The DOI matches its Crossref record; 17 of the 17 references it cites were found in a registry or an index.
Extracellular matrix as an inductive scaffold for functional tissue reconstruction
Open accessAbstract
The extracellular matrix (ECM) is a meshwork of both structural and functional proteins assembled in unique tissue-specific architectures. The ECM both provides the mechanical framework for each tissue and organ and is a substrate for cell signaling. The ECM is highly dynamic, and cells both receive signals from the ECM and contribute to its content and organization. This process of “dynamic reciprocity” is key to tissue development and for homeostasis. Based upon these important functions, ECM-based materials have been used in a wide variety of tissue engineering and regenerative medicine approaches to tissue reconstruction. It has been demonstrated that ECM-based materials, when appropriately prepared, can act as inductive templates for constructive remodeling. Specifically, such materials act as templates for the induction of de novo functional, site-appropriate, tissue formation. Herein, the diverse structural and functional roles of the ECM are reviewed to provide a rationale for the use of ECM scaffolds in regenerative medicine. Translational examples of ECM scaffolds in regenerative are provided, and the potential mechanisms by which ECM scaffolds elicit constructive remodeling are discussed. A better understanding of the ability of ECM scaffold materials to define the microenvironment of the injury site will lead to improved clinical outcomes associated with their use.
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Cites
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Metadata
- Authors
- Brown, B. N., & Badylak, S. F.
- Venue
- Translational Research
- Publisher
- Elsevier BV
- Published
- 2014-04
- Volume
- 163
- Issue
- 4
- Pages
- 268-285
- ISSN
- 1878-1810 (ISSN-L)
- 1931-5244
- OpenAlex
- W2094650509
- Cited by
- 516
- References
- 17
- FWCI
- 22.75
- Type
- journal article
- Language
- en
- Open access
- green
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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.
