120 research outputs found

    Verifying for Compliance to Data Constraints in Collaborative Business Processes.

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    Production processes are nowadays fragmented across different companies and organized in global collaborative networks. This is the result of the first wave of globalization that, among the various factors, was enabled by the diffusion of Internet-based Information and Communication Technologies (ICTs) at the beginning of the years 2000. The recent wave of new technologies possibly leading to the fourth industrial revolution – the so-called Industry 4.0 – is further multiplying opportunities. Accessing global customers opens great opportunities for organizations, including small and medium enterprises (SMEs), but it requires the ability to adapt to different requirements and conditions, volatile demand patterns and fast-changing technologies. Regardless of the industrial sector, the processes used in an organization must be compliant to rules, standards, laws and regulations. Non-compliance subjects enterprises to litigation and financial fines. Thus, compliance verification is a major concern, not only to keep pace with changing regulations but also to address the rising concerns of security, product and service quality and data privacy. The software, in particular process automation, used must be designed accordingly. In relation to process management, we propose a new way to pro-actively check the compliance of current running business processes using Descriptive Logic and Linear Temporal Logic to describe the constraints related to data. Related algorithms are presented to detect the potential violations

    Busulphan-Cyclophosphamide Cause Endothelial Injury, Remodeling of Resistance Arteries and Enhanced Expression of Endothelial Nitric Oxide Synthase

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    Stem cell transplantation (SCT) is a curative treatment for malignant and non malignant diseases. However, transplantation-related complications including cardiovascular disease deteriorate the clinical outcome and quality of life. We have investigated the acute effects of conditioning regimen on the pharmacology, physiology and structure of large elastic arteries and small resistance-sized arteries in a SCT mouse model. Mesenteric resistance arteries and aorta were dissected from Balb/c mice conditioned with busulphan (Bu) and cyclophosphamide (Cy). In vitro isometric force development and pharmacology, in combination with RT-PCR, Western blotting and electron microscopy were used to study vascular properties. Compared with controls, mesenteric resistance arteries from the Bu-Cy group had larger internal circumference, showed enhanced endothelium mediated relaxation and increased expression of endothelial nitric oxide synthase (eNOS). Bu-Cy treated animals had lower mean blood pressure and signs of endothelial injury. Aortas of treated animals had a higher reactivity to noradrenaline. We conclude that short-term consequences of Bu-Cy treatment divergently affect large and small arteries of the cardiovascular system. The increased noradrenaline reactivity of large elastic arteries was not associated with increased blood pressure at rest. Instead, Bu-Cy treatment lowered blood pressure via augmented microvascular endothelial dependent relaxation, increased expression of vascular eNOS and remodeling toward a larger lumen. The changes in the properties of resistance arteries can be associated with direct effects of the compounds on vascular wall or possibly indirectly induced via altered translational activity associated with the reduced hematocrit and shear stress. This study contributes to understanding the mechanisms that underlie the early effects of conditioning regimen on resistance arteries and may help in designing further investigations to understand the late effects on vascular system

    Mining Predicted Essential Genes of Brugia malayi for Nematode Drug Targets

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    We report results from the first genome-wide application of a rational drug target selection methodology to a metazoan pathogen genome, the completed draft sequence of Brugia malayi, a parasitic nematode responsible for human lymphatic filariasis. More than 1.5 billion people worldwide are at risk of contracting lymphatic filariasis and onchocerciasis, a related filarial disease. Drug treatments for filariasis have not changed significantly in over 20 years, and with the risk of resistance rising, there is an urgent need for the development of new anti-filarial drug therapies. The recent publication of the draft genomic sequence for B. malayi enables a genome-wide search for new drug targets. However, there is no functional genomics data in B. malayi to guide the selection of potential drug targets. To circumvent this problem, we have utilized the free-living model nematode Caenorhabditis elegans as a surrogate for B. malayi. Sequence comparisons between the two genomes allow us to map C. elegans orthologs to B. malayi genes. Using these orthology mappings and by incorporating the extensive genomic and functional genomic data, including genome-wide RNAi screens, that already exist for C. elegans, we identify potentially essential genes in B. malayi. Further incorporation of human host genome sequence data and a custom algorithm for prioritization enables us to collect and rank nearly 600 drug target candidates. Previously identified potential drug targets cluster near the top of our prioritized list, lending credibility to our methodology. Over-represented Gene Ontology terms, predicted InterPro domains, and RNAi phenotypes of C. elegans orthologs associated with the potential target pool are identified. By virtue of the selection procedure, the potential B. malayi drug targets highlight components of key processes in nematode biology such as central metabolism, molting and regulation of gene expression

    Identification of novel common variants associated with chronic pain using conditional false discovery rate analysis with major depressive disorder and assessment of pleiotropic effects of LRFN5

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    Chronic pain is a complex trait that is moderately heritable and genetically, as well as phenotypically, correlated with major depressive disorder (MDD). Use of the conditional false discovery rate (cFDR) approach, which leverages pleiotropy identified from existing GWAS outputs, has been successful in discovering novel associated variants in related phenotypes. Here, genome-wide association study outputs for both von Korff chronic pain grade and for MDD were used to identify variants meeting a cFDR threshold for each outcome phenotype separately, as well as a conjunctional cFDR (ccFDR) threshold for both phenotypes together. Using a moderately conservative threshold, we identified a total of 11 novel single nucleotide polymorphisms (SNPs), six of which were associated with chronic pain grade and nine of which were associated with MDD. Four SNPs on chromosome 14 were associated with both chronic pain grade and MDD. SNPs associated only with chronic pain grade were located within SLC16A7 on chromosome 12. SNPs associated only with MDD were located either in a gene-dense region on chromosome 1 harbouring LINC01360, LRRIQ3, FPGT and FPGT-TNNI3K, or within/close to LRFN5 on chromosome 14. The SNPs associated with both outcomes were also located within LRFN5. Several of the SNPs on chromosomes 1 and 14 were identified as being associated with expression levels of nearby genes in the brain and central nervous system. Overall, using the cFDR approach, we identified several novel genetic loci associated with chronic pain and we describe likely pleiotropic effects of a recently identified MDD locus on chronic pain
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