3 resultados para FLOW MATHEMATICAL-MODEL

em DigitalCommons@The Texas Medical Center


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In order to evaluate factors regulating substrate metabolism in vivo positron emitting radionuclides were used for the assessment of skeletal muscle blood flow and glucose utilization. The potassium analog, Rb-82 was used to measure skeletal muscle blood flow and the glucose analog, 18-F-2-deoxy-2-fluoro-D-glucose (FDG) was used to examine the kinetics of skeletal muscle transport and phosphorylation.^ New Zealand white rabbits' blood flow ranged from 1.0-70 ml/min/100g with the lowest flows occurring under baseline conditions and the highest flows were measured immediately after exercise. Elevated plasma glucose had no effect on increasing blood flow, whereas high physiologic to pharmacologic levels of insulin doubled flow as measured by the radiolabeled microspheres, but a proportionate increase was not detected by Rb-82. The data suggest that skeletal muscle blood flow can be measured using the positron emitting K+ analog Rb-82 under low flow and high flow conditions but not when insulin levels in the plasma are elevated. This may be due to the fact that insulin induces an increase in the Na+/K+-ATPase activity of the cell indirectly through a direct increase in the Na+/H+pump activity. This suggests that the increased cation pump activity counteracts the normal decrease in extraction seen at higher flows resulting in an underestimation of flow as measured by rubidium-82.^ Glucose uptake as measured by FDG employed a three compartment mathematical model describing the rates of transport, countertransport and phosphorylation of hexose. The absolute values for the metabolic rate of FDG were found to be an order of magnitude higher than those reported by other investigators. Changes noted in the rate constant for transport (k1) were found to disagree with the a priori information on the effects of insulin on skeletal muscle hexose transport. Glucose metabolism was however, found to increase above control levels with administration of insulin and electrical stimulation. The data indicate that valid measurements of skeletal muscle glucose transport and phosphorylation using the positron emitting glucose analog FDG requires further model application and biochemical validation. (Abstract shortened with permission of author.) ^

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The induction of late long-term potentiation (L-LTP) involves complex interactions among second-messenger cascades. To gain insights into these interactions, a mathematical model was developed for L-LTP induction in the CA1 region of the hippocampus. The differential equation-based model represents actions of protein kinase A (PKA), MAP kinase (MAPK), and CaM kinase II (CAMKII) in the vicinity of the synapse, and activation of transcription by CaM kinase IV (CAMKIV) and MAPK. L-LTP is represented by increases in a synaptic weight. Simulations suggest that steep, supralinear stimulus-response relationships between stimuli (e.g., elevations in [Ca(2+)]) and kinase activation are essential for translating brief stimuli into long-lasting gene activation and synaptic weight increases. Convergence of multiple kinase activities to induce L-LTP helps to generate a threshold whereby the amount of L-LTP varies steeply with the number of brief (tetanic) electrical stimuli. The model simulates tetanic, -burst, pairing-induced, and chemical L-LTP, as well as L-LTP due to synaptic tagging. The model also simulates inhibition of L-LTP by inhibition of MAPK, CAMKII, PKA, or CAMKIV. The model predicts results of experiments to delineate mechanisms underlying L-LTP induction and expression. For example, the cAMP antagonist RpcAMPs, which inhibits L-LTP induction, is predicted to inhibit ERK activation. The model also appears useful to clarify similarities and differences between hippocampal L-LTP and long-term synaptic strengthening in other systems.

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Late long-term potentiation (L-LTP) denotes long-lasting strengthening of synapses between neurons. L-LTP appears essential for the formation of long-term memory, with memories at least partly encoded by patterns of strengthened synapses. How memories are preserved for months or years, despite molecular turnover, is not well understood. Ongoing recurrent neuronal activity, during memory recall or during sleep, has been hypothesized to preferentially potentiate strong synapses, preserving memories. This hypothesis has not been evaluated in the context of a mathematical model representing ongoing activity and biochemical pathways important for L-LTP. In this study, ongoing activity was incorporated into two such models - a reduced model that represents some of the essential biochemical processes, and a more detailed published model. The reduced model represents synaptic tagging and gene induction simply and intuitively, and the detailed model adds activation of essential kinases by Ca(2+). Ongoing activity was modeled as continual brief elevations of Ca(2+). In each model, two stable states of synaptic strength/weight resulted. Positive feedback between synaptic weight and the amplitude of ongoing Ca(2+) transients underlies this bistability. A tetanic or theta-burst stimulus switches a model synapse from a low basal weight to a high weight that is stabilized by ongoing activity. Bistability was robust to parameter variations in both models. Simulations illustrated that prolonged periods of decreased activity reset synaptic strengths to low values, suggesting a plausible forgetting mechanism. However, episodic activity with shorter inactive intervals maintained strong synapses. Both models support experimental predictions. Tests of these predictions are expected to further understanding of how neuronal activity is coupled to maintenance of synaptic strength. Further investigations that examine the dynamics of activity and synaptic maintenance can be expected to help in understanding how memories are preserved for up to a lifetime in animals including humans.