An examination of the factorial invariance and refinement of the multidimensional school anger inventory for five Pacific Rim countries

The validity of the Multidimensional School Anger Inventory (MSAI) was examined with adolescents from 5 Pacific Rim countries (N ¼ 3,181 adolescents; age, M ¼ 14.8 years; 52% females). Confirmatory factor analyses examined configural invariance for the MSAI’s anger experience, hostility, destructive expression, and anger coping subscales. The model did not converge for Peruvian students. Using the top 4 loaded items for anger experience, hostility, and destructive expression configural invariance and partial metric and scalar invariances were found. Latent means analysis compared mean responses on each subscale to the U.S. sample. Students from other countries showed higher mean responses on the anger experience subscale (ds ¼ .37–.73). Australian (d ¼ .40) and Japanese students (d ¼ .21) had significantly higher mean hostility subscale scores. Australian students had higher mean scores on the destructive expression subscale (d ¼ .30), whereas Japanese students had lower mean scores (d ¼ 2.17). The largest latent mean gender differences (females lower than males) were for destructive expression among Australian (d ¼ 2.67), Guatemalan (d ¼ 2.42), and U.S. (d ¼ 2.66) students. This study supported an abbreviated, 12-item MSAI with partial invariance. Implications for the use of the MSAI in comparative research are discussed.

Unveiling hidden unstructured regions in process models

Process models define allowed process execution scenarios. The models are usually depicted as directed graphs, with gateway nodes regulating the control flow routing logic and with edges specifying the execution order constraints between tasks. While arbitrarily structured control flow patterns in process models complicate model analysis, they also permit creativity and full expressiveness when capturing non-trivial process scenarios. This paper gives a classification of arbitrarily structured process models based on the hierarchical process model decomposition technique. We identify a structural class of models consisting of block structured patterns which, when combined, define complex execution scenarios spanning across the individual patterns. We show that complex behavior can be localized by examining structural relations of loops in hidden unstructured regions of control flow. The correctness of the behavior of process models within these regions can be validated in linear time. These observations allow us to suggest techniques for transforming hidden unstructured regions into block-structured ones.

The biconnected verification of workflow nets

Formal representations of business processes are used for analysis of the process behavior. Workflow nets are a widely used formalism for describing the behavior of business processes. Structure theory of processes investigates the relation between the structure of a model and its behavior. In this paper, we propose to employ the connectivity property of workflow nets as an angle to their structural analysis. In particular, we show how soundness verification can be organized using biconnected components of a workflow net. This allows for efficient identification and localization of flaws in the behavior of workflow nets and for supporting process analysts with diagnostic information

Structural and functional characterization of three DsbA Paralogues from Salmonella enterica Serovar Typhimurium

In prototypic Escherichia coli K-12 the introduction of disulfide bonds into folding proteins is mediated by the Dsb family of enzymes, primarily through the actions of the highly oxidizing protein EcDsbA. Homologues of the Dsb catalysts are found in most bacteria. Interestingly, pathogens have developed distinct Dsb machineries that play a pivotal role in the biogenesis of virulence factors, hence contributing to their pathogenicity. Salmonella enterica serovar (sv.) Typhimurium encodes an extended number of sulfhydryl oxidases, namely SeDsbA, SeDsbL, and SeSrgA. Here we report a comprehensive analysis of the sv. Typhimurium thiol oxidative system through the structural and functional characterization of the three Salmonella DsbA paralogues. The three proteins share low sequence identity, which results in several unique three-dimensional characteristics, principally in areas involved in substrate binding and disulfide catalysis. Furthermore, the Salmonella DsbA-like proteins also have different redox properties. Whereas functional characterization revealed some degree of redundancy, the properties of SeDsbA, SeDsbL, and SeSrgA and their expression pattern in sv. Typhimurium indicate a diverse role for these enzymes in virulence.

Genetics of rheumatoid arthritis contributes to biology and drug discovery

A major challenge in human genetics is to devise a systematic strategy to integrate disease-associated variants with diverse genomic and biological data sets to provide insight into disease pathogenesis and guide drug discovery for complex traits such as rheumatoid arthritis (RA)1. Here we performed a genome-wide association study meta-analysis in a total of >100,000 subjects of European and Asian ancestries (29,880 RA cases and 73,758 controls), by evaluating ~10 million single-nucleotide polymorphisms. We discovered 42 novel RA risk loci at a genome-wide level of significance, bringing the total to 101 (refs 2, 3, 4). We devised an in silico pipeline using established bioinformatics methods based on functional annotation5, cis-acting expression quantitative trait loci6 and pathway analyses7, 8, 9—as well as novel methods based on genetic overlap with human primary immunodeficiency, haematological cancer somatic mutations and knockout mouse phenotypes—to identify 98 biological candidate genes at these 101 risk loci. We demonstrate that these genes are the targets of approved therapies for RA, and further suggest that drugs approved for other indications may be repurposed for the treatment of RA. Together, this comprehensive genetic study sheds light on fundamental genes, pathways and cell types that contribute to RA pathogenesis, and provides empirical evidence that the genetics of RA can provide important information for drug discovery.