BackgroundNo clinically proven effective antiviral strategy exists for the epidemic Coronavirus Disease 2019 . MethodsWe conducted a prospective, randomized, controlled, open-label multicenter trial involving adult patients with COVID-19. Patients were randomly assigned in a 1:1 ratio to receive conventional therapy plus Umifenovir (Arbidol) (200mg*3/day) or Favipiravir (1600mg*2/first day followed by 600mg*2/day) for 10 days. The primary outcome was clinical recovery rate of Day 7. Latency to relief for pyrexia and cough, the rate of auxiliary oxygen therapy (AOT) or noninvasive mechanical ventilation (NMV) were the secondary outcomes. Safety data were collected for 17 days.

Background: In addition to supportive therapy, antiviral therapy is an effective treatment for coronavirus disease 2019 (COVID-19).Objective: To compare the efficacy and safety of favipiravir and umifenovir (Arbidol) to treat COVID-19 patients.Methods: We conducted a prospective, randomized, controlled, open-label multicenter trial involving adult patients with COVID-19. Enrolled patients with initial symptoms within 12 days were randomly assigned in a 1:1 ratio to receive conventional therapy plus Arbidol (200 mg*3/day) or favipiravir (1600 mg*2/first day followed by 600 mg*2/day) for 7 days. The primary outcome was the clinical recovery rate at day 7 of drug administration (relief for pyrexia and cough, respiratory frequency ≤24 times/min; oxygen saturation ≥98%). Latency to relief for pyrexia and cough and the rate of auxiliary oxygen therapy (AOT) or noninvasive mechanical ventilation (NMV)/mechanical ventilation (MV) were the secondary outcomes. Safety data were collected for 17 days.Results: A total of 240 enrolled COVID-19 patients underwent randomization; 120 patients were assigned to receive favipiravir (116 assessed), and 120 patients were assigned to receive Arbidol (120 assessed). The clinical recovery rate at day 7 of drug administration did not significantly differ between the favipiravir group (71/116) and Arbidol group (62/120) (p = 0.1396, difference in recovery rate: 0.0954; 95% CI: −0.0305∼0.2213). Favipiravir contributed to relief for both pyrexia (difference: 1.70 days, p < 0.0001) and cough (difference: 1.75 days, p < 0.0001). No difference was observed in the AOT or NMV/MV rate (both p > 0.05). The most frequently observed favipiravir-associated adverse event was increased serum uric acid (16/116, OR: 5.52, p = 0.0014).Conclusion: Among patients with COVID-19, favipiravir, compared to Arbidol, did not significantly improve the clinical recovery rate at day 7. Favipiravir significantly improved the latency to relieve pyrexia and cough. Adverse effects caused by favipiravir are mild and manageable.

Human clear cell renal cell carcinoma (ccRCC) is the most common solid lesion within kidney, and its prognostic is influenced by the progression covering a complex network of gene interactions. In our study, we screened differential expressed genes, and constructed protein-protein interaction (PPI) network and a weighted gene co-expression network to identify key genes and pathways associated with the progression of ccRCC (n = 56). Functional and pathway enrichment analysis demonstrated that upregulated differentially expressed genes (DEGs) were significantly enriched in response to wounding, positive regulation of immune system process, leukocyte activation, immune response and cell activation. Downregulated DEGs were significantly enriched in oxidation reduction, monovalent inorganic cation transport, ion transport, excretion and anion transport. In the PPI network, top 10 hub genes were identified (TOP2A, MYC, ALB, CDK1, VEGFA, MMP9, PTPRC, CASR, EGFR and PTGS2). In co-expression network, 6 ccRCC-related modules were identified. They were associated with immune response, metabolic process, cell cycle regulation, angiogenesis and ion transport. In conclusion, our study illustrated the hub genes and pathways involved in the progress of ccRCC, and further molecular biological experiments are needed to confirm the function of the candidate biomarkers in human ccRCC.

Breast cancer is one of the most common malignancies among females, and its prognosis is affected by a complex network of gene interactions. In this study, we constructed free-scale gene co-expression networks using weighted gene co-expression network analysis (WGCNA). The gene expression profiles of GSE25055 were downloaded from the Gene Expression Omnibus (GEO) database to identify potential biomarkers associated with breast cancer progression. GSE42568 was downloaded for validation. A total of 9 modules were established via the average linkage hierarchical clustering. We identified 3 hub genes (ASPM, CDC20, and TTK) in the significant module ( R 2 = 0.52), which were significantly correlated with poor prognosis both in test and validation datasets. In the datasets GSE25055 and GSE42568, higher expression levels of ASPM, CDC20, and TTK correlated with advanced tumor grades. Immunohistochemistry data from the Human Protein Atlas also demonstrated that their protein levels were higher in tumor samples. According to gene set enrichment analysis, 4 commonly enriched pathways were identified: cell cycle pathway, DNA replication pathway, homologous recombination pathway, and P53 signaling pathway. In addition, strong correlations were found among their expression levels. In conclusion, our WGCNA analysis identified candidate prognostic biomarkers for further basic and clinical researches.

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