State Key Laboratory of Chemical Resource Engineering, Beijing University of Chemical Technology, Beijing 100029, China.
International Center for Materials Nanoarchitectonics (MANA), National Institute for Materials Science (NIMS), 1-1 Namiki, Tsukuba 305-0044, Japan.
Nanoscale. 2019 Jul 21;11(27):12889-12897. doi: 10.1039/c9nr03643a. Epub 2019 Jun 27.
The effective discrimination of dopamine (DA) analogues is an enduring challenge because of their very tiny structural differences, and thus a separation technique is generally required during the conventional analysis. In this study, a hyperbranched polyethyleneimine (hPEI)-based fluorescent sensor array has been constructed for the separation-free and effective differentiation of four DA analogues. The discrimination includes two steps: firstly, the formation of fluorescent polymer nanoparticles (FPNs) with diverse emission profiles via hPEI-mediated self-polymerization reaction of DA analogues and secondly, the linear discriminant analysis of fluorescence patterns of the formed FPNs for the differentiation of DA analogues. The hPEI-assisted self-polymerization reaction of DA analogues and substitution group mediated optical properties of the resulted FPNs enable an excellent discrimination of four DA analogues at a concentration of 1.0 μM when linear discriminant analysis and hierarchical cluster analysis are smartly combined. Additionally, binary, tertiary and even quaternary mixtures of analogues can also be well distinguished with the proposed sensor array. The practicability of this established sensor array is validated by a high accuracy (100%) evaluation of 88 blind samples containing a single analogue or a mixture of two, three or four analogues.
有效区分多巴胺 (DA) 类似物是一项持久的挑战，因为它们的结构差异非常小，因此在常规分析中通常需要分离技术。在这项研究中，构建了基于超支化聚乙烯亚胺 (hPEI) 的荧光传感器阵列，用于无需分离即可有效区分四种 DA 类似物。这种区分包括两个步骤：首先，通过 hPEI 介导的 DA 类似物的自聚合反应，形成具有不同发射谱的荧光聚合物纳米粒子 (FPNs)；其次，对形成的 FPNs 的荧光模式进行线性判别分析，以区分 DA 类似物。DA 类似物的 hPEI 辅助自聚合反应和取代基介导的所得 FPNs 的光学性质，使得在浓度为 1.0 μM 时，可以通过巧妙结合线性判别分析和层次聚类分析，对四种 DA 类似物进行出色的区分。此外，还可以使用所提出的传感器阵列很好地区分二元、三元甚至四元混合物的类似物。通过对包含单个类似物或两种、三种或四种类似物混合物的 88 个盲样进行 100%的高精度评估，验证了该建立的传感器阵列的实用性。
