Introduction to EPI (Extreme Physical Information)

B. Roy Frieden
Optical Science
Univ. of Arizona
Tucson, Arizona 85721
roy.frieden@optics.arizona.edu
Presented in the Embryo Physics Course, October 20, 2010

Abstract

Living systems use information and energy to maintain stable entropy in a system that is far from thermodynamic equilibrium. However, a quantitative relationship between information and the function and growth of a living system has not yet been developed. We propose a fundamental principle of living systems is that every process of life, including metabolism, signal transduction and protein synthesis, represents a flow of information which, when expressed as Fisher information in particular, is constrained to be either a maximum or minimum. Either extreme state is invariant to first-order perturbation and, hence, maintains stable entropy, as required. Such a state also optimizes intracellular information flow, by the suitable adjustment of the information source and the trajectories of information carriers. This principle has, so far, predicted the (i) observable function and growth characteristics of normal cells or multicellular organisms; the (ii) Lotka-Volterra equations and (iii) power laws of allometry for normal growth. Similarly, it has predicted the (iv) loss of normal function and growth in early cancers, by assuming that carcinogenesis is fundamentally an information “catastrophe” where information regarding cell age and location undergoes transition from a maximum to a minimum state. The minimum leads to a predicted (and confirmed) power-law governing in situ cancer growth in time. (v) It also predicts a program of chemotherapy (termed “adaptive therapy”) that converts the process of cancer mass growth into one of monotonic mass reduction, indicating conversion to a chronic, but manageable, condition.

Presentation

/files/presentations/Frieden2010.pdf

Links

http://www.optics.arizona.edu/frieden/

http://www.optics.arizona.edu/frieden/Fisher_Information.htm

Functional and Malignant Cell Growth obey Extreme Information Pathways


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