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Updated: Mar 18, 2026

Quantification of Metal Leaching in Immobilized Metal Affinity Chromatography
Published on: January 17, 2020
A mini-review on functional nucleic acids-based heavy metal ion detection
Shenshan Zhan1, Yuangen Wu2, Lumei Wang3
1School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, PR China; School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai 200240, PR China; Key Laboratory of Urban Agriculture (South), Ministry of Agriculture, Shanghai 200240, PR China; Bor S. Luh Food Safety Research Center, Shanghai Jiao Tong University, Shanghai 200240, PR China.
Functional nucleic acid (FNA)-based sensors offer advanced heavy metal ion detection. This review details FNA types, lab-on-a-chip integration, and future directions for environmental monitoring.
Area of Science:
- Analytical Chemistry
- Biotechnology
- Environmental Science
Background:
- Functional nucleic acids (FNAs) are increasingly utilized for heavy metal ion detection.
- Existing reviews often focus on specific FNA types or applications.
- There is a need for a comprehensive overview of integrated FNA-based sensing systems.
Purpose of the Study:
- To review the main types of FNAs used for heavy metal ion detection.
- To detail lab-on-a-chip (LOC) platforms integrating FNAs for enhanced sensing.
- To discuss current challenges and future prospects in FNA-based heavy metal detection.
Main Methods:
- Literature review of recent publications on FNAs and heavy metal sensing.
- Categorization of FNAs based on their application in heavy metal detection.
- Classification of LOC systems incorporating FNAs into six distinct types.
Main Results:
- Four primary FNA types for heavy metal detection are identified.
- Six categories of integrated LOC systems (e.g., microfluidic, paper-based) are detailed.
- Sensing strategies, properties, advantages, and disadvantages of various FNA-based sensors are summarized.
Conclusions:
- FNA-based sensors, particularly integrated LOC systems, show significant promise for heavy metal detection.
- Further development is needed to address existing challenges and optimize performance.
- Future research should focus on improving automation, system integration, and real-world applicability.
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