基于金纳米粒子修饰二硫化钼和透明质酸基硫氨酸的DR1的灵敏电化学检测

IF 4.1 Q2 CHEMISTRY, ANALYTICAL
Yaping Zhang, Gao Si, Zhendong Wang, Yilong Wang, Xiaojing Cui, Huaixia Yang, Fuchun Si and Yanjiu Liu
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引用次数: 0

摘要

转录下调因子1 (DR1)的分析为桥本甲状腺炎(HT)的快速、无创诊断提供了重要信息。在这项研究中,我们报道了一种新的双信号放大电化学生物传感器,用于灵敏检测DR1。纳米金(AuNP)修饰的二硫化钼(MoS2@AuNPs)具有极强的电子转移能力和丰富的结合位点,首先修饰在电极表面作为衬底材料,实现第一次信号放大。在形成基于抗原和抗体特异性识别的三明治结构后,引入电活性分子透明质酸基硫氨酸(HA@Thi),实现第二次信号放大。利用这种双信号放大策略,所提出的生物传感器的线性范围为1 × 10−4-1 × 102 ng mL−1,低检测限为10.99 fg mL−1。此外,电化学生物传感器具有高选择性和良好的稳定性,适用于复杂生物基质下的DR1检测,有望为血清DR1监测的临床应用提供科学的方法。更重要的是,我们的方法可以扩展基于蛋白质的生物传感器在疾病诊断技术中的应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Sensitive electrochemical detection of DR1 based on gold nanoparticle-modified MoS2 and hyaluronic acid-based thionine

Sensitive electrochemical detection of DR1 based on gold nanoparticle-modified MoS2 and hyaluronic acid-based thionine

The analysis of down-regulator of transcription 1 (DR1) offers significant information for the rapid and non-invasive diagnosis of Hashimoto's thyroiditis (HT). In this study, we report a novel dual-signal amplification electrochemical biosensor for the sensitive detection of DR1. Gold nanoparticle (AuNP)-modified molybdenum disulfide (MoS2@AuNPs), which has extremely strong electron transfer ability and abundant binding sites, is first modified on an electrode surface as a substrate material to implement the first signal amplification. After the formation of the sandwich structure based on the specific recognition of antigens and antibodies, the electroactive molecules hyaluronic acid-based thionine (HA@Thi) are introduced to achieve the second signal amplification. Using this dual-signal amplification strategy, the proposed biosensor achieves a linear range of 1 × 10−4–1 × 102 ng mL−1 with a low detection limit of 10.99 fg mL−1. In addition, the electrochemical biosensor has high selectivity and good stability, and is applicable to the assay of DR1 in the presence of complex biological matrices, which is expected to provide a scientific approach for the clinical application of serum DR1 monitoring. More importantly, our method may extend the application of protein-based biosensors in disease diagnosis techniques.

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