Numerical and Experimental Analysis of Shear Stress Influence on Cellular Viability in Serpentine Vascular Channels

Abstract

3D bioprinting has emerged as a tool for developing in vitro tissue models for studying disease progression and drug development. The objective of the current study was to evaluate the influence of flow driven shear stress on the viability of cultured cells inside the luminal wall of a serpentine network. Fluid–structure interaction was modeled using COMSOL Multiphysics for representing the elasticity of the serpentine wall. Experimental analysis of the serpentine model was performed on the basis of a desirable inlet flow boundary condition for which the most homogeneously distributed wall shear stress had been obtained from numerical study. A blend of Gelatin-methacryloyl (GelMA) and PEGDA200 PhotoInk was used as a bioink for printing the serpentine network, while facilitating cell growth within the pores of the gelatin substrate. Human umbilical vein endothelial cells were seeded into the channels of the network to simulate the blood vessels. A Live-Dead assay was performed over a period of 14 days to observe the cellular viability in the printed vascular channels. It was observed that cell viability increases when the seeded cells were exposed to the evenly distributed shear stresses at an input flow rate of 4.62 mm/min of the culture media, similar to that predicted in the numerical model with the same inlet boundary condition. It leads to recruitment of a large number of focal adhesion point nodes on cellular membrane, emphasizing the influence of such phenomena on promoting cellular morphologies.

Influence of Non-Newtonian Viscosity on Flow Structures and Wall Deformation in Compliant Serpentine Microchannels: A Numerical Study

“…These pressure values were converted into their corresponding inlet velocities for serpentine geometries 1 and 2. Three different flow rates (corresponding to systolic, diastolic, and mean arterial pressure) based on the transient inlet velocity functions of sinusoidal (SF; V 1 , V 2 , and V 3 ) and physiological (PF; V 4 , V 5 , and V 6 ) were considered in the study [ 31 ]. The physiological functions (waveform) were derived from 4D Laser Doppler data of blood flow across the cross section of the subclavicular artery of a healthy subject.…”

“…The functions corresponding to the inlet flow velocity conditions for V 1 to V 6 are given in Table 1 . One complete cycle of both sinusoidal and physiological flows is equivalent to the required simulation time, as represented by T [ 31 ]. Different study models were formulated for S1 and S2 as tabulated in Table 2 .…”

“…The Navier–Stokes equation was used to represent the momentum of the fluid model. Time-dependent partial differential equation of incompressible Navier–Stokes (Equation (1)) was used for the simulation [ 31 , 32 ]: where is the fluid density, is the velocity vector, and is the dynamic viscosity. The non-Newtonian power-law formulation was also considered for evaluating the viscosity of the culture medium.…”

“…The following methods and termination parameters were used—nonlinear method: constant (Newton), termination technique: iteration or tolerance, and termination criteria: solution and residual. Sensitivity and uncertainty analyses were performed to observe the variability of the output parameters for different input parameters following previously used methods [ 31 ].…”

“…The Navier-Stokes equation was used to represent the momentum of the fluid model. Time-dependent partial differential equation of incompressible Navier-Stokes (Equation ( 1)) was used for the simulation [31,32]:…”