Development and Characterization of an Injectable Alginate/Chitosan Composite Hydrogel Reinforced with Cyclic-RGD Functionalized Graphene Oxide for Potential Tissue Regeneration Applications

<b>Background:</b> In tissue engineering, developing injectable hydrogels with tailored mechanical and bioactive properties remains a challenge. This study introduces an injectable hydrogel composite for soft tissue regeneration, composed of oxidized alginate (OA) and N-succinyl chitosan (NSC) cross-linked via Schiff base reaction, reinforced with graphene oxide (GOx) and cyclic arginylglycylaspartic acid (c-RGD). The objective was to create a multifunctional platform combining injectability, bioactivity, and structural stability. <b>Methods:</b> The OA/NSC/GOx-cRGD hydrogel was synthesized through Schiff base cross-linking (aldehyde-amine reaction). Characterization included FTIR (C=N bond at 1650 cm⁻¹), Raman spectroscopy (D/G bands at 1338/1567 cm⁻¹), SEM (porous microstructure), and rheological analysis (shear-thinning behavior). In vitro assays assessed fibroblast viability (MTT) and macrophage <i>TNF-α</i> secretion (ELISA), while ex-vivo injectability and retention were evaluated using chicken cardiac tissue. <b>Results:</b> The hydrogel exhibited shear-thinning behavior (viscosity: 10 to <1 Pa·s) and elastic-dominated mechanics (G' > G″), ensuring injectability. SEM revealed an interconnected porous structure mimicking native extracellular matrix. Fibroblast viability remained ≥95%, and <i>TNF-α</i> secretion in macrophages decreased by 80% (30 vs. 150 pg/μL in controls), demonstrating biocompatibility and anti-inflammatory effects. The hydrogel adhered stably to cardiac tissue without leakage. <b>Conclusions:</b> The OA/NSC/GOx-cRGD composite integrates injectability, bioactivity, and structural stability, offering a promising scaffold for tissue regeneration. Its modular design allows further functionalization with peptides or growth factors. Future work will focus on translational applications, including scalability and optimization for dynamic biological environments.