997 resultados para enzymatic properties


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Hydroxycinnamic acids (HCAs) are important phytochemicals possessing significant biological properties. Several investigators have studied in vitro antioxidant activity of HCAs in detail. In this review, we have gathered the studies focused on the structure-activity relationships (SARs) of these compounds that have used medicinal chemistry to generate more potent antioxidant molecules. Most of the reports indicated that the presence of an unsaturated bond on the side chain of HCAs is vital to their activity. The structural features that were reported to be of importance to the antioxidant activity were categorized as follows: modifications of the aromatic ring, which include alterations in the number and position of hydroxy groups and insertion of electron donating or withdrawing moieties as well as modifications of the carboxylic function that include esterification and amidation process. Furthermore, reports that have addressed the influence of physicochemical properties including redox potential, lipid solubility and dissociation constant on the antioxidant activity were also summarized. Finally, the pro-oxidant effect of HCAs in some test systems was addressed. Most of the investigations concluded that the presence of ortho-dihydroxy phenyl group (catechol moiety) is of significant importance to the antioxidant activity, while, the presence of three hydroxy groups does not necessarily improve the activity. Optimization of the structure of molecular leads is an important task of modern medicinal chemistry and its accomplishment relies on the careful assessment of SARs. SAR studies on HCAs can identify the most successful antioxidants that could be useful for management of oxidative stress-related diseases.

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Modern real-time systems, with a more flexible and adaptive nature, demand approaches for timeliness evaluation based on probabilistic measures of meeting deadlines. In this context, simulation can emerge as an adequate solution to understand and analyze the timing behaviour of actual systems. However, care must be taken with the obtained outputs under the penalty of obtaining results with lack of credibility. Particularly important is to consider that we are more interested in values from the tail of a probability distribution (near worst-case probabilities), instead of deriving confidence on mean values. We approach this subject by considering the random nature of simulation output data. We will start by discussing well known approaches for estimating distributions out of simulation output, and the confidence which can be applied to its mean values. This is the basis for a discussion on the applicability of such approaches to derive confidence on the tail of distributions, where the worst-case is expected to be.

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A recent trend in distributed computer-controlled systems (DCCS) is to interconnect the distributed computing elements by means of multi-point broadcast networks. Since the network medium is shared between a number of network nodes, access contention exists and must be solved by a medium access control (MAC) protocol. Usually, DCCS impose real-time constraints. In essence, by real-time constraints we mean that traffic must be sent and received within a bounded interval, otherwise a timing fault is said to occur. This motivates the use of communication networks with a MAC protocol that guarantees bounded access and response times to message requests. PROFIBUS is a communication network in which the MAC protocol is based on a simplified version of the timed-token protocol. In this paper we address the cycle time properties of the PROFIBUS MAC protocol, since the knowledge of these properties is of paramount importance for guaranteeing the real-time behaviour of a distributed computer-controlled system which is supported by this type of network.

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It has been shown that in reality at least two general scenarios of data structuring are possible: (a) a self-similar (SS) scenario when the measured data form an SS structure and (b) a quasi-periodic (QP) scenario when the repeated (strongly correlated) data form random sequences that are almost periodic with respect to each other. In the second case it becomes possible to describe their behavior and express a part of their randomness quantitatively in terms of the deterministic amplitude–frequency response belonging to the generalized Prony spectrum. This possibility allows us to re-examine the conventional concept of measurements and opens a new way for the description of a wide set of different data. In particular, it concerns different complex systems when the ‘best-fit’ model pretending to be the description of the data measured is absent but the barest necessity of description of these data in terms of the reduced number of quantitative parameters exists. The possibilities of the proposed approach and detection algorithm of the QP processes were demonstrated on actual data: spectroscopic data recorded for pure water and acoustic data for a test hole. The suggested methodology allows revising the accepted classification of different incommensurable and self-affine spatial structures and finding accurate interpretation of the generalized Prony spectroscopy that includes the Fourier spectroscopy as a partial case.

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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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The main aims of the present study are simultaneously to relate the brazing parameters with: (i) the correspondent interfacial microstructure, (ii) the resultant mechanical properties and (iii) the electrochemical degradation behaviour of AISI 316 stainless steel/alumina brazed joints. Filler metals on such as Ag–26.5Cu–3Ti and Ag–34.5Cu–1.5Ti were used to produce the joints. Three different brazing temperatures (850, 900 and 950 °C), keeping a constant holding time of 20 min, were tested. The objective was to understand the influence of the brazing temperature on the final microstructure and properties of the joints. The mechanical properties of the metal/ceramic (M/C) joints were assessed from bond strength tests carried out using a shear solicitation loading scheme. The fracture surfaces were studied both morphologically and structurally using scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS) and X-ray diffraction analysis (XRD). The degradation behaviour of the M/C joints was assessed by means of electrochemical techniques. It was found that using a Ag–26.5Cu–3Ti brazing alloy and a brazing temperature of 850 °C, produces the best results in terms of bond strength, 234 ± 18 MPa. The mechanical properties obtained could be explained on the basis of the different compounds identified on the fracture surfaces by XRD. On the other hand, the use of the Ag–34.5Cu–1.5Ti brazing alloy and a brazing temperature of 850 °C produces the best results in terms of corrosion rates (lower corrosion current density), 0.76 ± 0.21 μA cm−2. Nevertheless, the joints produced at 850 °C using a Ag–26.5Cu–3Ti brazing alloy present the best compromise between mechanical properties and degradation behaviour, 234 ± 18 MPa and 1.26 ± 0.58 μA cm−2, respectively. The role of Ti diffusion is fundamental in terms of the final value achieved for the M/C bond strength. On the contrary, the Ag and Cu distribution along the brazed interface seem to play the most relevant role in the metal/ceramic joints electrochemical performance.

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Chitosan biocompatibility and biodegradability properties make this biopolymer promising for the development of advanced internal fixation devices for orthopedic applications. This work presents a detailed study on the production and characterization of three dimensional (3D) dense, non-porous, chitosan-based structures, with the ability to be processed in different shapes, and also with high strength and stiffness. Such features are crucial for the application of such 3D structures as bioabsorbable implantable devices. The influence of chitosan's molecular weight and the addition of one plasticizer (glycerol) on 3D dense chitosan-based products' biomechanical properties were explored. Several specimens were produced and in vitro studies were performed in order to assess the cytotoxicity of these specimens and their physical behavior throughout the enzymatic degradation experiments. The results point out that glycerol does not impact on cytotoxicity and has a high impact in improving mechanical properties, both elasticity and compressive strength. In addition, human mesenchymal stem/stromal cells (MSC) were used as an ex-vivo model to study cell adhesion and proliferation on these structures, showing promising results with fold increase values in total cell number similar to the ones obtained in standard cell culture flasks. (C) 2014 Elsevier Ltd. All rights reserved.

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A new inherently chiral calix[4]arene ICC 1 has been disclosed. The dissymmetry of 1 is generated from a chirality plane in the quinol moiety of a 1,3-bridged bicyclic calix[4]arene. ICC 1 has been resolved by enantioselective HPLC, and the chiroptical properties of both isolated antipodes (pS)-1 and (pR)-1 confirm their enantiomeric nature. The absolute configuration of the (pS)-1/(pR)-1 enantiomeric pair was established through time-dependent density functional theory (TDDFT) calculations of electronic circular dichroism (CD) spectra. (C) 2014 Elsevier Ltd. All rights reserved.

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Supramolecular chirality was achieved in solutions and thin films of a calixarene-containing chiral aryleneethynylene copolymer. The observed chiroptical activity, which is primarily allied with the formation of aggregates of high molecular weight polymer chains, is the result of a combination of intrachain and interchain effects. The former arises by the adoption of an induced helix-sense by the polymer main-chain while the latter comes from the exciton coupling of aromatic backbone transitions. The co-existence of bulky bis-calixKlarene units and chiral side-chains on the polymer skeleton prevents efficient pi-stacking of neighbouring chains, keeping the chiral assembly highly emissive. In contrast, for a model polymer lacking calixarene moieties, the chiroptical activity is dominated by strong interchain exciton couplings as a result of more favourable packing of polymer chains, leading to a marked decrease of photoluminescence in the aggregate state. The enantiomeric recognition abilities of both polymers towards (R)- and (S)-alpha-methylbenzylamine were examined. It was found that a significant enantiodiscrimination is exhibited by the calixarene-based polymer in the aggregate state.

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A series of six new mixed-ligand dinuclear Mn(II, II) complexes of three different hydrazone Schiff bases (H3L1, H3L2 and H3L3), derived from condensation of the aromatic acid hydrazides benzohydrazide, 2-aminobenzohydrazide or 2-hydroxybenzohydrazide, with 2,3-dihydroxy benzaldehyde, respectively, is reported. Reactions of Mn(NO3)(2) center dot 4H(2)O with the H3L1-3 compounds, in the presence of pyridine (1 : 1 : 1 mole ratio), in methanol at room temperature, yield [Mn(H2L1)(py)(H2O)](2)(NO3)(2) center dot 2H(2)O (1 center dot 2H(2)O), [Mn(H2L2)(py)(CH3OH)](2)(NO3)(2) center dot 4H(2)O (2 center dot 4H(2)O) and [Mn(H2L3)(py)(H2O)](2)(NO3)(2) (3) respectively, whereas the use of excess pyridine yields complexes with two axially coordinated pyridine molecules at each Mn(II) centre, viz. [Mn(H2L1)(py)(2)] 2(NO3)(2) center dot H2O (4 center dot H2O), [Mn(H2L2)(py) H-O (6 center dot 2CH(3)OH), respectively. In all the complexes, the (H2L1-3)-ligand coordinates in the keto form. Complexes 1 center dot 2H(2)O, 2 center dot 4H(2)O, 4 center dot H2O, 5 center dot 2H(2)O and 6 center dot 2CH(3)OH are characterized by single crystal X-ray diffraction analysis. The complexes 1, 2 and 6, having different coordination environments, have been selected for variable temperature magnetic susceptibility measurements to examine the nature of magnetic interaction between magnetically coupled Mn(II) centres and also for exploration of the catalytic activity towards microwave assisted oxidation of alcohols. A yield of 81% (acetophenone) is obtained using a maximum of 0.4% molar ratio of catalyst relative to the substrate in the presence of TEMPO and in aqueous basic solution, under mild conditions.

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Laccases are multi-copper oxidases that oxidise a wide range of substrates including phenol and aniline derivatives, which could be further involved in coupling reactions leading to the formation of dimeric and trimeric structures. This paper describes the enzyme-mediated dimerisation of several ortho and meta, para-disubstituted aromatic amines into phenazine ("head-to-tail" dimers) and phenoxazinone chromophores. The redox properties of substituted aromatic amines were studied by cyclic voltammetry and the kinetic constants of CotA and Trametes versicolor laccases were measured for selected aromatic amines. The structure of novel enzymatically synthesised phenazine and phenoxazinone dyes using CotA laccase was assessed by NMR and MS. Overall our data show that this enzymatic green process is an efficient alternative to the classic chemical oxidation of aromatic amines and phenols, with an impact on the broad field of applications of these heterocyclic compounds.

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This work demonstrates the feasibility of using polymeric micro- and nanofiber-composed films and liquid crystals as electrically switchable scattering light shutters. We present a concept of electro-optic device based on an innovative combination of two mature technologies: optics of nematic liquid crystals and electrospinning of nanofibers. These devices have electric and optical characteristics far superior to other comparable methods. The simulation presented shows results that are highly consistent with those of experiments and that explain the working mechanism of the devices.

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A swift chemical route to synthesize Co-doped SnO2 nanopowders is described. Pure and highly stable Sn1-xCoxO2-delta (0 <= x <= 0.15) crystalline nanoparticles were synthesized, with mean grain sizes <5 nm and the dopant element homogeneously distributed in the SnO2 matrix. The UV-visible diffuse reflectance spectra of the Sn1-xCoxO2-delta samples reveal red shifts, the optical bandgap energies decreasing with increasing Co concentration. The samples' Urbach energies were calculated and correlated with their bandgap energies. The photocatalytic activity of the Sn1-xCoxO2-delta samples was investigated for the 4-hydroxylbenzoic acid (4-HBA) degradation process. A complete photodegradation of a 10 ppm 4-HBA solution was achieved using 0.02% (w/w) of Sn0.95Co0.05O2-delta nanoparticles in 60 min of irradiation. (C) 2014 Elsevier B.V. All rights reserved.

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This study focus on the probabilistic modelling of mechanical properties of prestressing strands based on data collected from tensile tests carried out in Laboratório Nacional de Engenharia Civil (LNEC), Portugal, for certification purposes, and covers a period of about 9 years of production. The strands studied were produced by six manufacturers from four countries, namely Portugal, Spain, Italy and Thailand. Variability of the most important mechanical properties is examined and the results are compared with the recommendations of the Probabilistic Model Code, as well as the Eurocodes and earlier studies. The obtained results show a very low variability which, of course, benefits structural safety. Based on those results, probabilistic models for the most important mechanical properties of prestressing strands are proposed.

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An aneurysm is a localized blood-filled dilatation of an artery whose consequences can be deadly. One of its current treatments is endovascular aneurysm repair, a minimally invasive procedure in which an endoprosthesis, called a stent-graft, is placed transluminally to prevent wall rupture. Early stent-grafts were custom designed for the patient through the assembling of off-the-shelf components by the operating surgeon. However, nowadays, stent-grafts have become a commercial product. The existing endoprostheses differ in several aspects, such as shape design and materials, but they have in common a metallic scaffold with a polymeric covering membrane. This article aims to gather relevant information for those who wish to understand the principles of stent-grafts and even to develop new devices. Hence, a stent-graft classification based on different characteristics is presented and the desired features for an ideal device are pointed out. Additionally, the materials currently in use to fabricate this type of endoprosthesis are reviewed and new materials are suggested.