Characterization of molecular damage induced by UV photons and carbon ions on biomimetic heterostructures

The study of the effect of radiation on living tissues is a rather complex task to address mainly because they are made of a set of complex functional biological structures and interfaces. Particularly if one is looking for where damage is taking place in a first stage and what are the underlying reaction mechanisms. In this work a new approach is addressed to study the effect of radiation by making use of well identified molecular hetero-structures samples which mimic the biological environment. These were obtained by assembling onto a solid support deoxyribonucleic acid (DNA) and phospholipids together with a soft water-containing polyelectrolyte precursor in layered structures and by producing lipid layers at liquid/air interface with DNA as subphase. The effects of both ultraviolet (UV) radiation and carbon ions beams were systematically investigated in these heterostructures, namely damage on DNA by means vacuum ultraviolet (VUV), infrared (IR), X-Ray Photoelectron (XPS) and impedance spectroscopy. Experimental results revealed that UV affects furanose, PO2-, thymines, cytosines and adenines groups. The XPS spectrometry carried out on the samples allowed validate the VUV and IR results and to conclude that ionized phosphate groups, surrounded by the sodium counterions, congregate hydration water molecules which play a role of UV protection. The ac electrical conductivity measurements revealed that the DNA electrical conduction is arising from DNA chain electron hopping between base-pairs and phosphate groups, with the hopping distance equal to the distance between DNA base-pairs and is strongly dependent on UV radiation exposure, due loss of phosphate groups. Characterization of DNA samples exposed to a 4 keV C3+ ions beam revealed also carbon-oxygen bonds break, phosphate groups damage and formation of new species. Results from radiation induced damage carried out on biomimetic heterostructures having different compositions revealed that damage is dependent on sample composition, with respect to functional targeted groups and extent of damage. Conversely, LbL films of 1,2-dipalmitoyl-sn-Glycero-3-[Phospho-rac-(1-glycerol)] (Sodium Salt) (DPPG) liposomes, alternated with poly(allylamine hydrochloride) (PAH) revealed to be unaffected, even by prolonged UV irradiation exposure, in the absence of water molecules. However, DPPG molecules were damaged by the UV radiation in presence of water with cleavage of C-O, C=O and –PO2- bonds. Finally, the study of DNA interaction with the ionic lipids at liquid/air interfaces revealed that electrical charge of the lipid influences the interaction of phospholipid with DNA. In the presence of DNA in the subphase, the effects from UV irrladiation were seen to be smaller, which means that ionic products from biomolecules degradation stabilize the intact DPPG molecules. This mechanism may explain why UV irradiation does not cause immediate cell collapse, thus providing time for the cellular machinery to repair elements damaged by UV.

Metal ions and protein folding: conformational and functional interplay

Dissertation presented to obtain a PhD degree in Biochemistry at Instituto de Tecnologia Química e Biológica, Universidade Nova de Lisboa

Magnetotransport properties of metal/LaAlO3/SrTiO3 heterostructures

The quasi two-dimensional electron gas (q2DEG) hosted in the interface of an epitaxially grown lanthanum aluminate (LaAlO3) thin film with a TiO2-termi-nated strontium titanate (SrTiO3) substrate (001) has been massively studied in the last few years. The confinement of mobile electrons to within a few nanome-ters from the interface, superconductive behavior at low temperatures and elec-tron mobility exceeding 1000 cm2/(V.s) make this system an interesting candi-date to explore the physics of spin injection and transport. However, due to the critical thickness for conduction of 4 unit cells (uc) of LaAlO3, a high tunneling resistance hampers electrical access to the q2DEG, preventing proper injection of spin polarized current. Recently, our group found that depositing a thin overlayer of Co on LaAlO3 reduces the critical thickness, enabling conduction with only 1 uc of LaAlO3. Two scenarios arise to explain this phenomenon: a pinning of the Fermi level in the metal, inducing charge transfer in the SrTiO3; the creation of oxygen vacancies at the interface between LaAlO3 and the metal, leading to an n-type doping of the SrTiO3. In this dissertation, we will report on magnetotransport of metal/LaAlO3/SrTiO3 (metal: Ti, Ta, Co, Py, Au, Pt, Pd) heterostructures with 2 uc of LaAlO3 studied at low temperatures (2 K) and high magnetic fields (9 T). We have analyzed the transport properties of the gas, namely, the carrier concen-tration, mobility and magnetotransport regime and we will discuss the results in the light of the two scenarios mentioned above.

Practices and trends of telework in the Portuguese industry: the results of surveys in the textile, metal and software sectors

The aim of the TeleRisk Project on labour relations and professional risks within the context of teleworking in Portugal – supported by IDICT – Institute for Development and Inspection of Working Conditions (Ministry of Labour), is to study the practices and forms of teleworking in the manufacturing sectors in Portugal. The project chose also the software industry as a reference sector, even though it does not intend to exclude from the study any other sector of activity or the so-called “hybrid” forms of work. However, the latter must have some of the characteristics of telework. The project thus takes into account the so-called “traditional” sectors of activity, namely textile and machinery and metal engineering (machinery and equipment), not usually associated to this type of work. However, telework could include, in the so-called “traditional” sectors, other variations that are not found in technologically based sectors. One of the evaluation methods for the dynamics associated to telework consisted in carrying out surveys by means of questionnaires, aimed at employers in the sectors analysed. This paper presents some of the results of those surveys. It is important to mention that, being a preliminary analysis, it means that it does not pretend to have exhausted all the issues in the survey, but has meant that it shows the bigger tendencies, in terms of teleworking practices, of the Portuguese industry.

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.

Structural and mechanistic studies of iron containing proteins

Dissertação apresentada para obtenção do Grau de Doutor em Bioquímica, ramo de Bioquímica-Física, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Protein folding, metal ions and conformational states: the case of a di-cluster ferredoxin

Dissertation presented to obtain the PhD degree in Biochemistry at the Instituto de Tecnologia Química e Biológica, Universidade Nova de Lisboa

Noble metal nanoparticles - Au and Ag - for biodetection

Dissertation submitted for obtainment of the Master’s Degree in Biotechnology, by the Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Anaerobic bacteria: an investigation of metabolic important enzymes: a novel type of oxygen reductase and enzymes of the tetrapyrrole biosynthesis

Desulfovibrio desulfuricans was the first species of a sulphatereducing bacterium to be isolated, in 1895. Since that time, many questions were raised in the scientific community regarding the metabolic and ecological aspects of these bacteria. At present, there is still a myriad of open questions remaining to be answered to enlarge our knowledge of the metabolic pathways operative in these bacteria that have implications in the sulfur cycle, in biocorrosion, namely in sewers and in oil and gas systems, and in bioremediation of several toxic metals. The work presented in this dissertation aimed at contributing with new insights of enzymes involved in two different metabolic systems on Desulfovibrio species, namely enzymes that play a role in the response to oxidative stress and that are involved in the haem biosynthetic pathway.(...)

Waste recovery into activated carbon for water purification from heavy metals

Dissertação apresentada para obtenção do Grau de Doutor em Engenharia Química Pela Universidade Nova de Lisboa,Faculdade de Ciências e Tecn

Metal ions modulate the folding and stability of the tumor suppressor protein S100A2

Febs Journal (2009)276:1776-1786

Heavy-metal resistance in Marinobacter aquaeolei 617 insights into copper resistance

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

Mulheres entre o som e o silêncio: imagens e representações das artistas de metal na LOUD!

Dissertação apresentada para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Estudos sobre as Mulheres

Desenvolvimento de membranas para separação de gases contendo MOFs (metal organic frameworks)

Disserta ção apresentada para obten ção do Grau de Mestre em Engenharia Química e Bioquímica

Development of new oxygen therapeutics using fluorinated ionic liquids

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