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Computational approaches for the prediction of the selective uptake of magnetofluorescent nanoparticles into human cells

机译:将磁荧光纳米粒子的选择性摄取预测到人细胞中的计算方法

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The use of functionalized nanomaterials is of high importance in biomedical applications like the efficient targeting of cancer cells. This paper proposes a comparison of different statistical and mechanistic aspects of new QSAR models generated to predict the selective uptake of a library of surface modified nanoparticles tested in different human cell types. Additionally, a new approach based on the combination of multivariate factorial analysis and QSAR is proposed to generate a 2-dimensional map of the selective uptake of the surface modified nanoparticles into multiple cell types. This map offers an immediate view of the uptake of the nanoparticles, distinguishing among those with high or low uptake in one or more of the studied cells. Finally, QSAR models are generated to predict the coordinates of the studied nanoparticles in the 2D map from their molecular structure. This predictive map is useful to screen new and existing surface modified nanoparticles for diagnostic and biomedical uses.
机译:官能化纳米材料的使用在生物医学应用中具有很高的重要性,如癌细胞的有效靶向。本文提出了对产生的新QSAR模型的不同统计和机械方面的比较预测不同人细胞类型测试的表面改性纳米粒子文库的选择性摄取。另外,提出了一种基于多变量阶乘分析和QSAR组合的新方法,以产生二维图的表面改性纳米粒子的选择性摄取到多个细胞类型。该地图提供了纳米粒子的摄取立即看,区分中的一种或多种研究的细胞中的高或低吸收。最后,产生QSAR模型以预测来自其分子结构的2D图中研究的纳米颗粒的坐标。该预测地图可用于筛选用于诊断和生物医学用途的新型和现有的表面改性纳米颗粒。

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