Methods: An Iranian population, 400 adults aged over 22 years were selected from the Iranian Multicenter Osteoporosis Study (IMOS). Genotyping for the near MC4R rs17782313 was performed by PCR-RFLP. Weight and height were measured. Dietary intake and physical activity were assessed by using validated questionnaires. Analysis was carried out in two groups with regard to BMI. Multiple linear regression models adjusted for covariates were used to examine the association between rs17782313 and dietary intake. Results: MC4R rs17782313 was associated with high energy intake (P smaller than 0.001), and BVD-523 inhibitor low carbohydrate and protein intakes

(P smaller than 0.001 and P smaller than 0.01 respectively). In Savolitinib addition, the significant association between variant rs17782313 and fat intake disappeared after adjusting for energy. Conclusions: The rs17782313 variant contributes to the variety of dietary energy and energy-dense macronutrient intakes. Moreover, a novel association was suggested between this polymorphism and dietary fat intake. (C) 2015 Elsevier B.V. All rights reserved.”
“There is a need to develop multiscale models of vascular adaptations to understand tissue-level

manifestations of cellular level mechanisms. Continuum-based biomechanical models are well suited for relating blood pressures and flows to stress-mediated changes in geometry and properties, but less so for describing underlying mechanobiological processes. Discrete stochastic agent-based models are well suited for representing biological processes at a cellular level, but not for describing tissue-level mechanical changes. We present here PD98059 datasheet a conceptually new approach to facilitate

the coupling of continuum and agent-based models. Because of ubiquitous limitations in both the tissue-and cell-level data from which one derives constitutive relations for continuum models and rule-sets for agent-based models, we suggest that model verification should enforce congruency across scales. That is, multiscale model parameters initially determined from data sets representing different scales should be refined, when possible, to ensure that common outputs are consistent. Potential advantages of this approach are illustrated by comparing simulated aortic responses to a sustained increase in blood pressure predicted by continuum and agent-based models both before and after instituting a genetic algorithm to refine 16 objectively bounded model parameters. We show that congruency-based parameter refinement not only yielded increased consistency across scales, it also yielded predictions that are closer to in vivo observations.”
“Background: The treatment of molar furcation defects remains a considerable challenge in clinical practice.