Liposome-encapsulated aggregation-induced emission fluorogen assisted with portable smartphone for dynamically on-site imaging of residual tetracycline

作者：Shen, Yizhong^*; Wei, Yunlong; Chen, Huanhuan; Wu, Zeyu; Ye, Yingwang^*; Han, De-Man^*

来源：Sensors and Actuators, B: Chemical , 2022, 350: 130871.

DOI：10.1016/j.snb.2021.130871

• Antibiotic residue
• Aggregation-induced emission fluorogen
• Ratiometric fluorescent
• Liposome
• On-site assay

Reliable on-site monitoring of antibiotic residue is critical to establish the efficient pollution early-warning mechanism for ensuring food safety and environmental health. Herein, we reported the engineering of liposome-encapsulated aggregation-induced emission fluorogen into the portable smartphone for achieving the visual on-site detection of residual tetracycline (TC). Through nanoprecipitation, the aggregation-induced emission fluorogen (AlEgen) tetraphenylethene (TPE) was encapsulated into an amphiphilic phospholipid polymer, affording a scaffold to assemble Eu3+ for forming Eu3+-functionalized liposome-based AlEgen (Eu3+@AIEgen) with bright blue fluorescence at similar to 456 nm. Upon assistance of citrate, TC was capable of triggering the remarkable fluorescence color change from bright blue (similar to 456 nm) to pink owing to the new red fluorescence emission appeared at similar to 611 nm, thereby emerging a significant dual-emission for ratiometric response. As expected, an ingenious citrate-assisted Eu3+@AIEgen liposome-based smartphone was proposed to precisely on-site report the residual levels of TC in real sample among the linear range of 0.0961-10.0 mu M. Furthermore, this portable sensor exhibited a high sensitivity attributable to the low detection limit of 28.83 nM together with a fast response kinetics of 2.0 min for TC, agreeing well with the demands of on-site assay. This study showed the promising potential for utilizing AIEgen liposome to develop a new category of portable sensors for the point-of-care detection of antibiotic residue in complicated food and environment-related matrixes, which might open a novel way to establish efficient pollution early-warning mechanism for safeguarding public health.