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基于咪唑调控的具有增强漆酶样活性的Cu@MOFs纳米酶的传感阵列用于酚类污染物的鉴别

Sensing array based on imidazole-regulated Cu@MOFs nanozymes with enhanced laccase-like activity for the discrimination of phenolic pollutants.

作者信息

Zhu Fang, Li Mengfan, Yang Yudi, Ai Fengxiang, Fan Yunxiang, Deng Chunmeng, Zeng Kun, Wei Dali, Deng Yibin, Zhang Zhen

机构信息

School of the Environment and Safety Engineering, School of the Emergency Management, Jiangsu University, Zhenjiang, 212013, China.

School of the Environment and Safety Engineering, School of the Emergency Management, Jiangsu University, Zhenjiang, 212013, China.

出版信息

Anal Chim Acta. 2025 Feb 8;1338:343592. doi: 10.1016/j.aca.2024.343592. Epub 2024 Dec 27.

Abstract

BACKGROUND

Phenolic pollutants with high toxicity and low biodegradability can disrupt environmental balance and severely affect human health, whereas existing methods are difficult to implement the rapid and high-throughput detection of multiple phenolic pollutants.

RESULTS

Herein, we developed a four-dimensional colorimetric sensor array based on imidazole-modulated Cu@MOFs for distinguishing and determining phenolic pollutants. Wherein, four Cu@MOFs (ATP@Cu, ADP@Cu, AMP@Cu, and GMP@Cu) nanozyme with laccase-like activity were firstly prepared, and a novel strategy of imidazole-containing molecules-regulated was proposed to improve the laccase-like activity of Cu@MOFs nanozymes. Interestingly, imidazole (IM) exhibited the strongest enhancing effects on the laccase-like activity of the four Cu@MOFs by accelerating electron transfer on the surface of laccase nanozymes and producing more reactive oxygen species. Subsequently, by using Cu@MOFs@IM as the recognition elements of the sensor array, a colorimetric sensor array based on imidazole-modulated Cu@MOFs was developed, and differentiation and classification of phenolic pollutants were carried out using LDA and HCA methods. More importantly, the proposed sensor array could accomplish the identification of 6 phenolic pollutants and their mixtures.

SIGNIFICANCE

Additionally, the designed sensor array was applied to identify these phenolic pollutants in real water samples, further highlighting the potentials for assessing water pollution.

摘要

背景

具有高毒性和低生物降解性的酚类污染物会破坏环境平衡并严重影响人类健康,而现有方法难以实现对多种酚类污染物的快速高通量检测。

结果

在此,我们开发了一种基于咪唑调制的Cu@MOFs的四维比色传感器阵列,用于区分和测定酚类污染物。其中,首先制备了四种具有漆酶样活性的Cu@MOFs(ATP@Cu、ADP@Cu、AMP@Cu和GMP@Cu)纳米酶,并提出了一种含咪唑分子调控的新策略来提高Cu@MOFs纳米酶的漆酶样活性。有趣的是,咪唑(IM)通过加速漆酶纳米酶表面的电子转移并产生更多活性氧,对四种Cu@MOFs的漆酶样活性表现出最强的增强作用。随后,以Cu@MOFs@IM作为传感器阵列的识别元件,开发了一种基于咪唑调制的Cu@MOFs的比色传感器阵列,并使用LDA和HCA方法对酚类污染物进行了区分和分类。更重要的是,所提出的传感器阵列可以完成6种酚类污染物及其混合物的识别。

意义

此外,将所设计的传感器阵列应用于实际水样中这些酚类污染物的识别,进一步突出了其在评估水污染方面的潜力。

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