多细胞生物体发育和衰老的耗散缩放效应

IF 2 4区 生物学 Q2 BIOLOGY
Andres Kriete
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引用次数: 0

摘要

进化、自我复制和本体生成是高度动态、不可逆和自组织的耗能过程。虽然在破解热力学在细胞裂变中的作用方面取得了进展,但熵平衡如何影响生物体的生长和衰老尚不清楚。本文推导出生物体生命史的一般耗散理论。它暗示了一种自我调节的能量耗散,这种能量耗散促进了生物在分层和降低熵的自组织中的指数增长。该理论预测了由几何约束强加的能量消耗上限,它促进了发育过程中的热优化,以及生物体间的耗散缩放,这与结合了等距和异距项的生态缩放定律是一致的。该理论还说明了生长中的生物如何通过不断扩展和产生新的低熵耗散结构来承受损害。然而,当生物体降低细胞分裂速度并达到稳定的成体状态时,它们就会变得热力学不稳定,通过积累损伤增加内部熵,并逐渐衰老。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Dissipative scaling of development and aging in multicellular organisms

Evolution, self-replication and ontogenesis are highly dynamic, irreversible and self-organizing processes dissipating energy. While progress has been made to decipher the role of thermodynamics in cellular fission, it is not yet clear how entropic balances shape organism growth and aging. This paper derives a general dissipation theory for the life history of organisms. It implies a self-regulated energy dissipation facilitating exponential growth within a hierarchical and entropy lowering self-organization. The theory predicts ceilings in energy expenditures imposed by geometric constrains, which promote thermal optimality during development, and a dissipative scaling across organisms consistent with ecological scaling laws combining isometric and allometric terms. The theory also illustrates how growing organisms can tolerate damage through continuous extension and production of new dissipative structures low in entropy. However, when organisms reduce their rate of cell division and reach a steady adult state, they become thermodynamically unstable, increase internal entropy by accumulating damage, and age.

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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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