The DOI matches its Crossref record; 17 of the 17 references it cites were found in a registry or an index.
Directing cell migration with asymmetric micropatterns
Open accessAbstract
This report shows that the direction of polarization of attached mammalian cells determines the direction in which they move. Surfaces micropatterned with appropriately functionalized self-assembled monolayers constrain individual cells to asymmetric geometries (for example, a teardrop); these geometries polarize the morphology of the cell. After electrochemical desorption of the self-assembled monolayers removes these constraints and allows the cells to move across the surface, they move toward their blunt ends.
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Cites
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Cited by
Local force and geometry sensing regulate cell functions
Vogel, V., & Sheetz, M. (2006) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm1890 · Cited by 2,328
Geometric cues for directing the differentiation of mesenchymal stem cells
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Functional and Biomimetic Materials for Engineering of the Three-Dimensional Cell Microenvironment
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Micropatterning as a tool to decipher cell morphogenesis and functions
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The regulation of stem cell differentiation by cell-cell contact on micropatterned material surfaces
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Metadata
- Authors
- Jiang, X., Bruzewicz, D. A., Wong, A. P., Piel, M., & Whitesides, G. M.
- Venue
- Proceedings of the National Academy of Sciences
- Published
- 2005-01-14
- Volume
- 102
- Issue
- 4
- Pages
- 975-978
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- OpenAlex
- W2049471883
- Cited by
- 447
- References
- 17
- FWCI
- 8.41
- Type
- journal article
- Language
- en
- Open access
- green
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- Jiang, X., Bruzewicz, D. A., Wong, A. P., Piel, M., & Whitesides, G. M. (2005). Directing cell migration with asymmetric micropatterns. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.0408954102
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.
