Porcine epidemic diarrhea virus (PEDV) has caused huge economic losses to the global pig industry. The swine enteric coronavirus spike (S) protein recognizes various cell surface molecules to ...regulate viral infection. In this study, we identified 211 host membrane proteins related to the S1 protein by pulldown combined with liquid-chromatography tandem mass spectrometry (LC-MS/MS) analysis. Among these, heat shock protein family A member 5 (HSPA5) was identified through screening as having a specific interaction with the PEDV S protein, and positive regulation of PEDV infection was validated by knockdown and overexpression tests. Further studies verified the role of HSPA5 in viral attachment and internalization. In addition, we found that HSPA5 interacts with S proteins through its nucleotide-binding structural domain (NBD) and that polyclonal antibodies can block viral infection. In detail, HSPA5 was found to be involved in viral trafficking via the endo-/lysosomal pathway. Inhibition of HSPA5 activity during internalization would reduce the subcellular colocalization of PEDV with lysosomes in the endo-/lysosomal pathway. Together, these findings show that HSPA5 is a novel PEDV potential target for the creation of therapeutic drugs.
PEDV infection causes severe piglet mortality and threatens the global pig industry. However, the complex invasion mechanism of PEDV makes its prevention and control difficult. Here, we determined that HSPA5 is a novel target for PEDV which interacts with its S protein and is involved in viral attachment and internalization, influencing its transport via the endo-/lysosomal pathway. Our work extends knowledge about the relationship between the PEDV S and host proteins and provides a new therapeutic target against PEDV infection.
Pseudorabies Virus (PRV) is the causative agent of Pseudorabies (PR), also known as Aujeszky’s Disease, one of the most important infectious diseases in swine, resulting in huge economic losses to ...the swine industry globally. The emergence of mutant PRV strains after 2011 resulted in a sharp decrease in the efficacy of available commercial vaccines. To develop a more effective vaccine that can prevent the spread of PRV, glycoprotein B (gB), glycoprotein C (gC) and glycoprotein D (gD) from recent PRV isolates were expressed in a baculovirus system and their protective efficacy was tested in mice and piglets. Neutralizing antibody titers (NAs) in mice vaccinated with gB, gC and gD peaked at 28 days after immunization and then slowly declined. NAs in the mice immunized with gD were remarkably higher than other groups. After a lethal challenge of 5 LD50 with mutant PRV-HNLH strain, the survival rates of gB and gD were 100% and 87.5% respectively, which was significantly higher than gC group (50%). Piglets vaccinated with the gD and gB + D vaccines developed the highest NAs 7 days post immunization. No piglets in these two groups exhibited clinical symptoms, high body temperature or virus shedding following challenge with 106.6 TCID50 with the mutant PRV-HNLH strain. Histopathology and immunohistochemistry showed remarkably reduced pathological damage and viral loads in gD and gB + D groups. Furthermore, the duration of the NAs induced by gD vaccine could maintain as long as four months after a single dose. The current study indicates that a gD-based vaccine could be developed for the efficient control of PRV.
Depth-map estimation reflects the geometry of the visible surface in the environment directly and plays an important role in perception and decision for intelligent robots. However, sparse LiDAR only ...provides low-resolution depth information, which is a huge challenge for accurate sensing algorithms. To address this problem, this article proposes a novel fusion framework to generate dense depth-map based on event camera and sparse LiDAR. The approach uses the geometric information provided by the point cloud as prior knowledge and clusters point cloud data by an improved density clustering algorithm. Combined with the 3-D surface model of each cluster, the approach can provide 3-D reconstructions of the coordinate points of events and further obtain the dense-depth map by depth expansion and hole filling. Finally, we deploy our approach in MVSEC datasets and real-world applications. Experimental results show that, compared with other approaches, our approach can obtain more accurate depth information.
Abstract
Objectives
This study was aimed to evaluate the protective effects of phenylethanoid glycosides extract from Cistanche deserticola against atherosclerosis and its molecular mechanism.
...Methods
Total phenylethanoid glycosides were extracted and purified from C. deserticola, and the C. deserticola extract (CDE) was used to treat a mice model of atherosclerosis.
Key findings
CDE containing 81.00% total phenylethanoid glycosides, with the contents of echinacoside and acteoside being 31.36% and 7.23%, respectively. A 13-week of CDE supplementation (1000 mg/kg body weight/day) significantly reduced atherosclerotic lesions in the aortic sinus and entire aorta in ApoE−/− mice fed with a high-fat diet. In addition, varying doses of CDE (250, 500 and 1000 mg/kg body weight/day) lowered plasma total cholesterol, triglyceride and non-high-density lipoprotein cholesterol levels. Transcriptomic analysis of the small intestine revealed the changes enriched in cholesterol metabolic pathway and the activation of Abca1 gene. Further validation using real-time quantitative PCR and western blot confirmed that CDE significantly increased the mRNA levels and protein expressions of ABCA1, LXRα and PPARγ.
Conclusions
Our results demonstrate the beneficial effects of C. deserticola on atherosclerotic plaques and lipid homeostasis, and it is, at least partially, by activating PPARγ-LXRα-ABCA1 pathway in small intestine.
Nonalcoholic fatty liver disease (NAFLD) is a multisystem metabolic disease associated with gut microflora dysbiosis and inflammation. Hydrogen (H2) is a novel and effective antiinflammatory agent. ...The present study was aimed to clarify the effects of 4% H2 inhalation on NAFLD and its mechanism of action. Sprague-Dawley rats were fed a high-fat diet for 10 weeks to induce NAFLD. Rats in treatment group inhaled 4% H2 each day for 2 h. The protective effects on hepatic histopathology, glucose tolerance, inflammatory markers, and intestinal epithelial tight junctions were assessed. Transcriptome sequencing of liver and 16 S-seq of cecal contents were also performed to explore the related mechanisms of H2 inhalation. H2 improved the hepatic histological changes and glucose tolerance, decreased the liver function parameters of plasma alanine aminotransferase and aspartate aminotransferase, and relieved liver inflammation. Liver transcriptomic data suggested that H2 treatment significantly downregulated inflammatory response genes, and the lipopolysaccharide (LPS)/Toll-like receptor (TLR) 4/nuclear transcription factor kappa B (NF-κB) signaling pathway might be involved, and the expressions of critical proteins were further validated. Meanwhile, the plasma LPS level was significantly decreased by the H2 intervention. H2 also improved the intestinal tight junction barrier by enhancing the expressions of zonula occludens-1 and occluding. Based on 16S rRNA sequencing, H2 altered the composition of gut microbiota, improving the relative abundance of Bacteroidetes-to-Firmicutes. Collectively, our data show that H2 could prevent NAFLD induced by high-fat diet, and the anti-NAFLD effect is associated with the modulation of gut microbiota and inhibition of LPS/TLR4/NF-κB inflammatory pathway.
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•We study the interactive heterogeneity of edge-strategies in multi-game.•When multiple heterogeneities are combined, the level of cooperation may be reduced.•Players are allowed to adopt different ...strategies for different neighbors.
In real-world social networks, the diversity of social members usually affects the decision-making behaviors in daily human life. Here, to better capture the interaction characteristics of realistic individuals, we explore the evolution of cooperative behaviour in multi-game under interactive heterogeneity based on edge dynamics. Simulation results show that interactive heterogeneity can lead to the formation of larger clusters of cooperators in the network and significantly improve the cooperative behaviour of the group. However, when interactive heterogeneity and network heterogeneity coexist, worse results are obtained.
Accurate measurement of inclined oil-water two-phase flows is vital for guiding reservoir management. Internal waves in such flows present a major challenge to production logging in oil wells. This ...study combines an electromagnetic flowmeter and a differential pressure sensor to measure the inclined oil-water flows in a 20-mm pipe. To address the problem that the Flores flow pattern map is unsuitable for predicting flow patterns in the small diameter pipe, recurrence plots based on differential pressure signals are used for effective identification of the experimental flow patterns. The ideal water holdup is measured by correlating the two-phase friction factor and the Reynolds number of the mixture fluid. Based on the water holdup and the flow pattern classification, a new meter factor model is developed to correct the electromagnetic flowmeter. Then, the individual phase superficial velocity is predicted in combination with the drift-flux model. These contributions provide a new perspective on the combined measurement of inclined oil-water flows.
Computational analysis of paratope-epitope interactions between antibodies and their corresponding antigens can facilitate our understanding of the molecular mechanism underlying humoral immunity and ...boost the design of new therapeutics for many diseases. The recent breakthrough in artificial intelligence has made it possible to predict protein-protein interactions and model their structures. Unfortunately, detecting antigen-binding sites associated with a specific antibody is still a challenging problem. To tackle this challenge, we implemented a deep learning model to characterize interaction patterns between antibodies and their corresponding antigens. With high accuracy, our model can distinguish between antibody-antigen complexes and other types of protein-protein complexes. More intriguingly, we can identify antigens from other common protein binding regions with an accuracy of higher than 70% even if we only have the epitope information. This indicates that antigens have distinct features on their surface that antibodies can recognize. Additionally, our model was unable to predict the partnerships between antibodies and their particular antigens. This result suggests that one antigen may be targeted by more than one antibody and that antibodies may bind to previously unidentified proteins. Taken together, our results support the precision of antibody-antigen interactions while also suggesting positive future progress in the prediction of specific pairing.
•A deep learning model was implemented to characterize interaction patterns between antibodies and their corresponding antigens.•Our model can distinguish antibody-antigen complexes from other types of protein-protein complexes.•We can identify antigens from other common proteins with only the epitope information.•Our studies provided a useful computational tool to characterize the structure of antibody-antigen interactions.
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