scholarly journals CONTROL WITH UNCERTAINTY IN THE MATHEMATICAL MODEL OF ANTIVIRAL IMMUNE RESPONSE

2017 ◽  
Vol 7 (4) ◽  
pp. 226-228
Author(s):  
M.V. Chirkov ◽  
2018 ◽  
Vol 36 (3) ◽  
pp. 381-410 ◽  
Author(s):  
Angela M Jarrett ◽  
Meghan J Bloom ◽  
Wesley Godfrey ◽  
Anum K Syed ◽  
David A Ekrut ◽  
...  

Abstract The goal of this study is to develop an integrated, mathematical–experimental approach for understanding the interactions between the immune system and the effects of trastuzumab on breast cancer that overexpresses the human epidermal growth factor receptor 2 (HER2+). A system of coupled, ordinary differential equations was constructed to describe the temporal changes in tumour growth, along with intratumoural changes in the immune response, vascularity, necrosis and hypoxia. The mathematical model is calibrated with serially acquired experimental data of tumour volume, vascularity, necrosis and hypoxia obtained from either imaging or histology from a murine model of HER2+ breast cancer. Sensitivity analysis shows that model components are sensitive for 12 of 13 parameters, but accounting for uncertainty in the parameter values, model simulations still agree with the experimental data. Given theinitial conditions, the mathematical model predicts an increase in the immune infiltrates over time in the treated animals. Immunofluorescent staining results are presented that validate this prediction by showing an increased co-staining of CD11c and F4/80 (proteins expressed by dendritic cells and/or macrophages) in the total tissue for the treated tumours compared to the controls ($p < 0.03$). We posit that the proposed mathematical–experimental approach can be used to elucidate driving interactions between the trastuzumab-induced responses in the tumour and the immune system that drive the stabilization of vasculature while simultaneously decreasing tumour growth—conclusions revealed by the mathematical model that were not deducible from the experimental data alone.


Author(s):  
N.A. Babushkina ◽  
E.A. Kuzina ◽  
A.A. Loos ◽  
E.V. Belyaeva

The paper presents the mathematical description of the two stages of tumor cells’ death as a result of immune response after antitumor viral vaccine introduction. This mathematical description is presented by the system of nonlinear equations implemented in the MatLab-Simulink system. As a result of the computing experiment, two strategies for effective application of the antitumor viral vaccine were identified. The first strategy leads to complete elimination of the tumor cells after a single-shot administration of the vaccine. The second strategy makes it possible to stabilize tumor size through the recurrent introductions of the vaccine. Using the mathematical model of antitumor therapy, appropriate dosages were identified based on the number of tumor cells that die at the two stages of immune response. Dynamics of tumor growth for the two strategies of the viral vaccine application was forecasted based on the mathematical model of antitumor therapy with discontinuous trajectories of tumor growth. The computing experiments made it possible to identify initial tumor size at the start of the therapy and the dosages that allow complete elimination of the tumor cells after the single-shot introduction. For the second strategy, dosages and intervals between recurrent vaccine introductions required to stabilize tumor size at the initial level were also identified. The proposed approach to exploring the effectiveness of vaccine therapy may be applied to different types of experimental tumors and antitumor vaccines.


2015 ◽  
Vol 08 (05) ◽  
pp. 1550069 ◽  
Author(s):  
Ayesha Sohail ◽  
Sadia Arshad ◽  
Sana Javed ◽  
Khadija Maqbool

In this paper, the tumor-immune dynamics are simulated by solving a nonlinear system of differential equations. The fractional-order mathematical model incorporated with three Michaelis–Menten terms to indicate the saturated effect of immune response, the limited immune response to the tumor and to account the self-limiting production of cytokine interleukin-2. Two types of treatments were considered in the mathematical model to demonstrate the importance of immunotherapy. The limiting values of these treatments were considered, satisfying the stability criteria for fractional differential system. A graphical analysis is made to highlight the effects of antigenicity of the tumor and the fractional-order derivative on the tumor mass.


2010 ◽  
Vol 18 (01) ◽  
pp. 75-91 ◽  
Author(s):  
SIDDHARTHA P. CHAKRABARTY ◽  
SANDIP BANERJEE

The mathematical model depicting cancer remission as presented by Banerjee and Sarkar1is reinvestigated here. Mathematical tools from control theory have been used to analyze and determine how an optimal external treatment of Adaptive Cellular Immunotherapy and interleukin-2 can result in more effective remission of malignant tumors while minimizing any adverse affect on the immune response.


2020 ◽  
Vol 13 (5) ◽  
pp. 5-18
Author(s):  
N. I. ARALOVA ◽  

The aim of the study was to develop a mathematical model to research hypoxic states in case of simulation of an organism infectious lesions. The model is based on the methods of mathematical modeling and the theory of optimal control of moving objects. The processes of organism damage are simulated with the mathematical model of immune response developed by G.I. Marchuk and the members of his scientific school, adapted to current conditions. This model is based on Burnet’s clone selection theory of the determining role of antigen. Simulation results using the model are presented. The dependencies of infectious courses on the volumetric velocity of systemic blood flow is analyzed on the complex mathematical model of immune response, respiratory and blood circulation systems. The immune system is shown to be rather sensitive to the changes in blood flow via capillaries. Thus, the organ blood flows can be used as parameters for the model by which the respiratory, immune response, and blood circulation systems interact and interplay.


Author(s):  
P.V. Trusov ◽  
N.V. Zaitseva ◽  
V.M. Chigvintsev ◽  
D.V. Lanin

To know the processes occurring in the neuroendocrine and immune system, the complex and branching regulation mechanisms should be taken into account. Most of the studies in this area are dedicated to the biological and mathematical description of individual parts of the regulatory mechanisms, and it greatly facilitates the understanding of the phenomena being studied. But there is a lack of comprehensive description of the processes and internal communications. In the present article, a mathematical model for describing the antiviral immune response is considered taking into account the interacting regulatory influences of the immune and neuroendocrine systems. To describe the innate immunity, the proposed model uses parameters reflecting quantitative measures of the interferon concentration (the inductor of resistance to the infection of target organ cells) and NK-cells (responsible for removing of the infected cells). The simulation of acquired immunity is performed using parameters characterizing the concentration of virus-specific cytotoxic T cells and antibody-forming B lymphocytes. The regulatory mechanisms considered in the model cover the influence of the hypothalamic-pituitary-adrenal axis and the populations of the T-helper cells. The model is developed within the framework of the concept of a multi-level model of the human body, taking into account the interactions between systems and the functional state of the organs included in the review. The model also takes into account the spatial organization of immune and infectious processes in various organs and tissues, for which the delay time of interaction of the components is introduced. The model includes a system of 18 ordinary differential equations with a delayed argument, the parameters of which characterize the rates of various processes that affect the dynamics of infection. The parameters are identified according to published experimental data describing the process of infection of the body with a virus. The dynamics of the immune and neuroendocrine systems under viral infection was calculated, taking into account the disturbance of the synthetic function of the bone marrow. The study provides a qualitative picture of the biological factors that can explain the kinetics of the development of a viral infection.


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