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Enzymatically activated reduction-caged SERS reporters for versatile bioassays.
Wenjing Guo1, Yihui Hu, Hui Wei
1Department of Biomedical Engineering, College of Engineering and Applied Sciences, Collaborative Innovation Center of Chemistry for Life Sciences, Nanjing National Laboratory of Microstructures, Nanjing University, Nanjing, Jiangsu 210093, China. weihui@nju.edu.cn.
Researchers developed a new method to activate Raman reporters using peroxidases for surface-enhanced Raman scattering (SERS) bioassays. This enables sensitive detection of small molecules and C-reactive protein (CRP) for disease diagnostics.
Area of Science:
- Biochemistry
- Analytical Chemistry
- Materials Science
Background:
- Surface-enhanced Raman scattering (SERS) offers high sensitivity for molecular detection.
- Activation of caged Raman reporters is crucial for developing SERS-based bioassays.
- Peroxidases are enzymes that can be utilized for triggering chemical reactions.
Purpose of the Study:
- To develop a facile strategy for activating reduction caged Raman reporters using peroxidases for SERS.
- To create versatile bioassays for detecting bioactive small molecules.
- To establish an immunoassay for C-reactive protein (CRP) as a cardiovascular disease biomarker.
Main Methods:
- Selection of appropriate caged Raman reporters.
- Enzymatic activation of reporters using peroxidases.
- Development of SERS-based bioassays for small molecules.
- Development of a SERS-based immunoassay for CRP detection.
Main Results:
- A facile strategy for activating caged Raman reporters with peroxidases was successfully established.
- Versatile bioassays for detecting bioactive small molecules were developed using the SERS approach.
- A sensitive immunoassay for C-reactive protein (CRP) was demonstrated, showing potential for disease biomarker detection.
Conclusions:
- The developed strategy provides a robust platform for SERS-based bioanalysis.
- This method enables sensitive and specific detection of analytes, including disease biomarkers.
- The approach holds promise for advancing diagnostic tools in clinical applications.
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