132 research outputs found

    Are turbulent spheres suitable initial conditions for star-forming clouds?

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    To date, most numerical simulations of molecular clouds, and star formation within them, assume a uniform density sphere or box with an imposed turbulent velocity field. In this work, we select molecular clouds from galactic scale simulations as initial conditions, increase their resolution, and re-simulate them using the smoothed particle hydrodynamics code GADGET2. Our approach provides clouds with morphologies, internal structures and kinematics that constitute more consistent and realistic initial conditions for simulations of star formation. We perform comparisons between molecular clouds derived from a galactic simulation, and spheres of turbulent gas of similar dimensions, mass and velocity dispersion. We focus on properties of the clouds such as their density, velocity structure and star formation rate. We find that the inherited velocity structure of the galactic clouds has a significant impact on the star formation rate and evolution of the cloud. Our results indicate that, although we can follow the time evolution of star formation in any simulated cloud, capturing the entire history is difficult as we ignore any star formation that might have occurred before initialization. Overall, the turbulent spheres do not match the complexity of the galactic clouds

    Supercritical fluid technology as a tool to prepare gradient multifunctional architectures towards regeneration of osteochondral injuries

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    Platelet lysates (PLs) are a natural source of growth factors (GFs) known for its stimulatory role on stem cells which can be obtained after activation of platelets from blood plasma. The possibility to use PLs as growth factor source for tissue healing and regeneration has been pursued following different strategies. Platelet lysates are an enriched pool of growth factors which can be used as either a GFs source or as a three-dimensional (3D) hydrogel. However, most of current PLs-based hydrogels lack stability, exhibiting significant shrinking behavior. This chapter focuses on the application of supercritical fluid technology to develop three-dimensional architectures of PL constructs, crosslinked with genipin. The proposed technology allows in a single step operation the development of mechanically stable porous structures, through chemical crosslinking of the growth factors present in the PL pool, followed by supercritical drying of the samples. Furthermore gradient structures of PL-based structures with bioactive glass are also presented and are described as an interesting approach to the treatment of osteochondral defects.info:eu-repo/semantics/publishedVersio

    Goedel-type Universes and the Landau Problem

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    We point out a close relation between a family of Goedel-type solutions of 3+1 General Relativity and the Landau problem in S^2, R^2 and H_2; in particular, the classical geodesics correspond to Larmor orbits in the Landau problem. We discuss the extent of this relation, by analyzing the solutions of the Klein-Gordon equation in these backgrounds. For the R^2 case, this relation was independently noticed in hep-th/0306148. Guided by the analogy with the Landau problem, we speculate on the possible holographic description of a single chronologically safe region.Comment: Latex, 21 pages, 1 figure. v2 missing references to previous work on the subject adde

    Whole-genome sequencing to determine origin of multinational outbreak of Sarocladium kiliense bloodstream infections

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    We used whole-genome sequence typing (WGST) to investigate an outbreak of Sarocladium kiliense bloodstream infections (BSI) associated with receipt of contaminated antinausea medication among oncology patients in Colombia and Chile during 2013-2014. Twenty-five outbreak isolates (18 from patients and 7 from medication vials) and 11 control isolates unrelated to this outbreak were subjected to WGST to elucidate a source of infection. All outbreak isolates were nearly indistinguishable (≀5 single-nucleotide polymorphisms), and >21,000 single-nucleotide polymorphisms were identified from unrelated control isolates, suggesting a point source for this outbreak. S. kiliense has been previously implicated in healthcare-related infections; however, the lack of available typing methods has precluded the ability to substantiate point sources. WGST for outbreak investigation caused by eukaryotic pathogens without reference genomes or existing genotyping methods enables accurate source identification to guide implementation of appropriate control and prevention measures. © 2016, Centers for Disease Control and Prevention (CDC). All rights reserved

    No silver bullet for digital soil mapping: country-specific soil organic carbon estimates across Latin America.

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    Country-specific soil organic carbon (SOC) estimates are the baseline for the Global SOC Map of the Global Soil Partnership (GSOCmap-GSP). This endeavor is key to explaining the uncertainty of global SOC estimates but requires harmonizing heterogeneous datasets and building country-specific capacities for digital soil mapping (DSM).We identified country-specific predictors for SOC and tested the performance of five predictive algorithms for mapping SOC across Latin America. The algorithms included support vector machines (SVMs), random forest (RF), kernel-weighted nearest neighbors (KK), partial least squares regression (PL), and regression kriging based on stepwise multiple linear models (RK). Country-specific training data and SOC predictors (5 x 5 km pixel resolution) were obtained from ISRIC - World Soil Information. Temperature, soil type, vegetation indices, and topographic constraints were the best predictors for SOC, but country-specific predictors and their respective weights varied across Latin America. We compared a large diversity of country-specific datasets and models, and were able to explain SOC variability in a range between ~ 1 and ~ 60 %, with no universal predictive algorithm among countries. A regional (n = 11 268 SOC estimates) ensemble of these five algorithms was able to explain ~ 39% of SOC variability from repeated 5-fold cross-validation.We report a combined SOC stock of 77.8 +- 43.6 Pg (uncertainty represented by the full conditional response of independent model residuals) across Latin America. SOC stocks were higher in tropical forests (30 +- 16.5 Pg) and croplands (13 +- 8.1 Pg). Country-specific and regional ensembles revealed spatial discrepancies across geopolitical borders, higher elevations, and coastal plains, but provided similar regional stocks (77.8 +- 42.2 and 76.8 +- 45.1 Pg, respectively). These results are conservative compared to global estimates (e.g., SoilGrids250m 185.8 Pg, the Harmonized World Soil Database 138.4 Pg, or the GSOCmap-GSP 99.7 Pg). Countries with large area (i.e., Brazil, Bolivia, Mexico, Peru) and large spatial SOC heterogeneity had lower SOC stocks per unit area and larger uncertainty in their predictions. We highlight that expert opinion is needed to set boundary prediction limits to avoid unrealistically high modeling estimates. For maximizing explained variance while minimizing prediction bias, the selection of predictive algorithms for SOC mapping should consider density of available data and variability of country-specific environmental gradients. This study highlights the large degree of spatial uncertainty in SOC estimates across Latin America. We provide a framework for improving country-specific mapping efforts and reducing current discrepancy of global, regional, and country-specific SOC estimates

    Association between HLA-DRB1 alleles polymorphism and hepatocellular carcinoma: a meta-analysis

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    <p>Abstract</p> <p>Background</p> <p>HLA-DRB1 allele polymorphisms have been reported to be associated with hepatocellular carcinoma susceptibility, but the results of these previous studies have been inconsistent. The purpose of the present study was to explore whether specific HLA-DRB1 alleles (DRB1*07, DRB1*12, DRB1*15) confer susceptibility to hepatocellular carcinoma.</p> <p>Methods</p> <p>Case-control studies on HLA-DRB1 alleles association with HCC were searched up to January 2010 through a systematic review of the literature. The odds ratios (ORs) of HLA-DRB1 allele distributions in patients with hepatocellular carcinoma were analyzed against healthy controls. The meta-analysis software REVMAN 5.0 was applied for investigating heterogeneity among individual studies and for summarizing all the studies. Meta-analysis was performed using fixed-effect or random-effect methods, depending on absence or presence of significant heterogeneity.</p> <p>Results</p> <p>Eight case-control studies were included in the final analysis. Among the 3 HLA-DRB1 alleles studied, DRB1*07 and DRB1*12 were significantly associated with the risk of HCC in the whole populations (OR = 1.65, 95% CI: 1.08-2.51, P = 0.02 and OR = 1.59, 95% CI: 1.09-2.32, P = 0.02, respectively). No significant association was established for DRB1*15 allele with HCC in the whole populations. Subgroup analysis by ethnicity showed that DRB1*07, DRB1*12 and DRB1*15 alleles significantly increased the risk of hepatocellular carcinoma in Asians (OR = 2.10, 95% CI: 1.06-4.14, P = 0.03; OR = 1.73, 95% CI: 1.17-2.57, P = 0.006 and <b><it>OR </it></b>= 2.88, <it><b>95%CI: 1</b></it>.77-4.69, P <<it><b>0.001</b></it>, respectively).</p> <p>Conclusion</p> <p>These results support the hypothesis that specific HLA-DRB1 alleles might influence the susceptibility of hepatocellular carcinoma. Large, multi-ethnic confirmatory and well designed studies are needed to determine the host genetic determinants of hepatocellular carcinoma.</p

    External validation of multidimensional prognostic indices (ADO, BODEx and DOSE) in a primary care international cohort (PROEPOC/COPD cohort)

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    Background: Due to the heterogeneous and systemic nature of the chronic obstructive pulmonary disease (COPD), the new guidelines are oriented toward individualized attention. Multidimensional scales could facilitate its proper clinical and prognostic assessment, but not all of them were validated in an international primary care cohort, different from the original ones used for model development. Therefore, our main aim is to assess the prognostic capacity of the ADO, BODEx and DOSE indices in primary care for predicting mortality in COPD patients and to validate the models obtained in subgroups of patients, classified by revised Global Initiative for Chronic Obstructive Lung Disease (2011) and updated Spanish Guideline (2014). Besides, we want to confirm that the prognostic capacity of all indices increases if the number of exacerbations is substituted by the interval between them and to assess the impact on health of the patient''s lifestyle, social network and adherence to treatment. Methods: Design: External validation of scales, open and prospective cohort study in primary care. Setting: 36 health centres in 6 European high, medium and low income countries. Subjects: 477 patients diagnosed with COPD, captured in clinical visit by their General Practitioner/Nurse. Predictors: Detailed patient history, exacerbations, lung function test and questionnaires at baseline. Outcomes: Exacerbations, all-cause mortality and specific mortality, within 5 years of recruitment. Analysis: Multivariate logistic regression and Cox regression will be used. Possible non-linear effect of the indices will be studied by using Structured Additive Regression models with penalised splines. Subsequently, we will assess different aspects of the regression models: discrimination, calibration and diagnostic precision. Clinical variables modulated in primary care and the interval between exacerbations will be considered and incorporated into the analysis. Discussion: The Research Agenda for General Practice/Family Medicine highlights that the evidence on predictive values of prognostic indices in primary care is scarce. A prospective cohort like that of PROEPOC/COPD provides good opportunities for research into COPD and make communication easier between family practitioners, nursing staff, pneumologists and other professionals, supporting a multi-disciplinary approach to the treatment of these patients. Trial registration:ISRCTN52402811. Date: 15/01/2015. Prospectively registered

    Improved functionalization of oleic acid-coated iron oxide nanoparticles for biomedical applications

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    Superparamagnetic iron oxide nanoparticles can providemultiple benefits for biomedical applications in aqueous environments such asmagnetic separation or magnetic resonance imaging. To increase the colloidal stability and allow subsequent reactions, the introduction of hydrophilic functional groups onto the particles’ surface is essential. During this process, the original coating is exchanged by preferably covalently bonded ligands such as trialkoxysilanes. The duration of the silane exchange reaction, which commonly takes more than 24 h, is an important drawback for this approach. In this paper, we present a novel method, which introduces ultrasonication as an energy source to dramatically accelerate this process, resulting in high-quality waterdispersible nanoparticles around 10 nmin size. To prove the generic character, different functional groups were introduced on the surface including polyethylene glycol chains, carboxylic acid, amine, and thiol groups. Their colloidal stability in various aqueous buffer solutions as well as human plasma and serum was investigated to allow implementation in biomedical and sensing applications.status: publishe
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