Pig BVDV-2 non-structural protein (Npro) links to cellular antiviral response in vitro.

In this study, we constructed for the first time a full-length cDNA clone of pig-original bovine viral diarrhea virus 2 (BVDV-2) strain SH-28, modified the cDNA clone (pASH28) for mutant pASHΔNpro and derived virus strain vASHΔNpro by deleting the genomic region encoding the Npro polypeptide, and examined significance of protein Npro for antiviral responses in vitro. Data showed that Npro-deletion mutant virus vASHΔNpro led to significant overexpression of oligo adenylate synthetase (OAS), myxovirus-resistant protein 1 (Mx1), and ubiquitin-like protein 15 (ISG15). Data also revealed that overexpression of Npro, but not NS2 and NS3 proteins, resulted in significant down-regulation of OAS, Mx1, and ISG15 production (p ≤ 0.05) in bovine cells as well as porcine cells transfected with Npro recombinant eukaryotic expression plasmids. Npro (but not NS2 and NS3) was also found to inhibit poly(IC) from inducing production of type I interferon (IFN-I). These results indicated that protein Npro may play multiple roles in regulating antiviral response in host cells interfered by pig BVDV-2 strain, and provided useful information to understand better the mechanism of BVDV-2 persistent infection in pigs.

A pushing-grasping collaborative method based on deep Q-network algorithm in dual viewpoints.

In the field of intelligent manufacturing, robot grasping and sorting is important content. However, there are some disadvantages in the traditional single-view-based manipulator grasping methods by using a 2D camera, where the efficiency and the accuracy of grasping are both low when facing the scene of stacking and occlusion for the reason that there is information missing by single-view 2D camera-based methods while acquiring scene information, and the methods of grasping only can't change the difficult-to-grasp scene which is stack and occluded. Regarding the issue above, a pushing-grasping collaborative method based on the deep Q-network in dual viewpoints is proposed in this paper. This method in this paper adopts an improved deep Q-network algorithm, with an RGB-D camera to obtain the information of objects' RGB images and point clouds from two viewpoints, which solved the problem of lack of information missing. What's more, it combines the pushing and grasping actions with the deep Q-network, which make it have the ability of active exploration, so that the trained manipulator can make the scenes less stacking and occlusion, and with the help of that, it can perform well in more complicated grasping scenes. In addition, we improved the reward function of the deep Q-network and propose the piecewise reward function to speed up the convergence of the deep Q-network. We trained different models and tried different methods in the V-REP simulation environment, and it drew a conclusion that the method proposed in this paper converges quickly and the success rate of grasping objects in unstructured scenes raises up to 83.5%. Besides, it shows the generalization ability and well performance when novel objects appear in the scenes that the manipulator has never grasped before.

Bovine viral diarrhea virus (BVDV) infections in pigs.

Cattle are the natural hosts of bovine viral diarrhea virus (BVDV), which causes mucosal disease, respiratory and gastrointestinal tract infections, and reproductive problems in cattle. However, BVDV can also infect goats, sheep, deer, and pigs. The prevalence of BVDV infection in pig herds has substantially increased in the last several years, causing increased economic losses to the global pig breeding industry. This article is a summary of BVDV infections in pigs, including a historical overview, clinical signs, pathology, source of infection, genetic characteristics, impacts of porcine BVDV infection for diagnosis of classical swine fever virus (CSFV), differentiation of infection with CSFV and BVDV, and future prospects of porcine BVDV infection.