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Objective It aimed to analyze the epidemic situation of new coronary pneumonia (COVID-19) based on the epidemiological Markov model, and to study the clinical risk factors of the patients based on the patient’s cardinal data and clinical symptoms. Methods A total of 500 patients with COVID-19 diagnosed by nucleic acid testing in the X hospital from January 2020 to May 2020 were collected. According to the severity of the disease, they were classified into general group (200 cases) and acute critical group (300 cases). Markov model to predict the number of COVID-19 infections was constructed. Patient’s general information, clinical characteristics, and prevention methods were analyzed. Results According to Markov model statistics, the developmental expected stay time of patients infected with COVID-19 was 14 days. 2. The two groups of patients had statistically considerable differences in complications such as gender, age, hypertension, coronary heart disease, shortness of breath, myocardial damage, and thrombocytopenia ( P < 0.05). 3. Logistic multivariate regression analysis showed that the clinical risk factors for patients with COVID-19 mainly included the patient’s gender, age, whether they were associated with hypertension, coronary heart disease, shortness of breath, myocardial damage, and thrombocytopenia. Conclusion Markov model can be utilized to judge the time course of the COVID-19 in various development states. In addition, the COVID-19 spread rapidly and is extremely harmful. Clinically, through active prevention, the treatment effect can be improved, the patient’s respiratory function, and the quality of life can also be improved.

Asthma, a great public health burden, is triggered by inflammatory responses in the airways and these are not addressed appropriately by current therapies. This study aims to investigate the regulatory mechanism of microRNA-22-3p (miR-22-3p) on the proliferation of bronchial epithelial cells exposed to lipopolysaccharide (LPS) and expression of pro-inflammatory cytokines in a murine asthma model challenged by ovalbumin. We first confirmed the downregulation of miR-22-3p in the murine asthma model and bronchial epithelial cells. miR-22-3p remarkably reversed the decline in bronchial epithelial cell viability, enhancement in apoptosis rate and release of inflammatory factors induced by LPS. miR-22-3p targeted and conversely regulated NACHT, LRR and PYD domains-containing protein 3 (NLRP3). Overexpression of NLRP3 counteracted the inhibitory effect of miR-22-3p on inflammatory damage in bronchial epithelial cells through activation of caspase-1/interleukin (IL)-1β. In an in vivo model, overexpression of miR-22-3p significantly attenuated airway obstruction and tissue damage in mice. In summary, our study underscores that miR-22-3p serves both as a negative regulator of the NLRP3-caspase-1-IL-1β axis and as a protective factor against the inflammatory response, suggesting a future therapeutic role in asthma. K E Y W O R D Sasthma, caspase-1, IL-1β, microRNA-22-3p, NLRP3 INTRODUCTIONMicroRNAs (miRNAs), short 18-22 nt single-stranded RNAs that play important parts in modulating protein expression and regulating cellular signalling, have been implicated in the development of chronic airway diseases, including asthma (Tan et al., 2020). The symptoms of asthma result from a chronic airway inflammatory response to a trigger, most frequently inhaled allergen(s), that induces airway hyper-

Purpose. To explore the diagnostic value of fractional exhaled nitric oxide (FeNO), small airway function, and a combined of both in differentiating cough-variant asthma (CVA) from typical asthma (TA). Methods. A total of 206 asthma subjects, including 104 CVA and 102 TA, were tested for pulmonary function, bronchial provocation test and FeNO. The correlation between FeNO, small airway function and other pulmonary indicators was analyzed by single correlation and multiple regression analysis. The receiver operating characteristic (ROC) curve was established to evaluate the diagnostic efficiency of FeNO, small airway function, and their combination and to predict the optimal cut-off point. Results. All the respiratory function parameters and small airway function indicators in TA group were significantly different from those in CVA group, and FeNO value was significantly higher than that in CVA group. In addition, the area under the ROC curve (AUC) was estimated to be 0.660 for FeNO, 0.895 for MMEF75%/25%, 0.873 for FEF50%, 0.898 for FEF25%, 0.695 for Fres, 0.650 for R5-R20, and 0.645 for X5. The optimal cut-off points of FeNO, MMEF75%/25%, FEF50%, FEF25%, Fres, R5-R20 and X5, were 48.50 ppb, 60.02%, 63.46%, 45.26%, 16.63 Hz, 0.38 kPa·L−1·s−1, and −1.32, respectively. And the AUC of FeNO combined with small airway function indexes FEF25%, Fres, R5-R20, and X5 were prior than single indicators. Conclusion. FeNO and small airway function indexes might have great diagnostic value for differentiating CVA from TA. The combination of FeNO and FEF25%, Fres, R5-R20, and X5 provided a significantly better prediction than either alone.

ObjectivesTo determine the incidence of pneumoconiosis worldwide and its influencing factors.DesignSystematic review and meta-analysis.SettingCohort studies on occupational pneumoconiosis.ParticipantsPubMed, Embase, the Cochrane Library and Web of Science were searched until November 2021. Studies were selected for meta-analysis if they involved at least one variable investigated as an influencing factor for the incidence of pneumoconiosis and reported either the parameters and 95% CIs of the risk fit to the data, or sufficient information to allow for the calculation of those values.Primary outcome measuresThe pooled incidence of pneumoconiosis and risk ratio (RR) and 95% CIs of influencing factors.ResultsOur meta-analysis included 19 studies with a total of 335 424 participants, of whom 29 972 developed pneumoconiosis. The pooled incidence of pneumoconiosis was 0.093 (95% CI 0.085 to 0.135). We identified the following influencing factors: (1) male (RR 3.74; 95% CI 1.31 to 10.64; p=0.01), (2) smoking (RR 1.80; 95% CI 1.34 to 2.43; p=0.0001), (3) tunnelling category (RR 4.75; 95% CI 1.96 to 11.53; p<0.0001), (4) helping category (RR 0.07; 95% CI 0.13 to 0.16; p<0.0001), (5) age (the highest incidence occurs between the ages of 50 and 60), (6) duration of dust exposure (RR 4.59, 95% CI 2.41 to 8.74, p<0.01) and (7) cumulative total dust exposure (CTD) (RR 34.14, 95% CI 17.50 to 66.63, p<0.01). A dose–response analysis revealed a significant positive linear dose–response association between the risk of pneumoconiosis and duration of exposure and CTD (P-non-linearity=0.10, P-non-linearity=0.16; respectively). The Pearson correlation analysis revealed that silicosis incidence was highly correlated with cumulative silica exposure (r=0.794, p<0.001).ConclusionThe incidence of pneumoconiosis in occupational workers was 0.093 and seven factors were found to be associated with the incidence, providing some insight into the prevention of pneumoconiosis.PROSPERO registration numberCRD42022323233.