Suppr超能文献

基于电化学生物传感器标签的适体设计用于检测血清样本中的双酚 A。

Biosensor design using an electroactive label-based aptamer to detect bisphenol A in serum samples.

机构信息

Biosensor Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.

出版信息

J Biosci. 2019 Sep;44(4).

Abstract

A new and simple procedure was applied to detect bisphenol A (BPA) based on a BPA aptamer and its complementary strand (Comp. Str.). An electrode was modified with a mixture of carboxylated multiwalled carbon nanotubes and chitosan. The Comp. Str. was immobilized on a modified-glassy carbon electrode (GCE) surface via covalent binding. After the incubation of the aptamer with the electrode surface, it could interact with the Comp. Str. In the presence of BPA, its aptamer will interact with the analyte, resulting in some changes in the configuration and leading to separation from the electrode surface. Due to the attached ferrocene (Fc) group on the 50 head of the aptamer, the redox current of Fc has reduced. This aptasensor can sense the level of BPA in the linear range of 0.2-2 nM, with a limit of detection of 0.38 nM and a sensitivity of 24.51 lA/μM. The proposed aptasensor showed great reliability and selectivity. The acceptable selectivity is due to the specificity of BPA binding to its aptamer. The serum sample was used as a real sample; the aptasensor was able to effectively recover the spiked BPA amounts. It can on-site monitor the BPA in serum samples with acceptable recoveries.

摘要

一种新的简单方法被应用于检测双酚 A(BPA),该方法基于 BPA 适体及其互补链(Comp. Str.)。电极用羧基化多壁碳纳米管和壳聚糖的混合物修饰。Comp. Str.通过共价键固定在修饰的玻碳电极(GCE)表面上。在适体与电极表面孵育后,它可以与 Comp. Str.相互作用。在存在 BPA 的情况下,它的适体将与分析物相互作用,导致构象发生一些变化,并导致与电极表面分离。由于适体 50 端上附着的二茂铁(Fc)基团,Fc 的氧化还原电流减小。这种适体传感器可以在 0.2-2 nM 的线性范围内感应 BPA 的水平,检测限为 0.38 nM,灵敏度为 24.51 lA/μM。所提出的适体传感器具有很好的可靠性和选择性。可接受的选择性归因于 BPA 与其适体的特异性结合。血清样品被用作实际样品;适体传感器能够有效地回收添加的 BPA 量。它可以现场监测血清样品中的 BPA,回收率可接受。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验