Although huge progress has been made in therapeutics against hepatocellular carcinoma (HCC) over the decades, the prognosis of this lethal disease remains poor. To find out risk factors for HCC-related outcome and better predict the prognosis, there is an unmet need to identify novel biomarkers of HCC. Accumulating evidence suggests that circRNAs play pivotal roles in carcinogenesis of several malignancies. In this study, we analyzed two datasets (GSE 94508 and GSE 97332) to examine differentially expressed circRNAs markedly related to HCC pathogenesis. Using Limma package in R and WGCNA analysis, hsa_circ_0000517 was significantly up-regulated in HCC (adjusted P < 0.01). Thereafter, a hsa_circ_0000517-related regulatory network was built based on application of databases including CSCD, TargetScan, miRDB, and miRTarBase. We uncovered the potential function of hsa_circ_0000517 through bioinformatics approaches, such as PPI network, GO, and KEGG pathway analyses. Specifically, functional analysis unveiled that hsa_circ_0000517 was likely to regulate the MAPK and Ras pathway through sponging several miRNAs and having an impact on the expression of TP53, MYC, and AKT1. To verify our initial finding, the expression of hsa_circ_0000517 in 60 HCC patients was detected by qRT-PCR and the expression in cancer tissues was higher compared with the paracarcinoma tissues. Survival analysis suggests high hsa_circ_0000517 expression was associated with adverse prognosis in HCC patients. Furthermore, this circRNA was significantly up-regulated in worse TNM stage, consistent with the progressive-stage-specific characteristic of circRNAs. A prognostic nomogram built on AFP and has_circ_0000517 showed significant diagnostic value. In all, we concluded that hsa_circ_0000517, a promising molecular in underlying mechanism of HCC, is a potent valuable biomarker for prognosis prediction.

A study on the relationships between ambient air pollutants (PM2.5, SO2 and NO2) and hospital emergency room visits (ERVs) for respiratory diseases from 2013 to 2014 was performed in both urban and suburban areas of Jinan, a heavily air-polluted city in Eastern China. This research was analyzed using generalized additive models (GAM) with Poisson regression, which controls for long-time trends, the “day of the week” effect and meteorological parameters. An increase of 10 μg/m3 in PM2.5, SO2 and NO2 corresponded to a 1.4% (95% confidence interval (CI): 0.7%, 2.1%), 1.2% (95% CI: 0.5%, 1.9%), and 2.5% (95%: 0.8%, 4.2%) growth in ERVs for the urban population, respectively, and a 1.5% (95%: 0.4%, 2.6%), 0.8% (95%: −0.7%, 2.3%), and 3.1% (95%: 0.5%, 5.7%) rise in ERVs for the suburban population, respectively. It was found that females were more susceptible than males to air pollution in the urban area when the analysis was stratified by gender, and the reverse result was seen in the suburban area. Our results suggest that the increase in ERVs for respiratory illnesses is linked to the levels of air pollutants in Jinan, and there may be some urban-suburban discrepancies in health outcomes from air pollutant exposure.

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