Hypercomplex models of insulin and glucose dynamics: Do they predict experimental results?

A. M. Albisser, Y. Yamasaki, H. Broekhuyse, J. Tiran

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

A hypercomplex circulation and organs model of glucose and insulin dynamics is presented. The model is based on physiological parameters, incorporating blood and plasma flow rates, circulatory paths, intra- and extravascular glucose and insulin spaces, as well as the specific organs and tissues involved both with insulin disappearance and with glucose production or uptake. Its simulations readily lend themselves to physiological interpretation. To explore its validity, the model was assigned parameters typical of a 12 kg dog and was arranged to accept known glucose and insulin infusions from two different experiments on pancreatectomized diabetic animals. It predicted the observed glucose and insulin concentrations as well as uptake rates for both moieties in the individual organs and tissues. This confirmed the ability of the model to predict with consistency the group mean outcomes of both experiments when differing routes (portal or peripheral) of infusion were applied. Excellent agreement was achieved for the studies. The model isolates glucose uptake in the periphery, the liver, the brain, and the gut and allows a direct comparison of glucose disposal along various routes. Thus, the total amount of glucose uptake by peripheral, insulin-dependent tissues is directly calculated to be 30% of an intravenous glucose load, with peripheral infusion, which is higher than that with portal infusion (18%).

Original languageEnglish
Pages (from-to)539-557
Number of pages19
JournalAnnals of Biomedical Engineering
Volume8
Issue number4-6
DOIs
StatePublished - 1 Jul 1980

ASJC Scopus subject areas

  • Biomedical Engineering

Fingerprint

Dive into the research topics of 'Hypercomplex models of insulin and glucose dynamics: Do they predict experimental results?'. Together they form a unique fingerprint.

Cite this