How organisms decrease their entropy.

IF 1.9 4区 生物学 Q2 BIOLOGY
Yoram Schiffmann
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引用次数: 0

Abstract

It is recognised that the second law does not, in principle, preclude the decrease of entropy of biological organisms. However, we want to know how it is done. We start from the entropy reduction that underlies biological work, using the framework of the thermodynamics of irreversible processes, as formulated for continuous systems. This formulation includes time and rate, which are absent in classical thermodynamics. We then note that this entropy reduction can be made spatially differential in continuous systems due to another entropy reduction: the one brought about by the Turing instability with cAMP and ATP as the Turing morphogens. Both entropy reductions require holding ATP hydrolysis far from thermodynamic equilibrium. This solution to the mechanism of entropy decrease in organisms simultaneously provides solutions to other major problems in biology, including the missing link in molecular biology between the molecular level and the macroscopic level, the problem of spontaneous self-organisation and epigenesis, and the problem of coherence and coordination between all biochemical processes in space and time.

生物体如何减少它们的熵。
人们认识到,第二定律在原则上并不排除生物有机体熵的减少。然而,我们想知道它是如何做到的。我们从生物工作的基础上的熵减开始,使用不可逆过程的热力学框架,作为连续系统的公式。这个公式包含了经典热力学中不存在的时间和速率。然后我们注意到,由于另一种熵减少,这种熵减少可以在连续系统中产生空间差异:以cAMP和ATP为图灵形态原的图灵不稳定性带来的熵减少。这两种熵的减少都需要保持ATP水解远离热力学平衡。这种对生物体熵减少机制的解决,同时也为解决生物学中的其他重大问题提供了解决方案,包括分子生物学中分子水平与宏观水平之间缺失的一环,自发自组织和表观发生问题,以及所有生化过程在空间和时间上的一致性和协调性问题。
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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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