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The effect of social network structure on team performance is difficult to investigate using standard field observational studies. This is because social network structure is an endogeneous variable, in that prior team performance can influence the values of structural measures such as centrality and connectedness. In this work we propose a novel simulation model based on agent-based modeling that allows social network structure to be treated as an exogeneous variable but still be allowed to evolve over time. The simulation model consists of experiments with multiple runs in each experiment. The social network amongst the agents is allowed to evolve between runs based on past performance. However, within each run, the social network is treated as an exogenous variable where it directly affects workflow performance. The simulation model we describe has several inputs and parameters that increase its validity, including a realistic workflow management depiction and real-world cognitive strategies by the agents.
Inflammatory lung diseases such as asthma and chronic obstructive pulmonary disease are common and difficult to diagnose and characterize. This is due in large part to difficulty in obtaining samples directly from the inflamed lung. The collection of lung secretions by traditional methods including bronchoalveolar lavage and induced sputum collection are limited by their invasive nature. Exhaled breath condensate (EBC) is a simple and non-invasive technique of collecting fluid samples, which are representative of airway lining fluid. Advances in collection methods and evolving molecular techniques have led to development of more sensitive assays for existing biomarkers and identification of new biomarkers, which can be potentially useful in monitoring lung inflammation. In this review, we present the current understanding of various biomarkers including small molecules (H2O2, pH and nitric oxide related biomarkers), lipid mediators (8-isprostane, leukotrienes and prostaglandins), small proteins (cytokines and chemokines) and nucleic acids (DNA and microRNAs). We also discuss the differential profile of biomarkers in recognizing different patterns of lung inflammation. As the sensitivity of methods of EBC improves, this biofluid will play an increasing role in diagnosis and monitoring of lung diseases.