Glucose effectiveness assessed under dynamic and steady state conditions. Comparability of uptake versus production components.

Glucose tolerance is determined by both insulin action and insulin-independent effects, or "glucose effectiveness," which includes glucose-mediated stimulation of glucose uptake (Rd) and suppression of hepatic glucose output (HGO). Despite its importance to tolerance, controversy surrounds accurate assessment of glucose effectiveness. Furthermore, the relative contributions of glucose's actions on Rd and HGO under steady state and dynamic conditions are unclear. We performed hyperglycemic clamps and intravenous glucose tolerance tests in eight normal dogs, and assessed glucose effectiveness by two independent methods. During clamps, glucose was raised to three successive 90-min hyperglycemic plateaus by variable labeled glucose infusion rate; glucose effectiveness (GE) was quantified as the slope of the dose-response relationship between steady state glucose and glucose infusion rate (GE[CLAMP(total)]), Rd (GE[CLAMP(uptake)]) or HGO (GE[CLAMP(HGO)]). During intravenous glucose tolerance tests, tritiated glucose (1.2 microCi/kg) was injected with cold glucose (0.3 g/kg); glucose and tracer dynamics were analyzed using a two-compartment model of glucose kinetics to obtain Rd and HGO components of glucose effectiveness. All experiments were performed during somatostatin inhibition of islet secretion, and basal insulin and glucagon replacement. During clamps, Rd rose from basal (2.54+/-0.20) to 3.95+/-0.54, 6.76+/-1.21, and 9.48+/-1.27 mg/min per kg during stepwise hyperglycemia; conversely, HGO declined to 2.06+/-0.17, 1.17+/-0.19, and 0.52+/-0.33 mg/min per kg. Clamp-based glucose effectiveness was 0.0451+/-0.0061, 0.0337+/-0.0060, and 0.0102+/-0.0009 dl/min per kg for GE[CLAMP(total)], GE[CLAMP(uptake)], and GE[CLAMP(HGO)], respectively. Glucose's action on Rd dominated overall glucose effectiveness (72.2+/-3.3% of total), a result virtually identical to that obtained during intravenous glucose tolerance tests (71.6+/-6.1% of total). Both methods yielded similar estimates of glucose effectiveness. These results provide strong support that glucose effectiveness can be reliably estimated, and that glucose-stimulated Rd is the dominant component during both steady state and dynamic conditions.

Reassessment of glucose effectiveness and insulin sensitivity from minimal model analysis: a theoretical evaluation of the single-compartment glucose distribution assumption.

Minimal model analysis with the frequently sampled intravenous glucose tolerance test provides an effective way to measure two important metabolic parameters in vivo under non-steady-state conditions: glucose effectiveness (SG) and insulin sensitivity (SI). Two questions regarding the validity of SG and SI have recently emerged. First, SG from the minimal model is suspected to be overestimated. Second, the occurrence of SI values indistinguishable from zero ("zero-SI") is not negligible in large clinical studies, and its physiological meaning is uncertain. In this study, we examined the significance of the assumed single-compartment glucose distribution embedded in the minimal model on the estimation of SG and SI. A more accurate two-compartment model was constructed by incorporating insulin action on hepatic glucose output and uptake into a previously validated construction. The two-compartment results were compared with the one-compartment minimal model results. It was shown that the one-compartment assumption contributes to a systematic deviation of SG (slope = 0.54, y-intercept = 0.014 min[-1]; n = 195 simulations). However, SG from the minimal model was linearly correlated to SG determined from the two-compartment model (r = 0.996). The one-compartment assumption also contributed to the occurrence of zero SI values for insulin-resistant subjects. A similar linear relationship was found between SI estimated by both the minimal model and the two-compartment model (slope = 0.58, y-intercept = -0.57 x 10[-4] min[-1] per pU/ml, r = 0.998). In conclusion, SG and SI from the minimal model are not necessarily equivalent to values emanating from the more accurate two-compartment model. However, the very high correlation between one- and two-compartment results suggests that the minimal model-derived SG and SI are dependable indexes of in vivo glucose effectiveness and insulin sensitivity. Minimal model analysis' advantages of simplicity, minimal invasiveness, reasonable reflection of non-steady-state glucose kinetics, and cost-effectiveness could in many cases outweigh the structural bias introduced by the model simplification.

Application of biochemical systems theory to metabolism in human red blood cells. Signal propagation and accuracy of representation.

Human erythrocytes are among the simplest of cells. Many of their enzymes have been characterized kinetically using steady-state methods in vitro, and several investigators have assembled this kinetic information into mathematical models of the integrated system. However, despite its relative simplicity, the integrated behavior of erythrocyte metabolism is still complex and not well understood. Errors will inevitably be encountered in any such model because of this complexity; thus, the construction of an integrative model must be considered an iterative process of assessment and refinement. In a previous study, we selected a recent model of erythrocyte metabolism as our starting point and took it through three stages of model assessment and refinement using systematic strategies provided by biochemical systems theory. At each stage deficiencies were diagnosed, putative remedies were identified, and modifications consistent with existing experimental evidence were incorporated into the working model. In this paper we address two issues: the propagation of biochemical signals within the metabolic network, and the accuracy of kinetic representation. The analysis of signal propagation reveals the importance of glutathione peroxidase, transaldolase, and the concentration of total glutathione in determining systemic behavior. It also reveals a highly amplified diversion of flux between the pathways of pentose phosphate and nucleotide metabolism. In determining the range of accurate representation based on alternative kinetic formalisms we discovered large discrepancies. These were identified with the behavior of the model represented within the Michaelis-Menten formalism. This model fails to exhibit a nominal steady state when the activity of glutathione peroxidase is decreased by as little as 9%. Our current understanding, as embodied in this working model, is in need of further refinement, and the results presented in this paper suggest areas of the model where such effort might profitably be concentrated.

Model assessment and refinement using strategies from biochemical systems theory: application to metabolism in human red blood cells.

Models of biochemical systems are typically formulated with kinetic data obtained from isolated enzymes studied in vitro, and one has always to question whether or not all the relevant metabolites, processes and regulatory interactions have been identified and whether the parameter values obtained in vitro reflect the actual intracellular environment. In this paper we extend and further test strategies for model assessment and refinement that take advantage of the power-law formalism, which provides the systematic structure underlying biochemical systems theory. Our purpose is three fold. First, we introduce an algorithm for systematically scanning a model for putative errors, which, if corrected, would reconcile its behavior with the experimental system. Second, we further test the working hypothesis that systems in nature are selected to be robust and, hence, that the profile of parameter sensitivities can be used to identify poorly defined regions of a model. Third, we illustrate the use of these strategies within the context of a relatively large and realistic biochemical system--the metabolic pathways of the human red blood cell. Our results show that the reference model we have used is neither locally stable nor robust. The algorithm identifies a number of putative regulatory interactions that, when added to the model, are capable of stabilizing the nominal steady state. We include one of these, the feedback inhibition of hexokinase by fructose-6-phosphate, in a first refinement of the model because there is experimental support for it in the literature. Careful re-examination of the most sensitive section in this model, the pathways of nucleotide metabolism, reveals two mechanisms that were omitted from the reference model: membrane transport of adenosine and inosine, and regulation of phosphoribosyl pyrophosphate synthetase by adenosine diphosphate, 2,3 diphosphoglycerate and 5-phosphoribosyl-1-pyrophosphate. It was also found that the concentration of inorganic phosphate had been inappropriately assumed to be a constant. Modifications to correct these deficiencies produced a second refinement of the model whose parameter sensitivities are reduced on average by 10-fold. Although these refinements are modest and there is substantial room for further improvement, this application identified several biochemically relevant features of the model that had been overlooked. It also points to nucleotide metabolism as the area most in need of further experimental study.