1,827 research outputs found
Seleção artificial de uma linhagem de Spodoptera frugiperda com resistência ao milho transgênico expressando Cry1F.
Resumo
Afadin downregulation by helicobacter pylori Induces epithelial to mesenchymal transition in gastric cells
Afadin is a cytoplasmic protein of the adherens junctions, which regulates the formation and stabilization of both the adherens and the tight junctions. Aberrant expression of Afadin has been shown in cancer and its loss has been associated with epithelial-tomesenchymal transition (EMT). EMT is characterized by the change from an epithelial to a mesenchymal phenotype, with modifications on the expression of adhesion molecules and acquisition of a migratory and invasive cell behavior. While it is known that Helicobacter pylori disrupts the tight and the adherens junctions and induces EMT, the effect of the bacteria on Afadin is still unknown. The aim of this study was to disclose the effect of H. pylori on Afadin and its impact in the induction of an EMT phenotype in gastric cells. Using two different cell lines, we observed that H. pylori infection decreased Afadin protein levels, independently of CagA, T4SS, and VacA virulence factors. H. pylori infection of cell lines recapitulated several EMT features, displacing and downregulating multiple proteins from cell–cell junctions, and increasing the expression of ZEB1, Vimentin, Slug, N-cadherin, and Snail. Silencing of Afadin by RNAi promoted delocalization of junctional proteins from the cell–cell contacts, increased paracellular permeability, and decreased transepithelial electrical resistance, all compatible with impaired junctional integrity. Afadin silencing also led to increased expression of the EMT marker Snail, and to the formation of actin stress fibers, together with increased cell motility and invasion. Finally, and in line with our in vitro data, the gastric mucosa of individuals infected with H. pylori showed decrease/loss of Afadin membrane staining at cell–cell contacts significantly more frequently than uninfected individuals. In conclusion, Afadin is downregulated by H. pylori infection in vitro and in vivo, and its downregulation leads to the emergence of EMT and to the acquisition of an aggressive phenotype in gastric cells, which can contribute to gastric carcinogenesis.This article is a result of the project NORTE-01-0145-FEDER-000029, supported by Norte Portugal Regional Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF). i3S was financed by ERDF funds through the COMPETE 2020 and Portugal 2020, and by Portuguese funds through FCT – Fundação para a Ciência e a Tecnologia/Ministério da Ciência, Tecnologia e Inovação (POCI-01-0145-FEDER-007274). MM, JM, and ML have fellowships from FCT (SFRH/BD/95631/2013, SFRH/BD/116965/2016, and SFRH/BPD/110065/2015)
Avaliação de variáveis comportamentais como metodologia para estudo de organismos não alvo em milho Bt.
bitstream/item/79556/1/circ-185.pd
Aplicação de celulases imobilizadas nahidrólise de Brachiaria brizantha.
O objetivo deste trabalho foi desenvolver um biocatalisador para aplicação na hidrólise de holocelulose de braquiária
Adaptação de Spodoptera frugiperda (J.E.Smith, 1797) (Lepidoptera: noctuidae) em diferentes genótipos de sorgo sacarino.
In-car damage dirt and stain estimation with RGB images
Shared autonomous vehicles (SAV) numbers are going to increase over the next years. The absence of human driver will create a new paradigm for in-car safety. This paper addresses the problem, presenting a monitoring system capable of estimating the state of the car interior, namely the presence of damage, dirt and stains. We propose the use of Semantic Segmentation methods to perform appropriate pixel-wise classification of certain textures found in the car's cabin as defect classes. Two methods, U-Net and DeepLabV3+, were trained and tested for different hiper-parameter and ablation scenarios, using RGB images. To be able to test and validate these approaches an In-car dataset was created, comprised by 1861 samples from 78 cars, and than splitted in 1303 train, 186 validation and 372 test RGB images. DeepLabV3+ showed promissing results, achieving an average accuracy for good, damage, stain and dirt of 77.17%, 58.60%, 65.81% and 68.82%, respectively.POFC - Programa Operacional Temático Factores de competitividade(039334); European Structural and Investment Funds in the FEDER component, through the Operational Competitiveness and Internationalization Programme (COMPETE 2020) [Project
nº 039334; Funding Reference: POCI-01-0247-FEDER-039334
Efeito da interação de Podisus nigrispinus e milho Bt na evolução de injúrias causadas pela infestação de Spodoptera frugiperda.
CaracterÃsticas biológicas de uma população da lagarta-do-cartucho relacionadas ao milho Bt expressando a toxina Cry 1F.
Attack of Atarsocoris brachiariae Becker, a new pest of pasturelands in Mato Grosso, Brazil
Estudou-se o efeito da textura do solo, relevo, espécie forrageira, idade e sistema de formação da pastagem, sobre o ataque de Atarsocoris brachiariae. Não foram observadas diferenças significativas entre as espécies de forrageiras ou tipo de relevo quanto ao ataque da praga. As maiores densidades foram observadas em solos de textura arenosa, pastagens com mais de quatro anos, sistema de formação convencional e na faixa de 20-30 cm de profundidade. O ataque foi em reboleiras, e a maior densidade ocorreu na região de transição entre a área de pastagem morta e a área em que esta apresentava desenvolvimento normal.The effect of soil texture, landscape, grass species, age and system of pasture formation on attack intensity of Atarsocoris brachiariae Becker was studied. No differences were found among grass species or landscape on attack intensity of this bug. Higher densities of A. brachiariae were observed in sandy soils, in pastures over four years old, in those with traditional formation and between 20-30 cm underground. Attack of A. brachiariae occurred in patches specially in the transition areas between dead grass and normal growing grass
- …