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

Prenatal exposures and exposomics of asthma

This review examines the causal investigation of preclinical development of childhood asthma using exposomic tools. We examine the current state of knowledge regarding early-life exposure to non-biogenic indoor air pollution and the developmental modulation of the immune system. We examine how metabolomics technologies could aid not only in the biomarker identification of a particular asthma phenotype, but also the mechanisms underlying the immunopathologic process. Within such a framework, we propose alternate components of exposomic investigation of asthma in which, the exposome represents a reiterative investigative process of targeted biomarker identification, validation through computational systems biology and physical sampling of environmental medi

A framework for user equilibrium dynamic traffic assignment

Several analytic approaches have been developed to describe or predict traffic flows on networks with timevarying (dynamic) travel demands, flows and travel times. A key component of these models lies in modelling the flows and/or travel times on the individual links, but as this is made more realistic or accurate it tends to make the overall model less computationally tractable. To help overcome this, and for other reasons, we develop a bi-level user equilibrium (UE) framework that separates the assignment or loading of flows on the time–space network from the modelling of flows and trip times within individual links. We show that this model or framework satisfies appropriate definitions of UE satisfies a first-in-first-out (FIFO) property of road traffic, and has other desirable properties. The model can be solved by iterating between (a) a linear networkloading model that takes the lengths of time–space links as fixed (within narrow ranges), and (b) a set of link flow sub-models which update the link trip times to construct a new time–space network. This allows links to be processed sequentially or in parallel and avoids having to enumerate paths and compute path flows or travel times. We test and demonstrate the model and algorithms using example networks and find that the algorithm converges quickly and the solutions behave as expected. We show how to extend the model to handle elastic demands, multiple destinations and multiple traffic types, and traffic spillback within links and from link to link

Maternal age at delivery, lung function and asthma in offspring: a population-based survey

There is limited information about potential impact of maternal age on the respiratory health of offspring. We investigated the association of maternal age at delivery with adult offspring's lung function, respiratory symptoms and asthma, and potential differences according to offspring sex. 10 692 adults from 13 countries participating in the European Community Respiratory Health Survey (ECRHS) II responded to standardised interviews and provided lung function measurements and serum for IgE measurements at age 25–55 years. In logistic and linear multilevel mixed models we adjusted for participants’ characteristics (age, education, centre, number of older siblings) and maternal characteristics (smoking in pregnancy, education) while investigating for differential effects by sex. Maternal age was validated in a subsample using data from the Norwegian birth registry. Increasing maternal age was associated with increasing forced expiratory volume in 1 s (2.33 mL per year, 95% CI 0.34–4.32 mL per year), more consistent in females (ptrend 0.025) than in males (ptrend 0.14). Asthma (OR 0.85, 95% CI 0.79–0.92) and respiratory symptoms (OR 0.87, 95% CI 0.82–0.92) decreased with increasing maternal age (per 5 years) in females, but not in males (pinteraction 0.05 and 0.001, respectively). The results were consistent across centres and not explained by confounding factors. Maternal ageing was related to higher adult lung function and less asthma/symptoms in females. Biological characteristics in offspring related to maternal ageing are plausible and need further investigation

A dynamic user equilibrium model for traffic assignment in urban areas

info:eu-repo/semantics/publishe