Issue 19, 2023

A bimetallic metal–organic framework with high enzyme-mimicking activity for an integrated electrochemical immunoassay of carcinoembryonic antigen

Abstract

Metal–organic frameworks (MOFs) show excellent catalytic activity and have been widely applied in diagnosis of diseases and tumors. However, current assay methods usually involve cumbersome configurations and complicated procedures, which inhibit their practical applications. Hence, a Cu–Ni MOF/carbon printed electrode (CPE)-based integrated electrochemical immunosensor was constructed for highly sensitive and efficient determination of carcinoembryonic antigen (CEA). First, highly conductive carbon ink was screen-printed onto a polyethylene terephthalate substrate to manufacture a CPE. Afterward, an aminated Cu-Ni MOF was prepared by a typical solvothermal strategy and modified on the CPE. Owing to its excellent peroxidase activity, the Cu–Ni MOF can catalytically oxidize hydroquinone using hydrogen peroxide, which greatly amplifies the peak current signal. Then the formation of an immune complex inhibited the catalytic activity of the MOF, thus enabling the quantitative determination of CEA content with a wide linear range of 0.5 pg mL−1–500 ng mL−1 and a low detection limit of 0.16 pg mL−1. Furthermore, the Cu–Ni MOF/CPE-based integrated portable electrochemical immunosensor also showed satisfactory performance in the detection of CEA in clinical serum samples with excellent accuracy, showing great potential for application in point-of-care disease diagnosis.

Graphical abstract: A bimetallic metal–organic framework with high enzyme-mimicking activity for an integrated electrochemical immunoassay of carcinoembryonic antigen

Supplementary files

Article information

Article type
Paper
Submitted
18 júl 2023
Accepted
11 aug 2023
First published
11 aug 2023

Analyst, 2023,148, 4721-4729

A bimetallic metal–organic framework with high enzyme-mimicking activity for an integrated electrochemical immunoassay of carcinoembryonic antigen

Y. Shu, L. Yan, M. Ye, L. Chen, Q. Xu and X. Hu, Analyst, 2023, 148, 4721 DOI: 10.1039/D3AN01221B

To request permission to reproduce material from this article, please go to the Copyright Clearance Center request page.

If you are an author contributing to an RSC publication, you do not need to request permission provided correct acknowledgement is given.

If you are the author of this article, you do not need to request permission to reproduce figures and diagrams provided correct acknowledgement is given. If you want to reproduce the whole article in a third-party publication (excluding your thesis/dissertation for which permission is not required) please go to the Copyright Clearance Center request page.

Read more about how to correctly acknowledge RSC content.

Social activity

Spotlight

Advertisements