929 resultados para GENE NETWORK INTERACTIONS


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This work clarifies the relation between network circuit (topology) and behaviour (information transmission and synchronization) in active networks, e.g. neural networks. As an application, we show how one can find network topologies that are able to transmit a large amount of information, possess a large number of communication channels, and are robust under large variations of the network coupling configuration. This theoretical approach is general and does not depend on the particular dynamic of the elements forming the network, since the network topology can be determined by finding a Laplacian matrix (the matrix that describes the connections and the coupling strengths among the elements) whose eigenvalues satisfy some special conditions. To illustrate our ideas and theoretical approaches, we use neural networks of electrically connected chaotic Hindmarsh-Rose neurons.

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A fundamental interaction for electrons is their hyperfine interaction (HFI) with nuclear spins. HFI is well characterized in free atoms and molecules, and is crucial for purposes from chemical identification of atoms to trapped ion quantum computing. However, electron wave functions near atomic sites, therefore HFI, are often not accurately known in solids. Here we perform an all-electron calculation for conduction electrons in silicon and obtain reliable information on HFI. We verify the outstanding quantum spin coherence in Si, which is critical for fault-tolerant solid state quantum computing.

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The energy barrier distribution E(b) of five samples with different concentrations x of Ni nanoparticles using scaling plots from ac magnetic susceptibility data has been determined. The scaling of the imaginary part of the susceptibility chi""(v, T) versus T ln (iota t/tau(0)) remains valid for all samples, which display Ni nanoparticles with similar shape and size. The mean value < E(b)> increases appreciably with increasing x, or more appropriately with increasing dipolar interactions between Ni nanoparticles. We argue that such an increase in < E(b)> constitutes a powerful tool for quality control in magnetic recording media technology where the dipolar interaction plays an important role. (c) 2011 American Institute of Physics. [doi: 10.1063/1.3533911]

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The role of dipolar interactions among Ni nanoparticles (NPs) embedded in an amorphous SiO(2)/C matrix with different concentrations has been studied performing ac magnetic susceptibility chi(ac) measurements. For very diluted samples, with Ni concentrations < 4 wt % Ni or very weak dipolar interactions, the data are well described by the Neacuteel-Arrhenius law. Increasing Ni concentration to values up to 12.8 wt % Ni results in changes in the Neacuteel-Arrhenius behavior, the dipolar interactions become important, and need to be considered to describe the magnetic response of the NPs system. We have found no evidence of a spin-glasslike behavior in our Ni NP systems even when dipolar interactions are clearly present.

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The MINOS experiment at Fermilab has recently reported a tension between the oscillation results for neutrinos and antineutrinos. We show that this tension, if it persists, can be understood in the framework of nonstandard neutrino interactions (NSI). While neutral current NSI (nonstandard matter effects) are disfavored by atmospheric neutrinos, a new charged current coupling between tau neutrinos and nucleons can fit the MINOS data without violating other constraints. In particular, we show that loop-level contributions to flavor-violating tau decays are sufficiently suppressed. However, conflicts with existing bounds could arise once the effective theory considered here is embedded into a complete renormalizable model. We predict the future sensitivity of the T2K and NOvA experiments to the NSI parameter region favored by the MINOS fit, and show that both experiments are excellent tools to test the NSI interpretation of the MINOS data.

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We numerically study the dynamics of a discrete spring-block model introduced by Olami, Feder, and Christensen (OFC) to mimic earthquakes and investigate to what extent this simple model is able to reproduce the observed spatiotemporal clustering of seismicity. Following a recently proposed method to characterize such clustering by networks of recurrent events [J. Davidsen, P. Grassberger, and M. Paczuski, Geophys. Res. Lett. 33, L11304 (2006)], we find that for synthetic catalogs generated by the OFC model these networks have many nontrivial statistical properties. This includes characteristic degree distributions, very similar to what has been observed for real seismicity. There are, however, also significant differences between the OFC model and earthquake catalogs, indicating that this simple model is insufficient to account for certain aspects of the spatiotemporal clustering of seismicity.

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We study the spin-1/2 Ising model on a Bethe lattice in the mean-field limit, with the interaction constants following one of two deterministic aperiodic sequences, the Fibonacci or period-doubling one. New algorithms of sequence generation were implemented, which were fundamental in obtaining long sequences and, therefore, precise results. We calculate the exact critical temperature for both sequences, as well as the critical exponents beta, gamma, and delta. For the Fibonacci sequence, the exponents are classical, while for the period-doubling one they depend on the ratio between the two exchange constants. The usual relations between critical exponents are satisfied, within error bars, for the period-doubling sequence. Therefore, we show that mean-field-like procedures may lead to nonclassical critical exponents.

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Positional information in developing embryos is specified by spatial gradients of transcriptional regulators. One of the classic systems for studying this is the activation of the hunchback (hb) gene in early fruit fly (Drosophila) segmentation by the maternally-derived gradient of the Bicoid (Bcd) protein. Gene regulation is subject to intrinsic noise which can produce variable expression. This variability must be constrained in the highly reproducible and coordinated events of development. We identify means by which noise is controlled during gene expression by characterizing the dependence of hb mRNA and protein output noise on hb promoter structure and transcriptional dynamics. We use a stochastic model of the hb promoter in which the number and strength of Bcd and Hb (self-regulatory) binding sites can be varied. Model parameters are fit to data from WT embryos, the self-regulation mutant hb(14F), and lacZ reporter constructs using different portions of the hb promoter. We have corroborated model noise predictions experimentally. The results indicate that WT (self-regulatory) Hb output noise is predominantly dependent on the transcription and translation dynamics of its own expression, rather than on Bcd fluctuations. The constructs and mutant, which lack self-regulation, indicate that the multiple Bcd binding sites in the hb promoter (and their strengths) also play a role in buffering noise. The model is robust to the variation in Bcd binding site number across a number of fly species. This study identifies particular ways in which promoter structure and regulatory dynamics reduce hb output noise. Insofar as many of these are common features of genes (e. g. multiple regulatory sites, cooperativity, self-feedback), the current results contribute to the general understanding of the reproducibility and determinacy of spatial patterning in early development.

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Complex networks have been characterised by their specific connectivity patterns (network motifs), but their building blocks can also be identified and described by node-motifs-a combination of local network features. One technique to identify single node-motifs has been presented by Costa et al. (L. D. F. Costa, F. A. Rodrigues, C. C. Hilgetag, and M. Kaiser, Europhys. Lett., 87, 1, 2009). Here, we first suggest improvements to the method including how its parameters can be determined automatically. Such automatic routines make high-throughput studies of many networks feasible. Second, the new routines are validated in different network-series. Third, we provide an example of how the method can be used to analyse network time-series. In conclusion, we provide a robust method for systematically discovering and classifying characteristic nodes of a network. In contrast to classical motif analysis, our approach can identify individual components (here: nodes) that are specific to a network. Such special nodes, as hubs before, might be found to play critical roles in real-world networks.

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A technique is proposed for creating nonground-state Bose-Einstein condensates in a trapping potential by means of the temporal modulation of atomic interactions. Applying a time-dependent spatially homogeneous magnetic field modifies the atomic scattering length. A modulation of the scattering length excites the condensate, which, under special conditions, can be transferred to an excited nonlinear coherent mode. It is shown that a phase-transition-like behavior occurs in the time-averaged population imbalance between the ground and excited states. The application of the technique is analyzed and it is shown that the considered effect can be realized for experimentally available condensates.

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We report electron-paramagnetic resonance (EPR) studies at similar to 9.5 GHz (X band) and similar to 34 GHz (Q band) of powder and single-crystal samples of the compound Cu(2)[TzTs](4) [N-thiazol-2-yl-toluenesulfonamidatecopper(II)], C(40)H(36)Cu(2)N(8)O(8)S(8), having copper(II) ions in dinuclear units. Our data allow determining an antiferromagnetic interaction J(0)=(-113 +/- 1) cm(-1) (H(ex)=-J(0)S(1)center dot S(2)) between Cu(II) ions in the dinuclear unit and the anisotropic contributions to the spin-spin coupling matrix D (H(ani)=S(1)center dot D center dot S(2)), a traceless symmetric matrix with principal values D/4=(0.198 +/- 0.003) cm(-1) and E/4=(0.001 +/- 0.003) cm(-1) arising from magnetic dipole-dipole and anisotropic exchange couplings within the units. In addition, the single-crystal EPR measurements allow detecting and estimating very weak exchange couplings between neighbor dinuclear units, with an estimated magnitude parallel to J(')parallel to=(0.060 +/- 0.015) cm(-1). The interactions between a dinuclear unit and the ""environment"" of similar units in the structure of the compound produce a spin dynamics that averages out the intradinuclear dipolar interactions. This coupling with the environment leads to decoherence, a quantum phase transition that collapses the dipolar interaction when the isotropic exchange coupling with neighbor dinuclear units equals the magnitude of the intradinuclear dipolar coupling. Our EPR experiments provide a new procedure to follow the classical exchange-narrowing process as a shift and collapse of the line structure (not only as a change of the resonance width), which is described with general (but otherwise simple) theories of magnetic resonance. Using complementary procedures, our EPR measurements in powder and single-crystal samples allow measuring simultaneously three types of interactions differing by more than three orders of magnitude (between 113 cm(-1) and 0.060 cm(-1)).

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We investigate the performance of a variant of Axelrod's model for dissemination of culture-the Adaptive Culture Heuristic (ACH)-on solving an NP-Complete optimization problem, namely, the classification of binary input patterns of size F by a Boolean Binary Perceptron. In this heuristic, N agents, characterized by binary strings of length F which represent possible solutions to the optimization problem, are fixed at the sites of a square lattice and interact with their nearest neighbors only. The interactions are such that the agents' strings (or cultures) become more similar to the low-cost strings of their neighbors resulting in the dissemination of these strings across the lattice. Eventually the dynamics freezes into a homogeneous absorbing configuration in which all agents exhibit identical solutions to the optimization problem. We find through extensive simulations that the probability of finding the optimal solution is a function of the reduced variable F/N(1/4) so that the number of agents must increase with the fourth power of the problem size, N proportional to F(4), to guarantee a fixed probability of success. In this case, we find that the relaxation time to reach an absorbing configuration scales with F(6) which can be interpreted as the overall computational cost of the ACH to find an optimal set of weights for a Boolean binary perceptron, given a fixed probability of success.

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We introduce an analytical approximation scheme to diagonalize parabolically confined two-dimensional (2D) electron systems with both the Rashba and Dresselhaus spin-orbit interactions. The starting point of our perturbative expansion is a zeroth-order Hamiltonian for an electron confined in a quantum wire with an effective spin-orbit induced magnetic field along the wire, obtained by properly rotating the usual spin-orbit Hamiltonian. We find that the spin-orbit-related transverse coupling terms can be recast into two parts W and V, which couple crossing and noncrossing adjacent transverse modes, respectively. Interestingly, the zeroth-order Hamiltonian together with W can be solved exactly, as it maps onto the Jaynes-Cummings model of quantum optics. We treat the V coupling by performing a Schrieffer-Wolff transformation. This allows us to obtain an effective Hamiltonian to third order in the coupling strength k(R)l of V, which can be straightforwardly diagonalized via an additional unitary transformation. We also apply our approach to other types of effective parabolic confinement, e. g., 2D electrons in a perpendicular magnetic field. To demonstrate the usefulness of our approximate eigensolutions, we obtain analytical expressions for the nth Landau-level g(n) factors in the presence of both Rashba and Dresselhaus couplings. For small values of the bulk g factors, we find that spin-orbit effects cancel out entirely for particular values of the spin-orbit couplings. By solving simple transcendental equations we also obtain the band minima of a Rashba-coupled quantum wire as a function of an external magnetic field. These can be used to describe Shubnikov-de Haas oscillations. This procedure makes it easier to extract the strength of the spin-orbit interaction in these systems via proper fitting of the data.

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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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Diffuse infiltrating gliomas are the most common tumors of the central nervous system. Gliomas are classified by the WHO according to their histopathological and clinical characteristics into four classes: grade I (pilocytic astrocytoma), grade II (diffuse astrocytoma), grade III (anaplastic astrocytoma), and grade IV (glioblastoma multiforme). Several genes have already been correlated with astrocytomas, but many others are yet to be uncovered. By analyzing the public SAGE data from 21 patients, comprising low malignant grade astrocytomas and glioblastomas, we found COL6A1 to be differentially expressed, confirming this finding by real time RT-PCR in 66 surgical samples. To the best of our knowledge, COL6A1 has never been described in gliomas. The expression of this gene has significantly different means when normal glia is compared with low-grade astrocytomas (grades I and II) and high-grade astrocytomas (grades III and IV), with a tendency to be greater in higher grade samples, thus rendering it a powerful tumor marker.