Singh Prim B
Department of Biomedical Sciences, School of Medicine, Nazarbayev University, 5/1 Kerei, Zhanibek Khandar Street, Astana 010000, Kazakhstan.
Cells. 2025 Aug 13;14(16):1249. doi: 10.3390/cells14161249.
We present a synthesis based on epigenetics, machine learning and polymer physics from which emerges new relationships between the thermodynamic Flory-Huggins parameter (χ), epigenetic age (eAge) and Shannon entropy. Using a framework for the estimation of χ in the nuclear environment we show that χ∝eAge-1 and χ∝Shannon Entropy-1. As cells age, epigenetic drift results in "smoothing out" of the epigenetic landscape reducing the magnitude of χ. Epigenetic rejuvenation reverses epigenetic drift and restores χ to levels found in young cells with concomitant reduction in both eAge and Shannon entropy.
我们提出了一种基于表观遗传学、机器学习和高分子物理学的综合理论,从中揭示了热力学弗洛里-哈金斯参数(χ)、表观遗传年龄(eAge)和香农熵之间的新关系。通过一个用于估计核环境中χ的框架,我们表明χ∝eAge-1且χ∝香农熵-1。随着细胞衰老,表观遗传漂变导致表观遗传景观“平滑化”,降低了χ的大小。表观遗传年轻化逆转表观遗传漂变,并将χ恢复到年轻细胞中的水平,同时降低eAge和香农熵。