Glycemia Regulation: From Feedback Loops to Organizational Closure - Bich, Leonardo; Mossio, Matteo; Soto, Ana M. (Frontiers in Physiology, 2020)
Endocrinologists apply the idea of feedback control to explain how hormones regulate certain bodily functions such as glucose metabolism. More precisely, these feedback loops center on the maintenance of the plasma concentrations of glucose within a narrow range. In this paper we put forward a different interpretation of endocrine regulation considering an organicist theoretical perspective, which relies on the pivotal concept of closure of constraints. From this perspective, biological systems are understood as organized ones, which in turn means that they are constituted by a set of mutually dependent functional structures working as constraints, whose maintenance depends on their reciprocal interactions. Closure refers specifically to the mutual dependence among functional constraints in an organism. The goal of this paper is to apply this theoretical framework to the control of glycaemia. The organizational approach requires the identification of the relevant processes and the first-order constraints acting upon them. Then, the dependencies between the constraints are represented to obtain a closed graph, in which at least a subset of constraints are maintained by processes under the control of other constraints, so that the entire network can be said to realize collective self-maintenance. To understand how this set of primary constraints is modulated in response to external perturbations or changes in the internal state of the system, second-order dynamically decoupled constraints need to be identified (such as the hormones insulin and glucagon). Additionally, organs such as the brain and the intestine participate in the modulation of the second order constraints (insulin and glucagon secretion in our example) while responding to particular environmental and internal conditions. Unlike the feedback model which involves a flat network of components, the organizational framework can handle these additional regulatory subsystems by including in the closed graph the pertinent processes and constraints, and by making explicit the different hierarchical orders involved. We expect that the development of the proposed theoretical framework will facilitate the construction of mathematical models and provide a better understanding of endocrine regulation from the perspective of the organism and the subsystem being modeled.