Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.22/6769
Título: Selective recognition in potentiometric transduction of amoxicillin by molecularly imprinted materials
Autor: Guerreiro, J. Rafaela L.
Sales, M. Goreti F.
Moreira, Felismina T. C.
Rebelo, Tânia S. C. R.
Palavras-chave: Amoxicillin
Molecularly imprinted sensors
Data: 2011
Editora: Springer
Resumo: The indiscriminate use of antibiotics in food-producing animals has received increasing attention as a contributory factor in the international emergence of antibiotic-resistant bacteria (Woodward in Pesticide, veterinary and other residues in food, CRC Press, Boca Raton, 2004). Numerous analytical methods for quantifying antibacterial residues in edible animal products have been developed over years (Woodward in Pesticide, veterinary and other residues in food, CRC Press, Boca Raton, 2004; Botsoglou and Fletouris in Handbook of food analysis, residues and other food component analysis, Marcel Dekker, Ghent, 2004). Being Amoxicillin (AMOX) one of those critical veterinary drugs, efforts have been made to develop simple and expeditious methods for its control in food samples. In literature, only one AMOX-selective electrode has been reported so far. In that work, phosphotungstate:amoxycillinium ion exchanger was used as electroactive material (Shoukry et al. in Electroanalysis 6:914–917, 1994). Designing new materials based on molecularly imprinted polymers (MIPs) which are complementary to the size and charge of AMOX could lead to very selective interactions, thus enhancing the selectivity of the sensing unit. AMOX-selective electrodes used imprinted polymers as electroactive materials having AMOX as target molecule to design a biomimetic imprinted cavity. Poly(vinyl chloride), sensors of methacrylic acid displayed Nernstian slopes (60.7 mV/decade) and low detection limits (2.9 × 10−5 mol/L). The potentiometric responses were not affected by pH within 4–5 and showed good selectivity. The electrodes were applied successfully to the analysis of real samples.
URI: http://hdl.handle.net/10400.22/6769
DOI: 10.1007/s00217-010-1360-1
Versão do Editor: http://link.springer.com/article/10.1007%2Fs00217-010-1360-1
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