ABSTRACT
The rapid development of Internet in recent years has led to a proliferation of social media networks as people who can gather online to share information, knowledge, and opinions. However, the network public opinion tends to generate strongly misleading and a large number of messages can cause shocks to the public once major emergencies appear. Therefore, we need to make correct prediction regarding and timely identify a potential crisis in the early warning of network public opinion. In view of this, this study fully considers the features of development and the propagation characteristics, so as to construct a network public opinion early warning index system that includes 4 first-level indicators and 13 second-level indicators. The weight of each indicator is calculated by the "CRITIC" method, so that the comprehensive evaluation value of each time point can be obtained and the early warning level of internet public opinion can be divided. Then, the Back Propagation neural network based on Genetic Algorithm (GA-BP) is used to establish a network public opinion early warning model. Finally, the major public health emergency, COVID-19 pandemic, is taken as a case for empirical analysis. The results show that by comparing with the traditional classification methods, such as BP neural network, decision tree, random forest, support vector machine and naive Bayes, GA-BP neural network has a higher accuracy rate for early warning of network public opinion. Consequently, the index system and early warning model constructed in this study have good feasibility and can provide references for related research on internet public opinion.
ABSTRACT
Ubiquitination plays a crucial role in retinoic acid-inducible gene I (RIG-I)-induced antiviral responses. However, the precise regulatory mechanisms of RIG-I activity mediated by conjugated and unanchored ubiquitin chains remain to be determined. In this study, we discovered that T55 of RIG-I was required for its binding ability for the unanchored ubiquitin chains. Experimental and mathematical analysis showed that unanchored ubiquitin chains associated with RIG-I were essential for sustained activation of type I interferon (IFN) signaling. Transcriptomics study revealed that the binding of RIG-I with unanchored ubiquitin chains additionally regulated the expression of a subset of metabolic and cell fate decision genes. Moreover, we found that ubiquitin-specific peptidase 21 (USP21) and USP3 deubiquitinate conjugated and unanchored ubiquitin chains on RIG-I respectively. Taken together, characterization of the regulation mode and functions of conjugated ubiquitination and the unconjugated ubiquitin chain-binding of RIG-I may provide means to fine-tune RIG-I-mediated type I IFN signaling.
ABSTRACT
Pediatric-onset colitis and inflammatory bowel disease (IBD) have significant effects on the growth of infants and children, but the etiopathogenesis underlying disease subtypes remains incompletely understood. Here, we report single-cell clustering, immune phenotyping, and risk gene analysis for children with undifferentiated colitis, Crohn's disease, and ulcerative colitis. We demonstrate disease-specific characteristics, as well as common pathogenesis marked by impaired cyclic AMP (cAMP)-response signaling. Specifically, infiltration of PDE4B- and TNF-expressing macrophages, decreased abundance of CD39-expressing intraepithelial T cells, and platelet aggregation and release of 5-hydroxytryptamine at the colonic mucosae were common in colitis and IBD patients. Targeting these pathways by using the phosphodiesterase inhibitor dipyridamole restored immune homeostasis and improved colitis symptoms in a pilot study. In summary, comprehensive analysis of the colonic mucosae has uncovered common pathogenesis and therapeutic targets for children with colitis and IBD.
