A supply of glucose to a nervous tissue is fulfilled by a cerebrovascular network, and further diffusion is known to occur at both an arteriolar and a microvascular level. Despite a direct relation, a blood flow dynamic and reaction-diffusion of metabolites are usually considered separately in the mathematical models. In the present study they are coupled in a multiphysical approach which allows to evaluate the effects of capillary blood flow changes on near-vessels nutrient concentration gradients evidently. Cerebral blood flow (CBF) was described by the non-steady-state Navier-Stokes equations for a non-Newtonian fluid whose constitutive law is given by the Carreau model. A three-level organization of blood–brain barrier (BBB) is modelled by the flux dysconnectivity functions including densities and kinetic properties of glucose transporters. The velocity of a fluid flow in brain extracellular space (ECS) was estimated using Darcy’s law. The equations of reaction-diffusion with convection based on a generated flow field for continues and porous media were used to describe spatial-time gradients of glucose in the capillary lumen and brain parenchyma of a neurovascular unit (NVU), respectively. Changes in CBF were directly simulated using smoothing step-like functions altering the difference of intracapillary pressure in time. The changes of CBF cover both the decrease (on 70%) and the increase (on 50%) in a capillary flow velocity. Analyzing the dynamics of glucose gradients, it was shown that a rapid decrease of a capillary blood flow yields an enhanced level of glucose in a near-capillary nervous tissue if the contacts between astrocytes end-feet are not tight. Under the increased CBF velocities the amplitude of glucose concentration gradients is always enhanced. The introduced approach can be used for estimation of blood flow changes influence not only on glucose but also on other nutrients concentration gradients and for the modelling of distributions of their concentrations near blood vessels in other tissues as well.
Objective: Investigating the cardiovascular system is challenging due to its complex regulation by humoral and neuronal factors. Despite this complexity, many existing research methods are limited to the assessment of a few parameters leading to an incomplete characterization of cardiovascular function. Thus, we aim to establish a murine in vivo model for integrated assessment of the cardiovascular system under conditions of controlled heart rate. Utilizing this model, we assessed blood pressure, cardiac output, stroke volume, total peripheral resistance, and electrocardiogram (ECG).
Hypothesis: We hypothesize that (i) our in vivo model can be utilized to investigate cardiac and vascular responses to pharmacological intervention with the α1-agonist phenylephrine, and (ii) we can study cardiovascular function during artificial pacing of the heart, modulating cardiac function without a direct vascular effect.
Methods: We included 12 mice that were randomly assigned to either vehicle or phenylephrine intervention through intraperitoneal administration. Mice were anesthetized with isoflurane and intubated endotracheally for mechanical ventilation. We measured blood pressure via a solid-state catheter in the aortic arch, blood flow via a probe on the ascending aorta, and ECG from needle electrodes on the extremities. Right atrium was electrically paced at a frequency ranging from 10 to 11.3 Hz before and after either vehicle or phenylephrine administration.
Results: Phenylephrine significantly increased blood pressure, stroke volume, and total peripheral resistance compared to the vehicle group. Moreover, heart rate was significantly decreased following phenylephrine administration. Pacing significantly decreased stroke volume and cardiac output both prior to and after drug administration. However, phenylephrine-induced changes in blood pressure and total peripheral resistance were maintained with increasing pacing frequencies compared to the vehicle group. Total peripheral resistance was not significantly altered with increasing pacing frequencies suggesting that the effect of phenylephrine is primarily of vascular origin.
Conclusion: In conclusion, this in vivo murine model is capable of distinguishing between changes in peripheral vascular and cardiac functions. This study underlines the primary effect of phenylephrine on vascular function with secondary changes to cardiac function. Hence, this in vivo model is useful for the integrated assessment of the cardiovascular system.