Biological Characterizations of H5Nx Avian Influenza Viruses Embodying Different Neuraminidases

The H5 subtype virus of Highly Pathogenic Avian Influenza Virus has caused huge economic losses to the poultry industry and is a threat to human health. Until 2010, H5N1 subtype virus was the major genotype in China. Since 2011, reassortant H5N2, H5N6, and H5N8 viruses were identified in domestic poultry in China. The clade 2.3.4.4 H5N6 and H5N8 AIV has now spread to most of China. Clade 2.3.4.4 H5N6 virus has caused 17 human deaths. However, the prevalence, pathogenicity, and transmissibility of the distinct NA reassortment with H5 subtypes viruses (H5Nx) is unknown. We constructed five clade 2.3.4.4 reassortant H5Nx viruses that shared the same HA and six internal gene segments. The NA gene segment was replaced with N1, N2, N6, ΔN6 (with an 11 amino acid deletion at the 58th to 68th of NA stalk region), and N8 strains, respectively. The reassortant viruses with distinct NAs of clade 2.3.4.4 H5 subtype had different degrees of fitness. All reassortant H5Nx viruses formed plaques on MDCK cell monolayers, but the ΔH5N6 grew more efficiently in mammalian and avian cells. The reassortant H5Nx viruses were more virulent in mice as compared to the H5N2 virus. The H5N6 and H5N8 reassortant viruses exhibited enhanced pathogenicity and transmissibility in chickens as compared to the H5N1 reassortant virus. We suggest that comprehensive surveillance work should be undertaken to monitor the H5Nx viruses

IHGA: An interactive web server for large-scale and comprehensive discovery of genes of interest in hepatocellular carcinoma

Mining gene expression data is valuable for discovering novel biomarkers and therapeutic targets in hepatocellular carcinoma (HCC). Although emerging data mining tools are available for pan-cancer–related gene data analysis, few tools are dedicated to HCC. Moreover, tools specifically designed for HCC have restrictions such as small data scale and limited functionality. Therefore, we developed IHGA, a new interactive web server for discovering genes of interest in HCC on a large-scale and comprehensive basis. Integrative HCC Gene Analysis (IHGA) contains over 100 independent HCC patient-derived datasets (with over 10,000 tissue samples) and more than 90 cell models. IHGA allows users to conduct a series of large-scale and comprehensive analyses and data visualizations based on gene mRNA levels, including expression comparison, correlation analysis, clinical characteristics analysis, survival analysis, immune system interaction analysis, and drug sensitivity analysis. This method notably enhanced the richness of clinical data in IHGA. Additionally, IHGA integrates artificial intelligence (AI)–assisted gene screening based on natural language models. IHGA is free, user-friendly, and can effectively reduce time spent during data collection, organization, and analysis. In conclusion, IHGA is competitive in terms of data scale, data diversity, and functionality. It effectively alleviates the obstacles caused by HCC heterogeneity to data mining work and helps advance research on the molecular mechanisms of HCC