{"title":"Cancer model and its possible control—A Z-type control approach","authors":"Sudip Samanta , Sandip Sarkar , Kaushik Kayal","doi":"10.1016/j.mex.2024.102895","DOIUrl":null,"url":null,"abstract":"<div><p>This paper investigates the dynamics of a three-dimensional nonlinear cancer model involving interactions among cancer cells, normal cells, and immune cells. By performing a linear stability analysis of the equilibria and investigating the Hopf bifurcation in relation to the immune cell growth rate, we reveal the possibility of chaotic behavior when radiation is absent. However, with the appropriate implementation of radiotherapy, the cancer model demonstrates stable solutions, transitioning from chaotic oscillations through period-halving bifurcation. Additionally, we propose and examine an indirect Z-control mechanism within the cancer model. Our findings indicate that using the indirect Z-controller on the immune population successfully manages chaos and adjusts the cancer cell density to a desired level. Through extensive investigation, we demonstrate the robustness of the Z-controller in managing oscillations and provide insights into determining the minimum number of immune cells needed to achieve a predetermined cancer cell density. This study underscores the importance of control mechanisms in mitigating cancer progression and highlights the potential of Z-control for therapeutic intervention strategies.</p></div>","PeriodicalId":18446,"journal":{"name":"MethodsX","volume":"13 ","pages":"Article 102895"},"PeriodicalIF":1.6000,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2215016124003479/pdfft?md5=adedd04bb666e0dd90157528122478a3&pid=1-s2.0-S2215016124003479-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"MethodsX","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2215016124003479","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
This paper investigates the dynamics of a three-dimensional nonlinear cancer model involving interactions among cancer cells, normal cells, and immune cells. By performing a linear stability analysis of the equilibria and investigating the Hopf bifurcation in relation to the immune cell growth rate, we reveal the possibility of chaotic behavior when radiation is absent. However, with the appropriate implementation of radiotherapy, the cancer model demonstrates stable solutions, transitioning from chaotic oscillations through period-halving bifurcation. Additionally, we propose and examine an indirect Z-control mechanism within the cancer model. Our findings indicate that using the indirect Z-controller on the immune population successfully manages chaos and adjusts the cancer cell density to a desired level. Through extensive investigation, we demonstrate the robustness of the Z-controller in managing oscillations and provide insights into determining the minimum number of immune cells needed to achieve a predetermined cancer cell density. This study underscores the importance of control mechanisms in mitigating cancer progression and highlights the potential of Z-control for therapeutic intervention strategies.
本文研究了涉及癌细胞、正常细胞和免疫细胞之间相互作用的三维非线性癌症模型的动力学。通过对平衡点进行线性稳定性分析,并研究与免疫细胞增长率相关的霍普夫分岔,我们揭示了在没有辐射时出现混沌行为的可能性。然而,在适当实施放射治疗的情况下,癌症模型表现出稳定的解,从混沌振荡过渡到周期-霍普夫分岔。此外,我们还提出并研究了癌症模型中的间接 Z 控制机制。我们的研究结果表明,在免疫群体中使用间接 Z 控制机制可以成功控制混乱,并将癌细胞密度调整到理想水平。通过广泛的研究,我们证明了 Z 控制器在管理振荡方面的稳健性,并为确定达到预定癌细胞密度所需的最小免疫细胞数量提供了见解。这项研究强调了控制机制在缓解癌症进展方面的重要性,并突出了 Z 控制在治疗干预策略方面的潜力。