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Entropy and diffusion characterize mutation accumulation and biological information loss.

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Aging increases entropy, or "falling apart," as biological information changes over time. Managing this entropy, through mechanisms like entropy management, may explain how organisms evolve longer lifespans.

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Area of Science:

  • Gerontology
  • Evolutionary Biology
  • Biophysics

Background:

  • Aging is a universal biological process without a unified theoretical framework.
  • Existing theories of aging lack a comprehensive explanation for the diversity of lifespans across species.

Purpose of the Study:

  • To propose and validate a universal theory of aging based on the concept of entropy.
  • To model biological information change using principles of physics and mathematics.
  • To investigate the relationship between entropy, mutation, and lifespan.

Main Methods:

  • Conceptualizing biological information change as mutational distance, analogous to physical distance.
  • Applying an advection-diffusion equation to model informational change over time.
  • Utilizing the binomial distribution to quantify entropy increase with mutations.
  • Correlating modeled entropy with observed lifespans across the tree of life.

Main Results:

  • The advection-diffusion equation successfully models entropy in diverse biological systems.
  • Entropy demonstrably increases with the accumulation of mutations and epimutations.
  • The proposed model shows that entropy scales with lifespan across different species.
  • Entropy management emerges as a potential evolutionary strategy for enhanced longevity.

Conclusions:

  • Entropy provides an inclusive framework for understanding aging, integrating various biological observations.
  • This entropy-based perspective offers mechanistic insights into lifespan evolution.
  • The model generates testable hypotheses regarding the biological mechanisms of aging and longevity.