Honeybee microbiome is stabilized in the presence of propolis

Honeybees have developed many unique mechanisms to help ensure the proper maintenance of homeostasis within the hive. One method includes the collection of chemically complex plant resins combined with wax to form propolis, which is deposited throughout the hive. Propolis is believed to play a significant role in reducing disease load in the colony due to its antimicrobial and antiseptic properties. However, little is known about how propolis may interact with bee-associated microbial symbionts, and if propolis alters microbial community structure. In this study, we found that propolis appears to maintain a stable microbial community composition and reduce the overall taxonomic diversity of the honeybee microbiome. Several key members of the gut microbiota were significantly altered in the absence of propolis, suggesting that it may play an important role in maintaining favourable abundance and composition of gut symbionts. Overall, these findings suggest that propolis may help to maintain honeybee colony microbial health by limiting changes to the overall microbial community

Genome of Drosophila suzukii, the spotted wing drosophila.

Drosophila suzukii Matsumura (spotted wing drosophila) has recently become a serious pest of a wide variety of fruit crops in the United States as well as in Europe, leading to substantial yearly crop losses. To enable basic and applied research of this important pest, we sequenced the D. suzukii genome to obtain a high-quality reference sequence. Here, we discuss the basic properties of the genome and transcriptome and describe patterns of genome evolution in D. suzukii and its close relatives. Our analyses and genome annotations are presented in a web portal, SpottedWingFlyBase, to facilitate public access

Projected SO(5) Hamiltonian for Cuprates and Its Applications

The projected SO(5) (pSO(5)) Hamiltonian incorporates the quantum spin and superconducting fluctuations of underdoped cuprates in terms of four bosons moving on a coarse grained lattice. A simple mean field approximation can explain some key feautures of the experimental phase diagram: (i) The Mott transition between antiferromagnet and superconductor, (ii) The increase of T_c and superfluid stiffness with hole concentration x and (iii) The increase of antiferromagnetic resonance energy as sqrt{x-x_c} in the superconducting phase. We apply this theory to explain the ``two gaps'' problem found in underdoped cuprate Superconductor-Normal- Superconductor junctions. In particular we explain the sharp subgap Andreev peaks of the differential resistance, as signatures of the antiferromagnetic resonance (the magnon mass gap). A critical test of this theory is proposed. The tunneling charge, as measured by shot noise, should change by increments of Delta Q= 2e at the Andreev peaks, rather than by Delta Q=e as in conventional superconductors.Comment: 3 EPS figure

Comparison of nitric oxide measurements in the mesosphere and lower thermosphere from ACE-FTS, MIPAS, SCIAMACHY, and SMR

We compare the nitric oxide measurements in the mesosphere and lower thermosphere (60 to 150 km) from four instruments: ACE-FTS, MIPAS, SCIAMACHY, and SMR. We use the daily zonal mean data in that altitude range for the years 2004-2010 (ACE-FTS), 2005-2012 (MIPAS), 2008-2012 (SCIAMACHY), and 2003-2012 (SMR). We first compare the data qualitatively with respect to the morphology, focussing on the major features, and then compare the time series directly and quantitatively. In three geographical regions, we compare the vertical density profiles on coincident measurement days. Since none of the instruments delivers continuous daily measurements in this altitude region, we carried out a multi-linear regression analysis. This regression analysis considers annual and semi-annual variability in form of harmonic terms and inter-annual variability by responding linearly to the solar Lyman-alpha; radiation index and the geomagnetic Kp index. This analysis helps to find similarities and differences in the individual data sets with respect to the inter-annual variations caused by geomagnetic and solar variability. We find that the data sets are consistent and that they only disagree on minor aspects. SMR and ACE-FTS deliver the longest time series in the mesosphere and they both agree remarkably well. The shorter time series from MIPAS and SCIAMACHY also agree with them where they overlap. The data agree within ten to twenty percent when the number densities are large, but they can differ by 50 to 100% in some cases

In silico assessment of potential druggable pockets on the surface of α1-Antitrypsin conformers

The search for druggable pockets on the surface of a protein is often performed on a single conformer, treated as a rigid body. Transient druggable pockets may be missed in this approach. Here, we describe a methodology for systematic in silico analysis of surface clefts across multiple conformers of the metastable protein α1-antitrypsin (A1AT). Pathological mutations disturb the conformational landscape of A1AT, triggering polymerisation that leads to emphysema and hepatic cirrhosis. Computational screens for small molecule inhibitors of polymerisation have generally focused on one major druggable site visible in all crystal structures of native A1AT. In an alternative approach, we scan all surface clefts observed in crystal structures of A1AT and in 100 computationally produced conformers, mimicking the native solution ensemble. We assess the persistence, variability and druggability of these pockets. Finally, we employ molecular docking using publicly available libraries of small molecules to explore scaffold preferences for each site. Our approach identifies a number of novel target sites for drug design. In particular one transient site shows favourable characteristics for druggability due to high enclosure and hydrophobicity. Hits against this and other druggable sites achieve docking scores corresponding to a Kd in the µM–nM range, comparing favourably with a recently identified promising lead. Preliminary ThermoFluor studies support the docking predictions. In conclusion, our strategy shows considerable promise compared with the conventional single pocket/single conformer approach to in silico screening. Our best-scoring ligands warrant further experimental investigation

NRLMSIS 2.1: An Empirical Model of Nitric Oxide Incorporated Into MSIS

We have developed an empirical model of nitric oxide (NO) number density at altitudes from similar to 73 km to the exobase, as a function of altitude, latitude, day of year, solar zenith angle, solar activity, and geomagnetic activity. The model is part of the NRLMSIS (R) 2.1 empirical model of atmospheric temperature and species densities; this upgrade to NRLMSIS 2.0 consists solely of the addition of NO. MSIS 2.1 assimilates observations from six space-based instruments: UARS/HALOE, SNOE, Envisat/MIPAS, ACE/FTS, Odin/SMR, and AIM/SOFIE. We additionally evaluated the new model against independent extant NO data sets. In this paper, we describe the formulation and fitting of the model, examine biases between the data sets and model and among the data sets, compare with another empirical NO model (NOEM), and discuss scientific aspects of our analysis

Autophagy diminishes the early interferon- ? response to influenza A virus resulting in differential expression of interferon- stimulated genes

Influenza A virus (IAV) infection perturbs metabolic pathways such as autophagy, a stress-induced catabolic pathway that crosstalks with cellular inflammatory responses. However, the impact of autophagy perturbation on IAV gene expression or host cell responses remains disputed. Discrepant results may be a reflection of in vivo studies using cell-specific autophagy-related (Atg) gene-deficient mouse strains, which do not delineate modification of developmental programmes from more proximal effects on inflammatory response. In vitro experiments can be confounded by gene expression divergence in wild-type cultivated cell lines, as compared to those experiencing long-term absence of autophagy. With the goal to investigate cellular processes within cells that are competent or incompetent for autophagy, we generated a novel experimental cell line in which autophagy can be restored by ATG5 protein stabilization in an otherwise Atg5-deficient background. We confirmed that IAV induced autophagosome formation and p62 accumulation in infected cells and demonstrated that perturbation of autophagy did not impact viral infection or replication in ATG5-stablized cells. Notably, the induction of interferon-stimulated genes (ISGs) by IAV was diminished when cells were autophagy competent. We further demonstrated that, in the absence of ATG5, IAV-induced interferon-β (IFN-β) expression was increased as compared to levels in autophagy-competent lines, a mechanism that was independent of IAV non-structural protein 1. In sum, we report that induction of autophagy by IAV infection reduces ISG expression in infected cells by limiting IFN-β expression, which may benefit viral replication and spread

Numerical solution of the eXtended Pom-Pom model for viscoelastic free surface flows

In this paper we present a finite difference method for solving two-dimensional viscoelastic unsteady free surface flows governed by the single equation version of the eXtended Pom-Pom (XPP) model. The momentum equations are solved by a projection method which uncouples the velocity and pressure fields. We are interested in low Reynolds number flows and, to enhance the stability of the numerical method, an implicit technique for computing the pressure condition on the free surface is employed. This strategy is invoked to solve the governing equations within a Marker-and-Cell type approach while simultaneously calculating the correct normal stress condition on the free surface. The numerical code is validated by performing mesh refinement on a two-dimensional channel flow. Numerical results include an investigation of the influence of the parameters of the XPP equation on the extrudate swelling ratio and the simulation of the Barus effect for XPP fluids

Efficient Algorithm on a Non-staggered Mesh for Simulating Rayleigh-Benard Convection in a Box

An efficient semi-implicit second-order-accurate finite-difference method is described for studying incompressible Rayleigh-Benard convection in a box, with sidewalls that are periodic, thermally insulated, or thermally conducting. Operator-splitting and a projection method reduce the algorithm at each time step to the solution of four Helmholtz equations and one Poisson equation, and these are are solved by fast direct methods. The method is numerically stable even though all field values are placed on a single non-staggered mesh commensurate with the boundaries. The efficiency and accuracy of the method are characterized for several representative convection problems.Comment: REVTeX, 30 pages, 5 figure