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A General Approach for the Modelling of Negative Feedback Physiological Control Systems

Authors :
Alfonso Maria Ponsiglione
Francesco Montefusco
Leandro Donisi
Annarita Tedesco
Carlo Cosentino
Alessio Merola
Maria Romano
Francesco Amato
Source :
Bioengineering, Vol 10, Iss 7, p 835 (2023)
Publication Year :
2023
Publisher :
MDPI AG, 2023.

Abstract

Mathematical models can improve the understanding of physiological systems behaviour, which is a fundamental topic in the bioengineering field. Having a reliable model enables researchers to carry out in silico experiments, which require less time and resources compared to their in vivo and in vitro counterparts. This work’s objective is to capture the characteristics that a nonlinear dynamical mathematical model should exhibit, in order to describe physiological control systems at different scales. The similarities among various negative feedback physiological systems have been investigated and a unique general framework to describe them has been proposed. Within such a framework, both the existence and stability of equilibrium points are investigated. The model here introduced is based on a closed-loop topology, on which the homeostatic process is based. Finally, to validate the model, three paradigmatic examples of physiological control systems are illustrated and discussed: the ultrasensitivity mechanism for achieving homeostasis in biomolecular circuits, the blood glucose regulation, and the neuromuscular reflex arc (also referred to as muscle stretch reflex). The results show that, by a suitable choice of the modelling functions, the dynamic evolution of the systems under study can be described through the proposed general nonlinear model. Furthermore, the analysis of the equilibrium points and dynamics of the above-mentioned systems are consistent with the literature.

Details

Language :
English
ISSN :
23065354
Volume :
10
Issue :
7
Database :
Directory of Open Access Journals
Journal :
Bioengineering
Publication Type :
Academic Journal
Accession number :
edsdoj.1cd64da062c44fefb08dff0952152cb6
Document Type :
article
Full Text :
https://doi.org/10.3390/bioengineering10070835