Beyond Linear Elastic Modulus: Viscoelastic Models for Brain and Brain Mimetic Hydrogels

Abstract

With their high degree of specificity and investigator control, in vitro disease models provide a natural complement to in vivo models. Especially in organs such as the brain, where anatomical limitations make in vivo experiments challenging, in vitro models have been increasingly used to mimic disease pathology. However, brain mimetic models may not fully replicate the mechanical environment in vivo, which has been shown to influence a variety of cell behaviors. Specifically, many disease models consider only the linear elastic modulus of brain, which describes the stiffness of a material with the assumption that mechanical behavior is independent of loading rate. Here, we characterized porcine brain tissue using a modified stress relaxation test, and across a panel of viscoelastic models, showed that stiffness depends on loading rate. As such, the linear elastic modulus does not accurately reflect the viscoelastic properties of native brain. Among viscoelastic models, the Maxwell model was selected for further analysis because of its simplicity and excellent curve fit (R 2 = 0.99 ± 0.0006). Thus, mechanical response of native brain and hydrogel mimetic models was analyzed using the Maxwell model and the linear elastic model to evaluate the effects of strain rate, time post mortem, region, tissue type (i.e., bulk brain vs white matter), and in brain mimetic models, hydrogel composition, on observed mechanical properties. In comparing the Maxwell and linear elastic models, linear elastic modulus is consistently lower than the Maxwell elastic modulus across all brain regions. Additionally, the Maxwell model is sensitive to changes in viscosity and small changes in elasticity, demonstrating improved fidelity. These findings demonstrate the insufficiency of linear elastic modulus as a primary mechanical characterization for brain mimetic materials and provide quantitative information toward the future design of materials that more closely mimic mechanical features of brain.

Hydrogel scaffolds based on blood plasma cryoprecipitate and collagen derived from various sources: Structural, mechanical and biological characteristics

“…For example, O. Chaudhuri et al (2016) found out that cells'spreading, proliferation, and osteogenic differentiation of mesenchymal stem cells (MSCs) are all enhanced in cells cultured in gels with faster relaxation [18]. That is why extensive research is devoted to the study of the physicomechanical properties of hydrogels and the development of new methods for assessing these properties [[19], [20], [21], [22], [23]]. Although it is currently difficult to obtain cytocompatible hydrogels with the mechanical properties of native tissues, significant progress has been achieved in the development of materials with custom properties [[24], [25], [26]].…”

Spike frequency–dependent inhibition and excitation of neural activity by high-frequency ultrasound

“…Simulations of acoustic pressure, heating, and static displacement in response to radiation force were performed as described previously ( Prieto et al, 2018 ). For simulation of dynamic tissue displacement in response to radiation force, the brain slice was modeled as a incompressible, linear viscoelastic material ( Calhoun et al, 2019 ), characterized by Young’s modulus, Poisson’s ratio, and shear viscosity, loaded by the fluid layer above it. The polystyrene was modeled as a linear elastic material, because we determined in a series of simulations that including viscosity of the polystyrene had no effect on the tissue displacement.…”

Multiscale Experimental Evaluation of Agarose-Based Semi-Interpenetrating Polymer Network Hydrogels as Materials with Tunable Rheological and Transport Performance

“…Calculation of the mesh sizes from frequency sweep tests (using Equations ( 3) to ( 6)) is based on the rubber elasticity theory [72]. Although the validity of this theory for gels has continuously been questioned [73,74], it has been repeatedly utilized to calculate the mesh size of hydrogels based on rheometric parameters [52,75]. Previously, we have applied this approach in the determination of mesh size of polysaccharide-based phase-separated hydrogels [76].…”