Computational analyses of agarose constructs to establish mechanobiological conditions for experiments

Hydrogels such as cell-seeded agarose provide versatile experimental systems for studying mechanobiological responses of chondrocytes, yet the intra-gel mechanical environment during loading remains poorly understood. In this study we aimed to quantify local mechanical cues within agarose constructs subjected to physiologically relevant loading conditions. We established sixty 3-D finite element simulations spanning five agarose concentrations from 3-5%, three loading modes (tension, compression, shear), two loading protocols (force- and displacement-controlled), and two magnitudes (low and high). We quantified spatial distributions of stresses, strains, strain energy densities, and fluid pressures to characterize intra-gel mechanics relevant to mechanotransduction in chondrocytes. Results revealed that even homogeneous constructs under simple cyclic loading generated heterogeneous local mechanical environments relevant to cartilage biology. Because gel stiffness scales with concentration, force-controlled loading maintains approximately constant stress while strain decreases with increasing stiffness. Conversely, displacement-controlled loading maintains constant strain while stress increases with increasing stiffness. This framework enables independent modulation of stress and strain when probing mechanobiology. Importantly, varying agarose concentration also mimics softening of the pericellular matrix during progression of osteoarthritis, thereby linking computational predictions to disease-relevant changes. These findings demonstrate that local mechanical cues differ fundamentally between force- and displacement-driven protocols and highlight the importance of accounting for spatial heterogeneity when interpreting experiments with homogeneous agarose constructs. By integrating computational modeling with experimental loading conditions, this study establishes a mechanistic framework to link intra-gel mechanics to responses of chondrocytes, providing both tools to advance understanding of chondrocyte/cartilage mechanobiology (thus also transcriptomics, proteomics, and metabolomics) and guidance for design of future experimental studies.