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[Display omitted] • To identify the characteristics of research over the past 13 years on mining knowledge from EHRs using AI methods, a mixed analysis was conducted. • Classification and regression are main AI tasks, and decision tree algorithms, deep learning are the most frequently used AI algorithms. • Blood immune system diseases, cancer and circulatory system diseases are main diseases studied. The use of Electronic Health Records is the most important milestone in the digitization and intelligence of the entire medical industry. AI can effectively mine the immense medical information contained in EHRs, potentially assist doctors in reducing many medical errors. This article aims to summarize the research status and trends in using AI to mine medical information from EHRs for the past thirteen years and investigate its information application. A systematic search was carried out in 5 databases, including Web of Science Core Collection and PubMed, to identify research using AI to mine medical information from EHRs for the past thirteen years. Furthermore, bibliometric and content analysis were used to explore the research hotspots and trends, and systematically analyze the conversion rate of research resources in this field. A total of 631 articles were included and analyzed. The number of published articles has increased rapidly after 2017, with an average annual growth rate of 55.73%. The US (41.68%) and China (19.65%) publish the most articles, but there is a lack of international cooperation. The extraction of disease lesions is a hot topic at present, and the research topic is gradually shifting from disease risk grading to disease risk prediction. Classification (66%), and regress (15%) are the main implemented AI tasks. For AI algorithms, deep learning (31.70%), decision tree algorithms family (26.47%), and regression algorithms family (17.43%) are used most frequently. The funding rate for publications is 69.26%, and the input–output conversion rate is 21.05%. Over the past decade, the use of AI to mine medical information from EHRs has been developing rapidly. However, it is necessary to strengthen international cooperation, improve EHRs data availability, focus on interpretable AI algorithms, and improve the resource conversion rate in future research. [ABSTRACT FROM AUTHOR]

Autophagy related 16 like 1 (ATG16L1) is a crucial component of autophagy that regulates the formation of the autophagosome. In mammals, ATG16L1 also performs important roles in immunity, including controlling viral replication and regulating innate immune signaling; however, investigation on the role of piscine ATG16L1 in immunity is rare. In this report, the ATG16L1 homolog of black carp Mylopharyngodon piceus (bcATG16L1) was cloned and identified, and its negative regulatory role in mitochondrial antiviral signaling protein (MAVS)-mediated antiviral signaling was described. The coding region of bcATG16L1 consists of 1830 nucleotides and encodes 609 amino acids, including one coiled-coil domain at the N-terminus, three low complexity region domains in the middle, and seven WD40 domains at the C-terminus. By immunofluorescence assay and immunoblotting, we found that bcATG16L1 is a cytosolic protein with a molecular weight of ∼74 kDa. In addition, over-expression of bcATG16L1 suppressed bcMAVS-mediated bcIFNa and DrIFNφ1 promoters transcriptional activity and inhibited bcMAVS-mediated antiviral activity. We further confirmed the co-localization of bcATG16L1 and bcMAVS by immunofluorescence assay and verified the protein interaction between bcATG16L1 and bcMAVS by immunoprecipitation assay. Our results report for the first time that black carp ATG16L1 suppresses MAVS-mediated antiviral signaling in teleost fish. • bcATG16L1 interacts with bcMAVS. • bcATG16L1 suppresses bcMAVS-mediated activation of bcIFNa and DrIFNφ1 promoters. • bcATG16L1 negatively regulates bcMAVS-mediated antiviral activity. [ABSTRACT FROM AUTHOR]

Interferon regulatory factor 3 (IRF3) is activated by IκB kinase ε (IKKε) and Tank-binding kinase 1 (TBK1), which plays a crucial role in the interferon signaling in vertebrates. However, the regulation of teleost IRF3 by IKKε remains largely unknown. In this study, the IRF3 homologue (bcIRF3) of black carp (Mylopharyngodon piceus) has been cloned and characterized. The transcription of bcIRF3 was detected to increase in host cells in response to different stimuli. bcIRF3 distributed predominantly in the cytosolic area; however, translocated into nuclei after virus infection. bcIRF3 showed IFN-inducing ability in reporter assay and EPC cells expressing bcIRF3 showed enhanced antiviral ability against both grass carp reovirus (GCRV) and spring viremia of carp virus (SVCV). Moreover, knockdown of bcIRF3 reduced the antiviral ability of the host cells, and the transcription of antiviral-related cytokines was obviously lower in bcIRF3-deficient host cells than that of control cells. The data of reporter assay and plaque assay demonstrated that bcIKKε obviously enhanced bcIRF3-mediated IFN production and antiviral activity. Immunofluorescent staining and co-immunoprecipitation assay revealed that bcIKKε interacted with bcIRF3. It was interesting that the nuclear translocation of bcIRF3 and bcIKKε was enhanced by each other when these two molecules were co-expressed in the cells, however, the protein levels of bcIRF3 and bcIKKε were decreased mutually. Thus, our data support the conclusion that bcIKKε interacts with bcIRF3 and enhances bcIRF3-mediated antiviral signaling during host innate immune activation. • bcIKKε interacted with bcIRF3 and enhanced bcIRF3/IFN signaling. • The nuclear translocation of bcIRF3 and bcIKKε was enhanced by each other when co-expressed. • Knockdown of bcIRF3 led to the dampened antiviral activity of the host cells. [ABSTRACT FROM AUTHOR]