An evidence-based diagnostic algorithm for adult asthma is necessary for effective treatment and management. We present a diagnostic algorithm that utilizes a random forest (RF) and an optimized eXtreme Gradient Boosting (XGBoost) classifier to diagnose adult asthma as an auxiliary tool. Data were gathered from the medical records of 566 adult outpatients who visited Kindai University Hospital with complaints of nonspecific respiratory symptoms. Specialists made a thorough diagnosis of asthma based on symptoms, physical indicators, and objective testing, including airway hyperresponsiveness. We used two decision-tree classifiers to identify the diagnostic algorithms: RF and XGBoost. Bayesian optimization was used to optimize the hyperparameters of RF and XGBoost. Accuracy and area under the curve (AUC) were used as evaluation metrics. The XGBoost classifier outperformed the RF classifier with an accuracy of 81% and an AUC of 85%. A combination of symptom–physical signs and lung function tests was successfully used to construct a diagnostic algorithm on importance features for diagnosing adult asthma. These results indicate that the proposed model can be reliably used to construct diagnostic algorithms with selected features from objective tests in different settings.

Light detection and ranging (LIDAR) can estimate daily volumes of sand dust particles from the East Asian desert to Japan. The objective of this study was to investigate the relationship between sand dust particles and pulmonary function, and respiratory symptoms in adult patients with asthma. One hundred thirty-seven patients were included in the study. From March 2013 to May 2013, the patients measured their morning peak expiratory flow (PEF) and kept daily lower respiratory symptom diaries. A linear mixed model was used to estimate the correlation of the median daily levels of sand dust particles, symptoms scores, and PEF. A heavy sand dust day was defined as an hourly concentration of sand dust particles of >0.1 km⁻¹. By this criterion, there were 8 heavy sand dust days during the study period. Elevated sand dust particles levels were significantly associated with the symptom score (0.04; 95% confidence interval (CI); 0.03, 0.05), and this increase persisted for 5 days. There was no significant association between PEF and heavy dust exposure (0.01 L/min; 95% CI, −0.62, 0.11). The present study found that sand dust particles were significantly associated with worsened lower respiratory tract symptoms in adult patients with asthma, but not with pulmonary function.

This study aimed to investigate the effects of winter and spring particulate matter (PM) on airway inflammation and allergies in a mouse asthma model. PM was collected during 7–28 February 2013 (winter) and during 7–28 April 2013 (spring) in Yonago, Japan. NC/Nga mice were co-sensitized using intranasal instillation of the PMs and Dermatophagoides farinae (Df) for 5 consecutive days, and were subsequently challenged using intranasal Df at 7 days after the last sensitization. At 24 h after the challenge, serum immunoglobulin levels, differential leukocyte counts, and inflammatory cytokines levels were measured in the mice’s bronchoalveolar lavage fluid (BALF). Compared to co-sensitization using spring PM and Df, winter PM and Df induced greater increases in the BALF neutrophil and eosinophil counts and total serum IgE and IgG2a levels. Furthermore, winter PM-sensitized mice exhibited higher BALF levels of interleukin-5, interleukin-13, interleukin-6, and keratinocyte-derived chemokine. Therefore, we observed seasonal variations in the effects of PM on asthma-related airway inflammation. These findings suggest that the compositions of PM vary according to season, and that it is important to evaluate PM compositions in order to understand the associations between asthma and PM.

Ambient particulate matter (PM) can increase airway inflammation and induce bronchoconstriction in asthma. This study aimed to investigate the effect of tiotropium bromide, a long-acting muscarinic antagonist, on airway inflammation and bronchoconstriction induced by ambient PM in a mouse model of asthma. We compared the effect of tiotropium bromide to that of fluticasone propionate and formoterol fumarate. BALB/c mice were sensitized to ovalbumin (OVA) via the airways and then administered tiotropium bromide, fluticasone propionate, or formoterol fumarate. Mice were also sensitized to ambient PM via intranasal instillation. Differential leukocyte counts and the concentrations of interferon (IFN)-γ, interleukin (IL)-5, IL-6, IL-13, and keratinocyte-derived chemokine (KC/CXCL1) were measured in bronchoalveolar lavage fluid (BALF). Diacron-reactive oxygen metabolites (dROMs) were measured in the serum. Airway resistance and airway inflammation were evaluated in lung tissue 24 h after the OVA challenge. Ambient PM markedly increased neutrophilic airway inflammation in mice with OVA-induced asthma. Tiotropium bromide improved bronchoconstriction, and reduced neutrophil numbers, decreased the concentrations of IL-5, IL-6, IL-13, and KC/CXCL1 in BALF. However, tiotropium bromide did not decrease the levels of dROMs increased by ambient PM. Though eosinophilic airway inflammation was reduced with fluticasone propionate, neutrophilic airway inflammation was unaffected. Bronchoconstriction was improved with formoterol fumarate, but not with fluticasone propionate. In conclusion, tiotropium bromide reduced bronchoconstriction, subsequently leading to reduced neutrophilic airway inflammation induced by ambient PM.

Outdoor fungi are important components of airborne particulate matter (PM). However, the associations between pulmonary function and outdoor fungi are less well known compared to other airborne PM constituents. The objective of this study was to investigate the association between outdoor fungi and pulmonary function in children. Morning peak expiratory flow (PEF) rates were measured daily in 339 schoolchildren (including 36 with asthma), aged 10 to 12, 2 to 27 February 2015. Airborne PM was collected on filters, using a high volume air sampler, each day during the study period. The daily concentration of outdoor fungi-associated PM was calculated using a culture-based method. A linear mixed model was used to estimate the association between PEF values and daily concentrations of outdoor fungi, and the daily levels of suspended PM (SPM) and PM ≤ 2.5 μm (PM_2.5). An increase in the interquartile range (46.2 CFU/m³) for outdoor fungal concentration led to PEF changes of −1.18 L/min (95% confidence interval, −2.27 to −0.08) in all children, 1.22 L/min (−2.96 to 5.41) in children without asthma, and −1.44 L/min (−2.57 to −0.32) in children with asthma. Outdoor fungi showed a significant negative correlation with PM_2.5 levels (r = −0.4, p = 0.04), but not with SPM (r = ‒0.3, p = 0.10) levels. Outdoor fungi may be associated with pulmonary dysfunction in children. Furthermore, children with asthma may show greater pulmonary dysfunction than those without asthma.