Highly Selective Detection of Paraoxon in Food Based on the Platform of Cu Nanocluster/MnO2 Nanosheets
- PMID: 35564138
- PMCID: PMC9100620
- DOI: 10.3390/nano12091429
Highly Selective Detection of Paraoxon in Food Based on the Platform of Cu Nanocluster/MnO2 Nanosheets
Abstract
Selective and sensitive identification of paraoxon residue in agricultural products is greatly significant for food safety but remains a challenging task. Herein, a detection platform was developed by integrating Cu nanoclusters (Cu NCs) with MnO2 nanosheets, where the fluorescence of Cu NCs was effectively quenched. Upon introducing butyrylcholinesterase and butyrylcholine into the system, their hydrolysate, thiocholine, leads to the decomposition of the platform through a reaction between the MnO2 nanosheets and thiol groups on thiocholine. The electron-rich groups on thiocholine can further promote the fluorescence intensity of Cu NCs through host-guest interactions. Adding paraoxon results in the failure of fluorescence recovery and further promotion, which could be utilized for the quantitative detection of paraoxon, and a limit of detection as low as 0.22 ng/mL can be achieved. The detection platform shows strong tolerance to common interference species, which endows its applications for the detection of paraoxon in vegetables and fruit. These presented results not only open a new door for the functionalization of metal nanoclusters but also offer an inspiring strategy for analytic techniques in nanomedicine and environmental science.
Keywords: MnO2 nanosheets; fluorescence quenching; fluorometry assay; metal nanoclusters; organophosphorus pesticides.
Conflict of interest statement
The authors declare no conflict of interest.
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Grants and funding
- 22007027/National Natural Science Foundation of China
- B2021201038/Science Fund for Creative Research Groups of Nature Science Foundation of Hebei Prov-ince
- B2020201060/he Outstanding Youth Project of Natural Science Foundation of Hebei Province
- E2019050011/One Hundred Talent Project of Hebei Province
- BJ2020033/Science and Technology Project of Hebei Education Department
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