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Dynamic heterogeneity and non-Gaussian statistics for acetylcholine receptors on live cell membrane

Author

Listed:
  • W. He

    (Nano Science and Technology Program, Hong Kong University of Science and Technology)

  • H. Song

    (Hong Kong University of Science and Technology)

  • Y. Su

    (Hong Kong University of Science and Technology)

  • L. Geng

    (Hong Kong University of Science and Technology)

  • B. J. Ackerson

    (Oklahoma State University)

  • H. B. Peng

    (Hong Kong University of Science and Technology)

  • P. Tong

    (Hong Kong University of Science and Technology)

Abstract

The Brownian motion of molecules at thermal equilibrium usually has a finite correlation time and will eventually be randomized after a long delay time, so that their displacement follows the Gaussian statistics. This is true even when the molecules have experienced a complex environment with a finite correlation time. Here, we report that the lateral motion of the acetylcholine receptors on live muscle cell membranes does not follow the Gaussian statistics for normal Brownian diffusion. From a careful analysis of a large volume of the protein trajectories obtained over a wide range of sampling rates and long durations, we find that the normalized histogram of the protein displacements shows an exponential tail, which is robust and universal for cells under different conditions. The experiment indicates that the observed non-Gaussian statistics and dynamic heterogeneity are inherently linked to the slow-active remodelling of the underlying cortical actin network.

Suggested Citation

  • W. He & H. Song & Y. Su & L. Geng & B. J. Ackerson & H. B. Peng & P. Tong, 2016. "Dynamic heterogeneity and non-Gaussian statistics for acetylcholine receptors on live cell membrane," Nature Communications, Nature, vol. 7(1), pages 1-8, September.
    • Handle: RePEc:nat:natcom:v:7:y:2016:i:1:d:10.1038_ncomms11701
    DOI: 10.1038/ncomms11701
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    Cited by:

    1. Čukić, Milena & Galovic, Slobodanka, 2023. "Mathematical modeling of anomalous diffusive behavior in transdermal drug-delivery including time-delayed flux concept," Chaos, Solitons & Fractals, Elsevier, vol. 172(C).
    2. Wang, Xudong & Chen, Yao, 2021. "Ergodic property of Langevin systems with superstatistical, uncorrelated or correlated diffusivity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 577(C).
    3. Ahamad, Nabi & Debnath, Pallavi, 2020. "Rouse model in crowded environment modeled by “diffusing diffusivity”," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 549(C).
    4. Du, Qiang & Toniazzi, Lorenzo & Zhou, Zhi, 2020. "Stochastic representation of solution to nonlocal-in-time diffusion," Stochastic Processes and their Applications, Elsevier, vol. 130(4), pages 2058-2085.

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