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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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The circadian—or biological—clock is an intrinsic, timekeeping, molecular mechanism that allows plants to coordinate physiological activities over 24-hour cycles called circadian rhythms. Photoperiodism is a collective term for the biological responses of plants to variations in the relative lengths of dark and light periods. The period of light-exposure is called the photoperiod.
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The biological clock is involved in many aspects of regulating complex physiology in all animals. It was in 1935 when German zoologists, Hans Kalmus and Erwin Bünning, discovered the existence of circadian rhythm in Drosophila melanogaster. However, the internal molecular mechanisms behind the circadian clock remained a mystery until 1984, when Jeffrey C. Hall, Michael Rosbash, and Michael W. Young discovered the expression of the Per gene oscillating over a 24-hour cycle. In subsequent...
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Related Experiment Video

Updated: Feb 28, 2026

Measuring Single-Cell Aging with an Imaging-based Biomarker of Chromatin and Epigenetic Aging
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Imaging-based organ-specific aging clock predicts human diseases and mortality.

Peng Ren1,2, Wenjing Su1,2, Jia You1,2

  • 1Institute of Science and Technology for Brain-Inspired Intelligence, Department of Neurology, Huashan Hospital, State Key Laboratory of Brain Function and Disorders and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China.

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Summary

New imaging-based aging clocks reveal organ-specific biological age. These clocks predict disease risk and mortality, offering personalized interventions for aging organs.

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Area of Science:

  • Biomedical imaging
  • Gerontology
  • Personalized medicine

Background:

  • Organ-specific aging clocks are crucial for assessing organ health.
  • In vivo imaging offers objective, organ-specific structural and functional data.
  • Systematic evaluation of imaging-based aging clocks is lacking.

Purpose of the Study:

  • To develop and evaluate organ-specific biological aging clocks using in vivo imaging.
  • To investigate the association of organ-specific age gap with incident diseases and mortality.
  • To identify molecular signatures, modifiable factors, and drug targets for organ aging.

Main Methods:

  • Utilized 1777 imaging-derived phenotypes (IDPs) from 11,000 healthy participants.
  • Assessed biological age for seven organs using imaging data.
  • Performed proteomic analysis to identify molecular signatures of aging.
  • Identified modifiable factors and drug targets.

Main Results:

  • Developed organ-specific aging clocks for seven organs.
  • Organ-specific age gap correlated with corresponding organ-related diseases and mortality.
  • Top IDPs predicted dementia with an AUC of 0.82.
  • Identified 966 shared and 507 organ-specific molecular aging signatures.
  • Discovered key modifiable factors and 14 drug targets for organ aging.

Conclusions:

  • Imaging-based aging clocks demonstrate organ-specificity at macro and micro scales.
  • These clocks can serve as biomarkers for disease prediction.
  • Findings support personalized interventions and treatments for organ aging.