Mechanistic implications of zinc(II) ions on the degradation of phenol by the fenton reaction

A study of the interference of Zn2+ ions on phenol degradation by Fenton reaction (Fe2+/Fe3+ + H2O2) is reported. One of the first intermediates formed in the reaction, catechol, can reduce Fe3+ to Fe2+ and, in the presence of H2O2 initiates an efficient catalytic redox cycle. In the initial stages of the reaction, this catechol-mediated cycle becomes the principal route of thermal degradation of phenol and its oxidation products. The Zn2+ ion addition enhances the persistence time of catechol, probably by stabilization of the corresponding semiquinone radical via complexation.

Interference of inorganic ions on phenol degradation by the Fenton reaction

The addition of Cu2+ ions to the classical Fenton reaction (Fe2+ plus H2O2 at pH 3) is found to accelerate the degradation of organic compounds. This synergic effect causes an approximately 15 % additional reduction of the total organic carbon (TOC), representing an overall improvement of the efficiency of the mineralization of phenol. Although Fe2+ exhibits a high initial rate of degradation, the degradation is not complete due to the formation of compounds refractory to the hydroxyl radical. The interference of copper ions on the degradation of phenol by the Fenton reaction was investigated. In the presence of Cu2+, the degradation is slower, but results in a greater reduction of TOC at the end of the reaction (t = 120 min). In the final stages of the reaction, when the Fe3+ in the solution is complexed in the form of ferrioxalate, the copper ions assume the role of the main catalyst of the degradation

M-protein is down-regulated in cardiac hypertrophy driven by thyroid hormone in rats

Although it is well known that the thyroid hormone (T3) is an important positive regulator of cardiac function over a short term and that it also promotes deleterious effects over a long term, the molecular mechanisms for such effects are not yet well understood. Because most alterations in cardiac function are associated with changes in sarcomeric machinery, the present work was undertaken to find novel sarcomeric hot spots driven by T3 in the heart. A microarray analysis indicated that the M-band is a major hot spot, and the structural sarcomeric gene coding for the M-protein is severely down-regulated by T3. Real-time quantitative PCR-based measurements confirmed that T3 (1, 5, 50, and 100 physiological doses for 2 days) sharply decreased the M-protein gene and protein expression in vivo in a dose-dependent manner. Furthermore, the M-protein gene expression was elevated 3.4-fold in hypothyroid rats. Accordingly, T3 was able to rapidly and strongly reduce the M-protein gene expression in neonatal cardiomyocytes. Deletions at the M-protein promoter and bioinformatics approach suggested an area responsive to T3, which was confirmed by chromatin immunoprecipitation assay. Functional assays in cultured neonatal cardiomyocytes revealed that depletion of M-protein (by small interfering RNA) drives a severe decrease in speed of contraction. Interestingly, mRNA and protein levels of other M-band components, myomesin and embryonic-heart myomesin, were not altered by T3. We concluded that the M-protein expression is strongly and rapidly repressed by T3 in cardiomyocytes, which represents an important aspect for the basis of T3-dependent sarcomeric deleterious effects in the heart.

A Fuzzy Ontology-Driven Approach to Semantic Interoperability in e-Government Big Data

With the increasing production of information from e-government initiatives, there is also the need to transform a large volume of unstructured data into useful information for society. All this information should be easily accessible and made available in a meaningful and effective way in order to achieve semantic interoperability in electronic government services, which is a challenge to be pursued by governments round the world. Our aim is to discuss the context of e-Government Big Data and to present a framework to promote semantic interoperability through automatic generation of ontologies from unstructured information found in the Internet. We propose the use of fuzzy mechanisms to deal with natural language terms and present some related works found in this area. The results achieved in this study are based on the architectural definition and major components and requirements in order to compose the proposed framework. With this, it is possible to take advantage of the large volume of information generated from e-Government initiatives and use it to benefit society.