Mining for osteogenic surface topographies
In silico design to in vivo osseo-integration
Frits F.B. Hulshof (University of Twente, Maastricht University)
Bernke J. Papenburg (Materiomics B.V.)
Aliaksei Vasilevich (Maastricht University)
Marc Hulsman (TU Delft - Pattern Recognition and Bioinformatics)
Yiping Zhao (Materiomics B.V.)
Marloes Levers (Materiomics B.V.)
Natalie Fekete (Materiomics B.V.)
Meint de Boer (University of Twente)
Huipin Yuan (Xpand Biotechnology BV)
Marcel Reinders (TU Delft - Pattern Recognition and Bioinformatics)
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Abstract
Stem cells respond to the physicochemical parameters of the substrate on which they grow. Quantitative material activity relationships – the relationships between substrate parameters and the phenotypes they induce – have so far poorly predicted the success of bioactive implant surfaces. In this report, we screened a library of randomly selected designed surface topographies for those inducing osteogenic differentiation of bone marrow-derived mesenchymal stem cells. Cell shape features, surface design parameters, and osteogenic marker expression were strongly correlated in vitro. Furthermore, the surfaces with the highest osteogenic potential in vitro also demonstrated their osteogenic effect in vivo: these indeed strongly enhanced bone bonding in a rabbit femur model. Our work shows that by giving stem cells specific physicochemical parameters through designed surface topographies, differentiation of these cells can be dictated.
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