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Evolutionary design of optimal surface topographies Sci Rep published.pdf (2.33 MB)
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Evolutionary design of optimal surface topographies for biomaterials

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posted on 21.12.2020, 02:30 by David WinklerDavid Winkler, Alexei Vasilevich, Amelie Carlier, S Singh, Jan de Boer.
AbstractNatural evolution tackles optimization by producing many genetic variants and exposing these variants to selective pressure, resulting in the survival of the fittest. We use high throughput screening of large libraries of materials with differing surface topographies to probe the interactions of implantable device coatings with cells and tissues. However, the vast size of possible parameter design space precludes a brute force approach to screening all topographical possibilities. Here, we took inspiration from Nature to optimize materials surface topographies using evolutionary algorithms. We show that successive cycles of material design, production, fitness assessment, selection, and mutation results in optimization of biomaterials designs. Starting from a small selection of topographically designed surfaces that upregulate expression of an osteogenic marker, we used genetic crossover and random mutagenesis to generate new generations of topographies.

History

Publication Date

17/12/2020

Journal

Scientific Reports

Volume

10

Issue

1

Article Number

22160

Publisher

Springer Nature

ISSN

2045-2322

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The Author reserves all moral rights over the deposited text and must be credited if any re-use occurs. Documents deposited in OPAL are the Open Access versions of outputs published elsewhere. Changes resulting from the publishing process may therefore not be reflected in this document. The final published version may be obtained via the publisher’s DOI. Please note that additional copyright and access restrictions may apply to the published version.

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