The antiviral effects of TRIM23 and TRIM32 proteins in rainbow trout (Oncorhynchus mykiss).

TRIM proteins play a crucial antiviral effector role in the innate immune system of vertebrates. In this study, we found that TRIM proteins exhibited the highest expression levels in immune organs such as spleen and kidney during IHNV infection in rainbow trout, meanwhile, we successfully amplified TRIM23 and TRIM32 from diseased rainbow trout and analyzed their gene sequences, revealing that rainbow trout TRIM23 and TRIM32 proteins are closely related to Atlantic salmon and Chinook salmon; In this experiment, the TRIM23 and TRIM32 protein genes were resoundingly constructed as a recombinant plasmids and expressed in CHSE-214 cells. Upon transfected with the recombinant plasmid, followed by viral infection, significant decreasion in the copy numbers of the virus was observed, indicating that the TRIM23 and TRIM32 proteins of rainbow trout play an important role in inhibiting virus replication, with the TRIM32 role being the most pronounced.

Effects of dietary carbohydrate/lipid ratios on non-specific immune responses, antioxidant capacity, hepatopancreas and intestines histology, and expression of TLR-MAPK/NF-κB signaling pathway-related genes of Procambarus clarkii.

To investigate the effects of dietary carbohydrate/lipid (CHO: L) ratios on non-specific immune responses, antioxidant capacity, and expression of TLR-MAPK/NF-κB signaling pathway-related genes of red swamp crayfish (Procambarus clarkii). Four isonitrogenous and isoenergetic diets containing different CHO: L ratios were formulated. The results showed that the group with a CHO: L ratio of 5.

Image Manipulation Localization Using Attentional Cross-Domain CNN Features.

Along with the advancement of manipulation technologies, image modification is becoming increasingly convenient and imperceptible. To tackle the challenging image tampering detection problem, this article presents an attentional cross-domain deep architecture, which can be trained end-to-end. This architecture is composed of three convolutional neural network (CNN) streams to extract three types of features, including visual perception, resampling, and local inconsistency features, from spatial and frequency domains.