衰老、变化和竞争:当选择一种模式的欲望损害了我们的理解力时。

IF 2 4区 生物学 Q2 BIOLOGY Biosystems Pub Date : 2024-11-12 DOI:10.1016/j.biosystems.2024.105364
André C.R. Martins
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引用次数: 0

摘要

我们为什么会衰老是一个根本性的问题。它关系到我们是谁,而且在我们试图找到延缓衰老的方法时,它也可能具有重要的现实意义。或者根本不会衰老。不同的原因为抗衰老药物的研究指出了不同的策略。虽然生物系统的主要工作原理是进化,但在相当长的一段时间里,人们认为衰老需要另一种解释。衰老似乎对个体伤害很大,即使它对群体有好处,这些好处也不可能足够。因此,许多科学家提出了一些非进化的解释,来解释我们为什么会衰老。但这些理论似乎无法解释物种衰老的所有数据。在这里,我将说明,坚持寻找一个能解释一切的观点,可能是难以获得全貌的根源。通过探索一个以地域性和时间性变化为基本问题的衰老进化模型,我将证明环境变化会导致群体优势的障碍变得更弱。这种弱化可能会帮助小群体优势累积到可以产生适应性差异的程度。要回答我们为什么会衰老,我们可能不得不放弃追问哪种模式是正确的。完整的答案可能来自于考虑每个现有模型背后的假设,包括进化和非进化模型,对现实世界的解决方案有多大贡献。
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Senescence, change, and competition: When the desire to pick one model harms our understanding
The question of why we age is a fundamental one. It is about who we are, and it also might have critical practical aspects as we try to find ways to age slower. Or to not age at all. Different reasons point at distinct strategies for the research of anti-aging drugs. While the main reason why biological systems work as they do is evolution, for quite a while, it was believed that aging required another explanation. Aging seems to harm individuals so much that even if it has group benefits, those benefits were unlikely to be enough. That has led many scientists to propose non-evolutionary explanations as to why we age. But those theories seem to fail at explaining all the data on how species age. Here, I will show that the insistence of finding the one idea that explains it all might be at the root of the difficulty of getting a full picture. By exploring an evolutionary model of aging where locality and temporal changes are fundamental aspects of the problem, I will show that environmental change causes the barrier for group advantages to become much weaker. That weakening might help small group advantages to add up to the point they could make an adaptive difference. To answer why we age, we might have to abandon asking which models are correct. The full answer might come from considering how much each hypothesis behind each existing model, evolutionary and non-evolutionary ones, contributes to the real world’s solution.
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来源期刊
Biosystems
Biosystems 生物-生物学
CiteScore
3.70
自引率
18.80%
发文量
129
审稿时长
34 days
期刊介绍: BioSystems encourages experimental, computational, and theoretical articles that link biology, evolutionary thinking, and the information processing sciences. The link areas form a circle that encompasses the fundamental nature of biological information processing, computational modeling of complex biological systems, evolutionary models of computation, the application of biological principles to the design of novel computing systems, and the use of biomolecular materials to synthesize artificial systems that capture essential principles of natural biological information processing.
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