22 research outputs found
Protocol for an observational study to identify potential predictors of an acute exacerbation in patients with chronic obstructive pulmonary disease (the PACE Study).
INTRODUCTION: Acute exacerbations of chronic obstructive pulmonary disease (AECOPD) are the most critical events for patients with COPD that have a negative impact on patients' quality of life, accelerate disease progression, and can result in hospital admissions and death. Although there is no distinct definition or detailed knowledge about AECOPD, it is commonly used as primary outcome in clinical studies. Furthermore, it may be difficult in clinical practice to differentiate the worsening of symptoms due to an AECOPD or to the development of heart failure. Therefore, it is of major clinical importance to investigate the underlying pathophysiology, and if possible, predictors of an AECOPD and thus to identify patients who are at high risk for developing an acute exacerbation. METHODS AND ANALYSIS: In total, 355 patients with COPD will be included prospectively to this study during a 3-week inpatient pulmonary rehabilitation programme at the Schoen Klinik Berchtesgadener Land, Schoenau am Koenigssee (Germany). All patients will be closely monitored from admission to discharge. Lung function, exercise tests, clinical parameters, quality of life, physical activity and symptoms will be recorded, and blood samples and exhaled air will be collected. If a patient develops an AECOPD, there will be additional comprehensive diagnostic assessments to differentiate between cardiac, pulmonary or cardiopulmonary causes of worsening. Follow-up measures will be performed at 6, 12 and 24 months.Exploratory data analyses methods will be used for the primary research question (screening and identification of possible factors to predict an AECOPD). Regression analyses and a generalised linear model with a binomial outcome (AECOPD) will be applied to test if predictors are significant. ETHICS AND DISSEMINATION: This study has been approved by the Ethical Committee of the Philipps University Marburg, Germany (No. 61/19). The results will be presented in conferences and published in a peer-reviewed journal. TRIAL REGISTRATION NUMBER: NCT04140097
Inhibition of the interactions between eosinophil cationic protein and airway epithelial cells by traditional Chinese herbs
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Tracer Modeling in an Urban Environment
The accurate simulation of the transport of a tracer released into an urban area requires sufficiently high model resolution to resolve buildings and urban street canyons. Within the authors' group a modeling effort has been underway to develop a model -- termed HIGRAD -- capable of simulating flow at the high spatial resolution required within the urban environment. HIGRAD uses state-of-the-art numerical techniques to accurately simulate the regions of strong shear found near edges of buildings. HIGRAD also employs a newly developed radiation package which in addition to standard shortwave and longwave heating/cooling effects can account for the shadowing effects of building complexes on the urban flow field. Idealized simulations have been conducted which clearly illustrate the role radiation plays in transport and dispersion in an urban setting. The authors have also modeled the flow of an inert tracer in a realistic, complex urban environment. Complex flow/building interactions were produced during the simulation and these interactions had a significant impact on the transport of the tracer
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Regional-scale simulations of the western US climate
Over the past two decades the meteorological community has witnessed the evolution of general circulation models (GCMs) from studies attempting to simulate realistic large-scale dynamical regimes and energy transports to present investigations examining future climate change scenarios. From these pioneering studies, we were inspired to begin to develop regional climatologies with the Colorado State University Regional Atmospheric Modeling System (CSU-RAMS). Our major goal is to develop a better understanding of the hydrologic cycle in the mountainous, and west. An advantage of using the RAMS code is that we can generate detailed descriptions of precipitation processes, which will hopefully translate into realistic surface yields of both rain and snow. In the ensuing sections, we first describe the model and its microphysics parameterizations, then continue with our methodology for incorporating large-scale data into the model grid. Preliminary results demonstrating the mesoscale variation of precipitation over the mountainous western US are then presented