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Registro Completo |
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Biblioteca(s): |
Embrapa Instrumentação. |
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Data corrente: |
24/03/2022 |
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Data da última atualização: |
23/01/2024 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
SOARES, J. C.; SOARES, A. C.; POPOLIN-NETO, M.; PAULOVICH, F. V.; OLIVEIRA JR, O. N.; MATTOSO, L. H. C. |
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Afiliação: |
LUIZ HENRIQUE CAPPARELLI MATTOSO, CNPDIA. |
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Título: |
Detection of Staphylococcus aureus in milk samples using impedance spectroscopy and data processing with information visualization techniques and multidimensional calibration space. |
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Ano de publicação: |
2022 |
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Fonte/Imprenta: |
Sensors and Actuators Reports, v. 4, 100083, 2022. |
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Páginas: |
10 p. |
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ISSN: |
2666-0539 |
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DOI: |
https://doi.org/10.1016/j.snr.2022.100083 |
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Idioma: |
Inglês |
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Conteúdo: |
Early diagnosis of cattle diseases such as mastitis caused by Staphylococcus aureus (S. aureus) can be made effective if on-site detection methods with portable instruments are available. In this work, we fabricated immunosensors based on a layer-by-layer (LbL) film of chitosan and carbon nanotubes coated with a layer of antibodies to detect S. aureus. Using electrical and electrochemical impedance spectroscopies, detection was possible in buffer solutions and in milk with limits of detection which could be as low as 2.6 CFU/mL for milk,sufficient to detect mastitis at early stages. This high sensitivity is ascribed to the specific interactions involving the antibodies, as demonstrated with polarization-modulated infrared reflection absorption spectroscopy (PMIRRAS). The selectivity of the immunosensor was verified by distinguishing S. aureus-containing samples from possible interferents found in milk, for which the interactive document mapping (IDMAP) was employed.Because the interferents affected the spectra, in spite of this distinguishability, we treated the data with a machine learning technique with decision tree models. A multidimensional calibration space was then obtained with rules that permit interpretability and predictability in detecting S. aureus in matrices with high variability as in milk. |
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Palavras-Chave: |
Immunosensor; Machine learning; Nanostructured film. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/232884/1/P-Detection-of-Staphylococcus-aureus-in-milk-samples-using-impedance.pdf
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Marc: |
LEADER 02179naa a2200253 a 4500
001 2141236
005 2024-01-23
008 2022 bl uuuu u00u1 u #d
022 $a2666-0539
024 7 $ahttps://doi.org/10.1016/j.snr.2022.100083$2DOI
100 1 $aSOARES, J. C.
245 $aDetection of Staphylococcus aureus in milk samples using impedance spectroscopy and data processing with information visualization techniques and multidimensional calibration space.$h[electronic resource]
260 $c2022
300 $a10 p.
520 $aEarly diagnosis of cattle diseases such as mastitis caused by Staphylococcus aureus (S. aureus) can be made effective if on-site detection methods with portable instruments are available. In this work, we fabricated immunosensors based on a layer-by-layer (LbL) film of chitosan and carbon nanotubes coated with a layer of antibodies to detect S. aureus. Using electrical and electrochemical impedance spectroscopies, detection was possible in buffer solutions and in milk with limits of detection which could be as low as 2.6 CFU/mL for milk,sufficient to detect mastitis at early stages. This high sensitivity is ascribed to the specific interactions involving the antibodies, as demonstrated with polarization-modulated infrared reflection absorption spectroscopy (PMIRRAS). The selectivity of the immunosensor was verified by distinguishing S. aureus-containing samples from possible interferents found in milk, for which the interactive document mapping (IDMAP) was employed.Because the interferents affected the spectra, in spite of this distinguishability, we treated the data with a machine learning technique with decision tree models. A multidimensional calibration space was then obtained with rules that permit interpretability and predictability in detecting S. aureus in matrices with high variability as in milk.
653 $aImmunosensor
653 $aMachine learning
653 $aNanostructured film
700 1 $aSOARES, A. C.
700 1 $aPOPOLIN-NETO, M.
700 1 $aPAULOVICH, F. V.
700 1 $aOLIVEIRA JR, O. N.
700 1 $aMATTOSO, L. H. C.
773 $tSensors and Actuators Reports$gv. 4, 100083, 2022.
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Registro original: |
Embrapa Instrumentação (CNPDIA) |
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| Registros recuperados : 4 | |
| 2. |  | DAIKUZONO, C. M.; SHIMIZU, F. M.; MANZOLI, A.; RIUL JUNIOR, A.; PIAZZETA, M. H. O.; GOBBI, A. L.; CORREA, D. S.; PAULOVICH, F. V.; OLIVEIRA JUNIOR, O. N. Information visualization and feature selection methods applied to detect gliadin in gluten-containing foodstuff with a microfluidic eletronic tongue. In: Applied Materials & Interfaces, v. 9, p. 19646-19652, 2017.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Instrumentação. |
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| 3. | | COATRINI-SOARES, A.; COATRINI-SOARES, J.; POPOLIN NETO, M.; MELLO, S. S. de; PINTO, D. S. C.; CARVALHO, W. A.; GILMORE, M. S.; PIAZZETTA, M. H. O.; GOBBI, A. L.; BRANDÃO, H. M.; PAULOVICH, F. V.; OLIVEIRA JR, O. N.; MATTOSO, L. H. C. Microfluidic E-tongue to diagnose bovine mastitis with milk samples using machine learning with decision tree models. Chemical Engineering Journal, v. 451, e138523, 2022. 1 - 9| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Gado de Leite; Embrapa Instrumentação. |
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| 4. | | 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. Nanoarchitectonic E-tongue of electrospun zein/curcumin carbon dots for detecting Staphylococcus aureus in milk. ACS Omega, v. 8, n. 15, p. 13721-13732, 2023.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 4 |
| Biblioteca(s): Embrapa Gado de Leite; Embrapa Instrumentação. |
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| Registros recuperados : 4 | |
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