Optimization of 3D Synthetic Scaffolds for Neuronal Tissue Engineering Applications

CHEMISTRY-A EUROPEAN JOURNAL(2024)

引用 0|浏览6
暂无评分
摘要
The increasing prevalence of neurodegenerative diseases has spurred researchers to develop advanced 3D models that accurately mimic neural tissues. Hydrogels stand out as ideal candidates as their properties closely resemble those of the extracellular matrix. A critical challenge in this regard is to comprehend the influence of the scaffold's mechanical properties on cell growth and differentiation, thus enabling targeted modifications. In light of this, a synthesis and comprehensive analysis of acrylamide-based hydrogels incorporating a peptide has been conducted. Adequate cell adhesion and development is achieved due to their bioactive nature and specific interactions with cellular receptors. The integration of a precisely controlled physicochemical hydrogel matrix and inclusion of the arginine-glycine-aspartic acid peptide sequence has endowed this system with an optimal structure, thus providing a unique ability to interact effectively with biomolecules. The analysis fully examined essential properties governing cell behavior, including pore size, mechanical characteristics, and swelling ability. Cell-viability experiments were performed to assess the hydrogel's biocompatibility, while the incorporation of grow factors aimed to promote the differentiation of neuroblastoma cells. The results underscore the hydrogel's ability to stimulate cell viability and differentiation in the presence of the peptide within the matrix. The increasing prevalence of neurodegenerative diseases has prompted researchers to develop advanced three-dimensional models that accurately mimic neuronal tissues. In this regard, the synthesis of an acrylamide-based hydrogel incorporating the peptide sequence arginine-glycine-aspartic acid has been carried out, examined in depth the matrix properties that govern cell behavior.image
更多
查看译文
关键词
3D scaffold,extracellular matrix,hydrogel,neurodegenerative disease,RGD peptide
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要