IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v65y2014icp5-19.html
   My bibliography  Save this article

The butterfly effect in ER dynamics and ER-mitochondrial contacts

Author

Listed:
  • Pham, Tuan D.

Abstract

The endoplasmic reticulum (ER) is a major organelle of cells in eukaryotic organisms. The ER that is a polygonal network consisting of tubules and sheets has been known to be extremely dynamic in animal cells. However, understanding about the mechanism underlying ER-network motions is rarely explored. Discovering the type of dynamics that governs the movements of the ER network is essential for gaining insights into the structure and functions of cells. For the first time, this paper shows the evidence of chaotic behavior in the dynamics of the ER network and ER-mitochondrial contacts which were captured by time-lapse microscopy images. The chaotic properties of ER-network dynamics and ER-mitochondrial interactions were quantified using the largest Lyapunov exponent and fractal analysis. The results also suggest that the degree of chaos in ER dynamics reduces after drug treatment. New knowledge about the nonlinear dynamics that gives rise to the complex behavior of the organelles will lead to a new perspective of experimental design, and addressing questions relating to their functions and regulations.

Suggested Citation

  • Pham, Tuan D., 2014. "The butterfly effect in ER dynamics and ER-mitochondrial contacts," Chaos, Solitons & Fractals, Elsevier, vol. 65(C), pages 5-19.
  • Handle: RePEc:eee:chsofr:v:65:y:2014:i:c:p:5-19
    DOI: 10.1016/j.chaos.2014.04.007
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077914000538
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.chaos.2014.04.007?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.

    References listed on IDEAS

    as
    1. Wang, Qingyun & Zheng, Yanhong & Ma, Jun, 2013. "Cooperative dynamics in neuronal networks," Chaos, Solitons & Fractals, Elsevier, vol. 56(C), pages 19-27.
    2. Quiroz, G. & Bonifas, I. & Barajas-Ramirez, J.G. & Femat, R., 2012. "Chaos evidence in catecholamine secretion at chromaffin cells," Chaos, Solitons & Fractals, Elsevier, vol. 45(7), pages 988-997.
    3. Wang, Wenqin & Zhong, Shouming & Liu, Feng, 2012. "Robust filtering of uncertain stochastic genetic regulatory networks with time-varying delays," Chaos, Solitons & Fractals, Elsevier, vol. 45(7), pages 915-929.
    4. El-Gohary, Awad, 2008. "Chaos and optimal control of cancer self-remission and tumor system steady states," Chaos, Solitons & Fractals, Elsevier, vol. 37(5), pages 1305-1316.
    5. Aurora Espinoza-Valdez & Francisco C. Ordaz-Salazar & Edgardo Ugalde & Ricardo Femat, 2013. "Analysis of a Model for the Morphological Structure of Renal Arterial Tree: Fractal Structure," Journal of Applied Mathematics, Hindawi, vol. 2013, pages 1-6, July.
    6. Pham, Tuan D. & Thang, Truong Cong & Oyama-Higa, Mayumi & Sugiyama, Masahide, 2013. "Mental-disorder detection using chaos and nonlinear dynamical analysis of photoplethysmographic signals," Chaos, Solitons & Fractals, Elsevier, vol. 51(C), pages 64-74.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Pham, Tuan D. & Yan, Hong, 2018. "A regularity statistic for images," Chaos, Solitons & Fractals, Elsevier, vol. 106(C), pages 227-232.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Huang, Shoufang & Zhang, Jiqian & Wang, Maosheng & Hu, Chin-Kun, 2018. "Firing patterns transition and desynchronization induced by time delay in neural networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 499(C), pages 88-97.
    2. Liu, Jinhai & Su, Hanguang & Ma, Yanjuan & Wang, Gang & Wang, Yuan & Zhang, Kun, 2016. "Chaos characteristics and least squares support vector machines based online pipeline small leakages detection," Chaos, Solitons & Fractals, Elsevier, vol. 91(C), pages 656-669.
    3. El-Gohary, Awad, 2009. "Chaos and optimal control of equilibrium states of tumor system with drug," Chaos, Solitons & Fractals, Elsevier, vol. 41(1), pages 425-435.
    4. Llanos-Pérez, J.A. & Betancourt-Mar, J.A. & Cocho, G. & Mansilla, R. & Nieto-Villar, José Manuel, 2016. "Phase transitions in tumor growth: III vascular and metastasis behavior," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 560-568.
    5. Zheng, Y.G. & Bao, L.J., 2017. "Effect of topological structure on synchronizability of network with connection delay," Chaos, Solitons & Fractals, Elsevier, vol. 98(C), pages 145-151.
    6. Mondal, Argha & Upadhyay, Ranjit Kumar, 2017. "Dynamics of a modified Hindmarsh–Rose neural model with random perturbations: Moment analysis and firing activities," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 486(C), pages 144-160.
    7. Vázquez-Medina, R. & Jiménez-Ramírez, O. & A. Quiroz-Juárez, M. & L. Aragón, J., 2013. "Arbitrary waveform generator biologically inspired," Chaos, Solitons & Fractals, Elsevier, vol. 51(C), pages 36-51.
    8. Sviridova, Nina & Zhao, Tiejun & Aihara, Kazuyuki & Nakamura, Kazuyuki & Nakano, Akimasa, 2018. "Photoplethysmogram at green light: Where does chaos arise from?," Chaos, Solitons & Fractals, Elsevier, vol. 116(C), pages 157-165.
    9. Khajanchi, Subhas & Nieto, Juan J., 2019. "Mathematical modeling of tumor-immune competitive system, considering the role of time delay," Applied Mathematics and Computation, Elsevier, vol. 340(C), pages 180-205.
    10. Bazine, Hasnaa & Mabrouki, Mustapha, 2019. "Chaotic dynamics applied in time prediction of photovoltaic production," Renewable Energy, Elsevier, vol. 136(C), pages 1255-1265.
    11. Fedaravičius, Augustinas Povilas & Cao, Maosen & Ragulskis, Minvydas, 2016. "Control of a dendritic neuron driven by a phase-independent stimulation," Chaos, Solitons & Fractals, Elsevier, vol. 85(C), pages 77-83.
    12. Mohammad Shahzad, 2016. "Chaos Control in Three Dimensional Cancer Model by State Space Exact Linearization Based on Lie Algebra," Mathematics, MDPI, vol. 4(2), pages 1-11, May.
    13. Huang, Shoufang & Zhang, Jiqian & Hu, Chin-Kun, 2019. "Effects of external stimulations on transition behaviors in neural network with time-delay," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    14. Das, Parthasakha & Das, Samhita & Upadhyay, Ranjit Kumar & Das, Pritha, 2020. "Optimal treatment strategies for delayed cancer-immune system with multiple therapeutic approach," Chaos, Solitons & Fractals, Elsevier, vol. 136(C).
    15. Upadhyay, Ranjit Kumar & Mondal, Argha, 2017. "Synchronization of bursting neurons with a slowly varying d. c. current," Chaos, Solitons & Fractals, Elsevier, vol. 99(C), pages 195-208.
    16. Dehingia, Kaushik & Das, Parthasakha & Upadhyay, Ranjit Kumar & Misra, Arvind Kumar & Rihan, Fathalla A. & Hosseini, Kamyar, 2023. "Modelling and analysis of delayed tumour–immune system with hunting T-cells," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 203(C), pages 669-684.
    17. El-Gohary, Awad & Alwasel, I.A., 2009. "The chaos and optimal control of cancer model with complete unknown parameters," Chaos, Solitons & Fractals, Elsevier, vol. 42(5), pages 2865-2874.
    18. Ancillao, Andrea & Galli, Manuela & Rigoldi, Chiara & Albertini, Giorgio, 2014. "Linear correlation between fractal dimension of surface EMG signal from Rectus Femoris and height of vertical jump," Chaos, Solitons & Fractals, Elsevier, vol. 66(C), pages 120-126.
    19. Sviridova, Nina & Sakai, Kenshi, 2015. "Human photoplethysmogram: new insight into chaotic characteristics," Chaos, Solitons & Fractals, Elsevier, vol. 77(C), pages 53-63.

    More about this item

    Statistics

    Access and download statistics

    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:chsofr:v:65:y:2014:i:c:p:5-19. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Thayer, Thomas R. (email available below). General contact details of provider: https://www.journals.elsevier.com/chaos-solitons-and-fractals .

    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.