Classification of antimicrobial resistance using artificial neural networks and the relationship of 38 genes associated with the virulence of Escherichia coli isolates from broilers

Avian pathogenic Escherichia coli (APEC) is responsible for various pathological processes in birds and is considered as one of the principal causes of morbidity and mortality, associated with economic losses to the poultry industry. The objective of this study was to demonstrate that it is possible to predict antimicrobial resistance of 256 samples (APEC) using 38 different genes responsible for virulence factors, through a computer program of artificial neural networks (ANNs). A second target was to find the relationship between (PI) pathogenicity index and resistance to 14 antibiotics by statistical analysis. The results showed that the RNAs were able to make the correct classification of the behavior of APEC samples with a range from 74.22 to 98.44%, and make it possible to predict antimicrobial resistance. The statistical analysis to assess the relationship between the pathogenic index (PI) and resistance against 14 antibiotics showed that these variables are independent, i.e. peaks in PI can happen without changing the antimicrobial resistance, or the opposite, changing the antimicrobial resistance without a change in PI.

Relationship between weight, age and hatching success and the concentration of heavy metals in nestling blue macaw (Anodorhynchus hyacinthinus Latham, 1790) in the Pantanal,Mato Grosso do Sul

Abstract: The concentration of heavy metals (Cr, Fe, Al, As, Cd, Cu, Pb, Mo, Ni, Se and Zn) was evaluated in the blood of nestling blue macaws (Anodorhynchus hyacinthinus) captured in the Pantanal, Mato Grosso do Sul (n=26) in 2012; this was based on the hypothesis that these birds exhibit levels of these heavy metals in their organism and that these interfere in hatching success, weight and age of the chicks. Blood samples were digested with nitric acid and hydrochloric acid and the quantification of metals was performed by ICP-OES (Optical Emission Spectroscopy and Inductively Coupled Plasma). Blood samples of nestlings showed concentrations of Cr (0.10μg/g) Fe (3.06μg/g) Al (3.46μg/g), Cd (0.25μg/g) Cu (0.74μg/g), Mo (0.33μg/g), Ni (0.61μg/g), Se (0.98μg/g), and Zn (2.08μg/g). The levels of heavy metals found were not associated with weight, age and hatching success of the chicks.

Modelling Long-Run Relationship between Spot and Future Prices of Different Commodities

The purpose of this study is to investigate whether there exists any kind of relationship between the spot and future prices of the different commodities or not. Commodities like cocoa, coffee, crude oil, gold, natural gas and silver are considered from January 3, 2000 to December 31, 2012. For this purpose, ADF test and KPSS test are used in testing the stationarity whereas Johansen Cointegration test is used in testing the long-run relationship. Johansen co-integration test exhibits that there at least 5 co-integrating pairs out of 6 except crude oil. Moreover, the result of Granger Causality supports the fact that if two or more than two time series tend to be co-integrated there exists either uni-directional or bi-directional relationship. However, our results reveled that although there exists the co-integration between the variable, one might not granger causes another .VAR model is also used to measure the proportion of effects. These findings will help the derivative market and arbitragers in developing the strategies to gain the maximum profit in the financial market.