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使用基于智能手机的比色传感器阵列快速精准识别抗氧化剂和农药。

Accelerated and precise identification of antioxidants and pesticides using a smartphone-based colorimetric sensor array.

作者信息

Luan Tian, Zhang Yu, Song Zhimin, Zhou Yanru, Ma Chong-Bo, Lu Lehui, Du Yan

机构信息

Key Laboratory of Polyoxometalate and Reticular Material Chemistry of Ministry of Education, National & Local United Engineering Laboratory for Power Batteries, Key Laboratory of Nanobiosensing and Nanobioanalysis at Universities of Jilin Province, Analysis and Testing Center, Department of Chemistry, Northeast Normal University, Changchun, Jilin, 130024, China; State Key Laboratory of Electroanalytical Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, Jilin, 130022, China; School of Applied Chemistry and Engineering, University of Science and Technology of China, Hefei, Anhui, 230026, China.

State Key Laboratory of Electroanalytical Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, Jilin, 130022, China; School of Applied Chemistry and Engineering, University of Science and Technology of China, Hefei, Anhui, 230026, China.

出版信息

Talanta. 2024 Sep 1;277:126275. doi: 10.1016/j.talanta.2024.126275. Epub 2024 May 22.

Abstract

The integration of smartphones with conventional analytical approaches plays a crucial role in enhancing on-site detection platforms for point-of-care testing. Here, we developed a simple, rapid, and efficient three-channel colorimetric sensor array, leveraging the peroxidase (POD)-like activity of polydopamine-decorated FeNi foam (PDFeNi foam), to identify antioxidants using both microplate readers and smartphones for signal readouts. The exceptional catalytic capacity of PDFeNi foam enabled the quick catalytic oxidation of three typical peroxidase substrates (TMB, OPD and 4-AT) within 3 min. Consequently, we constructed a colorimetric sensor array with cross-reactive responses, which was successfully applied to differentiate five antioxidants (i.e., glycine (GLY), glutathione (GSH), citric acid (CA), ascorbic acid (AA), and tannic acid (TAN)) within the concentration range of 0.1-10 μM, quantitatively analyze individual antioxidants (with AA and CA as model analytes), and assess binary mixtures of AA and GSH. The practical application was further validated by discriminating antioxidants in serum samples with a smartphone for signal readout. In addition, since pesticides could be absorbed on the surface of PDFeNi foam through π-π stacking and hydrogen bonding, the active sites were differentially masked, leading to featured modulation on POD-like activity of PDFeNi foam, thereby forming the basis for pesticides discrimination on the sensor array. The nanozyme-based sensor array provides a simple, rapid, visual and high-throughput strategy for precise identification of various analytes with a versatile platform, highlighting its potential application in point-care-of diagnostic, food safety and environmental surveillance.

摘要

智能手机与传统分析方法的集成在增强即时检测的现场检测平台方面发挥着关键作用。在此,我们开发了一种简单、快速且高效的三通道比色传感器阵列,利用聚多巴胺修饰的泡沫铁镍(PDFeNi泡沫)的过氧化物酶(POD)样活性,使用酶标仪和智能手机进行信号读取来识别抗氧化剂。PDFeNi泡沫出色的催化能力能够在3分钟内快速催化氧化三种典型的过氧化物酶底物(TMB、OPD和4-AT)。因此,我们构建了具有交叉反应响应的比色传感器阵列,该阵列成功应用于区分浓度范围为0.1 - 10 μM的五种抗氧化剂(即甘氨酸(GLY)、谷胱甘肽(GSH)、柠檬酸(CA)、抗坏血酸(AA)和单宁酸(TAN)),定量分析单个抗氧化剂(以AA和CA作为模型分析物),并评估AA和GSH的二元混合物。通过使用智能手机读取信号来鉴别血清样品中的抗氧化剂,进一步验证了该实际应用。此外,由于农药可以通过π-π堆积和氢键吸附在PDFeNi泡沫表面,活性位点被不同程度地掩盖,导致PDFeNi泡沫的POD样活性发生特征性调制,从而形成了在传感器阵列上鉴别农药的基础。基于纳米酶的传感器阵列提供了一种简单、快速、可视化且高通量的策略,用于在通用平台上精确识别各种分析物,突出了其在即时诊断、食品安全和环境监测中的潜在应用。

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