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Purpose: Bronchial thermoplasty (BT) is a bronchoscopic intervention for the treatment of severe asthma. Despite demonstrated symptomatic benefit, the underlying mechanisms by which this is achieved remain uncertain. We hypothesize that the effects of BT are driven by improvements in ventilation heterogeneity as assessed using functional respiratory imaging (FRI). Patient and Methods: Eighteen consecutive patients with severe asthma who underwent clinically indicated BT were recruited. Patients were assessed at baseline, 4-week after treatment of the left lung, and 12-month after treatment of the right lung. Data collected included short-acting beta-agonist (SABA) and oral prednisolone (OCS) use, asthma control questionnaire (ACQ-5) and exacerbation history. Patients also underwent lung function tests and chest computed tomography. Ventilation parameters including interquartile distance (IQD; measure of ventilation heterogeneity) were derived using FRI. Results: 12 months after BT, significant improvements were seen in SABA and OCS use, ACQ-5, and number of OCS-requiring exacerbations. Apart from pre-bronchodilator FEV1, no other significant changes were observed in lung function. Ventilation heterogeneity significantly improved after treatment of the left lung (0.18 ± 0.04 vs 0.20 ± 0.04, p=0.045), with treatment effect persisting up to 12 months later (0.18 ± 0.05 vs 0.20 ± 0.04, p=0.028). Ventilation heterogeneity also improved after treatment of the right lung, although this did not reach statistical significance (0.18 ± 0.05 vs 0.19 ± 0.04, p=0.06). Conclusion: Clinical benefits after BT are accompanied by improvements in ventilation heterogeneity, advancing our understanding of its mechanism of action. Beyond BT, FRI has the potential to be expanded into other clinical applications. [ABSTRACT FROM AUTHOR]

Structure–function relationships occur throughout the sciences. Motivated by optimization of such systems, we develop a framework for estimating the input modes from the singular value decomposition from the action of the forward operator alone. These can then be used to determine the input (structure) changes, which induce the largest output (function) changes. The accuracy of the estimate is determined by reference to the method of snapshots. The proposed method is demonstrated on several example problems, and finally used to approximate the optimal airway treatment set for a problem in respiratory physiology. [ABSTRACT FROM AUTHOR]

Critical transitions are abrupt transition in time-varying systems. They occur in many different scientific contexts, ranging from climate and ecology to physiology and electricity transmission, and can be driven by different underlying mathematical structures. Here we focus on those driven by underlying bifurcations (so-called B-tipping), which are associated with qualitative changes in the underlying system energy landscape. Building on Kuehn's fast-slow framework (Kuehn, 2011), we relax the assumptions of stationarity and reflecting boundary conditions by employing a distribution moment approach, which allows us to classify the utility of early warning signals (such as the variance) even when the timescales are not well separated, or the reflection boundary assumption is restrictive. This allows a more complete characterisation of moment-based early warning signals. • Critical transitions are important phenomena in many real-world systems. • Early warning signals of these transitions can be valuable, but their origins must be understood. • Early warning signals for critical transitions can be well-approximated using a distribution moment approach. • This compares favourably with existing approaches based on different approximations. [ABSTRACT FROM AUTHOR]