Biochemical and structural characterization of β-lactamases tem-180 and tem-201

With the constant development of new antibiotics, selective pressure is a force to reckon when investigating antibiotic resistance. Although advantageous for medical treatments, it leads to increasing resistance. It is essential to use more potent and toxic antibiotics. Enzymes capable of hydrolyzing antibiotics are among the most common ways of resistance and TEM variants have been detected in several resistant isolates. Due to the rapid evolution of these variants, complex phenotypes have emerged and the need to understand their biological activity becomes crucial. To investigate the biochemical properties of TEM-180 and TEM-201 several computational methodologies have been used, allowing the comprehension of their structure and catalytic activity, which translates into their biological phenotype. In this work we intent to characterize the interface between these proteins and the several antibiotics used as ligands. We performed explicit solvent molecular dynamics (MD) simulations of these complexes and studied a variety of structural and energetic features. The interfacial residues show a distinct behavior when in complex with different antibiotics. Nevertheless, it was possible to identify some common Hot Spots among several complexes – Lys73, Tyr105 and Glu166. The structural changes that occur during the Molecular Dynamic (MD) simulation lead to the conclusion that these variants have an inherent capacity of adapting to the various antibiotics. This capability might be the reason why they can hydrolyze antibiotics that have not been described until now to be degraded by TEM variants. The results obtained with computational and experimental methodologies for the complex with Imipenem have shown that in order to this type of enzymes be able to acylate the antibiotics, they need to be capable to protect the ligand from water molecules.

Distributed energy resource short-term scheduling using signaled particle swarm optimization

Distributed Energy Resources (DER) scheduling in smart grids presents a new challenge to system operators. The increase of new resources, such as storage systems and demand response programs, results in additional computational efforts for optimization problems. On the other hand, since natural resources, such as wind and sun, can only be precisely forecasted with small anticipation, short-term scheduling is especially relevant requiring a very good performance on large dimension problems. Traditional techniques such as Mixed-Integer Non-Linear Programming (MINLP) do not cope well with large scale problems. This type of problems can be appropriately addressed by metaheuristics approaches. This paper proposes a new methodology called Signaled Particle Swarm Optimization (SiPSO) to address the energy resources management problem in the scope of smart grids, with intensive use of DER. The proposed methodology’s performance is illustrated by a case study with 99 distributed generators, 208 loads, and 27 storage units. The results are compared with those obtained in other methodologies, namely MINLP, Genetic Algorithm, original Particle Swarm Optimization (PSO), Evolutionary PSO, and New PSO. SiPSO performance is superior to the other tested PSO variants, demonstrating its adequacy to solve large dimension problems which require a decision in a short period of time.

Antifungal activity of Imidazolidin-4-ones of the antimalarial primaquine

The 5-Isopropyl-3-[4-(6-methoxy-quinolin-8-ylamino)-pentyl]-2,2-dimethyl-imidazolidin-4-one (ValPQacet) was sinthesized through acylation of the anti-malarial primaquine with α-valine and subsequent reaction of the resulting -aminoamide with propanone (Sheme 1).Imidazolidin-4-ones of the anti malarial primaquine are being sinthesized to develop new variants in order to improve more effective treatments against malaria . Recently it has been observed that primaquine derivates could have effect in a new kind of yeast . To study the fungicidal activity against Candida albicans, Candida tropicalis, Issatchenkia orientalis, Sacharomyces cerevisae, the ValPQacet was put in the form of the hydrochloride salt. The minimal inhibitory concentration (MIC) could be determined for all yeast in the concentration range assayed. Also was determined MIC’s of primaquine hydrochloride salt for all yeast, and this shows that the parent drug is less active than our compound. Further studies are being performed to determine viability and cellular injury with this drugs.

Análise de risco em sequenciamento de actividades com restrições de recursos

Mestrado em Engenharia Electrotécnica e de Computadores. Área de Especialização em Sistemas e Planeamento Industrial.

Modelo generalista de páginas Web para motores de pesquisa com interface 3D

Web tornou-se uma ferramenta indispensável para a sociedade moderna. A capacidade de aceder a enormes quantidades de informação, disponível em praticamente todo o mundo, é uma grande vantagem para as nossas vidas. No entanto, a quantidade avassaladora de informação disponível torna-se um problema, que é o de encontrar a informação que precisamos no meio de muita informação irrelevante. Para nos ajudar nesta tarefa, foram criados poderosos motores de pesquisa online, que esquadrinham a Web à procura dos melhores resultados, segundo os seus critérios, para os dados que precisamos. Actualmente, os motores de pesquisa em voga, usam um formato de apresentação de resultados simples, que consiste apenas numa caixa de texto para o utilizador inserir as palavras-chave sobre o tema que quer pesquisar e os resultados são dispostos sobre uma lista de hiperligações ordenada pela relevância que o motor atribui a cada resultado. Porém, existem outras formas de apresentar resultados. Uma das alternativas é apresentar os resultados sobre interfaces em 3 dimensões. É nestes tipos de sistemas que este trabalho vai incidir, os motores de pesquisa com interfaces em 3 dimensões. O problema é que as páginas Web não estão preparadas para serem consumidas por este tipo de motores de pesquisa. Para resolver este problema foi construído um modelo generalista para páginas Web, que consegue alimentar os requisitos das diversas variantes destes motores de pesquisa. Foi também desenvolvido um protótipo de instanciação automático, que recolhe as informações necessárias das páginas Web e preenche o modelo.

New insights on integer-programming models for the kidney exchange problem

In recent years several countries have set up policies that allow exchange of kidneys between two or more incompatible patient–donor pairs. These policies lead to what is commonly known as kidney exchange programs. The underlying optimization problems can be formulated as integer programming models. Previously proposed models for kidney exchange programs have exponential numbers of constraints or variables, which makes them fairly difficult to solve when the problem size is large. In this work we propose two compact formulations for the problem, explain how these formulations can be adapted to address some problem variants, and provide results on the dominance of some models over others. Finally we present a systematic comparison between our models and two previously proposed ones via thorough computational analysis. Results show that compact formulations have advantages over non-compact ones when the problem size is large.

Application-specific modified particle swarm optimization for energy resource scheduling considering vehicle-to-grid

This paper presents a modified Particle Swarm Optimization (PSO) methodology to solve the problem of energy resources management with high penetration of distributed generation and Electric Vehicles (EVs) with gridable capability (V2G). The objective of the day-ahead scheduling problem in this work is to minimize operation costs, namely energy costs, regarding he management of these resources in the smart grid context. The modifications applied to the PSO aimed to improve its adequacy to solve the mentioned problem. The proposed Application Specific Modified Particle Swarm Optimization (ASMPSO) includes an intelligent mechanism to adjust velocity limits during the search process, as well as self-parameterization of PSO parameters making it more user-independent. It presents better robustness and convergence characteristics compared with the tested PSO variants as well as better constraint handling. This enables its use for addressing real world large-scale problems in much shorter times than the deterministic methods, providing system operators with adequate decision support and achieving efficient resource scheduling, even when a significant number of alternative scenarios should be considered. The paper includes two realistic case studies with different penetration of gridable vehicles (1000 and 2000). The proposed methodology is about 2600 times faster than Mixed-Integer Non-Linear Programming (MINLP) reference technique, reducing the time required from 25 h to 36 s for the scenario with 2000 vehicles, with about one percent of difference in the objective function cost value.

Nonmonotone hybrid tabu search for inequalities and equalities: an experimental study

The main goal of this paper is to analyze the behavior of nonmono- tone hybrid tabu search approaches when solving systems of nonlinear inequalities and equalities through the global optimization of an appro- priate merit function. The algorithm combines global and local searches and uses a nonmonotone reduction of the merit function to choose the local search. Relaxing the condition aims to call the local search more often and reduces the overall computational e ort. Two variants of a perturbed pattern search method are implemented as local search. An experimental study involving a variety of problems available in the lit- erature is presented.

Regulation of histone H2A.Z expression is mediated by sirtuin 1 in prostate cancer

Histone variants seem to play a major role in gene expression regulation. In prostate cancer, H2A.Z and its acetylated form are implicated in oncogenes’ upregulation. SIRT1, which may act either as tumor suppressor or oncogene, reduces H2A.Z levels in cardiomyocytes, via proteasome-mediated degradation, and this mechanism might be impaired in prostate cancer cells due to sirtuin 1 downregulation. Thus, we aimed to characterize the mechanisms underlying H2A.Z and SIRT1 deregulation in prostate carcinogenesis and how they interact. We found that H2AFZ and SIRT1 were up- and downregulated, respectively, at transcript level in primary prostate cancer and high-grade prostatic intraepithelial neoplasia compared to normal prostatic tissues. Induced SIRT1 overexpression in prostate cancer cell lines resulted in almost complete absence of H2A.Z. Inhibition of mTOR had a modest effect on H2A.Z levels, but proteasome inhibition prevented the marked reduction of H2A.Z due to sirtuin 1 overexpression. Prostate cancer cells exposed to epigenetic modifying drugs trichostatin A, alone or combined with 5-aza-2’-deoxycytidine, increased H2AFZ transcript, although with a concomitant decrease in protein levels. Conversely, SIRT1 transcript and protein levels increased after exposure. ChIP revealed an increase of activation marks within the TSS region for both genes. Remarkably, inhibition of sirtuin 1 with nicotinamide, increased H2A.Z levels, whereas activation of sirtuin 1 by resveratrol led to an abrupt decrease in H2A.Z. Finally, protein-ligation assay showed that exposure to epigenetic modifying drugs fostered the interaction between sirtuin 1 and H2A.Z. We concluded that sirtuin 1 and H2A.Z deregulation in prostate cancer are reciprocally related. Epigenetic mechanisms, mostly histone post-translational modifications, are likely involved and impair sirtuin 1-mediated downregulation of H2A.Z via proteasome-mediated degradation. Epigenetic modifying drugs in conjunction with enzymatic modulators are able to restore the normal functions of sirtuin 1 and might constitute relevant tools for targeted therapy of prostate cancer patients

Extending fixed task-priority schedulability by interference limitation

While the earliest deadline first algorithm is known to be optimal as a uniprocessor scheduling policy, the implementation comes at a cost in terms of complexity. Fixed taskpriority algorithms on the other hand have lower complexity but higher likelihood of task sets being declared unschedulable, when compared to earliest deadline first (EDF). Various attempts have been undertaken to increase the chances of proving a task set schedulable with similar low complexity. In some cases, this was achieved by modifying applications to limit preemptions, at the cost of flexibility. In this work, we explore several variants of a concept to limit interference by locking down the ready queue at certain instances. The aim is to increase the prospects of schedulability of a given task system, without compromising on complexity or flexibility, when compared to the regular fixed task-priority algorithm. As a final contribution, a new preemption threshold assignment algorithm is provided which is less complex and more straightforward than the previous method available in the literature.

Multi-criteria optimization manipulator trajectory planning

In the last twenty years genetic algorithms (GAs) were applied in a plethora of fields such as: control, system identification, robotics, planning and scheduling, image processing, and pattern and speech recognition (Bäck et al., 1997). In robotics the problems of trajectory planning, collision avoidance and manipulator structure design considering a single criteria has been solved using several techniques (Alander, 2003). Most engineering applications require the optimization of several criteria simultaneously. Often the problems are complex, include discrete and continuous variables and there is no prior knowledge about the search space. These kind of problems are very more complex, since they consider multiple design criteria simultaneously within the optimization procedure. This is known as a multi-criteria (or multiobjective) optimization, that has been addressed successfully through GAs (Deb, 2001). The overall aim of multi-criteria evolutionary algorithms is to achieve a set of non-dominated optimal solutions known as Pareto front. At the end of the optimization procedure, instead of a single optimal (or near optimal) solution, the decision maker can select a solution from the Pareto front. Some of the key issues in multi-criteria GAs are: i) the number of objectives, ii) to obtain a Pareto front as wide as possible and iii) to achieve a Pareto front uniformly spread. Indeed, multi-objective techniques using GAs have been increasing in relevance as a research area. In 1989, Goldberg suggested the use of a GA to solve multi-objective problems and since then other researchers have been developing new methods, such as the multi-objective genetic algorithm (MOGA) (Fonseca & Fleming, 1995), the non-dominated sorted genetic algorithm (NSGA) (Deb, 2001), and the niched Pareto genetic algorithm (NPGA) (Horn et al., 1994), among several other variants (Coello, 1998). In this work the trajectory planning problem considers: i) robots with 2 and 3 degrees of freedom (dof ), ii) the inclusion of obstacles in the workspace and iii) up to five criteria that are used to qualify the evolving trajectory, namely the: joint traveling distance, joint velocity, end effector / Cartesian distance, end effector / Cartesian velocity and energy involved. These criteria are used to minimize the joint and end effector traveled distance, trajectory ripple and energy required by the manipulator to reach at destination point. Bearing this ideas in mind, the paper addresses the planning of robot trajectories, meaning the development of an algorithm to find a continuous motion that takes the manipulator from a given starting configuration up to a desired end position without colliding with any obstacle in the workspace. The chapter is organized as follows. Section 2 describes the trajectory planning and several approaches proposed in the literature. Section 3 formulates the problem, namely the representation adopted to solve the trajectory planning and the objectives considered in the optimization. Section 4 studies the algorithm convergence. Section 5 studies a 2R manipulator (i.e., a robot with two rotational joints/links) when the optimization trajectory considers two and five objectives. Sections 6 and 7 show the results for the 3R redundant manipulator with five goals and for other complementary experiments are described, respectively. Finally, section 8 draws the main conclusions.

Modified particle swarm optimization for day-ahead distributed energy resources scheduling including vehicle-to-grid

Mestrado em Engenharia Electrotécnica – Sistemas Eléctricos de Energia

Application-Specific Modified Particle Swarm Optimization for energy resource scheduling considering vehicle-to-grid

This paper presents a modified Particle Swarm Optimization (PSO) methodology to solve the problem of energy resources management with high penetration of distributed generation and Electric Vehicles (EVs) with gridable capability (V2G). The objective of the day-ahead scheduling problem in this work is to minimize operation costs, namely energy costs, regarding the management of these resources in the smart grid context. The modifications applied to the PSO aimed to improve its adequacy to solve the mentioned problem. The proposed Application Specific Modified Particle Swarm Optimization (ASMPSO) includes an intelligent mechanism to adjust velocity limits during the search process, as well as self-parameterization of PSO parameters making it more user-independent. It presents better robustness and convergence characteristics compared with the tested PSO variants as well as better constraint handling. This enables its use for addressing real world large-scale problems in much shorter times than the deterministic methods, providing system operators with adequate decision support and achieving efficient resource scheduling, even when a significant number of alternative scenarios should be considered. The paper includes two realistic case studies with different penetration of gridable vehicles (1000 and 2000). The proposed methodology is about 2600 times faster than Mixed-Integer Non-Linear Programming (MINLP) reference technique, reducing the time required from 25 h to 36 s for the scenario with 2000 vehicles, with about one percent of difference in the objective function cost value.

Organização e disposição dos armazéns

Relatório de Estágio Curricular apresentado ao Instituto Superior de Contabilidade e Administração do Porto para obtenção do Grau de Mestre em Logística Orientado pelo Doutor Júlio Faceira Guedes Coorientado pelo Engenheiro Ricardo Costa Moreira

Stability of the Transthyretin Molecule as a Key Factor in

Transthyretin (TTR) protects against A-Beta toxicity by binding the peptide thus inhibiting its aggregation. Previous work showed different TTR mutations interact differently with A-Beta, with increasing affinities correlating with decreasing amyloidogenecity of the TTR mutant; this did not impact on the levels of inhibition of A-Beta aggregation, as assessed by transmission electron microscopy. Our work aimed at probing differences in binding to A-Beta by WT, T119M and L55P TTR using quantitative assays, and at identifying factors affecting this interaction. We addressed the impact of such factors in TTR ability to degrade A-Beta. Using a dot blot approach with the anti-oligomeric antibody A11, we showed that A-Beta formed oligomers transiently, indicating aggregation and fibril formation, whereas in the presence of WT and T119M TTR the oligomers persisted longer, indicative that these variants avoided further aggregation into fibrils. In contrast, L55PTTR was not able to inhibit oligomerization or to prevent evolution to aggregates and fibrils. Furthermore, apoptosis assessment showed WT and T119M TTR were able to protect against A-Beta toxicity. Because the amyloidogenic potential of TTR is inversely correlated with its stability, the use of drugs able to stabilize TTR tetrameric fold could result in increased TTR/ABeta binding. Here we showed that iododiflunisal, 3-dinitrophenol, resveratrol, [2-(3,5-dichlorophenyl)amino] (DCPA) and [4- (3,5-difluorophenyl)] (DFPB) were able to increase TTR binding to A-Beta; however only DCPA and DFPB improved TTR proteolytic activity. Thyroxine, a TTR ligand, did not influence TTR/A-Beta interaction and A-Beta degradation by TTR, whereas RBP, another TTR ligand, not only obstructed the interaction but also inhibited TTR proteolytic activity. Our results showed differences between WT and T119M TTR, and L55PTTR mutant regarding their interaction with A-Beta and prompt the stability of TTR as a key factor in this interaction, which may be relevant in AD pathogenesis and for the design of therapeutic TTR-based therapies.