Dataset Information

Rate of entropy model for irreversible processes in living systems.

ABSTRACT: In living systems, it is crucial to study the exchange of entropy that plays a fundamental role in the understanding of irreversible chemical reactions. However, there are not yet works able to describe in a systematic way the rate of entropy production associated to irreversible processes. Hence, here we develop a theoretical model to compute the rate of entropy in the minimum living system. In particular, we apply the model to the most interesting and relevant case of metabolic network, the glucose catabolism in normal and cancer cells. We show, (i) the rate of internal entropy is mainly due to irreversible chemical reactions, and (ii) the rate of external entropy is mostly correlated to the heat flow towards the intercellular environment. The future applications of our model could be of fundamental importance for a more complete understanding of self-renewal and physiopatologic processes and could potentially be a support for cancer detection.

SUBMITTER: Zivieri R

PROVIDER: S-EPMC5567375 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Rate of entropy model for irreversible processes in living systems.

Zivieri R R Pacini N N Finocchio G G Carpentieri M M

Scientific reports 20170822 1

In living systems, it is crucial to study the exchange of entropy that plays a fundamental role in the understanding of irreversible chemical reactions. However, there are not yet works able to describe in a systematic way the rate of entropy production associated to irreversible processes. Hence, here we develop a theoretical model to compute the rate of entropy in the minimum living system. In particular, we apply the model to the most interesting and relevant case of metabolic network, the gl ...[more]

PMID: 28831153

Similar Datasets

Project description:Parasites and pathogens are a fundamental driving force in the ecology and evolution of mammalian populations, and understanding disease processes in natural populations is an urgent priority in the face of increased rates of infectious disease emergence. In this review, we argue that mammalogists are uniquely placed to contribute to addressing these challenges because in-depth knowledge of mammal species is fundamental to the development of wild model systems that could accelerate discovery in disease ecology. The use of animal models-species for which a broad range of diagnostic, molecular, and genetic tools have been developed-in tightly controlled laboratory environments has been instrumental in driving progress in the biomedical sciences. However, in natural populations, disease processes operate in the context of enormous genetic, phenotypic, and environmental variability. Understanding diseases in animal populations (including humans) thus requires investment in "wild animal models" that explicitly include individual variation and relevant environmental gradients. Wild mammal groups such as primates and rodents have already been identified as potentially useful models of infectious diseases in the wild. Here, we discuss the enormous potential that ungulates hold as candidates for wild model systems. The diversity, broad geographic distribution, and often high abundance of species in this group make them a highly accessible target for disease research. Moreover, a depth of background knowledge, close relationships to domesticated animals, and ongoing management of many wild ungulate species provide context, tools, and opportunity for cutting-edge research at the interface of ecological and biomedical sciences. Studies of wild ungulates are already helping to unravel some key challenges in infectious disease research, including the role of parasites in trophic cascades, the consequences of climate change for disease dynamics, and the systems biology of host-parasite interactions. Other areas where ungulate studies may provide new insight include research on the sources and drivers of emerging infectious diseases.

Dataset Information

Rate of entropy model for irreversible processes in living systems.

Publications

Rate of entropy model for irreversible processes in living systems.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets