标题:A novel ultrasensitive sandwich-type photoelectrochemical immunoassay for PSA detection based on dual inhibition effect of Au/MWCNTs nanohybrids on N-GQDs/CdS QDs dual sensitized urchin-like TiO2
作者:Sun, Xiaokai ;Li, Canguo ;Zhu, Qiying ;Chen, Jie ;Li, Jiangtao ;Ding, Hengle ;Sang, Feng ;Kong, Ling ;Chen, Zhiwei ;Wei, Qin
作者机构:[Sun, Xiaokai ;Li, Canguo ;Zhu, Qiying ;Chen, Jie ;Li, Jiangtao ;Ding, Hengle ;Sang, Feng ;Kong, Ling ] School of Life Sciences, Shandong University o 更多
通讯作者:Kong, Ling
来源:Electrochimica Acta
出版年:2020
卷:333
DOI:10.1016/j.electacta.2019.135480
摘要:An ultrasensitive sandwich-type photoelectrochemical immunosensor (PEC) was designed successfully for the quantify detection of prostate specific antigen (PSA). Here, urchin-like TiO2, which was dual sensitized by N-doped graphene quantum dots (N-GQDs) and CdS quantum dots (QDs), were fixed on the surface of ITO electrode and produced a significant photocurrent signal. The TiO2/N-GQDs/CdS QDs composite was not only could use as an excellent photoactive substrate but also could provide abundant functional group to immobilized PSA antibodies (Ab1). Using Au/MWCNTs nanohybrids as the label of the secondary antibody (Ab2), Au nanoparticles (NPs) and CdS QDs generated excition-plasmon interactions, and Au NPs produced surface plasmon resonance under photoexcitation. Meanwhile along with the energy transfer process, the photocurrent was inhibited which results in an increase in the sensitivity of the immunosensor. In addition, the loading amount of the labeled Ab2 could be increased due to the large surface area of Au/MWCNTs, the photocurrent signal was further reduced after the specific immune recognition. Under the optimal performance, the sandwich immunosensor proved an ideal linear relationship ranging from 0.1 pg/mL to 50 ng/mL and the detection limit was 6.16 fg/mL with good sensitivity and stability, which provided a promising PEC platform and valuable referential idea for the detection of other trace tumor markers.
© 2019 Elsevier Ltd
收录类别:EI
资源类型:期刊论文
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