172 research outputs found

    A generalization of the differential approach to recursive query evaluation

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    AbstractThe differential (or seminaive) approach to query evaluation in function free, recursively defined, Horn clauses was recently proposed as an improvement to the naive bottom-up evaluation strategy. In this paper, we extend the approach to efficiently accomodate n recursively defined predicates in the body of a Horn clause

    Generating Random Logic Programs Using Constraint Programming

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    Testing algorithms across a wide range of problem instances is crucial to ensure the validity of any claim about one algorithm's superiority over another. However, when it comes to inference algorithms for probabilistic logic programs, experimental evaluations are limited to only a few programs. Existing methods to generate random logic programs are limited to propositional programs and often impose stringent syntactic restrictions. We present a novel approach to generating random logic programs and random probabilistic logic programs using constraint programming, introducing a new constraint to control the independence structure of the underlying probability distribution. We also provide a combinatorial argument for the correctness of the model, show how the model scales with parameter values, and use the model to compare probabilistic inference algorithms across a range of synthetic problems. Our model allows inference algorithm developers to evaluate and compare the algorithms across a wide range of instances, providing a detailed picture of their (comparative) strengths and weaknesses.Comment: This is an extended version of the paper published in CP 202

    Distribution and outcomes of a phenotype-based approach to guide COPD management: Results from the CHAIN cohort

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    Rationale: The Spanish guideline for COPD (GesEPOC) recommends COPD treatment according to four clinical phenotypes: non-exacerbator phenotype with either chronic bronchitis or emphysema (NE), asthma-COPD overlap syndrome (ACOS), frequent exacerbator phenotype with emphysema (FEE) or frequent exacerbator phenotype with chronic bronchitis (FECB). However, little is known on the distribution and outcomes of the four suggested phenotypes. Objective: We aimed to determine the distribution of these COPD phenotypes, and their relation with one-year clinical outcomes. Methods: We followed a cohort of well-characterized patients with COPD up to one-year. Baseline characteristics, health status (CAT), BODE index, rate of exacerbations and mortality up to one year of follow-up were compared between the four phenotypes. Results: Overall, 831 stable COPD patients were evaluated. They were distributed as NE, 550 (66.2%); ACOS, 125 (15.0%); FEE, 38 (4.6%); and FECB, 99 (11.9%); additionally 19 (2.3%) COPD patients with frequent exacerbations did not fulfill the criteria for neither FEE nor FECB. At baseline, there were significant differences in symptoms, FEV1 and BODE index (all p<0.05). The FECB phenotype had the highest CAT score (17.1±8.2, p<0.05 compared to the other phenotypes). Frequent exacerbator groups (FEE and FECB) were receiving more pharmacological treatment at baseline, and also experienced more exacerbations the year after (all p<0.05) with no differences in one-year mortality. Most of NE (93%) and half of exacerbators were stable after one year. Conclusions: There is an uneven distribution of COPD phenotypes in stable COPD patients, with significant differences in demographics, patient-centered outcomes and health care resources use

    New GOLD classification: longitudinal data on group assignment

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    Rationale: Little is known about the longitudinal changes associated with using the 2013 update of the multidimensional GOLD strategy for chronic obstructive pulmonary disease (COPD). Objective: To determine the COPD patient distribution of the new GOLD proposal and evaluate how this classification changes over one year compared with the previous GOLD staging based on spirometry only. Methods: We analyzed data from the CHAIN study, a multicenter observational Spanish cohort of COPD patients who are monitored annually. Categories were defined according to the proposed GOLD: FEV1%, mMRC dyspnea, COPD Assessment Test (CAT), Clinical COPD Questionnaire (CCQ), and exacerbations-hospitalizations. One-year follow-up information was available for all variables except CCQ data. Results: At baseline, 828 stable COPD patients were evaluated. On the basis of mMRC dyspnea versus CAT, the patients were distributed as follows: 38.2% vs. 27.2% in group A, 17.6% vs. 28.3% in group B, 15.8% vs. 12.9% in group C, and 28.4% vs. 31.6% in group D. Information was available for 526 patients at one year: 64.2% of patients remained in the same group but groups C and D show different degrees of variability. The annual progression by group was mainly associated with one-year changes in CAT scores (RR, 1.138; 95%CI: 1.074-1.206) and BODE index values (RR, 2.012; 95%CI: 1.487-2.722). Conclusions: In the new GOLD grading classification, the type of tool used to determine the level of symptoms can substantially alter the group assignment. A change in category after one year was associated with longitudinal changes in the CAT and BODE index

    New GOLD classification: Longitudinal data on group assignment

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    Rationale: Little is known about the longitudinal changes associated with using the 2013 update of the multidimensional GOLD strategy for chronic obstructive pulmonary disease (COPD). Objective: To determine the COPD patient distribution of the new GOLD proposal and evaluate how this classification changes over one year compared with the previous GOLD staging based on spirometry only. Methods: We analyzed data from the CHAIN study, a multicenter observational Spanish cohort of COPD patients who are monitored annually. Categories were defined according to the proposed GOLD: FEV1%, mMRC dyspnea, COPD Assessment Test (CAT), Clinical COPD Questionnaire (CCQ), and exacerbations-hospitalizations. One-year follow-up information was available for all variables except CCQ data. Results: At baseline, 828 stable COPD patients were evaluated. On the basis of mMRC dyspnea versus CAT, the patients were distributed as follows: 38.2% vs. 27.2% in group A, 17.6% vs. 28.3% in group B, 15.8% vs. 12.9% in group C, and 28.4% vs. 31.6% in group D. Information was available for 526 patients at one year: 64.2% of patients remained in the same group but groups C and D show different degrees of variability. The annual progression by group was mainly associated with one-year changes in CAT scores (RR, 1.138; 95%CI: 1.074-1.206) and BODE index values (RR, 2.012; 95%CI: 1.487-2.722). Conclusions: In the new GOLD grading classification, the type of tool used to determine the level of symptoms can substantially alter the group assignment. A change in category after one year was associated with longitudinal changes in the CAT and BODE index

    A strategy to incorporate prior knowledge into correlation network cutoff selection

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    Correlation networks are frequently used to statistically extract biological interactions between omics markers. Network edge selection is typically based on the statistical significance of the correlation coefficients. This procedure, however, is not guaranteed to capture biological mechanisms. We here propose an alternative approach for network reconstruction: a cutoff selection algorithm that maximizes the overlap of the inferred network with available prior knowledge. We first evaluate the approach on IgG glycomics data, for which the biochemical pathway is known and well-characterized. Importantly, even in the case of incomplete or incorrect prior knowledge, the optimal network is close to the true optimum. We then demonstrate the generalizability of the approach with applications to untargeted metabolomics and transcriptomics data. For the transcriptomics case, we demonstrate that the optimized network is superior to statistical networks in systematically retrieving interactions that were not included in the biological reference used for optimization

    Distinct Peripheral Blood RNA Responses to Salmonella in Pigs Differing in Salmonella Shedding Levels: Intersection of IFNG, TLR and miRNA Pathways

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    Transcriptomic analysis of the response to bacterial pathogens has been reported for several species, yet few studies have investigated the transcriptional differences in whole blood in subjects that differ in their disease response phenotypes. Salmonella species infect many vertebrate species, and pigs colonized with Salmonella enterica serovar Typhimurium (ST) are usually asymptomatic, making detection of these Salmonella-carrier pigs difficult. The variable fecal shedding of Salmonella is an important cause of foodborne illness and zoonotic disease. To investigate gene pathways and biomarkers associated with the variance in Salmonella shedding following experimental inoculation, we initiated the first analysis of the whole blood transcriptional response induced by Salmonella. A population of pigs (n = 40) was inoculated with ST and peripheral blood and fecal Salmonella counts were collected between 2 and 20 days post-inoculation (dpi). Two groups of pigs with either low shedding (LS) or persistent shedding (PS) phenotypes were identified. Global transcriptional changes in response to ST inoculation were identified by Affymetrix Genechip® analysis of peripheral blood RNA at day 0 and 2 dpi. ST inoculation triggered substantial gene expression changes in the pigs and there was differential expression of many genes between LS and PS pigs. Analysis of the differential profiles of gene expression within and between PS and LS phenotypic classes identified distinct regulatory pathways mediated by IFN-γ, TNF, NF-κB, or one of several miRNAs. We confirmed the activation of two regulatory factors, SPI1 and CEBPB, and demonstrated that expression of miR-155 was decreased specifically in the PS animals. These data provide insight into specific pathways associated with extremes in Salmonella fecal shedding that can be targeted for further exploration on why some animals develop a carrier state. This knowledge can also be used to develop rational manipulations of genetics, pharmaceuticals, nutrition or husbandry methods to decrease Salmonella colonization, shedding and spread

    Challenges for Sustained Observing and Forecasting Systems in the Mediterranean Sea

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    The Mediterranean community represented in this paper is the result of more than 30 years of EU and nationally funded coordination, which has led to key contributions in science concepts and operational initiatives. Together with the establishment of operational services, the community has coordinated with universities, research centers, research infrastructures and private companies to implement advanced multi-platform and integrated observing and forecasting systems that facilitate the advancement of operational services, scientific achievements and mission-oriented innovation. Thus, the community can respond to societal challenges and stakeholders needs, developing a variety of fit-for-purpose services such as the Copernicus Marine Service. The combination of state-of-the-art observations and forecasting provides new opportunities for downstream services in response to the needs of the heavily populated Mediterranean coastal areas and to climate change. The challenge over the next decade is to sustain ocean observations within the research community, to monitor the variability at small scales, e.g., the mesoscale/submesoscale, to resolve the sub-basin/seasonal and inter-annual variability in the circulation, and thus establish the decadal variability, understand and correct the model-associated biases and to enhance model-data integration and ensemble forecasting for uncertainty estimation. Better knowledge and understanding of the level of Mediterranean variability will enable a subsequent evaluation of the impacts and mitigation of the effect of human activities and climate change on the biodiversity and the ecosystem, which will support environmental assessments and decisions. Further challenges include extending the science-based added-value products into societal relevant downstream services and engaging with communities to build initiatives that will contribute to the 2030 Agenda and more specifically to SDG14 and the UN's Decade of Ocean Science for sustainable development, by this contributing to bridge the science-policy gap. The Mediterranean observing and forecasting capacity was built on the basis of community best practices in monitoring and modeling, and can serve as a basis for the development of an integrated global ocean observing system
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