Arteries grow and remodel following mechanical perturbation. Vascular smooth muscle cells (VSMCs) within the artery undergo hyperplasia, hypertrophy, or change their contractility following sustained changes in loading. Experimental evidence in vivo and in vitro suggests that VSMCs grow and remodel to maintain a constant transmural stress, or "target" stress. This behavior is often described using a stress-dependent finite growth framework. Typically, computational models of arterial growth and remodeling account for VSMC behavior in a constrained mixture formulation that incorporates behavior of each component of the artery. However, these models do not account for differential VSMC architecture observed in situ, which may significantly influence growth and remodeling behavior. Here, we used cellular microbiaxial stretching (CμBS) to characterize how VSMCs with different cytoskeletal architectures respond to a sustained step change in strain. We find that VSMC F-actin architecture becomes more aligned following stretch and retains this alignment after 24 h. Further, we find that VSMC stress magnitude depends on cellular architecture. Qualitatively, however, stress behavior following stretch is consistent across cell architectures - stress increases following stretch and returns to prestretch magnitudes after 24 h. Finally, we formulated an architecture-dependent targeted growth law that accounts for experimentally measured cytoskeletal alignment and attributes stress evolution to individual fiber growth and find that this model robustly captures long-term stress evolution in single VSMCs. These results suggest that VSMC mechano-adaptation depends on cellular architecture, which has implications for growth and remodeling in regions of arteries with differential architecture, such as at bifurcations.
Bibliographical noteFunding Information:
We acknowledge support from the U.S. National Science Foundation (NSF): CMMI-156319 (P.W.A.) and the University of Minnesota College of Science and Engineering Fellowship (B.L.C). Portions of this work were conducted in the Minnesota Nano-Center, which is supported by the National Science Foundation through the National Nano-Coordinated Infrastructure Network (NNCI) under Award Number ECCS-2025124.
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