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Cited by 392

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Composite poly(vinyl alcohol)/poly(vinyl acetate) electrospun nanofibrous mats as a novel wound dressing matrix for controlled release of drugs

Open access
Varshosaz, Jaleh, Jannesari, Marziyeh, Morshed, Mohammad, Zamani, Maedeh·2011·International Journal of Nanomedicine

Abstract

The aim of this study was to develop novel biomedicated nanofiber electrospun mats for controlled drug release, especially drug release directly to an injury site to accelerate wound healing. Nanofibers of poly(vinyl alcohol) (PVA), poly(vinyl acetate) (PVAc), and a 50:50 composite blend, loaded with ciprofloxacin HCl (CipHCl), were successfully prepared by an electrospinning technique for the first time. The morphology and average diameter of the electrospun nanofibers were investigated by scanning electron microscopy. X-ray diffraction studies indicated an amorphous distribution of the drug inside the nanofiber blend. Introducing the drug into polymeric solutions significantly decreased solution viscosities as well as nanofiber diameter. In vitro drug release evaluations showed that both the kind of polymer and the amount of drug loaded greatly affected the degree of swelling, weight loss, and initial burst and rate of drug release. Blending PVA and PVAc exhibited a useful and convenient method for electrospinning in order to control the rate and period of drug release in wound healing applications. Also, the thickness of the blend nanofiber mats strongly influenced the initial release and rate of drug release.

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Crossref · 10.2147/ijn.s17595

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Metadata

Authors
Varshosaz, J., Jannesari, M., Morshed, M., & Zamani, M.
Venue
International Journal of Nanomedicine
Published
2011-05
Volume
6
Pages
993
ISSN
  • 1176-9114 (ISSN-L)
  • 1178-2013
OpenAlex
W2046564987
Cited by
392
References
1
FWCI
7.53
Type
journal article
Language
en
Open access
gold

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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).

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