1000 resultados para Credit profile


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The potential profile for a model of squid axon membrane has been determined for two physiological states: resting and action states. The non-linear Poisson-Boltzmann equation has been solved by considering the volumetric charge densities due to charges dissolved in an electrolytic solution and fixed on both glycocalyx and cytoplasmatic proteins. Results showing the features of the potential profile along the outer electrolytic region are similar for both resting and action states. However, the potential fall along glycocalyx at action state is lower than at resting. A small variation in the Na+ concentration drastically affects the surface membrane potentials and vice versa. We conclude that effects on the potential profile due to surface lipidic bilayer charge and contiguous electric double layers are more relevant than those provoked by fixed charges distributed along the cell cytoplasm. (c) 2007 Elsevier B.V. All rights reserved.

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In this work we reported the synthesis and evaluation of the analgesic, anti-inflammatory, and platelet anti-aggregating properties of new 3-(arylideneamino)-2-methyl-6,7-methylenedioxy-quinazolin-4 (3H)-one derivatives (3a-j), designed as conformationally constrained analogues of analgesic 1,3- benzodioxolyl-N- acylhydrazones (1) previously developed at LASSBio. Target compounds were synthesized in very good yields exploiting abundant Brazilian natural product safrole (2) as starting material. The pharmacological assays lead us to identify compounds LASSBio-1240 (3b) and LASSBio-1272 (3d) as new analgesic prototypes, presenting an antinociceptive pro. le more potent and effective than dipyrone and indomethacin used, respectively, as standards in AcOH-induced abdominal constrictions assay and in the formalin test. These results confirmed the success in the exploitation of conformation restriction strategy for identification of novel cyclic N-acylhydrazone analogues with optimized analgesic profile (C) 2009 Elsevier Ltd. All rights reserved.

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This study describes the morphological evolution of gold grains in a lateritic weathering profile in an equatorial rainforest climate. Primary sources of gold are quartz veins associated with shallow granophyric intrusion. Gold grains were found in fresh ore, saprolite, transition zones, ferruginous duricrust, red latosol, and yellow latosol. Irregularly shaped grains predominate, with smaller proportions of dendritic and prismatic forms. Gold grains are weathered in the uppermost 10 m of the regolith. Mean gold grain size is maximum in the duricrust (> 125 mu m) and decreases progressively upward into the yellow latosol (<90 mu m). Voids and corrosion pits appear on grain surfaces, and progressive rounding is observed from the bottom of the profile to the top. Gold grains can be classified as either homogeneous or zoned with respect to their chemical composition. Homogeneous grains contain 2-15% Ag (mean 8.3%). Zoned grains have more variable Ag contents; grain cores have means of approximately 10% or 23% Ag, with Ag-poor zones of approximately 3.7% Ag along internal discontinuities and/or outer rims. Formation of Ag-poor rims is due to preferential depletion of silver. Processes responsible for duricrust formation may preserve some grains as large aggregates, but subsequent transformation into latosol further modifies them. (c) 2007 Elsevier Ltd. All rights reserved.

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We introduce jump processes in R(k), called density-profile processes, to model biological signaling networks. Our modeling setup describes the macroscopic evolution of a finite-size spin-flip model with k types of spins with arbitrary number of internal states interacting through a non-reversible stochastic dynamics. We are mostly interested on the multi-dimensional empirical-magnetization vector in the thermodynamic limit, and prove that, within arbitrary finite time-intervals, its path converges almost surely to a deterministic trajectory determined by a first-order (non-linear) differential equation with explicit bounds on the distance between the stochastic and deterministic trajectories. As parameters of the spin-flip dynamics change, the associated dynamical system may go through bifurcations, associated to phase transitions in the statistical mechanical setting. We present a simple example of spin-flip stochastic model, associated to a synthetic biology model known as repressilator, which leads to a dynamical system with Hopf and pitchfork bifurcations. Depending on the parameter values, the magnetization random path can either converge to a unique stable fixed point, converge to one of a pair of stable fixed points, or asymptotically evolve close to a deterministic orbit in Rk. We also discuss a simple signaling pathway related to cancer research, called p53 module.

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In the xylem vessels of susceptible hosts, such as citrus trees, Xylella fastidiosa forms biofilm-like colonies that can block water transport, which appears to correlate to disease symptoms. Besides aiding host colonization, bacterial biofilms play an important role in resistance against antimicrobial agents, for instance antimicrobial peptides (AMPs). Here, we show that gomesin, a potent AMP from a tarantula spider, modulates X. fastidiosa gene expression profile upon 60 min of treatment with a sublethal concentration. DNA microarray hybridizations revealed that among the upregulated coding sequences, some are related to biofilm production. In addition, we show that the biofilm formed by gomesin-treated bacteria is thicker than that formed by nontreated cells or cells exposed to streptomycin. We have also observed that the treatment of X. fastidiosa with a sublethal concentration of gomesin before inoculation in tobacco plants correlates with a reduction in foliar symptoms, an effect possibly due to the trapping of bacterial cells to fewer xylem vessels, given the enhancement in biofilm production. These results warrant further investigation of how X. fastidiosa would respond to the AMPs produced by citrus endophytes and by the insect vector, leading to a better understanding of the mechanism of action of these molecules on bacterial virulence.

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In this work, we study the effect of doping depth profile on the photocatalytic and surface properties of TiO(2) films. Two thin film layers of TiO(2) (200 nm) and Co (5 nm), respectively, were deposited by physical evaporation on glass substrate. These films were annealed for 1 s at 100 and 400 A degrees C and the Co layer was removed by chemical etching. Atomic force microscopy (AFM) phase images showed changes in the surface in function of thermal treatment. The grazing-incidence X-ray fluorescence (GIXRF) measurements indicated that the thermal treatment caused migration of Co atoms to below the surface, the depths found were between 19 and 29 nm. The contact angle showed distinct values in function of the doped profile or Co surface concentration. The UV-vis spectra presented a red shift with the increasing of thermal treatment. Photocatalytical assays were performed by methylene blue discoloration and the higher activity was found for TiO(2)-Co treated at 400 A degrees C, the ESI-MS showed the fragments formed during the methylene blue decomposition.

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2,4-Dinitrophenol (DNP) is classically known as a mitochondrial uncoupler and, at high concentrations, is toxic to a variety of cells. However, it has recently been shown that, at subtoxic concentrations, DNP protects neurons against a variety of insults and promotes neuronal differentiation and neuritogenesis. The molecular and cellular mechanisms underlying the beneficial neuroactive properties of DNP are still largely unknown. We have now used DNA microarray analysis to investigate changes in gene expression in rat hippocampal neurons in culture treated with low micromolar concentrations of DNP. Under conditions that did not affect neuronal viability, high-energy phosphate levels or mitochondrial oxygen consumption, DNP induced up-regulation of 275 genes and down-regulation of 231 genes. Significantly, several up-regulated genes were linked to intracellular cAMP signaling, known to be involved in neurite outgrowth, synaptic plasticity, and neuronal survival. Differential expression of specific genes was validated by quantitative RT-PCR using independent samples. Results shed light on molecular mechanisms underlying neuroprotection by DNP and point to possible targets for development of novel therapeutics for neurodegenerative disorders.

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Acute expression of E7 oncogene from human papillomavirus (HPV) 16 or HPV18 is sufficient to overcome tumor necrosis factor (TNF)-alpha cytostatic effect on primary human keratinocytes. In the present study, we investigated the molecular basis of E7-induced TNF resistance through a comparative analysis of the effect of this cytokine on the proliferation and global gene expression of normal and E7-expressing keratinocytes. Using E7 functional mutants, we show that E7-induced TNF resistance correlates with its ability to mediate pRb degradation and cell transformation. On the other hand, this effect does not depend on E7 sequences required to override DNA damage-induced cell cycle arrest or extend keratinocyte life span. Furthermore, we identified a group of 66 genes whose expression pattern differs between normal and E7-expressing cells upon cytokine treatment. These genes are mainly involved in cell cycle regulation suggesting that their altered expression may contribute to sustained cell proliferation even in the presence of a cytostatic stimulus. Differential expression of TCN1 (transcobalamin I), IFI44 (Interferon-induced protein 44), HMGB2 (high-mobility group box 2) and FUS [Fusion (involved in t(12; 16) in malignant liposarcoma)] among other genes were further confirmed by western-blot and/or real-time polymerase chain reaction. Moreover, FUS upregulation was detected in HPV-positive cervical high-grade squamous intraepithelial lesions when compared with normal cervical tissue. Further evaluation of the role of such genes in TNF resistance and HPVassociated disease development is warranted.

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In order to investigate the chemical profile of 14 specimens of Aplysina spp. marine sponges, we have developed a method based on LC-PDA-MS for the detection of bromotyrosine-derived metabolites. The method enabled the dereplication of three distinct chemotypes of bromotyrosine-derived compounds based on UV absorptions, which were further refined by electrospray ionization-mass spectrometry analysis of the brominated quasi-molecular ion clusters. This procedure led to either a single compound assignment, or a maximum of two possible isobaric compounds. The dereplication study indicated that the chemical profile of the 14 specimens of Aplysina spp. analyzed presented practically the same dibromotyrosine-derived compounds. The results obtained suggested a possible biogenetic pathway for the formation of dibromotyrosine-derived compounds of wide occurrence in Verongida sponges.

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An analytical procedure for the separation and quantification of 20 amino acids in cachacas has been developed involving C18 solid phase cleanup, derivatization with o-phthalaldehyde/2-mercaptoethanol, and reverse phase liquid chromatography with fluorescence detection. The detection limit was between 0.0050 (Cys) and 0.25 (Ser) mg L-1, whereas the recovery index varies from 69.5 (Lys) to 100 (Tyr)%. Relative standard deviations vary from 1.39 (Trp) to 13.4 (Glu)% and from 3.08 (Glu) to 13.5 (His) for the repeatability and intermediate precision, respectively. From the quantitative profile of amino acids in 41 cachacas, 5 turns, and 12 whisky samples, the following order of amino acids in significant quantities is observed: Gly = Ser < Cys < Ile < His < Pro = Asp < Asn < Tyr for cachaca; Phe < Glu = Gln = Val = Ala < His = Gly Thr = Arg = Tyr < Asn Ser = Lys = Pro < Cys = Asp for rum; and Ala = Asn < Trp < Gln = His = Met = Ile = Cys < Thr < Asp Leu < Phe = Lys < Ser = Gly = Tyr = Val < Glu = Pro < Arg for whisky samples. (C) 2007 Elsevier Ltd. All rights reserved.

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To identify chemical descriptors to distinguish Cuban from non-Cuban rums, analyses of 44 samples of rum from 15 different countries are described. To provide the chemical descriptors, analyses of the the mineral fraction, phenolic compounds, caramel, alcohols, acetic acid, ethyl acetate, ketones, and aldehydes were carried out. The analytical data were treated through the following chemometric methods: principal component analysis (PCA), partial least square-discriminate analysis (PLS-DA), and linear discriminate analysis (LDA). These analyses indicated 23 analytes as relevant chemical descriptors for the separation of rums into two distinct groups. The possibility of clustering the rum samples investigated through PCA analysis led to an accumulative percentage of 70.4% in the first three principal components, and isoamyl alcohol, n-propyl alcohol, copper, iron, 2-furfuraldehyde (furfuraldehyde), phenylmethanal (benzaldehyde), epicatechin, and vanillin were used as chemical descriptors. By applying the PLS-DA technique to the whole set of analytical data, the following analytes have been selected as descriptors: acetone, sec-butyl alcohol, isobutyl alcohol, ethyl acetate, methanol, isoamyl alcohol, magnesium, sodium, lead, iron, manganese, copper, zinc, 4-hydroxy3,5-dimethoxybenzaldehyde (syringaldehyde), methaldehyde (formaldehyde), 5-hydroxymethyl-2furfuraldehyde (5-HMF), acetalclehyde, 2-furfuraldehyde, 2-butenal (crotonaldehyde), n-pentanal (valeraldehyde), iso-pentanal (isovaleraldehyde), benzaldehyde, 2,3-butanodione monoxime, acetylacetone, epicatechin, and vanillin. By applying the LIDA technique, a model was developed, and the following analytes were selected as descriptors: ethyl acetate, sec-butyl alcohol, n-propyl alcohol, n-butyl alcohol, isoamyl alcohol, isobutyl alcohol, caramel, catechin, vanillin, epicatechin, manganese, acetalclehyde, 4-hydroxy-3-methoxybenzoic acid, 2-butenal, 4-hydroxy-3,5-dimethoxybenzoic acid, cyclopentanone, acetone, lead, zinc, calcium, barium, strontium, and sodium. This model allowed the discrimination of Cuban rums from the others with 88.2% accuracy.

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The use of roll-formed products in automotive, furniture, buildings etc. increases every year due to the low part-production cost and the complicated cross-sections that can be produced. The limitation with roll-forming until recent years is that one could only produce profiles with a constant cross-section in the longitudinal direction. About eight years ago ORTIC AB [1] developed a machine in which it was possible to produce profiles with a variable width (“3D roll-forming”) for the building industry. Experimental equipment was recently built for research and prototyping of profiles with variable cross-section in both width and depth for the automotive industry. The objective with the current study is to investigate the new tooling concept that makes it possible to roll-form hat-profiles, made of ultra high strength steel, with variable cross-section in depth and width. The result shows that it is possible to produce 3D roll-formed profiles with close tolerances.

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This paper traces the developments of credit risk modeling in the past 10 years. Our work can be divided into two parts: selecting articles and summarizing results. On the one hand, by constructing an ordered logit model on historical Journal of Economic Literature (JEL) codes of articles about credit risk modeling, we sort out articles which are the most related to our topic. The result indicates that the JEL codes have become the standard to classify researches in credit risk modeling. On the other hand, comparing with the classical review Altman and Saunders(1998), we observe some important changes of research methods of credit risk. The main finding is that current focuses on credit risk modeling have moved from static individual-level models to dynamic portfolio models.

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This paper presents the techniques of likelihood prediction for the generalized linear mixed models. Methods of likelihood prediction is explained through a series of examples; from a classical one to more complicated ones. The examples show, in simple cases, that the likelihood prediction (LP) coincides with already known best frequentist practice such as the best linear unbiased predictor. The paper outlines a way to deal with the covariate uncertainty while producing predictive inference. Using a Poisson error-in-variable generalized linear model, it has been shown that in complicated cases LP produces better results than already know methods.