인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
개인구독
소속 기관이 없으신 경우, 개인 정기구독을 하시면 저렴하게
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지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
Background: Inflammation induces dysfunction of endothelial cells via inflammatory cell adhesion, and this phenomenon and reactive oxygen species accumulation are pivotal triggers for atherosclerosis-related vascular disease. Although exosomes are excellent candidate as an inhibitor in the inflammation pathway, it is necessary to develop exosome-mimetic nanovesicles (NVs) due to limitations of extremely low release rate and difficult isolation of natural exosomes. NVs are produced in much larger quantities than natural exosomes, but due to the low flexibility of the cell membranes, the high loss caused by hanging on the filter membranes during extrusion remains a challenge to overcome. Therefore, by making cell membranes more flexible, more efficient production of NVs can be expected. Methods: To increase the flexibility of the cell membranes, the suspension of umbilical cord-mesenchymal stem cells (UC-MSCs) was subjected to 5 freeze and thaw cycles (FT) before serial extrusion. After serial extrusion through membranes with three different pore sizes, FT/NVs were isolated using a tangential flow filtration (TFF) system. NVs or FT/NVs were pretreated to the human coronary artery endothelial cells (HCAECs), and then inflammation was induced using tumor necrosis factor-α (TNF-α). Results: With the freeze and thaw process, the production yield of exosome-mimetic nanovesicles (FT/NVs) was about 3 times higher than the conventional production method. The FT/NVs have similar biological properties as NVs for attenuating TNF-α induced inflammation. Conclusion: We proposed the efficient protocol for the production of NVs with UC-MSCs using the combination of freeze and thaw process with a TFF system. The FT/NVs successfully attenuated the TNF-α induced inflammation in HCAECs.
본문·목차
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.