| Literature DB >> 33394220 |
Spencer Frank1,2, Abdulrahman Jbaily3,4, Ling Hinshaw5, Rita Basu6, Ananda Basu6, Andrew J Szeri3,7.
Abstract
To shed light on how acute exercise affects blood glucose (BG) concentrations in nondiabetic subjects, we develop a physiological pharmacokinetic/pharmacodynamic model of postprandial glucose dynamics during exercise. We unify several concepts of exercise physiology to derive a multiscale model that includes three important effects of exercise on glucose dynamics: increased endogenous glucose production (EGP), increased glucose uptake in skeletal muscle (SM), and increased glucose delivery to SM by capillary recruitment (i.e. an increase in surface area and blood flow in capillary beds). We compare simulations to experimental observations taken in two cohorts of healthy nondiabetic subjects (resting subjects (n = 12) and exercising subjects (n = 12)) who were each given a mixed-meal tolerance test. Metabolic tracers were used to quantify the glucose flux. Simulations reasonably agree with postprandial measurements of BG concentration and EGP during exercise. Exercise-induced capillary recruitment is predicted to increase glucose transport to SM by 100%, causing hypoglycemia. When recruitment is blunted, as in those with capillary dysfunction, the opposite occurs and higher than expected BG levels are predicted. Model simulations show how three important exercise-induced phenomena interact, impacting BG concentrations. This model describes nondiabetic subjects, but it is a first step to a model that describes glucose dynamics during exercise in those with type 1 diabetes (T1D). Clinicians and engineers can use the insights gained from the model simulations to better understand the connection between exercise and glucose dynamics and ultimately help patients with T1D make more informed insulin dosing decisions around exercise.Entities:
Keywords: Artificial pancreas; Capillary recruitment; Endogenous glucose production; Exercise; Glucose dynamics; Kinetics; Metabolic tracers; Modeling; Type 1 diabetes
Mesh:
Substances:
Year: 2021 PMID: 33394220 PMCID: PMC8281614 DOI: 10.1007/s10928-020-09726-9
Source DB: PubMed Journal: J Pharmacokinet Pharmacodyn ISSN: 1567-567X Impact factor: 2.745