894 resultados para Feature mediator


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We have reconsidered the Bell-Lavis model of liquid water and investigated its relation to its isotropic version, the antiferromagnetic Blume-Emery-Griffiths model on the triangular lattice. Our study was carried out by means of an exact solution on the sequential Husimi cactus. We show that the ground states of both models share the same topology and that fluid phases (gas and low- and high-density liquids) can be mapped onto magnetic phases (paramagnetic, antiferromagnetic, and dense paramagnetic, respectively). Both models present liquid-liquid coexistence and several thermodynamic anomalies. This result suggests that anisotropy introduced through orientational variables play no specific role in producing the density anomaly, in agreement with a similar conclusion discussed previously following results for continuous soft core,models. We propose that the presence of liquid anomalies may be related to energetic frustration, a feature common to both models.

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Supersymmetric theories with bilinear R-parity violation can give rise to the observed neutrino masses and mixings. One important feature of such models is that the lightest supersymmetric particle might have a sufficiently large lifetime to produce detached vertices. Working in the framework of supergravity models, we analyze the potential of the LHCb experiment to search for supersymmetric models exhibiting bilinear R-parity violation. We show that the LHCb experiment can probe a large fraction of the m(0)circle times m(1/2), being able to explore gluino masses up to 1.3 TeV. The LHCb discover potential for these kinds of models is similar to the ATLAS and CMS ones in the low luminosity phase of operation of the LHC.

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We investigate a neutrino mass model in which the neutrino data is accounted for by bilinear R-parity violating supersymmetry with anomaly mediated supersymmetry breaking. We focus on the CERN Large Hadron Collider (LHC) phenomenology, studying the reach of generic supersymmetry search channels with leptons, missing energy and jets. A special feature of this model is the existence of long-lived neutralinos and charginos which decay inside the detector leading to detached vertices. We demonstrate that the largest reach is obtained in the displaced vertices channel and that practically all of the reasonable parameter space will be covered with an integrated luminosity of 10 fb(-1). We also compare the displaced vertex reaches of the LHC and Tevatron.

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Magnetic nanoparticles (NP) of magnetite (Fe(3)O(4)) coated with oleic acid (OA) and dodecanoic acid (DA) were synthesized and investigated through transmission electron microscopy (TEM), magnetization M, and ac magnetic susceptibility measurements. The OA coated samples were produced with different magnetic concentrations (78%, 76%, and 65%) and the DA sample with 63% of Fe(3)O(4). Images from TEM indicate that the NP have a nearly spherical geometry and mean diameter similar to 5.5 nm. Magnetization measurements, performed in zero-field cooled (ZFC) and field cooled processes under different external magnetic fields H, exhibited a maximum at a given temperature T(B) in the ZFC curves, which depends on the NP coating (OA or DA), magnetite concentration, and H. The temperature T(B) decreases monotonically with increasing H and, for a given H, the increase in the magnetite concentration results in an increase in T(B). The observed behavior is related to the dipolar interaction between NP, which seems to be an important mechanism in all samples studied. This is supported by the results of the ac magnetic susceptibility chi(ac) measurements, where the temperature in which chi' peaks for different frequencies follows the Vogel-Fulcher model, a feature commonly found in systems with dipolar interactions. Curves of H versus T(B)/T(B) (H=0) for samples with different coatings and magnetite concentrations collapse into a universal curve, indicating that the qualitative magnetic behavior of the samples may be described by the NP themselves, instead of the coating or the strength of the dipolar interaction. Below T(B), M versus H curves show a coercive field (H(C)) that increases monotonically with decreasing temperature. The saturation magnetization (M(S)) follows the Bloch's law and values of M(S) at room temperature as high as 78 emu/g were estimated, a result corresponding to similar to 80% of the bulk value. The overlap of M/M(S) versus H/T curves for a given sample and the low H(C) at high temperatures suggest superparamagnetic behavior in all samples studied. The overlap of M/M(S) versus H curves at constant temperature for different samples indicates that the NP magnetization behavior is preserved, independently of the coating and magnetite concentration. (C) 2010 American Institute of Physics. [doi: 10.1063/1.3311611]

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The squashed Kaluza-Klien (KK) black holes differ from the Schwarzschild black holes with asymptotic flatness or the black strings even at energies for which the KK modes are not excited yet, so that squashed KK black holes open a window in higher dimensions. Another important feature is that the squashed KK black holes are apparently stable and, thereby, let us avoid the Gregory-Laflamme instability. In the present paper, the evolution of scalar and gravitational perturbations in time and frequency domains is considered for these squashed KK black holes. The scalar field perturbations are analyzed for general rotating squashed KK black holes. Gravitational perturbations for the so-called zero mode are shown to be decayed for nonrotating black holes, in concordance with the stability of the squashed KK black holes. The correlation of quasinormal frequencies with the size of extra dimension is discussed.

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Online music databases have increased significantly as a consequence of the rapid growth of the Internet and digital audio, requiring the development of faster and more efficient tools for music content analysis. Musical genres are widely used to organize music collections. In this paper, the problem of automatic single and multi-label music genre classification is addressed by exploring rhythm-based features obtained from a respective complex network representation. A Markov model is built in order to analyse the temporal sequence of rhythmic notation events. Feature analysis is performed by using two multi-variate statistical approaches: principal components analysis (unsupervised) and linear discriminant analysis (supervised). Similarly, two classifiers are applied in order to identify the category of rhythms: parametric Bayesian classifier under the Gaussian hypothesis (supervised) and agglomerative hierarchical clustering (unsupervised). Qualitative results obtained by using the kappa coefficient and the obtained clusters corroborated the effectiveness of the proposed method.

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One important issue implied by the finite nature of real-world networks regards the identification of their more external (border) and internal nodes. The present work proposes a formal and objective definition of these properties, founded on the recently introduced concept of node diversity. It is shown that this feature does not exhibit any relevant correlation with several well-established complex networks measurements. A methodology for the identification of the borders of complex networks is described and illustrated with respect to theoretical (geographical and knitted networks) as well as real-world networks (urban and word association networks), yielding interesting results and insights in both cases.

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We theoretically investigate the Rashba spin-orbit interaction in InAs/GaSb quantum wells (QWs). We find that the Rashba spin-splitting (RSS) sensitively depends on the thickness of the InAs layer. The RSS exhibits nonlinear behavior for narrow InAs/GaSb QWs and the oscillating feature for wide InAs/GaSb QWs. The nonlinear and oscillating behaviors arise from the weakened and enhanced interband coupling. The RSS also show asymmetric features respect to the direction of the external electric field. (C) 2008 American Institute of Physics.

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Background: Schistosoma mansoni is the major causative agent of schistosomiasis. The parasite takes advantage of host signals to complete its development in the human body. Tumor necrosis factor-alpha (TNF-alpha) is a human cytokine involved in skin inflammatory responses, and although its effect on the adult parasite's metabolism and egg-laying process has been previously described, a comprehensive assessment of the TNF-alpha pathway and its downstream molecular effects is lacking. Methodology/Principal Findings: In the present work we describe a possible TNF-alpha receptor (TNFR) homolog gene in S. mansoni (SmTNFR). SmTNFR encodes a complete receptor sequence composed of 599 amino acids, and contains four cysteine-rich domains as described for TNFR members. Real-time RT-PCR experiments revealed that SmTNFR highest expression level is in cercariae, 3.5 (+/- 0.7) times higher than in adult worms. Downstream members of the known human TNF-alpha pathway were identified by an in silico analysis, revealing a possible TNF-alpha signaling pathway in the parasite. In order to simulate parasite's exposure to human cytokine during penetration of the skin, schistosomula were exposed to human TNF-alpha just 3 h after cercariae-to-schistosomula in vitro transformation, and large-scale gene expression measurements were performed with microarrays. A total of 548 genes with significantly altered expression were detected, when compared to control parasites. In addition, treatment of adult worms with TNF-alpha caused a significantly altered expression of 1857 genes. Interestingly, the set of genes altered in adults is different from that of schistosomula, with 58 genes in common, representing 3% of altered genes in adults and 11% in 3 h-old early schistosomula. Conclusions/Significance: We describe the possible molecular elements and targets involved in human TNF-alpha effect on S. mansoni, highlighting the mechanism by which recently transformed schistosomula may sense and respond to this host mediator at the site of cercarial penetration into the skin.

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The valence and core levels of In(2)O(3) and Sn-doped In(2)O(3) have been studied by hard x-ray photoemission spectroscopy (hv = 6000 eV) and by conventional Al K alpha (hv = 1486.6 eV) x-ray photoemission spectroscopy. The experimental spectra are compared with density-functional theory calculations. It is shown that structure deriving from electronic levels with significant In or Sn 5s character is selectively enhanced under 6000 eV excitation. This allows us to infer that conduction band states in Sn-doped samples and states at the bottom of the valence band both contain a pronounced In 5s contribution. The In 3d core line measured at hv = 1486.6 eV for both undoped and Sn-doped In(2)O(3) display an asymmetric lineshape, and may be fitted with two components associated with screened and unscreened final states. The In 3d core line spectra excited at hv = 6000 eV for the Sn-doped samples display pronounced shoulders and demand a fit with two components. The In 3d core line spectrum for the undoped sample can also be fitted with two components, although the relative intensity of the component associated with the screened final state is low, compared to excitation at 1486.6 eV. These results are consistent with a high concentration of carriers confined close to the surface of nominally undoped In(2)O(3). This conclusion is in accord with the fact that a conduction band feature observed for undoped In(2)O(3) in Al K alpha x-ray photoemission is much weaker than expected in hard x-ray photoemission.

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Thanks to recent advances in molecular biology, allied to an ever increasing amount of experimental data, the functional state of thousands of genes can now be extracted simultaneously by using methods such as cDNA microarrays and RNA-Seq. Particularly important related investigations are the modeling and identification of gene regulatory networks from expression data sets. Such a knowledge is fundamental for many applications, such as disease treatment, therapeutic intervention strategies and drugs design, as well as for planning high-throughput new experiments. Methods have been developed for gene networks modeling and identification from expression profiles. However, an important open problem regards how to validate such approaches and its results. This work presents an objective approach for validation of gene network modeling and identification which comprises the following three main aspects: (1) Artificial Gene Networks (AGNs) model generation through theoretical models of complex networks, which is used to simulate temporal expression data; (2) a computational method for gene network identification from the simulated data, which is founded on a feature selection approach where a target gene is fixed and the expression profile is observed for all other genes in order to identify a relevant subset of predictors; and (3) validation of the identified AGN-based network through comparison with the original network. The proposed framework allows several types of AGNs to be generated and used in order to simulate temporal expression data. The results of the network identification method can then be compared to the original network in order to estimate its properties and accuracy. Some of the most important theoretical models of complex networks have been assessed: the uniformly-random Erdos-Renyi (ER), the small-world Watts-Strogatz (WS), the scale-free Barabasi-Albert (BA), and geographical networks (GG). The experimental results indicate that the inference method was sensitive to average degree k variation, decreasing its network recovery rate with the increase of k. The signal size was important for the inference method to get better accuracy in the network identification rate, presenting very good results with small expression profiles. However, the adopted inference method was not sensible to recognize distinct structures of interaction among genes, presenting a similar behavior when applied to different network topologies. In summary, the proposed framework, though simple, was adequate for the validation of the inferred networks by identifying some properties of the evaluated method, which can be extended to other inference methods.

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Background: The inference of gene regulatory networks (GRNs) from large-scale expression profiles is one of the most challenging problems of Systems Biology nowadays. Many techniques and models have been proposed for this task. However, it is not generally possible to recover the original topology with great accuracy, mainly due to the short time series data in face of the high complexity of the networks and the intrinsic noise of the expression measurements. In order to improve the accuracy of GRNs inference methods based on entropy (mutual information), a new criterion function is here proposed. Results: In this paper we introduce the use of generalized entropy proposed by Tsallis, for the inference of GRNs from time series expression profiles. The inference process is based on a feature selection approach and the conditional entropy is applied as criterion function. In order to assess the proposed methodology, the algorithm is applied to recover the network topology from temporal expressions generated by an artificial gene network (AGN) model as well as from the DREAM challenge. The adopted AGN is based on theoretical models of complex networks and its gene transference function is obtained from random drawing on the set of possible Boolean functions, thus creating its dynamics. On the other hand, DREAM time series data presents variation of network size and its topologies are based on real networks. The dynamics are generated by continuous differential equations with noise and perturbation. By adopting both data sources, it is possible to estimate the average quality of the inference with respect to different network topologies, transfer functions and network sizes. Conclusions: A remarkable improvement of accuracy was observed in the experimental results by reducing the number of false connections in the inferred topology by the non-Shannon entropy. The obtained best free parameter of the Tsallis entropy was on average in the range 2.5 <= q <= 3.5 (hence, subextensive entropy), which opens new perspectives for GRNs inference methods based on information theory and for investigation of the nonextensivity of such networks. The inference algorithm and criterion function proposed here were implemented and included in the DimReduction software, which is freely available at http://sourceforge.net/projects/dimreduction and http://code.google.com/p/dimreduction/.

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Background: Persistent infection by high risk HPV types (e.g. HPV-16, -18, -31, and -45) is the main risk factor for development of cervical intraepithelial neoplasia and cervical cancer. Tumor necrosis factor (TNF) is a key mediator of epithelial cell inflammatory response and exerts a potent cytostatic effect on normal or HPV16, but not on HPV18 immortalized keratinocytes. Moreover, several cervical carcinoma-derived cell lines are resistant to TNF anti-proliferative effect suggesting that the acquisition of TNF-resistance may constitute an important step in HPV-mediated carcinogenesis. In the present study, we compared the gene expression profiles of normal and HPV16 or 18 immortalized human keratinocytes before and after treatment with TNF for 3 or 60 hours. Methods: In this study, we determined the transcriptional changes 3 and 60 hours after TNF treatment of normal, HPV16 and HPV18 immortalized keratinocytes by microarray analysis. The expression pattern of two genes observed by microarray was confirmed by Northern Blot. NF-kappa B activation was also determined by electrophoretic mobility shift assay (EMSA) using specific oligonucleotides and nuclear protein extracts. Results: We observed the differential expression of a common set of genes in two TNF-sensitive cell lines that differs from those modulated in TNF-resistant ones. This information was used to define genes whose differential expression could be associated with the differential response to TNF, such as: KLK7 (kallikrein 7), SOD2 (superoxide dismutase 2), 100P (S100 calcium binding protein P), PI3 (protease inhibitor 3, skin-derived), CSTA (cystatin A), RARRES1 (retinoic acid receptor responder 1), and LXN (latexin). The differential expression of the KLK7 and SOD2 transcripts was confirmed by Northern blot. Moreover, we observed that SOD2 expression correlates with the differential NF-kappa B activation exhibited by TNF-sensitive and TNF-resistant cells. Conclusion: This is the first in depth analysis of the differential effect of TNF on normal and HPV16 or HPV18 immortalized keratinocytes. Our findings may be useful for the identification of genes involved in TNF resistance acquisition and candidate genes which deregulated expression may be associated with cervical disease establishment and/or progression.

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In order for solar energy to serve as a primary energy source, it must be paired with energy storage on a massive scale. At this scale, solar fuels and energy storage in chemical bonds is the only practical approach. Solar fuels are produced in massive amounts by photosynthesis with the reduction of CO(2) by water to give carbohydrates but efficiencies are low. In photosystem II (PSII), the oxygen-producing site for photosynthesis, light absorption and sensitization trigger a cascade of coupled electron-proton transfer events with time scales ranging from picoseconds to microseconds. Oxidative equivalents are built up at the oxygen evolving complex (OEC) for water oxidation by the Kok cycle. A systematic approach to artificial photo synthesis is available based on a ""modular approach"" in which the separate functions of a final device are studied separately, maximized for rates and stability, and used as modules in constructing integrated devices based on molecular assemblies, nanoscale arrays, self-assembled monolayers, etc. Considerable simplification is available by adopting a ""dyesensitized photoelectrosynthesis cell"" (DSPEC) approach inspired by dye-sensitized solar cells (DSSCs). Water oxidation catalysis is a key feature, and significant progress has been made in developing a single-site solution and surface catalysts based on polypyridyl complexes of Ru. In this series, ligand variations can be used to tune redox potentials and reactivity over a wide range. Water oxidation electrocatalysis has been extended to chromophore-catalyst assemblies for both water oxidation and DSPEC applications.

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Prussian Blue has been introduced as a mediator to achieve stable, sensitive, reproducible, and interference-free biosensors. However, Na(+), Li(+), H(+), and all group II cations are capable to block the activity of Prussian Blue and, because Na(+) can be found in most human fluids, Prussian Blue analogs have already been developed to overcome this problem. These analogs, such as copper hexacyanoferrate, have also been introduced in a conducting polypyrrole matrix to create hybrid materials (copper hexacyanoferrate/polypyrrole, CuHCNFe/Ppy) with improved mechanical and electrochemical characteristics. Nowadays, the challenges in amperometric enzymatic biosensors consist of improving the enzyme immobilization and in making the chemical signal transduction more efficient. The incorporation of nanostructured materials in biosensors can optimize both steps and a nanostructured hybrid CuHCNFe/Ppy mediator has been developed using a template of colloidal polystyrene particles. The nanostructured material has achieved sensitivities 7.6 times higher than the bulk film during H(2)O(2) detection and it has also presented better results in other analytical parameters such as time response and detection limit. Besides, the nanostructured mediator was successfully applied at glucose biosensing in electrolytes containing Prussian Blue blocking cations. (C) 2008 The Electrochemical Society.