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Surface area and local curvature: Why roughness improves the bioactivity of neural implants

Ding, Ruikang and Miller, Nathaniel C. and Woeppel, Kevin M. and Cui, Xinyan T. and Jacobs, Tevis D. B. (2022) Surface area and local curvature: Why roughness improves the bioactivity of neural implants. Langmuir, 38. pp. 7512-7521. ISSN 1520-5827

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Abstract

While roughening the surface of neural implants has been shown to significantly improve their performance, the mechanism for this improvement is not understood, preventing systematic optimization of surfaces. Specifically, prior work has shown that the cellular response to a surface can be significantly enhanced by coating the implant surface with inorganic nanoparticles and neuroadhesion protein L1, and this improvement occurs even when the surface chemistry is identical between the nanoparticle-coated and uncoated electrodes, suggesting the critical importance of surface topography. Here, we use transmission electron microscopy to characterize the topography of bare and nanoparticle-coated implants across 7 orders of magnitude in size, from the device scale to the atomic scale. The results reveal multi-scale roughness, which cannot be adequately described using conventional roughness parameters. Indeed, the topography is nearly identical between the two samples at the smallest scales and also at the largest scales, but vastly different in the intermediate scales, especially in the range of 5-100 nm. Using a multi-scale topography analysis, we show that the coating
causes a 76% increase in the available surface area for contact, and an order-of-magnitude increase in local surface curvature at characteristic sizes corresponding to specific biological structures. These are correlated with a 75% increase in bound proteins on the surface, and a 134% increase in neurite outgrowth. The present investigation presents a framework for analyzing the scale-dependent topography of medical device-relevant surfaces, and suggests the most critical size scales that determine the biological response to implanted materials.


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Details

Item Type: Article
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Ding, RuikangRUD12@pitt.eduRUD120000-0003-2414-2655
Miller, Nathaniel C.ncm28@pitt.eduncm28
Woeppel, Kevin M.kmw103@pitt.edukmw103
Cui, Xinyan T.xic11@pitt.eduxic110000-0002-0470-2005
Jacobs, Tevis D. B.tjacobs@pitt.edutjacobs0000-0001-8576-914X
Date: 9 June 2022
Date Type: Publication
Journal or Publication Title: Langmuir
Volume: 38
Publisher: American Chemical Society
Page Range: pp. 7512-7521
DOI or Unique Handle: 10.1021/acs.langmuir.2c00473
Schools and Programs: Swanson School of Engineering > Materials Science and Engineering
Refereed: Yes
ISSN: 1520-5827
Funders: National Science Foundation under award number CMMI-1727378, the National Institute of Health under grant number R01NS110564, R01NS089688 and U01 NS113279
Article Type: Research Article
Date Deposited: 11 Jul 2022 16:38
Last Modified: 09 Jun 2023 05:15
URI: http://d-scholarship.pitt.edu/id/eprint/43283

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