Carlson B.E.,Biotechnology and Bioengineering Center |
Beard D.A.,Biotechnology and Bioengineering Center |
Beard D.A.,Medical College of Wisconsin
American Journal of Physiology - Heart and Circulatory Physiology | Year: 2011
Microcirculatory vessel response to changes in pressure, known as the myogenic response, is a key component of a tissue's ability to regulate blood flow. Experimental studies have not clearly elucidated the mechanical signal in the vessel wall governing steady-state reduction in vessel diameter upon an increase in intraluminal pressure. In this study, a multiscale computational model is constructed from established models of vessel wall mechanics, vascular smooth muscle (VSM) force generation, and VSM Ca2+ handling and electrophysiology to compare the plausibility of vessel wall stress or strain as an effective mechanical signal controlling steady-state vascular contraction in the myogenic response. It is shown that, at the scale of a resistance vessel, wall stress, and not stretch (strain), is the likely physiological signal controlling the steady-state myogenic response. The model is then used to test nine candidate VSM stress-controlled channel variants by fitting two separate sets of steady-state myogenic response data. The channel variants include nonselective cation (NSC), supplementary Ca2+ and Na+, L-type Ca2+, and large conductance Ca2+-activated K+ channels. The nine variants are tested in turn, and model fits suggest that stress control of Ca2+ or Na+ influx through NSC, supplementary Ca2+ or Na+, or L-type Ca2+ channels is sufficient to produce observed steady-state diameter changes with pressure. However, simulations of steady-state VSM membrane potential, cytosolic Ca2+, and Na+ with pressure show only that Na+ influx through NSC channel also generates known trends with increasing pressure, indicating that stress-controlled Na+ influx through NSC is sufficient to generate the myogenic response. © 2011 by the American Physiological Society.
Pannala V.R.,Biotechnology and Bioengineering Center |
Bazil J.N.,Biotechnology and Bioengineering Center |
Camara A.K.S.,Medical College of Wisconsin |
Dash R.K.,Biotechnology and Bioengineering Center
Free Radical Biology and Medicine | Year: 2013
Glutathione reductase (GR) catalyzes the reduction of oxidized glutathione (GSSG) to reduced glutathione (GSH) using NADPH as the reducing cofactor, and thereby maintains a constant GSH level in the system. GSH scavenges superoxide (O2 -) and hydroxyl radicals (OH) nonenzymatically or by serving as an electron donor to several enzymes involved in reactive oxygen species (ROS) detoxification. In either case, GSH oxidizes to GSSG and is subsequently regenerated by the catalytic action of GR. Although the GR kinetic mechanism has been extensively studied under various experimental conditions with variable substrates and products, the catalytic mechanism has not been studied in terms of a mechanistic model that accounts for the effects of the substrates and products on the reaction kinetics. The aim of this study is therefore to develop a comprehensive mathematical model for the catalytic mechanism of GR. We use available experimental data on GR kinetics from various species/sources to develop the mathematical model and estimate the associated model parameters. The model simulations are consistent with the experimental observation that GR operates via both ping-pong and sequential branching mechanisms based on relevant concentrations of its reaction substrate GSSG. Furthermore, we show the observed pH-dependent substrate inhibition of GR activity by GSSG and bimodal behavior of GR activity with pH. The model presents a unique opportunity to understand the effects of products on the kinetics of GR. The model simulations show that under physiological conditions, where both substrates and products are present, the flux distribution depends on the concentrations of both GSSG and NADP+, with ping-pong flux operating at low levels and sequential flux dominating at higher levels. The kinetic model of GR may serve as a key module for the development of integrated models for ROS-scavenging systems to understand protection of cells under normal and oxidative stress conditions. © 2013 Elsevier Inc. All rights reserved.