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Afshar N, Safaei S, Nickerson DP, et al. Computational Modeling of Glucose Uptake in the Enterocyte. Front Physiol. 2019;10:380doi: 10.3389/fphys.2019.00380.
Afshar, N., Safaei, S., Nickerson, D. P., Hunter, P. J., & Suresh, V. (2019). Computational Modeling of Glucose Uptake in the Enterocyte. Frontiers in physiology, 10380. https://doi.org/10.3389/fphys.2019.00380
Afshar, Nima, et al. "Computational Modeling of Glucose Uptake in the Enterocyte." Frontiers in physiology vol. 10 (2019): 380. doi: https://doi.org/10.3389/fphys.2019.00380
Afshar N, Safaei S, Nickerson DP, Hunter PJ, Suresh V. Computational Modeling of Glucose Uptake in the Enterocyte. Front Physiol. 2019 Apr 12;10:380. doi: 10.3389/fphys.2019.00380. eCollection 2019. PMID: 31031632; PMCID: PMC6473069.
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Front Physiol. 2019 Apr 12;10:380. doi: 10.3389/fphys.2019.00380. eCollection 2019.

Computational Modeling of Glucose Uptake in the Enterocyte.

Frontiers in physiology

Nima Afshar, Soroush Safaei, David P Nickerson, Peter J Hunter, Vinod Suresh

Affiliations

  1. Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand.
  2. Department of Engineering Science, University of Auckland, Auckland, New Zealand.

PMID: 31031632 PMCID: PMC6473069 DOI: 10.3389/fphys.2019.00380

Abstract

Absorption of glucose across the epithelial cells of the small intestine is a key process in human nutrition and initiates signaling cascades that regulate metabolic homeostasis. Validated and predictive mathematical models of glucose transport in intestinal epithelial cells are essential for interpreting experimental data, generating hypotheses, and understanding the contributions of and interactions between transport pathways. Here we report on the development of such a model that, in contrast to existing models, incorporates mechanistic descriptions of all relevant transport proteins and is implemented in the CellML framework. The model is validated against experimental and simulation data from the literature. It is then used to elucidate the relative contributions of the sodium-glucose cotransporter (SGLT1) and the glucose transporter type 2 (GLUT2) proteins in published measurements of glucose absorption from human intestinal epithelial cell lines. The model predicts that the contribution of SGLT1 dominates at low extracellular glucose concentrations (<20 mM) and short exposure times (<60 s) while the GLUT2 contribution is more significant at high glucose concentrations and long durations. Implementation in CellML permitted a modular structure in which the model was composed by reusing existing models of the individual transporters. The final structure also permits transparent changes of the model components and parameter values in order to facilitate model reuse, extension, and customization (for example, to simplify, or add complexity to specific transporter/pathway models, or reuse the model as a component of a larger framework) and carry out parameter sensitivity studies.

Keywords: CellML; GLUT2; OpenCOR; SGLT1; computational modeling; glucose uptake

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