Related Experiment Video
Updated: Jun 23, 2026
10:42
Bioorthogonal Chemical Imaging of Cell Metabolism Regulated by Aromatic Amino Acids
Published on: May 12, 2023
An Intelligent Sensing Paradigm Enabled by Phosphate-Regulated Nanozyme Activation and Machine Learning for
Junlei Liu1, Kaiqiang Yang1, Wenyan Zhang1
1School of Materials Science and Chemical Engineering, Ningbo University, Ningbo 315211, China.
Analytical Chemistry
|June 22, 2026
Summary
This study reactivates nanozymes for biosensing at neutral pH using phosphorylated metabolites. This enables accurate, machine learning-driven detection of antioxidants in supplements and biological samples.
Area of Science:
- Biomaterials Science
- Nanotechnology
- Analytical Chemistry
Background:
- Nanozymes with oxidase-like activity are promising for biosensing.
- Their catalytic efficiency is limited at neutral pH.
- Reactivation strategies are needed for practical applications.
Purpose of the Study:
- To develop a strategy for reactivating Ce-MOF nanozymes at neutral pH.
- To create a multi-analyte sensor for structurally similar antioxidants.
- To implement machine learning for concentration-independent analysis.
Main Methods:
- Utilized endogenous phosphorylated metabolites (ATP, CTP, GTP) to modulate Ce-MOF nanozymes.
- Constructed a triple-channel colorimetric sensor array.
- Employed a two-step machine learning framework (KNN and LDA) for data analysis.
Main Results:
- Phosphate coordination restored nanozyme activity by tuning Ce3+/Ce4+ ratio and superoxide generation.
- The sensor array discriminated and quantified seven antioxidants (0.140–1.91 μM detection limits).
- Machine learning achieved 98.1% accuracy for qualitative recognition and accurate quantification in real samples.
Conclusions:
- Developed an adaptive nanozyme engineering strategy.
- Established an intelligent sensing platform for complex sample analysis under neutral conditions.
- Demonstrated successful application in health supplements and biological fluid analysis.