ORCID Identifier(s)

0009-0005-6748-231X

Graduation Semester and Year

Summer 2024

Language

English

Document Type

Dissertation

Degree Name

Doctor of Philosophy in Mathematics

Department

Mathematics

First Advisor

Jianzhong Su

Second Advisor

Hristo V. Kojouharov

Third Advisor

Ren-Cang Li

Fourth Advisor

Pedro D. Maia

Abstract

Models of glucose metabolism in the brain often focus on chemical exchanges and reactions that occur as part of the tricarboxylic acid cycle (TCA cycle). Experiments involving nuclear magnetic resonance (NMR) spectroscopy to detect and measure carbon-labeled isotopomers of metabolites such as glutamate in vivo inform kinetic, mechanistic models used to study metabolic pathways. In the present work, a new model with two compartments, astrocytic and neuronal, is developed using known biochemical processes and fit to experimental data coming from fully labeled glucose infusions. A gradient descent method is introduced and employed to obtain optimal flux parameter values involved in the TCA cycle.

Keywords

Metabolic parametrization, Brain metabolism, Glucose metabolism model

Disciplines

Ordinary Differential Equations and Applied Dynamics

Comments

Acknowledgements:

  • Jianzhong Su, PhD, Department of Mathematics, UT Arlington
  • Hristo V. Kojouharov, PhD, Department of Mathematics, UT Arlington
  • Ren-Cang Li, PhD, Department of Mathematics, UT Arlington
  • Pedro D. Maia, PhD, Department of Mathematics, UT Arlington
  • Craig R. Malloy, MD, Advanced Imaging Research Center, UT Southwestern Medical Center
  • Juan M. Pascual, MD, PhD, Brain and Mind Research Institute, Weill Cornell Medical College

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