A multiscale active structural model of the arterial wall accounting for smooth muscle dynamics

Abstract

Arterial wall dynamics arise from the synergy of passive mechano-elastic properties of the vascular tissue and the active contractile behaviour of smooth muscle cells (SMCs) that form the media layer of vessels. We have developed a computational framework that incorporates both these components to account for vascular responses to mechanical and pharmacological stimuli. To validate the proposed framework and demonstrate its potential for testing hypotheses on the pathogenesis of vascular disease, we have employed a number of pharmacological probes that modulate the arterial wall contractile machinery by selectively inhibiting a range of intracellular signalling pathways. Experimental probes used on ring segments from the rabbit central ear artery are: phenylephrine, a selective α1-adrenergic receptor agonist that induces vasoconstriction; cyclopiazonic acid (CPA), a specific inhibitor of sarcoplasmic/endoplasmic reticulum Ca2+-ATPase; and ryanodine, a diterpenoid that modulates Ca2+ release from the sarcoplasmic reticulum. These interventions were able to delineate the role of membrane versus intracellular signalling, previously identified as main factors in smooth muscle contraction and the generation of vessel tone. Each SMC was modelled by a system of nonlinear differential equations that account for intracellular ionic signalling, and in particular Ca2+ dynamics. Cytosolic Ca2+ concentrations formed the catalytic input to a cross-bridge kinetics model. Contractile output from these cellular components forms the input to the finite-element model of the arterial rings under isometric conditions that reproduces the experimental conditions. The model does not account for the role of the endothelium, as the nitric oxide production was suppressed by the action of L-NAME, and also due to the absence of shear stress on the arterial ring, as the experimental set-up did not involve flow. Simulations generated by the integrated model closely matched experimental observations qualitatively, as well as quantitatively within a range of physiological parametric values. The model also illustrated how increased intercellular coupling led to smooth muscle coordination and the genesis of vascular tone.

Advanced Constitutive Modeling of the Thixotropic Elasto-Visco-Plastic Behavior of Blood: Steady-State Blood Flow in Microtubes

“…A proper calculation of WSS has an exceptional role, especially when blood flows in vivo because it is the stress applied on the internal Endothelial Cells (EC) surface. Vascular operations such as biochemical reactions are considerably affected by the WSS as it has been proved to be directly associated with Nitric Oxide (NO) production [ 43 ] and calcium activation in Smooth Muscle Cells (SMC) [ 90 ] by triggering the biochemical reactions that take place in vascular beds, leading to the regulation of vascular tone [ 91 ]. Although in one-dimensional blood flows, the prediction of WSS is not complex, we offer a consistent model for a proper prediction of WSS in more complicated flows.…”

On the Ca2+elevation in vascular endothelial cells due to inositol trisphosphate-sensitive store receptor activation: a data-driven modeling approach

“…This work lays the foundation for future experimental and modelling studies targeting the analysis and quantification of Ca 2+ dynamics in ECs and its effects on blood vessel contractility and permeability. The proposed model could indeed be combined with other models representing SMCs’ activity [59, 60] for quantifying the interaction between functionally different vascular cells, the resulting wall stress level and lumen deformation. These theoretical findings may also contribute to the development of new models for studying the blood-brain barrier function [61].…”

Spatiotemporal Characterizations of Spontaneously Beating Cardiomyocytes with Adaptive Reference Digital Image Correlation

“…These characterizations will enable better models to be constructed with sampling of parameters from the developing tissue whenever necessary. This is especially necessary for cardiovascular tissues which are inhomogeneous and may require sampling at multiple scale levels to achieve a sufficiently detailed model 21 . This will better inform developmental models and enable testing of hypotheses at distinct developmental tissue stages.…”