NMR assignment of the apo-form of a Desulfovibrio gigas protein containing a novel Mo–Cu cluster

Biomol NMR Assign (2007) 1:81–83 DOI 10.1007/s12104-007-9022-3

Incorporation of either molybdenum or tungsten into formate dehydrogenase from Desulfovibrio alaskensis NCIMB 13491; EPR assignment of the proximal iron-sulfur cluster to the pterin cofactor in formate dehydrogenases from sulfate-reducing bacteria

J Biol Inorg Chem (2004) 9: 145–151 DOI 10.1007/s00775-003-0506-z

A public transport bus assignment problem: parallel metaheuristics assessment

Combinatorial Optimization Problems occur in a wide variety of contexts and generally are NP-hard problems. At a corporate level solving this problems is of great importance since they contribute to the optimization of operational costs. In this thesis we propose to solve the Public Transport Bus Assignment problem considering an heterogeneous fleet and line exchanges, a variant of the Multi-Depot Vehicle Scheduling Problem in which additional constraints are enforced to model a real life scenario. The number of constraints involved and the large number of variables makes impracticable solving to optimality using complete search techniques. Therefore, we explore metaheuristics, that sacrifice optimality to produce solutions in feasible time. More concretely, we focus on the development of algorithms based on a sophisticated metaheuristic, Ant-Colony Optimization (ACO), which is based on a stochastic learning mechanism. For complex problems with a considerable number of constraints, sophisticated metaheuristics may fail to produce quality solutions in a reasonable amount of time. Thus, we developed parallel shared-memory (SM) synchronous ACO algorithms, however, synchronism originates the straggler problem. Therefore, we proposed three SM asynchronous algorithms that break the original algorithm semantics and differ on the degree of concurrency allowed while manipulating the learned information. Our results show that our sequential ACO algorithms produced better solutions than a Restarts metaheuristic, the ACO algorithms were able to learn and better solutions were achieved by increasing the amount of cooperation (number of search agents). Regarding parallel algorithms, our asynchronous ACO algorithms outperformed synchronous ones in terms of speedup and solution quality, achieving speedups of 17.6x. The cooperation scheme imposed by asynchronism also achieved a better learning rate than the original one.

The isolation and characterization of cytochrome c nitrite reductase subunits (NrfA and NrfH) from Desulfovibrio desulfuricans ATCC 27774

Eur. J. Biochem. 270, 3904–3915 (2003)

Automatic learning for the classification of chemical reactions and in statistical thermodynamics

This Thesis describes the application of automatic learning methods for a) the classification of organic and metabolic reactions, and b) the mapping of Potential Energy Surfaces(PES). The classification of reactions was approached with two distinct methodologies: a representation of chemical reactions based on NMR data, and a representation of chemical reactions from the reaction equation based on the physico-chemical and topological features of chemical bonds. NMR-based classification of photochemical and enzymatic reactions. Photochemical and metabolic reactions were classified by Kohonen Self-Organizing Maps (Kohonen SOMs) and Random Forests (RFs) taking as input the difference between the 1H NMR spectra of the products and the reactants. The development of such a representation can be applied in automatic analysis of changes in the 1H NMR spectrum of a mixture and their interpretation in terms of the chemical reactions taking place. Examples of possible applications are the monitoring of reaction processes, evaluation of the stability of chemicals, or even the interpretation of metabonomic data. A Kohonen SOM trained with a data set of metabolic reactions catalysed by transferases was able to correctly classify 75% of an independent test set in terms of the EC number subclass. Random Forests improved the correct predictions to 79%. With photochemical reactions classified into 7 groups, an independent test set was classified with 86-93% accuracy. The data set of photochemical reactions was also used to simulate mixtures with two reactions occurring simultaneously. Kohonen SOMs and Feed-Forward Neural Networks (FFNNs) were trained to classify the reactions occurring in a mixture based on the 1H NMR spectra of the products and reactants. Kohonen SOMs allowed the correct assignment of 53-63% of the mixtures (in a test set). Counter-Propagation Neural Networks (CPNNs) gave origin to similar results. The use of supervised learning techniques allowed an improvement in the results. They were improved to 77% of correct assignments when an ensemble of ten FFNNs were used and to 80% when Random Forests were used. This study was performed with NMR data simulated from the molecular structure by the SPINUS program. In the design of one test set, simulated data was combined with experimental data. The results support the proposal of linking databases of chemical reactions to experimental or simulated NMR data for automatic classification of reactions and mixtures of reactions. Genome-scale classification of enzymatic reactions from their reaction equation. The MOLMAP descriptor relies on a Kohonen SOM that defines types of bonds on the basis of their physico-chemical and topological properties. The MOLMAP descriptor of a molecule represents the types of bonds available in that molecule. The MOLMAP descriptor of a reaction is defined as the difference between the MOLMAPs of the products and the reactants, and numerically encodes the pattern of bonds that are broken, changed, and made during a chemical reaction. The automatic perception of chemical similarities between metabolic reactions is required for a variety of applications ranging from the computer validation of classification systems, genome-scale reconstruction (or comparison) of metabolic pathways, to the classification of enzymatic mechanisms. Catalytic functions of proteins are generally described by the EC numbers that are simultaneously employed as identifiers of reactions, enzymes, and enzyme genes, thus linking metabolic and genomic information. Different methods should be available to automatically compare metabolic reactions and for the automatic assignment of EC numbers to reactions still not officially classified. In this study, the genome-scale data set of enzymatic reactions available in the KEGG database was encoded by the MOLMAP descriptors, and was submitted to Kohonen SOMs to compare the resulting map with the official EC number classification, to explore the possibility of predicting EC numbers from the reaction equation, and to assess the internal consistency of the EC classification at the class level. A general agreement with the EC classification was observed, i.e. a relationship between the similarity of MOLMAPs and the similarity of EC numbers. At the same time, MOLMAPs were able to discriminate between EC sub-subclasses. EC numbers could be assigned at the class, subclass, and sub-subclass levels with accuracies up to 92%, 80%, and 70% for independent test sets. The correspondence between chemical similarity of metabolic reactions and their MOLMAP descriptors was applied to the identification of a number of reactions mapped into the same neuron but belonging to different EC classes, which demonstrated the ability of the MOLMAP/SOM approach to verify the internal consistency of classifications in databases of metabolic reactions. RFs were also used to assign the four levels of the EC hierarchy from the reaction equation. EC numbers were correctly assigned in 95%, 90%, 85% and 86% of the cases (for independent test sets) at the class, subclass, sub-subclass and full EC number level,respectively. Experiments for the classification of reactions from the main reactants and products were performed with RFs - EC numbers were assigned at the class, subclass and sub-subclass level with accuracies of 78%, 74% and 63%, respectively. In the course of the experiments with metabolic reactions we suggested that the MOLMAP / SOM concept could be extended to the representation of other levels of metabolic information such as metabolic pathways. Following the MOLMAP idea, the pattern of neurons activated by the reactions of a metabolic pathway is a representation of the reactions involved in that pathway - a descriptor of the metabolic pathway. This reasoning enabled the comparison of different pathways, the automatic classification of pathways, and a classification of organisms based on their biochemical machinery. The three levels of classification (from bonds to metabolic pathways) allowed to map and perceive chemical similarities between metabolic pathways even for pathways of different types of metabolism and pathways that do not share similarities in terms of EC numbers. Mapping of PES by neural networks (NNs). In a first series of experiments, ensembles of Feed-Forward NNs (EnsFFNNs) and Associative Neural Networks (ASNNs) were trained to reproduce PES represented by the Lennard-Jones (LJ) analytical potential function. The accuracy of the method was assessed by comparing the results of molecular dynamics simulations (thermal, structural, and dynamic properties) obtained from the NNs-PES and from the LJ function. The results indicated that for LJ-type potentials, NNs can be trained to generate accurate PES to be used in molecular simulations. EnsFFNNs and ASNNs gave better results than single FFNNs. A remarkable ability of the NNs models to interpolate between distant curves and accurately reproduce potentials to be used in molecular simulations is shown. The purpose of the first study was to systematically analyse the accuracy of different NNs. Our main motivation, however, is reflected in the next study: the mapping of multidimensional PES by NNs to simulate, by Molecular Dynamics or Monte Carlo, the adsorption and self-assembly of solvated organic molecules on noble-metal electrodes. Indeed, for such complex and heterogeneous systems the development of suitable analytical functions that fit quantum mechanical interaction energies is a non-trivial or even impossible task. The data consisted of energy values, from Density Functional Theory (DFT) calculations, at different distances, for several molecular orientations and three electrode adsorption sites. The results indicate that NNs require a data set large enough to cover well the diversity of possible interaction sites, distances, and orientations. NNs trained with such data sets can perform equally well or even better than analytical functions. Therefore, they can be used in molecular simulations, particularly for the ethanol/Au (111) interface which is the case studied in the present Thesis. Once properly trained, the networks are able to produce, as output, any required number of energy points for accurate interpolations.

Adesão ao regime terapêutico na pessoa com enfarte agudo do miócardio: contributo dos enfermeiros no internamento hospita

RESUMO: O Enfarte Agudo do Miocárdio (EAM) representa um dos principais problemas de saúde pública em Portugal. A rápida intervenção nos factores de risco determinantes da saúde cardíaca pode ter um impacto positivo em vários indicadores de saúde. O objectivo final dessa intervenção passa por capacitar a pessoa, para que, autonomamente, adopte um conjunto de comportamentos de saúde, baseados em estilos de vida protectores da saúde cardíaca, que favorecem positivamente o processo de reabilitação. Esta procura e aquisição do comportamento de saúde, adesão ao regime terapêutico, deve ser desenvolvido em parceria com os profissionais de saúde. O hospital representa a porta de entrada da pessoa com EAM no sistema de saúde. É neste contacto que se inicia uma intervenção de sensibilização e promoção da adesão ao regime terapêutico. Sendo os enfermeiros um grupo profissional que estabelece uma relação continua com a pessoa, importa conhecer um conjunto de dimensões do desempenho dos enfermeiros na promoção da adesão ao regime terapêutico. Breve referência ao desenho de estudo. Foram incluídas no estudo 143 enfermeiros de 9 serviços hospitalares da Região de Saúde de Lisboa e Vale do Tejo. Os dados foram obtidos através de um questionário auto-preenchido. Os dados mostraram que a população de enfermeiros é jovem (M= 30,5: dp= 8,0), 49% têm uma idade £ 26 anos e apresenta pouca experiência profissional (M=7,7; dp= 7,6), 48,2% exerce a profissão há menos de 3 anos. A antiguidade no serviço actual é reduzida (M= 4,7; dp= 4,6), 48,9% estão no serviço há menos de 2 anos. Os enfermeiros acreditam que deviam intervir com mais frequência nos factores de risco fisiológicos e comportamentais que nos factores psicossociais e ambientais; a confiança que têm nas capacidades para intervir nos factores de risco fisiológicos e comportamentais é maior que nos factores psicossociais e ambientais e no último ano, intervieram mais frequentemente nos factores de risco fisiológicos e comportamentais que nos psicossociais e ambientais. O “ensaio” da validação da escala de Will scale de Anderson et al (2004), sobre a capacidade de intervenção na saúde cardíaca, mostrou que o teste de Esfericidade de Bartlett e Medida de adequação da amostragem de Kaiser-Meyer- Olkin (KMO) permitiram a realização da análise factorial em componentes principais (AFCP). Da AFCP emergiram 16 factores, os mesmos que no estudo original de Anderson et al (2004), que revelaram boa consistência interna, com valores de alpha de Cronbach que variaram entre 0,71 a 0,98. Os resultados revelam a necessidade de sensibilizar os enfermeiros para valorizar a intervenção no âmbito dos factores de risco psicossociais e ambientais para promover a adesão ao regime terapêutico. Sugerem ainda que a intervenção baseada na evidência pode ser potenciada de forma a melhorar as práticas de cuidados dos enfermeiros. ABSTRACT: Myocardial infarction (MI) is one of the most important problems in public health in Portugal. A prompt intervention in cardiac health determinants means a positive impact in health outcomes, individually and collectively. The main purpose of this intervention lays on patient’s empowerment so he or she becomes able to choose healthy behaviours, based on heart health protective life styles, and therefore to manage his/hers therapeutic regime. This search and acquisition of health behaviours leading to therapeutic regime adherence may positively have an influence on the whole rehabilitation process and it must be developed in partnership with health workers. MI patients’ first contact with the Health System usually happens at the Hospital. Here the first steps are taken to start an intervention in order to promote therapeutic regime adherence. Nurses are a group of health workers who establish a unique and continuous relation with patients, so it matters to have knowledge of their performance skills that can actually promote a healthy behaviours and increase therapeutic regime adherence. Short Study design The study sample includes 143 nurses working on 9 different hospital wards, belonging to the Lisboa and Tejo’s Valley Health Region, in the district of Lisbon. Data were collected trough a self-administered questionnaire. It revealed that the nurses sample is a young population (M=30,5; dp=8,0), 49% of whom are aged less than 26 years old and has little professional experience (M=7,7; dp= 7,6); 48,2% work has nurses for less than 3 years. There’s a low percentage of seniority (M=4,7; dp=4,6), 48,9% of nurses work in these wards for less than 2 years. Nurses believe they should have intervene more frequently in physiological and behaviour risk factors than in psychological, social and environmental factors; they have greater confidence in their ability to intervene in physiological and behaviour risk factors than to intervene in psychological, social and environmental factors. In last year they took interventions more frequently in physiological and behaviour risk factors than in the other health determinants. The Scale Validation “essay” on Will Scale (Anderson et al, 2004), about heart health intervention capacity, revealed that the Bartlett’s test sphericity and the Kaiser-Meyer- Olkin’s (KMO) appropriate sample measure allowed the factorial analysis on main components (FAMC). From FAMC emerged 16 factors, the same number found on Anderson’s et al (2004) study, revealing good internal consistence, with Cronbach’s alpha values that varied between 0,71 and 0,98. The results point a need for nurses to attribute bigger value to other health determinants intervention - such as psychological, social and environmental determinants - so they’ll take part in promoting therapeutic regime adherence. The results also suggest t

Modern techniques for constraint solving the CASPER experience

Dissertação apresentada para obtenção do Grau de Doutor em Engenharia Informática, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Geospatial database generation from digital newspapers: use case for risk and disaster domains.

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Gold nanoparticle-DNA conjugates for oligonucleotide vectorization towards gene silencing

Dissertação para obtenção do Grau de Mestre em Genética Molecular e Biomedicina

Stochastic modelling of the reservoir lithological and petrophysical attributes. A case study of the Middle East carbonate reservoir

Dissertação para obtenção do Grau de Mestre em Engenharia Geológica (Georrecursos)

GI Systems for public health with an ontology based approach

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Low-Spin Heme b3 in the Catalytic Center of Nitric Oxide Reductase from Pseudomonas nautica

Biochemistry, 2011, 50 (20), pp 4251–4262 DOI: 10.1021/bi101605p

Artefacts induced on c-type haem proteins by electrode surfaces

J Biol Inorg Chem (2011) 16:209–215 DOI 10.1007/s00775-010-0717-z

Desulfovibrio gigas ferredoxin II: redox structural modulation of the [3Fe–4S] cluster

J Biol Inorg Chem (2006) 11: 307–315 DOI 10.1007/s00775-005-0077-2

The isolation and characterization of cytochrome c nitrite reductase subunits (NrfA and NrfH) from Desulfovibrio desulfuricans ATCC 27774

Eur. J. Biochem. 270, 3904–3915 (2003) doi:10.1046/j.1432-1033.2003.03772.x