Conductive Chitosan–Graphene Oxide Scaffold with Applications in Peripheral Nerve Tissue Engineering

This study aimed to develop a novel biomaterial for neural tissue regeneration by combining chitosan (CS), a natural polymer, with graphene oxide (GO) at concentrations of 3%, 6%, and 9%. The homogeneity, conductivity, three-dimensional characteristics, and ability to support cell viability of the composite materials were systematically evaluated. Fourier-Transform Infrared (FTIR) spectroscopy confirmed the successful incorporation of GO into the CS matrix, while UV-Vis and photoluminescence (PL) spectrometry revealed modifications in the optical properties with increasing GO content. Thermogravimetric analysis (TG-DSC) demonstrated improved thermal stability of the composites, and swelling tests indicated enhanced water absorption capacity. Although some agglomerates were observed, the homogeneity was reasonable at both macroscopic and microscopic level (optical visualization–FTIR and electron microscopy). The composite films exhibited promising physical and electrochemical properties, highlighting their potential for neural tissue engineering applications. Their biological activity was assessed by culturing neuronal cells on the CS-GO scaffolds. Results from MTT, LDH, and LIVE/DEAD assays demonstrated excellent cell viability, moderate-to-good cell attachment, and the promotion of intercellular network formation. Among the tested formulations, the CS-GO 6% scaffold showed the most favorable biological response, with a significant increase in SH-SY5Y cell viability after 7 days (p < 0.05) compared to the CS control. LIVE/DEAD imaging confirmed enhanced cell attachment and elongated morphology, while the LDH assay indicated minimal cytotoxicity. Notably, a critical threshold was identified between 6% and 9% GO, where conductivity increased by approximately 52-fold. Future studies should focus on optimizing the composite parameters, loading them with specific biologically active agents and thus targeting specific neuronal applications.