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Cited by 1,258

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Engineering Substrate Topography at the Micro‐ and Nanoscale to Control Cell Function

Open access
Bettinger, Christopher J., Langer, Robert, Borenstein, Jeffrey T.·2009·Angewandte Chemie International Edition

Abstract

The interaction of mammalian cells with nanoscale topography has proven to be an important signaling modality in controlling cell function. Naturally occurring nanotopographic structures within the extracellular matrix present surrounding cells with mechanotransductive cues that influence local migration, cell polarization, and other functions. Synthetically nanofabricated topography can also influence cell morphology, alignment, adhesion, migration, proliferation, and cytoskeleton organization. We review the use of in vitro synthetic cell–nanotopography interactions to control cell behavior and influence complex cellular processes, including stem‐cell differentiation and tissue organization. Future challenges and opportunities in cell–nanotopography engineering are also discussed, including the elucidation of mechanisms and applications in tissue engineering.

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Metadata

Authors
Bettinger, C. J., Langer, R., & Borenstein, J. T.
Venue
Angewandte Chemie International Edition
Publisher
Wiley
Published
2009-07-08
Volume
48
Issue
30
Pages
5406-5415
ISSN
  • 1433-7851 (ISSN-L)
  • 1521-3773
OpenAlex
W2170271633
Cited by
1,258
References
100
FWCI
28.19
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Engineering Substrate Topography at the Micro‐ and Nanoscale to Control Cell Function. https://app.cochat.ai/papers/10.1002/anie.200805179
The paper
Bettinger, C. J., Langer, R., & Borenstein, J. T. (2009). Engineering Substrate Topography at the Micro‐ and Nanoscale to Control Cell Function. Angewandte Chemie International Edition. https://doi.org/10.1002/anie.200805179

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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.