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 | Acesso ao texto completo restrito à biblioteca da Embrapa Suínos e Aves. Para informações adicionais entre em contato com cnpsa.biblioteca@embrapa.br. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Suínos e Aves. |
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Data corrente: |
11/08/2021 |
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Data da última atualização: |
11/08/2021 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
GOGONE, I. C. V. P.; FERREIRA, G. H.; GAVA, D.; SCHAEFER, R.; PAULA-LOPES, F. F. de; ROCHA, R. de A.; BARROS, F. R. O. de. |
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Afiliação: |
IZABEL C. V. P. COGONE, UTFPR; GLAUCIA H. FERREIRA, UNIFESP/Diadema; DANIELLE GAVA, CNPSA; REJANE SCHAEFER, CNPSA; FABÍOLA F. DE PAULA-LOPES, UNIFESP/Diadema; RAQUEL DE A. ROCHA, UTFPR; FLAVIA REGINA OLIVEIRA DE BARROS, UTFPR. |
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Título: |
Applicability of Raman spectroscopy on porcine parvovirus and porcine circovirus type 2 detection. |
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Ano de publicação: |
2021 |
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Fonte/Imprenta: |
Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, v. 249, n. 119336, 2021. |
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DOI: |
https://doi.org/10.1016/j.saa.2020.119336 |
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Idioma: |
Inglês |
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Conteúdo: |
Abstract: Porcine parvovirus (PPV) is one of the major infectious causes of reproductive failure of swine. This disease is characterized by embryonic and fetal infection and death, responsible for important economic losses. PPV is also implicated as a trigger in the development of post-weaning multisystemic wasting syndrome (PMWS) caused by Porcine circovirus type 2 (PCV2). Their detection is PCR-based, which is quite sensitive and specific, but laborious, costly and time-demanding. Therefore, this study aimed to assess Raman spectroscopy (RS) as a diagnostic tool for PPV and PCV2 due to its label-free properties and unique ability to search and identify molecular fingerprints. Briefly, swine testis (ST) cells were inoculated with PPV or PCV2 and in vitro cultured (37 C, 5% CO2) for four days. Fixed cells were then submitted to RS investigation using a 633 nm laser. A total of 225 spectra centered at 1300 cm1 was obtained for each sample (5 spectra/cell; 15 cells/replicate; 3 replicates) of PPV-, PCV2-infected and uninfected (control) ST cells. Clear statistical discrimination between samples from both virus-infected cells was achieved with a Principal Component ? Linear Discriminant Analysis (PCA-LDA) model, reaching sensitivity rates from 95.55% to 97.77%, respectively to PCV2- and PPV-infected cells. These results were then submitted to a Leave-One-Out (LOO) validation algorithm resulting in 99.97% of accuracy. Extensive band assignment was analyzed and compiled for better understanding of PPV and PCV2 virus-cell interaction, demonstrating that specific protein, lipids and DNA/RNA bands are the most important assignments related to discrimination of virus-infected from uninfected cells. In conclusion, these results represent promising bases for RS application on PCV2 and PPV detection for future diagnostic applications. MenosAbstract: Porcine parvovirus (PPV) is one of the major infectious causes of reproductive failure of swine. This disease is characterized by embryonic and fetal infection and death, responsible for important economic losses. PPV is also implicated as a trigger in the development of post-weaning multisystemic wasting syndrome (PMWS) caused by Porcine circovirus type 2 (PCV2). Their detection is PCR-based, which is quite sensitive and specific, but laborious, costly and time-demanding. Therefore, this study aimed to assess Raman spectroscopy (RS) as a diagnostic tool for PPV and PCV2 due to its label-free properties and unique ability to search and identify molecular fingerprints. Briefly, swine testis (ST) cells were inoculated with PPV or PCV2 and in vitro cultured (37 C, 5% CO2) for four days. Fixed cells were then submitted to RS investigation using a 633 nm laser. A total of 225 spectra centered at 1300 cm1 was obtained for each sample (5 spectra/cell; 15 cells/replicate; 3 replicates) of PPV-, PCV2-infected and uninfected (control) ST cells. Clear statistical discrimination between samples from both virus-infected cells was achieved with a Principal Component ? Linear Discriminant Analysis (PCA-LDA) model, reaching sensitivity rates from 95.55% to 97.77%, respectively to PCV2- and PPV-infected cells. These results were then submitted to a Leave-One-Out (LOO) validation algorithm resulting in 99.97% of accuracy. Extensive band assignment was analyzed and compiled for bette... Mostrar Tudo |
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Palavras-Chave: |
Molecular fingerprint; PCV2; PPV; Reproductive failure; Viral diagnostic. |
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Thesagro: |
Diagnostico; Parvovirose; Sanidade Animal; Suíno. |
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Thesaurus Nal: |
Animal diseases; Porcine circovirus-2; Raman spectroscopy; Reproductive success; Swine. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 02976naa a2200373 a 4500
001 2133480
005 2021-08-11
008 2021 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1016/j.saa.2020.119336$2DOI
100 1 $aGOGONE, I. C. V. P.
245 $aApplicability of Raman spectroscopy on porcine parvovirus and porcine circovirus type 2 detection.$h[electronic resource]
260 $c2021
520 $aAbstract: Porcine parvovirus (PPV) is one of the major infectious causes of reproductive failure of swine. This disease is characterized by embryonic and fetal infection and death, responsible for important economic losses. PPV is also implicated as a trigger in the development of post-weaning multisystemic wasting syndrome (PMWS) caused by Porcine circovirus type 2 (PCV2). Their detection is PCR-based, which is quite sensitive and specific, but laborious, costly and time-demanding. Therefore, this study aimed to assess Raman spectroscopy (RS) as a diagnostic tool for PPV and PCV2 due to its label-free properties and unique ability to search and identify molecular fingerprints. Briefly, swine testis (ST) cells were inoculated with PPV or PCV2 and in vitro cultured (37 C, 5% CO2) for four days. Fixed cells were then submitted to RS investigation using a 633 nm laser. A total of 225 spectra centered at 1300 cm1 was obtained for each sample (5 spectra/cell; 15 cells/replicate; 3 replicates) of PPV-, PCV2-infected and uninfected (control) ST cells. Clear statistical discrimination between samples from both virus-infected cells was achieved with a Principal Component ? Linear Discriminant Analysis (PCA-LDA) model, reaching sensitivity rates from 95.55% to 97.77%, respectively to PCV2- and PPV-infected cells. These results were then submitted to a Leave-One-Out (LOO) validation algorithm resulting in 99.97% of accuracy. Extensive band assignment was analyzed and compiled for better understanding of PPV and PCV2 virus-cell interaction, demonstrating that specific protein, lipids and DNA/RNA bands are the most important assignments related to discrimination of virus-infected from uninfected cells. In conclusion, these results represent promising bases for RS application on PCV2 and PPV detection for future diagnostic applications.
650 $aAnimal diseases
650 $aPorcine circovirus-2
650 $aRaman spectroscopy
650 $aReproductive success
650 $aSwine
650 $aDiagnostico
650 $aParvovirose
650 $aSanidade Animal
650 $aSuíno
653 $aMolecular fingerprint
653 $aPCV2
653 $aPPV
653 $aReproductive failure
653 $aViral diagnostic
700 1 $aFERREIRA, G. H.
700 1 $aGAVA, D.
700 1 $aSCHAEFER, R.
700 1 $aPAULA-LOPES, F. F. de
700 1 $aROCHA, R. de A.
700 1 $aBARROS, F. R. O. de
773 $tSpectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy$gv. 249, n. 119336, 2021.
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Registro original: |
Embrapa Suínos e Aves (CNPSA) |
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Tipo/Formato |
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| Acesso ao texto completo restrito à biblioteca da Embrapa Agroindústria Tropical. Para informações adicionais entre em contato com cnpat.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Agroindústria Tropical. |
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Data corrente: |
03/06/2020 |
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Data da última atualização: |
28/06/2020 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
B - 3 |
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Autoria: |
COSTA, J. N. da; LEAL, A. R.; NASCIMENTO, L. G. L.; RODRIGUES, D. C.; MUNIZ, C. R.; FIGUEIREDO, R. W.; MATA, P.; NORONHA, J. P.; SOUSA, P. H. M. de. |
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Afiliação: |
JULIANA N. DA COSTA, Departament of Food Engineering Federal University of Cear; AMANDA R. LEAL, Departament of Food Engineering Federal University of Cear; LUIS G. L. NASCIMENTO, Departament of Food Engineering Federal University of Ceara; DELANE C. RODRIGUES, Departament of Food Engineering Federal University of Ceara; CELLI RODRIGUES MUNIZ, CNPAT; RAIMUNDO W. FIGUEIREDO, Departament of Food Engineering Federal University of Ceara; PAULINA MATA, LAQV, REQUIMTE, Departament of Chemistry, Faculty of Science and Technology, New University of Lisbon; JOÃO PAULO NORONHA, LAQV, REQUIMTE, Departament of Chemistry, Faculty of Science and Technology, New University of Lisbon; PAULO HENRIQUE M. DE SOUSA, Departament of Food Engineering Federal University of Ceara. |
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Título: |
Texture, microstructure and volatile profile of structured guava using agar and gellan gum. |
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Ano de publicação: |
2020 |
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Fonte/Imprenta: |
International Journal of Gastronomy and Food Science, 20, art. no. 100207, 2020. |
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DOI: |
https://doi.org/10.1016/j.ijgfs.2020.100207 |
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Idioma: |
Inglês |
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Palavras-Chave: |
(COV); (VOCs); Compostos orgânicos voláteis; Frutas estruturadas; Goma gelana; Hidrocolóides; Microscopia eletrônica de varredura; Structured fruit; Texturometria; Texturometry. |
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Thesagro: |
Agar. |
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Thesaurus NAL: |
Gellan gum; Hydrocolloids; Scanning electron microscopy; Volatile organic compounds. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 01218naa a2200397 a 4500
001 2122970
005 2020-06-28
008 2020 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1016/j.ijgfs.2020.100207$2DOI
100 1 $aCOSTA, J. N. da
245 $aTexture, microstructure and volatile profile of structured guava using agar and gellan gum.$h[electronic resource]
260 $c2020
650 $aGellan gum
650 $aHydrocolloids
650 $aScanning electron microscopy
650 $aVolatile organic compounds
650 $aAgar
653 $a(COV)
653 $a(VOCs)
653 $aCompostos orgânicos voláteis
653 $aFrutas estruturadas
653 $aGoma gelana
653 $aHidrocolóides
653 $aMicroscopia eletrônica de varredura
653 $aStructured fruit
653 $aTexturometria
653 $aTexturometry
700 1 $aLEAL, A. R.
700 1 $aNASCIMENTO, L. G. L.
700 1 $aRODRIGUES, D. C.
700 1 $aMUNIZ, C. R.
700 1 $aFIGUEIREDO, R. W.
700 1 $aMATA, P.
700 1 $aNORONHA, J. P.
700 1 $aSOUSA, P. H. M. de
773 $tInternational Journal of Gastronomy and Food Science, 20, art. no. 100207, 2020.
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Embrapa Agroindústria Tropical (CNPAT) |
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