Mouse models to unravel the role of inhaled pollutants on allergic sensitization and airway inflammation

Air pollutant exposure has been linked to a rise in wheezing illnesses. Clinical data highlight that exposure to mainstream tobacco smoke (MS) and environmental tobacco smoke (ETS) as well as exposure to diesel exhaust particles (DEP) could promote allergic sensitization or aggravate symptoms of asthma, suggesting a role for these inhaled pollutants in the pathogenesis of asthma. Mouse models are a valuable tool to study the potential effects of these pollutants in the pathogenesis of asthma, with the opportunity to investigate their impact during processes leading to sensitization, acute inflammation and chronic disease. Mice allow us to perform mechanistic studies and to evaluate the importance of specific cell types in asthma pathogenesis. In this review, the major clinical effects of tobacco smoke and diesel exhaust exposure regarding to asthma development and progression are described. Clinical data are compared with findings from murine models of asthma and inhalable pollutant exposure. Moreover, the potential mechanisms by which both pollutants could aggravate asthma are discussed

Data from: Metadata capital in a data repository

This paper reports on a study exploring ‘metadata capital’ acquired via metadata reuse. Collaborative modeling and content analysis methods were used to study metadata capital in the Dryad data repository. A sample of 20 cases for two Dryad metadata workflows (Case A and Case B) consisting of 100 instantiations (60 metadata objects, 40 metadata activities) was analyzed. Results indicate that Dryad’s overall workflow builds metadata capital, with the total metadata reuse at 50% or greater for 8 of 12 metadata properties, and 5 of these 8 properties showing reuse at 80% or higher. Metadata reuse is frequent for basic bibliographic properties (e.g., author, title, subject), although it is limited or absent for more complex scientific properties (e.g., taxon, spatial, and temporal information). This paper provides background context, reports the research approach and findings, and considers research implications and system design priorities that may contribute to metadata capital—long term

Sociological Perspective: Underlying Causes

In this chapter, we use theory and research from sociology to better understand the complex ways that political, economic, and other sociocultural factors interact within and across country borders to cause human trafficking. First, we discuss how sociologists approach the study of social problems and phenomenon using a sociological imagination, including macrosociological and microsociological perspectives. We then illustrate how using one’s sociological imagination, and the macro- and micro-sociological perspectives, can inform our understanding of human trafficking. Using these analytical approaches, we present key sociological terms and apply these terms to the phenomenon of trafficking. Finally, we illustrate how applying sociological knowledge to trafficking can inform policies and practices established to eradicate this horrible crime

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Data showing metadata reuse in Dryad for Case A, during phase 2

figure_2_phase_1_case_a

Data showing metadata reuse in Dryad for Case A, during phase 1

figure_3_phase_2_case_b

Data showing metadata reuse in Dryad for Case B, during phase 2

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Data showing metadata reuse in Dryad for Case B, during phase 1