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Cited by 167

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Fibroblasts probe substrate rigidity with filopodia extensions before occupying an area

Open access
Wong, Stephanie, Guo, Wei-Hui, Wang, Yu-Li·2014·Proceedings of the National Academy of Sciences

Abstract

Significance: Mechanical properties of the extracellular environment provide important cues that regulate cell behavior. Understanding this mechanical signaling has become important in disease treatment as well as tissue engineering. To efficiently study cellular responses to rigidity signals, we have created a model system of micropatterned composite material based on the “cell-on-a-chip” concept. We demonstrate that a migrating fibroblast uses filopodia to probe substrate rigidity, such that it “feels” its way based on the deformability of a material before occupying an area. Myosin II plays a key role in rigidity sensing and responses. This mechanism allows cells to migrate efficiently by avoiding mechanically unfavorable areas without backtracking.

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Metadata

Authors
Wong, S., Guo, W.-H., & Wang, Y.-L.
Venue
Proceedings of the National Academy of Sciences
Published
2014-11-17
Volume
111
Issue
48
Pages
17176-17181
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W2021286146
Cited by
167
References
3
FWCI
4.79
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Fibroblasts probe substrate rigidity with filopodia extensions before occupying an area. https://app.cochat.ai/papers/10.1073/pnas.1412285111
The paper
Wong, S., Guo, W.-H., & Wang, Y.-L. (2014). Fibroblasts probe substrate rigidity with filopodia extensions before occupying an area. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.1412285111

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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.