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The accurate detection of blood glucose is of critical importance in the diagnosis and management of diabetes and its complications. Herein, we report a novel strategy based on an upconversion nanoparticles-polydopamine (UCNPs-PDA) nanosystem for the accurate detection of glucose in human serum and whole blood through a simple blending of test samples with ligand-free UCNPs, dopamine, and glucose oxidase (GOx). Owing to the high affinity of lanthanide ions exposed on the surface of ligand-free UCNPs, dopamine monomers could spontaneously attach to the UCNPs and further polymerize to form a PDA shell, resulting in a remarkable upconversion luminescence (UCL) quenching (97.4%) of UCNPs under 980-nm excitation. Such UCL quenching can be effectively inhibited by H2O2 produced from the GOx/glucose enzymatic reaction, thus enabling the detection of H2O2 or glucose based on the UCL quenching/inhibition bioassay. Owing to the highly sensitive UCL response and background-free interference of the UCNPs-PDA nanosystem, we achieved a sensitive, selective, and high-throughput bioassay for glucose in human serum and whole blood, thereby revealing the great potential of the UCNPs-PDA nanosystem for the accurate detection of blood glucose or other H2O2-generated biomolecules in clinical bioassays.

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Publication history
Copyright
Acknowledgements

Publication history

Received: 17 April 2017
Revised: 02 June 2017
Accepted: 10 June 2017
Published: 22 May 2018
Issue date: June 2018

Copyright

© Tsinghua University Press and Springer-Verlag Berlin Heidelberg 2017

Acknowledgements

Acknowledgements

This work is supported by the National Basic Research Program of China (973 Program) (No. 2014CB845605), the National Natural Science Foundation of China (NSFC) (Nos. U1305244, 21325104, 51402294 and 21501180), the CAS/SAFEA International Partnership Program for Creative Research Teams, Strategic Priority Research Program of the CAS (Nos. XDA09030307 and XDB20000000), the Youth Innovation Promotion Association (No. 2016277) and the Chunmiao Project of Haixi Institute of the CAS (No. CMZX-2016-002), and the Natural Science Foundation of Fujian Province (Nos. 2015J05116, 2017J05095, 2017J01105 and 2017I0018).

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