Influenza Viruses Display High-Affinity Binding to Human Polyglycosylceramides Represented on a Solid-Phase Assay Surface

AbstractPolyglycosylceramides (PGCs), complex glycolipids containing up to 50 or more sugar residues, are recognized as the minor components of the cell-surface membranes, but a knowledge on their tissue distribution, structure, and function is limited. In this study, the binding of influenza viruses to preparations of PGCs was investigated using a TLC overlay assay and a microwell adsorption assay. The ability of PGCs to bind influenza virus was dependent on the source from which they were derived. Preparations of PGCs from human erythrocytes were found to support binding of A and B influenza virus strains at a much lower concentration than sialyl-6-paragloboside and to be somewhat better receptors for these viruses compared to the sialylglycoprotein fetuin. A high virus-binding activity of PGCs suggests that these species could potentially serve as biologically important cell-surface receptors for influenza viruses

Complementarity and the uncertainty relations

We formulate a general complementarity relation starting from any Hermitian operator with discrete non-degenerate eigenvalues. We then elucidate the relationship between quantum complementarity and the Heisenberg-Robertson's uncertainty relation. We show that they are intimately connected. Finally we exemplify the general theory with some specific suggested experiments.Comment: 9 pages, 4 figures, REVTeX, uses epsf.sty and multicol.st

A robust sample of galaxies at redshifts 6.0<z<8.7: stellar populations, star-formation rates and stellar masses

We present the results of a photometric redshift analysis designed to identify z>6 galaxies from the near-IR HST imaging in three deep fields (HUDF, HUDF09-2 & ERS). By adopting a rigorous set of criteria for rejecting low-z interlopers, and by employing a deconfusion technique to allow the available IRAC imaging to be included in the candidate selection process, we have derived a robust sample of 70 Lyman-break galaxies (LBGs) spanning the redshift range 6.0<z<8.7. Based on our final sample we investigate the distribution of UV spectral slopes (beta), finding a variance-weighted mean value of =-2.05 +/- 0.09 which, contrary to some previous results, is not significantly bluer than displayed by lower-redshift starburst galaxies. We confirm the correlation between UV luminosity and stellar mass reported elsewhere, but based on fitting galaxy templates featuring a range of star-formation histories, metallicities and reddening we find that, at z>=6, the range in mass-to-light ratio (M*/L_UV) at a given UV luminosity could span a factor of ~50. Focusing on a sub-sample of twenty-one candidates with IRAC detections at 3.6-microns we find that L* LBGs at z~6.5 have a median stellar mass of M* = (2.1 +/- 1.1) x 10^9 Msun and a median specific star-formation rate of 1.9 +/- 0.8 Gyr^-1. Using the same sub-sample we have investigated the influence of nebular continuum and line emission, finding that for the majority of candidates (16 out of 21) the best-fitting stellar-mass estimates are reduced by less than a factor of 2.5. Finally, a detailed comparison of our final sample with the results of previous studies suggests that, at faint magnitudes, several high-redshift galaxy samples in the literature are significantly contaminated by low-redshift interlopers (abridged).Comment: 35 pages, 22 figures, replaced to match version accepted by MNRAS, minor changes onl

Differential expression analysis for sequence count data

*Motivation:* High-throughput nucleotide sequencing provides quantitative readouts in assays for RNA expression (RNA-Seq), protein-DNA binding (ChIP-Seq) or cell counting (barcode sequencing). Statistical inference of differential signal in such data requires estimation of their variability throughout the dynamic range. When the number of replicates is small, error modelling is needed to achieve statistical power.&#xd;&#xa;&#xd;&#xa;*Results:* We propose an error model that uses the negative binomial distribution, with variance and mean linked by local regression, to model the null distribution of the count data. The method controls type-I error and provides good detection power. &#xd;&#xa;&#xd;&#xa;*Availability:* A free open-source R software package, _DESeq_, is available from the Bioconductor project and from &#x22;http://www-huber.embl.de/users/anders/DESeq&#x22;:http://www-huber.embl.de/users/anders/DESeq

Effects of metal enrichment and metal cooling in galaxy growth and cosmic star formation history

We present the results of a numerical study on the effects of metal enrichment and metal cooling on galaxy formation and cosmic star formation (SF) history using cosmological hydrodynamic simulations. We find following differences in the simulation with metal cooling when compared to the run without it: (1) the cosmic star formation rate (SFR) is enhanced by about 50 & 20% at z=1 & 3, respectively; (2) the gas mass fraction in galaxies is lower; (3) the total baryonic mass function (gas + star) at z=3 does not differ significantly, but shows an increase in the number of relatively massive galaxies at z=1; (4) the baryonic mass fraction of intergalactic medium (IGM) is reduced at z<3 due to more efficient cooling and gas accretion onto galaxies. Our results suggest that the metal cooling enhances the galaxy growth by two different mechanisms: (1) increase of SF efficiency in the local interstellar medium (ISM), and (2) increase of IGM accretion onto galaxies. The former process is effective throughout most of the cosmic history, while the latter is effective only at z<3 when the IGM is sufficiently enriched by metals owing to feedback.Comment: 16 pages, 11 figures, 1 table, accepted for publication in MNRAS. A full resolution version is available at http://www.physics.unlv.edu/~jhchoi/astro-ph/Metalcooling.pd

The Boundary Conditions of the Heliosphere: Photoionization Models Constrained by Interstellar and In Situ Data

The boundary conditions of the heliosphere are set by the ionization, density and composition of inflowing interstellar matter. Constraining the properties of the Local Interstellar Cloud (LIC) at the heliosphere requires radiative transfer ionization models. We model the background interstellar radiation field using observed stellar FUV and EUV emission and the diffuse soft X-ray background. We also model the emission from the boundary between the LIC and the hot Local Bubble (LB) plasma, assuming that the cloud is evaporating because of thermal conduction. We create a grid of models covering a plausible range of LIC and LB properties, and use the modeled radiation field as input to radiative transfer/thermal equilibrium calculations using the Cloudy code. Data from in situ observations of He^O, pickup ions and anomalous cosmic rays in the heliosphere, and absorption line measurements towards epsilon CMa were used to constrain the input parameters. A restricted range of assumed LIC HI column densities and LB plasma temperatures produce models that match all the observational constraints. The relative weakness of the constraints on N(HI) and T_h contrast with the narrow limits predicted for the H^O and electron density in the LIC at the Sun, n(H^0) = 0.19 - 0.20 cm^-3, and n(e) = 0.07 +/- 0.01 cm^-3. Derived abundances are mostly typical for low density gas, with sub-solar Mg, Si and Fe, possibly subsolar O and N, and S about solar; however C is supersolar. The interstellar gas at the Sun is warm, low density, and partially ionized, with n(H) = 0.23 - 0.27 cm^-3, T = 6300 K, X(H^+) ~ 0.2, and X(He^+) ~ 0.4. These results appear to be robust since acceptable models are found for substantially different input radiation fields. Our results favor low values for the reference solar abundances for the LIC composition.Comment: 14 pages, 4 figures, submitted to Astronomy & Astrophysics together with papers from the International Space Sciences Institute workshop on Interstellar Hydrogen in the Heliospher

Early star-forming galaxies and the reionization of the Universe

Star forming galaxies represent a valuable tracer of cosmic history. Recent observational progress with Hubble Space Telescope has led to the discovery and study of the earliest-known galaxies corresponding to a period when the Universe was only ~800 million years old. Intense ultraviolet radiation from these early galaxies probably induced a major event in cosmic history: the reionization of intergalactic hydrogen. New techniques are being developed to understand the properties of these most distant galaxies and determine their influence on the evolution of the universe.Comment: Review article appearing in Nature. This posting reflects a submitted version of the review formatted by the authors, in accordance with Nature publication policies. For the official, published version of the review, please see http://www.nature.com/nature/archive/index.htm

Preferred analysis methods for single genomic regions in RNA sequencing revealed by processing the shape of coverage

The informational content of RNA sequencing is currently far from being completely explored. Most of the analyses focus on processing tables of counts or finding isoform deconvolution via exon junctions. This article presents a comparison of several techniques that can be used to estimate differential expression of exons or small genomic regions of expression, based on their coverage function shapes. The problem is defined as finding the differentially expressed exons between two samples using local expression profile normalization and statistical measures to spot the differences between two profile shapes. Initial experiments have been done using synthetic data, and real data modified with synthetically created differential patterns. Then, 160 pipelines (5 types of generator × 4 normalizations × 8 difference measures) are compared. As a result, the best analysis pipelines are selected based on linearity of the differential expression estimation and the area under the ROC curve. These platform-independent techniques have been implemented in the Bioconductor package rnaSeqMap. They point out the exons with differential expression or internal splicing, even if the counts of reads may not show this. The areas of application include significant difference searches, splicing identification algorithms and finding suitable regions for QPCR primers