One-dimensional quasi-relativistic particle in the box

Two-term Weyl-type asymptotic law for the eigenvalues of one-dimensional quasi-relativistic Hamiltonian (-h^2 c^2 d^2/dx^2 + m^2 c^4)^(1/2) + V_well(x) (the Klein-Gordon square-root operator with electrostatic potential) with the infinite square well potential V_well(x) is given: the n-th eigenvalue is equal to (n pi/2 - pi/8) h c/a + O(1/n), where 2a is the width of the potential well. Simplicity of eigenvalues is proved. Some L^2 and L^infinity properties of eigenfunctions are also studied. Eigenvalues represent energies of a `massive particle in the box' quasi-relativistic model.Comment: 40 pages, 4 figures; minor correction

In Silico Approaches and the Role of Ontologies in Aging Research

The 2013 Rostock Symposium on Systems Biology and Bioinformatics in Aging Research was again dedicated to dissecting the aging process using in silico means. A particular focus was on ontologies, as these are a key technology to systematically integrate heterogeneous information about the aging process. Related topics were databases and data integration. Other talks tackled modeling issues and applications, the latter including talks focussed on marker development and cellular stress as well as on diseases, in particular on diseases of kidney and skin

Computing the shortest elementary flux modes in genome-scale metabolic networks

This article is available open access through the publisher’s website through the link below. Copyright @ The Author 2009.Motivation: Elementary flux modes (EFMs) represent a key concept to analyze metabolic networks from a pathway-oriented perspective. In spite of considerable work in this field, the computation of the full set of elementary flux modes in large-scale metabolic networks still constitutes a challenging issue due to its underlying combinatorial complexity. Results: In this article, we illustrate that the full set of EFMs can be enumerated in increasing order of number of reactions via integer linear programming. In this light, we present a novel procedure to efficiently determine the K-shortest EFMs in large-scale metabolic networks. Our method was applied to find the K-shortest EFMs that produce lysine in the genome-scale metabolic networks of Escherichia coli and Corynebacterium glutamicum. A detailed analysis of the biological significance of the K-shortest EFMs was conducted, finding that glucose catabolism, ammonium assimilation, lysine anabolism and cofactor balancing were correctly predicted. The work presented here represents an important step forward in the analysis and computation of EFMs for large-scale metabolic networks, where traditional methods fail for networks of even moderate size. Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics online (http://bioinformatics.oxfordjournals.org/cgi/content/full/btp564/DC1).Fundação Calouste Gulbenkian, Fundação para a Ciência e a Tecnologia (FCT) and Siemens SA Portugal

Gearing motion in cogwheel pairs of molecular rotors: weak-coupling limit

Variable-​temp. (VT) crystal structures, VT 1H spin-​lattice relaxation in static crystals, and DFT modeling of the rotational barriers of BCP rotators in cryst. arrays of a rod-​like mol. contg. two 1,​3-​bis(ethynyl)​bicyclo[1.1.1]​pentane (BCP) units demonstrate that a correlated gearing motion occurs in the limit of a weak coupling between two rotors in a pair

Meneco, a Topology-Based Gap-Filling Tool Applicable to Degraded Genome-Wide Metabolic Networks

International audienceIncreasing amounts of sequence data are becoming available for a wide range of non-model organisms. Investigating and modelling the metabolic behaviour of those organisms is highly relevant to understand their biology and ecology. As sequences are often incomplete and poorly annotated, draft networks of their metabolism largely suffer from incompleteness. Appropriate gap-filling methods to identify and add missing reactions are therefore required to address this issue. However, current tools rely on phenotypic or taxonomic information, or are very sensitive to the stoichiometric balance of metabolic reactions, especially concerning the co-factors. This type of information is often not available or at least prone to errors for newly-explored organisms. Here we introduce Meneco, a tool dedicated to the topological gap-filling of genome-scale draft metabolic networks. Meneco reformulates gap-filling as a qualitative combinatorial optimization problem, omitting constraints raised by the stoichiometry of a metabolic network considered in other methods, and solves this problem using Answer Set Programming. Run on several artificial test sets gathering 10,800 degraded Escherichia coli networks Meneco was able to efficiently identify essential reactions missing in networks at high degradation rates, outperforming the stoichiometry-based tools in scalability. To demonstrate the utility of Meneco we applied it to two case studies. Its application to recent metabolic networks reconstructed for the brown algal model Ectocarpus siliculosus and an associated bacterium Candidatus Phaeomarinobacter ectocarpi revealed several candidate metabolic pathways for algal-bacterial interactions. Then Meneco was used to reconstruct, from transcriptomic and metabolomic data, the first metabolic network for the microalga Euglena mutabilis. These two case studies show that Meneco is a versatile tool to complete draft genome-scale metabolic networks produced from heterogeneous data, and to suggest relevant reactions that explain the metabolic capacity of a biological system

EQ-5D in Central and Eastern Europe : 2000-2015

Objective: Cost per quality-adjusted life year data are required for reimbursement decisions in many Central and Eastern European (CEE) countries. EQ-5D is by far the most commonly used instrument to generate utility values in CEE. This study aims to systematically review the literature on EQ-5D from eight CEE countries. Methods: An electronic database search was performed up to July 1, 2015 to identify original EQ-5D studies from the countries of interest. We analysed the use of EQ-5D with respect to clinical areas, methodological rigor, population norms and value sets. Results: We identified 143 studies providing 152 country-specific results with a total sample size of 81,619: Austria (n=11), Bulgaria (n=6), Czech Republic (n=18), Hungary (n=47), Poland (n=51), Romania (n=2), Slovakia (n=3) and Slovenia (n=14). Cardiovascular (20%), neurologic (16%), musculoskeletal (15%) and endocrine/nutritional/metabolic diseases (14%) were the most frequently studied clinical areas. Overall 112 (78%) of the studies reported EQ VAS results and 86 (60%) EQ-5D index scores, of which 27 (31%) did not specify the applied tariff. Hungary, Poland and Slovenia have population norms. Poland and Slovenia also have a national value set. Conclusions: Increasing use of EQ-5D is observed throughout CEE. The spread of health technology assessment activities in countries seems to be reflected in the number of EQ-5D studies. However, improvement in informed use and methodological quality of reporting is needed. In jurisdictions where no national value set is available, in order to ensure comparability we recommend to apply the most frequently used UK tariff. Regional collaboration between CEE countries should be strengthened

Avian infectious bronchitis: viral persistence in the harderian gland and histological changes after eyedrop vaccination

The histological changes in the harderian gland (HG) induced by the attenuated H-120 infectious bronchitis virus (IBV) vaccine strain and the persistence of this virus in the stroma of the gland was evaluated in chickens after eyedrop vaccination. Virus replication induced an increase in IBV-specific enzyme-linked immunosorbent assay antibody levels from marginal levels at vaccination (26 days of age) to significantly higher levels 10 days after exposure. IBV antigen was detected in the HG by both immunofluorescence using a monoclonal antibody and virus reisolation in embryonated chickens eggs until day 14 postvaccination. Lymphocytic, heterophilic, erythrocytic, and plasma cell infiltration as well as epithelial cell integrity in collecting tubules and acini were evaluated in the HG throughout the experimental period. IBV vaccination with the attenuated vaccine strain H-120 resulted in partial damage to the HG, as demonstrated by both the presence of plasma cells showing Russell bodies and by tubule epithelial cell exfoliation that occurs simultaneously with the presence of detectable IBV. The increase in plasma cell number and the enlargement of lymphoid foci appear to be expressions of the immunocompetence of this paraocular glan

Serological surveillance reveals patterns of exposure to H5 and H7 influenza A viruses in European poultry

Influenza A viruses of H5 and H7 subtype in poultry can circulate subclinically, and subsequently mutate from low to high pathogenicity with potentially devastating economic and welfare consequences. European Union Member States undertake surveillance of commercial and backyard poultry for early detection and control of subclinical H5 and H7 influenza A infection. This surveillance has moved towards a risk‐based sampling approach in recent years; however quantitative measures of relative risk associated with risk factors utilised in this approach are necessary for optimisation. This study describes serosurveillance for H5 and H7 influenza A in domestic and commercial poultry undertaken in the European Union from 2004 to 2010, where a random sampling and thus representative approach to serosurveillance was undertaken. Using these representative data, this study measured relative risk of seropositivity across poultry categories and spatially across the EU. Data were analysed using multivariable logistic regression. Domestic waterfowl, game birds, fattening turkeys, ratites, backyard poultry and the “other” poultry category holdings had relatively increased probability of H5 and/or H7 influenza A seropositivity, compared to laying‐hen holdings. Amongst laying‐hen holdings, free‐range rearing was associated with increased probability of H7 seropositivity. Spatial analyses detected ‘hotspots’ for H5 influenza A seropositivity in western France and England, and H7 influenza A seropositivity in Italy and Belgium, which may be explained by the demographics and distribution of poultry categories. Findings suggest certain poultry category holdings are at increased risk of subclinical H5 and/or H7 influenza A circulation, and free‐range rearing increases the likelihood of exposure to H7 influenza A. These findings may be used in further refining risk‐based surveillance strategies, and prioritising management strategies in influenza A outbreaks

Stoichiometric representation of geneproteinreaction associations leverages constraint-based analysis from reaction to gene-level phenotype prediction

Genome-scale metabolic reconstructions are currently available for hundreds of organisms. Constraint-based modeling enables the analysis of the phenotypic landscape of these organisms, predicting the response to genetic and environmental perturbations. However, since constraint-based models can only describe the metabolic phenotype at the reaction level, understanding the mechanistic link between genotype and phenotype is still hampered by the complexity of gene-protein-reaction associations. We implement a model transformation that enables constraint-based methods to be applied at the gene level by explicitly accounting for the individual fluxes of enzymes (and subunits) encoded by each gene. We show how this can be applied to different kinds of constraint-based analysis: flux distribution prediction, gene essentiality analysis, random flux sampling, elementary mode analysis, transcriptomics data integration, and rational strain design. In each case we demonstrate how this approach can lead to improved phenotype predictions and a deeper understanding of the genotype-to-phenotype link. In particular, we show that a large fraction of reaction-based designs obtained by current strain design methods are not actually feasible, and show how our approach allows using the same methods to obtain feasible gene-based designs. We also show, by extensive comparison with experimental 13C-flux data, how simple reformulations of different simulation methods with gene-wise objective functions result in improved prediction accuracy. The model transformation proposed in this work enables existing constraint-based methods to be used at the gene level without modification. This automatically leverages phenotype analysis from reaction to gene level, improving the biological insight that can be obtained from genome-scale models.DM was supported by the Portuguese Foundationfor Science and Technologythrough a post-doc fellowship (ref: SFRH/BPD/111519/ 2015). This study was supported by the PortugueseFoundationfor Science and Technology (FCT) under the scope of the strategic fundingof UID/BIO/04469/2013 unitand COMPETE2020 (POCI-01-0145-FEDER-006684) and BioTecNorte operation (NORTE-01-0145FEDER-000004) fundedby EuropeanRegional Development Fund under the scope of Norte2020Programa Operacional Regional do Norte. This project has received fundingfrom the European Union’s Horizon 2020 research and innovation programme under grant agreementNo 686070. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript