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Selective Differentiation of Neural Progenitor Cells by High-Epitope Density Nanofibers
Abstract
Neural progenitor cells were encapsulated in vitro within a three-dimensional network of nanofibers formed by self-assembly of peptide amphiphile molecules. The self-assembly is triggered by mixing cell suspensions in media with dilute aqueous solutions of the molecules, and cells survive the growth of the nanofibers around them. These nanofibers were designed to present to cells the neurite-promoting laminin epitope IKVAV at nearly van der Waals density. Relative to laminin or soluble peptide, the artificial nanofiber scaffold induced very rapid differentiation of cells into neurons, while discouraging the development of astrocytes. This rapid selective differentiation is linked to the amplification of bioactive epitope presentation to cells by the nanofibers.
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Cites
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Tibbitt, M. W., & Anseth, K. S. (2009) · Biotechnology and Bioengineering · doi:10.1002/bit.22361 · Cited by 2,727
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Stevens, M. M., & George, J. H. (2005) · Science · doi:10.1126/science.1106587 · Cited by 2,607
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Moghimi, S. M., Hunter, A. C., & Murray, J. C. (2005) · The FASEB Journal · doi:10.1096/fj.04-2747rev · Cited by 2,029
Metadata
- Authors
- Silva, G. A., Czeisler, C., Niece, K. L., Beniash, E., Harrington, D. A., Kessler, J. A., & Stupp, S. I.
- Venue
- Science
- Published
- 2004-02-27
- Volume
- 303
- Issue
- 5662
- Pages
- 1352-1355
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W2073795835
- Cited by
- 2,169
- References
- 1
- FWCI
- 52.89
- Type
- journal article
- Language
- en
- Open access
- closed
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- Silva, G. A., Czeisler, C., Niece, K. L., Beniash, E., Harrington, D. A., Kessler, J. A., & Stupp, S. I. (2004). Selective Differentiation of Neural Progenitor Cells by High-Epitope Density Nanofibers. Science. https://doi.org/10.1126/science.1093783
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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.
