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Registro Completo |
Biblioteca(s): |
Embrapa Gado de Leite. |
Data corrente: |
19/09/2016 |
Data da última atualização: |
06/02/2024 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Autoria: |
BENADUCCI, T.; SARDI, J. de C. O.; LOURENCETTI, N. M. S.; SCORZONI, L.; GULLO, F. P.; ROSSI, S. A.; DERISSI, J. B.; PRATA, M. C. de A.; FUSCO-ALMEIDA, A. M.; MENDES-GIANNINI, M. J. S. |
Afiliação: |
Tatiane Benaducci, UNESP; Janaina de C. O. Sardi, UNESP; Natalia M. S. Lourencetti, UNESP; Liliana Scorzoni, UNESP; Fernanda P. Gullo, UNESP; Suélen A. Rossi, UNESP; Jaqueline B. Derissi, UNESP; MARCIA CRISTINA DE AZEVEDO PRATA, CNPGL; Ana M. Fusco-Almeida, UNESP; Maria J. S. Mendes-Giannini, UNESP. |
Título: |
Virulence of Cryptococcus sp. biofilms in vitro and in vivo using Galleria mellonella as an alternative model. |
Ano de publicação: |
2016 |
Fonte/Imprenta: |
Frontiers in Microbiology, v. 7, n. 290, p. 76-86, 2016. |
DOI: |
http://dx.doi.org/10.3389/fmicb.2016.00290 |
Idioma: |
Inglês |
Conteúdo: |
Cryptococcus neoformans and C. gattii are fungal pathogens that are most commonly found in infections of the central nervous system, which cause life-threatening meningoencephalitis and can grow as a biofilm. Biofilms are structures conferring protection and resistance of microorganism to the antifungal drugs. This study compared the virulence of planktonic and biofilm cells of C. neoformans and C. gattii in Galleria mellonella model, as well as, the quantification of gene transcripts LAC1, URE1, and CAP59 by real time PCR. All three of the genes showed significantly increased expressions in the biofilm conditions for two species of Cryptococcus, when compared to planktonic cells. C. neoformans and C. gattii cells in the biofilm forms were more virulent than the planktonic cells in G. mellonella. This suggests that the biofilm conditions may contribute to the virulence profile. Our results contribute to a better understanding of the agents of cryptococcosis in the host-yeast aspects of the interaction. |
Palavras-Chave: |
Biofilms; Cryptococcus sp. |
Thesaurus Nal: |
Galleria mellonella; virulence. |
Categoria do assunto: |
L Ciência Animal e Produtos de Origem Animal |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/147527/1/Cnpgl-2016-FrontiersinMicrob-Virulence.pdf
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Marc: |
LEADER 01918naa a2200289 a 4500 001 2053051 005 2024-02-06 008 2016 bl uuuu u00u1 u #d 024 7 $ahttp://dx.doi.org/10.3389/fmicb.2016.00290$2DOI 100 1 $aBENADUCCI, T. 245 $aVirulence of Cryptococcus sp. biofilms in vitro and in vivo using Galleria mellonella as an alternative model.$h[electronic resource] 260 $c2016 520 $aCryptococcus neoformans and C. gattii are fungal pathogens that are most commonly found in infections of the central nervous system, which cause life-threatening meningoencephalitis and can grow as a biofilm. Biofilms are structures conferring protection and resistance of microorganism to the antifungal drugs. This study compared the virulence of planktonic and biofilm cells of C. neoformans and C. gattii in Galleria mellonella model, as well as, the quantification of gene transcripts LAC1, URE1, and CAP59 by real time PCR. All three of the genes showed significantly increased expressions in the biofilm conditions for two species of Cryptococcus, when compared to planktonic cells. C. neoformans and C. gattii cells in the biofilm forms were more virulent than the planktonic cells in G. mellonella. This suggests that the biofilm conditions may contribute to the virulence profile. Our results contribute to a better understanding of the agents of cryptococcosis in the host-yeast aspects of the interaction. 650 $aGalleria mellonella 650 $avirulence 653 $aBiofilms 653 $aCryptococcus sp 700 1 $aSARDI, J. de C. O. 700 1 $aLOURENCETTI, N. M. S. 700 1 $aSCORZONI, L. 700 1 $aGULLO, F. P. 700 1 $aROSSI, S. A. 700 1 $aDERISSI, J. B. 700 1 $aPRATA, M. C. de A. 700 1 $aFUSCO-ALMEIDA, A. M. 700 1 $aMENDES-GIANNINI, M. J. S. 773 $tFrontiers in Microbiology$gv. 7, n. 290, p. 76-86, 2016.
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Embrapa Gado de Leite (CNPGL) |
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Registro Completo
Biblioteca(s): |
Embrapa Meio Ambiente; Embrapa Semiárido. |
Data corrente: |
04/07/2022 |
Data da última atualização: |
04/07/2022 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Circulação/Nível: |
A - 1 |
Autoria: |
MELO, D. C. D.; ANACHE, J. A. A.; BORGES, V. P.; MIRALLES, D. G.; MARTENS, B.; FISHER, J. B.; NÓBREGA, R. L. B.; MORENO, A.; CABRAL, O. M. R.; RODRIGUES, T. R.; BEZERRA, B.; SILVA, C. M. S.; MEIRA NETO, A. A.; MOURA, M. S. B. de; MARQUES, T. V.; CAMPOS, S.; NOGUEIRA, J. S.; ROSOLEM, R.; SOUZA, R. M. S.; ANTONINO, A. C. D.; HOLL, D.; GALLEGUILLOS, M.; PEREZ-QUEZADA, J. F.; VERHOEF, A.; KUTZBACH, L.; LIMA, J. R. S.; SOUZA, E. S.; GASSMAN, M. I.; PEREZ, C. F.; TONTI, N.; POSSE, G.; RAINS, D.; OLIVEIRA, P. T. S.; WENDLAND, E. |
Afiliação: |
D. C. D. MELO, UFPB; J. A. A. ANACHE, UFMS; V. P. BORGES, UFPB; D. G. MIRALLES, Hydro-Climate Extremes Lab (H-CEL), Ghent University, Ghent, Belgium; B. MARTENS, Hydro-Climate Extremes Lab (H-CEL), Ghent University, Ghent, Belgium; J. B. FISHER, Schmid College of Science and Technology, Chapman University, Orange, CA; R. L. B. NÓBREGA, Department of Life Sciences, Imperial College London; A. MORENO, Numerical Terradynamic Simulation Group, University of Montana, Missoula, MT; OSVALDO MACHADO RODRIGUES CABRAL, CNPMA; T. R. RODRIGUES, UFMS; B. BEZERRA, UFRN; C. M. S. SILVA, UFRN; A. A. MEIRA NETO, Department of Hydrology and Atmospheric Sciences, The University of Arizona, Tucson, AZ; MAGNA SOELMA BESERRA DE MOURA, CPATSA; T. V. MARQUES, UFRN; S. CAMPOS, UFRN; J. S. NOGUEIRA, UFMT; R. ROSOLEM, University of Bristol, Bristol, UK; R. M. S. SOUZA, Department of Biological and Agricultural Engineering, Texas A&M University, College Station, TX; A. C. D. ANTONINO, UFPE; D. HOLL, Center for Earth System Research and Sustainability (CEN), Universität Hamburg, Hamburg, Germany; M. GALLEGUILLOS, Department of Environmental Science and Renewable Natural Resources, University of Chile, Santiago, Chile; J. F. PEREZ-QUEZADA, Department of Environmental Science and Renewable Natural Resources, University of Chile, Santiago, Chile; A. VERHOEF, Department of Geography and Environmental Science, The University of Reading, Reading, UK; L. KUTZBACH, Center for Earth System Research and Sustainability (CEN), Universität Hamburg, Hamburg, Germany; J. R. S. LIMA, Federal University of the Agreste of Pernambuco, Garanhuns, PE; E. S. SOUZA, UFRPE, Garanhuns, PE; M. I. GASSMAN, Department of Atmospheric and Ocean Sciences, FCEN — UBA, Buenos Aires, Argentina; C. F. PEREZ, Department of Atmospheric and Ocean Sciences, FCEN ? UBA, Buenos Aires, Argentina; N. TONTI, Department of Atmospheric and Ocean Sciences, FCEN — UBA, Buenos Aires, Argentina; G. POSSE, INTA; D. RAINS, Hydro-Climate Extremes Lab (H-CEL), Ghent University, Ghent, Belgium; P. T. S. OLIVEIRA, UFMS; E. WENDLAND, Department of Hydraulics and Sanitary Engineering, University of São Paulo, São Carlos, SP. |
Título: |
Are remote sensing evapotranspiration models reliable across South American ecoregions? |
Ano de publicação: |
2021 |
Fonte/Imprenta: |
Water Resources Research, v. 57, n. 11, e2020WR028752, 2021. |
DOI: |
https://doi.org/10.1029/2020WR028752 |
Idioma: |
Inglês |
Conteúdo: |
Many remote sensing-based evapotranspiration (RSBET) algorithms have been proposed in the past decades and evaluated using flux tower data, mainly over North America and Europe. Model evaluation across South America has been done locally or using only a single algorithm at a time. Here, we provide the first evaluation of multiple RSBET models, at a daily scale, across a wide variety of biomes, climate zones, and land uses in South America. We used meteorological data from 25 flux towers to force four RSBET models: Priestley?Taylor Jet Propulsion Laboratory (PT-JPL), Global Land Evaporation Amsterdam Model (GLEAM), Penman?Monteith Mu model (PM-MOD), and Penman?Monteith Nagler model (PM-VI). E ET was predicted satisfactorily by all four models, with correlations consistently higher (?20.6ER) for GLEAM and PT-JPL, and PM-MOD and PM-VI presenting overall better responses in terms of percent bias (?? ?1010EPBIAS%). As for PM-VI, this outcome is expected, given that the model requires calibration with local data. Model skill seems to be unrelated to land-use but instead presented some dependency on biome and climate, with the models producing the best results for wet to moderately wet environments. Our findings show the suitability of individual models for a number of combinations of land cover types, biomes, and climates. At the same time, no model outperformed the others for all conditions, which emphasizes the need for adapting individual algorithms to take into account intrinsic characteristics of climates and ecosystems in South America. MenosMany remote sensing-based evapotranspiration (RSBET) algorithms have been proposed in the past decades and evaluated using flux tower data, mainly over North America and Europe. Model evaluation across South America has been done locally or using only a single algorithm at a time. Here, we provide the first evaluation of multiple RSBET models, at a daily scale, across a wide variety of biomes, climate zones, and land uses in South America. We used meteorological data from 25 flux towers to force four RSBET models: Priestley?Taylor Jet Propulsion Laboratory (PT-JPL), Global Land Evaporation Amsterdam Model (GLEAM), Penman?Monteith Mu model (PM-MOD), and Penman?Monteith Nagler model (PM-VI). E ET was predicted satisfactorily by all four models, with correlations consistently higher (?20.6ER) for GLEAM and PT-JPL, and PM-MOD and PM-VI presenting overall better responses in terms of percent bias (?? ?1010EPBIAS%). As for PM-VI, this outcome is expected, given that the model requires calibration with local data. Model skill seems to be unrelated to land-use but instead presented some dependency on biome and climate, with the models producing the best results for wet to moderately wet environments. Our findings show the suitability of individual models for a number of combinations of land cover types, biomes, and climates. At the same time, no model outperformed the others for all conditions, which emphasizes the need for adapting individual algorithms to take into account int... Mostrar Tudo |
Palavras-Chave: |
MODIS; Penman-Monteith; Priestley-Taylor. |
Thesagro: |
Evapotranspiração; Sensoriamento Remoto; Vegetação. |
Thesaurus NAL: |
Remote sensing. |
Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra |
Marc: |
LEADER 03247naa a2200613 a 4500 001 2144450 005 2022-07-04 008 2021 bl uuuu u00u1 u #d 024 7 $ahttps://doi.org/10.1029/2020WR028752$2DOI 100 1 $aMELO, D. C. D. 245 $aAre remote sensing evapotranspiration models reliable across South American ecoregions?$h[electronic resource] 260 $c2021 520 $aMany remote sensing-based evapotranspiration (RSBET) algorithms have been proposed in the past decades and evaluated using flux tower data, mainly over North America and Europe. Model evaluation across South America has been done locally or using only a single algorithm at a time. Here, we provide the first evaluation of multiple RSBET models, at a daily scale, across a wide variety of biomes, climate zones, and land uses in South America. We used meteorological data from 25 flux towers to force four RSBET models: Priestley?Taylor Jet Propulsion Laboratory (PT-JPL), Global Land Evaporation Amsterdam Model (GLEAM), Penman?Monteith Mu model (PM-MOD), and Penman?Monteith Nagler model (PM-VI). E ET was predicted satisfactorily by all four models, with correlations consistently higher (?20.6ER) for GLEAM and PT-JPL, and PM-MOD and PM-VI presenting overall better responses in terms of percent bias (?? ?1010EPBIAS%). As for PM-VI, this outcome is expected, given that the model requires calibration with local data. Model skill seems to be unrelated to land-use but instead presented some dependency on biome and climate, with the models producing the best results for wet to moderately wet environments. Our findings show the suitability of individual models for a number of combinations of land cover types, biomes, and climates. At the same time, no model outperformed the others for all conditions, which emphasizes the need for adapting individual algorithms to take into account intrinsic characteristics of climates and ecosystems in South America. 650 $aRemote sensing 650 $aEvapotranspiração 650 $aSensoriamento Remoto 650 $aVegetação 653 $aMODIS 653 $aPenman-Monteith 653 $aPriestley-Taylor 700 1 $aANACHE, J. A. A. 700 1 $aBORGES, V. P. 700 1 $aMIRALLES, D. G. 700 1 $aMARTENS, B. 700 1 $aFISHER, J. B. 700 1 $aNÓBREGA, R. L. B. 700 1 $aMORENO, A. 700 1 $aCABRAL, O. M. R. 700 1 $aRODRIGUES, T. R. 700 1 $aBEZERRA, B. 700 1 $aSILVA, C. M. S. 700 1 $aMEIRA NETO, A. A. 700 1 $aMOURA, M. S. B. de 700 1 $aMARQUES, T. V. 700 1 $aCAMPOS, S. 700 1 $aNOGUEIRA, J. S. 700 1 $aROSOLEM, R. 700 1 $aSOUZA, R. M. S. 700 1 $aANTONINO, A. C. D. 700 1 $aHOLL, D. 700 1 $aGALLEGUILLOS, M. 700 1 $aPEREZ-QUEZADA, J. F. 700 1 $aVERHOEF, A. 700 1 $aKUTZBACH, L. 700 1 $aLIMA, J. R. S. 700 1 $aSOUZA, E. S. 700 1 $aGASSMAN, M. I. 700 1 $aPEREZ, C. F. 700 1 $aTONTI, N. 700 1 $aPOSSE, G. 700 1 $aRAINS, D. 700 1 $aOLIVEIRA, P. T. S. 700 1 $aWENDLAND, E. 773 $tWater Resources Research$gv. 57, n. 11, e2020WR028752, 2021.
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