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3D Printing of Microgel?Loaded Modular Microcages as Instructive Scaffolds for Tissue Engineering

Novel 3D printed microcages that can be easily assembled via simple stacking to fit the complexity of various tissue defects are introduced. Individual microcage units allow for spatial loading of biomolecules to instruct site?specific cell migration three?dimensionally and facilitate neovascularization in vivo, thus accelerating the process of healing.Biomaterial scaffolds have served as the foundation of tissue engineering and regenerative medicine. However, scaffold systems are often difficult to scale in size or shape in order to fit defect?specific dimensions, and thus provide only limited spatiotemporal control of therapeutic delivery and host tissue responses. Here, a lithography?based 3D printing strategy is used to fabricate a novel miniaturized modular microcage scaffold system, which can be assembled and scaled manually with ease. Scalability is based on an intuitive concept of stacking modules, like conventional toy interlocking plastic blocks, allowing for literally thousands of potential geometric configurations, and without the need for specialized equipment. Moreover, the modular hollow?microcage design allows each unit to be loaded with biologic cargo of different compositions, thus enabling controllable and easy patterning of therapeutics within the material in 3D. In summary, the concept of miniaturized microcage designs with such straight?forward assembly and scalability, as well as controllable loading properties, is a flexible platform that can be extended to a wide range of materials for improved biological performance.

Publication date: 23/07/2020

Author: Ramesh Subbiah, Christina Hipfinger, Anthony Tahayeri, Avathamsa Athirasala, Sivaporn Horsophonphong, Greeshma Thrivikraman, Cristiane Miranda França, Diana Araujo Cunha, Amin Mansoorifar, Albena Zahariev, James M. Jones, Paulo G. Coelho, Luk

Reference: doi:10.1002/adma.202001736

Advanced Materials

      

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 870292.