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Proc Natl Acad Sci U S A. 2011 Oct 4;108(40):16565-70. doi: 10.1073/pnas.1109861108. Epub 2011 Sep 26.

An algorithm-based topographical biomaterials library to instruct cell fate.

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1
Department of Tissue Regeneration, MIRA Institute for Biomedical Technology and Technical Medicine, University of Twente, 7500AE, Enschede, The Netherlands.

Erratum in

  • Proc Natl Acad Sci U S A. 2013 Apr 2;110(14):5731.
  • Proc Natl Acad Sci U S A. 2012 Apr 10;109(15):5905. Carpenter, Anne E [added]; Wessling, Matthias [added].

Abstract

It is increasingly recognized that material surface topography is able to evoke specific cellular responses, endowing materials with instructive properties that were formerly reserved for growth factors. This opens the window to improve upon, in a cost-effective manner, biological performance of any surface used in the human body. Unfortunately, the interplay between surface topographies and cell behavior is complex and still incompletely understood. Rational approaches to search for bioactive surfaces will therefore omit previously unperceived interactions. Hence, in the present study, we use mathematical algorithms to design nonbiased, random surface features and produce chips of poly(lactic acid) with 2,176 different topographies. With human mesenchymal stromal cells (hMSCs) grown on the chips and using high-content imaging, we reveal unique, formerly unknown, surface topographies that are able to induce MSC proliferation or osteogenic differentiation. Moreover, we correlate parameters of the mathematical algorithms to cellular responses, which yield novel design criteria for these particular parameters. In conclusion, we demonstrate that randomized libraries of surface topographies can be broadly applied to unravel the interplay between cells and surface topography and to find improved material surfaces.

Comment in

PMID:
21949368
PMCID:
PMC3189082
DOI:
10.1073/pnas.1109861108
[Indexed for MEDLINE]
Free PMC Article
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