Helicobacter suis infection alters glycosylation and decreases the pathogen growth inhibiting effect and binding avidity of gastric mucins

Helicobacter suis is the most prevalent non-Helicobacter pylori Helicobacter species in the human stomach and is associated with chronic gastritis, peptic ulcer disease, and gastric mucosa-associated lymphoid tissue (MALT) lymphoma. H. suis colonizes the gastric mucosa of 60-95% of pigs at slaughter age, and is associated with chronic gastritis, decreased weight gain, and ulcers. Here, we show that experimental H. suis infection changes the mucin composition and glycosylation, decreasing the amount of H. suis-binding glycan structures in the pig gastric mucus niche. Similarly, the H. suis-binding ability of mucins from H. pylori-infected humans is lower than that of noninfected individuals. Furthermore, the H. suis growth-inhibiting effect of mucins from both noninfected humans and pigs is replaced by a growth-enhancing effect by mucins from infected individuals/pigs. Thus, Helicobacter spp. infections impair the mucus barrier by decreasing the H. suis-binding ability of the mucins and by decreasing the antiprolific activity that mucins can have on H. suis. Inhibition of these mucus-based defenses creates a more stable and inhabitable niche for H. suis. This is likely of importance for long-term colonization and outcome of infection, and reversing these impairments may have therapeutic benefits

Challenging claims in the study of migratory birds and climate change

Recent shifts in phenology in response to climate change are well established but often poorly understood. Many animals integrate climate change across a spatially and temporally dispersed annual life cycle, and effects are modulated by ecological interactions, evolutionary change and endogenous control mechanisms. Here we assess and discuss key statements emerging from the rapidly developing study of changing spring phenology in migratory birds. These well-studied organisms have been instrumental for understanding climate-change effects, but research is developing rapidly and there is a need to attack the big issues rather than risking affirmative science. Although we agree poorly on the support for most claims, agreement regarding the knowledge basis enables consensus regarding broad patterns and likely causes. Empirical data needed for disentangling mechanisms are still scarce, and consequences at a population level and on community composition remain unclear. With increasing knowledge, the overall support (‘consensus view’) for a claim increased and between-researcher variability in support (‘expert opinions') decreased, indicating the importance of assessing and communicating the knowledge basis. A proper integration across biological disciplines seems essential for the field's transition from affirming patterns to understanding mechanisms and making robust predictions regarding future consequences of shifting phenologies

Enlightening the structure and dynamics of Abell 1942

We present a dynamical analysis of the galaxy cluster Abell 1942 based on a set of 128 velocities obtained at the European Southern Observatory. Data on individual galaxies are presented and the accuracy of the determined velocities is discussed as well as some properties of the cluster. We have also made use of publicly available Chandra X-ray data. We obtained an improved mean redshift value z = 0.22513 \pm 0.0008 and velocity dispersion sigma = 908^{+147}_{-139} km/s. Our analysis indicates that inside a radius of ~1.5 h_{70}^{-1} Mpc (~7 arcmin) the cluster is well relaxed, without any remarkable feature and the X-ray emission traces fairly well the galaxy distribution. Two possible optical substructures are seen at ~5 arcmin from the centre towards the Northwest and the Southwest direction, but are not confirmed by the velocity field. These clumps are however, kinematically bound to the main structure of Abell 1942. X-ray spectroscopic analysis of Chandra data resulted in a temperature kT = 5.5 \pm 0.5 keV and metal abundance Z = 0.33 \pm 0.15 Z_odot. The velocity dispersion corresponding to this temperature using the T_X-sigma scaling relation is in good agreement with the measured galaxies velocities. Our photometric redshift analysis suggests that the weak lensing signal observed at the south of the cluster and previously attributed to a "dark clump", is produced by background sources, possibly distributed as a filamentary structure.Comment: Accepted for publication in Astronomy & Astrophysics, 15 pages, 15 figures, table w/ positions, photometric data and redshift

The sign problem in Monte Carlo simulations of frustrated quantum spin systems

We discuss the sign problem arising in Monte Carlo simulations of frustrated quantum spin systems. We show that for a class of ``semi-frustrated'' systems (Heisenberg models with ferromagnetic couplings $J_z(r) < 0$ along the $z$-axis and antiferromagnetic couplings $J_{xy}(r)=-J_z(r)$ in the $xy$-plane, for arbitrary distances $r$) the sign problem present for algorithms operating in the $z$-basis can be solved within a recent ``operator-loop'' formulation of the stochastic series expansion method (a cluster algorithm for sampling the diagonal matrix elements of the power series expansion of ${\rm exp}(-\beta H)$ to all orders). The solution relies on identification of operator-loops which change the configuration sign when updated (``merons'') and is similar to the meron-cluster algorithm recently proposed by Chandrasekharan and Wiese for solving the sign problem for a class of fermion models (Phys. Rev. Lett. {\bf 83}, 3116 (1999)). Some important expectation values, e.g., the internal energy, can be evaluated in the subspace with no merons, where the weight function is positive definite. Calculations of other expectation values require sampling of configurations with only a small number of merons (typically zero or two), with an accompanying sign problem which is not serious. We also discuss problems which arise in applying the meron concept to more general quantum spin models with frustrated interactions.Comment: 13 pages, 16 figure

The elusive source of quantum effectiveness

We discuss two qualities of quantum systems: various correlations existing between their subsystems and the distingushability of different quantum states. This is then applied to analysing quantum information processing. While quantum correlations, or entanglement, are clearly of paramount importance for efficient pure state manipulations, mixed states present a much richer arena and reveal a more subtle interplay between correlations and distinguishability. The current work explores a number of issues related with identifying the important ingredients needed for quantum information processing. We discuss the Deutsch-Jozsa algorithm, the Shor algorithm, the Grover algorithm and the power of a single qubit class of algorithms. One section is dedicated to cluster states where entanglement is crucial, but its precise role is highly counter-intuitive. Here we see that distinguishability becomes a more useful concept.Comment: 8 pages, no figure

Stochastic series expansion method with operator-loop update

A cluster update (the ``operator-loop'') is developed within the framework of a numerically exact quantum Monte Carlo method based on the power series expansion of exp(-BH) (stochastic series expansion). The method is generally applicable to a wide class of lattice Hamiltonians for which the expansion is positive definite. For some important models the operator-loop algorithm is more efficient than loop updates previously developed for ``worldline'' simulations. The method is here tested on a two-dimensional anisotropic Heisenberg antiferromagnet in a magnetic field.Comment: 5 pages, 4 figure

The role of winding numbers in quantum Monte Carlo simulations

We discuss the effects of fixing the winding number in quantum Monte Carlo simulations. We present a simple geometrical argument as well as strong numerical evidence that one can obtain exact ground state results for periodic boundary conditions without changing the winding number. However, for very small systems the temperature has to be considerably lower than in simulations with fluctuating winding numbers. The relative deviation of a calculated observable from the exact ground state result typically scales as $T^{\gamma}$, where the exponent $\gamma$ is model and observable dependent and the prefactor decreases with increasing system size. Analytic results for a quantum rotor model further support our claim.Comment: 5 pages, 5 figure

Groups of Galaxies in AEGIS: The 200 ksec Chandra Extended X-ray Source catalogue

We present the discovery of seven X-ray emitting groups of galaxies selected as extended X-ray sources in the 200 ksec Chandra coverage of the All-wavelength Extended Groth Strip International Survey (AEGIS). In addition, we report on AGN activity associated to these systems. Using the DEEP2 Galaxy Redshift Survey coverage, we identify optical counterparts and determine velocity dispersions. In particular, we find three massive high-redshift groups at z>0.7, one of which is at z=1.13, the first X-ray detections of spectroscopically selected DEEP2 groups. We also present a first look at the the L_X-T, L_X-sigma, and sigma-T scaling relations for high-redshift massive groups. We find that the properties of these X-ray selected systems agree well with the scaling relations of similar systems at low redshift, although there are X-ray undetected groups in the DEEP2 catalogue with similar velocity dispersions. The other three X-ray groups with identified redshifts are associated with lower mass groups at z~0.07 and together form part of a large structure or "supergroup" in the southern portion of the AEGIS field. All of the low-redshift systems are centred on massive elliptical galaxies, and all of the high-redshift groups have likely central galaxies or galaxy pairs. All of the central group galaxies host X-ray point sources, radio sources, and/or show optical AGN emission. Particularly interesting examples of central AGN activity include a bent-double radio source plus X-ray point source at the center of a group at z=0.74, extended radio and double X-ray point sources associated to the central galaxy in the lowest-redshift group at z=0.066, and a bright green valley galaxy (part of a pair) in the z=1.13 group which shows optical AGN emission lines.Comment: accepted to MNRAS, 15 pages, 11 figures, for version with full resolution figures see http://www.ucolick.org/~tesla/aegis_groups.ps.g

Entanglement on mixed stabilizer states: normal forms and reduction procedures

Published versio

Boosting Schizophrenia Genetics by Utilizing Genetic Overlap With Brain Morphology

Background Schizophrenia is a complex polygenic disorder with subtle, distributed abnormalities in brain morphology. There are indications of shared genetic architecture between schizophrenia and brain measures despite low genetic correlations. Through the use of analytical methods that allow for mixed directions of effects, this overlap may be leveraged to improve our understanding of underlying mechanisms of schizophrenia and enrich polygenic risk prediction outcome. Methods We ran a multivariate genome-wide analysis of 175 brain morphology measures using data from 33,735 participants of the UK Biobank and analyzed the results in a conditional false discovery rate together with schizophrenia genome-wide association study summary statistics of the Psychiatric Genomics Consortium (PGC) Wave 3. We subsequently created a pleiotropy-enriched polygenic score based on the loci identified through the conditional false discovery rate approach and used this to predict schizophrenia in a nonoverlapping sample of 743 individuals with schizophrenia and 1074 healthy controls. Results We found that 20% of the loci and 50% of the genes significantly associated with schizophrenia were also associated with brain morphology. The conditional false discovery rate analysis identified 428 loci, including 267 novel loci, significantly associated with brain-linked schizophrenia risk, with functional annotation indicating high relevance for brain tissue. The pleiotropy-enriched polygenic score explained more variance in liability than conventional polygenic scores across several scenarios. Conclusions Our results indicate strong genetic overlap between schizophrenia and brain morphology with mixed directions of effect. The results also illustrate the potential of exploiting polygenetic overlap between brain morphology and mental disorders to boost discovery of brain tissue–specific genetic variants and its use in polygenic risk frameworks.publishedVersio