19 resultados para Food and feed safety


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

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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

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Mannans (linear mannan, glucomannan, galactomannan and galactoglucomannan) are the major constituents of the hemicellulose fraction in softwoods and show great importance as a renewable resource for fuel or feedstock applications. As complex polysaccharides, mannans can only be degraded through a synergistic action of different mannan-degrading enzymes, mannanases. Microbial mannanases are mainly extracellular enzymes that can act in wide range of pH and temperature, contributing to pulp and paper, pharmaceutical, food and feed, oil and textile successful industrial applications. Knowing and controlling these microbial mannan-degrading enzymes are essential to take advantage of their great biotechnological potential. The genome of the laboratory 168 strain of Bacillus subtilis carries genes gmuA-G dedicated to the degradation and utilization of glucomannan, including an extracellular -mannanase. Recently, the genome sequence of an undomesticated strain of B. subtilis, BSP1, was determined. In BSP1, the gmuA-G operon is maintained, interestingly, however, a second cluster of genes was found (gam cluster), which comprise a second putative extracellular β-mannanase, and most likely specify a system for the degradation and utilization of a different mannan polymer, galactoglucomannan. The genetic organization and function of the gam cluster, and whether its presence in BSP1 strain results in new hemicellulolytic capabilities, compared to those of the laboratory strain, was address in this work. In silico and in vivo mRNA analyses performed in this study revealed that the gam cluster, comprising nine genes, is organized and expressed in at least six different transcriptional units. Furthermore, cloning, expression, and production of Bbsp2923 in Escherichia coli was achieved and preliminary characterization shows that the enzyme is indeed a β-mannanase. Finally, the high hemicellulolytic capacity of the undomesticated B. subtilis BSP1, demonstrated in this work by qualitative analyses, suggests potential to be used in the food and feed industries.

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This study focus in the valorization of the apple pomace with the main goal of obtaining added value products. For that, hot compressed water technology was used for the extraction of phenolic compounds and hydrolysis of polysaccharides presents in the lignocellulosic structure of apple pomace to obtain simple sugars. The sugars have been utilized as alternative carbon source for growth, lipid accumulation and carotenoids production by five different yeast Yarrowia lipolytica, Rhodotorula mucilaginosa, Rhodotorula glutinis, Rhodosporidium babjevae and Rhodosporidium toruloides. Hydrolysis experiments were carried out with constant pressure of 100 bar, flow rate of 2mL/min and temperatures between 50°C and 250°C. The amount of total sugars present in apple pomace hydrolysates showed maximum values for the hydrolysis temperatures of 110°C and 190°C. In fact, these temperatures revealed the best results regarding the monosaccharides quantities. The amount of 5-HMF and furfural in each hydrolysate varied through the different temperatures. Maximum values for 5-HMF were obtained with 170°C, while furfural showed to be maximum at 210°C. Extraction of phenolic compounds were performed in simultaneously with hydrolysis reactions. Total phenolic compounds (TPC) increased along the temperature, however with small variations between 170°C and 250°C. Hydrolysates were then used as alternative carbon source to yeast growth. R. mucilaginosa shows the highest optical density, with the hydrolysate obtained at 130°C. Carotenoids produced by these yeast scored a total of 7.02μg carotenoids/g cell dry weight, while for the control assay, the same yeast scored 9.31μg caratonoides/g cell dry weight. β-carotene was quantified by HPLC, were 33% of the carotenoid production by R. mucilaginosa with hydrolysate as carbon source, corresponded to β-caroteno.

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

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Periodic drought is the primary limitation of plant growth and crop yield. The rise of water demand caused by the increase in world population and climate change, leads to one of the biggest challenges of modern agriculture: to increase food and feed production. De novo DNA methylation is a process regulated by small interfering RNA (siRNAs), which play a role in plant response and adaptation to abiotic stress. In the particular case of water deficit, growing evidences suggest a link between the siRNA pathways and drought response in the model legume Medicago truncatula. As a first step to understand the role of DNA methylation under water stress, we have set up several bioinformatics and molecular methodologies allowing the design of Clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 systems and the assembly of TALENs (transcription activator-like effector nucleases), to target both dicer-like 3 (MtDCL3) and RNA-Dependent RNA polymerase (MtRDR2), enzymes of the RNA-directed DNA methylation pathway. TALENs efficiency was evaluated prior to plant transformation by a yeast-based assay using two different strategies to test TALENs activity: Polyacrylamide gel electrophoresis (PAGE) and Single strand conformation polymorphisms (SSCP). In this assay, yeast cells triple transformation emerged as good and rapid alternative to laborious yeast mating strategies. PAGE analysis might be a valuable tool to test TALENs efficacy in vivo if we could increase TALENs activity. SSCP-based approach proved to be ineffective due to the generation of several false positives. TALENs and CRISPR/Cas9 system constructed and designed in this work will in the future certainly enable the successful disruption of DCL3 and RDR2 genes and shed the light on the relationship between plant stress resistance and epigenetic regulation mediated by siRNAs in M.truncatula.

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ABSTRACT - Despite improvements in healthcare interventions, the incidence of adverse events and other patient safety problems constitutes a major contributor to the global burden of diseases and a concern for Public Health. In the last years there have been some successful individual and institutional efforts to approach patient safety issues in Portugal, unless such effort has been fragmented or focused on specific small areas. Long-term and global improvement has remained elusive, and most of all the improvement of patient safety in Portugal, must evaluate not only the efficacy of a change but also what was effective for implementing the change. Clearly, patient safety issues result from various combinations of individual, team, organization, system and patient factors. A systemic and integrated approach to promote patient safety must acknowledge and strive to understand the complexity of work systems and processes in health care, including the interactions between people, technology, and the environment. Safety errors cannot be productively attributed to a single human error. Our objective with this paper is to provide a brief overview of the status quo in patient safety in Portugal, highlighting key aspects that should be taken into account in the design of a strategy for improving patient safety. With these key aspects in mind, policy makers and implementers can move forward and make better decisions about which changes should be made and about the way the needed changes to improve patient safety should be implemented. The contribution of colleagues that are international leaders on healthcare quality and patient safety may also contribute to more innovative research methods needed to create the knowledge that promotes less costly successful changes.---- ---------------------- RESUMO – As questões relacionadas com a Segurança do Doente, e em particular, com a ocorrência de eventos adversos tem constituído, de há uns tempos a esta parte, uma crescente preocupação para as organizações de saúde, para os decisores políticos, para os profissionais de saúde e para os doentes/utentes e suas famílias, sendo por isso considerado um problema de Saúde Pública a que urge dar resposta. Em Portugal, nos últimos anos, têm sido desenvolvidos esforços baseados, maioritariamente, em iniciativas isoladas, para abordar os aspectos da Segurança do Doente. O facto de essas iniciativas não serem integradas numa estratégia explícita e de dimensão regional ou nacional, faz com que os resultados sejam parcelares e tenham visibilidade reduzida. Paralelamente, a melhoria da qualidade dos cuidados de saúde (a longo prazo) resultante dessas iniciativas tem sido esparsa e nem sempre a avaliação tem sido feita tendo em conta critérios de efectividade e de eficiência. A Segurança do Doente resulta da interacção de diversos factores relacionados, por um lado, com o doente e, por outro, com a prestação de cuidados que envolvem elementos de natureza individual (falhas activas) e organizacional/estrutural (falhas latentes). Devido à multifactorialidade que está na base de «problemas/falhas» na Segurança do Doente, qualquer abordagem a considerar deve ser sistémica e integrada. Simultaneamente, tais abordagens devem contemplar a compreensão da complexidade dos sistemas e dos processos de prestação de cuidados de saúde e as suas interdependências (envolvendo aspectos individuais, tecnológicos e ambientais). O presente trabalho tem por objectivo reflectir sobre o «estado da arte» da Segurança do Doente em Portugal, destacando os elementos-chave que se consideram decisivos para uma estratégia de acção nesse domínio. Com esses elementos os responsáveis pela governação da saúde poderão valorizar os aspectos que consideram decisivos para uma política de Segurança do Doente mais eficaz. A contribuição de quatro colegas internacionalmente reconhecidos como líderes na área da Qualidade em Saúde e da Segurança do Doente, constitui, por certo, uma oportunidade ímpar para a identificação e discussão de alguns dos principais desafios, ameaças e oportunidades que s

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This paper aims to provide strategies for the organic supermarket chain “Alnatura” to shape the demand and its market share of the organic food & beverage (F&B) market in Germany within the next five years. Through the historic evolution and the current market assessment of Germany, compared to a benchmark country (US), as well as prospective trends in Germany, reasons and opportunities for market growth are evaluated. In addition, an industry attractiveness, competitor and company analysis is executed. Based on those findings and a conducted survey, suggestions to adjust Alnatura´s current business strategies are deduced and finally examined on its risk and feasibility.

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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.

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Life-Cycle Civil Engineering – Biondini & Frangopol

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Dissertation presented to obtain a Doctoral degree in Biology, Instituto de Tecnologia Química e Biológica, Universidade Nova de Lisboa.

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Dissertação para obtenção do Grau de Mestre em Engenharia e Gestão Industrial

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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

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Dissertation for the Master Degree in Technology and Food Security

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Dissertação para obtenção do Grau de Mestre em Biotecnologia