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Cited by 286

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

Skin regeneration scaffolds: a multimodal bottom-up approach

Open access
Yildirimer, Lara, Thanh, Nguyen T.K., Seifalian, Alexander M.·2012·Trends in Biotechnology

Abstract

Skin wounds are a major social and financial burden. However, current treatments are suboptimal. The gradual comprehension of the finely orchestrated nature of intercellular communication has stimulated scientists to investigate growth factor (GF) or stem cell (SC) incorporation into suitable scaffolds for local delivery into wound beds in an attempt to accelerate healing. This review provides a critical evaluation of the status quo of current research into GF and SC therapy and subsequent future prospects, including benefits and possible long-term dangers associated with their use. Additionally, we stress the importance of a bottom-up approach in scaffold fabrication to enable controlled factor incorporation as well as production of complex scaffold micro- and nanostructures resembling that of natural extracellular matrix.

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Crossref · 10.1016/j.tibtech.2012.08.004

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Metadata

Authors
Yildirimer, L., Thanh, N. T. K., & Seifalian, A. M.
Venue
Trends in Biotechnology
Publisher
Elsevier BV
Published
2012-12
Volume
30
Issue
12
Pages
638-648
ISSN
0167-7799 (ISSN-L)
OpenAlex
W2117808317
Cited by
286
References
3
FWCI
1.84
Type
journal article
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: Skin regeneration scaffolds: a multimodal bottom-up approach. https://app.cochat.ai/papers/10.1016/j.tibtech.2012.08.004
The paper
Yildirimer, L., Thanh, N. T. K., & Seifalian, A. M. (2012). Skin regeneration scaffolds: a multimodal bottom-up approach. Trends in Biotechnology. https://doi.org/10.1016/j.tibtech.2012.08.004

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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.