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It is necessary to measure the situation of extinguishing agent concentration along with time in the ground simulation test of helicopter/airplane powerplant. The principle that the different percentage of agent in the air has different flow resistances when these agents passing through some porous plug is used, the relation of agent concentration and flow resistance is researched and confirmed by the calibration. The special extinguishing agent concentration measurement is developed, and used in the ground simulation test of several helicopters. The results show that, the measurement has sensitive response, can reflect the varying situation of extinguishing agent concentration in real-time, and satisfy the requirement of ground simulation test in the fire extinguisher system of helicopter/airplane powerplant.

Rationale: Previous studies have identified exercise intolerance in patients with mild-to-moderate chronic obstructive pulmonary disease (COPD). The associations of exercise tolerance with lung function decline and acute exacerbation risk in mild-to-moderate COPD is unclear, especially in the community population. Objectives: We evaluated exercise tolerance in mild-to-moderate COPD and analyzed its associations with respiratory health outcomes. Methods: We analyzed data from the Early Chronic Obstructive Pulmonary Disease community-based study of patients with mild-to-moderate COPD (post- bronchodilator FEV 1 /FVC <0.70 and FEV 1 ≥50% predicted). Patients who completed questionnaires, spirometry, and cardiopulmonary exercise testing at baseline were included. Annual exacerbation assessment and spirometry testing were conducted for 2 years consecutively. Exercise tolerance was defined as the percentage of predicted peak oxygen uptake ( VO 2peak %predicted). We analyzed the association between exercise tolerance, annual lung function decline, and acute exacerbation risk. Measurements and Main Results: Overall, 338 patients were included in the baseline analysis, and 319 completed the 2-year follow-up. The mean and standard deviation (SD) of VO 2peak %predicted was 79.8±13.7. Low VO 2peak %predicted was associated with more chronic respiratory symptoms, worse lung function, severe emphysema, and air trapping at baseline. During the 2-year follow-up, a decrease of 13.7% (1-SD) in VO 2peak %predicted was associated with a decline in pre-bronchodilator FEV 1 /FVC (difference=0.4%, 95% CI: 0.1%-0.7%, P= 0.003), and higher total exacerbation risk (relative risk [RR]=1.25, 95% CI: 1.08-1.46, P=0.004) after adjustment. Conclusions: Mild-to-moderate COPD patients with exercise intolerance have worse respiratory health outcomes, for which a low exercise tolerance as a prognostic marker.

Background: In recent years, more and more patients with chronic obstructive pulmonary disease (COPD) have remained undiagnosed despite having undergone medical examination. This study aimed to develop a convolutional neural network (CNN) model for automatically detecting COPD using double-phase (inspiratory and expiratory) chest computed tomography (CT) images and clinical information., Methods: A total of 2,047 participants, including never-smokers, ex-smokers, and current smokers, were prospectively recruited from three hospitals. The double-phase CT images and clinical information of each participant were collected for training the proposed CNN model which integrated a sequence of residual feature extracting blocks network (RFEBNet) for extracting CT image features and a fully connected feed-forward network (FCNet) for extracting clinical features. In addition, the RFEBNet utilizing double- or single-phase CT images and the FCNet using clinical information were conducted for comparison., Results: The proposed CNN model, which utilized double-phase CT images and clinical information, outperformed other models in detecting COPD with an area under the receiver operating characteristic curve (AUC) of 0.930 [95% confidence interval (CI): 0.913-0.951] on an internal test set (n=307). The AUC was higher than the RFEBNet using double-phase CT images (AUC =0.912, 95% CI: 0.891-0.932), single inspiratory CT images (AUC =0.888, 95% CI: 0.863-0.915), single expiratory CT images (AUC =0.897, 95% CI: 0.874-0.925), and FCNet using clinical information (AUC =0.805, 95% CI: 0.777-0.841). The proposed model also achieved the best performance on an external test (n=516) with an AUC of 0.896 (95% CI: 0.871-0.931)., Conclusions: The proposed CNN model using double-phase CT images and clinical information can automatically detect COPD with high accuracy., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jtd.amegroups.com/article/view/10.21037/jtd-24-367/coif). The authors have no conflicts of interest to declare., (2024 AME Publishing Company. All rights reserved.)

Background: Impaired ventilatory efficiency during exercise is a predictor of mortality in chronic obstructive pulmonary disease. However, little is known about the clinical features and associated factors of impaired ventilatory efficiency in China., Methods: We conducted a cross-sectional community-based study in China and collected demographic and clinical information, cardiopulmonary exercise testing, spirometry, and CT data. Impaired ventilatory efficiency was defined by a nadir ventilatory equivalent for CO 2 production above the upper limit of normal. Multivariable linear and logistic regression models were used to explore the clinical features and associated factors of impaired ventilatory efficiency., Results: The final analyses included 941 subjects, 702 (74.6%) of whom had normal ventilatory efficiency and 239 (25.4%) had impaired ventilatory efficiency. Participants with impaired ventilatory efficiency had more chronic respiratory symptoms, poorer lung function and exercise capacity, and more severe emphysema (natural logarithm transformation of the low-attenuation area of the lung with attenuation values below -950 Hounsfield units, logLAA -950 : 0.19±0.65 vs -0.28±0.63, p<0.001) and air trapping (logLAA -856 : 1.03±0.65 vs 0.68±0.70, p<0.001) than those with normal ventilatory efficiency. Older age (60-69 years, OR 3.10 (95% CI 1.33 to 7.21), p=0.009 and 70-80 years, OR 6.48 (95% CI 2.56 to 16.43), p<0.001 vs 40-49 years) and smoking (former, OR 3.19 (95% CI 1.29 to 7.86), p=0.012; current, OR 4.27 (95% CI 1.78 to 10.24), p=0.001 vs never) were identified as high risk factors of impaired ventilatory efficiency., Conclusions: Impaired ventilatory efficiency was associated with poorer respiratory characteristics. Longitudinal studies are warranted to explore the progression of individuals with impaired ventilatory efficiency., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: The relationship between airway inflammation in chronic obstructive pulmonary disease (COPD) and clinical characteristics remains unclear. This study aimed to investigate the airway inflammatory phenotypes in COPD and their association with clinical characteristics., Methods: 895 patients with COPD were recruited from Guangdong Province, China in this study. Each patient underwent questionnaire interviews, spirometry testing, CT scans and induced sputum examination. Classification of airway inflammation phenotypes was based on sputum inflammatory cell counts. Covariance analysis was applied to assess associations with airway inflammation phenotypes., Results: In this study, we found that neutrophilic phenotype (NP, 58.0%) was the most common airway inflammation phenotype in patients with COPD, followed by mixed granulocytic phenotype (MGP, 32.6%), eosinophilic phenotype (EP, 5.4%) and paucigranulocytic phenotype (PP, 4.0%). Compared with NP patients, those with MGP exhibited more frequent chronic respiratory symptoms, and a higher proportion of individuals classified under Global Initiative for Chronic Obstructive Lung Disease stages 3 and 4. After adjusting for confounding factors, MGP patients had lower lung function, and more severe emphysema and air trapping. On the contrary, patients with PP had the best pulmonary function and less emphysema and air trapping., Conclusions: NP was the most common airway inflammation phenotype in patients with COPD. Patients with MGP had more respiratory symptoms, greater loss of lung function, and more severe emphysema and gas trapping compared with those with NP. Meanwhile, PP may be a phenotype of mild damage to lung structure in patients with COPD., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease and its clinically relevant subtypes are not well understood. Which clinical characteristics are more likely to be present among individuals who develop COPD remains to be studied in depth. Therefore, we designed a prospective observational cohort study, entitled the Early Chronic Obstructive Pulmonary Disease (ECOPD) study, to fill this evidence gap. The ECOPD study has four specific aims: (I) identification of characteristics, parameters, and biomarkers that may predict the development of airflow obstruction and annual decline in lung function with normal spirometry; (II) identification of clinically relevant early COPD subtypes; (III) identification of characteristics, parameters, and biomarkers that may predict disease progression in these early COPD subtypes; (IV) development and validation of machine learning models to predict development of airflow obstruction and disease progression., Methods: We will recruit approximately 2,000 participants aged 40-80 years, including approximately 1,000 with COPD [post-bronchodilator forced expiratory volume in 1 second (FEV1)/forced vital capacity (FVC) <0.7] and approximately 1,000 without COPD, using a population-based survey for COPD. We will assess all participants using standard respiratory epidemiological questionnaires, pulmonary function tests [pre-bronchodilator and post-bronchodilator spirometry, and impulse oscillometry (IOS)], health outcomes [modified British Medical Research Council (mMRC) dyspnea scale, COPD assessment test (CAT), COPD clinical questionnaire (CCQ)], inspiratory and expiratory chest computed tomography (CT), and biomarker measurements (blood and urine), as well as satellite remote sensing pollutant exposure measures. Subgroup will additionally complete induced sputum, exercise capacity tests [6-minute walk test (6MWT) and cardiopulmonary exercise testing (CPET)] and home monitoring/personal sampling as pollutant exposure measures. Study procedures will be performed at baseline and every 1 year thereafter., Discussion: The ECOPD study will provide insight into many aspects of early COPD and improve our understanding of COPD development, which may facilitate therapeutic interventions with the potential to modify the course of disease., Trial Registration: Chinese Clinical Trial Registry, ChiCTR1900024643. Registered on 19 July, 2019., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://dx.doi.org/10.21037/jtd-21-1379). The authors have no conflicts of interest to declare., (2021 Journal of Thoracic Disease. All rights reserved.)