3D Fabrication with Integration Molding of a Graphene Oxide/Polycaprolactone Nanoscaffold for Neurite Regeneration and Angiogenesis

Abstract: Treating peripheral nerve injury faces major challenges and may benefit from bioactive scaffolds due to the limited autograft resources. Graphene oxide (GO) has emerged as a promising nanomaterial with excellent physical and chemical properties. GO has functional groups that confer biocompatibility that is better than that of graphene. Here, GO/polycaprolactone (PCL) nanoscaffolds are fabricated using an integration molding method. The nanoscaffolds exhibit many merits, including even GO nanoparticle distribution, macroporous structure, and strong mechanical support. Additionally, the process enables excellent quality control. In vitro studies confirm the advantages of the GO/PCL nanoscaffolds in terms of Schwann cell proliferation, viability, and attachment, as well as neural characteristics maintenance. This is the first study to evaluate the in vivo performance of GO‐based nanoscaffolds in this context. GO release and PCL biodegradation is analyzed after long‐term in vivo study. It is also found that the GO/PCL nerve guidance conduit could successfully repair a 15 mm sciatic nerve defect. The pro‐angiogenic characteristic of GO is evaluated in vivo using immunohistochemistry. In addition, the AKT‐endothelial nitric oxide synthase (eNOS)‐vascular endothelial growth factor (VEGF) signaling pathway might play a major role in the angiogenic process. These findings demonstrate that the GO/PCL nanoscaffold efficiently promotes functional and morphological recovery in peripheral nerve regeneration, indicating its promise for tissue engineering applications.

Angaben zum Objekt

• Standort: Deutsche Nationalbibliothek Frankfurt am Main
• Umfang: Online-Ressource
• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: 3D Fabrication with Integration Molding of a Graphene Oxide/Polycaprolactone Nanoscaffold for Neurite Regeneration and Angiogenesis ; volume:5 ; number:4 ; year:2018 ; extent:18 ; Advanced science ; 5, Heft 4 (2018) (gesamt 18)

Beteiligte, Orts- und Zeitangaben

• Urheber: Qian, Yun ; Song, Jialin ; Zhao, Xiaotian ; Chen, Wei ; Ouyang, Yuanming ; Yuan, Weien ; Fan, Cunyi

Weitere Informationen

• DOI: 10.1002/advs.201700499
• URN: urn:nbn:de:101:1-2022082308553360486697
• Rechteinformation: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
• Letzte Aktualisierung: 15.08.2025, 07:33 MESZ