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Registro Completo |
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Biblioteca(s): |
Embrapa Florestas. |
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Data corrente: |
22/03/2012 |
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Data da última atualização: |
29/01/2016 |
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Tipo da produção científica: |
Artigo em Anais de Congresso |
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Autoria: |
FARIAS NETO, A. L. de; MORAES, M. C. M. M. de; REIS, J. C. dos; PITTA, R. M.; REIS, C. A. F. |
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Afiliação: |
AUSTECLINIO LOPES DE FARIAS NETO, CPAMT; MARCELO CARAUTA M M DE MORAES, CPAMT; JULIO CESAR DOS REIS, CPAMT; RAFAEL MAJOR PITTA, CPAMT; CRISTIANE APARECIDA FIORAVANTE REIS, CNPF. |
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Título: |
Melhoramento genético de plantas em sistemas de integração lavoura pecuária floresta. |
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Ano de publicação: |
2011 |
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Fonte/Imprenta: |
In: SIMPÓSIO DE MELHORAMENTO GENÉTICO DE PLANTAS, 1., Sinop. Melhoramento de plantas para sistemas agrícolas no Estado de Mato Grosso: anais. Sinop: UFMT: Embrapa Agrossilvipastoril, 2011. p. 13-45. |
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ISBN: |
978-85-327-0452-8 |
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Idioma: |
Português |
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Palavras-Chave: |
ILPF; Melhoramento de plantas; Melhoramento genético; Sistema agrossilvipastoril. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 00813naa a2200217 a 4500
001 1920005
005 2016-01-29
008 2011 bl uuuu u00u1 u #d
020 $a978-85-327-0452-8
100 1 $aFARIAS NETO, A. L. de
245 $aMelhoramento genético de plantas em sistemas de integração lavoura pecuária floresta.
260 $c2011
653 $aILPF
653 $aMelhoramento de plantas
653 $aMelhoramento genético
653 $aSistema agrossilvipastoril
700 1 $aMORAES, M. C. M. M. de
700 1 $aREIS, J. C. dos
700 1 $aPITTA, R. M.
700 1 $aREIS, C. A. F.
773 $tIn: SIMPÓSIO DE MELHORAMENTO GENÉTICO DE PLANTAS, 1., Sinop. Melhoramento de plantas para sistemas agrícolas no Estado de Mato Grosso: anais. Sinop: UFMT: Embrapa Agrossilvipastoril, 2011. p. 13-45.
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Registro original: |
Embrapa Florestas (CNPF) |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Instrumentação. Para informações adicionais entre em contato com cnpdia.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Instrumentação. |
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Data corrente: |
19/10/2021 |
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Data da última atualização: |
09/06/2022 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 1 |
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Autoria: |
SOARES, J. C.; SOARES, A. C.; RODRIGUES, V. C.; OITICICA, P. R. A.; RAYMUNDO-PEREIRA, P. A.; BOTT-NETO, J. L.; BUSCAGLIA, L. A.; CASTRO, L. D. C. de; RIBAS, L. C.; SCABINI, L.; BRAZACA, L. C.; CORREA, D. S.; MATTOSO, L. H. C.; OLIVEIRA, M. C. F. de; CARVALHO, A. C. P. L. de; CARRILHO, E.; BRUNO, O. M.; MELENDEZ, M. E.; OLIVEIRA JR, O. N. |
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Afiliação: |
DANIEL SOUZA CORREA, CNPDIA; LUIZ HENRIQUE CAPPARELLI MATTOSO, CNPDIA. |
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Título: |
Detection of a SARS-CoV-2 sequence with genosensors using data analysis based on information visualization and machine learning techniques. |
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Ano de publicação: |
2021 |
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Fonte/Imprenta: |
Materials Chemistry Frontiers, v. 5, 2021. |
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Páginas: |
5658-5670 |
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DOI: |
10.1039/d1qm00665g |
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Idioma: |
Português |
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Conteúdo: |
We report on genosensors to detect an ssDNA sequence from the SARS-CoV-2 genome, which mimics the GU280 gp10 gene (coding the viral nucleocapsid phosphoprotein), using four distinct principles of detection and treating the data with information visualization and machine learning techniques. Genosensors were fabricated on either gold (Au) interdigitated electrodes for electrical and electrochemical measurements or on Au nanoparticles on a glass slide for optical measurements. They contained a matrix of 11-mercaptoundecanoic acid (11-MUA) self-assembled monolayer (SAM) onto which a layer of capture probe (cpDNA) sequence was immobilized. Detection was performed using electrical and electrochemical impedance spectroscopies and localized surface plasmon resonance (LSPR). The highest sensitivity was reached with impedance spectroscopy, including using a low-cost (US$ 100) homemade impedance analyzer. Complementary ssDNA sequences were detected with a detection limit of 0.5 aM (0.3 copy per mL). This performance may be attributed to the high sensitivity of the electrical impedance technique combined with an appropriate arrangement of the sequences on the electrodes and hybridization between the complementary sequences, as inferred from polarizationmodulated infrared reflection absorption spectroscopy (PM-IRRAS). The selectivity of the genosensor was confirmed by plotting the impedance spectroscopy data with a multidimensional projection technique (interactive document mapping, IDMAP), where a clear separation was observed among the samples of the complementary DNA sequence at various concentrations and from buffer samples containing a non-complementary sequence and other DNA biomarkers. The diagnosis of SARS-CoV-2 mimicking sequences was also achieved with machine learning techniques applied to scanning electron microscope images taken from genosensors exposed to distinct concentrations of the complementary ssDNA sequences. In summary, the genosensors proposed here are promising for detecting SARS-CoV2 genetic material (RNA) in biological fluids in point-of-care settings MenosWe report on genosensors to detect an ssDNA sequence from the SARS-CoV-2 genome, which mimics the GU280 gp10 gene (coding the viral nucleocapsid phosphoprotein), using four distinct principles of detection and treating the data with information visualization and machine learning techniques. Genosensors were fabricated on either gold (Au) interdigitated electrodes for electrical and electrochemical measurements or on Au nanoparticles on a glass slide for optical measurements. They contained a matrix of 11-mercaptoundecanoic acid (11-MUA) self-assembled monolayer (SAM) onto which a layer of capture probe (cpDNA) sequence was immobilized. Detection was performed using electrical and electrochemical impedance spectroscopies and localized surface plasmon resonance (LSPR). The highest sensitivity was reached with impedance spectroscopy, including using a low-cost (US$ 100) homemade impedance analyzer. Complementary ssDNA sequences were detected with a detection limit of 0.5 aM (0.3 copy per mL). This performance may be attributed to the high sensitivity of the electrical impedance technique combined with an appropriate arrangement of the sequences on the electrodes and hybridization between the complementary sequences, as inferred from polarizationmodulated infrared reflection absorption spectroscopy (PM-IRRAS). The selectivity of the genosensor was confirmed by plotting the impedance spectroscopy data with a multidimensional projection technique (interactive document mapping, IDM... Mostrar Tudo |
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Palavras-Chave: |
Genetic material (RNA); SsDNA; Viral nucleocapsid phosphoprotein). |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 03303naa a2200397 a 4500
001 2135418
005 2022-06-09
008 2021 bl uuuu u00u1 u #d
024 7 $a10.1039/d1qm00665g$2DOI
100 1 $aSOARES, J. C.
245 $aDetection of a SARS-CoV-2 sequence with genosensors using data analysis based on information visualization and machine learning techniques.$h[electronic resource]
260 $c2021
300 $a5658-5670
520 $aWe report on genosensors to detect an ssDNA sequence from the SARS-CoV-2 genome, which mimics the GU280 gp10 gene (coding the viral nucleocapsid phosphoprotein), using four distinct principles of detection and treating the data with information visualization and machine learning techniques. Genosensors were fabricated on either gold (Au) interdigitated electrodes for electrical and electrochemical measurements or on Au nanoparticles on a glass slide for optical measurements. They contained a matrix of 11-mercaptoundecanoic acid (11-MUA) self-assembled monolayer (SAM) onto which a layer of capture probe (cpDNA) sequence was immobilized. Detection was performed using electrical and electrochemical impedance spectroscopies and localized surface plasmon resonance (LSPR). The highest sensitivity was reached with impedance spectroscopy, including using a low-cost (US$ 100) homemade impedance analyzer. Complementary ssDNA sequences were detected with a detection limit of 0.5 aM (0.3 copy per mL). This performance may be attributed to the high sensitivity of the electrical impedance technique combined with an appropriate arrangement of the sequences on the electrodes and hybridization between the complementary sequences, as inferred from polarizationmodulated infrared reflection absorption spectroscopy (PM-IRRAS). The selectivity of the genosensor was confirmed by plotting the impedance spectroscopy data with a multidimensional projection technique (interactive document mapping, IDMAP), where a clear separation was observed among the samples of the complementary DNA sequence at various concentrations and from buffer samples containing a non-complementary sequence and other DNA biomarkers. The diagnosis of SARS-CoV-2 mimicking sequences was also achieved with machine learning techniques applied to scanning electron microscope images taken from genosensors exposed to distinct concentrations of the complementary ssDNA sequences. In summary, the genosensors proposed here are promising for detecting SARS-CoV2 genetic material (RNA) in biological fluids in point-of-care settings
653 $aGenetic material (RNA)
653 $aSsDNA
653 $aViral nucleocapsid phosphoprotein)
700 1 $aSOARES, A. C.
700 1 $aRODRIGUES, V. C.
700 1 $aOITICICA, P. R. A.
700 1 $aRAYMUNDO-PEREIRA, P. A.
700 1 $aBOTT-NETO, J. L.
700 1 $aBUSCAGLIA, L. A.
700 1 $aCASTRO, L. D. C. de
700 1 $aRIBAS, L. C.
700 1 $aSCABINI, L.
700 1 $aBRAZACA, L. C.
700 1 $aCORREA, D. S.
700 1 $aMATTOSO, L. H. C.
700 1 $aOLIVEIRA, M. C. F. de
700 1 $aCARVALHO, A. C. P. L. de
700 1 $aCARRILHO, E.
700 1 $aBRUNO, O. M.
700 1 $aMELENDEZ, M. E.
700 1 $aOLIVEIRA JR, O. N.
773 $tMaterials Chemistry Frontiers$gv. 5, 2021.
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