Endogenous cell recruitment strategy for articular cartilage regeneration

Acta Biomaterialia(2020)

引用 0|浏览0
暂无评分
摘要
In the absence of timely and proper treatments, injuries to articular cartilage (AC) can lead to cartilage degeneration and ultimately result in osteoarthritis. Regenerative medicine and tissue engineering techniques are emerging as promising approaches for AC regeneration and repair. Although the use of cell-seeded scaffolds prior to implantation can regenerate and repair cartilage lesions to some extent, these approaches are still restricted by limited cell sources, excessive costs, risks of disease transmission and complex manufacturing practices. Recently developed acellular scaffold approaches that rely on the recruitment of endogenous cells to the injured sites avoid these drawbacks and offer great promise for in situ AC regeneration. Multiple endogenous stem/progenitor cells (ESPCs) are found in joint-resident niches and have the capability to migrate to sites of injury to participate in AC regeneration. However, the natural recruitment of ESPCs is insufficient, and the local microenvironment is hostile after injury. Hence, an endogenous cell recruitment strategy based on the combination of chemoattractants and acellular scaffolds to effectively and specifically recruit ESPCs and improve local microenvironment may provide new insights into in situ AC regeneration. This review provides a brief overview of: (1) the status of endogenous cell recruitment strategy; (2) the subpopulations, potential migration routes (PMRs) of joint-resident ESPCs and their immunomodulatory and reparative effects; (3) chemoattractants and their potential adverse effects; (4) scaffold-based drug delivery systems (SDDSs) that are utilized for in situ AC regeneration; and (5) the challenges and future perspectives of endogenous cell recruitment strategy for AC regeneration.
更多
查看译文
关键词
Endogenous cell recruitment,Cartilage regeneration,Endogenous stem/progenitor cells,Chemoattractants,Scaffold-based drug delivery systems
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