Cates Rubin (crosslarch3)

This paper has as a main goal to evaluate how models of the forecast will work with a group of variables that were selected based only on their correlation with the average tariff variation. Two forecast models are used, the first based on multiple linear regression techniques and the second based on the application of artificial neural networks (perceptron). We intend to use those models to reach the current water tariff based on the historic variation of the charge and the selected variables applied to municipal and private companies that operate water supply and wastewater systems in the South and Southeast regions of Brazil. The subsidiary data for the elaboration of the models were obtained through the National Sanitation Information System (SNIS). The obtained results indicated that the forecasting processes, in both models used, were able to forecast with high accuracy the fees, and guaranteed the maintenance of the surplus for the analyzed systems.Objective Rapid and convenient detection of protein-protein interactions (PPIs) is of great significance for understanding function of protein. Results For efficiently detecting PPIs, we used the changes of proteins fluorescence localization to design a novel system, fluorescence translocation co-localization (FTCL), based on nuclear localization signal (NLS) in living cells. Depending on the original state of protein localization (both in the cytoplasm, both in the nucleus, one in the nucleus and another in the cytoplasm), two target proteins can be partitioned into the cytoplasm and nucleus by adding a NLS or mutating an existing NLS. Three independent results display that the changes of protein fluorescence co-localization were observed following co-expression of the two target proteins. At the same time, we verified the accuracy of fluorescence co-localization by co-immunoprecipitation. Conclusions There FTCL system provided a novel detection method for PPIs, regardless of protein localization in the nucleus or cytoplasm. More importantly, this study provides a new strategy for future protein interaction studies through organelle localization (such as mitochondria, Golgi and cytomembrane, etc.).Objectives To evaluate a strain of Fusarium verticillioides ITV03 isolated from wood residues in the Veracruz region of Mexico. Endoglucanase and β-glucosidase production by submerged fermentation was optimized using a Box-Behnken design, where the independent variables were urea, ammonium sulfate and yeast extract. Results After optimization, an endoglucanase activity of 0.27 U/mL was achieved; subsequently, three carbon sources were evaluated (carboxymethyl cellulose, sweet sorghum bagasse cellulose and delignified sweet sorghum bagasse (DSSB). The results showed that DSSB yielded the greatest endoglucanase (0.28 U/mL) and β-glucosidase (0.12 U/mL) activities. Both enzymatic activities were characterized for the effect of pH, temperature and thermostability. The optimal parameters of β-glucosidase and endoglucanase activity were pH 5 and 4 respectively, the optimum temperature 60 °C. These enzymes were stable at 50 °C for 150.68 h and 8.54 h, with an activation energy (Ea(day)) of 265.55 kJ/mol and 44.40 kJ/mol respectively, for β-glucosidase and endoglucanase. Conclusion The present work shows that a native strain like F. verticillioides ITV03 using DSSB supplemented with nitrogen has a great potential as a producer of cellulase for lignocellulosic residue hydrolysis.Periodontal disease (PD) is common and increases cardiovascular diseases. However, it is unclear whether PD is associated with increased risk of dementia. We carried out a systematic review and meta-analysis to investigate the influence of PD on dementia. We projected the number of dementia cases to be saved by reducing PD prevalence in the world. We searched cohort and case-control studies reporting the association of PD with all dementia (or any specific type of dementia) through PubMed, MEDLINE, PsycINFO, SocIN