Vitamin D3 eradicates Helicobacter pylori by inducing VDR-CAMP signaling

BackgroundVitamin D3 [VitD3, 1,25 (OH)2D3] is known to have immunomodulatory and anti-microbial properties; however, its activity against Helicobacter pylori is unclear. In this study, we established H. pylori infection models in wild-type and VitD3 receptor (VDR) knockdown mice and analyzed the effects of VitD3 and their underlying mechanisms.MethodsVDR+/+ and VDR+/– mice were intragastrically infected with the H. pylori SS1 strain. After confirmation of H. pylori infection, mice were treated with different doses of VitD3. The infection levels in stomach tissues were quantified using the colony-forming assay, and the expression levels of the VDR and cathelicidin antimicrobial peptide (CAMP) in the gastric mucosa were analyzed by immunohistochemistry and western blotting.ResultsThe gastric mucosa of VDR+/– mice was more susceptible to H. pylori colonization and had lower levels of VDR and CAMP expression than that of VDR+/+ mice. H. pylori infection upregulated VDR and CAMP expression in the stomach of both wild-type and mutant mice, and VitD3 treatment resulted in further increase of VDR and CAMP levels, while significantly and dose-dependently decreasing the H. pylori colonization rate in both mouse groups, without affecting blood calcium or phosphorus levels.ConclusionOur data indicate that oral administration of VitD3 reduces the H. pylori colonization rate and upregulates VDR and CAMP expression in the gastric mucosa, suggesting a role for VitD3/VDR/CAMP signaling in the eradication of H. pylori in the stomach. These findings provide important insights into the mechanism underlying the anti-H. pylori activity of VitD3 and should be useful in the development of measures to eradicate H. pylori

Leader-following identical consensus for Markov jump nonlinear multi-agent systems subjected to attacks with impulse

The issue of leader-following identical consensus for nonlinear Markov jump multiagent systems (NMJMASs) under deception attacks (DAs) or denial-of-service (DoS) attacks is investigated in this paper. The Bernoulli random variable is introduced to describe whether the controller is injected with false data, that is, whether the systems are subjected to DAs. A connectivity recovery mechanism is constructed to maintain the connection among multi-agents when the systems are subjected to DoS attack. The impulsive control strategy is adopted to ensure that the systems can normally work under DAs or DoS attacks. Based on graph theory, Lyapunov stability theory, and impulsive theory, using the Lyapunov direct method and stochastic analysis method, the sufficient conditions of identical consensus for Markov jump multi-agent systems (MJMASs) under DAs or DoS are obtained, respectively. Finally, the correctness of the results and the effectiveness of the method are verified by two numerical examples

Epigenetic regulation of human FOXP3+ Tregs: from homeostasis maintenance to pathogen defense

Regulatory T cells (Tregs), characterized by the expression of Forkhead Box P3 (FOXP3), constitute a distinct subset of T cells crucial for immune regulation. Tregs can exert direct and indirect control over immune homeostasis by releasing inhibitory factors or differentiating into Th-like Treg (Th-Treg), thereby actively contributing to the prevention and treatment of autoimmune diseases. The epigenetic regulation of FOXP3, encompassing DNA methylation, histone modifications, and post-translational modifications, governs the development and optimal suppressive function of Tregs. In addition, Tregs can also possess the ability to maintain homeostasis in diverse microenvironments through non-suppressive mechanisms. In this review, we primarily focus on elucidating the epigenetic regulation of Tregs as well as their multifaceted roles within diverse physiological contexts while looking forward to potential strategies involving augmentation or suppression of Tregs activity for disease management, particularly in light of the ongoing global COVID-19 pandemic

The application and research progress of anti-angiogenesis therapy in tumor immunotherapy

Tumor immunotherapy, as the focus of scientific research and clinical tumor treatment in recent years, has received extensive attention. Due to its remarkable curative effect and fewer side effects than traditional treatments, it has significant clinical benefits for the treatment of various advanced cancers and can improve cancer patient survival in the long term. Currently, most patients cannot benefit from immunotherapy, and some patients may experience tumor recurrence and drug resistance even if they achieve remission overcome. Numerous studies have shown that the abnormal angiogenesis state of tumors can lead to immunosuppressive tumor microenvironment, which affects the efficacy of immunotherapy. Actually, to improve the efficacy of immunotherapy, the application of anti-angiogenesis drugs to normalize abnormal tumor vessel has been widely confirmed in basic and clinical research. This review not only discusses the risk factors, mechanisms, and effects of abnormal and normalized tumor angiogenesis state on the immune environment, but summarizes the latest progress of immunotherapy combined with anti-angiogenic therapy. We hope this review provides an applied reference for anti-angiogenesis drugs and synergistic immunotherapy therapy

Operation parameters multi-objective optimization method of large vertical mill based on CFD-DPM

The association mechanism between the main operation parameters and multi-physical fields of the large-scale vertical mill system is unclear, which leads to the difficulty in optimizing operation parameters to improve the performance of large vertical mill systems. To investigate the mechanism of multi-physical field coupling in the operation of the large vertical mill, the numerical simulation method is constructed by coupled CFD-DPM model to calculate the finished product quality, the simulation results were in good agreement with the actual operation results. Based on the Kriging surrogate model, a multi-objective optimization framework for large vertical mills is proposed. Finally, the multi-objective optimization design of LGM large vertical mills is carried out. Combined with CFD-DPM coupling method is developed, design variables and output responses are determined. The Kriging method is used for correlation analysis. The multi-objective optimization function was established. The NSGA-II. optimization algorithm was used to update the surrogate model and obtain the optimal solution, and the optimized operating parameters increased the vertical mill yield by 5.34% and the specific surface area by 9.07%. The maximum relative error between the simulated value and the optimized value is 2.02% through numerical calculation, which verifies the superiority of the optimization method of large vertical mill for performance improvement