De-Epithelialization Protocol with Tapered Sodium Dodecyl Sulfate Concentrations Enhances Short-Term Chondrocyte Survival in Porcine Chimeric Tracheal Allografts

International Journal of Medical Students(2023)

引用 1|浏览11
暂无评分
摘要
Background: Tracheal transplantation is indicated in cases where injury exceeds 50% of the organ in adults and 30% in children. However, transplantation is not yet considered a viable treatment option partly due to high morbidity and mortality associated with graft rejection. Recently, decellularization (decell) has been explored as a technique for creating bioengineered tracheal grafts. However, risk of post-operative stenosis increases due to the death of chondrocytes, which are critical to maintain the biochemical and mechanical integrity of tracheal cartilage. In this project, we propose a new de-epithelialization protocol that adequately removes epithelial, mucosal, and submucosal cells while maintaining a greater proportion of viable chondrocytes. Methods: The trachea of adult male outbred Yorkshire pigs were extracted, decontaminated, and decellularized according to the original and new protocols before incubation at 37 °C in DMEM for 10 days. Chondrocyte viability was quantified immediately following post-decellularization and on days 1, 4, 7, and 10. Histology was performed pre-decellularization, post-decellularization, and post-incubation. Results: The new protocol showed a significant (p < 0.05) increase in chondrocyte viability up to four days after de-ep when compared to the original protocol. We also found that the new protocol preserves ECM composition to a similar degree as the original protocol. When scaffolds created using the new protocol were re-epithelialized, cell growth curves were near identical to published data from the original protocol. Conclusion: While not without limitations, our new protocol may be used to engineer chimeric tracheal allografts without the need for cartilage regeneration.
更多
查看译文
关键词
porcine chimeric tracheal allografts,de-epithelialization,short-term
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