HIV-1 Vpu and SARS-CoV-2 ORF3a proteins disrupt STING-mediated activation of antiviral NF-κB signaling.

Activation of the stimulator of interferon genes (STING) pathway by cytosolic DNA leads to the activation of the transcription factors interferon regulatory factor 3 (IRF3) and nuclear factor κB (NF-κB). Although many viruses produce proteins that inhibit IRF3-dependent antiviral responses, some viruses produce proteins that inhibit STING-induced NF-κB activation without blocking IRF3 activation. Here, we found that STING-activated, NF-κB-dependent, and IRF3-independent innate immunity inhibited the replication of the DNA virus herpes simplex virus type 1 (HSV-1), the RNA virus coxsackievirus A16 (CV-A16), and the retrovirus HIV-1.

A glimpse into viral warfare: decoding the intriguing role of highly pathogenic coronavirus proteins in apoptosis regulation.

Coronaviruses employ various strategies for survival, among which the activation of endogenous or exogenous apoptosis stands out, with viral proteins playing a pivotal role. Notably, highly pathogenic coronaviruses such as SARS-CoV-2, SARS-CoV, and MERS-CoV exhibit a greater array of non-structural proteins compared to low-pathogenic strains, facilitating their ability to induce apoptosis via multiple pathways. Moreover, these viral proteins are adept at dampening host immune responses, thereby bolstering viral replication and persistence.

SARS-CoV-2 ORF3a inhibits cGAS-STING-mediated autophagy flux and antiviral function.

Recognizing aberrant cytoplasmic dsDNA and stimulating cGAS-STING-mediated innate immunity is essential for the host defense against viruses. Recent studies have reported that SARS-CoV-2 infection, responsible for the COVID-19 pandemic, triggers cGAS-STING activation. cGAS-STING activation can trigger IRF3-Type I interferon (IFN) and autophagy-mediated antiviral activity.

Examining Bayesian network modeling in identification of dangerous driving behavior.

Traffic safety problems are still very serious and human factor is the one of most important factors affecting traffic crashes. Taking Next Generation Simulation (NGSIM) data as the research object, this study defines six control indicators and uses principal component analysis and K-means++ clustering methods to get the driving style of different drivers. Then use the Bayesian Networks Toolbox (BNT) and MCMC algorithm to realize the structure learning of Bayesian network.