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The tumor microenvironment (TME) plays an important role in the development of tumors. Immunoregulatory cells and cytokines facilitate cancer cells to avoid immune surveillance. Overexpression of immune checkpoint molecules such as CTLA-4 and PD-1/PD-L1 inhibits immune function and enables cancer cells to avoid clearance by the immune system. Thus, minimizing tumor immunosuppression could be an important strategy for cancer therapy. Currently, many immune checkpoint-targeted drugs, such as PD-1/PD-L1 inhibitors, have been approved for marketing and have shown unique advantages in the clinical treatment of cancers. The concept of "strengthening resistance to eliminate pathogenic factors" in traditional Chinese medicine (TCM) is consistent with the immunotherapy of cancer. According to previous studies, the role of TCM in tumor immunotherapy is mainly associated with the positive regulation of natural killer cells, CD8/CD4 T cells, dendritic cells, M2 macrophages, interleukin-2, tumor necrosis factor- α , and IFN- γ , as well as with the negative regulation of Tregs, myeloid-derived suppressor cells, cancer-associated fibroblasts, PD-1/PD-L1, transforming growth factor- β , and tumor necrosis factor- β. This paper summarizes the current research on the effect of TCM targeting the TME, and further introduces the research progress on studying the effects of TCM on immune checkpoints. Modern pharmacological studies have demonstrated that TCM can directly or indirectly affect the TME by inhibiting the overexpression of immune checkpoint molecules and enhancing the efficacy of tumor immunotherapy. TCM with immunomodulatory stimulation could be the key factor to achieve benefits from immunotherapy for patients with non-inflammatory, or "cold", tumors. [ABSTRACT FROM AUTHOR]

In recent years, due to advancements in medical conditions and the development of scientific research, the fundamental research of TCM antitumor treatments has progressed from the cellular level to the molecular and genetic levels. Previous studies have demonstrated the significant role of traditional Chinese medicine (TCM) in antitumor therapy through various mechanisms and pathways. Its mechanism of action is closely associated with cancer biology across different stages. This includes inhibiting tumor cell proliferation, blocking invasion and metastasis to surrounding tissues, inducing tumor cell apoptosis, inhibiting tumor angiogenesis, regulating immune function, maintaining genome stability, preventing mutation, and regulating cell energy metabolism. The use of TCM for eliciting antitumor effects not only has a good therapeutic effect and low side effects, it also provides a solid theoretical basis for clinical treatment and medication. This paper reviews the mechanism of the antitumor effects of TCM based on tumor characteristics. Through our review, we found that TCM not only directly inhibits tumors, but also enhances the body's immunity, thereby indirectly inducing an antitumor effect. This function aligns with the TCM theory of "strengthening the body's resistance to eliminate pathogenic factors". Furthermore, TCM will play a significant role in tumor treatment in clinical settings. [ABSTRACT FROM AUTHOR]

In this paper, we study a mathematical model of Hepatitis C Virus (HCV) infection. We present a compartmental mathematical model involving healthy hepatocytes, infected hepatocytes, non-activated dendritic cells, activated dendritic cells and cytotoxic T lymphocytes. The derivative used is of non-local fractional order and with non-singular kernel. The existence and uniqueness of the system is proven and its stability is analyzed. Then, by applying the Laplace Adomian decomposition method for the fractional derivative, we present the semi-analytical solution of the model. Finally, some numerical simulations are performed for concrete values of the parameters and several graphs are plotted to reveal the qualitative properties of the solutions. [ABSTRACT FROM AUTHOR]

Cancer is a main life-threatening disease worldwide. Due to the adverse effects of conventional chemotherapies and radiotherapies, immunotherapy has emerged as a potent strategy to treat cancer. In cancer immunotherapy, cancer immune surveillance plays a crucial role in the cancer process, which contains various effector cells from innate and adaptive immunity. This review summarized the functions of innate and adaptive immune cells in cancer immunosurveillance and their main reported targets. Moreover, the potential targets about the modulatory effects of cancer immunosurveillance were predicted using network-based target analysis, with total predicted pathways not only reporting previously reported pathways, but also putative signaling pathways pending for investigation. In addition, the potential use of herbal medicines and their phytochemicals in the modulation of cancer immunosurveillance were also discussed. Taken together, this review paper aims to provide scientific insight into further drug development, particularly herbs, phytochemicals, and TCM formulae, in the modulatory effects of cancer immunosurveillance. [ABSTRACT FROM AUTHOR]

Considered as one of the emerging evolutionary algorithms, the Dendritic Cell Algorithm (DCA) is based on the behavior of specific immune agents; known as Dendritic Cells (DCs). Studies related with DCA are increasingly becoming popular and this is due to the worthy characteristics expressed by the algorithm as it exhibits several potentially beneficial features for binary classification problems. Yet, according to our best knowledge, there is no study summarizing the basic features of the DCA developed versions all in one paper. Hence, in this paper we aim at summarizing the powerful characteristics of the DCA while making a general review of the algorithm. We aim at studying the various versions of DCA while highlighting their characteristics, advantages and limitations. Based on this study and from the conducted conclusions, we intend to generate a well-studied novel DC classifier based on the positive aspects reflected by the previously proposed DCA versions. Results show that our proposed algorithm succeeds in obtaining significantly improved classification accuracy. [ABSTRACT FROM AUTHOR]

This paper deals with a control strategy through impulsive drug treatment to study the effect of Chemotherapy and CTL activator drug to eradicate the cervical cancer. CTL kills the HPV infected cells and helps to prevent cervical cancer. Dendritic cell (DC) plays a crucial role in this disease dynamics in enhancing the activity of CTL. To explore these effects, we have formulated a mathematical model consisting of six compartments to describe the interactions between HPV and three classes of cervical cells (susceptible, infected, cancerous), with DC and CTL. Calculating the basic reproduction ratio, we find that there exists a disease-free equilibrium point and an endemic equilibrium point. In our study, we have shown that though DC enhances the activity of CTL, it is not sufficient to eradicate the disease totally. How we could restrict the cancer development by using double drug in an impulsive way with particular drug doses is being reflected in the results. To illustrate our results, numerical simulations are also presented. [ABSTRACT FROM AUTHOR]

In the past decade, we have witnessed the rapid development of a increasing body of research focused on Physarum polycephalum, which has been employed to solve many complicated problems in real-world applications. In this paper, we give an overview towards the developments of Physarum-inspired models for graph-optimization problems. Specifically, we reported the applications of Physarum in the following graph-optimization problems: influential nodes identification, shortest path tree problem, biobjective shortest path problem, improved Physarum algorithm and approximating the transport network. [ABSTRACT FROM AUTHOR]

In this research paper, our main objective is to find out the meticulous role of activated dendritic cells (DCs) during the human immunodeficiency virus (HIV) infection process. DCs play a dual role by enhancing both HIV infection progression, as well as antiviral immune response. To explore the implications of these dual roles, we have formulated our mathematical model and analyzed the model by both analytical and numerical approaches. By using an impulsive differential equation, we have studied the effect of DC-based vaccination. Analytically we have determined the threshold value of drug dosage and dosing interval for optimum levels of infection. We have also investigated the effect of perfect adherence of drug dose on the immune cell count in extreme cases and observed that, systematic drug dose of the immune cells leads to its maximum level. [ABSTRACT FROM AUTHOR]

In this paper, a new mathematical model of the interactions between a growing tumor and an immune system is presented by incorporating the danger model. The populations involved are tumor cells, CD8+ T-cells, natural killer cells (NK-cells), dendritic cells (DCs) and cytokine interleukin-12 (IL-12). A key feature of this work is the inclusion of the danger model into the dynamics of the immune system, which is rarely considered by previous works. Regarding the constructed mathematical model, both the location of equilibria and their stability properties are discussed, which are useful not only to gain a broad understanding of the specific system dynamics, but also to help guide the development of therapies. Moreover, numerical simulations of the system with chemotherapy and immunotherapy by using specific parameters are presented to illustrate that proper therapy is able to eliminate the entire tumor. In addition, we illustrate cases for which neither chemotherapy nor immunotherapy alone are able to control tumor growth, but a combination treatment is sufficient to eliminate the tumor cells. [ABSTRACT FROM AUTHOR]

In this paper, we investigated the impact of thickness and mole fraction AlInGaN back barrier on the DC performance of AlGaN/GaN high electron mobility transistors (HEMTs) by numerical simulation. The simulations are performed using the hydrodynamic transport model (HD). The simulation results indicated that an inserted AlInGaN back barrier with increasing thickness and mole fraction could effectively confine the electron in the channel, resulting in a significant improvement of the channel current and transconductance. Additionally, the variation of conduction band offset and the increase of total number electron in the channel led to the threshold voltage moving toward a more negative value. [ABSTRACT FROM AUTHOR]

Immunotherapy has become a rapidly developing approach in the treatment of cancer. Cancer immunotherapy aims at promoting the immune system response to react against the tumor. In view of this, we develop a mathematical model for immune–tumor interplays with immunotherapeutic drug, and strategies for optimally administering treatment. The tumor–immune dynamics are given by a system of five coupled nonlinear ordinary differential equations which represent the interaction among tumor-specific CD4+T cells, tumor-specific CD8+T cells, tumor cells, dendritic cells and the immuno-stimulatory cytokine interleukin-2 (IL-2), extended through the addition of a control function describing the application of a dendritic cell vaccination. Dynamical behavior of the system is studied from the analytical as well as numerical points of view. The main aim is to investigate the treatment regimens which minimize the tumor cell burden and the toxicity of dendritic cell vaccination. Our numerical simulations demonstrate that the optimal treatment strategies using dendritic cell vaccination reduce the tumor cell burden and increase the cell count of CD4+T cells, CD8+T cells, dendritic cells and IL-2. The most influential parameters having significant impacts on the tumor cells are identified by employing the approach of global sensitivity analysis. [ABSTRACT FROM AUTHOR]

We develop a mathematical model of tumor-immune interactions, including six populations (tumor cells, CD8 + T cells, natural killer (NK) cells, dendritic cells, helper T cells, cytokine interleukin-12 (IL-12)) and three potential treatments (chemotherapy, Tumor-infiltrating lymphocyte (TIL) therapy and IL-12 therapy). We characterize the dynamics of our model without treatment through stability and sensitivity analysis, which provides a broad understanding of the long-term qualitative behavior. To find the best combination of the chemo-immunotherapy regimens to eliminate tumors, we formulate an optimal control problem with path constraints of total drug dose and solve it numerically with the optimal control software Pyomo. We also simulate the scenarios of traditional treatment protocols as a comparison and find that our optimal treatment strategies have a better therapeutic effect. In addition, numerical simulation results show that IL-12 therapy is a good adjunctive therapy and has a high potential for inhibiting a large tumor in combination with other therapy. In most cases, combination therapy is more effective than a single treatment. [ABSTRACT FROM AUTHOR]

Successful immunologic control of HIV infection can be achieved in long-term non-progressors or HIV-1 controllers. Dendritic cells (DCs) are required for specific antigen presentation to naïve T lymphocytes and for antiviral, type I interferon secretion. To understand this mechanism, we develop a mathematical model that describes the role of direct presentation (replicating virus-infected DCs or other CD 4 + T cells directly) and cross presentation (DCs obtain antigen processed in other infected cells such as CD 4 + T lymphocytes) during HIV-1 infection. We find equilibria and determine stability in the case of no vaccination, and then, when vaccination is taken, we determine analytical thresholds for the strength and frequency of the vaccine to ensure the disease-free equilibrium remains stable. Our theoretical results suggest that the restoration of DC numbers may be predictive of immune restoration and may be a goal for immunotherapy to enhance viral control in a larger proportion of patients. [ABSTRACT FROM AUTHOR]

To develop an anticancer drug, the mathematical models are nowadays indispensable because of complex immunological mechanisms defying with high experimentation costs as well as a large number of parameters. Based on immunological theories and vision of experimentation data, a simple and sufficient compartment model is designed that can accurately interpret and predict the effects of dendritic cell (DC)-based immunotherapy in accordance with experimentation data. The model includes effector cells, regulatory T cells, helper T cells, and DCs. A new key feature is the inclusion of immunotherapy with DCs matured with different materials. All the parameters of the model have been optimally obtained by fitting the experimental data using genetic algorithm. The proposed model has been used to predict a near-optimal pattern that minimizes tumor size after vaccination. This pattern has been validated by carrying out the associated in-vivo experimentation. The model recommends maturation materials and doses that activate a small amount of Treg in the early days and a large Th1/Treg ratio in the next days. The performance of the model compared with the previous study was shown to be superior, both qualitatively and quantitatively. [ABSTRACT FROM AUTHOR]