Yong Xu1, Rebecca Rothe2,3, Dagmar Voigt4, Sandra Hauser2, Meiying Cui1, Takuya Miyagawa1, Michelle Patino Gaillez1, Thomas Kurth5, Martin Bornhäuser6,7, Jens Pietzsch8,9, Yixin Zhang10,11. 1. Technische Universität Dresden, B CUBE Center for Molecular Bioengineering, Dresden, Germany. 2. Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Institute of Radiopharmaceutical Cancer Research Department of Radiopharmaceutical and Chemical Biology, Dresden, Germany. 3. Technische Universität Dresden, School of Science, Faculty of Chemistry and Food Chemistry, Dresden, Germany. 4. Technische Universität Dresden, Institute for Botany, Faculty of Biology, Dresden, Germany. 5. Technische Universität Dresden, Center for Molecular and Cellular Bioengineering (CMCB), Technology Platform, EM Facilty, Dresden, Germany. 6. Center for Regenerative Therapies Dresden (CRTD), Technische Universität Dresden, Dresden, Germany. 7. University Hospital Carl Gustav Carus der Technischen Universität Dresden, Medizinische Klinik und Poliklinik I, Dresden, Germany. 8. Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Institute of Radiopharmaceutical Cancer Research Department of Radiopharmaceutical and Chemical Biology, Dresden, Germany. j.pietzsch@hzdr.de. 9. Technische Universität Dresden, School of Science, Faculty of Chemistry and Food Chemistry, Dresden, Germany. j.pietzsch@hzdr.de. 10. Technische Universität Dresden, B CUBE Center for Molecular Bioengineering, Dresden, Germany. yixin.zhang1@tu-dresden.de. 11. Cluster of Excellence Physics of Life, Technische Universität Dresden, Dresden, Germany. yixin.zhang1@tu-dresden.de.
Abstract
Many features of extracellular matrices, e.g., self-healing, adhesiveness, viscoelasticity, and conductivity, are associated with the intricate networks composed of many different covalent and non-covalent chemical bonds. Whereas a reductionism approach would have the limitation to fully recapitulate various biological properties with simple chemical structures, mimicking such sophisticated networks by incorporating many different functional groups in a macromolecular system is synthetically challenging. Herein, we propose a strategy of convergent synthesis of complex polymer networks to produce biomimetic electroconductive liquid metal hydrogels. Four precursors could be individually synthesized in one to two reaction steps and characterized, then assembled to form hydrogel adhesives. The convergent synthesis allows us to combine materials of different natures to generate matrices with high adhesive strength, enhanced electroconductivity, good cytocompatibility in vitro and high biocompatibility in vivo. The reversible networks exhibit self-healing and shear-thinning properties, thus allowing for 3D printing and minimally invasive injection for in vivo experiments.
Many features of extracellular matrices, e.g., self-healing, an class="Disease">dhesiveness, viscoelasticity, and conductivity, are associated with the intricate networks composed of many different covalent and non-covalent chemical bonds. Whereas a reductionism approach would have the limitation to fully recapitulate various biological properties with simple chemical structures, mimicking such sophisticated networks by incorporating many different functional groups in a macromolecular system is synthetically challenging. Herein, we propose a strategy of convergent synthesis of complex polymer networks to produce biomimetic electroconductive liquid metal hydrogels. Four precursors could be individually synthesized in one to two reaction steps and characterized, then assembled to form hydrogel adhesives. The convergent synthesis allows us to combine materials of different natures to generate matrices with high adhesive strength, enhanced electroconductivity, good cytocompatibility in vitro and high biocompatibility in vivo. The reversible networks exhibit self-healing and shear-thinning properties, thus allowing for 3D printing and minimally invasive injection for in vivo experiments.
Authors: Farshid Guilak; Daniel M Cohen; Bradley T Estes; Jeffrey M Gimble; Wolfgang Liedtke; Christopher S Chen Journal: Cell Stem Cell Date: 2009-07-02 Impact factor: 24.633