Machine Learning-Assisted Chemical Tongues Based on Dual-channel Inclusion Complexes for Rapid Identification of Nonsteroidal Anti-inflammatory Drugs in Food

• DOI: 10.1021/acssensors.4c02806
• Publication Date: 2025-02-24T17:40:42Z
• Authors: Lian Xu; Yan Xiao; Kun Yu; Hongshuo Pan; Jiayi Xu; Yiyun Guan; Mengke Wang; Xiangyu Xu; Hao Wang
• Keywords: Identification; Anti-inflammatory

The improper application of nonsteroidal anti-inflammatory drugs (NSAIDs) presents significant health hazards via vector food contamination. A critical limitation these traditional existing approaches is their inability to concurrently discern and distinguish among diverse NSAIDs, presenting a notable gap in the analytical capabilities within this domain. Herein, creative dual-channel fluorescence sensor array was developed for rapid discrimination determination utilizing complexes cucurbit[8]uril (CB[8]) with three distinct modified poly(ethylenimines) (PEIs) address challenge. successfully differentiated identified 19 NSAIDs 97% accuracy at concentration 1 mM. In addition, it also achieved analyses individual across range concentrations, NSAID mixtures, impurities aspirin using statistical analysis methods. More importantly, approach effectively detected complex matrices, such as milk urine, demonstrating its potential real-world applications.