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Updated: Jun 17, 2026

A Filter-based Surface Enhanced Raman Spectroscopic Assay for Rapid Detection of Chemical Contaminants
Published on: February 19, 2016
Target-Responsive Metal-Organic Framework Nanosystem with Synergetic Sensitive Detection and Controllable Degradation
Jintong Liu1,2, Yan Yang Mo1, Heng Zhang1
1Jiangsu Key Laboratory of Pesticide Science, College of Sciences, Nanjing Agricultural University, Nanjing 210095, China.
Abstract:
Developing sensitive practical sensors for monitoring pesticide residues in edible foods and environmental samples is vital for food safety and environmental protection. Enzyme-inhibited biosensors offer effective alternative sensing strategies by using the inherent characteristics of pesticides. To further improve the degradation function of pesticide sensors, here, a target-triggered porphyrin metal-organic framework (MOF)-based nanosystem was designed with the synergetic bifunction of sensitive detection and controllable degradation of the triazophos pesticide. As a result of triazophos-inhibited glutathione consumption, the MOF collapsed and released the ligand porphyrin, leading to the recovery of fluorescence and photosensitization of the free porphyrin. The fluorescence recovery resulted in a sensitive detection limit of 0.6 ng mL-1 for triazophos, which was also applied for the determination of contaminated samples and bioaccumulation in rice. Furthermore, the target-activated photocatalytic ability of porphyrin endowed the system with the ability to effectively generate reactive oxygen species for degrading triazophos with a removal rate of ∼85%, achieving eco-friendly synergetic detection and photodegradation in a controllable way. Therefore, the intelligent multifunctional MOF system demonstrated the potential of programmable systems for jointly controllable tracking and elimination of pesticide residues in the environment and opened a new avenue for designing a precise mechanism for stimulus-triggered degradation of pesticide residues accompanied by sensitive detection for environmental friendliness and food safety.
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