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This study reveals how internal enzymatic activity in soft biological networks creates nonequilibrium dynamics. We found that probe cycling frequencies scale with distance, revealing insights into entropy production.

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Area of Science:

  • Biophysics
  • Soft Matter Physics
  • Statistical Mechanics

Background:

  • Quantifying nonequilibrium dynamics in active biological systems is challenging due to stochasticity and limited experimental variables.
  • Active soft matter systems, like biological tissues, exhibit complex behaviors driven by internal forces.

Purpose of the Study:

  • To investigate extractable nonequilibrium information from noninvasive measurements in active biological systems.
  • To model and quantify the relationship between internal activity, probe distance, and nonequilibrium dynamics in soft elastic networks.

Main Methods:

  • Utilized a stochastic model of soft elastic networks with heterogeneous enzymatic activity.
  • Employed noninvasive tracking of two probes within the network to measure nonequilibrium dynamics.
  • Quantified dynamics using cycling frequencies and analyzed their scaling with probe distance.

Main Results:

  • Cycling frequencies, a measure of circulating currents, exhibit power-law scaling with the distance between probes.
  • This scaling behavior was shown to govern the entropy production rate recoverable from the probed system.
  • Demonstrated how internal enzymatic driving generates nonequilibrium dynamics across various scales in soft biological assemblies.

Conclusions:

  • Noninvasive probe tracking can effectively quantify nonequilibrium dynamics in active soft matter.
  • Power-law scaling of cycling frequencies provides a measurable link between microscopic activity and macroscopic emergent behavior.
  • The findings offer insights into the fundamental mechanisms of energy dissipation and organization in biological systems.