A novel tRNA-derived fragment tRF-3023b suppresses inflammation in RAW264.7 cells by targeting Cul4a through NF-κB signaling.

The role of transfer RNA (tRNA)-derived fragment (tRF) in various diseases has been established. However, the effect of tRF-3023b on inflammation remains unclear. Inflammation was imitated in RAW264.7 cells by adding Lipopolysaccharide (LPS). Cells were first divided into control, LPS, and LPS + Bulleyaconitine A (BLA) groups. The contents of TNF-α, IL-6, and MCP-1 were quantified using ELISA. The levels of cyclooxygenase-2 (COX2), inducible nitric oxide synthase (iNOS), and the phosphorylation of nuclear factor-kappa B (NF-κB)-P65 (p-P65) were detected by Western blotting. RNA sequencing was utilized to find differentially expressed tRFs (DE-tRFs) among three groups. The levels of various tRFs were checked by quantitative real-time PCR (qRT-PCR). Cell cycle and apoptosis were checked by flow cytometry. Dluciferase reporter assay was applied to predict and confirm the interaction between tRF-3023b and Cullin 4A (Cul4a), subsequently RNA pull-down followed by mass spectrometry analysis were conducted. BLA treatment decreased the contents of TNF-α, IL-6, MCP-1, and the expression levels of COX2, iNOS, p-P65. We found 6 DE-tRFs in LPS + BLA group compared to LPS group, tRF-3023b was high expression in control and BLA groups, and the lowest in LPS group. Cul4a was a direct target of tRF-3023b. tRF-3023b mimic affected the cell cycle distribution, promoted cells apoptosis, and suppressed the TNF-α, IL-6, MCP-1, COX2, iNOS and p-P65. The suppression of Cul4a affected the cell cycle distribution, resulted in an increase of cell apoptosis while a decrease of TNF-α, IL-6, MCP-1, COX2, iNOS and p-P65. Furthermore, Cul4a overexpression reversed the effect of tRF-3023b mimic. Cul4a knockdown reversed the effect of tRF-3023b inhibitor. Our study positions tRF-3023b as a compelling candidate, through its interaction with Cul4a, the underlying mechanism on inflammation maybe related to NF-κB pathway. The study provides a basis for exploring new therapeutic strategies for inflammation.

Nanoparticles of conformation-stabilized canine distemper virus hemagglutinin are highly immunogenic and induce robust immunity.

BACKGROUND: Canine distemper virus (CDV) infection of ferrets, dogs, and giant pandas causes an acute systemic disease involving multiple organ systems, including the respiratory tract, lymphoid system, and central nervous system. In this study, we tested a new candidate CDV vaccine-CDV nanoparticles-based on hemagglutinin protein. METHODS: The nanoparticles were generated from conformation-stabilized CDV hemagglutinin tetramers. Immune responses against CDV were evaluated in mice. Immunization was initiated 6 weeks after birth and boosted two times with 4-week intervals. The blood and mucosal samples were collected 2 weeks after each immunization. RESULTS: Vaccination with CDV nanoparticles elicited high levels of IgG antibody titers in mice (approximately sevenfold to eightfold higher than that obtained with soluble CDV H protein) and mucosal immune responses and developed increased CDV-specific neutralizing antibody. The mice that received nanoparticles showed significantly higher IFN-γ- and IL-4-secreting cell population in the spleen and lymph node compared with mice immunized with soluble H protein. The co-stimulatory molecular expression of CD80 and CD86 on the surface of DCs was also upregulated. CONCLUSION: The results demonstrate that self-assembly into nanoparticles can increase the immunogenicity of vaccine antigens, and nanoparticles assembled from conformation-stabilized CDV H protein can serve as a new CDV vaccine.

Ferroptosis exacerbates hyperlipidemic acute pancreatitis by enhancing lipid peroxidation and modulating the immune microenvironment.

Abnormal activation of ferroptosis worsens the severity of acute pancreatitis and intensifies the inflammatory response and organ damage, but the detailed underlying mechanisms are unknown. Compared with other types of pancreatitis, hyperlipidemic acute pancreatitis (HLAP) is more likely to progress to necrotizing pancreatitis, possibly due to peripancreatic lipolysis and the production of unsaturated fatty acids. Moreover, high levels of unsaturated fatty acids undergo lipid peroxidation and trigger ferroptosis to further exacerbate inflammation and worsen HLAP. This paper focuses on the malignant development of hyperlipidemic pancreatitis with severe disease combined with the core features of ferroptosis to explore and describe the mechanism of this phenomenon and shows that the activation of lipid peroxidation and the aberrant intracellular release of many inflammatory mediators during ferroptosis are the key processes that regulate the degree of disease development in patients with HLAP. Inhibiting the activation of ferroptosis effectively reduces the intensity of the inflammatory response, thus reducing organ damage in patients and preventing the risk of HLAP exacerbation. Additionally, this paper summarizes the key targets and potential therapeutic agents of ferroptosis associated with HLAP deterioration to provide new ideas for future clinical applications.

DMEformer: A newly designed dynamic model ensemble transformer for crude oil futures prediction.

Crude oil futures prediction plays an important role in ensuring sustainable energy development. However, the performance of existing models is not satisfactory, which limits its further application. The poor performance mainly results from the lack of data mining of economic models and the poor stability of most data analysis models. To solve the above problems, this paper proposes a new dynamic model ensemble transformer (DMEformer). The model uses three different Transformer variants as base models. It not only ensures the difference of base models but also makes the prediction results of base models not to appear disparity. In addition, NSGA-II is adopted to ensemble the results of base models, which considers both the modeling stability and accuracy in the optimization. Finally, the proposed model adopts a dynamic ensemble scheme, which could timely adjust the weight vector according to the fluctuation of energy futures. It further improves the reliability of the model. Comparative experiments from the perspective of single models and ensemble models are also designed. The following conclusions can be drawn from the experimental results: (1) The proposed dynamic ensemble method can improve the performance of the base model and traditional static ensemble method by 16% and 5% respectively. (2) DMEformer can achieve better performance than 20 other models, and its accuracy and MAPE values were 72.5% and 2.8043%, respectively. (3) The proposed model can accurately predict crude oil futures, which provides effective support for energy regulation and sustainable development.