142 research outputs found

    Aircraft observations on a continuous haze pollution event in Shijiazhuang area

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    A continuous haze event was recorded on November 14th∼17th, 2020 over Shijiazhuang. Two flights of King-air 350 meteorological research aircraft were performed on November 14th and 16th for the retrieval and observations of meteorological elements, aerosols, and black carbon. In this study, we combined airborne data with air pollution data (PM2.5), ground meteorological data, and ERA-5 reanalysis data to describe the vertical distribution of aerosols (namely 0.1–3.0 μm) and black carbon. We further explicated the formation of this haze event. PM2.5 pollution dominated this haze event, and the highest concentration of PM2.5 was 209 μg/m3. The intensity and height of thermal layers highly linked with the vertical transport of pollution. The highest number concentration of aerosols and black carbon was found below the thermal layers on both airborne sounding days. On the 14th, both BC and aerosol concentrations showed unimodal distribution, and the highest concentrations of BC and aerosols were 12683 ng/m3 and 6965.125#/L at 250 m within layer Ⅰ. The intensity of the thermal layer near-ground was weaker on the 16th that the number concentrations of BC and aerosols also remained at high levels in layer Ⅱ. Backward trajectories of air mass indicated the long-range transport of pollution contributed to the high level of pollution on the 16th. Vapor conditions were more favorable for aerosols growth through moisture absorption. The maximum concentration of 943.58#/L was recorded at particles with a diameter of 0.4 μm on the 16th, while 749.26#/L was reached at 0.14 μm on the 14th. The corresponding height was consistent with the height of maximum concentration in the vertical distribution

    Trans-omics biomarker model improves prognostic prediction accuracy for early-stage lung adenocarcinoma

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    Limited studies have focused on developing prognostic models with trans-omics biomarkers for early-stage lung adenocarcinoma (LUAD). We performed integrative analysis of clinical information, DNA methylation, and gene expression data using 825 early-stage LUAD patients from 5 cohorts. Ranger algorithm was used to screen prognosis-associated biomarkers, which were confirmed with a validation phase. Clinical and biomarker information was fused using an iCluster plus algorithm, which significantly distinguished patients into high- and low-mortality risk groups (Pdiscovery = 0.01 and Pvalidation = 2.71×10-3). Further, potential functional DNA methylation-gene expression-overall survival pathways were evaluated by causal mediation analysis. The effect of DNA methylation level on LUAD survival was significantly mediated through gene expression level. By adding DNA methylation and gene expression biomarkers to a model of only clinical data, the AUCs of the trans-omics model improved by 18.3% (to 87.2%) and 16.4% (to 85.3%) in discovery and validation phases, respectively. Further, concordance index of the nomogram was 0.81 and 0.77 in discovery and validation phases, respectively. Based on systematic review of published literatures, our model was superior to all existing models for early-stage LUAD. In summary, our trans-omics model may help physicians accurately identify patients with high mortality risk

    SIPA1L3 methylation modifies the benefit of smoking cessation on lung adenocarcinoma survival: an epigenomic-smoking interaction analysis

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    Smoking cessation prolongs survival and decreases mortality of patients with non‐small‐cell lung cancer (NSCLC). In addition, epigenetic alterations of some genes are associated with survival. However, potential interactions between smoking cessation and epigenetics have not been assessed. Here, we conducted an epigenome‐wide interaction analysis between DNA methylation and smoking cessation on NSCLC survival. We used a two‐stage study design to identify DNA methylation-smoking cessation interactions that affect overall survival for early‐stage NSCLC. The discovery phase contained NSCLC patients from Harvard, Spain, Norway, and Sweden. A histology‐stratified Cox proportional hazards model adjusted for age, sex, clinical stage, and study center was used to test DNA methylation-smoking cessation interaction terms. Interactions with false discovery rate‐q ≤ 0.05 were further confirmed in a validation phase using The Cancer Genome Atlas database. Histology‐specific interactions were identified by stratification analysis in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) patients. We identified one CpG probe (cg02268510SIPA1L3) that significantly and exclusively modified the effect of smoking cessation on survival in LUAD patients [hazard ratio (HR)interaction = 1.12; 95% confidence interval (CI): 1.07-1.16; P = 4.30 × 10-7]. Further, the effect of smoking cessation on early‐stage LUAD survival varied across patients with different methylation levels of cg02268510SIPA1L3. Smoking cessation only benefited LUAD patients with low methylation (HR = 0.53; 95% CI: 0.34-0.82; P = 4.61 × 10-3) rather than medium or high methylation (HR = 1.21; 95% CI: 0.86-1.70; P = 0.266) of cg02268510SIPA1L3. Moreover, there was an antagonistic interaction between elevated methylation of cg02268510SIPA1L3 and smoking cessation (HRinteraction = 2.1835; 95% CI: 1.27-3.74; P = 4.46 × 10−3). In summary, smoking cessation benefited survival of LUAD patients with low methylation at cg02268510SIPA1L3. The results have implications for not only smoking cessation after diagnosis, but also possible methylation‐specific drug targeting

    Some New Results of Mitrinović–Cusa’s and Related Inequalities Based on the Interpolation and Approximation Method

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    In this paper, new refinements and improvements of Mitrinović–Cusa’s and related inequalities are presented. First, we give new polynomial bounds for sinc(x) and cos(x) functions using the interpolation and approximation method. Based on the obtained results of the above two functions, we establish new bounds for Mitrinović–Cusa’s, Wilker’s, Huygens’, Wu–Srivastava’s, and Neuman–Sándor’s inequalities. The analysis results show that our bounds are tighter than the previous methods

    New Refinements and Improvements of Jordan’s Inequality

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    The polynomial bounds of Jordan’s inequality, especially the cubic and quartic polynomial bounds, have been studied and improved in a lot of the literature; however, the linear and quadratic polynomial bounds can not be improved very much. In this paper, new refinements and improvements of Jordan’s inequality are given. We present new lower bounds and upper bounds for strengthened Jordan’s inequality using polynomials of degrees 1 and 2. Our bounds are tighter than the previous results of polynomials of degrees 1 and 2. More importantly, we give new improvements of Jordan’s inequality using polynomials of degree 5, which can achieve much tighter bounds than those previous methods

    New Polynomial Bounds for Jordan’s and Kober’s Inequalities Based on the Interpolation and Approximation Method

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    In this paper, new refinements and improvements of Jordan’s and Kober’s inequalities are presented. We give new polynomial bounds for the s i n c ( x ) and cos ( x ) functions based on the interpolation and approximation method. The results show that our bounds are tighter than the previous methods
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