Avaliação dos efeitos de um extrato bruto de cianobactérias contendo microcistinas sobre o desempenho reprodutivo e a embriofetotoxicidade de ratos

The presence of cyanobacterial blooms in reservoirs intended for supply to the population can create public health problems for many species could produce potentially toxic compounds and these are not eliminated in the conventional procedures used in water treatment plants. So even in amounts less than the maximum allowable limit imposed by MS, cyanotoxins can be present in drinking water distributed to the population, creating a chronic exposure. There is little information about the long-term effects of oral exposure to cyanotoxins. This work aimed to show the exposure orally (v.o) of animals to a crude extract of cyanobacteria containing cyanotoxins to evaluate the reproductive performance of pregnant rats and their offspring and fertility of male rats. The presence of microcystins (MCs) in samples collected during the flowering processes in freshwater reservoirs in the Rio Grande do Norte, was analyzed by enzyme immunoassay and its variants have been identified and quantified by chromatographic methods. It was observed that by administration v.o. cyanobacterial extract containing MCs (40, 100 or 250 ng of MCs / kg / day) did not cause systemic toxicity in adult rats or effect on reproductive performance of male and female rats treated. It was also not observed any changes in skeletal study in the offspring of pregnant rats treated with the extract above. Because the solutions used contained MCs in a concentration equal to or greater than the tolerable daily intake for MCs, the results suggest, therefore, that the development of this work contributed to better assess public health risk as the oral exposure to cyanotoxins, increasing thus the credibility of the maximum allowable limit (LMP) of MCs in drinking water distributed to the population of several countries that use the LMP established by WHO in its legislation

Plasticidade de células tronco mesenquimais de medula óssea de ratos na presença de meio condicionado do nervo facial e do fator de crescimento fibroblástico 2

A number of evidences show the influence of the growth of injured nerve fibers in Peripheral Nervous System (PNS) as well as potential implant stem cells (SCs) to make it more suitable for nerve regeneration medium. In this perspective, this study aimed to evaluate the plasticity of mesenchymal stem cells from bone marrow of mice in the presence of culture medium conditioned with facial nerve explants (D-10) and fibroblast growth factor-2 (FGF-2). In this perspective, the cells were cultivated only with DMEM (group 1), only with D-10(group 2), only with FGF-2(group 3) or with D-10 and FGF-2(group 4). The growth and morphology were assessed over 72 hours. Quantitative phenotypic analysis was taken from the immunocytochemistry for GFAP, OX-42, MAP-2, β-tubulin III, NeuN and NF-200 on the fourth day of cultivation. Cells cultured with conditioned medium alone or combined with FGF-2 showed distinct morphological features similar apparent at certain times with neurons and glial cells and a significant proliferative activity in groups 2 and 4 throughout the days. Cells cultived only with conditioned medium acquired a glial phenotype. Cells cultured with FGF-2 and conditioned medium expressed GFAP, OX-42, MAP-2, β-tubulin III, NeuN and NF-200. On average, area and perimeter fo the group of cells positive for GFAP and the área of the cells immunostained for OX-42 were higher than those of the group 4. This study enabled the plasticity of mesenchymal cells (MCs) in neuronal and glial nineage and opened prospects for the search with cell therapy and transdifferentiation

Utilizando Pesos estáticos e dinâmicos em sistemas multi-classificadores com diferentes níveis de diversidade

Although some individual techniques of supervised Machine Learning (ML), also known as classifiers, or algorithms of classification, to supply solutions that, most of the time, are considered efficient, have experimental results gotten with the use of large sets of pattern and/or that they have a expressive amount of irrelevant data or incomplete characteristic, that show a decrease in the efficiency of the precision of these techniques. In other words, such techniques can t do an recognition of patterns of an efficient form in complex problems. With the intention to get better performance and efficiency of these ML techniques, were thought about the idea to using some types of LM algorithms work jointly, thus origin to the term Multi-Classifier System (MCS). The MCS s presents, as component, different of LM algorithms, called of base classifiers, and realized a combination of results gotten for these algorithms to reach the final result. So that the MCS has a better performance that the base classifiers, the results gotten for each base classifier must present an certain diversity, in other words, a difference between the results gotten for each classifier that compose the system. It can be said that it does not make signification to have MCS s whose base classifiers have identical answers to the sames patterns. Although the MCS s present better results that the individually systems, has always the search to improve the results gotten for this type of system. Aim at this improvement and a better consistency in the results, as well as a larger diversity of the classifiers of a MCS, comes being recently searched methodologies that present as characteristic the use of weights, or confidence values. These weights can describe the importance that certain classifier supplied when associating with each pattern to a determined class. These weights still are used, in associate with the exits of the classifiers, during the process of recognition (use) of the MCS s. Exist different ways of calculating these weights and can be divided in two categories: the static weights and the dynamic weights. The first category of weights is characterizes for not having the modification of its values during the classification process, different it occurs with the second category, where the values suffers modifications during the classification process. In this work an analysis will be made to verify if the use of the weights, statics as much as dynamics, they can increase the perfomance of the MCS s in comparison with the individually systems. Moreover, will be made an analysis in the diversity gotten for the MCS s, for this mode verify if it has some relation between the use of the weights in the MCS s with different levels of diversity