9 resultados para Hesperidin and piperidol mixture
Resumo:
CIAV2013 – International Conference on Vernacular Architecture, 7º ATP, VerSus, 16-20 october 2013
Resumo:
The main objective of this work was the development of polymeric structures, gel and films, generated from the dissolution of the Chitin-Glucan Complex (CGC) in biocompatible ionic liquids for biomedical applications. Similar as chitin, CGC is only soluble in some special solvents which are toxic and corrosive. Due to this fact and the urgent development of biomedical applications, the need to use biocompatible ionic liquids to dissolve the CGC is indispensable. For the dissolution of CGC, the biocompatible ionic liquid used was Choline acetate. Two different CGC’s, KiOnutrime from KitoZyme and biologically produced CGC from Faculdade de Ciencias e Tecnologia (FCT) - Universidade Nova de Lisboa, were characterized in order to develop biocompatible wound dressing materials. The similar result is shown in term of the ratio of chitin:glucan, which is 1:1.72 for CGC-FCT and 1:1.69 for CGC-Commercial. For the analysis of metal element content, water and inorganic salts content and protein content, both polymers showed some discrepancies, where the content in CGC-FCT is always higher compared to the commercial one. The different characterization results between CGC-FCT and CGC-Commercial could be addressed to differences in the purification method, and the difference of its original strain yeast, whereas CGC-FCT is derived from P.pastoris and the commercial CGC is from A.niger. This work also investigated the effect of biopolymers, temperature dissolution, non-solvent composition on the characteristics of generated polymeric structure with biocompatible ionic liquid. The films were prepared by casting a polymer mixture, immersion in a non-solvent, followed by drying at ambient temperature. Three different non-solvents were tested in phase inversion method, i.e. water, methanol, and glycerol. The results indicate that the composition of non-solvent in the coagulation bath has great influence in generated polymeric structure. Water was found to be the best coagulant for producing a CGC polymeric film structure. The characterizations that have been done include the analysis of viscosity and viscoelasticity measurement, as well as sugar composition in the membrane and total sugar that was released during the phase inversion method. The rheology test showed that both polymer mixtures exhibit a non- Newtonian shear thinning behaviour. Where the viscosity and viscoelasticity test reveal that CGCFCT mixture has a typical behaviour of a viscous solution with entangled polymer chains and CGCCommercial mixture has true gel behaviour. The experimental results show us that the generated CGC solution from choline acetate could be used to develop both polymeric film structure and gel. The generated structures are thermally stable at 100° C, and are hydrophilic. The produced films have dense structure and mechanical stabilities against puncture up to 60 kPa.
Resumo:
Contemporary painting places, and will continue to place, several questions about its meaning, its chemical nature, its durability and the best way to preserve it. This research aims at putting together comprehensive data on vinyl based paints, including their components, their properties, their aging behavior and their response to selected cleaning products. In this project degradation mechanisms of vinyl binders and formulations used in the 20th and 21st century were studied. Stability over time of selected vinyl polymers was assessed through natural indoor and artificially aging. The objective was to enhance knowledge and understanding of vinyl emulsion formulations and their performance over time. Overall conservation state of pictorial layers namely, adhesion, cohesion and discoloration of selected case studies from the Portuguese artist Julião Sarmento (b.1948) was correlated with the observed molecular level changes studied in laboratory experiments. Sarmento’s paintings were chosen due to conservation concerns (discoloration) on some of his works from the 90’s. Besides, research was carried out to start increasing the knowledge of what can be expected of PVAc based paints in terms of response to conservation treatments namely, surface cleaning. Artificial aging showed that the most recent formulations which are based on a poly(vinyl acetate), poly(vinyl chloride) and polyethylene terpolymer are less stable when compared to some homopolymer formulations. From the four pigments studied, titanium dioxide rutile and a carbon based black proved to be stabilizers for both types of polymer. The mixture lithopone plus calcium carbonate has showed to have a photocatalytic effect on the binders. The studied paintings showed to be in an overall good state of conservation except for the paintings created in the 90’s with white glue and a mixture of white lithoponeand calcium carbonate. Discoloration of this white paint seems to be irreversible and ongoing and is still a major concern. The disapearance of the plasticizer was the only change detected. The current works created by Sarmento are expected to be more stable as they were painted using the rutile titanium dioxide. Immersion/cleaning tests showed that vinyl based paints can be susceptible to water and organic solvents like ethanol as some evidences point to the removal/diffusion of additives from the paint. The observations made point to the need to further proceed in this research field.
Resumo:
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.
Resumo:
Dissertação apresentada para a obtenção do Grau de Mestre em Genética Molecular e Biomedicina, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia
Resumo:
Dissertação para obtenção do Grau de Mestre em Engenharia do Ambiente
Resumo:
Pollution in coastal ecosystems is a serious threat to the biota and human populations there residing. Anthropogenic activities in these ecosystems are the main cause of contamination by endocrine disruption compounds (EDCs), which can interfere with hormonal regulation and cause adverse effects to growth, stress response and reproduction. Although the chemical nature of many EDCs is unknown, it is believed that most are organic contaminants. Under an environmental risk assessment for a contaminated estuary (the Sado, SW Portugal), the present work intended to detect endocrine disruption in a flatsfish, Solea senegalensis Kaup, 1858, and its potential relationship to organic toxicants. Animals were collected from two areas in the estuary with distinct influences (industrial and rural) and from an external reference area. To evaluate endocrine disruption, hepatic vitellogenin (VTG) concentrations in males and gonad histology were analysed. As biomarkers of exposure to organic contaminants, cytochrome P450 (CYP1A) induction and the ethoxyresorufin-O-deethylase (EROD) activity were determined. The results were contrasted to sediment contamination levels, which are overall considered low, although the area presents a complex mixture of toxicants. Either males or females were found sexually immature and showed no significant evidence of degenerative pathologies. However, hepatic VTG concentrations in males from the industrial area in estuary were superior than those from the Reference, even reaching levels comparable to those in females, which may indicate an oestrogenic effect resulting from the complex contaminant mixture. These individuals also presented higher levels of CYP1A induction and EROD activity, which is consistent with contamination by organic substances. The combination of the results suggest that the exposure of flatfish to an environment contaminated by mixed toxicants, even at low levels, may cause endocrine disruption, therefore affecting populations, which implies the need for further research in identification of potential EDCs, their sources and risks at ecosystem scale.
Resumo:
Due to their toxicity, especially their carcinogenic potential, polycyclic aromatic hydrocarbons (PAHs) became priority pollutants in biomonitoring programmes and environmental policy, such as the European Water Framework Directive. The model substances tested in this study, namely benzo[b]fluoranthene (B[b]F), considered potentially carcinogenic to humans and an effector carcinogenic PAH to wildlife, and phenanthrene (Phe), deemed a non-carcinogenic PAH, are common PAHs in coastal waters, owning distinct properties reflected in different, albeit overlapping, mechanisms of toxicity. Still, as for similar PAHs, their interaction effects remain largely unknown. In order to study the genotoxic effects of caused by the interaction of carcinogenic and non-carcinogenic PAHs, and their relation to histopathological alterations, juvenile sea basses, Dicentrarchus labrax, a highly ecologically- and economically-relevant marine fish, were injected with different doses (5 and 10 μg.g-1 fish ww) of the two PAHs, isolated or in mixture, and incubated for 48 h. Individuals injected with B[b]F and the PAH mixture exhibited higher clastogenic/aneugenic effects and DNA strand breakage in blood cells, determined through the erythrocytic nuclear abnormalities (ENA) and Comet assays, respectively. Also, hepatic histopathological alterations were found in all animals, especially those injected with B[b]F and the PAH mixture, relating especially to inflammation. Still, Phe also exhibited genotoxic effects in sea bass, especially in higher doses, revealing a very significant acute effect that was accordant with the Microtox test performed undergone in parallel. Overall, sea bass was sensitive to B[b]F (a higher molecular weight PAH), likely due to efficient bioactivation of the pollutant (yielding genotoxic metabolites and reactive oxygen species), when compared to Phe, the latter revealing a more significant acute effect. The results indicate no significant additive effect between the substances, under the current experimental conditions. The present study highlights the importance of understanding PAH interactions in aquatic organisms, since they are usually present in the aquatic environment in complex mixtures.
Resumo:
Materials engineering focuses on the assembly of materials´ properties to design new products with the best performance. By using sub-micrometer size materials in the production of composites, it is possible to obtain objects with properties that none of their compounds show individually. Once three-dimensional materials can be easily customized to obtain desired properties, much interest has been paid to nanostructured poly-mers in order to build biocompatible devices. Over the past years, the thermosensitive microgels have become more common in the framework of bio-materials with potential applicability in therapy and/or diagnostics. In addition, high aspect ratio biopolymers fibers have been produced using the cost-effective method called electrospinning. Taking advantage of both microgels and electrospun fibers, surfaces with enhanced functionalities can be obtained and, therefore employed in a wide range of applications. This dissertation reports on the confinement of stimuli-responsive microgels through the colloidal electro-spinning process. The process mainly depends on the composition, properties and patterning of the precur-sor materials within the polymer jet. Microgels as well as the electrospun non-woven mats were investigated to correlate the starting materials with the final morphology of the composite fibers. PNIPAAm and PNIPAAm/Chitosan thermosensitive microgels with different compositions were obtained via surfactant free emulsion polymerization (SFEP) and characterized in terms of chemical structure, morphology, thermal sta-bility, swelling properties and thermosensitivity. Finally, the colloidal electrospinning method was carried out from spinning solutions composed of the stable microgel dispersions (up to a concentration of about 35 wt. % microgels) and a polymer solution of PEO/water/ethanol mixture acting as fiber template solution. The confinement of microgels was confirmed by Scanning Electron Microscopy (SEM). The electrospinning process was statistically analysed providing the optimum set of parameters aimed to minimize the fiber diameter, which give rise to electrospun nanofibers of PNIPAAm microgels/PEO with a mean fiber diameter of 63 ± 25 nm.