242 research outputs found

    Local Electronic Structure of a Single Magnetic Impurity in a Superconductor

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    The electronic structure near a single classical magnetic impurity in a superconductor is determined using a fully self-consistent Koster-Slater algorithm. Localized excited states are found within the energy gap which are half electron and half hole. Within a jellium model we find the new result that the spatial structure of the positive-frequency (electron-like) spectral weight (or local density of states), can differ strongly from that of the negative frequency (hole-like) spectral weight. The effect of the impurity on the continuum states above the energy gap is calculated with good spectral resolution for the first time. This is also the first three-dimensional self-consistent calculation for a strong magnetic impurity potential.Comment: 13 pages, RevTex, change in heuristic picture, no change in numerical result

    Including metabolite concentrations into flux balance analysis: thermodynamic realizability as a constraint on flux distributions in metabolic networks

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    <p>Abstract</p> <p>Background</p> <p>In recent years, constrained optimization – usually referred to as flux balance analysis (FBA) – has become a widely applied method for the computation of stationary fluxes in large-scale metabolic networks. The striking advantage of FBA as compared to kinetic modeling is that it basically requires only knowledge of the stoichiometry of the network. On the other hand, results of FBA are to a large degree hypothetical because the method relies on plausible but hardly provable optimality principles that are thought to govern metabolic flux distributions.</p> <p>Results</p> <p>To augment the reliability of FBA-based flux calculations we propose an additional side constraint which assures thermodynamic realizability, i.e. that the flux directions are consistent with the corresponding changes of Gibb's free energies. The latter depend on metabolite levels for which plausible ranges can be inferred from experimental data. Computationally, our method results in the solution of a mixed integer linear optimization problem with quadratic scoring function. An optimal flux distribution together with a metabolite profile is determined which assures thermodynamic realizability with minimal deviations of metabolite levels from their expected values. We applied our novel approach to two exemplary metabolic networks of different complexity, the metabolic core network of erythrocytes (30 reactions) and the metabolic network iJR904 of <it>Escherichia coli </it>(931 reactions). Our calculations show that increasing network complexity entails increasing sensitivity of predicted flux distributions to variations of standard Gibb's free energy changes and metabolite concentration ranges. We demonstrate the usefulness of our method for assessing critical concentrations of external metabolites preventing attainment of a metabolic steady state.</p> <p>Conclusion</p> <p>Our method incorporates the thermodynamic link between flux directions and metabolite concentrations into a practical computational algorithm. The weakness of conventional FBA to rely on intuitive assumptions about the reversibility of biochemical reactions is overcome. This enables the computation of reliable flux distributions even under extreme conditions of the network (e.g. enzyme inhibition, depletion of substrates or accumulation of end products) where metabolite concentrations may be drastically altered.</p

    Local Electronic Structure of Defects in Superconductors

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    The electronic structure near defects (such as impurities) in superconductors is explored using a new, fully self-consistent technique. This technique exploits the short-range nature of the impurity potential and the induced change in the superconducting order parameter to calculate features in the electronic structure down to the atomic scale with unprecedented spectral resolution. Magnetic and non-magnetic static impurity potentials are considered, as well as local alterations in the pairing interaction. Extensions to strong-coupling superconductors and superconductors with anisotropic order parameters are formulated.Comment: RevTex source, 20 pages including 22 figures in text with eps

    Thermodynamic analysis of regulation in metabolic networks using constraint-based modeling

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    <p>Abstract</p> <p>Background</p> <p><it>Geobacter sulfurreducens </it>is a member of the <it>Geobacter </it>species, which are capable of oxidation of organic waste coupled to the reduction of heavy metals and electrode with applications in bioremediation and bioenergy generation. While the metabolism of this organism has been studied through the development of a stoichiometry based genome-scale metabolic model, the associated regulatory network has not yet been well studied. In this manuscript, we report on the implementation of a thermodynamics based metabolic flux model for <it>Geobacter sulfurreducens</it>. We use this updated model to identify reactions that are subject to regulatory control in the metabolic network of <it>G. sulfurreducens </it>using thermodynamic variability analysis.</p> <p>Findings</p> <p>As a first step, we have validated the regulatory sites and bottleneck reactions predicted by the thermodynamic flux analysis in <it>E. coli </it>by evaluating the expression ranges of the corresponding genes. We then identified ten reactions in the metabolic network of <it>G. sulfurreducens </it>that are predicted to be candidates for regulation. We then compared the free energy ranges for these reactions with the corresponding gene expression fold changes under conditions of different environmental and genetic perturbations and show that the model predictions of regulation are consistent with data. In addition, we also identify reactions that operate close to equilibrium and show that the experimentally determined exchange coefficient (a measure of reversibility) is significant for these reactions.</p> <p>Conclusions</p> <p>Application of the thermodynamic constraints resulted in identification of potential bottleneck reactions not only from the central metabolism but also from the nucleotide and amino acid subsystems, thereby showing the highly coupled nature of the thermodynamic constraints. In addition, thermodynamic variability analysis serves as a valuable tool in estimating the ranges of Δ<sub>r</sub>G' of every reaction in the model leading to the prediction of regulatory sites in the metabolic network, thereby characterizing the regulatory network in both a model organism such as <it>E. coli </it>as well as a non model organism such as <it>G. sulfurreducens</it>.</p

    Evidence for a Massive Post-Starburst Galaxy at z ~ 6.5

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    We present results from a search for high-redshift J--band ``dropout'' galaxies in the portion of the GOODS southern field that is covered by extremely deep imaging from the Hubble Ultradeep Field (HUDF).Using observations at optical, near-infrared and mid-infrared wavelengths from the Hubble and Spitzer Space Telescopes and the ESO-VLT, we search for very massive galaxies at high redshifts and find one particularly remarkable candidate. Its spectral energy distribution is consistent with a galaxy at z ~ 6.5 and a stellar mass of 6x10e11 M(sun) (for a Salpeter IMF). We interpret a prominent photometric break between the near-infrared and Spitzer bandpasses as the 3646A Balmer discontinuity. The best-fitting models have low reddening and ages of several hundred Myr, placing the formation of the bulk of the stars at z > 9. Alternative models of dusty galaxies at z ~ 2.5 are possible but provide significantly poorer fits. The object is detected with Spitzer at 24 micron. This emission originats from an obscured active nucleus or star formation. We present optical and near-infrared spectroscopy which has, thus far, failed to detect any spectral features. This helps limit the solution in which the galaxy is a starburst or active galaxy at z ~ 2.5. If the high-redshift interpretation is correct, this object would be an example of a galaxy that formed by a process strongly resembling traditional models of monolithic collapse, in a way which a very large mass of stars formed within a remarkably short period of time, at very high redshift.Comment: Accepted for publication in Ap.J. 31 pages, 6 diagram

    Advances in ab-initio theory of Multiferroics. Materials and mechanisms: modelling and understanding

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    Within the broad class of multiferroics (compounds showing a coexistence of magnetism and ferroelectricity), we focus on the subclass of "improper electronic ferroelectrics", i.e. correlated materials where electronic degrees of freedom (such as spin, charge or orbital) drive ferroelectricity. In particular, in spin-induced ferroelectrics, there is not only a {\em coexistence} of the two intriguing magnetic and dipolar orders; rather, there is such an intimate link that one drives the other, suggesting a giant magnetoelectric coupling. Via first-principles approaches based on density functional theory, we review the microscopic mechanisms at the basis of multiferroicity in several compounds, ranging from transition metal oxides to organic multiferroics (MFs) to organic-inorganic hybrids (i.e. metal-organic frameworks, MOFs)Comment: 22 pages, 9 figure

    Optimal flux spaces of genome-scale stoichiometric models are determined by a few subnetworks

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    The metabolism of organisms can be studied with comprehensive stoichiometric models of their metabolic networks. Flux balance analysis (FBA) calculates optimal metabolic performance of stoichiometric models. However, detailed biological interpretation of FBA is limited because, in general, a huge number of flux patterns give rise to the same optimal performance. The complete description of the resulting optimal solution spaces was thus far a computationally intractable problem. Here we present CoPE-FBA: Comprehensive Polyhedra Enumeration Flux Balance Analysis, a computational method that solves this problem. CoPE-FBA indicates that the thousands to millions of optimal flux patterns result from a combinatorial explosion of flux patterns in just a few metabolic sub-networks. The entire optimal solution space can now be compactly described in terms of the topology of these sub-networks. CoPE-FBA simplifies the biological interpretation of stoichiometric models of metabolism, and provides a profound understanding of metabolic flexibility in optimal states

    A procedure for the estimation over time of metabolic fluxes in scenarios where measurements are uncertain and/or insufficient

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    <p>Abstract</p> <p>Background</p> <p>An indirect approach is usually used to estimate the metabolic fluxes of an organism: couple the available measurements with known biological constraints (e.g. stoichiometry). Typically this estimation is done under a static point of view. Therefore, the fluxes so obtained are only valid while the environmental conditions and the cell state remain stable. However, estimating the evolution over time of the metabolic fluxes is valuable to investigate the dynamic behaviour of an organism and also to monitor industrial processes. Although Metabolic Flux Analysis can be successively applied with this aim, this approach has two drawbacks: i) sometimes it cannot be used because there is a lack of measurable fluxes, and ii) the uncertainty of experimental measurements cannot be considered. The Flux Balance Analysis could be used instead, but the assumption of optimal behaviour of the organism brings other difficulties.</p> <p>Results</p> <p>We propose a procedure to estimate the evolution of the metabolic fluxes that is structured as follows: 1) measure the concentrations of extracellular species and biomass, 2) convert this data to measured fluxes and 3) estimate the non-measured fluxes using the Flux Spectrum Approach, a variant of Metabolic Flux Analysis that overcomes the difficulties mentioned above without assuming optimal behaviour. We apply the procedure to a real problem taken from the literature: estimate the metabolic fluxes during a cultivation of CHO cells in batch mode. We show that it provides a reliable and rich estimation of the non-measured fluxes, thanks to considering measurements uncertainty and reversibility constraints. We also demonstrate that this procedure can estimate the non-measured fluxes even when there is a lack of measurable species. In addition, it offers a new method to deal with inconsistency.</p> <p>Conclusion</p> <p>This work introduces a procedure to estimate time-varying metabolic fluxes that copes with the insufficiency of measured species and with its intrinsic uncertainty. The procedure can be used as an off-line analysis of previously collected data, providing an insight into the dynamic behaviour of the organism. It can be also profitable to the on-line monitoring of a running process, mitigating the traditional lack of reliable on-line sensors in industrial environments.</p

    A Novel Role for the Centrosomal Protein, Pericentrin, in Regulation of Insulin Secretory Vesicle Docking in Mouse Pancreatic β-cells

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    The centrosome is important for microtubule organization and cell cycle progression in animal cells. Recently, mutations in the centrosomal protein, pericentrin, have been linked to human microcephalic osteodysplastic primordial dwarfism (MOPD II), a rare genetic disease characterized by severe growth retardation and early onset of type 2 diabetes among other clinical manifestations. While the link between centrosomal and cell cycle defects may account for growth deficiencies, the mechanism linking pericentrin mutations with dysregulated glucose homeostasis and pre-pubertal onset of diabetes is unknown. In this report we observed abundant expression of pericentrin in quiescent pancreatic β-cells of normal animals which led us to hypothesize that pericentrin may have a critical function in β-cells distinct from its known role in regulating cell cycle progression. In addition to the typical centrosome localization, pericentrin was also enriched with secretory vesicles in the cytoplasm. Pericentrin overexpression in β-cells resulted in aggregation of insulin-containing secretory vesicles with cytoplasmic, but not centrosomal, pericentriolar material and an increase in total levels of intracellular insulin. RNAi- mediated silencing of pericentrin in secretory β-cells caused dysregulated secretory vesicle hypersecretion of insulin into the media. Together, these data suggest that pericentrin may regulate the intracellular distribution and secretion of insulin. Mice transplanted with pericentrin-depleted islets exhibited abnormal fasting hypoglycemia and inability to regulate blood glucose normally during a glucose challenge, which is consistent with our in vitro data. This previously unrecognized function for a centrosomal protein to mediate vesicle docking in secretory endocrine cells emphasizes the adaptability of these scaffolding proteins to regulate diverse cellular processes and identifies a novel target for modulating regulated protein secretion in disorders such as diabetes

    A modular tethering complex for endosomal recycling.

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    How proteins migrate through the interconnected organelles of the endolysosomal system is poorly understood. A piece of the puzzle has been added with the identification of a complex of tethering factors that functions in the recycling of proteins towards the cell surface
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