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Related Concept Videos

Aging01:26

Aging

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Aging is a complex biological phenomenon influenced by various processes that affect cellular and systemic functions. Several prominent theories attempt to explain its mechanisms, highlighting cellular limitations, oxidative damage, and hormonal changes as central factors in aging.
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The cellular clock theory posits that the human lifespan is closely tied to the finite capacity of cells to divide, a phenomenon governed by telomeres, which are protective caps at the ends of...
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Mitochondria are eukaryotic cellular organelles that are known to produce energy through a process called oxidative phosphorylation. Besides their primary function, mitochondria are involved in various cellular processes, including cell growth, differentiation, signaling, metabolism, and senescence. Age-related changes cause a decline in mitochondrial quality and integrity due to increased mitochondrial mutations and oxidative damage. Thus, aging can severely impact mitochondrial functions,...
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Related Experiment Video

Updated: May 13, 2025

Combining Magnetic Sorting of Mother Cells and Fluctuation Tests to Analyze Genome Instability During Mitotic Cell Aging in Saccharomyces cerevisiae
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The Dissipation Theory of Aging: A Quantitative Analysis Using a Cellular Aging Map.

Farhan Khodaee1, Rohola Zandie1, Yufan Xia1

  • 1Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA.

Arxiv
|May 5, 2025
PubMed
Summary

Aging is a dissipative process in biological systems, according to a new dynamical systems theory. A computational method quantifies cellular aging changes using machine learning and gene expression data.

Keywords:
agingdissipationdynamical systemslanguage modelingmultimodal foundation modelsingle-cell RNA sequencing

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Area of Science:

  • Biophysics
  • Computational Biology
  • Systems Biology

Background:

  • Aging is a complex biological process involving cellular changes.
  • Understanding the fundamental dynamics of aging remains a challenge.
  • Existing models often lack a dynamical systems perspective.

Purpose of the Study:

  • To propose a novel theory of aging based on dynamical systems.
  • To develop a computational method for quantifying cellular aging dynamics.
  • To investigate aging as a dissipative process in biological systems.

Main Methods:

  • Applied ergodic theory to decompose aging dynamics.
  • Utilized a transformer-based machine learning algorithm for gene expression analysis.
  • Incorporated age as a token in machine learning models to analyze embeddings.
  • Developed a cellular aging map (CAM) to visualize age-related changes.

Main Results:

  • Aging was characterized as a fundamental dissipative process.
  • Identified age-related dissipation patterns in gene and age embeddings.
  • Observed divergence in gene embedding space and nonlinear transitions.
  • Detected variations in entropy during aging across different tissues and cell types.

Conclusions:

  • Aging can be conceptualized as a dissipative process within biological systems.
  • The proposed computational framework enables molecular-level measurement of aging.
  • The cellular aging map (CAM) offers a novel tool for aging research.
  • This work provides a new perspective on the dynamics of cellular aging.