(*) Understanding the Spatiotemporal Degradation Behavior of Aggrecanase-Sensitive Poly(ethylene glycol) Hydrogels for Use in Cartilage Tissue Engineering

(*) 了解用于软骨组织工程的聚集蛋白酶敏感型聚乙二醇水凝胶的时空降解行为

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Abstract

Enzyme-sensitive hydrogels are promising cell delivery vehicles for cartilage tissue engineering. However, a better understanding of their spatiotemporal degradation behavior and its impact on tissue growth is needed. The goal of this study was to combine experimental and computational approaches to provide new insights into spatiotemporal changes in hydrogel crosslink density and extracellular matrix (ECM) growth and how these changes influence the evolving macroscopic properties as a function of time. Hydrogels were designed from aggrecanase-sensitive peptide crosslinks using a simple and robust thiol-norbornene photoclick reaction. To study the influence of variations in cellular activity of different donors, chondrocytes were isolated from either juvenile or adult bovine donors. Initial studies were performed to validate and calibrate the model against experiments. Through this process, two key features were identified. These included spatial variations in the hydrogel crosslink density in the immediate vicinity of the cell and the presence of cell clustering within the construct. When these spatial heterogeneities were incorporated into the computational model along with model inputs of initial hydrogel properties and cellular activity (i.e., enzyme and ECM production rates), the model was able to capture the spatial and temporal evolution of ECM growth that was observed experimentally for both donors. In this study, the juvenile chondrocytes produced an interconnected matrix within the cell clusters leading to overall improved ECM growth, while the adult chondrocytes resulted in poor ECM growth. Overall, the computational model was able to capture the spatiotemporal ECM growth of two different donors and provided new insights into the importance of spatial heterogeneities in facilitating ECM growth. Our long-term goal is to use this model to predict optimal hydrogel designs for a wide range of donors and improve cartilage tissue engineering.

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