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“Asthma is a chronic inflammatory disease that affects about 300 million people worldwide, a total that is expected to rise to about 400 million over the next 15-20 years. Most asthmatic individuals respond well to the currently available treatments of inhaled corticosteroids and beta-adrenergic SRT1720 nmr agonists; however, 5-10% have severe disease that responds

poorly. Improved knowledge of asthma mechanisms has led to the recognition of different asthma phenotypes that might reflect distinct types of inflammation, explaining the effectiveness of anti-leucotrienes and the anti-IgE monoclonal antibody omalizumab in some patients. However, more knowledge of the inflammatory mechanisms within the airways is required. Improvements in available

therapies-such as the development of BAY 11-7082 solubility dmso fast-onset, once-a-day combination drugs with better safety profiles-will occur. Other drugs, such as inhaled p38 MAPK inhibitors and anti-oxidants, that target specific pathways or mediators could prove useful as monotherapies, but could also, in combination with corticosteroids, reduce the corticosteroid insensitivity often seen in severe asthma. Biological agents directed against the interleukin-13 pathway and new immunoregulatory agents that modulate functions of T-regulatory and T-helper-17 cells are likely to be successful. Patient-specific treatments will depend on the development of discriminatory handprints of distinct asthma subtypes and are probably over the horizon. Although a cure is unlikely to be developed in the near future, a greater understanding of disease mechanisms could bring such a situation nearer to reality.”
“Although assessment of asthma control is important to guide treatment, it is difficult since the temporal pattern and risk of exacerbations are often

unpredictable. In this Review, we summarise the classic methods to assess control with unidimensional and Succinyl-CoA multidimensional approaches. Next, we show how ideas from the science of complexity can explain the seemingly unpredictable nature of bronchial asthma and emphysema, with implications for chronic obstructive pulmonary disease. We show that fluctuation analysis, a method used in statistical physics, can be used to gain insight into asthma as a dynamic disease of the respiratory system, viewed as a set of interacting subsystems (eg, inflammatory, immunological, and mechanical). The basis of the fluctuation analysis methods is the quantification of the long-term temporal history of lung function parameters. We summarise how this analysis can be used to assess the risk of future asthma episodes, with implications for asthma severity and control both in children and adults.