The human body consists of about 3.7´1013 cells, while a rough average of 109 chemical reactions per second occur inside each cell, yielding a total of about 1022 per second. The huge complexity of this system, and the lack of a synthetic theory, inevitably affect the possibility of explaining events and processes, thus setting limits e.g. to the understanding and management of recalcitrant diseases like allergies, autoimmune and metabolic syndromes, cardiovascular disorders, neurodegenerative processes, and cancer. Life sciences principally model the body’s functioning by using open chains (i.e. open loops), but the body is a self-sustained system maintaining steady state, meaning that its processes must be conversely regulated by closed loops. Loop dynamics can lead to stable equilibrium points, such as the regulation of body temperature and blood pressure, or give rise to sustained oscillations, like hormone fluctuations, pacemaker activities, and neural oscillatory activity. We considered endocrine and neural networks from literature data and experimental recordings, and then modeled them in terms of functional agents (loop nodes) and their interactions (loop arcs), allowing us to investigate loop dynamics at different scales. We performed a structural analysis of the resulting dynamic loop network, described in terms of an ordinary differential-equation model, and of the associated interaction matrix. Our analysis revealed the presence of candidate oscillators, each admitting a single equilibrium point that can either be stable or give rise to oscillatory instability. Such a result could represent a recurrent motif of loop arrangements, both within and among cells and organs, possibly leading to a general paradigm with direct repercussions on medicine and health care.
|Titolo:||Loopomics: explaining the complexity of life by conjugating physiology and control theory|
|Data di pubblicazione:||2019|
|Appare nelle tipologie:||01.05 - Abstract su rivista|