An in vitro evaluation of zinc silicate fortified chitosan scaffolds for bone tissue engineering
Abstract
Tissue engineering aims at replacement, repair, and regeneration of tissues by a combination of scaffolds, growth factors, and cells. In this study, we report the synthesis of biodegradable composite scaffolds fortified with mesoporous zinc silicate (mZS) and assessment of in vitro properties for bone tissue engineering (BTE) applications. The scaffolds consisted of chitosan (CS) incorporated with mZS at 0.1, 0.2, 0.3, and 0.5 wt%. The bio-composite scaffolds were visualized using Field Emission Scanning Electron Microscopy (FE-SEM). The incorporation of mZS was confirmed using Energy dispersive x-ray (EDS) analysis. Biomineralization studies were conducted in simulated body fluid (SBF) and indicated bioactivity of fabricated scaffolds. The scaffolds also displayed antibacterial action against Staphylococcus aureus. Cellular attachment within the scaffold network established biocompatibility of the material. Incorporation of mZS within the chitosan scaffolds matrix improved properties such as porosity, degradation rate, and biomineralization. Therefore, fabricated scaffolds exhibit exceptional features and have the potential to serve as an implant for BTE applications.
Read the paper
Related studies
- The Matrisome: In Silico Definition and In Vivo Characterization by Proteomics of Normal and Tumor Extracellular Matrices
- The Escherichia coli MG1655 in silico metabolic genotype: Its definition, characteristics, and capabilities
- In silico pharmacology for drug discovery: methods for virtual ligand screening and profiling
- In silico prediction of splice-altering single nucleotide variants in the human genome
- In silico clinical trials: how computer simulation will transform the biomedical industry
- In silico optimization of a guava antimicrobial peptide enables combinatorial exploration for peptide design
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.