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Fullerenol Quantum Dots-Based Highly Sensitive Fluorescence Aptasensor for Patulin in Apple Juice
Hua Pang1,2,3, Hui Li1,2,3,4,5, Wen Zhang1,2,3,4,5
1Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan 430062, China.
Toxins
|April 21, 2022
Summary
A novel aptasensor effectively detects patulin (PAT) using fullerenol quantum dots and TAMRA fluorescence quenching. This method offers high sensitivity and selectivity for food safety analysis.
Area of Science:
- Nanotechnology
- Biosensors
- Analytical Chemistry
Background:
- Patulin (PAT) is a mycotoxin found in foods, posing health risks.
- Accurate detection of PAT is crucial for food safety and quality control.
- Existing detection methods may lack sensitivity, selectivity, or require complex procedures.
Purpose of the Study:
- To develop a highly selective and sensitive aptasensor for patulin detection.
- To utilize the fluorescence quenching properties of fullerenol quantum dots (FOQDs) and TAMRA.
- To establish a reliable method for patulin quantification in food samples.
Main Methods:
- Construction of an aptasensor based on FOQDs and a patulin-specific aptamer labeled with TAMRA.
- Exploitation of the photoinduced electron transfer (PET) mechanism for fluorescence quenching.
- Investigation of π-π stacking interactions between the aptamer and FOQDs for signal modulation.
- Validation of the aptasensor in apple juice samples.
Main Results:
- The aptasensor exhibited high sensitivity and selectivity for patulin detection.
- A linear correlation was observed between fluorescence recovery and patulin concentration (0.02-1 ng/mL) with a detection limit of 0.01 ng/mL.
- The aptasensor demonstrated effective performance in apple juice samples within a linear dynamic range of 0.05-1 ng/mL.
- Maximum fluorescence quenching efficiency reached 85% without non-specific quenching.
Conclusions:
- The developed FOQD-based aptasensor provides a sensitive and selective platform for patulin detection.
- The homogeneous fluorescence assay shows promise for real-time monitoring of food contaminants.
- This approach has broad applicability for detecting various food pollutants.

