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Immune Modulation by Design: Using Topography to Control Human Monocyte Attachment and Macrophage Differentiation

Vassey, Matthew J.; Figueredo, Grazziela P.; Scurr, David J.; Vasilevich, Aliaksei S.; Vermeulen, Steven; Carlier, Aur�lie; Luckett, Jeni; Beijer, Nick R.M.; Williams, Paul; Winkler, David A.; de Boer, Jan; Ghaemmaghami, Amir M.; Alexander, Morgan R.

Immune Modulation by Design: Using Topography to Control Human Monocyte Attachment and Macrophage Differentiation Thumbnail


Authors

Matthew J. Vassey

DAVID SCURR DAVID.SCURR@NOTTINGHAM.AC.UK
Principal Research Fellow

Aliaksei S. Vasilevich

Steven Vermeulen

Aur�lie Carlier

JENI LUCKETT JENI.LUCKETT@NOTTINGHAM.AC.UK
Senior Research Fellow

Nick R.M. Beijer

PAUL WILLIAMS PAUL.WILLIAMS@NOTTINGHAM.AC.UK
Professor of Molecular Microbiology

David A. Winkler

Jan de Boer

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MORGAN ALEXANDER MORGAN.ALEXANDER@NOTTINGHAM.AC.UK
Professor of Biomedical Surfaces



Abstract

© 2020 The Authors. Published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim Macrophages play a central role in orchestrating immune responses to foreign materials, which are often responsible for the failure of implanted medical devices. Material topography is known to influence macrophage attachment and phenotype, providing opportunities for the rational design of “immune-instructive” topographies to modulate macrophage function and thus foreign body responses to biomaterials. However, no generalizable understanding of the inter-relationship between topography and cell response exists. A high throughput screening approach is therefore utilized to investigate the relationship between topography and human monocyte–derived macrophage attachment and phenotype, using a diverse library of 2176 micropatterns generated by an algorithm. This reveals that micropillars 5–10µm in diameter play a dominant role in driving macrophage attachment compared to the many other topographies screened, an observation that aligns with studies of the interaction of macrophages with particles. Combining the pillar size with the micropillar density is found to be key in modulation of cell phenotype from pro to anti-inflammatory states. Machine learning is used to successfully build a model that correlates cell attachment and phenotype with a selection of descriptors, illustrating that materials can potentially be designed to modulate inflammatory responses for future applications in the fight against foreign body rejection of medical devices.

Journal Article Type Article
Acceptance Date Mar 11, 2020
Online Publication Date Apr 28, 2020
Publication Date 2020-06
Deposit Date Apr 3, 2020
Publicly Available Date Apr 30, 2020
Journal Advanced Science
Electronic ISSN 2198-3844
Publisher Wiley
Peer Reviewed Peer Reviewed
Volume 7
Issue 11
Article Number 1903392
DOI https://doi.org/10.1002/advs.201903392
Keywords General Engineering; General Physics and Astronomy; General Materials Science; Medicine (miscellaneous); General Chemical Engineering; Biochemistry, Genetics and Molecular Biology (miscellaneous)
Public URL https://nottingham-repository.worktribe.com/output/4246086
Publisher URL https://onlinelibrary.wiley.com/doi/full/10.1002/advs.201903392
Additional Information Received: 2019-12-11; Accepted: 2020-03-11; Published: 2020-04-28