IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v506y2018icp462-475.html
   My bibliography  Save this article

On the learning control effects in the cancer-immune system competition

Author

Listed:
  • Masurel, Léon
  • Bianca, Carlo
  • Lemarchand, Annie

Abstract

The interactions between a tumor and the immune system are modeled at cell scale in the framework of thermostatted kinetic theory. Cell activation and learning are reproduced by the increase of cell activity during interactions. The second moment of the activity of the whole system is controlled by a thermostat which reproduces the regulation of the learning process and memory loss through cell death. An algorithm inspired from the direct simulation Monte Carlo (DSMC) method is used to simulate stochastic trajectories for the numbers of cells and to study the sensitivity of the dynamics to various parameters. The nonintuitive role played by the thermostat is pointed out. For inefficient thermalization, the divergence of the number of cancer cells is obtained in spite of favored production of immune system cells. Conversely, when the activity fluctuations are controlled, the development of cancer is contained even for weakened immune defenses. These results may be correlated to unexpected clinical observations in the case of different cancers, such as carcinoma, lymphoma, and melanoma.

Suggested Citation

  • Masurel, Léon & Bianca, Carlo & Lemarchand, Annie, 2018. "On the learning control effects in the cancer-immune system competition," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 462-475.
  • Handle: RePEc:eee:phsmap:v:506:y:2018:i:c:p:462-475
    DOI: 10.1016/j.physa.2018.04.077
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437118305053
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2018.04.077?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Bruno Carbonaro & Marco Menale, 2019. "Dependence on the Initial Data for the Continuous Thermostatted Framework," Mathematics, MDPI, vol. 7(7), pages 1-11, July.
    2. Mikhail Kolev, 2019. "Mathematical Analysis of an Autoimmune Diseases Model: Kinetic Approach," Mathematics, MDPI, vol. 7(11), pages 1-14, October.
    3. Gabriel Morgado & Annie Lemarchand & Carlo Bianca, 2023. "From Cell–Cell Interaction to Stochastic and Deterministic Descriptions of a Cancer–Immune System Competition Model," Mathematics, MDPI, vol. 11(9), pages 1-25, May.
    4. Sana Abdulkream Alharbi & Azmin Sham Rambely, 2020. "A New ODE-Based Model for Tumor Cells and Immune System Competition," Mathematics, MDPI, vol. 8(8), pages 1-14, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:506:y:2018:i:c:p:462-475. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.