Enhanced transcriptomic resilience following increased alternative splicing and differential isoform production between air pollution conurbations

Adversehealth outcomes caused by ambient particulate matter (PM) pollution occur in a 16progressive process, with neutrophils eliciting inflammation or pathogenesis. We investigated the 17toxico-transcriptomic mechanisms of PM in real-life settings by comparing healthy residents living 18in Beijing and Chengde, the opposing ends of a well-recognised air pollution (AP) corridor in China. 19Beijing recruits (BRs) uniquelyexpressed ~12,000 alternativesplicing (AS)-derived transcripts, 20largely elevating the proportion of transcripts significantly correlated with PM concentration. BRs 21expressed PM-associated isoforms (PMAIs) of PFKFB3and LDHA,encoding enzymes responsible 22for stimulatingand maintaining glycolysis. PMAIsof PFKFB3featured different COOH-terminals, 23targeting PFKFB3 to different sub-cellular functional compartments and stimulating glycolysis. 24PMAIs of LDHAhavelonger 3’UTRs relative to those expressed in Chengderecruits (CRs),allowing 25glycolysis maintenance by enhancing LDHAmRNA stability and translational efficiency. PMAIs 26weredirectly regulated by different HIF-1Aand HIF-1Bisoforms. BRs expressed more non-func-27tional Fasisoforms and a resultant reduction of intact Fasproportion is expectedto inhibit the trans-28mission of apoptotic signals and prolong neutrophil lifespan. BRs expressed both membrane-bound 29and soluble IL-6Risoforms insteadof only one in CRs. The presence of both IL-6Risoforms sug-30gested a higher migration capacity of neutrophils in BRs. PMAIs of HIF-1Aand PFKFB3were down-31regulated inChronic Obstructive Pulmonary Disease patients compared with BRs, implying HIF-1 32mediated defective glycolysis may mediate neutrophil dysfunction. PMAIs could explain large var-33iances of different phenotypes, highlighting their potential application as biomarkers and therapeu-34tic targets in PM-induced diseases, which remain poorly elucidated

Support Vector Machine Regression Algorithm Based on Chunking Incremental Learning

Abstract. On the basis of least squares support vector machine regression (LSSVR), an adaptive and iterative support vector machine regression algorithm based on chunking incremental learning (CISVR) is presented in this paper. CISVR is an iterative algorithm and the samples are added to the working set in batches. The inverse of the matrix of coefficients from previous iteration is used to calculate the regression parameters. Therefore, the proposed approach permits to avoid the calculation of the inverse of a large-scale matrix and improves the learning speed of the algorithm. Support vectors are selected adaptively in the iteration to maintain the sparseness. Experimental results show that the learning speed of CISVR is improved greatly compared with LSSVR for the similar training accuracy. At the same time the number of the support vectors obtained by the presented algorithm is less than that obtained by LSSVR greatly

Machine Learning-Based Keywords Extraction for Scientific Literature

Abstract: With the currently growing interest in the Semantic Web, keywords/metadata extraction is coming to play an increasingly important role. Keywords extraction from documents is a complex task in natural languages processing. Ideally this task concerns sophisticated semantic analysis. However, the complexity of the problem makes 1472 current semantic analysis techniques insufficient. Machine learning methods can support the initial phases of keywords extraction and can thus improve the input to further semantic analysis phases. In this paper we propose a machine learning-based keywords extraction for given documents domain, namely scientific literature. More specifically, the least square support vector machine is used as a machine learning method. The proposed method takes the advantages of machine learning techniques and moves the complexity of the task to the process of learning from appropriate samples obtaine

Adverse events of pirfenidone for the treatment of pulmonary fibrosis: a meta-analysis of randomized controlled trials.

BACKGROUND: Pirfenidone (PFD) is a novel antifibrotic agent approved for patients with pulmonary fibrosis. However, there are concerns regarding toxicity of the drug. In this meta-analysis, we analyzed the adverse events (AEs) of PFD for the treatment of pulmonary fibrosis. METHODS: We performed a systematic search of PubMed, Embase, ClinicalTrials.gov, and Cochrane Central Register of Controlled Trials for trials published between January 1999 and October 2011. Data extracted from literature were analyzed with Review manager 5.0.24. RESULTS: The results of six randomized controlled trials (1073 participants) revealed that the number of individuals who discontinued PFD therapy was significantly higher than patients receiving placebo. The PFD group had a significantly higher rate of gastrointestinal (nausea, dyspepsia, diarrhea, and anorexia), neurological (dizziness and fatigue), and dermatological (photosensitivity and rash) AEs compared to the placebo group. CONCLUSIONS: PFD used for the treatment of pulmonary fibrosis is not so safe or well-tolerated. Notably, gastrointestinal, neurological and dermatological adverse effects were more common in patients receiving PFD therapy, and therefore appropriate precaution is needed

Fasudil, a Rho-Kinase Inhibitor, Attenuates Bleomycin-Induced Pulmonary Fibrosis in Mice

The mechanisms underlying the pathogenesis of idiopathic pulmonary fibrosis (IPF) involve multiple pathways, such as inflammation, epithelial mesenchymal transition, coagulation, oxidative stress, and developmental processes. The small GTPase, RhoA, and its target protein, Rho-kinase (ROCK), may interact with other signaling pathways known to contribute to pulmonary fibrosis. This study aimed to determine the beneficial effects and mechanisms of fasudil, a selective ROCK inhibitor, on bleomycin-induced pulmonary fibrosis in mice. Our results showed that the Aschcroft score and hydroxyproline content of the bleomycin-treated mouse lung decreased in response to fasudil treatment. The number of infiltrated inflammatory cells in the bronchoalveolar lavage fluid (BALF) was attenuated by fasudil. In addition, fasudil reduced the production of transforming growth factor-β1 (TGF-β1), connective tissue growth factor (CTGF), alpha-smooth muscle actin (α-SMA), and plasminogen activator inhibitor-1 (PAI-1) mRNA and protein expression in bleomycin-induced pulmonary fibrosis. These findings suggest that fasudil may be a potential therapeutic candidate for the treatment of pulmonary fibrosis

Imbalance between Th17 and Regulatory T-Cells in Sarcoidosis

Sarcoidosis is a systemic granulomatous disease, which is thought to result from an aberrant immune response. CD4+ T lymphocytes play an important role in the development of granulomas. Previously, the immunopathogenesis of sarcoidosis was focused on Th1/Th2 disturbances. The aim of this study was to evaluate the balance between newer CD4+ T lymphocytes, i.e., Treg and Th17 cells. In our studies, a decrease in Treg cells and an increase in Th17 cells were observed in the peripheral blood and BALF of sarcoidosis patients. A significant increase in the Th17/Treg cell ratio was observed in sarcoidosis patients. After treatment with prednisone, the expression of Foxp3 mRNA was elevated in the peripheral blood, and expression of (ROR)γt mRNA showed a downward trend. These findings suggest that sarcoidosis is associated with an imbalance between Th17 and Treg cells in peripheral blood and BALF. Therefore, targeting the cytokines that affect the Th17/Treg ratio could provide a new promising therapy for pulmonary sarcoidosis

Clinical manifestations and prognostic factors analysis of patients hospitalised with acute exacerbation of idiopathic pulmonary fibrosis and other interstitial lung diseases

Background Acute exacerbation (AE) is a life-threatening condition taking place not only in idiopathic pulmonary fibrosis (IPF) but also in interstitial lung diseases (ILD) other than IPF (non-IPF ILD). This study aims to compare the clinical manifestations between patients hospitalised with AE-IPF and AE-non-IPF ILD, and further analyse the risk factors related to in-hospital mortality.Methods Clinical data of 406 patients hospitalised with AE-IPF (93 cases) and AE-non-IPF ILD (313 cases) were retrospectively collected. Clinical features were compared between the two groups. Risk factors related to in-hospital mortality in patients with overall AE-ILD, AE-IPF and AE-non-IPF ILD were identified by multiple logistic regression analyses, respectively, and assessed by receiver operating characteristic curve.Results In addition to having more smokers and males, the AE-IPF group also had more respiratory failure on admission, comorbidities of pulmonary hypertension (PAH) or coronary artery disease/heart failure, a longer history of pre-existing ILD. Comorbidity of coronary heart disease/heart failure, respiratory failure at admission, neutrophil (N)%, serum hydroxybutyrate dehydrogenase (HBDH), lactate dehydrogenase (LDH) and low cholesterol levels were independent risk factors for patients with AE-ILD, while respiratory failure on admission, N%, serum HBDH, urea nitrogen, LDH and low albumin levels were risk factors for the AE-non-IPF ILD group, and fever, N% and PAH were the AE-IPF group’s. Among them, HBDH 0.758 (sensitivity 85.5%, specificity 56%, cut-off 237.5 U/L) for patients with AE-ILD; N% 0.838 (sensitivity 62.5%, specificity 91.18%, cut-off 83.55%) for the AE-IPF group and HBDH 0.779 (sensitivity 86.4%, specificity 55.1%, cut-off 243.5 U/L) for the AE-non-IPF ILD group were the risk factors with the highest area under the curve.Conclusions Clinical characteristics differ between patients with AE-IPF and AE-non-IPF ILD. HBDH outperformed LDH in predicting the prognosis for patients with AE-ILD and AE-non-IPF ILD. N% was an independent predictor of death in-hospital in all three groups, especially in the AE-IPF group

Score risk model for predicting severe fever with thrombocytopenia syndrome mortality

Abstract Background Severe fever with thrombocytopenia syndrome (SFTS) is an emerging epidemic infectious disease with high mortality in East Aisa, especially in China. To predict the prognosis of SFTS precisely is important in clinical practice. Methods From May 2013 to November 2015, 233 suspected SFTS patients were tested for SFTS virus using RT-PCR. Cox regression model was utilized to comfirm independent risk factors for mortality. A risk score model for mortality was constructed based on regression coefficient of risk factors. Log-rank test was used to evaluate the significance of this model. Results One hundred seventy-four patients were confirmed with SFTS, of which 40 patients died (23%). Baseline age, serum aspartate aminotransferase (AST) and serum creatinine (sCr) level were independent risk factors of mortality. The area under ROC curve (AUCs) of these parameters for predicting death were 0.771, 0.797 and 0.764, respectively. And hazard ratio (HR) were 1.128, 1.002 and 1.013, respectively. The cutoff value of the risk model was 10. AUC of the model for predicting mortality was 0.892, with sensitivity and specificity of 82.5 and 86.6%, respectively. Log-rank test indicated strong statistical significance (\ud7 2 \u2009=\u200988.35, p \u2009<\u20090.001). Conclusions This risk score model may be helpful to predicting the prognosis of SFTS patients

Correlation between white blood cell count at admission and mortality in COVID-19 patients: a retrospective study

Abstract Background Coronavirus disease-19 (COVID-19) has become a world health threaten. Its risk factors with death were still not known. White blood cells (WBC) count as a reflection of inflammation has played a vital role in COVID-19, however its level with death is not yet investigated. Methods In this retrospective, single-center study, all confirmed patients with COVID-19 at West Branch of Union Hospital from Jan 29 to Feb 28, 2020 were collected and analyzed. Demographic and clinical data including laboratory examinations were analyzed and compared between recovery and death patients. Results A total of 163 patients including 33 death cases were included in this study. Significant association was found between WBC count and death (HR = 1.14, 95%CI: 1.09–1.20, p  6.16 × 10^9/L). The difference was still exist after adjusting for confounding factors (HR = 6.26, 95%CI: 1.72–22.77, p = 0.005). In addition, Kaplan-meier survival analysis showed that there was a significant decline of the cumulative survival rate (p < 0.001) in those with WBC count ≥6.16 × 10^9/L. Conclusion WBC count at admission is significantly corelated with death in COVID-19 patients. Higher level of WBC count should be given more attention in the treatment of COVID-19

Upper respiratory tract microbiota is associated with small airway function and asthma severity

Abstract Background Characteristics of airway microbiota might influence asthma status or asthma phenotype. Identifying the airway microbiome can help to investigate its role in the development of asthma phenotypes or small airway function. Methods Bacterial microbiota profiles were analyzed in induced sputum from 31 asthma patients and 12 healthy individuals from Beijing, China. Associations between small airway function and airway microbiomes were examined. Results Composition of sputum microbiota significantly changed with small airway function in asthma patients. Two microbiome-driven clusters were identified and characterized by small airway function and taxa that had linear relationship with small airway functions were identified. Conclusions Our findings confirm that airway microbiota was associated with small airway function in asthma patients