Molecularly imprinted electrochemiluminescence sensor based on luminol functionalized Co-MOF for rifampicin detection

IF 5.3 2区 化学 Q1 CHEMISTRY, ANALYTICAL
Shuning Yang, Li Tian, Yongbo Feng, Yujia Song, Ruidan Li, Yanjia Guo, Huiling Li, Chao Li, Juan Lu
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Abstract

A highly sensitive molecularly imprinted electrochemiluminescence (MIECL) sensor was developed for detecting rifampicin (RIF) based on luminol@Co-MOF. Co-MOF had a significant enhancement of ECL signaling in the luminol-O2 system. Molecular imprinted polymers (MIPs) with the introduction of RIF provide new properties for the specific recognition of RIF. A noteworthy decrease in ECL intensity was observed with higher concentrations of RIF. Consequently, the ECL signal was controlled by RIF elution from and adsorption by the MIP, thus establishing a new method for RIF detection. Under optimal conditions, this sensor exhibited linear detection ranges of RIF between 1.0 × 10−11 mol L−1 and 1.0 × 10−6 mol L−1, with a detection limit of 3.3 × 10−12 mol L−1 (S/N = 3). The recoveries ranged between 98.1 and 106.0% in fish samples. This method can be used as a sensitive and rapid method to detect RIF in real samples.

Graphical Abstract

基于发光酚功能化 Co-MOF 的分子印迹电化学发光传感器用于检测利福平
基于 luminol@Co-MOF 开发了一种用于检测利福平(RIF)的高灵敏度分子印迹电化学发光(MIECL)传感器。在 luminol-O2 系统中,Co-MOF 可显著增强 ECL 信号。引入 RIF 的分子印迹聚合物(MIPs)为 RIF 的特异性识别提供了新的特性。随着 RIF 浓度的升高,ECL 强度明显降低。因此,ECL 信号受 RIF 从 MIP 中洗脱和 MIP 吸附的控制,从而建立了一种新的 RIF 检测方法。在最佳条件下,该传感器对 RIF 的线性检测范围为 1.0 × 10-11 mol L-1 至 1.0 × 10-6 mol L-1,检测限为 3.3 × 10-12 mol L-1(信噪比为 3)。在鱼类样品中的回收率为 98.1% 至 106.0%。该方法可用于灵敏、快速地检测实际样品中的 RIF。
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来源期刊
Microchimica Acta
Microchimica Acta 化学-分析化学
CiteScore
9.80
自引率
5.30%
发文量
410
审稿时长
2.7 months
期刊介绍: As a peer-reviewed journal for analytical sciences and technologies on the micro- and nanoscale, Microchimica Acta has established itself as a premier forum for truly novel approaches in chemical and biochemical analysis. Coverage includes methods and devices that provide expedient solutions to the most contemporary demands in this area. Examples are point-of-care technologies, wearable (bio)sensors, in-vivo-monitoring, micro/nanomotors and materials based on synthetic biology as well as biomedical imaging and targeting.
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