Self-assembly in chains, rings, and branches: a single component system with two critical points

Agências financiadoras: FCT - PEstOE/FIS/UI0618/2011; PTDC/FIS/098254/2008 ERC-PATCHYCOLLOIDS e MIUR-PRIN

Chlormequat selective electrodes: construction, evaluation and application at FIA systems

A flow injection analysis (FIA) system having a chlormequat selective electrode is proposed. Several electrodes with poly(vinyl chloride) based membranes were constructed for this purpose. Comparative characterization suggestedthe use of membrane with chlormequat tetraphenylborate and dibutylphthalate. On a single-line FIA set-up, operating with 1x10-2 mol L-1 ionic strength and 6.3 pH, calibration curves presented slopes of 53.6±0.4mV decade-1 within 5.0x10-6 and1.0x10-3 mol L-1, andsquaredcorrelation coefficients >0.9953. The detection limit was 2.2x10-6 mol L-1 and the repeatability equal to ±0.68mV (0.7%). A dual-channel FIA manifold was therefore constructed, enabling automatic attainment of previous ionic strength andpH conditions and thus eliminating sample preparation steps. Slopes of 45.5±0.2mV decade -1 along a concentration range of 8.0x10-6 to 1.0x10-3 mol L-1 with a repeatability ±0.4mV (0.69%) were obtained. Analyses of real samples were performed, and recovery gave results ranging from 96.6 to 101.1%.

Flow injection potentiometric determination of chlorpromazine

New chlorpromazine selective electrodes with a tubular arrangement and no internal reference solution are proposed. Selective membranes are of poly(vinyl chloride) (PVC) with the tetraphenylborate•chlorpromazine (TPB•CPZ) ion-exchanger dissolved in o-nitrophenyl octyl ether (oNPOE). Analytical features of the electrodes were evaluated on a single-channel flow assembly having 500 µl injection volumes and flow-rates of 4.5 ml min−1. For a carrier solution of 3.3×10−3Min sodium sulphate, Nernstian responsewas observed over the concentration range 1.0×10−5 to 1.0×10−2 M. Average slopes were about 59mVdecade−1 and squared correlation coefficients were >0.9984. Slight hiper-Nernstian behaviour was observed in buffer solutions of 4.4 pH; average slopes were of 62.06mVdecade−1. The electrode displayed a good selectivity for CPZ, with respect to, several foreign inorganic and organic species. The selective electrodes were successfully applied to the analysis of pure solutions and pharmaceutical preparations. Proposed method allows the analysis of 84 samples h−1, producing wastewaters of low toxicity. The proposed method offers the advantage of simplicity, accuracy, applicability to coloured and turbid samples, and automation feasibility.

FIA potentiometric system based on periodate polymeric membrane sensors for the assessment of ascorbic acid in commercial drinks

Ascorbic acid is found in many food samples. Its clinical and technological importance demands an easyto- use, rapid, robust and inexpensive method of analysis. For this purpose, this work proposes a new flow procedure based on the oxidation of ascorbic acid by periodate. A new potentiometric periodate sensor was constructed to monitor this reaction. The selective membranes were of PVC with porphyrin-based sensing systems and a lipophilic cation as additive. The sensor displayed a near-Nernstian response for periodate over 1.0x10-2–6.0x10-6 M, with an anionic slope of 73.9 ± 0.9 mV decade-1. It was pH independent in acidic media and presented good selectivity features towards several inorganic anions. The flow set-up operated in double-channel, carrying a 5.0x10-4 M IO- 4 solution and a suitable buffer; these were mixed in a 50-cm reaction coil. The overall flow rate was 7 ml min-1 and the injection volume 70 µl. Under these conditions, a linear behaviour against concentration was observed for 17.7–194.0 µg ml-1, presenting slopes of 0.169 mV (mg/l)-1, a reproducibility of ±1.1 mV (n = 5), and a sampling rate of ~96 samples h-1. The proposed method was applied to the analysis of beverages and pharmaceuticals.

Laccase–Prussian blue film–graphene doped carbon paste modified electrode for carbamate pesticides quantification

A novel enzymatic biosensor for carbamate pesticides detection was developed through the direct immobilization of Trametes versicolor laccase on graphene doped carbon paste electrode functionalized with Prussianblue films (LACC/PB/GPE). Graphene was prepared by graphite sonication-assisted exfoliation and characterized by transmission electron microscopy and X-ray photoelectron spectro- scopy. The Prussian blue film electrodeposited onto graphene doped carbon paste electrode allowed considerable reduction of the charge transfer resistance and of the capacitance of the device.The combined effects of pH, enzyme concentration and incubation time on biosensor response were optimized using a 23 full-factorial statistical design and response surface methodology. Based on the inhibition of laccase activity and using 4-aminophenol as redox mediator at pH 5.0,LACC/PB/GPE exhibited suitable characteristics in terms of sensitivity, intra-and inter-day repeatability (1.8–3.8% RSD), reproducibility (4.1 and 6.3%RSD),selectivity(13.2% bias at the higher interference: substrate ratios tested),accuracy and stability(ca. twenty days)for quantification of five carbamates widely applied on tomato and potato crops.The attained detection limits ranged between 5.2×10−9 mol L−1(0.002 mg kg−1 w/w for ziram)and 1.0×10−7 mol L−1 (0.022 mg kg−1 w/w for carbofuran).Recovery values for the two tested spiking levels ranged from 90.2±0.1%(carbofuran)to 101.1±0.3% (ziram) for tomato and from 91.0±0.1%(formetanate)to 100.8±0.1%(ziram)for potato samples.The proposed methodology is appropriate to enable testing pesticide levels in food samples to fit with regulations and food inspections.

Electrochemical determination of the herbicide bentazone using a carbon nanotube b-Cyclodextrin modified electrode

An electrochemical sensor has been developed for the determination of the herbicide bentazone, based on a GC electrode modified by a combination of multiwalled carbon nanotubes (MWCNT) with b-cyclodextrin (b-CD) incorporated in a polyaniline film. The results indicate that the b-CD/MWCNT modified GC electrode exhibits efficient electrocatalytic oxidation of bentazone with high sensitivity and stability. A cyclic voltammetric method to determine bentazone in phosphate buffer solution at pH 6.0, was developed, without any previous extraction, clean-up, or derivatization steps, in the range of 10–80 mmolL 1, with a detection limit of 1.6 mmolL 1 in water. The results were compared with those obtained by an established HPLC technique. No statistically significant differences being found between both methods.

Bilirubin directly disrupts membrane lipid polarity and fluidity, protein order, and redox status in rat mitochondria

Background/Aims: Unconjugated bilirubin (UCB) impairs crucial aspects of cell function and induces apoptosis in primary cultured neurones. While mechanisms of cytotoxicity begin to unfold, mitochondria appear as potential primary targets. Methods: We used electron paramagnetic resonance spectroscopy analysis of isolated rat mitochondria to test the hypothesis that UCB physically interacts with mitochondria to induce structural membrane perturbation, leading to increased permeability, and subsequent release of apoptotic factors. Results: Our data demonstrate profound changes on mitochondrial membrane properties during incubation with UCB, including modified membrane lipid polarity and fluidity (P , 0:01), as well as disrupted protein mobility(P , 0:001). Consistent with increased permeability, cytochrome c was released from the intermembrane space(P , 0:01), perhaps uncoupling the respiratory chain and further increasing oxidative stress (P , 0:01). Both ursodeoxycholate, a mitochondrial-membrane stabilising agent, and cyclosporine A, an inhibitor of the permeability transition, almost completely abrogated UCB-induced perturbation. Conclusions: UCB directly interacts with mitochondria influencing membrane lipid and protein properties, redox status, and cytochrome c content. Thus, apoptosis induced by UCB may be mediated, at least in part, by physical perturbation of the mitochondrial membrane. These novel findings should ultimately prove useful to our evolving understanding of UCB cytotoxicity.

Into a new phase of the research on restructuring of work in the knowledge society: the Third WORKS General Assembly in Sofia (Bulgaria)

The WORKS Project started two years ago (2005), involving the efforts of research institutes of 13 European countries with the main purpose of improving the understanding of the major changes in work in the knowledge-based society, taking account both of global forces and the regional diversity within Europe. This research meeting in Sofia (Bulgaria) aimed to present synthetically the massive amount of data collected in the case studies (occupational and organisational) and with the quantitative research during last year.

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.

Bifacial dye-sensitized solar cells: a strategy to enhance overall efficiency based on transparent polyaniline electrode

Dye-sensitized solar cell (DSSC) is a promising solution to global energy and environmental problems because of its clean, low-cost, high efficiency, good durability, and easy fabrication. However, enhancing the efficiency of the DSSC still is an important issue. Here we devise a bifacial DSSC based on a transparent polyaniline (PANI) counter electrode (CE). Owing to the sunlight irradiation simultaneously from the front and the rear sides, more dye molecules are excited and more carriers are generated, which results in the enhancement of short-circuit current density and therefore overall conversion efficiency. The photoelectric properties of PANI can be improved by modifying with 4-aminothiophenol (4-ATP). The bifacial DSSC with 4-ATP/PANI CE achieves a light-to-electric energy conversion efficiency of 8.35%, which is increased by ,24.6% compared to the DSSC irradiated from the front only. This new concept along with promising results provides a new approach for enhancing the photovoltaic performances of solar cells.

Analysis of the nano-surface of a modified glassy carbon electrode by pseudo phase plane method

This paper presents the Pseudo phase plane (PPP) method for detecting the existence of a nanofilm on the nitroazobenzene-modified glassy carbon electrode (NAB-GC) system. This modified electrode systems and nitroazobenze-nanofilm were prepared by the electrochemical reduction of diazonium salt of NAB at the glassy carbon electrodes (GCE) in nonaqueous media. The IR spectra of the bare glassy carbon electrodes (GCE), the NAB-GC electrode system and the organic NAB film were recorded. The IR data of the bare GC, NAB-GC and NAB film were categorized into five series consisting of FILM1, GC-NAB1, GC1; FILM2, GC-NAB2, GC2; FILM3, GC-NAB3, GC3 and FILM4, GC-NAB4, GC4 respectively. The PPP approach was applied to each group of the data of unmodified and modified electrode systems with nanofilm. The results provided by PPP method show the existence of the NAB film on the modified GC electrode.

Characterization approach to modified glassy carbon electrode-nanofilm system within multidimensional scaling

The aim of this work is to characterize the nanofilm consisting of the benzoic acid-modified glassy carbon (GC) electrode system through multidimensional scaling space analysis. The surface modification is based on the electrochemical reaction between the GC electrode and benzoic acid-diazonium salt (BA-DAS). As a result, the nonofilms regarding the benzoic acid-glassy carbon (BA-GC) electrode surface was obtained. For the analysis of the naonfilm of BC-GC electrode system, the IR spectra of the modified BA-GC electrode surface, GC surface and BA-DAS were recorded in the spectral range of 599.84 – 3996.34 [cm–1]. The IR data vectors of the above three forms were processed by the using the multidimensional scaling space approach to demonstrate the existence of a nanofilm on the modified BA-GC electrode system. Two- and three-dimensional MDS profiles obtained by application of multidimensional scaling approach to the data sets {CG1,...,CG10}, {BA-GC1,...,BA-GC10} and {FILM1,...,FILM10} allow a good recognition of the nanofilm on the modified glassy carbon (GC) electrode system.

Localization studies of the FemXAB protein family in Staphylococcus aureus

Dissertação apresentada para a obtenção do Grau de Mestre em Genética Molecular e Biomedicina, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Quantitative description of the self-assembly of patchy particles into chains and rings

We numerically study a simple fluid composed of particles having a hard-core repulsion complemented by two patchy attractive sites on the particle poles. An appropriate choice of the patch angular width allows for the formation of ring structures which, at low temperatures and low densities, compete with the growth of linear aggregates. The simplicity of the model makes it possible to compare simulation results and theoretical predictions based on the Wertheim perturbation theory, specialized to the case in which ring formation is allowed. Such a comparison offers a unique framework for establishing the quality of the analytic predictions. We find that the Wertheim theory describes remarkably well the simulation results.

The influence of sludge characteristics from fullscale MBR in membrane filterability

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do grau de Mestre em Engenharia do Ambiente,perfil Sanitária