Yang Yumin, Du Kunze, Liu Meng, He Xicheng, Li Hui, Li Haixiang, Li Xiaoxia
School of Chinese Materia Medica, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China; State Key Laboratory of Chinese Medicine Modernization, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China; Tianjin Key Laboratory of Therapeutic Substance of Traditional Chinese Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China.
State Key Laboratory of Chinese Medicine Modernization, Tianjin University of Traditional Chinese Medicine, Tianjin 301617, China.
Food Chem. 2025 Nov 1;491:145219. doi: 10.1016/j.foodchem.2025.145219. Epub 2025 Jun 20.
Zearalenone (ZEN), a common mycotoxin, is prevalent in food and agricultural by-products, presenting considerable health risks. A novel strategy was established in this research based on the computer-aided design synthesis of Poly(DES)@MIL-101-NH(Cr) for effective removal of ZEN. Initially, the optimal ratio of template molecules to deep eutectic solvents (DES) was predicted using density functional theory (DFT), and Poly(DES)@MIL-101-NH(Cr) was synthesized through surface imprinting technology. The adsorption mechanism for ZEN was elucidated using electrostatic potential (ESP) distribution and the independent gradient model (IGMH). Adsorption experiments demonstrated that incorporating DES significantly enhanced the material's adsorption performance. Ultimately, the specific removal and detection of ZEN in coix seeds were achieved by combining solid-phase extraction (SPE) with high-performance liquid chromatography (HPLC), yielding a recovery rate of 93.99 %, a detection limit of 0.0146 mg/L, and a quantification limit of 0.0485 mg/L. The computer-aided design method for polymers provides a new reference for the effective removal of other trace contaminants in food.
玉米赤霉烯酮（ZEN）是一种常见的霉菌毒素，在食品和农业副产品中普遍存在，会带来相当大的健康风险。本研究基于计算机辅助设计合成聚（DES）@MIL-101-NH（Cr）建立了一种有效去除ZEN的新策略。首先，利用密度泛函理论（DFT）预测模板分子与低共熔溶剂（DES）的最佳比例，并通过表面印迹技术合成聚（DES）@MIL-101-NH（Cr）。利用静电势（ESP）分布和独立梯度模型（IGMH）阐明了ZEN的吸附机制。吸附实验表明，加入DES显著提高了材料的吸附性能。最终，通过固相萃取（SPE）与高效液相色谱（HPLC）联用实现了对薏苡仁中ZEN的特异性去除和检测，回收率为93.99%，检测限为0.0146 mg/L，定量限为0.0485 mg/L。聚合物的计算机辅助设计方法为有效去除食品中的其他微量污染物提供了新的参考。
