Heavy-metal resistance in Marinobacter aquaeolei 617 insights into copper resistance

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

Technology market transfer plan launch of DELIVES to E.U. Market©

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

Modelação numérica de uma caldeira doméstica a pellets

A biomassa é uma das fontes de energia renovável com maior potencial em Portugal, sendo a capacidade de produção de pellets de biomassa atualmente instalada superior a 1 milhão de toneladas/ano. Contudo, a maioria desta produção destina-se à exportação ou à utilização em centrais térmicas a biomassa, cujo crescimento tem sido significativo nos últimos anos, prevendo-se que a capacidade instalada em 2020 seja de aproximadamente 250 MW. O mercado português de caldeiras a pellets é bastante diversificado. O estudo que realizamos permitiu concluir que cerca de 90% das caldeiras existentes no mercado português têm potências inferiores a 60 kW, possuindo na sua maioria grelha fixa (81%), com sistema de ignição eléctrica (92%) e alimentação superior do biocombustível sólido (94%). O objetivo do presente trabalho foi o desenvolvimento de um modelo para simulação de uma caldeira a pellets de biomassa, que para além de permitir otimizar o projeto e operação deste tipo de equipamento, permitisse avaliar as inovações tecnológicas nesta área. Para tal recorreu-se o BiomassGasificationFoam, um código recentemente publicado, e escrito para utilização com o OpenFOAM, uma ferramenta computacional de acesso livre, que permite a simulação dos processos de pirólise, gasificação e combustão de biomassa. Este código, que foi inicialmente desenvolvido para descrever o processo de gasificação na análise termogravimétrica de biomassa, foi por nós adaptado para considerar as reações de combustão em fase gasosa dos gases libertados durante a pirólise da biomassa (recorrendo para tal ao solver reactingFoam), e ter a possibilidade de realizar a ignição da biomassa, o que foi conseguido através de uma adaptação do código de ignição do XiFoam. O esquema de ignição da biomassa não se revelou adequado, pois verificou-se que a combustão parava sempre que a ignição era inativada, independentemente do tempo que ela estivesse ativa. Como alternativa, usaram-se outros dois esquemas para a combustão da biomassa: uma corrente de ar quente, e uma resistência de aquecimento. Ambos os esquemas funcionaram, mas nunca foi possível fazer com que a combustão fosse autossustentável. A análise dos resultados obtidos permitiu concluir que a extensão das reações de pirólise e de gasificação, que são ambas endotérmicas, é muito pequena, pelo que a quantidade de gases libertados é igualmente muito pequena, não sendo suficiente para libertar a energia necessária à combustão completa da biomassa de uma maneira sustentável. Para tentar ultrapassar esta dificuldade foram testadas várias alternativas, , que incluíram o uso de diferentes composições de biomassa, diferentes cinéticas, calores de reação, parâmetros de transferência de calor, velocidades do ar de alimentação, esquemas de resolução numérica do sistema de equações diferenciais, e diferentes parâmetros dos esquemas de resolução utilizados. Todas estas tentativas se revelaram infrutíferas. Este estudo permitiu concluir que o solver BiomassGasificationFoam, que foi desenvolvido para descrever o processo de gasificação de biomassa em meio inerte, e em que a biomassa é aquecida através de calor fornecido pelas paredes do reator, aparentemente não é adequado à descrição do processo de combustão da biomassa, em que a combustão deve ser autossustentável, e em que as reações de combustão em fase gasosa são importantes. Assim, é necessário um estudo mais aprofundado que permita adaptar este código à simulação do processo de combustão de sólidos porosos em leito fixo.

Development of electrospun Ion jelly fibers® for drug delivery

Dissertação para obtenção do Grau de Mestre em Biotecnologia

Assessing and comparing the total antioxidant capacity of commercial beverages: application to beers, wines, waters and soft drinks using TRAP, TEAC and FRAP methods.

This work measures and tries to compare the Antioxidant Capacity (AC) of 50 commercial beverages of different kinds: 6 wines, 12 beers, 18 soft drinks and 14 flavoured waters. Because there is no reference procedure established for this purpose, three different optical methods were used to analyse these samples: Total Radical trapping Antioxidant Parameter (TRAP), Trolox Equivalent Antioxidant Capacity (TEAC) and Ferric ion Reducing Antioxidant Parameter (FRAP). These methods differ on the chemical background and nature of redox system. The TRAP method involves the transfer of hydrogen atoms while TEAC and FRAP involves electron transfer reactions. The AC was also assessed against three antioxidants of reference, Ascorbic acid (AA), Gallic acid (GA) and 6-hydroxy-2,5,7,8-tetramethyl- 2-carboxylic acid (Trolox). The results obtained were analyzed statistically. Anova one-way tests were applied to all results and suggested that methods and standards exhibited significant statistical differences. The possible effect of sample features in the AC, such as gas, flavours, food colouring, sweeteners, acidity regulators, preservatives, stabilizers, vitamins, juice percentage, alcohol percentage, antioxidants and the colour was also investigated. The AC levels seemed to change with brand, kind of antioxidants added, and kind of flavour, depending on the sample. In general, higher ACs were obtained for FRAP as method, and beer for kind of sample, and the standard expressing the smaller AC values was GA.

Measuring the cytochrome c nitrite reductase activity—practical considerations on the enzyme assays

Hindawi Publishing Corporation Bioinorganic Chemistry and Applications Volume 2010, Article ID 634597, 8 pages

The effect of water inorganic matrix in ibuprofen adsorption onto activated carbon for water and wastewater treatment

Dissertação para obtenção do Grau de Mestre em Engenharia Química e Bioquímica

Kinetics of growth of Leishmania (Leishmania) chagasi cycle in McCoy cell culture

The kinetics of growth of Leishmania performed in vitro after internalization of the promastigote form in the cell and the occurrence of the transformation of the parasite into the amastigote form have been described by several authors. They used explants of macrophages in hamster spleen cell culture or in a human macrophage lineage cell, the U937. Using microscopy, the description of morphologic inter-relationship and the analysis of the production of specific molecules, it has been possible to define some of the peculiarities of the biology of the parasite. The present study shows the growth cycle of Leishmania chagasi during the observation of kinetic analysis undertaken with a McCoy cell lineage that lasted for a period of 144 hours. During the process, the morphologic transformation was revealed by indirect immunofluorescence (IF) and the molecules liberated in the extra cellular medium were observed by SDS-PAGE at 24-hour intervals during the whole 144-hour period. It was observed that in the first 72 hours the promastigote form of L. chagasi adhered to the cell membranes and assumed a rounded (amastigote-like) form. At 96 hours the infected cells showed morphologic alterations; at 120 hours the cells had liberated soluble fluorescent antigens into the extra cellular medium. At 144 hours, new elongated forms of the parasites, similar to promastigotes, were observed. In the SDS-PAGE, specific molecular weight proteins were observed at each point of the kinetic analysis showing that the McCoy cell imitates the macrophage and may be considered a useful model for the study of the infection of the Leishmania/cell binomial.

Alterations in lipid transfer to High-Density Lipoprotein (HDL) and activity of paraoxonase-1 in HIV+ patients

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.

Measuring data transfer in heterogeneous IoT environments

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

High-Content Analysis of Breast Cancer Using Single-Cell Deep Transfer Learning

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.

Insight into the multicopper oxidases stability

Dissertation presented to obtain the PhD degree in Biochemistry

The mechanism of formate oxidation by metal-dependent formate dehydrogenases

J Biol Inorg Chem (2011) 16:1255–1268 DOI 10.1007/s00775-011-0813-8

The electron transfer complex between nitrous oxide reductase and its electron donors

J Biol Inorg Chem (2011) 16:1241–1254 DOI 10.1007/s00775-011-0812-9

New spectroscopic and electrochemical insights on a class I superoxide reductase: evidence for an intramolecular electron-transfer pathway

Biochem. J. (2011) 438,485–494 doi:10.1042/BJ20110836