A new bright z = 6.82 quasar discovered with VISTA: VHS J0411-0907

We present the discovery of a new $z \sim 6.8$ quasar discovered with the near-IR VISTA Hemisphere Survey (VHS) which has been spectroscopically confirmed by the ESO New Technology Telescope (NTT) and the Magellan telescope. This quasar has been selected by spectral energy distribution (SED) classification using near infrared data from VISTA, optical data from Pan-STARRS, and mid-IR data from WISE. The SED classification algorithm is used to statistically rank two classes; foreground Galactic low-mass stars and high redshift quasars, prior to spectroscopic observation. Forced photometry on Pan-STARRS pixels for VHS J0411-0907 allows to improve the SED classification reduced-$\chi^2$ and photometric redshift. VHS J0411-0907 ($z=6.82$, $y_{AB} = 20.1$ mag, $J_{AB} = 20.0$ mag) has the brightest J-band continuum magnitude of the nine known quasars at $z > 6.7$ and is currently the highest redshift quasar detected in the Pan-STARRS survey. This quasar has one of the lowest black hole mass ($M_{\rm{BH}}= (6.13 \pm 0.51)\times 10^8\:\mathrm{M_{\odot}}$) and the highest Eddington ratio ($2.37\pm0.22$) of the known quasars at $z>6.5$. The high Eddington ratio indicates that some very high-$z$ quasars are undergoing super Eddington accretion. We also present coefficients of the best polynomials fits for colours vs spectral type on the Pan-STARRS, VISTA and WISE system for MLT dwarfs and present a forecast for the expected numbers of quasars at $z>6.5$

Stability of closed gaps for the alternating Kronig-Penney Hamiltonian

We consider the Kronig-Penney model for a quantum crystal with equispaced periodic delta-interactions of alternating strength. For this model all spectral gaps at the centre of the Brillouin zone are known to vanish, although so far this noticeable property has only been proved through a very delicate analysis of the discriminant of the corresponding ODE and the associated monodromy matrix. We provide a new, alternative proof by showing that this model can be approximated, in the norm resolvent sense, by a model of regular periodic interactions with finite range for which all gaps at the centre of the Brillouin zone are still vanishing. In particular this shows that the vanishing gap property is stable in the sense that it is present also for the "physical" approximants and is not only a feature of the idealised model of zero-range interactions. \ua9 2015, Springer Basel

Response of the Hepatic Transcriptome to Aflatoxin B1 in Domestic Turkey (Meleagris gallopavo)

Dietary exposure to aflatoxin B1 (AFB1) is detrimental to avian health and leads to major economic losses for the poultry industry. AFB1 is especially hepatotoxic in domestic turkeys (Meleagris gallopavo), since these birds are unable to detoxify AFB1 by glutathione-conjugation. The impacts of AFB1 on the turkey hepatic transcriptome and the potential protection from pretreatment with a Lactobacillus-based probiotic mixture were investigated through RNA-sequencing. Animals were divided into four treatment groups and RNA was subsequently recovered from liver samples. Four pooled RNA-seq libraries were sequenced to produce over 322 M reads totaling 13.8 Gb of sequence. Approximately 170,000 predicted transcripts were de novo assembled, of which 803 had significant differential expression in at least one pair-wise comparison between treatment groups. Functional analysis linked many of the transcripts significantly affected by AFB1 exposure to cancer, apoptosis, the cell cycle or lipid regulation. Most notable were transcripts from the genes encoding E3 ubiquitin-protein ligase Mdm2, osteopontin, S-adenosylmethionine synthase isoform type-2, and lipoprotein lipase. Expression was modulated by the probiotics, but treatment did not completely mitigate the effects of AFB1. Genes identified through transcriptome analysis provide candidates for further study of AFB1 toxicity and targets for efforts to improve the health of domestic turkeys exposed to AFB1.published_or_final_versio

Contribution of murine IgG Fc regions to antibody binding to the capsule of Burkholderia pseudomallei.

Immunoglobulin G3 (IgG3) is the predominant IgG subclass elicited in response to polysaccharide antigens in mice. This specific subclass has been shown to crosslink its fragment crystallizable (Fc) regions following binding to multivalent polysaccharides. Crosslinking leads to increased affinity through avidity, which theoretically should lead to more effective protection against bacteria and yeast displaying capsular polysaccharides on their surface. To investigate this further we have analyzed the binding characteristics of 2 IgG monoclonal antibody (mAb) subclass families that bind to the capsular polysaccharide (CPS) of Burkholderia pseudomallei. The first subclass family originated from an IgG3 hybridoma cell line (3C5); the second family was generated from an IgG1 cell line (2A5). When the Fc region of the 3C5 IgG3 is removed by proteolytic cleavage, the resulting F(ab')2 fragments exhibit decreased affinity compared to the full-length mAb. Similarly, when the parent IgG3 mAb is subclass-switched to IgG1, IgG2b, and IgG2a, all of these subclasses exhibit decreased affinity. This decrease in affinity is not seen when the 2A5 IgG1 mAb is switched to an IgG2b or IgG2a, strongly suggesting the drop in affinity is related to the IgG3 Fc region

Search algorithms as a framework for the optimization of drug combinations

Combination therapies are often needed for effective clinical outcomes in the management of complex diseases, but presently they are generally based on empirical clinical experience. Here we suggest a novel application of search algorithms, originally developed for digital communication, modified to optimize combinations of therapeutic interventions. In biological experiments measuring the restoration of the decline with age in heart function and exercise capacity in Drosophila melanogaster, we found that search algorithms correctly identified optimal combinations of four drugs with only one third of the tests performed in a fully factorial search. In experiments identifying combinations of three doses of up to six drugs for selective killing of human cancer cells, search algorithms resulted in a highly significant enrichment of selective combinations compared with random searches. In simulations using a network model of cell death, we found that the search algorithms identified the optimal combinations of 6-9 interventions in 80-90% of tests, compared with 15-30% for an equivalent random search. These findings suggest that modified search algorithms from information theory have the potential to enhance the discovery of novel therapeutic drug combinations. This report also helps to frame a biomedical problem that will benefit from an interdisciplinary effort and suggests a general strategy for its solution.Comment: 36 pages, 10 figures, revised versio

A model for selection of eyespots on butterfly wings

The development of eyespots on the wing surface of butterflies of the family Nympalidae is one of the most studied examples of biological pattern formation.However, little is known about the mechanism that determines the number and precise locations of eyespots on the wing. Eyespots develop around signaling centers, called foci, that are located equidistant from wing veins along the midline of a wing cell (an area bounded by veins). A fundamental question that remains unsolved is, why a certain wing cell develops an eyespot, while other wing cells do not. We illustrate that the key to understanding focus point selection may be in the venation system of the wing disc. Our main hypothesis is that changes in morphogen concentration along the proximal boundary veins of wing cells govern focus point selection. Based on previous studies, we focus on a spatially two-dimensional reaction-diffusion system model posed in the interior of each wing cell that describes the formation of focus points. Using finite element based numerical simulations, we demonstrate that variation in the proximal boundary condition is sufficient to robustly select whether an eyespot focus point forms in otherwise identical wing cells. We also illustrate that this behavior is robust to small perturbations in the parameters and geometry and moderate levels of noise. Hence, we suggest that an anterior-posterior pattern of morphogen concentration along the proximal vein may be the main determinant of the distribution of focus points on the wing surface. In order to complete our model, we propose a two stage reaction-diffusion system model, in which an one-dimensional surface reaction-diffusion system, posed on the proximal vein, generates the morphogen concentrations that act as non-homogeneous Dirichlet (i.e., fixed) boundary conditions for the two-dimensional reaction-diffusion model posed in the wing cells. The two-stage model appears capable of generating focus point distributions observed in nature. We therefore conclude that changes in the proximal boundary conditions are sufficient to explain the empirically observed distribution of eyespot focus points on the entire wing surface. The model predicts, subject to experimental verification, that the source strength of the activator at the proximal boundary should be lower in wing cells in which focus points form than in those that lack focus points. The model suggests that the number and locations of eyespot foci on the wing disc could be largely controlled by two kinds of gradients along two different directions, that is, the first one is the gradient in spatially varying parameters such as the reaction rate along the anterior-posterior direction on the proximal boundary of the wing cells, and the second one is the gradient in source values of the activator along the veins in the proximal-distal direction of the wing cell

Microbial ligand costimulation drives neutrophilic steroid-refractory asthma

Funding: The authors thank the Wellcome Trust (102705) and the Universities of Aberdeen and Cape Town for funding. This research was also supported, in part, by National Institutes of Health GM53522 and GM083016 to DLW. KF and BNL are funded by the Fonds Wetenschappelijk Onderzoek, BNL is the recipient of an European Research Commission consolidator grant and participates in the European Union FP7 programs EUBIOPRED and MedALL. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Peer reviewedPublisher PD

Elevated CO₂ does not increase eucalypt forest productivity on a low-phosphorus soil

Rising atmospheric CO2 stimulates photosynthesis and productivity of forests, offsetting CO2 emissions. Elevated CO2 experiments in temperate planted forests yielded ~23% increases in productivity over the initial years. Whether similar CO2 stimulation occurs in mature evergreen broadleaved forests on low-phosphorus (P) soils is unknown, largely due to lack of experimental evidence. This knowledge gap creates major uncertainties in future climate projections as a large part of the tropics is P-limited. Here,we increased atmospheric CO2 concentration in a mature broadleaved evergreen eucalypt forest for three years, in the first large-scale experiment on a P-limited site. We show that tree growth and other aboveground productivity components did not significantly increase in response to elevated CO2 in three years, despite a sustained 19% increase in leaf photosynthesis. Moreover, tree growth in ambient CO2 was strongly P-limited and increased by ~35% with added phosphorus. The findings suggest that P availability may potentially constrain CO2-enhanced productivity in P-limited forests; hence, future atmospheric CO2 trajectories may be higher than predicted by some models. As a result, coupled climate-carbon models should incorporate both nitrogen and phosphorus limitations to vegetation productivity in estimating future carbon sinks