Suppr超能文献

磁性色谱法改善了磁脂质体的胶体和磁共振成像属性,从而能够在胰腺癌模型中评估尺寸对生物分布的影响。

Magnetic chromatography improves colloidal and MRI attributes of magnetoliposomes enabling evaluation of the impact of size on bio-distribution in an model of pancreatic cancer.

作者信息

Moloney Cara, Roy Chaudhuri Tista, Straubinger Robert M, Brougham Dermot F

机构信息

School of Chemistry, University College Dublin, Belfield, Dublin 4, Ireland.

Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, University at Buffalo, State University of New York, Buffalo, NY, 14214, USA.

出版信息

J Mater Chem B. 2025 Feb 5;13(6):2203-2209. doi: 10.1039/d4tb02219j.

Abstract

Magnetic chromatography was exploited to fractionate suspensions of magnetoliposomes (SML: lumen-free lipid-encapsulated clusters of multiple magnetic iron-oxide nanoparticles) improving their colloidal properties and relaxivity (magnetic resonance image contrast capability). Fractionation (i) removed sub-populations that do not contribute to the MRI response, and thus (ii) enabled evaluation of the size-dependence of relaxivity for the MRI-active part, which was surprisingly weak in the 55-90 nm range. MC was therefore implemented for processing multiple PEGylated SML types having average sizes ranging from 85 to 105 nm, which were then shown to have strongly size-dependent uptake in an pancreatic cancer model. Hence for applications in cancer diagnosis, selection of SML of suitable size for the biological target is more important than size-dependence of relaxivity.

摘要

利用磁色谱法对磁脂质体悬浮液(SML:由多个磁性氧化铁纳米颗粒组成的无内腔脂质包裹簇)进行分级分离,改善其胶体性质和弛豫率(磁共振成像对比能力)。分级分离(i)去除了对MRI响应无贡献的亚群,因此(ii)能够评估MRI活性部分弛豫率的尺寸依赖性,令人惊讶的是,在55-90nm范围内这种依赖性很弱。因此,对平均尺寸在85至105nm范围内的多种聚乙二醇化SML类型实施了磁色谱法,然后显示这些SML在胰腺癌模型中具有强烈的尺寸依赖性摄取。因此,对于癌症诊断应用,为生物靶点选择合适尺寸的SML比弛豫率的尺寸依赖性更为重要。

相似文献

本文引用的文献

7
Ferumoxytol-enhanced MRI in the peripheral vasculature.铁氧体增强 MRI 在周围血管中的应用。
Clin Radiol. 2019 Jan;74(1):37-50. doi: 10.1016/j.crad.2018.02.021. Epub 2018 May 3.

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