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Quantification of cell adhesion using a spinning disc device and application to surface-reactive materials

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García, Andrés J., Ducheyne, Paul, Boettiger, David·1997·Biomaterials

Abstract

Quantitative analysis of cell adhesion is essential in understanding physiological phenomena and developing biotechnological applications. Electrochemical measurements demonstrated that the transport patterns associated with a spinning disc device approximate the fluid flow and mass transport fields for a disc spinning in an infinite fluid. Therefore, this device applies a linear range of forces to attached cells under uniform and constant chemical conditions at the interface. The application of this apparatus for examining cell adhesion to surface-active materials was illustrated by investigating the attachment of osteoblast-like cells to fibronectin adsorbed onto bioactive and non-reactive glasses for different chemical environments. Cells were seeded on fibronectin-coated substrates for 15 min and then subjected to detachment forces for 10 min. The number of adherent cells decreased non-linearly with applied force and the detachment profile was accurately described by a sigmoidal curve fit, as expected for a cell population with normally distributed adhesion properties.

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Metadata

Authors
García, A. J., Ducheyne, P., & Boettiger, D.
Venue
Biomaterials
Publisher
Elsevier BV
Published
1997-08
Volume
18
Issue
16
Pages
1091-1098
ISSN
0142-9612 (ISSN-L)
OpenAlex
W2058721966
Cited by
226
References
0
FWCI
1.45
Type
journal article
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: Quantification of cell adhesion using a spinning disc device and application to surface-reactive materials. https://app.cochat.ai/papers/10.1016/s0142-9612(97)00042-2
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García, A. J., Ducheyne, P., & Boettiger, D. (1997). Quantification of cell adhesion using a spinning disc device and application to surface-reactive materials. Biomaterials. https://doi.org/10.1016/s0142-9612(97)00042-2

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.