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Extreme escape from a cusp: When does geometry matter for the fastest Brownian particles moving in crowded cellular environments?

Kanishka BasnayakeDavid Holcman
Published in: The Journal of chemical physics (2020)
We study here the extreme statistics of Brownian particles escaping from a cusp funnel: the fastest Brownian particles among n follow an ensemble of optimal trajectories located near the shortest path from the source to the target. For the time of such first arrivers, we derive an asymptotic formula that differs from the mean first passage times obtained for classical narrow escape and dire strait. When particles are initially distributed at a given distance from a cusp, the time of the fastest particles depends on the cusp geometry. Therefore, when many particles diffuse around impermeable obstacles, the geometry plays a role in the time it takes to reach a target. In the context of cellular transduction with signaling molecules, having to escape from such cusp-like domains slows down signaling pathways. Consequently, generating multiple copies of the same molecule enables molecular signals to be delivered through crowded environments in sufficient time.
Keyphrases
  • climate change
  • signaling pathway
  • cell proliferation
  • deep learning
  • preterm infants
  • convolutional neural network
  • pi k akt
  • single molecule