Journal of theoretical biology
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Brain hypothermia treatment is used as a neuroprotectant to decompress the elevated intracranial pressure (ICP) in acute neuropatients. However, a quantitative relationship between decompression and brain hypothermia is still unclear, this makes medical treatment difficult and ineffective. The objective of this paper is to develop a general mathematical model integrating hemodynamics and biothermal dynamics to enable a quantitative prediction of transient responses of elevated ICP to ambient cooling temperature. ⋯ Gain of about 4.9 mmHg degrees C(-1), dead time of about 1.0 h and a time constant of about 9.8h are estimated for the hypothermic decompression. Based on the estimated characteristics, a feedback control of elevated ICP is introduced in a simulated intracranial hypertension of vasogenic brain edema. Simulation results suggest the possibility of an automatic control of the elevated ICP in brain hypothermia treatment.
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Following fractures, bones restore their original structural integrity through a complex process in which several cellular events are involved. Among other factors, this process is highly influenced by the mechanical environment of the fracture site. In this study, we present a mathematical model to simulate the effect of mechanical stimuli on most of the cellular processes that occur during fracture healing, namely proliferation, migration and differentiation. ⋯ The three processes were implemented in a Finite Element code as a combination of three coupled analysis stages: a biphasic, a diffusion and a thermoelastic step. We tested the mechano-biological regulatory model thus created by simulating the healing patterns of fractures with different gap sizes and different mechanical stimuli. The callus geometry, tissue differentiation patterns and fracture stiffness predicted by the model were similar to experimental observations for every analysed situation.
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Although the conditions under which altruistic behaviors evolve continue to be vigorously debated, there is general agreement that altruistic traits involving an absolute cost to altruists (strong altruism) cannot evolve when populations are structured with randomly formed groups. This conclusion implies that the evolution of such traits depends upon special environmental conditions or additional organismic capabilities that enable altruists to interact with each other more than would be expected with random grouping. Here we show, using both analytic and simulation results, that the positive assortment necessary for strong altruism to evolve does not require these additional mechanisms, but merely that randomly formed groups exist for more than one generation. ⋯ Until now random group formation models have neglected the significance of multigenerational groups-even though such groups are a central feature of classic "haystack" models of the evolution of altruism. We also explore the important role that stochasticity (effectively absent in the original infinite models) plays in the evolution of altruism. The fact that strong altruism can increase when groups are periodically and randomly formed suggests that altruism may evolve more readily and in simpler organisms than is generally appreciated.
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A compartmental model is developed for oxygen (O(2)) transport in brain microcirculation in the presence of blood substitutes (hemoglobin-based oxygen carriers). The cerebrovascular bed is represented as a series of vascular compartments, on the basis of diameters, surrounded by a tissue compartment. A mixture of red blood cells (RBC) and plasma/extracellular hemoglobin solution flows through the vascular bed from the arterioles through the capillaries to the venules. ⋯ O(2) affinity of the extracellular hemoglobin is increased, the flow rate of the mixture decreases, hematocrit decreases at constant flow, metabolic rate increases, and intravascular transport resistance in the arterioles is neglected; (b) precapillary PO(2) gradients are not sensitive to (i) intracapillary transport resistance, (ii) cooperativity (n(p)) of hemoglobin with oxygen in plasma, (iii) hemoglobin concentration in the plasma and (iv) hematocrit when accounting for viscosity variation in the flow; (c) tissue PO(2) is not sensitive to the variation of intravascular transport resistance in the arterioles. We also found that tissue PO(2) is a non-monotonic function of the Hill coefficient n(p) for the extracellular hemoglobin with a maximum occurring when n(p) equals the blood Hill coefficient. The results of the computations give estimates of the magnitudes of the increases in tissue PO(2) as arterial PO(2) increases,P(50 p) increases, flow rate increases, hematocrit increases, hemoglobin concentration in the plasma increases, metabolic rate decreases, the capillary mass transfer coefficient increases or the intracapillary transport resistance decreases.
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We consider a model for a network of phosphorylation-dephosphorylation cycles coupled through forward and backward regulatory interactions, such that a protein phosphorylated in a given cycle activates the phosphorylation of a protein by a kinase in the next cycle as well as the dephosphorylation of a protein by a phosphatase in a preceding cycle. The network is cyclically organized in such a way that the protein phosphorylated in the last cycle activates the kinase in the first cycle. We study the dynamics of the network in the presence of both forward and backward coupling, in conditions where a threshold exists in each cycle in the amount of protein phosphorylated as a function of the ratio of kinase to phosphatase maximum rates. ⋯ The progression of the system on the limit cycle can thus be temporarily halted as long as an inhibitor is present, much as when a domino is held in place. These results suggest that the eukaryotic cell cycle, governed by a network of phosphorylation-dephosphorylation reactions in which the negative control of cyclin-dependent kinases plays a prominent role, behaves as a limit-cycle oscillator impeded in the presence of inhibitors. We contrast the case where the sequence of domino-like transitions constitutes the clock with the case where the sequence of transitions is passively coupled to a biochemical oscillator operating as an independent clock.