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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.
Cellular Clock Theory
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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The Effect of Aging on Tissues01:19

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Several body functions deteriorate with age. The external signs of aging are easily identifiable. For example, the skin becomes dry, less elastic, and thins out, forming wrinkles. The skin of the face begins to appear looser due to a decrease in the levels of elastic and collagen fibers in the connective tissue. Additionally, melanin production in the hair follicle decreases with age, resulting in gray hair. Moreover, the senses of sight and hearing decline, so glasses and hearing aids may...
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Mitochondria01:37

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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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The dissipation theory of aging: a quantitative analysis using a cellular aging map.

Farhan Khodaee1, Rohola Zandie2, Louis-Alexandre Leger2

  • 1Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, USA. farhank@mit.edu.

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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, creating a cellular aging map.

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Area of Science:

  • Dynamical Systems Theory
  • Computational Biology
  • Genomics

Background:

  • Aging is a complex biological process characterized by progressive functional decline.
  • Existing models of aging often focus on molecular damage or genetic factors.
  • A dynamical systems perspective offers a novel framework for understanding aging dynamics.

Purpose of the Study:

  • To propose a new theory of aging based on dynamical systems.
  • To develop a data-driven computational method for quantifying cellular aging.
  • 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 to analyze gene expression data.
  • Incorporated age as a token in machine learning models to analyze gene and age embeddings.

Main Results:

  • Aging was characterized as a dissipative process, analogous to physical systems with non-conservative forces.
  • Developed a cellular aging map (CAM) by evaluating gene and age embedding dynamics.
  • Identified patterns of divergence, nonlinear transitions, and entropy variations in gene embedding space across tissues and cell types.

Conclusions:

  • Aging can be understood as a fundamental dissipative process within biological systems.
  • The developed computational framework enables precise measurement of age-related changes at the molecular level.
  • This research offers a novel perspective and quantitative tools for studying the biology of aging.