J- and Ks-band Galaxy Counts and Color Distributions in the AKARI North Ecliptic Pole Field

We present the J- and Ks-band galaxy counts and galaxy colors covering 750 square arcminutes in the deep AKARI North Ecliptic Pole (NEP) field, using the FLoridA Multi-object Imaging Near-ir Grism Observational Spectrometer (FLAMINGOS) on the Kitt Peak National Observatory (KPNO) 2.1m telescope. The limiting magnitudes with a signal-to-noise ratio of three in the deepest regions are 21.85 and 20.15 in the J- and Ks-bands respectively in the Vega magnitude system. The J- and Ks-band galaxy counts in the AKARI NEP field are broadly in good agreement with those of other results in the literature, however we find some indication of a change in the galaxy number count slope at J~19.5 and over the magnitude range 18.0 < Ks < 19.5. We interpret this feature as a change in the dominant population at these magnitudes because we also find an associated change in the B - Ks color distribution at these magnitudes where the number of blue samples in the magnitude range 18.5 < Ks < 19.5 is significantly larger than that of Ks < 17.5

Inelastic Quantum Transport

We solve a Schrodinger equation for inelastic quantum transport that retains full quantum coherence, in contrast to previous rate or Boltzmann equation approaches. The model Hamiltonian is the zero temperature 1d Holstein model for an electron coupled to optical phonons (polaron), in a strong electric field. The Hilbert space grows exponentially with electron position, forming a non-standard Bethe lattice. We calculate nonperturbatively the transport current, electron-phonon correlations, and quantum diffusion. This system is a toy model for the constantly branching ``wavefunction of the universe''.Comment: revtex, 13 pages, 4 figure

Local Electronic Structure of a Single Magnetic Impurity in a Superconductor

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

Local Electronic Structure of Defects in Superconductors

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

The First Measurements of Galaxy Clustering from IRAC Data of the Spitzer First Look Survey

We present the first results of the angular auto-correlation function of the galaxies detected by the Infrared Array Camera (IRAC) instrument in the First Look Survey (FLS) of the Spitzer Space Telescope. We detect significant signals of galaxy clustering within the survey area. The angular auto-correlation function of the galaxies detected in each of the four IRAC instrument channels is consistent with a power-law form $w(\theta)=A\theta^{1-\gamma}$ out to \theta = 0.2\arcdeg, with the slope ranging from $\gamma = 1.5$ to 1.8. We estimate the correlation amplitudes $A$ to be $2.95 \times 10^{-3}$, $2.03 \times 10^{-3}$, $4.53 \times 10^{-3}$, and $2.34 \times 10^{-3}$ at \theta=1\arcdeg for galaxies detected in the IRAC 3.6$\mu$m, 4.5$\mu$m, 5.8$\mu$m, and 8.0$\mu$m instrument channels, respectively. We compare our measurements at 3.6$\mu$m with the previous K-band measurements, and discuss the implications of these results.Comment: Accepted for publication in the ApJ Supplements Spitzer Special Issue; 12 pages including 3 figures and 1 tabl

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

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

TRAPPC4-ERK2 Interaction Activates ERK1/2, Modulates Its Nuclear Localization and Regulates Proliferation and Apoptosis of Colorectal Cancer Cells

The trafficking protein particle complex 4 (TRAPPC4) is implicated in vesicle-mediated transport, but its association with disease has rarely been reported. We explored its potential interaction with ERK2, part of the ERK1/2 complex in the Extracellular Signal-regulated Kinase/ Mitogen-activated Protein Kinase (ERK-MAPK) pathway, by a yeast two-hybrid screen and confirmed by co-immunoprecipitation (Co-IP) and glutathione S-transferase (GST) pull-down. Further investigation found that when TRAPPC4 was depleted, activated ERK1/2 specifically decreased in the nucleus, which was accompanied with cell growth suppression and apoptosis in colorectal cancer (CRC) cells. Overexpression of TRAPPC4 promoted cell viability and caused activated ERK1/2 to increase overall, but especially in the nucleus. TRAPPC4 was expressed more highly in the nucleus of CRC cells than in normal colonic epithelium or adenoma which corresponded with nuclear staining of pERK1/2. We demonstrate here that TRAPPC4 may regulate cell proliferation and apoptosis in CRC by interaction with ERK2 and subsequently phosphorylating ERK1/2 as well as modulating the subcellular location of pERK1/2 to activate the relevant signaling pathway

Incorporation of enzyme concentrations into FBA and identification of optimal metabolic pathways

<p>Abstract</p> <p>Background</p> <p>In the present article, we propose a method for determining optimal metabolic pathways in terms of the level of concentration of the enzymes catalyzing various reactions in the entire metabolic network. The method, first of all, generates data on reaction fluxes in a pathway based on steady state condition. A set of constraints is formulated incorporating weighting coefficients corresponding to concentration of enzymes catalyzing reactions in the pathway. Finally, the rate of yield of the target metabolite, starting with a given substrate, is maximized in order to identify an optimal pathway through these weighting coefficients.</p> <p>Results</p> <p>The effectiveness of the present method is demonstrated on two synthetic systems existing in the literature, two pentose phosphate, two glycolytic pathways, core carbon metabolism and a large network of carotenoid biosynthesis pathway of various organisms belonging to different phylogeny. A comparative study with the existing extreme pathway analysis also forms a part of this investigation. Biological relevance and validation of the results are provided. Finally, the impact of the method on metabolic engineering is explained with a few examples.</p> <p>Conclusions</p> <p>The method may be viewed as determining an optimal set of enzymes that is required to get an optimal metabolic pathway. Although it is a simple one, it has been able to identify a carotenoid biosynthesis pathway and the optimal pathway of core carbon metabolic network that is closer to some earlier investigations than that obtained by the extreme pathway analysis. Moreover, the present method has identified correctly optimal pathways for pentose phosphate and glycolytic pathways. It has been mentioned using some examples how the method can suitably be used in the context of metabolic engineering.</p

Hydrophobicity and Charge Shape Cellular Metabolite Concentrations

What governs the concentrations of metabolites within living cells? Beyond specific metabolic and enzymatic considerations, are there global trends that affect their values? We hypothesize that the physico-chemical properties of metabolites considerably affect their in-vivo concentrations. The recently achieved experimental capability to measure the concentrations of many metabolites simultaneously has made the testing of this hypothesis possible. Here, we analyze such recently available data sets of metabolite concentrations within E. coli, S. cerevisiae, B. subtilis and human. Overall, these data sets encompass more than twenty conditions, each containing dozens (28-108) of simultaneously measured metabolites. We test for correlations with various physico-chemical properties and find that the number of charged atoms, non-polar surface area, lipophilicity and solubility consistently correlate with concentration. In most data sets, a change in one of these properties elicits a ∼100 fold increase in metabolite concentrations. We find that the non-polar surface area and number of charged atoms account for almost half of the variation in concentrations in the most reliable and comprehensive data set. Analyzing specific groups of metabolites, such as amino-acids or phosphorylated nucleotides, reveals even a higher dependence of concentration on hydrophobicity. We suggest that these findings can be explained by evolutionary constraints imposed on metabolite concentrations and discuss possible selective pressures that can account for them. These include the reduction of solute leakage through the lipid membrane, avoidance of deleterious aggregates and reduction of non-specific hydrophobic binding. By highlighting the global constraints imposed on metabolic pathways, future research could shed light onto aspects of biochemical evolution and the chemical constraints that bound metabolic engineering efforts

Nutritional Systems Biology Modeling: From Molecular Mechanisms to Physiology

The use of computational modeling and simulation has increased in many biological fields, but despite their potential these techniques are only marginally applied in nutritional sciences. Nevertheless, recent applications of modeling have been instrumental in answering important nutritional questions from the cellular up to the physiological levels. Capturing the complexity of today's important nutritional research questions poses a challenge for modeling to become truly integrative in the consideration and interpretation of experimental data at widely differing scales of space and time. In this review, we discuss a selection of available modeling approaches and applications relevant for nutrition. We then put these models into perspective by categorizing them according to their space and time domain. Through this categorization process, we identified a dearth of models that consider processes occurring between the microscopic and macroscopic scale. We propose a “middle-out” strategy to develop the required full-scale, multilevel computational models. Exhaustive and accurate phenotyping, the use of the virtual patient concept, and the development of biomarkers from “-omics” signatures are identified as key elements of a successful systems biology modeling approach in nutrition research—one that integrates physiological mechanisms and data at multiple space and time scales