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Background: The application of positron emission tomography/computed tomography (PET/CT) helps provide accurate clinical staging for lung cancer patients. However, the effects and trends in early-stage lung cancer remain unclear. The aim of this study was to compare differences between clinical stage I lung cancer patients who received PET/CT for staging and those who did not. Methods: Data were obtained from the Taiwan Society of Cancer Registry. There were 6587 clinical stage I lung cancer patients between 2009 and 2014 analyzed in this study. We compared the characteristics of the PET/CT and no PET/CT groups. After propensity score matching, it resulted in both groups having 2649 patients. We measured the overall survival rates of all clinical stage I lung cancer patients and the overall survival rates of patients with PET/CT and without PET/CT. Results: The 1-, 3-, and 5-year survival rates of all clinical stage I lung cancer patients were 97.2%, 88.2%, and 79.0%, respectively. Patients with a larger tumor size tended to receive PET/CT for staging (stage Ib: 38.25% vs. 27.82%, p < 0.0001) and a larger resection (lobectomy: 74.62% vs. 66.61%, p < 0.0001). The 5-year survival rates were 79.8% in the PET/CT group and 78.2% in the no PET/CT group after propensity score matching (p = 0.6528). Conclusions: For clinical stage I lung cancer in Taiwan, patients with larger tumor sizes tend to have PET/CT for staging. Although PET/CT provided more precise clinical staging, these patients still received larger resections and had more pathological migration. However, there was no overall survival rate benefit after PET/CT. [ABSTRACT FROM AUTHOR]

The steady increase in droughts worldwide has compelled many researchers to focus on water allocation. Multi-objective decision support for irrigation systems is a popular topic due to its relevance to the national economy and food supply. However, the majority of researchers have relied on conventional top-k designs for their decision support systems despite their limitations with regard to multi-objective systems. Thus, we propose applying a skyline query to the problem. As the input and output formats of skyline queries differ significantly from those of existing systems, we developed a new genetic algorithm and objective ranking. Qualitative and quantitative experiments using real-world data from Taiwan's largest irrigated region demonstrate the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

Glycopyrronium (GLY) is a pharmacological maintenance treatment for chronic obstructive pulmonary disease (COPD). However, its effectiveness and tolerability for COPD patients in routine clinical practice have not been well-investigated. This study aimed to assess the effectiveness of GLY on health-related quality of life and its safety in patients with COPD in a routine clinical care setting. This multi-center, prospective, six-month observational study recruited patients diagnosed with COPD and treated with GLY at three medical centers in central Taiwan. The full analysis set (n = 102) had a significant improvement in the Clinical COPD Questionnaire total (mean ± SD = −0.39 ± 0.90, p = 0.002), symptoms (mean ± SD = −0.61 ± 0.90, p < 0.001) and mental state scores (mean ± SD = −0.54 ± 1.72, p = 0.021) but not the functional state score (mean ± SD = −0.10 ± 1.15, p = 0.529). During the observational period, 58 patients (52.73%) experienced adverse events; only one adverse event (dizziness) was suspected to be related to the study drug. Three patients (2.73%) discontinued the study and GLY treatment because of an adverse event. One patient (0.91%) died during the study period because of a cerebral infarction, which was judged to be not associated with GLY treatment. In conclusion, GLY could be effective in improving the health status and is safe for patients with COPD in a real-life setting. [ABSTRACT FROM AUTHOR]

Sensitization to fungal allergens is one of the proposed phenotypes in asthma. An association between fungal sensitization and worse clinical outcomes is apparent. Moreover, fungal sensitization in asthma that is associated with different type of immunological mechanism has been reported. How the role of cytokines mediates the association between fungal sensitization and poorer asthmatic outcomes remains unclear. We aimed to determine role of cytokines in the relationship between fungal sensitization and worse clinical outcomes in asthma. Method: We conducted a prospective study to recruit adult patients with asthma. Data including age, sex, height, weight, smoking history, medication, emergency visit and admission, pulmonary function testing result, and Asthma Control Test (ACT) scores were collected. We used the automated BioIC method to measure fungal allergen sIgE in sera. Serum levels of Interleukin (IL) -4, IL-13, IL-6, IL-9, IL-10, IL-17 A, IL-22, Interferon (IFN) -γ, Immunoglobulin E (IgE), Tumor necrosis factor-α (TNF-α), and Transforming growth factor-β (TGF-β) were measured using ELISA. Result: IL-6 and IL-17A had a significant positive correlation between sensitization and most fungi species compared to IgE. Sensitization to Candida albicans had strongly positive association both with IL-6 and IL-17A. However, only IL-17A had significant relationship with ED visit times. The mediation analysis result indicates that IL-17A had a significant positively mediating effect (ME) on the association between Candida albicans and ED visit times. Conclusion: IL-17A is a potential mediator to link Candida albicans sensitization and ED visits for asthma. We suggest that patients with fungal sensitization, such as Candida albicans, have poorer outcomes associated with Th17-mediated immune response rather than Th2. [ABSTRACT FROM AUTHOR]

Background: The study developed accurate explainable machine learning (ML) models for predicting first-time acute exacerbation of chronic obstructive pulmonary disease (COPD, AECOPD) at an individual level. Methods: We conducted a retrospective case–control study. A total of 606 patients with COPD were screened for eligibility using registry data from the COPD Pay-for-Performance Program (COPD P4P program) database at Changhua Christian Hospital between January 2017 and December 2019. Recursive feature elimination technology was used to select the optimal subset of features for predicting the occurrence of AECOPD. We developed four ML models to predict first-time AECOPD, and the highest-performing model was applied. Finally, an explainable approach based on ML and the SHapley Additive exPlanations (SHAP) and a local explanation method were used to evaluate the risk of AECOPD and to generate individual explanations of the model's decisions. Results: The gradient boosting machine (GBM) and support vector machine (SVM) models exhibited superior discrimination ability (area under curve [AUC] = 0.833 [95% confidence interval (CI) 0.745–0.921] and AUC = 0.836 [95% CI 0.757–0.915], respectively). The decision curve analysis indicated that the GBM model exhibited a higher net benefit in distinguishing patients at high risk for AECOPD when the threshold probability was <0.55. The COPD Assessment Test (CAT) and the symptom of wheezing were the two most important features and exhibited the highest SHAP values, followed by monocyte count and white blood cell (WBC) count, coughing, red blood cell (RBC) count, breathing rate, oral long-acting bronchodilator use, chronic pulmonary disease (CPD), systolic blood pressure (SBP), and others. Higher CAT score; monocyte, WBC, and RBC counts; BMI; diastolic blood pressure (DBP); neutrophil-to-lymphocyte ratio; and eosinophil and lymphocyte counts were associated with AECOPD. The presence of symptoms (wheezing, dyspnea, coughing), chronic disease (CPD, congestive heart failure [CHF], sleep disorders, and pneumonia), and use of COPD medications (triple-therapy long-acting bronchodilators, short-acting bronchodilators, oral long-acting bronchodilators, and antibiotics) were also positively associated with AECOPD. A high breathing rate, heart rate, or systolic blood pressure and methylxanthine use were negatively correlated with AECOPD. Conclusions: The ML model was able to accurately assess the risk of AECOPD. The ML model combined with SHAP and the local explanation method were able to provide interpretable and visual explanations of individualized risk predictions, which may assist clinical physicians in understanding the effects of key features in the model and the model's decision-making process. [ABSTRACT FROM AUTHOR]

Purpose: To understand the association between biomarkers and exacerbations of severe asthma in adult patients in Taiwan. Materials and Methods: Demographic, clinical characteristics and biomarkers were retrospectively collected from the medical charts of severe asthma patients in six hospitals in Taiwan. Exacerbations were defined as those requiring asthma-specific emergency department visits/hospitalizations, or systemic steroids. Enrolled patients were divided into: (1) those with no exacerbations (non-exacerbators) and (2) those with one or more exacerbations (exacerbators). Receiver operating characteristic curves were used to determine the optimal cut-off value for biomarkers. Generalized linear models evaluated the association between exacerbation and biomarkers. Results: 132 patients were enrolled in the study with 80 non-exacerbators and 52 exacerbators. There was no significant difference in demographic and clinical characteristics between the two groups. Exacerbators had significantly higher eosinophils (EOS) counts (367.8 ± 357.18 vs. 210.05 ± 175.24, p = 0.0043) compared to non-exacerbators. The optimal cut-off values were 292 for EOS counts and 19 for the Fractional exhaled Nitric Oxide (FeNO) measure. Patients with an EOS count ≥ 300 (RR = 1.88; 95% CI, 1.26–2.81; p = 0.002) or FeNO measure ≥ 20 (RR = 2.10; 95% CI, 1.05–4.18; p = 0.0356) had a significantly higher risk of exacerbation. Moreover, patients with both an EOS count ≥ 300 and FeNO measure ≥ 20 had a significantly higher risk of exacerbation than those with lower EOS count or lower FeNO measure (RR = 2.16; 95% CI, 1.47–3.18; p = < 0.0001). Conclusions: Higher EOS counts and FeNO measures were associated with increased risk of exacerbation. These biomarkers may help physicians identify patients at risk of exacerbations and personalize treatment for asthma patients. [ABSTRACT FROM AUTHOR]

Chronic obstructive pulmonary disease (COPD) is preventable and treatable. However, many patients remain undiagnosed and untreated due to the underutilization or unavailability of spirometers. Accordingly, we used Spirobank Smart, an app-based spirometer, for facilitating the early detection of COPD in outpatient clinics. This prospective study recruited individuals who were at risk of COPD (i.e., with age of ≥40 years, ≥10 pack-years of smoking, and at least one respiratory symptoms) but had no previous COPD diagnosis. Eligible participants were examined with Spirobank Smart and then underwent confirmatory spirometry (performed using a diagnostic spirometer), regardless of their Spirobank Smart test results. COPD was defined and confirmed using the postbronchodilator forced expiratory volume in 1 s/forced vital capacity values of <0.70 as measured by confirmatory spirometry. A total of 767 participants were enrolled and examined using Spirobank Smart; 370 participants (94.3% men, mean age of 60.9 years and mean 42.6 pack-years of smoking) underwent confirmatory spirometry. Confirmatory spirometry identified COPD in 103 participants (27.8%). At the optimal cutoff point of 0.74 that was determined using Spirobank Smart for COPD diagnosis, the area under the receiver operating characteristic was 0.903 (95% confidence interval (CI) = 0.860–0.947). Multivariate logistic regression revealed that participants who have an FEV1/FVC ratio of <74% that was determined using Spirobank Smart (odds ratio (OR) = 58.58, 95% CI = 27.29–125.75) and old age (OR = 3.23, 95% CI = 1.04–10.07 for 60 ≤ age < 65; OR = 5.82, 95% CI = 2.22–15.27 for age ≥ 65) had a higher risk of COPD. The Spirobank Smart is a simple and adequate tool for early COPD detection in outpatient clinics. Early diagnosis and appropriate therapy based on GOLD guidelines can positively influence respiratory symptoms and quality of life. [ABSTRACT FROM AUTHOR]

EGFR mutation status is considered as an important predictor of therapeutic responsiveness in non-small-cell lung carcinoma patients. Recent evidence suggests that antioxidant gene polymorphisms are potential predictors of lung cancer risk. Thus, stratification of EGFR mutation-related phenotypes by antioxidant gene polymorphism status can be an effective approach in terms of improving the prognosis of lung cancer patients. The present study was designed to evaluate the distribution frequency of antioxidant gene polymorphisms in lung adenocarcinoma, as well as its association with hotspot EGFR mutations. The study findings revealed that a statistically significant association exists between EGFR L858R mutation and AG + GG genotypes of SOD rs4880 polymorphism. Furthermore, the subgroup analysis data revealed that compared to AA genotype of SOD rs4880, AG + GG genotypes were significantly associated with advanced cancer stage and distant metastasis. Taken together, these findings can be utilized clinically to predict cancer aggressiveness, metastatic, potential and therapeutic responsiveness of lung cancer patients. [ABSTRACT FROM AUTHOR]

24-methyl-cholesta-5,24(28)-diene-3β,19-diol-7β-monoacetate (MeCDDA) is a natural steroid compound isolated from a wild-type soft coral ( Nephthea erecta ). The present study aimed to investigate the anti-small cell lung cancer (SCLC) effects of MeCDDA in vitro and in vivo, as well as to elucidate its underlying mechanism. Our results indicated that H1688 and H146 cells show relevant sensitivity to MeCDDA, and the exposure to MeCDDA in SCLC cells caused dose-dependent growth inhibitory responses. In addition, MeCDDA treatment promoted cell apoptosis and increased the activities of caspases in H1688 cells, reducing the mitochondrial membrane potential and stimulating the release of cytochrome c into the cytosol. Along with the increase in Bax expression and reduction in Bcl-2, the MeCDDA treatment also significantly decreased Akt and mTOR phosphorylation. Finally, MeCDDA treatment in the mouse xenograft model of H1688 cells exhibited significant inhibition of tumor growth, corroborating MeCDDA as a potential pre-clinical candidate for the treatment of SCLC. Overall, our results demonstrate that the cytotoxic effects of MeCDDA towards H1688 and H146 cells, possibly through the activation of the mitochondrial apoptotic pathway and inhibition of the PI3K/Akt/mTOR pathway, merit further studies for its possible clinical application in chemotherapy., Competing Interests: The authors declare that they have no competing interests.