A functional approach to homeostatic regulation.

IF 5.7 2区 生物学 Q1 BIOLOGY
Clemente F Arias, Francisco J Acosta, Federica Bertocchini, Cristina Fernández-Arias
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引用次数: 0

Abstract

In this work, we present a novel modeling framework for understanding the dynamics of homeostatic regulation. Inspired by engineering control theory, this framework incorporates unique features of biological systems. First, biological variables often play physiological roles, and taking this functional context into consideration is essential to fully understand the goals and constraints of homeostatic regulation. Second, biological signals are not abstract variables, but rather material molecules that may undergo complex turnover processes of synthesis and degradation. We suggest that the particular nature of biological signals may condition the type of information they can convey, and their potential role in shaping the dynamics and the ultimate purpose of homeostatic systems. We show that the dynamic interplay between regulated variables and control signals is a key determinant of biological homeostasis, challenging the necessity and the convenience of strictly extrapolating concepts from engineering control theory in modeling the dynamics of homeostatic systems. This work provides a simple, unified framework for studying biological regulation and identifies general principles that transcend molecular details of particular homeostatic mechanisms. We show how this approach can be naturally applied to apparently different regulatory systems, contributing to a deeper understanding of homeostasis as a fundamental process in living systems.

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来源期刊
Biology Direct
Biology Direct 生物-生物学
CiteScore
6.40
自引率
10.90%
发文量
32
审稿时长
7 months
期刊介绍: Biology Direct serves the life science research community as an open access, peer-reviewed online journal, providing authors and readers with an alternative to the traditional model of peer review. Biology Direct considers original research articles, hypotheses, comments, discovery notes and reviews in subject areas currently identified as those most conducive to the open review approach, primarily those with a significant non-experimental component.
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