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Registro Completo |
Biblioteca(s): |
Embrapa Gado de Leite; Embrapa Instrumentação. |
Data corrente: |
06/06/2023 |
Data da última atualização: |
06/06/2023 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Autoria: |
SOARES, A. C.; SOARES, J. C.; SANTOS, D. M. dos; MIGLIORINI, F. L.; POPOLIN-NETO, M.; PINTO, D. dos S. C.; CARVALHO, W. A.; BRANDAO, H. de M.; PAULOVICH, F. V.; CORREA, D. S.; OLIVEIRA JUNIOR, O. N.; MATTOSO, L. H. C. |
Afiliação: |
ANDREY COATRINI SOARES; JULIANA COATRINI SOARES, Universidade de São Paulo; DANILO MARTINS DOS SANTOS; FERNANDA L. MIGLIORINI; MARIO POPOLIN-NETO, Instituto Federal de Educação, Ciência e Tecnologia de São Paulo; DANIELLE DOS SANTOS CINELLI PINTO; WANESSA ARAUJO CARVALHO, CNPGL; HUMBERTO DE MELLO BRANDAO, CNPGL; FERNANDO VIEIRA PAULOVICH, Eindhoven University of Technology; DANIEL SOUZA CORREA, CNPDIA; OSVALDO N. OLIVEIRA JUNIOR, Universidade de São Paulo; LUIZ HENRIQUE CAPPARELLI MATTOSO, CNPDIA. |
Título: |
Nanoarchitectonic E-tongue of electrospun zein/curcumin carbon dots for detecting Staphylococcus aureus in milk. |
Ano de publicação: |
2023 |
Fonte/Imprenta: |
ACS Omega, v. 8, n. 15, p. 13721-13732, 2023. |
DOI: |
https://doi.org/10.1021/acsomega.2c07944?urlappend=%3Fref%3DPDF&jav=VoR&rel=cite-as |
Idioma: |
Inglês |
Conteúdo: |
We report a nanoarchitectonic electronic tongue made with flexible electrodes coated with curcumin carbon dots and zein electrospun nanofibers, which could detect Staphylococcus aureus(S. aureus) in milk using electrical impedance spectroscopy. Electronic tongues are based on the global selectivity concept in which the electrical responses of distinct sensing units are combined to provide a unique pattern, which in this case allowed the detection of S. aureus through non-specific interactions. The electronic tongue used here comprised 3 sensors with electrodes coated with zein nanofibers, carbon dots, and carbon dots with zein nanofibers. The capacitance data obtained with the three sensors were processed with a multidimensional projection technique referred to as interactive document mapping (IDMAP) and analyzed using the machine learning-based concept of multidimensional calibration space (MCS). The concentration of S. aureus could be determined with the sensing units, especially with the one containing zein as the limit of detection was 0.83 CFU/mL (CFU stands for colony-forming unit). This high sensitivity is attributed to molecular-level interactions between the protein zein and C?H groups in S. aureus according to polarization-modulated infrared reflection-absorption spectroscopy (PM-IRRAS) data. Using machine learning and IDMAP, we demonstrated the selectivity of the electronic tongue in distinguishing milk samples from mastitis-infected cows from milk collected from healthy cows, and from milk spiked with possible interferents. Calibration of the electronic tongue can also be reached with the MCS concept employing decision tree algorithms, with an 80.1% accuracy in the diagnosis of mastitis. The low-cost electronic tongue presented here may be exploited in diagnosing mastitis at early stages, with tests performed in the farms without requiring specialized laboratories or personnel. MenosWe report a nanoarchitectonic electronic tongue made with flexible electrodes coated with curcumin carbon dots and zein electrospun nanofibers, which could detect Staphylococcus aureus(S. aureus) in milk using electrical impedance spectroscopy. Electronic tongues are based on the global selectivity concept in which the electrical responses of distinct sensing units are combined to provide a unique pattern, which in this case allowed the detection of S. aureus through non-specific interactions. The electronic tongue used here comprised 3 sensors with electrodes coated with zein nanofibers, carbon dots, and carbon dots with zein nanofibers. The capacitance data obtained with the three sensors were processed with a multidimensional projection technique referred to as interactive document mapping (IDMAP) and analyzed using the machine learning-based concept of multidimensional calibration space (MCS). The concentration of S. aureus could be determined with the sensing units, especially with the one containing zein as the limit of detection was 0.83 CFU/mL (CFU stands for colony-forming unit). This high sensitivity is attributed to molecular-level interactions between the protein zein and C?H groups in S. aureus according to polarization-modulated infrared reflection-absorption spectroscopy (PM-IRRAS) data. Using machine learning and IDMAP, we demonstrated the selectivity of the electronic tongue in distinguishing milk samples from mastitis-infected cows from milk collected from ... Mostrar Tudo |
Palavras-Chave: |
Calibração; Doença infecciosa; Nanofibra; Produto lácteo; Propriedade elétrica. |
Thesagro: |
Bactéria; Leite; Produto Derivado do Leite; Zeína. |
Thesaurus Nal: |
Beverages; Calibration; Dairy products; Electrical properties; Infectious diseases. |
Categoria do assunto: |
L Ciência Animal e Produtos de Origem Animal |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/doc/1154290/1/Nanoarchitectonic-E8209tongue-of-electrospun-zein-curcumin-carbon.pdf
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Marc: |
LEADER 03232naa a2200433 a 4500 001 2154290 005 2023-06-06 008 2023 bl uuuu u00u1 u #d 024 7 $ahttps://doi.org/10.1021/acsomega.2c07944?urlappend=%3Fref%3DPDF&jav=VoR&rel=cite-as$2DOI 100 1 $aSOARES, A. C. 245 $aNanoarchitectonic E-tongue of electrospun zein/curcumin carbon dots for detecting Staphylococcus aureus in milk.$h[electronic resource] 260 $c2023 520 $aWe report a nanoarchitectonic electronic tongue made with flexible electrodes coated with curcumin carbon dots and zein electrospun nanofibers, which could detect Staphylococcus aureus(S. aureus) in milk using electrical impedance spectroscopy. Electronic tongues are based on the global selectivity concept in which the electrical responses of distinct sensing units are combined to provide a unique pattern, which in this case allowed the detection of S. aureus through non-specific interactions. The electronic tongue used here comprised 3 sensors with electrodes coated with zein nanofibers, carbon dots, and carbon dots with zein nanofibers. The capacitance data obtained with the three sensors were processed with a multidimensional projection technique referred to as interactive document mapping (IDMAP) and analyzed using the machine learning-based concept of multidimensional calibration space (MCS). The concentration of S. aureus could be determined with the sensing units, especially with the one containing zein as the limit of detection was 0.83 CFU/mL (CFU stands for colony-forming unit). This high sensitivity is attributed to molecular-level interactions between the protein zein and C?H groups in S. aureus according to polarization-modulated infrared reflection-absorption spectroscopy (PM-IRRAS) data. Using machine learning and IDMAP, we demonstrated the selectivity of the electronic tongue in distinguishing milk samples from mastitis-infected cows from milk collected from healthy cows, and from milk spiked with possible interferents. Calibration of the electronic tongue can also be reached with the MCS concept employing decision tree algorithms, with an 80.1% accuracy in the diagnosis of mastitis. The low-cost electronic tongue presented here may be exploited in diagnosing mastitis at early stages, with tests performed in the farms without requiring specialized laboratories or personnel. 650 $aBeverages 650 $aCalibration 650 $aDairy products 650 $aElectrical properties 650 $aInfectious diseases 650 $aBactéria 650 $aLeite 650 $aProduto Derivado do Leite 650 $aZeína 653 $aCalibração 653 $aDoença infecciosa 653 $aNanofibra 653 $aProduto lácteo 653 $aPropriedade elétrica 700 1 $aSOARES, J. C. 700 1 $aSANTOS, D. M. dos 700 1 $aMIGLIORINI, F. L. 700 1 $aPOPOLIN-NETO, M. 700 1 $aPINTO, D. dos S. C. 700 1 $aCARVALHO, W. A. 700 1 $aBRANDAO, H. de M. 700 1 $aPAULOVICH, F. V. 700 1 $aCORREA, D. S. 700 1 $aOLIVEIRA JUNIOR, O. N. 700 1 $aMATTOSO, L. H. C. 773 $tACS Omega$gv. 8, n. 15, p. 13721-13732, 2023.
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Registro original: |
Embrapa Gado de Leite (CNPGL) |
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