Suppr超能文献

用于静脉给药和脾脏靶向的隐形聚乙二醇化聚氰基丙烯酸酯纳米颗粒。

Stealth PEGylated polycyanoacrylate nanoparticles for intravenous administration and splenic targeting.

作者信息

Peracchia M T, Fattal E, Desmaële D, Besnard M, Noël J P, Gomis J M, Appel M, d'Angelo J, Couvreur P

机构信息

Université Paris XI, Pharmacotechnie, UMR CNRS 8612 - 5, rue J.B. Clément, 92296, Châtenay-Malabry, France.

出版信息

J Control Release. 1999 Jun 28;60(1):121-8. doi: 10.1016/s0168-3659(99)00063-2.

Abstract

The aim of the present work was to investigate the biodistribution characteristics of PEG-coated polycyanoacrylate nanoparticles prepared by the nanoprecipitation/solvent diffusion method using the previously synthesized poly(MePEGcyanoacrylate-hexadecylcyanoacrylate) copolymer. It was observed that [14C]-radiolabeled PEGylated nanoparticles remained for a longer time in the blood circulation after intravenous administration to mice, compared to the non-PEGylated poly(hexadecylcyanoacrylate) (PHDCA) nanoparticles. Furthermore, hepatic accumulation was dramatically reduced, whereas a highly increased spleen uptake was shown. The PEGylation degree of the polymer seemed not to affect the in vivo behavior of the nanoparticles, whereas previously obtained in vitro data have shown a modification of plasma protein adsorption depending on the density of PEG at the surface of the particles. Moreover, the study of the in vitro cytotoxicity of the nanoparticles revealed that the PEGylation of the cyanoacrylate polymer reduced its toxicity. These results open up interesting perspectives for the targeting of drugs to other tissues than the liver.

摘要

本研究的目的是利用先前合成的聚(甲氧基聚乙二醇氰基丙烯酸酯 - 十六烷基氰基丙烯酸酯)共聚物,通过纳米沉淀/溶剂扩散法制备聚乙二醇包覆的聚氰基丙烯酸酯纳米颗粒,并研究其生物分布特性。观察到,与未聚乙二醇化的聚(十六烷基氰基丙烯酸酯)(PHDCA)纳米颗粒相比,[14C]放射性标记的聚乙二醇化纳米颗粒在静脉注射给小鼠后在血液循环中停留的时间更长。此外,肝脏蓄积显著减少,而脾脏摄取则显著增加。聚合物的聚乙二醇化程度似乎不影响纳米颗粒的体内行为,而先前获得的体外数据表明,血浆蛋白吸附会根据颗粒表面聚乙二醇的密度而发生改变。此外,对纳米颗粒的体外细胞毒性研究表明,氰基丙烯酸酯聚合物的聚乙二醇化降低了其毒性。这些结果为将药物靶向肝脏以外的其他组织开辟了有趣的前景。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验