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Allergic rhinitis (AR) is a global health problem with increasing prevalence and association with an enormous medical and socioeconomic burden. New recognition of immune cells such as type 2 innate lymphocytes (ILC2s), T helper (Th2) 2 cells, follicular helper T cells, follicular regulatory T cells, regulatory T cells, B cells, dendritic cells, and epithelial cells in AR pathogenesis has been updated in this review paper. An in‐depth understanding of the mechanisms underlying AR will aid the identification of biomarkers associated with disease and ultimately provide valuable parameters critical to guide personalized targeted therapy. As the only etiological treatment option for AR, allergen‐specific immunotherapy (AIT) has attracted increasing attention, with evidence for effectiveness of AIT recently demonstrated in several randomized controlled trials and long‐term real‐life studies. The exploration of biologics as therapeutic options has only involved anti‐IgE and anti‐type 2 inflammatory agents; however, the cost‐effectiveness of these agents remains to be elucidated precisely. In the midst of the currently on‐going COVID‐19 pandemic, a global life‐threatening disease, although some studies have indicated that AR is not a risk factor for severity and mortality of COVID‐19, this needs to be confirmed in multi‐centre, real‐life studies of AR patients from different parts of the world. [ABSTRACT FROM AUTHOR]

• FOXP3 controls Treg differentiation and activity. • FOXP3 induces metabolic versatility in intra-tumoral Tregs. • Treg subsets show different reliance on FOXP3. Dysregulation of regulatory T cells (Tregs) is described in the context of inflammatory and autoimmune diseases, and cancer. Forkhead box P3 (FOXP3) is a transcription factor that its activity is an indicator of Treg identity. FOXP3 induces metabolic versatility in intra-tumoral Tregs, so that its deficiency mediates Treg instability or even gives rise to the acquisition of effector T cell phenotype. FOXP3 dysregulation and defectiveness occurs upon ubiquitination, methylation and presumably acetylation. Stimulators of PTEN, mammalian target of rapamycin complex 2 (mTORC2), and nucleus accumbens–associated protein-1 (NAC1), and inhibitors of B lymphocyte-induced maturation protein-1 (Blimp-1), Deltex1 (DTX1) and ubiquitin-specific peptidase 22 (USP22) are suggested to hamper FOXP3 stability, and to promote its downregulation and further Treg depletion. A point is that Treg subsets reveal different reliance on FOXP3, which indicates that not all Tregs are strictly dependent on FOXP3, and presumably Tregs with different origin rely on diverse regulators of FOXP3 stability. The focus of this review is over the current understanding toward FOXP3, its activity in Tregs and influence from different regulators within tumor microenvironment (TME). Implication of FOXP3 targeting in cancer immunotherapy is another focus of this paper. [ABSTRACT FROM AUTHOR]

Background: Clinical studies have shown that the efficacy of programmed cell death receptor-1/programmed cell death ligand-1 (PD-1/PD-L1) inhibitors on glioblastoma (GBM) is much lower than what is expected because of the low immunogenicity of GBM. Ferroptosis of cancer cells can induce the maturation of dendritic cells (DC cells) and increase the activity of T cell. The activated T cells release IFN-γ, which subsequently induces the ferroptosis of cancer cells. Thus, the aim of this paper is to set up a new GBM-targeted drug delivery system (Fe3O4-siPD-L1@M-BV2) to boost ferroptosis for immunotherapy of drug-resistant GBM. Results: Fe3O4-siPD-L1@M-BV2 significantly increased the accumulation of siPD-L1 and Fe2+ in orthotopic drug-resistant GBM tissue in mice. Fe3O4-siPD-L1@M-BV2 markedly decreased the protein expression of PD-L1 and increased the ratio between effector T cells and regulatory T cells in orthotopic drug-resistant GBM tissue. Moreover, Fe3O4-siPD-L1@M-BV2 induced ferroptosis of GBM cells and maturation of DC cell, and it also increased the ratio between M1-type microglia and M2-type microglia in orthotopic drug-resistant GBM tissue. Finally, the growth of orthotopic drug-resistant GBM in mice was significantly inhibited by Fe3O4-siPD-L1@M-BV2. Conclusion: The mutual cascade amplification effect between ferroptosis and immune reactivation induced by Fe3O4-siPD-L1@M-BV2 significantly inhibited the growth of orthotopic drug-resistant GBM and prolonged the survival time of orthotopic drug-resistant GBM mice. [ABSTRACT FROM AUTHOR]

• The importance of drug delivery timing and dosage in chemoimmunotherapy has been studied on a new model proposed in the paper. • The optimal controller is designed to reduce cancer cells for a lower dosage of immunotherapy and a fixed dosage of chemotherapy. • The suggested optimal timing and dosage of immunotherapy is able to reduce cancer cells, with less amount of drug injection compared to a fixed protocol. • The achievement of this paper could be the basis for designing new clinical trials. There are various approaches to control a mathematical dynamic of cancer, each of which is suitable for a special goal. Optimal control is considered as an applicable method to calculate the minimum necessary drug delivery in such systems. In this paper, a mathematical dynamic of cancer is proposed considering tumor cells, natural killer cells, CD8+ T cells, circulating lymphocytes, IL-2 cytokine and Regulatory T cells as the system states, and chemotherapy, IL-2 and activated CD8+ T cells injection rate as the control signals. After verifying the proposed mathematical model, the importance of the drug delivery timing and the effect of cancer cells initial condition are discussed. Afterwards, an optimal control is designed by defining a proper cost function with the goal of minimizing the number of tumor cells, and two immunotherapy drug amounts during treatment Results show that inappropriate injection of immunotherapy time schedule and the number of initial conditions of cancer cells might result in chemoimmunotherapy failure and auxiliary treatment must be prescribed to decrease tumor size before any treatment takes place. The obtained optimal control signals show that with lower amount of drug delivery and a suitable drug injection time schedule, tumor cells can be eliminated while a fixed immunotherapy time schedule protocol fails with larger amount of drug injection. This conclusion can be utilized with the aim of personalizing drug delivery and designing more accurate clinical trials based on the improved model simulations in order to save cost and time. [ABSTRACT FROM AUTHOR]

Dendritic cells (DCs) are the dominant class of antigen-presenting cells in humans; therefore, a range of DC-based approaches have been established to promote an immune response against cancer cells. The efficacy of DC-based immunotherapeutic approaches is markedly affected by the immunosuppressive factors related to the tumor microenvironment, such as adenosine. In this paper, based on immunological theories and experimental data, a hybrid model is designed that offers some insights into the effects of DC-based immunotherapy combined with adenosine inhibition. The model combines an individual-based model for describing tumor-immune system interactions with a set of ordinary differential equations for adenosine modeling. Computational simulations of the proposed model clarify the conditions for the onset of a successful immune response against cancer cells. Global and local sensitivity analysis of the model highlights the importance of adenosine blockage for strengthening effector cells. The model is used to determine the most effective suppressive mechanism caused by adenosine, proper vaccination time, and the appropriate time interval between injections. [Display omitted] • We propose a hybrid model to describe the immunosuppressive function of adenosine in tumor micro environment. • Our model provides immunologists with a new level of insight into the role of immunosuppressive factors of the immune system. • Our model highlights the importance of adenosine blockage for strengthening effector cells and suppressing Treg cells. • Model simulations are compatible with in vivo experimental data. • The results reveals that the appropriate time interval for administration of adenosine inhibitor is between 2 and 4 days. [ABSTRACT FROM AUTHOR]