| 双重介导脑靶向脂质体增强荷载阿霉素的体外血-脑脊液屏障渗透率 |
| 投稿时间：2022-09-22 修订日期：2022-10-12 点此下载全文 |
| 引用本文：黑玉,梅子,陈阳,滕彬宏.双重介导脑靶向脂质体增强荷载阿霉素的体外血-脑脊液屏障渗透率[J].医学研究杂志,2024,53(1):30-35 |
| DOI：
10.11969/j.issn.1673-548X.2024.01.008 |
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| 基金项目:国家自然科学基金资助项目(81202469) |
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| 中文摘要:目的 探讨双重介导脑靶向脂质体(RVGPR9-SSL)作为递送载体对阿霉素(doxorubicin, DOX)血-脑脊液屏障(blood brain barrier, BBB)渗透率的影响,为脑部药物递送提供新的策略。方法 利用前期构建的双重介导脑靶向脂质体(RVGPR9-SSL)作为载体包载DOX(DOX@RVGPR9-SSL)。培养脑毛细血管内皮细胞(brain microvascular endothelial cells, BMVEC),在体外构建BBB模型,通过4h渗漏实验、跨膜电阻值(transmembrane resistance value, TEER)测量、扫描透射电镜(scanning transmission electron microscope, SEM)观察细胞间的紧密连接等,鉴定体外BBB模型构建是否成功。在BBB模型构建成功后,利用荧光共振能量转移(fluorescence a resonance energy transfer, FRET),通过激光共聚焦显微镜,考察RVGPR9-SSL体跨越BBB后的完整性。通过对比分析脂质体给药前后,BBB的形态以及TEER值,考察RVGPR9-SSL跨越BBB后对BBB完整性的影响。通过荧光分光光度计,考察DOX@RVGPR9-SSL的BBB渗透率。结果 RVGPR9-SSL的包封率为97.25％。构建的BBB模型的TEER值均>200Ω·cm2,并通过SEM观察到BMVEC细胞排列紧密,存在着明显的紧密连接,说明体外BBB模型成功建立,可用于考察BBB渗透率。DOX@RVGPR9-SSL4h累积BBB渗透率>10%,显著高于游离DOX的4h累积BBB渗透率。给药后BBB与DOX@RVGPR9-SSL均能保持较好的完整性。结论 RVGPR9-SSL可以显著提高所包载的DOX的BBB渗透率,并且具有较好的安全性,是非常有前景的脑部药物递送载体。 |
| 中文关键词:双重介导脑靶向脂质体 血-脑脊液屏障 累积渗透率 荧光共振能量转移 |
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| A Review of the Knowledge Discovery Methods Based on Knowledge Graph in the Biomedical Field |
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| Abstract:Purpose/Significance To review the knowledge discovery methods based on knowledge graph in the biomedical field, and to provide references for researchers.Methods/Process The paper summarizes the knowledge discovery methods based on knowledge graph by systematically searching and analyzing the relevant literatures,and compares the advantages and disadvantages of various knowledge discovery methods. It points out that the limitations and challenges of knowledge discovery methods based on knowledge graph in the biomedical field, and puts forward suggestions and prospects.Result/Conclusion In the future research, it is suggested to improve the interpretability of knowledge discovery results, build an effective result evaluation framework, and establish a standardized knowledge discovery process with multi-domain experts’ collaboration, so as to improve the quality and efficiency of knowledge discovery research. |
| keywords:biomedicine knowledge graph knowledge discovery |
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