Ammonia-Etched Laccase-Mimicking Nanofiber-like Enzyme with Fluorescent Properties for the Detection of Oxytetracyclin

A nanofiber-like enzyme, e-Cu-BN, was synthesized, exhibiting enhanced laccase-like activity compared to Cu-BN without ammonia etching. This study utilized the laccase-like activity and fluorescent properties of e-Cu-BN to develop a dual-mode fluorescence-colorimetric sensor for the detection of oxytetracycline (OTC). Specifically, e-Cu-BN catalyzes the oxidation of 2,4-dichlorophenol (2,4-DP), resulting in the formation of red quinone imine dye (QI) in conjunction with 4-aminophenol (4-AP), which exhibits strong UV absorption at 510 nm, while the OTC inhibits this reaction. Meanwhile, the fluorescence intensity of e-Cu-BN decreases as the concentration of OTC increases. Utilizing the two signal changes, we successfully achieved the detection of OTC. In addition, a smartphone-assisted hydrogel-based simple sensing platform was designed. The real-time detection of OTC was realized by the smartphone RGB value analysis software, and we added logic gates to simplify the detection process. This approach offers a rapid and cost-effective solution for OTC detection. This study not only developed a dual-mode sensor for OTC detection but also provided insights for further research into multifunctional nanozymes.

Authors

Institutions

Publication Details

Journal
ACS Applied Nano Materials
Published
2025-04-22
DOI
https://doi.org/10.1021/acsanm.5c00965
Citations
5
Primary Topic
Advanced Nanomaterials in Catalysis
Type
article
Field-Weighted Citation Impact
2.59

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Ammonia-Etched Laccase-Mimicking Nanofiber-like Enzyme with Fluorescent Properties for the Detection of Oxytetracyclin

Huizhu Fan, Junli Hong, Ling Dai, Jie Liu et al.
5 citations
ACS Applied Nano Materials
Advanced Nanomaterials in Catalysis
2.59
article

Ammonia-Etched Laccase-Mimicking Nanofiber-like Enzyme with Fluorescent Properties for the Detection of Oxytetracyclin

Huizhu Fan, Junli Hong, Ling Dai, Jie Liu, Zhiying Jiang, Luxi Huang, Yin Dai
article en
5 citations

Abstract

A nanofiber-like enzyme, e-Cu-BN, was synthesized, exhibiting enhanced laccase-like activity compared to Cu-BN without ammonia etching. This study utilized the laccase-like activity and fluorescent properties of e-Cu-BN to develop a dual-mode fluorescence-colorimetric sensor for the detection of oxytetracycline (OTC). Specifically, e-Cu-BN catalyzes the oxidation of 2,4-dichlorophenol (2,4-DP), resulting in the formation of red quinone imine dye (QI) in conjunction with 4-aminophenol (4-AP), which exhibits strong UV absorption at 510 nm, while the OTC inhibits this reaction. Meanwhile, the fluorescence intensity of e-Cu-BN decreases as the concentration of OTC increases. Utilizing the two signal changes, we successfully achieved the detection of OTC. In addition, a smartphone-assisted hydrogel-based simple sensing platform was designed. The real-time detection of OTC was realized by the smartphone RGB value analysis software, and we added logic gates to simplify the detection process. This approach offers a rapid and cost-effective solution for OTC detection. This study not only developed a dual-mode sensor for OTC detection but also provided insights for further research into multifunctional nanozymes.

ACS Applied Nano MaterialsVol. 8(17)
Nanjing Normal University (CN), Second Affiliated Hospital of Nanjing Medical University (CN), Nanjing Medical University (CN)
National Natural Science Foundation of China, China Postdoctoral Science Foundation, Nanjing Medical University
Openalex Percentile: Top 11%
Advanced Nanomaterials in Catalysis
2.59
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.