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Langevin dynamics for subdiffusion with senescence effects.

Hailong Liu1, Xudong Wang1

  • 1Nanjing University of Science and Technology, School of Mathematics and Statistics, Nanjing 210094, People's Republic of China.

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Summary
This summary is machine-generated.

Cellular senescence, a process affecting cell mitosis, can be modeled using statistical mechanics. This study introduces a new model to explore senescence effects on anomalous diffusion, revealing strong senescence slows diffusion while weak senescence has no long-term impact.

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Area of Science:

  • Statistical Mechanics
  • Cellular Biology
  • Complex Systems

Background:

  • Cellular senescence is a fundamental biological process observed during cell mitosis.
  • Senescence can be mathematically described as a random walk process where properties decay with increasing transitions.
  • Understanding senescence's impact on diffusion is crucial for various biological and physical phenomena.

Purpose of the Study:

  • To investigate the influence of cellular senescence on anomalous diffusion.
  • To develop a novel theoretical framework incorporating senescence into diffusion models.
  • To analyze the distinct diffusion behaviors under varying senescence strengths.

Main Methods:

  • Proposed a new subordinated Langevin equation by incorporating a senescence term into the classical α-stable subordinator.
  • Utilized a power-law form for the senescence term f(s).
  • Derived Fokker-Planck equations and evaluated ensemble and time averages of mean-squared displacements.

Main Results:

  • Identified distinct diffusion regimes for weak and strong senescence.
  • Demonstrated that strong senescence significantly dampens and slows down subdiffusion.
  • Showed that weak senescence has no discernible impact on subdiffusion in the large-time limit.

Conclusions:

  • The developed subordinated Langevin equation provides a new perspective on modeling senescence effects in anomalous diffusion.
  • The findings highlight the critical role of senescence strength in modulating diffusion dynamics.
  • This work offers a quantitative framework for studying senescence in complex systems.