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Mining for osteogenic surface topographies

Authors :
Bernke J. Papenburg
Dimitrios Stamatialis
Marcel J. T. Reinders
Meint J. de Boer
Mark-Anthony Bray
Jan de Boer
Shantanu Singh
Frits Hulshof
Clemens van Blitterswijk
Yiping Zhao
Huipin Yuan
David J. Logan
Aliaksei Vasilevich
Anne E. Carpenter
Nick R.M. Beijer
Marloes Levers
Natalie Fekete
Marc Hulsman
Biomaterials Science and Technology
RS: MERLN - Cell Biology - Inspired Tissue Engineering (CBITE)
CBITE
Division Instructive Biomaterials Eng
RS: MERLN - Complex Tissue Regeneration (CTR)
RS: MERLN - Instructive Biomaterials Engineering (IBE)
CTR
Source :
Biomaterials, 137, 49-60. Elsevier, Biomaterials, 137, 49-60. ELSEVIER SCI LTD
Publication Year :
2017

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. (C) 2017 Elsevier Ltd. All rights reserved.

Details

Language :
English
ISSN :
01429612
Volume :
137
Database :
OpenAIRE
Journal :
Biomaterials
Accession number :
edsair.doi.dedup.....2894a0daf44a7c3dc844c3dc07015db5
Full Text :
https://doi.org/10.1016/j.biomaterials.2017.05.020