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Progress in quantum dot-based biosensors for microRNA assay: A review
Wen-Jing Liu1, Li-Juan Wang1, Chun-Yang Zhang1
1School of Chemistry and Chemical Engineering, Southeast University, Nanjing, 211189, China.
Analytica Chimica Acta
|September 14, 2023
Summary
Quantum dots (QDs) offer advanced biosensor technology for microRNA (miRNA) detection, crucial for disease diagnosis. This review details QD-based biosensors for sensitive miRNA analysis, covering various signal outputs and future prospects.
Area of Science:
- Biomedical Engineering
- Nanoscience
- Molecular Biology
Background:
- MicroRNAs (miRNAs) are key regulators of gene expression and potential disease biomarkers.
- Accurate and sensitive detection of miRNAs is critical for diagnostics.
- Quantum dots (QDs) possess unique optoelectronic properties making them suitable for biosensing applications.
Purpose of the Study:
- To provide a comprehensive review of Quantum Dot (QD)-based biosensors for microRNA (miRNA) detection.
- To classify QD-based miRNA biosensors based on their signal output types.
- To highlight the performance, challenges, and future directions in QD-based miRNA assay development.
Main Methods:
- Review of existing literature on QD-based biosensors for miRNA detection.
- Classification of biosensors by signal transduction mechanisms: fluorescent, electrochemical, electrochemiluminescent, and photoelectrochemical.
- Analysis of the features, principles, and reported performances of various QD-based miRNA assays.
Main Results:
- QD-based biosensors demonstrate high sensitivity and specificity for miRNA detection.
- Diverse signal outputs (fluorescent, electrochemical, etc.) offer flexibility in assay design.
- QD properties like brightness and photostability enhance biosensor performance.
Conclusions:
- QD-based biosensors represent a promising platform for sensitive and accurate miRNA analysis.
- Further research is needed to address challenges and optimize performance for clinical applications.
- This review provides a valuable resource for understanding the current landscape and future potential of QD-based miRNA detection.

