An Asp49 Phospholipase A2 From Snake Venom Induces Cyclooxygenase-2 Expression And Prostaglandin E2 Production Via Activation Of Nf-κb, P38mapk, And Pkc In Macrophages.

Phospholipases A2 (PLA2) are key enzymes for production of lipid mediators. We previously demonstrated that a snake venom sPLA2 named MT-III leads to prostaglandin (PG)E2 biosynthesis in macrophages by inducing the expression of cyclooxygenase-2 (COX-2). Herein, we explored the molecular mechanisms and signaling pathways leading to these MT-III-induced effects. Results demonstrated that MT-III induced activation of the transcription factor NF-κB in isolated macrophages. By using NF-κB selective inhibitors, the involvement of this factor in MT-III-induced COX-2 expression and PGE2 production was demonstrated. Moreover, MT-III-induced COX-2 protein expression and PGE2 release were attenuated by pretreatment of macrophages with SB202190, and Ly294002, and H-7-dihydro compounds, indicating the involvement of p38MAPK, PI3K, and PKC pathways, respectively. Consistent with this, MT-III triggered early phosphorylation of p38MAPK, PI3K, and PKC. Furthermore, SB202190, H-7-dihydro, but not Ly294002 treatment, abrogated activation of NF-κB induced by MT-III. Altogether, these results show for the first time that the induction of COX-2 protein expression and PGE2 release, which occur via NF-κB activation induced by the sPLA2-MT-III in macrophages, are modulated by p38MAPK and PKC, but not by PI3K signaling proteins.

Estimativa de parâmetros biofísicos de plantios de café a partir de imagens orbitais de alta resolução espacial

Remote sensing data are each time more available and can be used to monitor the vegetal development of main agricultural crops, such as the Arabic coffee in Brazil, since that the relationship between spectral and agronomical data be well known. Therefore, this work had the main objective to assess the use of Quickbird satellite images to estimate biophysical parameters of coffee crop. Test area was composed by 25 coffee fields located between the cities of Ribeirão Corrente, Franca and Cristais Paulista (SP), Brazil, and the biophysical parameters used were row and between plants spacing, plant height, LAI, canopy diameter, percentage of vegetation cover, roughness and biomass. Spectral data were the reflectance of four bands of QUICKBIRD and values of four vegetations indexes (NDVI, GVI, SAVI and RVI) based on the same satellite. All these data were analyzed using linear and nonlinear regression methods to generate estimation models of biophysical parameters. The use of regression models based on nonlinear equations was more appropriate to estimate parameters such as the LAI and the percentage of biomass, important to indicate the productivity of coffee crop.