate-glutamine cycle rate was particularly sensitive to changes in the model.
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Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Química Encefálica
/
Espectroscopia de Ressonância Magnética
Tipo de estudo:
Diagnostic_studies
/
Screening_studies
Limite:
Animals
/
Humans
Idioma:
En
Revista:
Neurochem Res
Ano de publicação:
2015
Tipo de documento:
Article