Bellomo, M* Dotaz Zobrazit nápovědu

Přesná shoda Sémantické

This review paper is devoted to study the conceptual difficulties that mathematics meets when attempting to describe the complexity of living matter focusing on the challenging perspective of developing a mathematical theory for living systems including mutations and selection. The quest starts with the identification of a number of common complexity features of living systems. Then, mathematical structures are derived to include these features, while mathematical models are derived by inserting in the structures models of individual based interactions. Three applications are examined by active particles methods, i.e., models of SARS2-CoV-2 pandemics, models of idiosyncratic learning in open markets and of the dynamics of prices accounting for human behaviors. A critical study, which pervades the whole paper, shows that also economics can be viewed as a behavioral science thus accounting for specific aspects typical of living systems.

Kniha

Acute kidney injury

... Acute kidney injury is defined as an abrupt change in serum creatinine and/or urine output, and a majority ...

Ronco, Claudio, (Claudio), 1951-
Autor Autorita ORCID
Bellomo, R. (Rinaldo), 1956-
Autor Autorita ORCID
Kellum, John A
Autor Autorita

Basel : Karger, 2007

Contributions to nephrology, ISSN 0302-5144 v. 156

xii, 463 s. : il. ; 25 cm

Článek online

Monte-Carlo modeling of the central carbon metabolism of Lactococcus lactis: insights into metabolic regulation

... Metabolic pathways are complex dynamic systems whose response to perturbations and environmental challenges ...

PLoS One. 2014 ; 9 (9) : e106453.

ISSN 1932-6203
Medvik
Zdroj

Metabolic pathways are complex dynamic systems whose response to perturbations and environmental challenges are governed by multiple interdependencies between enzyme properties, reactions rates, and substrate levels. Understanding the dynamics arising from such a network can be greatly enhanced by the construction of a computational model that embodies the properties of the respective system. Such models aim to incorporate mechanistic details of cellular interactions to mimic the temporal behavior of the biochemical reaction system and usually require substantial knowledge of kinetic parameters to allow meaningful conclusions. Several approaches have been suggested to overcome the severe data requirements of kinetic modeling, including the use of approximative kinetics and Monte-Carlo sampling of reaction parameters. In this work, we employ a probabilistic approach to study the response of a complex metabolic system, the central metabolism of the lactic acid bacterium Lactococcus lactis, subject to perturbations and brief periods of starvation. Supplementing existing methodologies, we show that it is possible to acquire a detailed understanding of the control properties of a corresponding metabolic pathway model that is directly based on experimental observations. In particular, we delineate the role of enzymatic regulation to maintain metabolic stability and metabolic recovery after periods of starvation. It is shown that the feedforward activation of the pyruvate kinase by fructose-1,6-bisphosphate qualitatively alters the bifurcation structure of the corresponding pathway model, indicating a crucial role of enzymatic regulation to prevent metabolic collapse for low external concentrations of glucose. We argue that similar probabilistic methodologies will help our understanding of dynamic properties of small-, medium- and large-scale metabolic networks models.