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用于选择性识别和提取马兜铃酸 I 的温敏和磁性分子印迹聚合物。

Thermosensitive and magnetic molecularly imprinted polymers for selective recognition and extraction of aristolochic acid I.

机构信息

State Key Laboratory of Food Science and Technology, Nanchang University, Nanchang 330047, China.

Jiangxi Province Key Laboratory of Modern Analytical Science, Nanchang University, Nanchang 330031, China.

出版信息

Food Chem. 2022 Mar 15;372:131250. doi: 10.1016/j.foodchem.2021.131250. Epub 2021 Sep 28.

DOI:10.1016/j.foodchem.2021.131250
PMID:34627093
Abstract

Recently, the natural compound of aristolochic acid I (AAI) has attracted wide attentions due to its strong nephrotoxicity and carcinogenicity. However, the extraction of AAI based on conventional molecularly imprinted polymers (MIPs) are tedious with extensive eluent, causing secondary pollution and poor regeneration. Herein, thermosensitive and magnetic MIPs (TMMIPs) were synthesized by a surface imprinting method, which achieved thermosensitive capture/release of AAI, along with rapid magnetic separation, significantly shortening the elution time and reducing organic-solvent consumption. TMMIPs with dual-stimuli responses exhibited superior affinity, selectivity, kinetics, and regeneration ability towards AAI. TMMIPs were applied to analyze AAI in Houttuynia cordata via dispersive solid-phase extraction (d-SPE) coupled with high performance liquid chromatography (HPLC), yielding satisfactory recoveries (79.03-99.67%) and relative standard deviations (≤5.78%). The limit of detection of AAI was as low as 26.67 µg/L. TMMIPs demonstrate great applicability for fast, selective and eco-friendly extraction of AAI in complicated matrices.

摘要

最近,天然化合物马兜铃酸 I(AAI)因其强烈的肾毒性和致癌性而引起了广泛关注。然而,基于常规分子印迹聚合物(MIPs)的 AAI 提取过程繁琐,需要大量洗脱液,会造成二次污染和较差的再生性。在此,通过表面印迹法合成了温敏和磁性分子印迹聚合物(TMMIPs),实现了 AAI 的温敏捕获/释放,以及快速的磁性分离,显著缩短了洗脱时间并减少了有机溶剂的消耗。TMMIPs 具有双重刺激响应,对 AAI 表现出优异的亲和力、选择性、动力学和再生能力。TMMIPs 通过分散固相萃取(d-SPE)与高效液相色谱(HPLC)结合,用于分析鱼腥草中的 AAI,获得了令人满意的回收率(79.03-99.67%)和相对标准偏差(≤5.78%)。AAI 的检测限低至 26.67 µg/L。TMMIPs 为快速、选择性和环保地从复杂基质中提取 AAI 提供了很好的适用性。

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引用本文的文献

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