Measurements and System Identification for the Characterization of Smooth Muscle Cell Dynamics

TL;DR

Vascular disease progression involves complex smooth muscle cell (SMC) mechanobiology and myogenic regulation of vessel tone. The authors apply a broadband frequency-domain system identification approach using random-phase multisine excitation and nanoindentation to extract the Best Linear Approximation $G_{BLA}(q)$ of single iPSC-derived vascular SMC dynamics, with FRF estimation via Local Polynomial Method (LPM). They report that nonlinear distortions account for roughly $30\%$ of the response in healthy cells across the range $[f_{min}, f_{max}] = [0.06, 1]$ Hz, validating the measurement-and-identification workflow on human cells and enabling future disease-versus-naive comparisons. This framework provides a practical, human-cell-based platform for broadband mechanobiology of SMCs, potentially reducing reliance on animal studies and informing mechanistic insights into tissue integrity and vascular disease.

Abstract

Biological tissue integrity is actively maintained by cells. It is essential to comprehend how cells accomplish this in order to stage tissue diseases. However, addressing the complexity of a cell's system of interrelated mechanisms poses a challenge. This necessitates a well-structured identification framework and an effective integration of measurements. Here we introduce the use of state-of-the-art frequency-domain system identification techniques combined with an indentation measurement platform to analyze the underlying mechanisms from the perspective of control system theory. The ultimate goal is to explore how mechanical and biological factors are related in induced Pluripotent Stem Cell-derived vascular smooth muscle cells. We study on the frequency-domain analysis for the investigation and characterization of cellular dynamics of smooth muscle cells from the measured data. The measurement model in this study exploits the availability of human tissue and samples, enabling fundamental investigations of vascular tissue disease. This approach using human cell lines holds significant potential to decrease the necessity for animal-based safety and efficacy studies. The focus of this review is to investigate the cellular dynamics underlying the myogenic response and to demonstrate the practicability of employing a nano-indentation measurement setup for the broadband frequency-domain characterization of induced Pluripotent Stem Cell-derived vascular smooth muscle cells.

Figures (9)

• Figure 1: Nanoindentation on a cell, created with BioRender.
• Figure 2: Measurement set up. r(t): reference multisine signal, u(t): load and y(t): indentation
• Figure 3: a) One period of the reference multisine signal. b) DFT spectrum of the reference multisine signal.
• Figure 4: Measured input $u(t)$ and output $y(t)$ of a nonlinear system with the unmodeled nonlinear contributions $y_s(t)$ and the additive noise source $n_y(t)$.
• Figure 5: a) 3 measured periods of load data for one phase realization of the multisine reference signal. b) Load data DFT spectrum for each of the 3 periods.