Experiences with Moodle as a communication tool for design teamwork: a users' perspective

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Acute brucella melitensis M16 infection model in mice treated with tumor necrosis factor-alpha inhibitors

Introduction: There is limited data in the literature about brucellosis related to an intracellular pathogen and anti-tumor necrosis factor alpha (anti-TNFα) medication. The aim of this study was to evaluate acute Brucella infections in mice receiving anti-TNFα drug treatment. Methodology: Anti-TNFα drugs were injected in mice on the first and fifth days of the study, after which the mice were infected with B. melitensis M16 strain. Mice were sacrificed on the fourteenth day after infection. Bacterial loads in the liver and spleen were defined, and histopathological changes were evaluated. Results: Neither the liver nor the spleen showed an increased bacterial load in all anti-TNFα drug groups when compared to a non-treated, infected group. The most significant histopathological findings were neutrophil infiltrations in the red pulp of the spleen and apoptotic cells with hepatocellular pleomorphism in the liver. There was no significant difference among the groups in terms of previously reported histopathological findings, such as extramedullary hematopoiesis and granuloma formation. Conclusions: There were no differences in hepatic and splenic bacterial load and granuloma formation, which indicate worsening of the acute Brucella infection in mice; in other words, anti-TNFα treatment did not exacerbate the acute Brucella spp. infection in mice. © 2015 Kutlu et al

Determination of Yield and Yield Components of Vetch and Cereal Mixture and Evaluation Using by GGE-Biplot Analysis

This study was carried out to determine forage and seed yield and its effecting component in different vetch and cereal mixtures, ecological condition of Tekirdağ-Thrace region of Turkey. The study was conducted using a total 5 vetch and cereals varieties includes three different vetch species orakefe, Hungarian vetch species sarıefe, narbon vetch candidate variety 570, two different cereals (barley variety scarpia, oat variety sebat) and their mixture combinations, each species were sown as sole, double and triple mixtures (8 combinations for each genotype) a randomized complete block design with 3 replications was laid out on 2013-2015 growing season. Eight mixture combinations for each genotype (common vetch, Hungarian vetch, Narbon vetch, barley and oat) were evaluated for yield and major plant structural characteristics. Genotype-Trait (GT) biplot analyses were used. Applying type of analyses to the multiple trait data revealed that GT biplot graphically displayed the interrelationships among traits and facilitated visual comparison of mixtures and selection for each genotype. Wide variation was observed for traits plant structure and components (plant height, branch number and pod number/plant, 1000 seed weight, individual genotype ratio). It was found that; seed yield, 1000 seed weight, plant height, branch and pod number /plant were the highest value in pure stand NV570. In addition (570+sebat) had maximum dry forage yield, sarıefe as pure stand has the maximum plant height and seed yield value. On the other had sarıefe+scarpia combination showed very high value for pod number/plant, branch number/plant and fresh and dry forage yield. Pure stand scarpia was the best performer in seed yield. CV+NV+scarpia had the highest 1000 seed weight, fresh and dry forage yield. Maximum planth height was determined from sebat+scarpia, CV+O+B and CV+HV+B combinations. Favorable seed yield and 1000 seed weight value was produced under pure stand sebat seeding. Intercrop NV570+O combination had the higher fresh and dry forage yield. CV+HV+O, CV+NV+O and CV+B+O combination had the highest plant height of sebat

Psychometric precision in phenotype definition is a useful step in molecular genetic investigation of psychiatric disorders

Affective disorders are highly heritable, but few genetic risk variants have been consistently replicated in molecular genetic association studies. The common method of defining psychiatric phenotypes in molecular genetic research is either a summation of symptom scores or binary threshold score representing the risk of diagnosis. Psychometric latent variable methods can improve the precision of psychiatric phenotypes, especially when the data structure is not straightforward. Using data from the British 1946 birth cohort, we compared summary scores with psychometric modeling based on the General Health Questionnaire (GHQ-28) scale for affective symptoms in an association analysis of 27 candidate genes (249 single-nucleotide polymorphisms (SNPs)). The psychometric method utilized a bi-factor model that partitioned the phenotype variances into five orthogonal latent variable factors, in accordance with the multidimensional data structure of the GHQ-28 involving somatic, social, anxiety and depression domains. Results showed that, compared with the summation approach, the affective symptoms defined by the bi-factor psychometric model had a higher number of associated SNPs of larger effect sizes. These results suggest that psychometrically defined mental health phenotypes can reflect the dimensions of complex phenotypes better than summation scores, and therefore offer a useful approach in genetic association investigations

Implications of strategic alliances for earnings quality and capital market investors

Strategic alliances are well-established organizational forms and a means of strategy implementation. Despite their growing pervasiveness in the economy, existent literature provides few insights about earnings quality of strategic alliances. This challenge is especially severe in contractual alliances (CAs), where firms do not form a new corporate entity that is separate from the parent organization in comparison to joint ventures (JVs). We investigate how earnings attributes differ depending on involvement in strategic alliances of 8137 CAs and 3026 JVs spanning 1997-2007. We find, in particular, that earnings attributes of firms involved in contractual alliances are broadly reflective of low underlying accounting quality. Relative to JV firms and non-alliance (NA) firms, they have higher levels of discretionary accruals, lower accrual quality, and earnings that are less persistent, less smooth, less relevant, less timely, and less conservative. They also have lower earnings response coefficients. © 2013 Elsevier Inc

Ovine pedomics : the first study of the ovine foot 16S rRNA-based microbiome

We report the first study of the bacterial microbiome of ovine interdigital skin based on 16S rRNA by pyrosequencing and conventional cloning with Sanger-sequencing. Three flocks were selected, one a flock with no signs of footrot or interdigital dermatitis, a second flock with interdigital dermatitis alone and a third flock with both interdigital dermatitis and footrot. The sheep were classified as having either healthy interdigital skin (H), interdigital dermatitis (ID) or virulent footrot (VFR). The ovine interdigital skin bacterial community varied significantly by flock and clinical condition. The diversity and richness of operational taxonomic units was greater in tissue from sheep with ID than H or VFR affected sheep. Actinobacteria, Bacteriodetes, Firmicutes and Proteobacteria were the most abundant phyla comprising 25 genera. Peptostreptococcus, Corynebacterium and Staphylococcus were associated with H, ID and VFR respectively. Sequences of Dichelobacter nodosus, the causal agent of ovine footrot, were not amplified due to mismatches in the 16S rRNA universal forward primer (27F). A specific real time PCR assay was used to demonstrate the presence of D. nodosus which was detected in all samples including the flock with no signs of ID or VFR. Sheep with ID had significantly higher numbers of D. nodosus (104-109 cells/g tissue) than those with H or VFR feet

Genetic Determinants of Circulating Sphingolipid Concentrations in European Populations

Sphingolipids have essential roles as structural components of cell membranes and in cell signalling, and disruption of their metabolism causes several diseases, with diverse neurological, psychiatric, and metabolic consequences. Increasingly, variants within a few of the genes that encode enzymes involved in sphingolipid metabolism are being associated with complex disease phenotypes. Direct experimental evidence supports a role of specific sphingolipid species in several common complex chronic disease processes including atherosclerotic plaque formation, myocardial infarction (MI), cardiomyopathy, pancreatic beta-cell failure, insulin resistance, and type 2 diabetes mellitus. Therefore, sphingolipids represent novel and important intermediate phenotypes for genetic analysis, yet little is known about the major genetic variants that influence their circulating levels in the general population. We performed a genome-wide association study (GWAS) between 318,237 single-nucleotide polymorphisms (SNPs) and levels of circulating sphingomyelin (SM), dihydrosphingomyelin (Dih-SM), ceramide (Cer), and glucosylceramide (GluCer) single lipid species (33 traits); and 43 matched metabolite ratios measured in 4,400 subjects from five diverse European populations. Associated variants (32) in five genomic regions were identified with genome-wide significant corrected p-values ranging down to 9.08 x 10(-66). The strongest associations were observed in or near 7 genes functionally involved in ceramide biosynthesis and trafficking: SPTLC3, LASS4, SGPP1, ATP10D, and FADS1-3. Variants in 3 loci (ATP10D, FADS3, and SPTLC3) associate with MI in a series of three German MI studies. An additional 70 variants across 23 candidate genes involved in sphingolipid-metabolizing pathways also demonstrate association (p = 10(-4) or less). Circulating concentrations of several key components in sphingolipid metabolism are thus under strong genetic control, and variants in these loci can be tested for a role in the development of common cardiovascular, metabolic, neurological, and psychiatric diseases

Service Oriented Big Data Management for Transport

International audienceThe increasing power of computer hardware and the sophistication of computer software have brought many new possibilities to information world. On one side the possibility to analyse massive data sets has brought new insight, knowledge and information. On the other, it has enabled to massively distribute computing and has opened to a new programming paradigm called Service Oriented Computing particularly well adapted to cloud computing. Applying these new technologies to the transport industry can bring new understanding to town transport infrastructures. The objective of our work is to manage and aggregate cloud services for managing big data and assist decision making for transport systems. Thus this paper presents our approach to propose a service oriented architecture for big data analytics for transport systems based on the cloud. Proposing big data management strategies for data produced by transport infra‐ structures, whilst maintaining cost effective systems deployed on the cloud, is a promising approach. We present the advancement for developing the Data acquisition service and Information extraction and cleaning service as well as the analysis for choosing a sharding strategy

Interparty Social Dynamics in the IT Service Level Agreement Negotiation Process: A Preliminary Assessment of Competing Theories

In response to the global economic crisis, organizations are cutting costs and focusing on core competencies. One natural corollary of this situation has been an increased interest in the outsourcing of IT services. Such sourcing relationships are established and maintained via formally negotiated IT service level agreements (SLAs), the goal of which is to generate utility for both parties. Understanding the processes that produce successful IT SLA negotiation outcomes is thus of critical importance. While several well-established social theories seem germane to IT service level agreement negotiations, the predictions of those theories are not entirely compatible and consistent. This paper therefore develops and tests several preliminary research propositions in an effort to assess the applicability of these competing theories to the IT SLA negotiation process

Identifying Relevant Socio-Theoretic Foundations for Supporting Multi-Issue IT Cloudsourcing Negotiations

Service level agreement (SLA) negotiations involving cloud-based information technology (IT) service providers and customers are now commonplace. Although historical research on negotiation has often relied on economic foundations, the important nature of IT service levels to organizations’ operational effectiveness suggests that negotiation complexities in the context of cloud-based outsourcing (or cloudsourcing) cannot be well understood by relying on economic perspectives alone. To that end, this paper reports on experiments designed to determine the relevance of competing sociotheoretic frameworks as they pertain to IT cloudsourcing negotiations. Contributions include a rigorous examination of hypotheses derived from social exchange theory, equity theory, learning theory, and the win–win theories of negotiation. Additional contributions include the development of methodological constructs (using the Euclidean geometry) that reflect the complex nature of IT cloudsourcing SLAs, i.e., that they are composed of numerous service category contract clauses where negotiation tradeoffs within a service category as well as across service categories are possible. We find strong support for the relevance of the social exchange theory to IT cloudsourcing negotiations, as well as moderate support for the win-win theories of negotiation. Our conclusions provide clear directions for extending our work into the realm of negotiation support systems, and we rely on our findings to conjecture that IT cloudsourcing negotiation is a unique context for sociotheoretic negotiation research due to the inherent importance of information technologies to organizations’ operational effectiveness