Machine Alarm Fatigue among Hemodialysis Nurses in 29 Tertiary Hospitals.

Objectives To understand the status quo and related influencing factors of machine alarm fatigue of hemodialysis nurses in tertiary hospitals in XXX. Methods This cross-sectional study employed convenience sampling to select 460 nurses from 29 tertiary hospitals in XXX, who are involved in hemodialysis care. Surveys were conducted using General Information Questionnaire, Alarm Fatigue Scale, National Aeronautics and Space Administration Task Load Index(NASA-TLX) and Maslach Burnout Inventory Scale (MBI). Results The overall machine alarm fatigue score for 460 hemodialysis nurses from 29 tertiary hospitals in XXX was (16.43±6.44), indicating a moderate level. The multiple linear regression analysis shows that years of experience in hemodialysis nursing, the number of patients managed per shift, whether specialized nursing training has been received, self-reported health status, emotional exhaustion, and workload have statistically significant associations with alarm fatigue among hemodialysis nurses (P < 0.05). Among them, years of experience in hemodialysis nursing, the number of patients managed per shift, and workload are positively correlated with alarm fatigue among hemodialysis nurses. Conclusion This study indicates that certain demographic factors, workload, and occupational burnout are associated with machine alarm fatigue among hemodialysis nurses. Therefore, hemodialysis-related managers should establish a Machine Alarm Management System, implement Personalized Thresholds and Delayed Alarms, ensure reasonable staffing arrangements, improve compassion fatigue, and enhance anticipatory care. These measures aim to improve the health and psychological well-being of hemodialysis nurses, provide a conducive environment for professional training in hemodialysis, and ultimately address the current situation of machine alarm fatigue among hemodialysis nurses.

KLF5-mediated pyroptosis of airway epithelial cells leads to airway inflammation in asthmatic mice through the miR-182-5p/TLR4 axis.

Asthma is viewed as an airway disease and an inflammatory condition. This study aims to reveal the role of Kruppel-like factor 5 (KLF5)-mediated pyroptosis of airway epithelial cells in airway inflammation in asthma. The asthmatic mouse model was established. The mice were infected with the lentivirus containing sh-KLF5, antagomiR-182-5p, and pc-Toll-like receptor 4 (TLR4). Airway hyperresponsiveness was measured, and the cells in bronchoalveolar lavage fluid (BALF) were sorted and counted. The expression levels of interleukin (IL)-4/IL-13/IL-6/IL-18/IL-1ß/NOD-like receptor family pyrin domain containing 3 (NLRP3)/N-gasdermin D (GSDMD-N)/cleaved caspase-1 were detected. The pathological changes in lung tissue were observed. The enrichment of KLF5 in the miR-182-5p promoter region was measured. The binding relationship among KLF5, miR-182-5p, and TLR4 were analyzed. KLF5 was highly expressed in asthmatic mice. Silencing KLF5 improved airway resistance and lung dynamic compliance, reduced the cells in BALF and the expression of IL-4/IL-13/IL-6/NLRP3/GSDMD-N/cleaved caspase-1/IL-18/IL-1ß, and alleviated the pathological changes. Mechanistically, KLF5 bonded to the miR-182-5p promoter to inhibit miR-182-5p expression, and miR-182-5p inhibited TLR4. Silencing miR-182-5p or TLR4 overexpression reversed the improvement of silencing KLF5 on airway inflammation and pyroptosis in asthmatic mice. In conclusion, KLF5 inhibited miR-182-5p to promote TLR4 expression, thus aggravating pyroptosis and airway inflammation in asthmatic mice.

Gut phageome: challenges in research and impact on human microbiota.

The human gut microbiome plays a critical role in maintaining our health. Fluctuations in the diversity and structure of the gut microbiota have been implicated in the pathogenesis of several metabolic and inflammatory conditions. Dietary patterns, medication, smoking, alcohol consumption, and physical activity can all influence the abundance of different types of microbiota in the gut, which in turn can affect the health of individuals. Intestinal phages are an essential component of the gut microbiome, but most studies predominantly focus on the structure and dynamics of gut bacteria while neglecting the role of phages in shaping the gut microbiome. As bacteria-killing viruses, the distribution of bacteriophages in the intestine, their role in influencing the intestinal microbiota, and their mechanisms of action remain elusive. Herein, we present an overview of the current knowledge of gut phages, their lifestyles, identification, and potential impact on the gut microbiota.

Genetic association analysis of dietary intake and idiopathic pulmonary fibrosis: a two-sample mendelian randomization study.

BACKGROUND: IPF is a complex lung disease whose aetiology is not fully understood, but diet may have an impact on its development and progression. Therefore, we investigated the potential causal connection between dietary intake and IPF through TSMR to offer insights for early disease prevention recommendations. METHODS: The study incorporated 29 dietary exposure factors, oily fish intake, bacon intake, processed meat intake, poultry intake, beef intake, pork intake, lamb/mutton intake, non-oily fish intake, fresh fruit intake, cooked vegetable intake, baked bean intake, fresh tomato intake, tinned tomato intake, salad/raw vegetable intake, Fresh fruit intake, coffee intake, tea intake, water intake, red wine intake, average weekly beer plus cider intake, alcoholic drinks per week, cereal intake, bread intake, whole-wheat intake, whole-wheat cereal intake, cheese intake, yogurt intake, salt added to food and whole egg intake. The study explored the causal link between diet and IPF using TSMR analysis, predominantly the IVW method, and performed sensitivity analyses to validate the results. RESULT: The study revealed that consuming oily fish, yogurt, and dried fruits had a protective effect against IPF, whereas the consumption of alcoholic beverages and beef was linked to an increased risk of IPF. CONCLUSION: In this MR study, it was discovered that the consumption of oily fish, yogurt, and dried fruits exhibited a protective effect against IPF, whereas the intake of alcoholic beverages and beef was associated with an elevated risk of IPF. These findings underscore the significance of making informed and timely dietary decisions in IPF prevention.

Whole transcriptome sequencing identifies key lncRNAs,circRNAs, and mRNAs for exploring the pathogenesis and therapeutic target of mouse pneumoconiosis.

BACKGROUND: Pneumoconiosis is a kind of lung dysfunction caused by the inhalation of mineral dust. However, the potential molecular mechanism of pneumoconiosis have not been fully elucidated. METHODS: In this study, the silica-treated pneumoconiosis mice model was constructed and the transcriptome sequencing data including lncRNA, circRNA, and mRNA were obtained. Firstly, differentially expressed lncRNA, circRNA, and mRNA (DElncRNA, DEcircRNA, DEGs) between control and pneumoconiosis/silicosis samples were screened, the target miRNAs (co-pre-miRNAs) were obtained by intersecting the miRNAs predicted by DElncRNA and DEcircRNA, respectively, and the target mRNAs (co-mRNA) were obtained by intersecting the mRNAs predicted by target miRNA and DEGs. Then, the lncRNA/circRNA-miRNA-mRNA networks were constructed by Cytoscape. Next, the key mRNAs were obtained by protein-protein interaction (PPI) analysis, and the key lncRNAs/circRNAs were selected by correlation analysis. Moreover, the expression of the key lncRNAs, circRNAs and mRNAs on chromosome were studied by the "circlize" package. Furthermore, the TFs-miRNA-mRNA network was constructed and the function of DEGs were explored by Ingenuity Pathway Analysis (IPA). To demonstrate the feasibility and value of the constructed ceRNA networks, we validated key genes and mmu-miR-682 pathway. Finally, We used the Drug-Gene Interaction database to predict potential drugs that could interfere with key genes,which may help to find promising treatment. RESULTS: There were 427 DElncRNAs, 107 DEcircRNAs and 1,597 DEGs between silicosis and control groups. Totals of 77 co-pre-miRNAs and 96 co-mRNA were screened, and the lncRNA/circRNA-miRNA-mRNA networks were constructed with 27 lncRNA/25 circRNAs, 74 miRNAs and 96 mRNAs. Then, 6 key mRNAs including Igf1, Klf4, Ptgs2, Epas1, Gnao1, and Il1a were obtained by PPI, and all of these key mRNAs and 10 key lncRNAs and 8 circRNAs were significantly different between the pneumoconiosis and normal groups, in which 10 lncRNAs and 9 circRNA that have not been previously studied in pneumoconiosis/silicosis can be used as new potential therapeutic targets. Moreover, the TFs-miRNA-mRNA network were constructed with 11 TFs, 1 key miRNA (mmu-miR-682) and 3 key mRNAs (Igf1, Epas1, Ptgs2). And the validation of key genes revealing by RNA-seq through experimental approaches shows the the predictive power of this study. Finally, IPA results indicated that 41 pathways were activated and 2 pathways were suppressed in pneumoconiosis/silicosis groups, and Pathogen Induced Cytokine Storm Signaling Pathway was the most significant pathway affected by pneumoconiosis/silicosis. In addition, 93 drugs were screened out by Drug-Gene Interaction database. Among them, Hydroxychloroquine was a kind of drug which associated with Il1a and Ptgs2, may be a promising treatment. CONCLUSION: This study constructed the lncRNA/circRNA-miRNA-mRNA and TFs-miRNA-mRNA networks, which could deepen the potential molecular regulatory mechanism of pneumoconiosis/silicosis.

Trends in the Epidemiology of Pneumocystis Pneumonia in Immunocompromised Patients without HIV Infection.

The increasing morbidity and mortality of life-threatening Pneumocystis pneumonia (PCP) in immunocompromised people poses a global concern, prompting the World Health Organization to list it as one of the 19 priority invasive fungal diseases, calling for increased research and public health action. In response to this initiative, we provide this review on the epidemiology of PCP in non-HIV patients with various immunodeficient conditions, including the use of immunosuppressive agents, cancer therapies, solid organ and stem cell transplantation, autoimmune and inflammatory diseases, inherited or primary immunodeficiencies, and COVID-19. Special attention is given to the molecular epidemiology of PCP outbreaks in solid organ transplant recipients; the risk of PCP associated with the increasing use of immunodepleting monoclonal antibodies and a wide range of genetic defects causing primary immunodeficiency; the trend of concurrent infection of PCP in COVID-19; the prevalence of colonization; and the rising evidence supporting de novo infection rather than reactivation of latent infection in the pathogenesis of PCP. Additionally, we provide a concise discussion of the varying effects of different immunodeficient conditions on distinct components of the immune system. The objective of this review is to increase awareness and knowledge of PCP in non-HIV patients, thereby improving the early identification and treatment of patients susceptible to PCP.

Efficient clinical data analysis for prediction of coal workers' pneumoconiosis using machine learning algorithms.

PURPOSE: The purpose of this study is to propose an efficient coal workers' pneumoconiosis (CWP) clinical prediction system and put it into clinical use for clinical diagnosis of pneumoconiosis. METHODS: Patients with CWP and dust-exposed workers who were enrolled from August 2021 to December 2021 were included in this study. Firstly, we chose the embedded method through using three feature selection approaches to perform the prediction analysis. Then, we performed the machine learning algorithms as the model backbone and combined them with three feature selection methods, respectively, to determine the optimal predictive model for CWP. RESULTS: Through applying three feature selection approaches based on machine learning algorithms, it was found that AaDO2 and some pulmonary function indicators played an important role in prediction for identifying CWP of early stage. The support vector machine (SVM) algorithm was proved as the optimal machine learning model for predicting CWP, with the ROC curves obtained from three feature selection methods using SVM algorithm whose AUC values of 97.78%, 93.7%, and 95.56%, respectively. CONCLUSION: We developed the optimal model (SVM algorithm) through comparisons and analyses among the performances of different models for the prediction of CWP as a clinical application.

A systematic review and meta-analysis of the prevalence and epidemiology of asthma in people over 14 years of age in China.

OBJECTIVE: Asthma is a common chronic respiratory disease that seriously affects the health of adults and children. The risk factors for asthma are constantly changing; thus, it is necessary to study the prevalence of asthma and risk factors in different populations. Currently, there have been no epidemiological studies on the prevalence and risk factors of asthma in people over 14 years in mainland China. Therefore, we performed a meta-analysis of the prevalence and risk factors for asthma in mainland China. METHODS: A literature search was conducted for studies on the epidemiology of asthma in China between 2000 and 2020 using English and Chinese databases. Prevalence and epidemiological information on asthma in people aged >14 years were extracted. Meta-analysis was performed using a random-effects model (If I2>50%) with 95% confidence intervals for forest plots. RESULTS: Nineteen studies (including data from 345,950 samples) met our evaluation criteria. The overall prevalence of asthma in Chinese adults is 2%, without differences between Northern and Southern China. The prevalence increased after 2010 compared with that before 2010. The prevalence of asthma also increased with age, with people aged 55-64 years being the most affected. The prevalence of asthma was independent of sex and residence area. In conclusion, the prevalence of asthma among adolescents (age >14 years) and adult population in China has increased since 2010. CONCLUSION: Further studies are necessary to monitor the prevalence of asthma in mainland China. The elderly population also has a high prevalence of asthma, which should be focused on more in the future.

Incidence and influencing factors of occupational pneumoconiosis: a systematic review and meta-analysis.

OBJECTIVES: To determine the incidence of pneumoconiosis worldwide and its influencing factors. DESIGN: Systematic review and meta-analysis. SETTING: Cohort studies on occupational pneumoconiosis. PARTICIPANTS: PubMed, 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 MEASURES: The pooled incidence of pneumoconiosis and risk ratio (RR) and 95% CIs of influencing factors. RESULTS: Our 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). CONCLUSION: The 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 NUMBER: CRD42022323233.

Exosomal miRNAs contribute to coal dust particle-induced pulmonary fibrosis in rats.

Coal workers' pneumoconiosis (CWP) is a fatal occupational disease caused by inhalation of coal dust particles, which leads to progressive pulmonary fibrosis. Recently, as new signal carriers for intercellular communication, exosomal miRNAs have been validated in the pathogenesis of multiple diseases. However, the research on exosomal miRNAs in CWP is still in the preliminary stage. Here, using miRNA sequencing, exosomal miRNA profiles in bronchoalveolar lavage fluid (BALF) from rats with pulmonary fibrosis induced by coal dust particles were analyzed, and the underlying biological function of putative target genes was explored by GO term analysis and KEGG pathway enrichment analysis. According to the results, intratracheal instillation of coal dust particles can alter the exosomal miRNAs expression in the BALF of rats. Further bioinformatics analysis provided some clues to reveal their function in pathological process of pneumoconiosis. More importantly, we identified 4 differentially expressed exosomal miRNAs (miRNA-21-5p, miRNA-29a-3p, miRNA-26a-5p, and miRNA-34a-5p) by qRT­PCR and further verified the temporal changes in the expression of these exosomal miRNAs in animal models from 2 weeks to 16 weeks postexposure. In addition, we conducted a preliminary study on Smad7 as a potential target of miRNA-21-5p and found that exosomal miRNA 21-5p/Smad7 may contribute to the pulmonary fibrosis induced by coal dust particles. Our study confirmed the contribution of exosomal miRNAs to coal dust particle-induced pulmonary fibrosis and provided new insights into the pathogenesis of CWP.

Lactobacillus fermentum CECT5716 Alleviates the Inflammatory Response in Asthma by Regulating TLR2/TLR4 Expression.

Background: Asthma is a chronic disease, which is harmful to the health of the body and the quality of life. Supplementation of Lactobacillus can affect the immune environment of the lungs through the gut-lung axis. This study aimed to explore the potential regulatory targets of Lactobacillus to relieve inflammation in asthma and determine a new approach for improving asthma. Methods: A mouse ovalbumin (OVA)-induced model was constructed. OVA mice were supplemented with Lactobacillus fermentum CECT5716 by gavage. The gut microbiota composition of normal and OVA mice was analyzed using 16S ribosomal DNA identification. BALF, serum, lung tissues, and duodenal tissues were collected. Wright's staining was performed to determine the cell content of the alveolar lavage fluid. Hematoxylin-eosin staining, Masson staining, and periodic acid-Schiff staining were performed to observe the improvement in the lungs of OVA mice supplemented with Lactobacillus. Immunofluorescence was performed to measure the severity of the intestinal barrier leakage. Enzyme-linked immunosorbent assay was carried out to determine the expression levels of inflammatory cell factors, while quantitative reverse transcription-polymerase chain reaction and western blotting were performed to detect the levels of toll-like receptor 2 (TLR2)/TLR4 expression and cell adhesion factors. Results: Compared with Control mice, OVA mice exhibited malignant conditions, such as intestinal leakage and lung edema. After supplementation with Lactobacillus, the inflammatory cell content in the bronchoalveolar lavage fluid decreased, and the inflammatory response was alleviated. The level of TLR2/TLR4 expression was reduced. The inflammatory cell infiltration in the airway mucosa of OVA mice was improved, alveolar swelling was reduced and the basement membrane appeared thinner. Conclusion: The Lactobacillus inhibited the TLR2/TLR4 expression in OVA mice. Supplementation with Lactobacillus can alleviate the inflammatory response in OVA mice, inhibit pulmonary fibrosis, and treat asthma.

Use data augmentation for a deep learning classification model with chest X-ray clinical imaging featuring coal workers' pneumoconiosis.

PURPOSE: This paper aims to develop a successful deep learning model with data augmentation technique to discover the clinical uniqueness of chest X-ray imaging features of coal workers' pneumoconiosis (CWP). PATIENTS AND METHODS: We enrolled 149 CWP patients and 68 dust-exposure workers for a prospective cohort observational study between August 2021 and December 2021 at First Hospital of Shanxi Medical University. Two hundred seventeen chest X-ray images were collected for this study, obtaining reliable diagnostic results through the radiologists' team, and confirming clinical imaging features. We segmented regions of interest with diagnosis reports, then classified them into three categories. To identify these clinical features, we developed a deep learning model (ShuffleNet V2-ECA Net) with data augmentation through performances of different deep learning models by assessment with Receiver Operation Characteristics (ROC) curve and area under the curve (AUC), accuracy (ACC), and Loss curves. RESULTS: We selected the ShuffleNet V2-ECA Net as the optimal model. The average AUC of this model was 0.98, and all classifications of clinical imaging features had an AUC above 0.95. CONCLUSION: We performed a study on a small dataset to classify the chest X-ray clinical imaging features of pneumoconiosis using a deep learning technique. A deep learning model of ShuffleNet V2 and ECA-Net was successfully constructed using data augmentation, which achieved an average accuracy of 98%. This method uncovered the uniqueness of the chest X-ray imaging features of CWP, thus supplying additional reference material for clinical application.

ESR2 regulates PINK1-mediated mitophagy via transcriptional repression of microRNA-423 expression to promote asthma development.

Asthma represents an inflammatory airway disease related to the induction of airway eosinophilia, mucus overproduction, and bronchial hyperresponsiveness. This study explored the effects of microRNA-423 (miR-423) on mitophagy and inflammation in asthmatic mice challenged with house dust mites (HDMs) and rhinovirus (RV). By searching for differentially expressed miRNAs in the GSE25230 microarray, miR-423 was identified as our target. Moreover, miR-423 was expressed at low levels in the lung tissues from patients with asthma, and agomiR-423 significantly inhibited RV-induced inflammatory injury and activation of inflammasome signaling in mouse lung tissues. Additionally, miR-423 downregulated the expression of IL-1ß/NLRP3/Caspase-1 inflammasome signaling by targeting phosphatase and tensin homolog-induced putative kinase 1 (PINK1). Furthermore, luciferase reporter experiments and ChIP-qPCR assays revealed that estrogen receptor 2 (ESR2) transcriptionally repressed miR-423 expression by coordinating with H3K9me2 modification of the miR-423 promoter histone. Overall, ESR2 synergized with the H3K9me2 modification of the miR-423 promoter histone to transcriptionally repress miR-423 expression and increase PINK1 expression in lung tissues, resulting in asthma exacerbation.

Identification of an ATP/P2X7/mast cell pathway mediating ozone-induced bronchial hyperresponsiveness.

Ozone is a highly reactive environmental pollutant with well-recognized adverse effects on lung health. Bronchial hyperresponsiveness (BHR) is one consequence of ozone exposure, particularly for individuals with underlying lung disease. Our data demonstrated that ozone induced substantial ATP release from human airway epithelia in vitro and into the airways of mice in vivo and that ATP served as a potent inducer of mast cell degranulation and BHR, acting through P2X7 receptors on mast cells. Both mast cell-deficient and P2X7 receptor-deficient (P2X7-/-) mice demonstrated markedly attenuated BHR to ozone. Reconstitution of mast cell-deficient mice with WT mast cells and P2X7-/- mast cells restored ozone-induced BHR. Despite equal numbers of mast cells in reconstituted mouse lungs, mice reconstituted with P2X7-/- mast cells demonstrated significantly less robust BHR than mice reconstituted with WT mast cells. These results support a model where P2X7 on mast cells and other cell types contribute to ozone-induced BHR.

Diagnostic Value of Fractional Exhaled Nitric Oxide and Small Airway Function in Differentiating Cough-Variant Asthma from Typical Asthma.

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.

microRNA-22-3p plays a protective role in a murine asthma model through the inhibition of the NLRP3-caspase-1-IL-1ß axis.

NEW FINDINGS: What is the central question of this study? How does miR-22-3p exert a protective role in asthma? What is the main finding and its importance? Upregulation of miR-22-3p hampered airway inflammation and release of inflammatory cytokines through blocking the activation of the NLRP3-caspase-1-IL-1ß signalling pathway in asthma. ABSTRACT: 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)-1ß. 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-1ß axis and as a protective factor against the inflammatory response, suggesting a future therapeutic role in asthma.

Classification of non-acute bronchial asthma according to allergy and eosinophil characteristics: a retrospective study.

BACKGROUND: Investigating the endotypes of the different asthma phenotypes would help disease monitoring, prognosis determination, and improving asthma management standardization. This study aimed to classify asthma into four endotypes according to the allergic and eosinophilic characteristics and explore the phenotypes (clinical characteristics, pulmonary functions, and fractional expired nitric oxide (FeNO)) of each endotype. METHODS: This retrospective study included non-acute asthma patients treated at the First Hospital of Shanxi Medical University (05/2016-01/2018). The patients were classified into the eosinophilic allergic, eosinophilic non-allergic, non-eosinophilic allergic, and non-eosinophilic non-allergic asthma endotypes. Serum sIgE, lung function, FeNO, and induced sputum cytology were tested and compared among groups. RESULTS: Of the 171 included patients, 22 had eosinophilic allergic asthma, 17 had eosinophilic non-allergic asthma, 66 had non-eosinophilic allergic asthma, and 66 had non-eosinophilic non-allergic asthma. Lung function measurements (FEV1%, FEF25%, FEF50%, FEF75%, and FEF25-75%) showed that airway dysfunction was worse in eosinophilic non-allergic asthma than in the other three endotypes (all P < 0.001). In allergic asthma patients, eosinophilic asthma had worse airway dysfunction than non-eosinophilic asthma (all P < 0.05). Similar results were found in non-allergic asthma (all P < 0.01). The FeNO levels in eosinophilic allergic asthma were higher than in eosinophilic non-allergic and non-eosinophilic non-allergic asthma (both P = 0.001). CONCLUSIONS: FeNO can objectively reflect eosinophilic airway inflammation in asthma. Endotypic classification of asthma patients regarding the allergic and eosinophilic characteristics is conducive to the effective management of patients with asthma.

Changes of clinical characteristics of asymptomatic patients with positive SARS-Cov-2 nucleic acid test during treatment cycle and related risk factors.

OBJECTIVE: This study was designed to explore the clinical characteristics, outcomes, and related influencing factors for asymptomatic patients with positive Severe Acute Respiratory Syndrome Corona Virus 2 (SARS-Cov-2) nucleic acid test. METHODS: Clinical data of 1568 patients with positive SARS-Cov-2 nucleic acid test (SNAT) were collected retrospectively. The patients were assigned to an asymptomatic group and a symptomatic group according to the existence of clinical symptoms when they got positive result in nucleic acid test, and the clinical data of the two groups were analyzed and compared. In addition, the data of asymptomatic patients who showed clinical symptoms later and the results of two-week follow-up after cure were analyzed. RESULTS: Among all enrolled patients, there were 1489 patients with positive symptoms and 79 asymptomatic patients, including 34 patients who developed symptoms during treatment. Logistic analysis revealed that age ≤45 years (OR=2.722, P<0.001), history of diabetes mellitus (OR=0.446, P=0.007), and history of cancer (OR=0.259, P=0.008) were independent factors for asymptomatic presentation in patients with positive SNAT, and age ≥46 years (OR=1.562, P=0.012) and history of hypertension (OR=2.077, P<0.001) were risk factors for the occurrence of clinical symptoms in asymptomatic patients with positive SNAT during hospitalization. During the follow-up after cure, 8 patients got reoccurring positive SNAT result. CONCLUSION: Asymptomatic patients with positive SNAT are mostly young and middle-aged people, and old age and hypertension are risk factors for the occurrence of positive clinical characteristics in asymptomatic patients.

Analysis of COVID-19 epidemic and clinical risk factors of patients under epidemiological Markov model.

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.

Integrated Bioinformatics Analysis Reveals Key Candidate Genes and Cytokine Pathways Involved in COVID-19 After Rhinovirus Infection in Asthma Patients.

BACKGROUND Rhinovirus (RV) is the most common pathogen involved in asthma, and COVID-19, caused by SARS-COV-2, may be more severe in asthma patients. Here, we applied integrated bioinformatics to identify potential key genes and cytokine pathways after RV infection in asthma, and analyzed changes in angiotensin-converting enzyme 2 (ACE2), the cellular receptor of SARS-COV-2. MATERIAL AND METHODS The gene expression profile dataset GSE149273 was downloaded from NCBI-GEO, which included 90 samples of non-infected, RVA, and RVC. Differentially expressed genes (DEGs) were identified using t tests in the limma R package, and subsequently investigated by GO, KEGG, and DO analysis. Moreover, the expression of ACE2 and the proportion of immune cells were further analyzed to determine the effects of RV on cytokines. RESULTS A total of 555 DEGs of RVA and 421 of RVC were identified. There were 415 DEGs in RVA and RVC, of which 406 were upregulated and 9 were downregulated. The functional enrichment analysis showed that most DEGs were obviously enriched in cytokines, and were mainly enriched in "influenza" and "hepatitis C, chronic". In addition, the expression of ACE2 increased significantly and the proportion of immune cytokines significantly changed after RV infection. Our results suggest that RV can activate the cytokine pathway associated with COVID-19 by increasing ACE2. CONCLUSIONS The DEGs and related cytokine pathways after asthma RV infection identified using integrated bioinformatics in this study elucidate the potential link between RV and COVID-19.