971 resultados para transfer pricing
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Pharmaceutical spending in many other countries has had a steep increase in the last decade. The Portuguese Government has adopted several measures to reduce pharmaceutical expenditure growth, ranging from increased co-payments to price decreases determined administratively. Promotion of generic consumption has also ranked high in political priorities. We assess the overall impact of the several policy measures on total pharmaceutical spending, using monthly data over the period January 1995 – August 2008. Endogenous structural breaks (time-series) methods were employed. Our findings suggest that policy measures aimed at controlling pharmaceutical expenditure have been, in general, unsuccessful. Two breaks were identified. Both coincide with administratively determined price decreases. Measures aimed at increasing competition in the market had no visible effect on the dynamics of Government spending in pharmaceutical products. In particular, the introduction of reference pricing had only a transitory effect of less than one year, with historical growth resuming quickly. The consequence of it is a transfer of financial burden from the Government to the patients, with no apparent effect on the dynamics of pharmaceutical spending. This strongly suggests that pharmaceutical companies have been able to adjust to policy measures, in order to sustain their sales. It remains a challenge for the future to identify firms’ strategies that supported continued growth of sales, despite the several policy measures adop
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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Biotecnologia
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Dissertação para obtenção do Grau de Doutor em Engenharia Física
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HIV+ patients often develop alterations of the plasma lipids that may implicate in development of premature coronary artery disease. High-density lipoprotein (HDL) has an important role in preventing atherogenesis and the aim of this study was to investigate aspects of HDL function in HIV+ patients. HIV+ patients (n = 48) and healthy control subjects (n = 45) of both sexes with similar age were studied. Twenty-five were not being treated with antiretroviral agents, 13 were under reverse transcriptase inhibitor nucleosidic and non-nucleosidic (NRTI+NNRTI) and 10 were under NRTI + protease inhibitors (NRTI+PI) treatment. Paraoxonase 1 (PON1) activity and the transfer of free and esterified cholesterol, tryglicerides and phospholipids from a lipidic nanoemulsion to HDL were analyzed. In comparison with healthy controls, HIV+ patients presented low PON-1 activity and diminished transfer of free cholesterol and tryglicerides. In contrast, phospholipid transfer was increased in those patients, whereas the transfer of cholesteryl esters was unchanged. NRTI+NNRTI increases the transfer of cholesteryl esters and triglycerides but in NRTI+PI there was no difference in respect to non-treated HIV+ patients. HDL from HIV+ patients has smaller antioxidant properties, as shown by lower PON-1 activity, and the transfer of lipids to this lipoprotein fraction is also altered, suggesting that HDL function is defective in those patients.
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Dissertação para obtenção do Grau de Mestre 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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J Biol Inorg Chem (2011) 16:1241–1254 DOI 10.1007/s00775-011-0812-9
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Biochem. J. (2011) 438,485–494 doi:10.1042/BJ20110836
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J Biol Inorg Chem (2011) 16:881–888 DOI 10.1007/s00775-011-0785-8
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Biochemistry. 2008 Oct 14;47(41):10852-62. doi: 10.1021/bi801375q
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J Biol Inorg Chem (2007) 12:691–698 DOI 10.1007/s00775-007-0219-9
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J Biol Inorg Chem (2006) 11: 433–444 DOI 10.1007/s00775-006-0090-0
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J Biol Inorg Chem (2004) 9: 839–849 DOI 10.1007/s00775-004-0584-6
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Dissertação para obtenção do Grau de Doutor em Bioquímica, ramo de Biotecnologia
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A dialyzable transfer factor (TFd) was obtained from spleen cells, of mice vaccinated with the avirulent PF strain of Trypanosoma cruzi. This factor reduced significahtly the parasitemia of animals treated before or after the infection with a virulent strain of the same parasite, but does not reduced the mortality rate to a level lower than that of the control mice. It is expected that in a next future, new techniques in the use ofsuch factor will bring better resutts.