Literature DB >> 27227541

Roughness gradients on zirconia for rapid screening of cell-surface interactions: Fabrication, characterization and application.

Quentin Flamant1,2, Ana-Maria Stanciuc3, Hugo Pavailler1, Christoph Martin Sprecher3, Mauro Alini3, Marianna Peroglio3, Marc Anglada1,2.   

Abstract

Roughness is one of the key parameters for successful osseointegration of dental implants. The understanding of how roughness affects cell response is thus crucial to improve implant performance. Surface gradients, which allow rapid and systematic investigations of cell-surface interactions, have the potential to facilitate this task. In this study, a novel method aiming to produce roughness gradients at the surface of zirconia using hydrofluoric acid etching was implemented. The topography was exhaustively characterized at the microscale and nanoscale by white light interferometry and atomic force microscopy, including the analysis of amplitude, spatial, hybrid, functional, and fractal parameters. A rapid screening of the influence of roughness on human mesenchymal stem cell morphology was conducted and potential correlations between roughness parameters and cell morphology were investigated. The roughness gradient induced significant changes in cell area (p < 0.001), aspect ratio (p = 0.01), and solidity (p = 0.026). Nanoroughness parameters were linearly correlated to cell solidity (p < 0.005), while microroughness parameters appeared nonlinearly correlated to cell area, highlighting the importance of multiscale optimization of implant topography to induce the desired cell response. The gradient method proposed here drastically reduces the efforts and resources necessary to study cell-surface interactions and provides results directly transferable to industry.
© 2016 Wiley Periodicals, Inc. J Biomed Mater Res Part A: 104A: 2502-2514, 2016. © 2016 Wiley Periodicals, Inc.

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Keywords:  Y-TZP ceramics; human mesenchymal stem cells; hydrofluoric acid etching; surface modification; topography

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Year:  2016        PMID: 27227541     DOI: 10.1002/jbm.a.35791

Source DB:  PubMed          Journal:  J Biomed Mater Res A        ISSN: 1549-3296            Impact factor:   4.396


  2 in total

1.  Adhesion and differentiation of Saos-2 osteoblast-like cells on chromium-doped diamond-like carbon coatings.

Authors:  Elena Filova; Marta Vandrovcova; Miroslav Jelinek; Josef Zemek; Jana Houdkova; Tomas Kocourek; Lubica Stankova; Lucie Bacakova
Journal:  J Mater Sci Mater Med       Date:  2016-12-20       Impact factor: 3.896

2.  Transfer Learning via Deep Neural Networks for Implant Fixture System Classification Using Periapical Radiographs.

Authors:  Jong-Eun Kim; Na-Eun Nam; June-Sung Shim; Yun-Hoa Jung; Bong-Hae Cho; Jae Joon Hwang
Journal:  J Clin Med       Date:  2020-04-14       Impact factor: 4.241

  2 in total

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