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相关概念视频

The Effect of Aging on Tissues01:19

The Effect of Aging on Tissues

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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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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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Mitochondria01:37

Mitochondria

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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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Updated: Jul 15, 2025

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
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从脸部照片中解读生物年龄,使用深度学习.

Osbert Zalay1,2,3, Dennis Bontempi1,2,4,5, Danielle S Bitterman1,2

  • 1Artificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, United States of America.

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概括
此摘要是机器生成的。

一个新的深度学习系统,FaceAge,通过面部照片估计生物年龄. 它发现癌症患者看起来更老,与更糟糕的生存率相关,并可以帮助终身护理决策.

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科学领域:

  • 生物医学工程 生物医学工程
  • 人工智能在医学中的应用
  • 老年学是一门学科.

背景情况:

  • 人类的衰老速度各不相同,这使得外表成为生物年龄和健康的潜在指标.
  • 目前对外表的医学评估是主观的,缺乏标准化.
  • 面部外观可以提供超越时间表年龄的生理健康洞察力.

研究的目的:

  • 开发和验证FaceAge,这是一个用于从面部照片中估计生物年龄的深度学习系统.
  • 评估FaceAge在癌症患者中的临床实用性和预后相关性.
  • 探索FaceAge与分子衰老机制的关联.

主要方法:

  • 在58,851名健康个体的面部数据上训练FaceAge.
  • 在美国和荷兰机构的6196名癌症患者中验证了临床效用.
  • 进行了生存分析,并将FaceAge集成到临床预测模型中,用于终身护理.

主要成果:

  • 平均而言,癌症患者看起来比他们的时间年龄更老.
  • 增加的明显年龄与癌症患者的整体存活率较差相关.
  • FaceAge在各种癌症类型和阶段中表现出独立的预后性能.

结论:

  • FaceAge可以改善医生的生存预测,特别是在治疗不治癌症患者的息治疗中.
  • 该算法提供客观的,从面部图像对生物年龄的定量测量,支持临床决策.
  • 这些发现表明FaceAge的潜在适用性超出了癌症,将视觉外观与分子衰老联系起来.