材料科学
脂质体
钙黄绿素
纳米颗粒
药物输送
纳米医学
阿霉素
氧化铁纳米粒子
渗透(战争)
磁性纳米粒子
脂质双层
磁流体
膜
纳米技术
化学工程
分析化学(期刊)
磁场
色谱法
化学
物理
工程类
外科
医学
量子力学
生物化学
化疗
运筹学
作者
Maria Eugênia Fortes Brollo,Ana Lucía Dominguez,Andrea Tabero,Vicente Domínguez-Arca,Victor G. Gisbert,Gerardo Prieto,Christer Johansson,Ricardo Garcı́a,Ángeles Villanueva,María Concepción Serrano,M. P. Morales
标识
DOI:10.1021/acsami.9b20603
摘要
We have developed a reproducible and facile one step strategy for the synthesis of doxorubicin loaded magnetoliposomes by using a thin-layer evaporation method. Liposomes of around 200 nm were made of 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC) and iron oxide nanoparticles (NPs) with negative, positive, and hydrophobic surfaces that were incorporated outside, inside, or between the lipid bilayers, respectively. To characterize how NPs are incorporated in liposomes, advanced cryoTEM and atomic force microscope (AFM) techniques have been used. It was observed that only when the NPs are attached outside the liposomes, the membrane integrity is preserved (lipid melt transition shifts to 38.7 °C with high enthalpy 34.8 J/g) avoiding the leakage of the encapsulated drug while having good colloidal properties and the best heating efficiency under an alternating magnetic field (AMF). These magnetoliposomes were tested with two cancer cell lines, MDA-MB-231 and HeLa cells. First, 100% of cellular uptake was achieved with a high cell survival (above 80%), which is preserved (83%) for doxorubicin-loaded magnetoliposomes. Then, we demonstrate that doxorubicin release can be triggered by remote control, using a noninvasive external AMF for 1 h, leading to a cell survival reduction of 20%. Magnetic field conditions of 202 kHz and 30 mT seem to be enough to produce an effective heating to avoid drug degradation. In conclusion, these drug-loaded magnetoliposomes prepared in one step could be used for drug release on demand at a specific time and place, efficiently using an external AMF to reduce or even eliminate side effects.
科研通智能强力驱动
Strongly Powered by AbleSci AI