The transformation of work? A quantitative evaluation of changes in work in Portugal

This report is made for the Work Package 15 of WORKS project and tries to develop more information on the Portuguese situation in the work structures changes in the recent years. It starts with an analysis of socio- economical indicators (Macro economical indicators, Employment indicators, Consumption, Technology at the workplace, Productivity), and then approaches the situation in terms of work flexibility in its dimensions of time use and New forms of work organisation. It traces employment in business functions with a sectoral and occupational approach, and analyses the occupational change in South Europe with particular relevance to Portugal (skill utilisation and job satisfaction, occupational and industrial mobility, quantitative evaluation of the shape of employment in Europe. Finaly are analysed the globalisation indicators.

Toxicological effects of a pharmaceutical, simvastatin, in Gammarus locusta: histopathological evaluation

Dissertação para obtenção do Grau de Mestre em Engenharia do Ambiente

Experimental high-throughput adsorption unit for multi-evaluation of adsorbents for gas capture, storage and separation applications

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

Thomsen-Friedenreich antigens in bladder cancer: evaluation of their prognostic value

RESUMO: Introdução. O cancro de bexiga é uma patologia comum que representa o 6° e o 5° cancro mais incidente em Portugal e na Itália, respetivamente. Em mais de metade dos casos ocorre reincidência durante o primeiro ano, requerendo acompanhamento clínico ao longo da vida. A instilação intravesical de Bacillus Calmette-Guérin (BCG) (uma estirpe atenuada do Mycobacterium bovis) representa uma imunoterapia eficaz no combate ao cancro de bexiga, no entanto, muitos aspetos da interação de BCG com as células tumorais bem como com as células do sistema imunitário permanecem por desvendar. As células tumorais de bexiga expressam frequentemente as formas sialiladas dos antigénios de Thomsen-Friedenreich (TF), i.e., sialil-T (sT) e sialil-Tn (sTn). Contudo ainda se desconhece o significado da sua expressão na malignidade tumoral e se afeta a eficácia da terapêutica BCG. Objetivo do estudo. Investigar o papel dos antigénios sT e sTn no fenótipo maligno de células de cancro de bexiga bem como na resposta mediada pelo sistema imunitário à terapia com BCG. Metodologia. Para tal, foram utilizadas as linhas celulares de cancro da bexiga HT1376 e MCR, geneticamente modificadas por transdução com vetores codificantes para as sialiltransferases ST3GAL1 ou ST6GALNAC1, de forma a expressar homogeneamente os antigénios sT ou sTn respetivamente. Estes modelos celulares foram estudados após confronto com BCG. O nível de BCG internalizado foi avaliado por citometria de fluxo. O perfil global de expressão genética dos modelos celulares antes e após incubação com BCG foi analisado pela tecnologia de microarray. O perfil de citocinas secretadas pelos modelos celulares após incubação com BCG, bem como de macrófagos estimulados pelo secretoma de células de cancro de bexiga que por sua vez foram estimuladas previamente por BCG, foi estudado pelo sistema multiplex de “imuno-esferas”. Resultados. A análise do transcritoma dos modelos celulares revelou que grupos de genes envolvidos em funções específicas foram modulados em paralelo nos dois modelos celulares, após transdução, independentemente da sialiltransferase expressa. Ou seja, em células que expressavam a sialiltransferase ST3GAL1 ou ST6GALNAC1, os genes envolvidos na regulação da segregação cromossómica e na reparação do DNA foram consistentemente regulados negativamente. Genes descritos na literatura como marcadores para o cancro de bexiga foram também modulados. A incubação com BCG resultou numa tendência ao aumento da expressão de genes relevantes na preservação e estabilidade genómica e menor malignidade, no entanto, apenas em células que expressavam sT ou sTn. Entre as dez citocinas testadas, apenas a IL-6 e IL-8 foram expressas pelas linhas celulares de cancro da bexiga, com indução destas após estimulação com BCG, e principalmente em células que expressavam ST3GAL1 ou ST6GALNAC1. Em macrófagos, citocinas inflamatórias, tais como IL-1β, IL-6 e TNFα, e a citocina anti-inflamatória IL-10, foram induzidas apenas pelo secretoma de células de cancro da bexiga confrontadas com BCG, com maior relevância quando estas expressavam ST3GAL1 ou ST6GALNAC1, prevendo a estimulação de macrófagos semelhantes aos de tipo M1 e uma melhor resposta à terapia com BCG. Conclusões. O efeito geral da expressão destas sialiltransferases e dos produtos enzimáticos sT ou sTn nas células de cancro de bexiga conduz a um fenótipo de maior malignidade. Contudo, a maior avidez de estas na produção de citocinas inflamatórias após confronto com BCG, bem como a maior capacidade de estimulação de macrófagos, predirá uma resposta à terapia com BCG mais eficaz em tumores que expressem os antigénios de TF sialilados. Tais conclusões são totalmente concordantes com os nossos mais recentes dados clínicos obtidos em colaboração, que mostram que em doentes com cancro de bexiga que expressam sTn respondem melhor a terapia BCG. ----------ABSTRACT: Background. Bladder cancer is a common malignancy representing the 6th and the 5th most incident cancer in Portugal and in Italy, respectively. More than half of the cases relapse within one year, requiring though a lifelong follow-up. Intravesical instillation of Bacillus Calmette-Guérin (BCG) (an attenuated strain of Mycobacterium bovis) represents an effective immunotherapy of bladder cancer, although many aspects of the interaction of BCG with cancer cells and host immune cells remain obscure. Bladder cancer cells often express the sialylated forms of the Thomsen-Friedenreich (TF), i.e., sialil-T (sT) e sialil-Tn (sTn). However, it’s still unknown the sense of such expression in tumour malignancy and in the BCG therapy efficacy. Aim of the study. To investigate the role of the sT and sTn antigens on the malignant phenotype of bladder cancer cells and the immune mediated response to BCG therapy. Experimental. We have utilized populations of the bladder cancer cell lines HT1376 and MCR, genetically modified by transduction with the sialyltransferases ST3GAL1 or ST6GALNAC1 to express homogeneously sT or sTn antigens. The level of BCG internalized was assessed by flow cytometry. The whole gene expression profile of BCG-challenged or unchallenged bladder cancer cell lines was studied by microarray technology. The profile of cytokines secreted by BCG-challenged bladder cancer cells and that of macrophages challenged by the secretome of BCG-challenged bladder cancer cells was studied by multiplex immune-beads assay. Results. Transcriptome analysis of the sialyltransferase-transduced cells revealed that groups of genes involved in specific functions were regulated in parallel in the two cell lines, regardless the sialyltransferase expressed. Namely, in sialyltransferase-expressing cells, genes involved in the proper chromosomal segregation and in the DNA repair were consistently down-regulated, while genes reported in literature as markers for bladder cancer were modulated. BCG-challenging induced a tendency to up-regulation of the genes preserving genomic stability and reducing malignancy, but only in cells expressing either sT or sTn. Among the ten cytokines tested, only IL-6 and IL-8 were expressed by bladder cancer cell lines and up-regulated by BCG-challenging, mainly in sialyltransferases-expressing cells. In macrophages, inflammatory cytokines, such as IL-1β, IL-6 and TNFα, and the antinflammatory IL-10 were induced only by the secretome of BCG-challenged bladder cancer cells, particularly when expressing either sialyltransferase, predicting the stimulation of M1-like macrophages and a better response to BCG therapy. Conclusions. The general effect of the expression of the two sialyltransferases and their products in the bladder cancer cells is toward a more malignant phenotype. However, the stronger ability of sialyltransferase expressing cells to produce inflammatory cytokines upon BCG-challenging and to stimulate macrophages predicts a more effective response to BCG in tumours expressing the sialylated TF antigens. This is fully consistent with our recent clinical data obtained in collaboration, showing that patients with bladder cancer expressing sTn respond better to BCG therapy.

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.

Evaluation of the potential of translocated common cockle for ecological risk assessment studies: bioaccumulation and biomarkers test

Thesis submitted to the Faculdade de Ciências e Tecnologia to obtain the Master’s degree in Environmental Engineering, profile in Ecological Engineering