Examinando por Autor "Castro, C."

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  • Miniatura
    ÍtemAcceso Abierto
    Adiponectin, leptin and TNF-α serum levels in obese and normal weight peruvian adults with and without chronic periodontitis
    (Medicina Oral S.L., 2015) Mendoza-Azpur, G.; Castro, C.; Peña, L.; Guerrero, M.-E.; de la Rosa, M.; Mendes, C.; Chambrone, L.
    Background: TNF-α, an adipokine involved in systemic inflammation and a member of a group of cytokines that stimulate the acute phase reaction, has been related to the pathogenesis of both periodontitis and obesity. The objective of this study was to assess the serum levels of adiponectin, leptin and TNF-α of periodontally healthy normal weight (NW) patients, NW patients with chronic periodontitis (CP), periodontally healthy obese patients and obese patients with CP. Material and Methods: Ninety-three patients were enrolled in this cross-sectional study: 30 periodontally healthy NW patients; 18 NW patients with CP; 21 periodontally healthy obese patients; and 24 obese patients with CP. Analyses included clinical and anthropometric outcomes, as well as the assessment of serum levels of adiponectin, leptin and TNF-α by enzyme linked immunosorbent assay (ELISA) or fully automated chemiluminescence immunoassay. One-Way ANOVA, Kruskal-Wallis One-Way on Ranks, Dunn's Test and multivariable logistic regression (MLR) analyses were conducted to estimate the degree of association between periodontitis and obesity. Results: Obese patients with CP showed significant more bleeding sites than the other three groups (p<0.05). Moreover, patients from the NWCP and OPH showed similar BOP percentages, as well as OPH group showed more bleeding sites than the NWPH group (p<0.05). The OPH group showed similar levels of adiponectin and leptin than the OCP group, but significantly higher than the NWPH and NWCP groups(p<0.05). MLR analyses showed that obesity was positively associated with the percentage of sites with bleeding on probing, with an odds ratio of 0.93 (95% confidence interval: -0.88, - 0.98; p=0.012). Conclusions: The serum levels of adiponectin, leptin and TNF-α were not influenced by CP. Obese patients showed almost 10% more sites with BoP. In chronic periodontitis patients, obese subjects presented significant more BOP sites than normal weight subjects. © Medicina Oral S. L. C.I.F.
  • Miniatura
    ÍtemAcceso Abierto
    Using autonomous search for solving constraint satisfaction problems via new modern approaches
    (Elsevier, 2016) Soto, R.; Crawford, B.; Olivares, R.; Galleguillos, C.; Castro, C.; Johnson, F.; Paredes, F.; Norero, E.
    Constraint Programming is a powerful paradigm which allows the resolution of many complex problems, such as scheduling, planning, and configuration. These problems are defined by a set of variables and a set of constraints. Each variable has non-empty domain of possible value and each constraint involves some subset of the variables and specifies the allowable combinations of values for that subset. The resolution of these problems is carried out by a constraint satisfaction solver which explores a search tree of potential solutions. This exploration is controlled by the enumeration strategy, which is responsible for choosing the order in which variables and values are selected to generate the potential solution. There exist different ways to perform this selection, and depending on the quality of this decision, the efficiency of the solving process may dramatically vary. Autonomous search is a particular case of adaptive systems that aims at improving its solving performance by adapting itself to the problem at hand without manual configuration of an expert user. The goal is to improve their solving performance by modifying and adjusting themselves, either by self-adaptation or by supervised adaptation. This approach has been effectively applied to different optimization and satisfaction techniques such as constraint programming, metaheuristics, and SAT. In this paper, we present a new Autonomous Search approach for constraint programming based on four modern bio-inspired metaheuristics. The goal of those metaheuristics is to optimize the self-tuning phase of the constraint programming search process. We illustrate promising results, where the proposed approach is able to efficiently solve several well-known constraint satisfaction problems. © 2016 Elsevier B.V.