journal article·2023-09

Design of IKVAV peptide/gold nanoparticle decorated, micro/nano-channeled PCL/PLGA film scaffolds for neuronal differentiation and neurite outgrowth

Asel Aydeger, Nese Aysit, Gulsena Baydas, Cagri Cakici, Umit Can Erim, Muhammet Davut Arpa, Ilyas Ozcicek

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Abstract

In the field of neural tissue engineering, intensive efforts are being made to develop tissue scaffolds that can support an effective functional recovery and neural development by guiding damaged axons and neurites. Micro/nano-channeled conductive biomaterials are considered a promising approach for repairing the injured neural tissues. Many studies have demonstrated that the micro/nano-channels and aligned nanofibers could guide the neurites to extend along the direction of alignment. However, an ideal biocompatible scaffold containing conductive arrays that could promote effective neural stem cell differentiation and development, and also stimulate high neurite guidance has not been fully developed. In the current study, we aimed to fabricate micro/nano-channeled polycaprolactone (PCL)/Poly-d,l-lactic-co-glycolic acid (PLGA) hybrid film scaffolds, decorate their surfaces with IKVAV pentapeptide/gold nanoparticles (AuNPs), and investigate the behavior of PC12 cells and neural stem cells (NSCs) on the developed biomaterial under static/bioreactor conditions. Here we show that channeled groups decorated with AuNPs highly promote neurite outgrowth and neuronal differentiation along linear lines in the presence of electrical stimulation, compared with the polypyrrole (PPy) coating, which has been used traditionally for many years. Hopefully, this newly developed channeled scaffold structure (PCL/PLGA-AuNPs-IKVAV) could help to support long-distance axonal regeneration and neuronal development after different neural damages.
Source: europepmc · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Graphene and Nanomaterials Applications · RNA Interference and Gene Delivery · Neuroscience and Neural Engineering

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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