Design of bio-inspired ionic liquids for protein stabilisation

Ionic Liquids (ILs) consist in organic salts that are liquid at/or near room temperature. Since ILs are entirely composed of ions, the formation of ion pairs is expected to be one essential feature for describing solvation in ILs. In recent years, protein - ionic liquid (P-IL) interactions have been the subject of intensive studies mainly because of their capability to promote folding/unfolding of proteins. However, the ion pairs and their lifetimes in ILs in P-IL thematic is dismissed, since the action of ILs is therefore the result of a subtle equilibrium between anion-cation interaction, ion-solvent and ion-protein interaction. The work developed in this thesis innovates in this thematic, once the design of ILs for protein stabilisation was bio-inspired in the high concentration of organic charged metabolites found in cell milieu. Although this perception is overlooked, those combined concentrations have been estimated to be ~300 mM among the macromolecules at concentrations exceeding 300 g/L (macromolecular crowding) and transient ion-pair can naturally occur with a potential specific biological role. Hence the main objective of this work is to develop new bio-ILs with a detectable ion-pair and understand its effects on protein structure and stability, under crowding environment, using advanced NMR techniques and calorimetric techniques. The choline-glutamate ([Ch][Glu]) IL was synthesized and characterized. The ion-pair was detected in water solutions using mainly the selective NOE NMR technique. Through the same technique, it was possible to detect a similar ion-pair promotion under synthetic and natural crowding environments. Using NMR spectroscopy (protein diffusion, HSQC experiments, and hydrogen-deuterium exchange) and differential scanning calorimetry (DSC), the model protein GB1 (production and purification in isotopic enrichment media) it was studied in the presence of [Ch][Glu] under macromolecular crowding conditions (PEG, BSA, lysozyme). Under dilute condition, it is possible to assert that the [Ch][Glu] induces a preferential hydration by weak and non-specific interactions, which leads to a significant stabilisation. On the other hand, under crowding environment, the [Ch][Glu] ion pair is promoted, destabilising the protein by favourable weak hydrophobic interactions , which disrupt the hydration layer of the protein. However, this capability can mitigates the effect of protein crowders. Overall, this work explored the ion-pair existence and its consequences on proteins in conditions similar to cell milieu. In this way, the charged metabolites found in cell can be understood as key for protein stabilisation.

Bio-inspired anatomy for autonomous DPWS-compliant automation components

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

New fluorescent chemosensors based on bio-inspired ligands and macrocycles: from single molecules to nanoparticles

Dissertação apresentada para obtenção do grau de Doutor em Biotecnologia pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia. A presente dissertação foi preparada no âmbito do protocolo de acordo bilateral de educação avançada (ERASMUS) entre a Universidade de Vigo e a Universidade Nova de Lisboa

Probabilistic maintenance and optimization strategies for deteriorating civil infrastructures

In developed countries, civil infrastructures are one of the most significant investments of governments, corporations, and individuals. Among these, transportation infrastructures, including highways, bridges, airports, and ports, are of huge importance, both economical and social. Most developed countries have built a fairly complete network of highways to fit their needs. As a result, the required investment in building new highways has diminished during the last decade, and should be further reduced in the following years. On the other hand, significant structural deteriorations have been detected in transportation networks, and a huge investment is necessary to keep these infrastructures safe and serviceable. Due to the significant importance of bridges in the serviceability of highway networks, maintenance of these structures plays a major role. In this paper, recent progress in probabilistic maintenance and optimization strategies for deteriorating civil infrastructures with emphasis on bridges is summarized. A novel model including interaction between structural safety analysis,through the safety index, and visual inspections and non destructive tests, through the condition index, is presented. Single objective optimization techniques leading to maintenance strategies associated with minimum expected cumulative cost and acceptable levels of condition and safety are presented. Furthermore, multi-objective optimization is used to simultaneously consider several performance indicators such as safety, condition, and cumulative cost. Realistic examples of the application of some of these techniques and strategies are also presented.

Recursive neuro fuzzy techniques for online identification and control

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

Optimization of ring oscillators

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

Environmental data management in the Sado Estuary

Estuaries are perhaps the most threatened environments in the coastal fringe; the coincidence of high natural value and attractiveness for human use has led to conflicts between conservation and development. These conflicts occur in the Sado Estuary since its location is near the industrialised zone of Peninsula of Setúbal and at the same time, a great part of the Estuary is classified as a Natural Reserve due to its high biodiversity. These facts led us to the need of implementing a model of environmental management and quality assessment, based on methodologies that enable the assessment of the Sado Estuary quality and evaluation of the human pressures in the estuary. These methodologies are based on indicators that can better depict the state of the environment and not necessarily all that could be measured or analysed. Sediments have always been considered as an important temporary source of some compounds or a sink for other type of materials or an interface where a great diversity of biogeochemical transformations occur. For all this they are of great importance in the formulation of coastal management system. Many authors have been using sediments to monitor aquatic contamination, showing great advantages when compared to the sampling of the traditional water column. The main objective of this thesis was to develop an estuary environmental management framework applied to Sado Estuary using the DPSIR Model (EMMSado), including data collection, data processing and data analysis. The support infrastructure of EMMSado were a set of spatially contiguous and homogeneous regions of sediment structure (management units). The environmental quality of the estuary was assessed through the sediment quality assessment and integrated in a preliminary stage with the human pressure for development. Besides the earlier explained advantages, studying the quality of the estuary mainly based on the indicators and indexes of the sediment compartment also turns this methodology easier, faster and human and financial resource saving. These are essential factors to an efficient environmental management of coastal areas. Data management, visualization, processing and analysis was obtained through the combined use of indicators and indices, sampling optimization techniques, Geographical Information Systems, remote sensing, statistics for spatial data, Global Positioning Systems and best expert judgments. As a global conclusion, from the nineteen management units delineated and analyzed three showed no ecological risk (18.5 % of the study area). The areas of more concern (5.6 % of the study area) are located in the North Channel and are under strong human pressure mainly due to industrial activities. These areas have also low hydrodynamics and are, thus associated with high levels of deposition. In particular the areas near Lisnave and Eurominas industries can also accumulate the contamination coming from Águas de Moura Channel, since particles coming from that channel can settle down in that area due to residual flow. In these areas the contaminants of concern, from those analyzed, are the heavy metals and metalloids (Cd, Cu, Zn and As exceeded the PEL guidelines) and the pesticides BHC isomers, heptachlor, isodrin, DDT and metabolits, endosulfan and endrin. In the remain management units (76 % of the study area) there is a moderate impact potential of occurrence of adverse ecological effects and in some of these areas no stress agents could be identified. This emphasizes the need for further research, since unmeasured chemicals may be causing or contributing to these adverse effects. Special attention must be taken to the units with moderate impact potential of occurrence of adverse ecological effects, located inside the natural reserve. Non-point source pollution coming from agriculture and aquaculture activities also seem to contribute with important pollution load into the estuary entering from Águas de Moura Channel. This pressure is expressed in a moderate impact potential for ecological risk existent in the areas near the entrance of this Channel. Pressures may also came from Alcácer Channel although they were not quantified in this study. The management framework presented here, including all the methodological tools may be applied and tested in other estuarine ecosystems, which will also allow a comparison between estuarine ecosystems in other parts of the globe.

Diagnosis of an EPS module

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

A learning approach to swarm-based path detection and tracking

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

Machine diagnosis based on artificial immune systems

Nowadays, many of the manufactory and industrial system has a diagnosis system on top of it, responsible for ensuring the lifetime of the system itself. It achieves this by performing both diagnosis and error recovery procedures in real production time, on each of the individual parts of the system. There are many paradigms currently being used for diagnosis. However, they still fail to answer all the requirements imposed by the enterprises making it necessary for a different approach to take place. This happens mostly on the error recovery paradigms since the great diversity that is nowadays present in the industrial environment makes it highly unlikely for every single error to be fixed under a real time, no production stop, perspective. This work proposes a still relatively unknown paradigm to manufactory. The Artificial Immune Systems (AIS), which relies on bio-inspired algorithms, comes as a valid alternative to the ones currently being used. The proposed work is a multi-agent architecture that establishes the Artificial Immune Systems, based on bio-inspired algorithms. The main goal of this architecture is to solve for a resolution to the error currently detected by the system. The proposed architecture was tested using two different simulation environment, each meant to prove different points of views, using different tests. These tests will determine if, as the research suggests, this paradigm is a promising alternative for the industrial environment. It will also define what should be done to improve the current architecture and if it should be applied in a decentralised system.

Invited review: Models for the optimization of regional wastewater treatment systems

European Journal of Operational Research, nº 73 (1994)

Modelling and optimization of the ion exchange membrane bioreactor for removal of anionic pollutants from drinking water streams

Dissertação para obtenção do Grau de Doutor em Engenharia Química, especialidade de Engenharia Bioquímica

Constraint reasoning with local search for continuous optimization

Optimization is a very important field for getting the best possible value for the optimization function. Continuous optimization is optimization over real intervals. There are many global and local search techniques. Global search techniques try to get the global optima of the optimization problem. However, local search techniques are used more since they try to find a local minimal solution within an area of the search space. In Continuous Constraint Satisfaction Problems (CCSP)s, constraints are viewed as relations between variables, and the computations are supported by interval analysis. The continuous constraint programming framework provides branch-and-prune algorithms for covering sets of solutions for the constraints with sets of interval boxes which are the Cartesian product of intervals. These algorithms begin with an initial crude cover of the feasible space (the Cartesian product of the initial variable domains) which is recursively refined by interleaving pruning and branching steps until a stopping criterion is satisfied. In this work, we try to find a convenient way to use the advantages in CCSP branchand- prune with local search of global optimization applied locally over each pruned branch of the CCSP. We apply local search techniques of continuous optimization over the pruned boxes outputted by the CCSP techniques. We mainly use steepest descent technique with different characteristics such as penalty calculation and step length. We implement two main different local search algorithms. We use “Procure”, which is a constraint reasoning and global optimization framework, to implement our techniques, then we produce and introduce our results over a set of benchmarks.

Optimization of breast tomosynthesis image reconstruction using parallel computing

Breast cancer is the most common cancer among women, being a major public health problem. Worldwide, X-ray mammography is the current gold-standard for medical imaging of breast cancer. However, it has associated some well-known limitations. The false-negative rates, up to 66% in symptomatic women, and the false-positive rates, up to 60%, are a continued source of concern and debate. These drawbacks prompt the development of other imaging techniques for breast cancer detection, in which Digital Breast Tomosynthesis (DBT) is included. DBT is a 3D radiographic technique that reduces the obscuring effect of tissue overlap and appears to address both issues of false-negative and false-positive rates. The 3D images in DBT are only achieved through image reconstruction methods. These methods play an important role in a clinical setting since there is a need to implement a reconstruction process that is both accurate and fast. This dissertation deals with the optimization of iterative algorithms, with parallel computing through an implementation on Graphics Processing Units (GPUs) to make the 3D reconstruction faster using Compute Unified Device Architecture (CUDA). Iterative algorithms have shown to produce the highest quality DBT images, but since they are computationally intensive, their clinical use is currently rejected. These algorithms have the potential to reduce patient dose in DBT scans. A method of integrating CUDA in Interactive Data Language (IDL) is proposed in order to accelerate the DBT image reconstructions. This method has never been attempted before for DBT. In this work the system matrix calculation, the most computationally expensive part of iterative algorithms, is accelerated. A speedup of 1.6 is achieved proving the fact that GPUs can accelerate the IDL implementation.

Phage display as a tool for generation of bio-therapeutic agents for breast cancer

Notch is a conserved signalling pathway, which plays a crucial role in a multiple cellular processes such as stem cell self-renewal, cell division, proliferation and apoptosis. In mammalian, four Notch receptors and five ligands are described, where interaction is achieved through their extracellular domains, leading to a transcription activation of different target genes. Increased expression of Notch ligands has been detected in several types of cancer, including breast cancer suggesting that these proteins represent possible therapeutic targets. The goal of this work was to generate quality protein targets and, by phage display technology, select function-blocking antibodies specific for Notch ligands. Phage display is a powerful technique that allows the generation of highly specific antibodies to be used for therapeutics, and it has also proved to be a reliable approach in identifying and validating new cancer-related targets. Also, we aimed at solving the tri-dimensional structure of the Notch ligands alone and in complex with selected antibodies. In this work, the initial phase focused on the optimization of the expression and purification of a human Delta-like 1 ligand mutant construct (hDLL1-DE3), by refolding from E. coli inclusion bodies. To confirm the biological activity of the produced recombinant protein cellular functional studies were performed, revealing that treatment with hDLL1-DE3 protein led to a modulation of Notch target genes. In a second stage of this study, Antibody fragments (Fabs) specific for hDLL1-DE3 were generated by phage display, using the produced protein as target, in which one good Fab candidate was selected to determine the best expression conditions. In parallel, multiple crystallization conditions were tested with hDLL1-DE3, but so far none led to positive results.