Issue 27, 2019, Issue in Progress

Enhancement of rotator cuff tendon–bone healing using combined aligned electrospun fibrous membranes and kartogenin

Abstract

Rotator cuff tear (RCT) is a major challenging shoulder disease because the fibrocartilage zone is hard to regenerate in the enthesis. Electrospun membranes with aligned nanofibers can guide the ordered tissue regeneration and kartogenin (KGN) is able to stimulate chondrocyte differentiation of mesenchymal stem cells. In this study, we fabricated a functional engineered scaffold for regenerating tendon–bone enthesis in RCTs by taking advantage of both the structural guiding ability of aligned nanofibers and the biology effects of KGN. Polycaprolactone (PCL) fibrous membranes with aligned nanofibers loaded with or without KGN were fabricated using electrospinning and characterized using scanning electron microscopy (SEM). The release of KGN from PCL membranes and the effects of KGN on differentiation of mesenchymal stem cells were investigated. Results indicated that 100 μM KGN-loaded PCL (KGN-PCL) membranes significantly stimulated chondrogenic and tenogenic differentiation of rat bone marrow stromal cells. In addition, after PCL and 100 μM KGN-PCL membranes were applied to an acute rat RCT model, KGN-PCL membranes promoted fibrocartilage formation and collagen organization as well as increased cross-sectional area and load failure. In conclusion, PCL electrospun fibrous membranes with aligned nanofibers and KGN could be an effective tissue engineering scaffold to enhance tendon–bone healing in RCTs.

Graphical abstract: Enhancement of rotator cuff tendon–bone healing using combined aligned electrospun fibrous membranes and kartogenin

Article information

Article type
Paper
Submitted
30 Nov 2018
Accepted
10 Apr 2019
First published
17 May 2019
This article is Open Access
Creative Commons BY-NC license

RSC Adv., 2019,9, 15582-15592

Enhancement of rotator cuff tendon–bone healing using combined aligned electrospun fibrous membranes and kartogenin

Q. Zhu, Z. Ma, H. Li, H. Wang and Y. He, RSC Adv., 2019, 9, 15582 DOI: 10.1039/C8RA09849B

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