The liver is a key, frontline immune tissue, with high exposure to circulating antigens and endotoxins from the gut microbiota, which is also highly concentrated in innate immune cells and chemicals. Tolerance is achieved in homeostasis by several processes that enable the suppression of immunological responses. The liver can rapidly activate immunity in response to infections or tissue damage. Different triggers mediate immune-cell activation depending on the underlying liver disease, such as viral hepatitis, cholestasis, nonalcoholic steatohepatitis (NASH), and hepatocellular carcinoma (HCC). Inflammatory reactions in the liver are triggered by conserved pathways such as molecular danger patterns, Toll-like receptor signaling, or inflammasome activation. The immune system is very complex, especially the molecular network in innate Immunity, and the human brain is unable to handle vast amounts of intricate biological data. In the era of artificial intelligence, an efficient research and development model for multi-omics data experimentation will become feasible through the data analysis and calculation model of machine learning and deep learning. It comprehensively analyzes the complex human immune system, discovers hidden mechanisms and associations, and significantly improves the efficiency of immunology research and the success rate of clinical trials. Specifically, in response to the immunomolecular therapy strategy, screening of tumor markers, molecular detection, and monitoring.
In this Research Topic, we aim to promote the continuous development of the interdisciplinary field of immunity and information, especially the deep learning of innate immune molecules. We welcome submissions that characterize the innate immune molecules, innate immune cell populations and pathways involved in the liver immune responses. We also aim to collect submissions that characterize the involvement of the dysregulation of liver innate immunity in various liver pathologies including, liver fibrosis, alcoholic liver disease (ALD), non-alcoholic fatty liver disease (NAFLD), cirrhosis, chronic infection, autoimmunity, and malignancies. Finally, we will also welcome studies which highlight the potential of the liver innate immune molecules as a therapeutic target for liver pathologies.
In this Research Topic, we welcome the submission of Original Research, Review, and Mini Review articles focusing on molecular innate immune responses and AI data analysis in hepatic disease. We welcome submissions covering, but not limited to, the following sub-topics:
• Innate immune cell populations and immune molecules expressed or secreted by them present in the hepatic disease
• Innate immune pathways regulating liver immunity in hepatic disease
• Innate immune mediators involved in liver immunity and inflammation
• Molecular transcriptional regulation of innate immune responses in hepatic diseases
• Novel therapeutics targeting the liver innate immune system
• Deep neural network analysis of liver innate immune molecule interaction analysis
• Immune molecular network construction, generation, and prediction based on graph representation learning
The liver is a key, frontline immune tissue, with high exposure to circulating antigens and endotoxins from the gut microbiota, which is also highly concentrated in innate immune cells and chemicals. Tolerance is achieved in homeostasis by several processes that enable the suppression of immunological responses. The liver can rapidly activate immunity in response to infections or tissue damage. Different triggers mediate immune-cell activation depending on the underlying liver disease, such as viral hepatitis, cholestasis, nonalcoholic steatohepatitis (NASH), and hepatocellular carcinoma (HCC). Inflammatory reactions in the liver are triggered by conserved pathways such as molecular danger patterns, Toll-like receptor signaling, or inflammasome activation. The immune system is very complex, especially the molecular network in innate Immunity, and the human brain is unable to handle vast amounts of intricate biological data. In the era of artificial intelligence, an efficient research and development model for multi-omics data experimentation will become feasible through the data analysis and calculation model of machine learning and deep learning. It comprehensively analyzes the complex human immune system, discovers hidden mechanisms and associations, and significantly improves the efficiency of immunology research and the success rate of clinical trials. Specifically, in response to the immunomolecular therapy strategy, screening of tumor markers, molecular detection, and monitoring.
In this Research Topic, we aim to promote the continuous development of the interdisciplinary field of immunity and information, especially the deep learning of innate immune molecules. We welcome submissions that characterize the innate immune molecules, innate immune cell populations and pathways involved in the liver immune responses. We also aim to collect submissions that characterize the involvement of the dysregulation of liver innate immunity in various liver pathologies including, liver fibrosis, alcoholic liver disease (ALD), non-alcoholic fatty liver disease (NAFLD), cirrhosis, chronic infection, autoimmunity, and malignancies. Finally, we will also welcome studies which highlight the potential of the liver innate immune molecules as a therapeutic target for liver pathologies.
In this Research Topic, we welcome the submission of Original Research, Review, and Mini Review articles focusing on molecular innate immune responses and AI data analysis in hepatic disease. We welcome submissions covering, but not limited to, the following sub-topics:
• Innate immune cell populations and immune molecules expressed or secreted by them present in the hepatic disease
• Innate immune pathways regulating liver immunity in hepatic disease
• Innate immune mediators involved in liver immunity and inflammation
• Molecular transcriptional regulation of innate immune responses in hepatic diseases
• Novel therapeutics targeting the liver innate immune system
• Deep neural network analysis of liver innate immune molecule interaction analysis
• Immune molecular network construction, generation, and prediction based on graph representation learning
