标题:CuS as co-reaction accelerator in PTCA-K2S2O8 system for enhancing electrochemiluminescence behavior of PTCA and its application in detection of amyloid-beta protein
作者:Song, Xianzhen; Li, Xiaojian; Wei, Dong; Feng, Rui; Yan, Tao; Wang, Yaoguang; Ren, Xiang; Du, Bin; Ma, Hongmin; Wei, Qin
作者机构:[Song, Xianzhen; Li, Xiaojian; Wei, Dong; Feng, Rui; Yan, Tao; Wang, Yaoguang; Ren, Xiang; Du, Bin; Ma, Hongmin; Wei, Qin] Univ Jinan, Univ Shandong, 更多
通讯作者:Ma, HM
通讯作者地址:[Ma, HM]Univ Jinan, Univ Shandong, Sch Chem & Chem Engn, Key Lab Interfacial React & Sensing Anal, Jinan 250022, Shandong, Peoples R China.
来源:BIOSENSORS & BIOELECTRONICS
出版年:2019
卷:126
页码:222-229
DOI:10.1016/j.bios.2018.10.068
关键词:PICA; CuS; Co-reaction accelerator; Amyloid-beta protein
摘要:In this work, 3,4,9,10-perylenetetracar-boxylic acid (PTCA) as luminophor was grafted on the surface of graphene oxide (PTCA-GO) directly. GO exhibited large specific surface area and excellent electrical conductivity which can immobilize large amounts of PTCA to improve the electrochemiluminescence (ECL) efficiency. Moreover, gold nanoparticles (Au NPs) were anchored on the surface of PTCA-GO to immobilize primary antibodies (Ab(1)) via Au-NH2 bond and enhance the electron transport of PTCA-GO. CuS was used as a novel co-reaction accelerator in PTCA-K2S2O8 system to label secondary antibodies (Ab(2)), which can react with the coreactant (K2S2O8) to produce more SO4 center dot-, SiO2 nanospheres with large specific surface area were used to load a mass of CuS and Au NPs, which can directly combine with Ab(2) and accelerate the ECL emission remarkably. Therefore, a novel sandwich-type ECL immunosensor was fabricated successfully for amyloid-beta protein (A beta) detection. Under the optimal condition, a wide detection range from 50 fg/mL to 25 ng/mL and a low detection limit of 18 fg/mL (S/N = 3) were obtained. Featuring favorable specificity, stability and reproducibility, the strategy can be a powerful analytical tool in sensitive trace detection of biomolecules in clinical analysis.
收录类别:SCIE
资源类型:期刊论文
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