Theoretical Biology Forum最新文献

For nearly a century the main focus in biological disciplines such as molecular biology, biochemistry, genetics and evolutionary theory was cellular life as a machine like process in which mechanistic pathways regulate metabolism, genetic reading and translation into proteins and evolution by variations (random error replications) and selection. Modern biochemistry started with the cellular theory of life. Also the modern synthesis focused on cells at the starting event of life. The dominance of this paradigm lasted until ten years ago. Then the comeback of virology offered new empirical data and explanatory models of how viruses determine cellular life through an abundance of parasite host interactions that overrule cellular processes. The RNA world hypothesis demonstrated that prior to cellular life RNA group interactions were at the beginning of biological selection before cellular life emerged. Last but not least the central dogma of molecular biology collapsed when epigenetics demonstrated that history and developmental experiences of the past can be epigenetically imprinted and serve as identity markings that in every replication process of any cell in any organism on this planet the timely and locally coordinated replication is regulated and orchestrated by these programmings. In the light of this knowledge a better explanatory model than an extension of the modern synthesis will be more successful in the 21st century.

The Third Way of Evolution was founded in 2014 to make the public aware that contemporary evolution science is not limited to the neo-Darwinian Modern Synthesis of the past century. This was important to do because evolution was challenged as incapable of explaining biological complexity by the Intelligent Design movement. Expounding biological theories like the Modern Synthesis is always subject to limited empirical evidence, fundamental concepts that inevitably change over time, and conceptual preferences that often prove to be misleading. The Modern Synthesis was based on Darwin's preference for the phyletic gradualism necessary to elevate Natural Selection as the sole force determining the direction of evolutionary change. In contradiction to this principle, agricultural crop breeding, direct observation in nature, and genomics have shown that genome change following symbiogenetic cell fusions or interspecific hybridization, not selection, are empirically the most effective methods for originating novel life forms and new species. By asserting that the accumulation of random "slight" variations was the basic mode of both short-term and long-term evolutionary change, the Modern Synthesis also ignored the distinction between (1) microevolutionary change within species by localized mutations and (2) macroevolutionary origination of new species and taxa by genome restructuring. In so doing, the Modern Synthesis failed to recognize the evolutionary importance of cellular capacities to generate large-scale genome changes. By focusing on individual protein-coding genes as the fundamental units of genetic information, the Modern Synthesis did not successfully incorporate either the full non-coding informa tion content in genomes or the major evolutionary potential of mobile DNA elements to generate multisite intragenomic networks necessary for the development of complex organisms. When all of the phenomena overlooked by the Modern Synthesis are taken into consideration, it is not difficult to answer Intelligent Design arguments and show that science is making real progress in understanding the evolution of biological complexity.

In this paper we report the description, implementation and application of a kinetic model designed for describing the Covid-19 epidemic spread in Italy and Germany in the period between February and June 2020 coinciding with the beginning of the statistical regime of the epidemic spread and the application of restrictive government measures aimed at its containment. The model, which makes use of a limited number of parameters, in spite of its simplicity is able of capturing the essential physical features of the epidemic spread highlighting the essential role of the restrictive measures and in particular the timeliness of their application for the containment of the most dramatic consequences. This work also confirms how the epidemic spread, if considered during its statistical-regime evolution, can be properly described - and hence probably better understood - using languages and methodologies typically adopted for chemical processes, such as the Mass Action Law and Chemical Kinetics.

It is well known that Giovanni Virginio Schiaparelli (1834-1910) wrote in 1898 an essay, Forme organiche naturali e forme geometriche pure. Studio comparativo, which was also appreciated by Vito Volterra (1860-1940). Recent studies have revised Schiaparelli's evolutionary ideas with new proposals and from this it is possible to obtain a dynamical (deterministic) model. In this paper I propose a related stochastic model (as toy model): thanks to this tool, we can describe a speciation phenomenology.

The recent Covid-19 epidemic has pointed out the inadequacy of the plans applied by industrial countries to limit the epidemic spread and frailty of the global economy to cope with a pandemic. Many countries were forced to a global lockdown with a great socio-economic impact. In Italy, one of the problems was the complex mobility network structure of the Northern regions that made ineffective the attempts to isolate the initial hotspots. In the paper we study a simple model that simulates the epidemic spread on a community network that may exchange population according to a daily mobility rate. In each community the epidemic evolution is provided by a stochastic compartmental model whose parameters are tuned to reproduce the Covid-19 evolution observed in Italy before the global lockdown policies. We initially study the delay in the epidemic spread due to the finite local mobility by proposing a power law relation for the increasing of the infection peak time in each node and the network distance from the initial node where the epidemic starts. We consider two scenarios to study the effectiveness of local lockdown policies: the presence of two clusters weakly connected by the mobility or a homogeneous chain of communities that exchange the population at a fixed rate. In both cases we show the existence of a threshold effect, in a probabilistic sense, for the effectiveness of lockdown policies as a function of the delay time at which such policies are applied, or of the network distance from the outbreak node.

1. Introduction. 2. The Specific-mate Recognition System (SMRS). 3. The Genetic Change As sociated with Speciation.