A Sensor Array Based on Molecularly Imprinted Polymers and Machine Learning for the Analysis of Fluoroquinolone Antibiotics
Wang, Mingyue (Universitat Autònoma de Barcelona. Departament de Química)
Cetó Alsedà, Xavier (Universitat Autònoma de Barcelona. Departament de Química)
Valle Zafra, Manuel del (Universitat Autònoma de Barcelona. Departament de Química)

Fecha:	2022
Resumen:	Fluoroquinolones (FQs) are one of the most important types of antibiotics in the clinical, poultry, and aquaculture industries, and their monitoring is required as the abuse has led to severe issues, such as antibiotic residues and antimicrobial resistance. In this study, we report a voltammetric electronic tongue (ET) for the simultaneous determination of ciprofloxacin, levofloxacin, and moxifloxacin in both pharmaceutical and biological samples. The ET comprises four sensors modified with three different customized molecularly imprinted polymers (MIPs) and a nonimprinted polymer integrated with Au nanoparticle-decorated multiwall carbon nanotubes (Au-fMWCNTs). MWCNTs were first functionalized to serve as a supporting substrate, while the anchored Au nanoparticles acted as a catalyst. Subsequently, MIP films were obtained by electropolymerization of pyrrole in the presence of the different target FQs. The sensors' morphology was characterized by scanning electron microscopy and transmission electron microscopy, while the modification process was followed electrochemically step by step employing [Fe(CN)] 3-/4- as the redox probe. Under the optimal conditions, the MIP(FQs)@Au-fMWCNT sensors exhibited different responses, limits of detection of ca. 1 μM, and a wide detection range up to 300 μM for the three FQs. Lastly, the developed ET presents satisfactory agreement between the expected and obtained values when used for the simultaneous determination of mixtures of the three FQs (R 2 ≥0. 960, testing subset), which was also applied to the analysis of FQs in commercial pharmaceuticals and spiked human urine samples.
Ayudas:	Ministerio de Ciencia e Innovación PID2019-107102RBC21
Derechos:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Lengua:	Anglès
Documento:	Article ; recerca ; Versió publicada
Materia:	Molecularly imprinted polymers ; Electronic tongues ; Artificial neural networks ; Fluoroquinolones ; Antibiotics ; Pharmaceutical analysis
Publicado en:	ACS Sensors, Vol. 7, Issue 11 (October 2022) , p. 3318-3325, ISSN 2379-3694

DOI: 10.1021/acssensors.2c01260
PMID: 36281963

8 p, 4.2 MB

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