931 resultados para philosophy of action


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A double-blind clinical trial involving 120 patients with chronic schistosomiasis was carried out to compare the tolerability and efficacy of praziquantel and oxamniquine. The patients were randomly allocated into two groups. One was treated with praziquantel, 55 mg/kg of body weight CBWT), and the other one with oxamniquine, 15mg/kg bwt, administered in a single oral dose. The diagnosis and the parasitological follow-up was based on stool examinations by quantitative Kato-Katz method and on rectal biopsies. Side-effects — mainly dizziness, sleepness, abdominal distress, headache, nausea and diarrhea — were observed in 87% of the cases. Their incidence, intensity and duration were similar for both drugs but abdominal pain was significantly more frequent after praziquantel intake and severe dizziness was more commonly reported after oxamniquine. A significant increase of alanine-aminotransferase and y-glutamyltransferase was found with the latter drug and of total bilirubin with the former one. A total of 48 patients treated with praziquantel and 46 with oxamniquine completed with negative findings the required three post-treatment parasitological controls — three slides of each stool sample on the first, third and sixth month. The achieved cure rates were 79.2% and 84.8%, respectively, a difference without statistical significance. The non-cured cases showed a mean reduction in the number of eggs per gram of feces of 93.5% after praziquantel and of 84.1% after oxamniquine. This diference also was not significant. Five patients retreated with praziquantel were cured but only one out of three treated a second time with oxamniquine. These findings show that both drugs — despite their different chemical structures, pharmacological properties and mechanisms-of-action — induce similar side-effects as well as a comparable therapeutical efficacy, in agreement with the results reported from analogous investigations.

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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Electrotécnica e de Computadores

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Nucleic Acid Research (2007) Vol.37 N. 14 4755-4766

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The industrial activity is inevitably associated with a certain degradation of the environmental quality, because is not possible to guarantee that a manufacturing process can be totally innocuous. The eco-efficiency concept is globally accepted as a philosophy of entreprise management, that encourages the companies to become more competitive, innovative and environmentally responsible by promoting the link between its companies objectives for excellence and its objectives of environmental excellence issues. This link imposes the creation of an organizational methodology where the performance of the company is concordant with the sustainable development. The main propose of this project is to apply the concept of eco-efficiency to the particular case of the metallurgical and metal workshop industries through the development of the particular indicators needed and to produce a manual of procedures for implementation of the accurate solution.

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Concurrent exposure of estuarine organisms to man-made and natural stressors has become a common occurrence. Numerous interactions of multiple stressors causing synergistic or antagonistic effects have been described. However, limited information is available on combined effects of emerging pharmaceuticals and natural stressors. This study investigated the joint effects of the antidepressant sertraline and salinity on Carcinus maenas. To improve knowledge about interactive effects and potential vulnerability,experiments were performed with organisms from two estuaries with differing histories of exposure to environmental contamination. Biomarkers related to mode of action of sertraline were employed to assess effects of environmentally realistic concentrations of sertraline at two salinity levels. Synergism and antagonism were identified for biomarkers of cholinergic neurotransmission, energy production,anti-oxidant defences and oxidative damage. Different interactions were found for the two study sites highlighting the need to account for differences in tolerance of local ecological receptors in risk evaluations.

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The impact of metals (Cd, Cr, Cu and Zn) on growth, cell volume and cell division of the freshwateralga Pseudokirchneriella subcapitata exposed over a period of 72 h was investigated. The algal cells wereexposed to three nominal concentrations of each metal: low (closed to 72 h-EC10values), intermediate(closed to 72 h-EC50values) and high (upper than 72 h-EC90values). The exposure to low metal concen-trations resulted in a decrease of cell volume. On the contrary, for the highest metal concentrations anincrease of cell volume was observed; this effect was particularly notorious for Cd and less pronouncedfor Zn. Two behaviours were found when algal cells were exposed to intermediate concentrations ofmetals: Cu(II) and Cr(VI) induced a reduction of cell volume, while Cd(II) and Zn(II) provoked an oppositeeffect. The simultaneous nucleus staining and cell image analysis, allowed distinguishing three phases inP. subcapitata cell cycle: growth of mother cell; cell division, which includes two divisions of the nucleus;and, release of four autospores. The exposure of P. subcapitata cells to the highest metal concentrationsresulted in the arrest of cell growth before the first nucleus division [for Cr(VI) and Cu(II)] or after thesecond nucleus division but before the cytokinesis (release of autospores) when exposed to Cd(II). Thedifferent impact of metals on algal cell volume and cell-cycle progression, suggests that different toxic-ity mechanisms underlie the action of different metals studied. The simultaneous nucleus staining andcell image analysis, used in the present work, can be a useful tool in the analysis of the toxicity of thepollutants, in P. subcapitata, and help in the elucidation of their different modes of action.

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OBJECTIVE: To evaluate the predictive value of genetic polymorphisms in the context of BCG immunotherapy outcome and create a predictive profile that may allow discriminating the risk of recurrence. MATERIAL AND METHODS: In a dataset of 204 patients treated with BCG, we evaluate 42 genetic polymorphisms in 38 genes involved in the BCG mechanism of action, using Sequenom MassARRAY technology. Stepwise multivariate Cox Regression was used for data mining. RESULTS: In agreement with previous studies we observed that gender, age, tumor multiplicity and treatment scheme were associated with BCG failure. Using stepwise multivariate Cox Regression analysis we propose the first predictive profile of BCG immunotherapy outcome and a risk score based on polymorphisms in immune system molecules (SNPs in TNFA-1031T/C (rs1799964), IL2RA rs2104286 T/C, IL17A-197G/A (rs2275913), IL17RA-809A/G (rs4819554), IL18R1 rs3771171 T/C, ICAM1 K469E (rs5498), FASL-844T/C (rs763110) and TRAILR1-397T/G (rs79037040) in association with clinicopathological variables. This risk score allows the categorization of patients into risk groups: patients within the Low Risk group have a 90% chance of successful treatment, whereas patients in the High Risk group present 75% chance of recurrence after BCG treatment. CONCLUSION: We have established the first predictive score of BCG immunotherapy outcome combining clinicopathological characteristics and a panel of genetic polymorphisms. Further studies using an independent cohort are warranted. Moreover, the inclusion of other biomarkers may help to improve the proposed model.

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Artificial Intelligence has been applied to dynamic games for many years. The ultimate goal is creating responses in virtual entities that display human-like reasoning in the definition of their behaviors. However, virtual entities that can be mistaken for real persons are yet very far from being fully achieved. This paper presents an adaptive learning based methodology for the definition of players’ profiles, with the purpose of supporting decisions of virtual entities. The proposed methodology is based on reinforcement learning algorithms, which are responsible for choosing, along the time, with the gathering of experience, the most appropriate from a set of different learning approaches. These learning approaches have very distinct natures, from mathematical to artificial intelligence and data analysis methodologies, so that the methodology is prepared for very distinct situations. This way it is equipped with a variety of tools that individually can be useful for each encountered situation. The proposed methodology is tested firstly on two simpler computer versus human player games: the rock-paper-scissors game, and a penalty-shootout simulation. Finally, the methodology is applied to the definition of action profiles of electricity market players; players that compete in a dynamic game-wise environment, in which the main goal is the achievement of the highest possible profits in the market.

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Human exposure to persistent organic pollutants (POPs) is a certainty, even to long banned pesticides like o,p′-dichlorodiphenyltrichloroethane (o,p′-DDT), and its metabolites p,p′-dichlorodiphenyldichloroethylene (p,p′-DDE), and p,p′-dichlorodiphenyldichloroethane (p,p′-DDD). POPs are known to be particularly toxic and have been associated with endocrine-disrupting effects in several mammals, including humans even at very low doses. As environmental estrogens, they could play a critical role in carcinogenesis, such as in breast cancer. With the purpose of evaluating their effect on breast cancer biology, o,p′-DDT, p,p′-DDE, and p,p′-DDD (50–1000 nM) were tested on two human breast adenocarcinoma cell lines: MCF-7 expressing estrogen receptor (ER) α and MDA-MB-231 negative for ERα, regarding cell proliferation and viability in addition to their invasive potential. Cell proliferation and viability were not equally affected by these compounds. In MCF-7 cells, the compounds were able to decrease cell proliferation and viability. On the other hand, no evident response was observed in treated MDA-MB-231 cells. Concerning the invasive potential, the less invasive cell line, MCF-7, had its invasion potential significantly induced, while the more invasive cell line MDA-MB-231, had its invasion potential dramatically reduced in the presence of the tested compounds. Altogether, the results showed that these compounds were able to modulate several cancer-related processes, namely in breast cancer cell lines, and underline the relevance of POP exposure to the risk of cancer development and progression, unraveling distinct pathways of action of these compounds on tumor cell biology.

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Sertraline is widely prescribed worldwide and frequently detected in aquatic systems. There is, however, a remarkable gap of information on its potential impact on estuarine and coastal invertebrates. This study investigated sertraline accumulation and effects in Carcinus maenas. Crabs from a moderately contaminated (Lima) and a low-impacted (Minho) estuary were exposed to environmental and high levels of sertraline (0.05, 5, 500 μg L−1). A battery of biomarkers related to sertraline mode of action was employed to assess neurotransmission, energy metabolism, biotransformation and oxidative stress pathways. After a seven-day exposure, sertraline accumulation in crabs’ soft tissues was found in Lima (5 μg L−1: 15.3 ng L−1 ww; 500 μg L−1: 1010 ng L−1 ww) and Minho (500 μg L−1: 605 ng L−1 ww) animals. Lima crabs were also more sensitive to sertraline than those from Minho, exhibiting decreased acetylcholinesterase activity, indicative of ventilatory and locomotory dysfunction, inhibition of anti-oxidant enzymes and increased oxidative damage at ≥0.05 μg L−1. The Integrated Biomarker Response (IBR) index indicated their low health status. In addition, Minho crabs showed non-monotonic responses of acetylcholinesterase suggestive of hormesis. The results pointed an influence of the exposure history on differential sensitivity to sertraline and the need to perform evaluations with site-specific ecological receptors to increase relevance of risk estimations when extrapolating from laboratory to field conditions.

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Dada a sua estrutura organizacional complexa e a natureza delicada do serviço prestado, os hospitais carecem de uma gestão eficaz e eficiente que os transforme em organizações de excelência. Fatores externos derivados das atuais imposições governamentais, como a necessidade de reorganização dos serviços no sentido de contenção de custos, a obtenção de resultados económicos positivos e, a incessante necessidade dos utentes em obter um atendimento de qualidade, são fatores que não simplificam o problema. As melhorias da qualidade dos serviços de saúde têm sido difíceis de implementar em Portugal, não só porque estas exigem uma mudança fundamental na forma de pensar e de agir que conduzam à alteração de comportamentos, hábitos e de práticas estabelecidas, mas também, porque estes processos requerem tempo, resiliência e uma participação ativa do Estado, e demais entidades reguladoras. A exigência neste processo torna-se fundamental ao nível da segurança, flexibilidade e da atuação sobre fatores estruturais e comportamentais, dado que os conceitos de economia, eficiência e eficácia são transversais a todos os procedimentos, desde o ato de atendimento, à qualidade dos serviços prestados por todos os profissionais e à performance global dos atores envolvidos. No entanto, apesar da importância de que se reveste um processo de mudança, o conhecimento de facto, por si só, não é suficiente para desencadear e manter esta transformação, ainda não existe uma clara e concreta a correlação entre análise e ação. Entende-se por isso, a necessidade do desenvolvimento do benchmarking hospitalar, integrado na filosofia do Balanced Scorecard, complementado com a opinião dos utentes e dos profissionais destes serviços de saúde, comparando o setor público com o privado. Após efetuada a análise aos dados recolhidos, recorrendo à utilização das metodologias previamente identificadas, concluimos que, a generalidade das hipóteses formuladas se verificaram, tendo, por isso, alcançado os objetivos a que nos propusemos nesta investigação.

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Dissertação para obtenção do Grau de Doutor em Engenharia Electrotécnica e de Computadores

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High-content analysis has revolutionized cancer drug discovery by identifying substances that alter the phenotype of a cell, which prevents tumor growth and metastasis. The high-resolution biofluorescence images from assays allow precise quantitative measures enabling the distinction of small molecules of a host cell from a tumor. In this work, we are particularly interested in the application of deep neural networks (DNNs), a cutting-edge machine learning method, to the classification of compounds in chemical mechanisms of action (MOAs). Compound classification has been performed using image-based profiling methods sometimes combined with feature reduction methods such as principal component analysis or factor analysis. In this article, we map the input features of each cell to a particular MOA class without using any treatment-level profiles or feature reduction methods. To the best of our knowledge, this is the first application of DNN in this domain, leveraging single-cell information. Furthermore, we use deep transfer learning (DTL) to alleviate the intensive and computational demanding effort of searching the huge parameter's space of a DNN. Results show that using this approach, we obtain a 30% speedup and a 2% accuracy improvement.

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Thesis submitted in Trinity Term 2001 for the degree of Master of Philosophy, Worcester College, Oxford