Biotoxicity assays of quantum dots in in vitro cultures of Medicago sativa and Medicago truncatula

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

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.

Making the cake and eating it as well

Educação Médica 1991; 2(2): p.3-4.

The impact of CdSe/ZnS Quantum Dots in cells of Medicago sativa in suspension culture

Abstract Background: Nanotechnology has the potential to provide agriculture with new tools that may be used in the rapid detection and molecular treatment of diseases and enhancement of plant ability to absorb nutrients, among others. Data on nanoparticle toxicity in plants is largely heterogeneous with a diversity of physicochemical parameters reported, which difficult generalizations. Here a cell biology approach was used to evaluate the impact of Quantum Dots (QDs) nanocrystals on plant cells, including their effect on cell growth, cell viability, oxidative stress and ROS accumulation, besides their cytomobility. Results: A plant cell suspension culture of Medicago sativa was settled for the assessment of the impact of the addition of mercaptopropanoic acid coated CdSe/ZnS QDs. Cell growth was significantly reduced when 100 mM of mercaptopropanoic acid -QDs was added during the exponential growth phase, with less than 50% of the cells viable 72 hours after mercaptopropanoic acid -QDs addition. They were up taken by Medicago sativa cells and accumulated in the cytoplasm and nucleus as revealed by optical thin confocal imaging. As part of the cellular response to internalization, Medicago sativa cells were found to increase the production of Reactive Oxygen Species (ROS) in a dose and time dependent manner. Using the fluorescent dye H2DCFDA it was observable that mercaptopropanoic acid-QDs concentrations between 5-180 nM led to a progressive and linear increase of ROS accumulation. Conclusions: Our results showed that the extent of mercaptopropanoic acid coated CdSe/ZnS QDs cytotoxicity in plant cells is dependent upon a number of factors including QDs properties, dose and the environmental conditions of administration and that, for Medicago sativa cells, a safe range of 1-5 nM should not be exceeded for biological applications.

Liaisons dangereuses, conservation of modern and contemporary art: a study of the synthetic binding media in Portugal

Dissertação apresentada para obtenção do Grau de Doutor em Conservação e Restauro, especialidade de Ciências da Conservação, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Biological activity of well defined hydantoin derivatives on efflux pump systems of bacteria and cancer cells

A multi-resistência a antibióticos e medicamentos usados em quimioterapia é um dos grandes problemas com os quais as instituições de saúde se debatem hoje em dia. A acção provocada por bombas de efluxo é uma das suas causas. Estas bombas têm uma importância fundamental, uma vez que, ao expelirem todo o tipo de tóxicos para o exterior das células, também expelem medicamentos, fazendo com que estes não tenham o efeito desejado dentro delas. As bombas de efluxo são transportadores que se encontram nas membranas de todo o tipo de células. Existem dois grandes tipos de bombas de efluxo: as primárias e as secundárias. As primeiras conferem multi-resistência principalmente em células eucariotas, como as células do cancro em humanos, tendo como função a mediação da repulsa de substâncias tóxicas por intermédio da hidrólise de ATP. A primeira a ser descoberta e mais estudada destas bombas foi a ABCB1 que é o gene que codifica a glicoproteína-P (P de permeabilidade). Enquanto as secundárias, que são a maior fonte de multi-resistência em bactérias, promovem a extrusão de substâncias tóxicas através da força motriz de protões. Neste tipo de bombas são conhecidas quatro famílias principais, das quais uma das mais importantes é a superfamília RND, uma vez que inclui a bomba AcrAB-TolC, que é muito importante no metabolismo xenobiótico de bactérias Gramnegativas, nomeadamente a E.coli. Com o objectivo de reverter a multi-resistência, tanto em células eucariotas como procariotas, têm-se desenvolvido estratégias de combate que envolvem a descoberta de substâncias que inibam as bombas de efluxo. Assim sendo, ao longo dos tempos têm sido descobertas variadas substâncias que cumprem este objectivo. É o caso, por exemplo, dos derivados de fluoroquinolonas usados como inibidores de bombas de efluxo em bactérias ou do Tamoxifen, utilizado na terapia de pacientes com cancro da mama. Um dos grupos de substâncias estudados para o desenvolvimento de possíveis compostos que actuem como reversores de multi-resistência são os compostos derivados de hidantoínas. Estes, são conhecidos por possuírem uma grande variedade de propriedades bioquímicas e farmacológicas, sendo portanto usados para tratarem algumas doenças em humanos, como a epilepsia. Nestes, estão englobados compostos com actividade anti-convulsão que constitui a sua grande mais-valia e, dependente da substituição no anel que os constitui, uma grande variedade de outras propriedades farmacológicas como a anti-fungica, a anti-arritmica, a anti-viral, a anti-diabética ou por exemplo a antagonização de determinados receptores, como os da serotonina. Apesar de pouco usados em estudos experimentais para desenvolver substâncias anti-carcinogénicas, existem alguns estudos com este efeito. Objectivos: O presente projecto envolve o estudo de bombas de efluxo primárias e secundárias, em células eucariotas e procariotas, respectivamente. Em bactérias, foram usados quatro modelos experimentais: Staphylococcus aureus ATCC 25923, Enterococcus faecalis ATCC 29212, E. coli AG 100 e Salmonella Enteritidis NCTC 13349. Em células de cancro foram usadas, células T de linfoma de rato parentais e células T de linfoma de rato transfectadas com o gene humano MDR-1. O principal objectivo deste estudo foi a pesquisa de novos moduladores de bombas de efluxo presentes em bactérias e células do cancro, tentando assim contribuir para o desenvolvimento de novos agentes farmacológicos que consigam reverter a multi-resistência a medicamentos. Assim sendo foram testados trinta compostos derivados de hidantoínas: SZ-2, SZ-7, LL-9, BS-1, JH-63, MN-3, TD-7k, GG-5k, P3, P7, P10, P11, RW-15b, AD-26, RW-13, AD-29, KF-2, PDPH-3, Mor-1, KK-XV, Thioam-1, JHF-1, JHC-2, JHP-1, Fur-2, GL-1, GL-7, GL-14, GL-16, GL-18. Como forma de atingir estes objectivos, a actividade biológica dos trinta compostos derivados de hidantoínas foi avaliada nas quatro estirpes de bactérias da seguinte forma: foram determinadas as concentrações mínimas inibitórias dos trinta compostos como forma de definir as concentrações em que os compostos seriam utilizados. Os compostos foram posteriormente testadas com um método fluorométrico de acumulação de brometo de etídeo, que é um substrato comum em bombas de efluxo bacterianas, desenvolvido por Viveiros et al. A actividade biológica dos compostos derivados de hidantoínas nas células de cancro foi demonstrada por diferentes métodos. O efeito anti-proliferativo e citotóxico dos trinta compostos foi avaliado nas células T de linfoma de rato transfectadas com o gene humano MDR-1 pelo método de thiazolyl de tetrazólio (MTT). Como o brometo de etídeo também é expelido pelos transportadores ABC, estes compostos foram posteriormente testados com um método fluorométrico de acumulação de brometo de etídeo desenvolvido por Spengler et al nos dois diferentes tipos de células eucariotas. Resultados: A maioria dos compostos derivados de hidantoínas foi eficaz na modulação de bombas de efluxo, nas duas estirpes de bactérias Gram-negativas e nos dois diferentes tipos de células T de linfoma. Em contraste com estes resultados, nas duas estirpes de células Gram-positivas, a maioria dos compostos tiveram pouco efeito na inibição de bombas de efluxo ou até nenhum, em muitos dos casos. De uma maneira geral os melhores compostos nas diferentes estirpes de bactérias foram: Thioam-1, SZ-2, P3, Rw-15b, AD-26, AD-29, GL-18, GL-7, KF-2, SZ-7, MN-3, GL-16 e GL- 14. Foram portanto estes os compostos que provocaram maior acumulação de brometo de etídeo, inibindo assim com maior eficácia as bombas de efluxo. No presente estudo, a maioria dos compostos conseguiu inibir a resistência provocada pela bomba de efluxo ABCB1, tanto nas células parentais bem como nas células que sobre-expressam esta bomba, causando a acumulação de brometo de etídeo dentro das células. As células que sobreexpressam a bomba ABCB1 foram posteriormente testadas com citometria de fluxo que é a técnica padrão para pesquisa de inibidores de bombas de efluxo. Os compostos que foram mais efectivos na inibição da bomba ABCB1, causando assim maior acumulação de brometo de etídeo nas células que sobre-expressam esta bomba foram: PDPH-3, GL-7, KK-XV, AD-29, Thioam-1, SZ-7, KF-2, MN-3, RW-13, LL-9, P3, AD-26, JH-63 e RW- 15b. Este facto não corroborou totalmente os resultados da citometria de fluxo uma vez que os moduladores que provocaram maior inibição da bomba ABCB1 foram o MN-3, JH-63 e o BS-1, sendo que o último não foi seleccionado como um bom composto usando o método fluorométrico de acumulação de brometo de etídeo. Conclusão: Os compostos derivados de hidantoínas testados tiveram maior efeito nas estirpes de bactérias Gram-negativas do que nas Gram-positivas. Relativamente às células eucariotas, as estruturas mais activas apresentam substituintes aromáticos bem como alguns fragmentos aminicos terciários.

Negative non-ground queries in well founded semantics

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

Study of forbidden transitions in atomic systems

A Thesis submitted for the co-tutelle degree of Doctor in Physics at Universidade Nova de Lisboa and Université Pierre et Marie Curie

Stratigraphic interpretation of Well-Log data of the Athabasca Oil Sands of Alberta Canada through Pattern recognition and Artificial Intelligence

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

Stochastic modeling of the thermal and catalytic degradation of polyethylene using simultaneous DSC/TG analysis

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

Quantum dots: synthesis, functionalization and bioconjugation for biological applications

Dissertation presented to obtain the Ph.D degree in Engineering Sciences and Technology

Fate of nitrogen in bioreactor landfills: lab-scale in situ aeration in well decomposed MSW

Dissertação para obtenção do Grau de Mestre em Engenharia do ambiente, perfil de engenharia sanitária

Hydrogen permeation in parabolic trough receivers

The continued economic and population development puts additional pressure on the already scarce energetic sources. Thus there is a growing urge to adopt a sustainable plan able to meet the present and future energetic demands. Since the last two decades, solar trough technology has been demonstrating to be a reliable alternative to fossil fuels. Currently, the trough industry seeks, by optimizing energy conversion, to drive the cost of electricity down and therefore to place itself as main player in the next energetic age. One of the issues that lately have gained considerable relevance came from the observation of significant heat losses in a large number of receiver modules. These heat losses were attributed to slow permeation of traces of hydrogen gas through the steel tube wall into the vacuum annulus. The presence of hydrogen gas in the absorber tube results from the decomposition of heat transfer fluid due to the long-term exposure to 400°C. The permeated hydrogen acts as heat conduction mean leading to a decrease in the receivers performance and thus its lifetime. In order to prevent hydrogen accumulation, it has been common practice to incorporate hydrogen getters in the vacuum annulus of the receivers. Nevertheless these materials are not only expensive but their gas absorbing capacity can be insufficient to assure the required level of vacuum for the receivers to function. In this work the building of a permeation measurement device, vulnerabilities detected in the construction process and its overcome are described. Furthermore an experimental procedure was optimized and the obtained permeability results, of different samples were evaluated. The data was compared to measurements performed by an external entity. The reliability of the comparative data was also addressed. In the end conclusions on the permeability results for the different samples characteristics, feasibility of the measurement device are drawn and recommendations on future line of work were made.

Reactive electron scattering from biomolecules and technologically relevant molecules

The role of a set of gases relevant within the context of biomolecules and technologically relevant molecules under the interaction of low-energy electrons was studied in an effort to contribute to the understanding of the underlying processes yielding negative ion formation. The results are relevant within the context of damage to living material exposed to energetic radiation, to the role of dopants in the ion-molecule chemistry processes, to Electron Beam Induced Deposition (EBID) and Ion Beam Induced Deposition (IBID) techniques. The research described in this thesis addresses dissociative electron attachment (DEA) and electron transfer studies involving experimental setups from the University of Innsbruck, Austria and Universidade Nova de Lisboa, Portugal, respectively. This thesis presents DEA studies, obtained by a double focusing mass spectrometer, of dimethyl disulphide (C2H6S2), two isomers, enflurane and isoflurane (C3F5Cl5) and two chlorinated ethanes, pentachloroethane (C2HCl5) and hexachloroethane (C2Cl6), along with quantum chemical calculations providing information on the molecular orbitals as well as thermochemical thresholds of anion formation for enflurane, isoflurane, pentachloroethane and hexachloroethane. The experiments represent the most accurate DEA studies to these molecules, with significant differences from previous work reported in the literature. As far as electron transfer studies are concerned, negative ion formation in collisions of neutral potassium atoms with N1 and N3 methylated pyrimidine molecules were obtained by time-of-flight mass spectrometry (TOF). The results obtained allowed to propose concerted mechanisms for site and bond selective excision of bonds.

Solution processed quantum dot photodetectors

To find sustainable solutions for the production of energy, it is necessary to create photovoltaic technologies that make every photon count. To pursue this necessity, in the present work photodetectors of zinc oxide embedded with nano-structured materials, that significantly raise the conversion of solar energy to electric energy, were developed. The novelty of this work is on the development of processing methodologies in which all steps are in solution: quantum dots synthesis, passivation of their surface and sol-gel deposition. The quantum dot solutions with different capping agents were characterized by UVvisible absorption spectroscopy, spectrofluorimetry, dynamic light scattering and transmission electron microscopy. The obtained quantum dots have dimensions between 2 and 3nm. These particles were suspended in zinc acetate solutions and used to produce doped zinc oxide films with embedded quantum dots, whose electric response was tested. The produced nano-structured zinc oxide materials have a superior performance than the bulk, in terms of the produced photo-current. This indicates that an intermediate band material should have been produced that acts as a photovoltaic medium for solar cells. The results are currently being compiled in a scientific article, that is being prepared for possible submission to Energy and Environmental Science or Nanoscale journals.