Background: In December 2019, an outbreak of a novel coronavirus disease (COVID-19; previously known as 2019-nCoV) was reported in Wuhan, Hubei province, China, which has subsequently affected more than 200 countries worldwide including Europe, North America, Oceania, Africa and other places. The number of infected people is rapidly increasing, while the diagnostic method of COVID-19 is only by nucleic acid testing. Objective: To explain the epidemiological characteristics, clinical features, imaging manifestations and to judge diagnostic value of COVID-19 by analyzing the clinical data of COVID-19 suspected and confirmed patients in a non-outbreak, Shanghai, China. To clarify the early epidemiology and clinical characteristics about COVID-19. Methods: Cross-sectional, single-center case reports of the 86 patients screened at Zhoupu Hospital in Pudong New District, Shanghai, China, from January 23 to February 16, 2020. Epidemiology, demography, clinical, laboratory and chest CTs were collected and analyzed. The screened patients were divided into COVID-19 and non-COVID-19 based on nucleic acid test results. Results: Of the 86 screened patients, 11 were confirmed (12.8%) by nucleic acid testing (mean age 40.73 ± 11.32, 5 males). No significant differences were found in clinical symptoms including fever, cough, dyspnea, sore throat, and fatigue (P > 0.05). No statistical difference was observed in plasma C-reactive protein (CRP) between the two groups (COVID-19 and non-COVID-19 ) of patients (P = 0.402), while the white blood cell count and lymphocyte count of the confirmed patients were slightly lower than those of the suspected patients (P < 0.05). Some non-COVID-19 chest CTs also showed subpleural lesions, such as ground-glass opacities (GGO) combined with bronchiectasis; or halo nodules distributed under the pleura with focal GGO; consolidation of subpleural distribution or combined with air bronchi sign and vascular bundle sign, etc. Conclusion: The early clinical manifestations and imaging findings of COVID-19 are not characteristic in non-outbreak areas. Etiological testing should be performed as early as possible for clinically suspected patients.

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Background Lung adenocarcinoma (LUAD) is a type of non-small cell carcinoma. Its pathogenesis is being explored and there is no cure for the disease. Material/Methods The Gene Expression Omnibus (GEO) was searched to obtain data on expression of messenger RNA. GEO2R, an interactive web tool, was used to calculate the differentially expressed genes (DEGs) in LUAD. All the DEGs from different datasets were imported into VENNY 2.1 ( https://bioinfogp.cnb.csic.es/tools/venny/index.html ) to identify the intersection of the DEGs. An online analysis tool, the Database for Annotation, Visualization, and Integrated Discovery (DAVID), was used to help understand the biological meaning of DEG enrichment in LUAD. Cytoscape 3.7.2 was used to perform centrality analysis and visualize hub genes and related networks. Furthermore, the prognostic value of the hub genes was evaluated with the Kaplan-Meier plotter survival analysis tool. Results The GEO database was used to obtain RNA sequencing information for LUAD and normal tissue from the GSE118370, GSE136043, and GSE140797 datasets. A total of 376 DEGs were identified from GSE118370, 248 were identified from GSE136403, and 718 DEGs were identified from GSE140797. The 10 genes with the highest degrees of expression – the hub genes – were CAV1, TEK, SLIT2, RHOJ, DGSX, HLF, MEIS1, PTPRD, FOXF1 , and ADRB2 . In addition, Kaplan-Meier survival evaluation showed that CAV1, TEK, SLIT2, HLF, MEIS1, PTPRD, FOXF1 , and ADRB2 were associated with favorable outcomes for LUAD. Conclusions CAV1, TEK, SLIT2, HLF, MEIS1, PTPRD, FOXF1 , and ADRB2 are hub genes in the DEG interaction network for LUAD and are involved in the development of and prognosis for the disease. The mechanisms underlying these genes should be the subject of further studies.

Background: The differential diagnosis of acute exacerbation of chronic obstructive pulmonary disease (AECOPD) with acute pulmonary embolism (APE) complications are difficult because of the variability of clinical presentations and the shortage of an unfailing screening biomarkers or instruments. Objective: Aimed to detect and compare the expression of serum microRNAs (miR-1233, miR-134) in AECOPD patients complicated with APE. Patients/Methods: Blood samples were collected from 52 AECOPD patients (13 patients with APE complications, 39 patients without APE) and 10 patients with stable COPD. Serum miRNAs expression was detected with real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR). The levels of plasma D-dimers were determined by detection with an enzyme-linked immunosorbent assay (ELISA). The receiver-operator characteristic (ROC) curve was used for evaluating the diagnostic accuracy of the studied miRNAs. Results: According to the Wells score, 42 of the 52 AECOPD patients were unlikely to have APE (≤4 points), whereas the remaining 10 (>4 points) were likely to have APE. There were 4 cases (4/13 30.8%) in the AECOPD combined with APE group with a Wells score of >4 points. The expression levels of miR-1233 and miR-134 in the serum were considerably upregulated in the AECOPD+APE group compared with the AECOPD group and the stable COPD group (P<0.05). The areas under the curve (AUCs) for miR-134 and miR-1233 were, respectively, 0.931 (95% CI 0.863-0.999) (P<0.05) and 0.884 (95% CI 0.79-0.978) (P<0.05) and were higher compared with the AUC for D-dimer of 0.628 (95% CI 0.447-0.809), the AUC for age-adjusted D-dimer of 0.705 (95% CI 0.525-0.885) and the AUC for Wells score of 0.577 (95% CI 0.389-0.765). Conclusion: Our study indicated that serum miR-1233 and miR-134 have high clinical value in the early diagnosis of AECOPD patients combined with APE, or could be used as potential biomarkers for clinical identification of AECOPD with or without APE complication.

Background Obstructive sleep apnea (OSA) increases health risks of cardiovascular disease and stroke. Both genetic factors and environmental exposures contribute to the occurrence of OSA. The purpose of this study was to determine the role of four functional inflammatory single nucleotide polymorphisms (SNPs) (VWF rs1063856, IL‐6 rs1800796, TNF rs1800629, and CRP rs2794521) in the susceptibility and severity of OSA. Methods A case–control study of OSA among Chinese population was conducted. Genotyping was performed using ABI TaqMan SNP genotyping technique. Results We found VWF rs1063856 (OR = 1.50, 95% CIs = 1.10–2.04; p = 0.010), IL‐6 rs1800796 (OR = 1.32, 95% CIs = 1.11–1.56; p = 0.002), TNF rs1800629 (OR = 1.44, 95% CIs = 1.13–1.83; p = 0.003), and CRP rs2794521 (OR = 1.27, 95% CIs = 1.04–1.55; p = 0.021) were all significantly associated with increased susceptibility of OSA, while VWF rs1063856 (OR = 1.75, 95% CIs = 1.18–2.62; p = 0.006), IL‐6 rs1800796 (OR = 1.39, 95% CIs = 1.10–1.76; p = 0.006) were associated with the severity of OSA. Conclusions Our study indicated that functional variants of inflammatory biomarkers could cause the occurrence of OSA and influence the severity of OSA. These findings further support that inflammatory cytokines were closely related to the occurrence and development of OSA.