The Spiral Model of Evolution: Stable Life Forms of Organisms and Unstable Life Forms of Cancers.

If one must prioritize among the vast array of contributing factors to cancer evolution, environmental-stress-mediated chromosome instability (CIN) should easily surpass individual gene mutations. CIN leads to the emergence of genomically unstable life forms, enabling them to grow dominantly within the stable life form of the host. In contrast, stochastic gene mutations play a role in aiding the growth of the cancer population, with their importance depending on the initial emergence of the new system. Furthermore, many specific gene mutations among the many available can perform this function, decreasing the clinical value of any specific gene mutation. Since these unstable life forms can respond to treatment differently than stable ones, cancer often escapes from drug treatment by forming new systems, which leads to problems during the treatment for patients. To understand how diverse factors impact CIN-mediated macroevolution and genome integrity-ensured microevolution, the concept of two-phased cancer evolution is used to reconcile some major characteristics of cancer, such as bioenergetic, unicellular, and multicellular evolution. Specifically, the spiral of life function model is proposed, which integrates major historical evolutionary innovations and conservation with information management. Unlike normal organismal evolution in the microevolutionary phase, where a given species occupies a specific location within the spiral, cancer populations are highly heterogenous at multiple levels, including epigenetic levels. Individual cells occupy different levels and positions within the spiral, leading to supersystems of mixed cellular populations that exhibit both macro and microevolution. This analysis, utilizing karyotype to define the genetic networks of the cellular system and CIN to determine the instability of the system, as well as considering gene mutation and epigenetics as modifiers of the system for information amplification and usage, explores the high evolutionary potential of cancer. It provides a new, unified understanding of cancer as a supersystem, encouraging efforts to leverage the dynamics of CIN to develop improved treatment options. Moreover, it offers a historically contingent model for organismal evolution that reconciles the roles of both evolutionary innovation and conservation through macroevolution and microevolution, respectively.

The Digital World of Cytogenetic and Cytogenomic Web Resources.

The dynamic growth of technological capabilities at the cellular and molecular level has led to a rapid increase in the amount of data on the genes and genomes of organisms. In order to store, access, compare, validate, classify, and understand the massive data generated by different researchers, and to promote effective communication among research communities, various genome and cytogenetic online databases have been established. These data platforms/resources are essential not only for computational analyses and theoretical syntheses but also for helping researchers select future research topics and prioritize molecular targets. Furthermore, they are valuable for identifying shared recurrent genomic patterns related to human diseases and for avoiding unnecessary duplications among different researchers. The website interface, menu, graphics, animations, text layout, and data from databases are displayed by a front end on the screen of a monitor or smartphone. A database front-end refers to the user interface or application that enables accessing tabular, structured, or raw data stored in the database. The Internet makes it possible to reach a greater number of users around the world and gives them quick access to information stored in databases. The number of ways of presenting this data by front-ends increases as well. This requires unifying the ways of operating and presenting information by front-ends and ensuring contextual switching between front-ends of different databases. This chapter aims to present selected cytogenetic and cytogenomic Internet resources in terms of obtaining the needed information and to indicate how to increase the efficiency of access to stored information. Through a brief introduction of these databases and by providing examples of their usage in cytogenetic analyses, we aim to bridge the gap between cytogenetics and molecular genomics by encouraging their utilization.

Life Entrapped in a Network of Atavistic Attractors: How to Find a Rescue.

In view of unified cell bioenergetics, cell bioenergetic problems related to cell overenergization can cause excessive disturbances in current cell fate and, as a result, lead to a change of cell-fate. At the onset of the problem, cell overenergization of multicellular organisms (especially overenergization of mitochondria) is solved inter alia by activation and then stimulation of the reversible Crabtree effect by cells. Unfortunately, this apparently good solution can also lead to a much bigger problem when, despite the activation of the Crabtree effect, cell overenergization persists for a long time. In such a case, cancer transformation, along with the Warburg effect, may occur to further reduce or stop the charging of mitochondria by high-energy molecules. Understanding the phenomena of cancer transformation and cancer development has become a real challenge for humanity. To date, many models have been developed to understand cancer-related mechanisms. Nowadays, combining all these models into one coherent universal model of cancer transformation and development can be considered a new challenge. In this light, the aim of this article is to present such a potentially universal model supported by a proposed new model of cellular functionality evolution. The methods of fighting cancer resulting from unified cell bioenergetics and the two presented models are also considered.

Study on attractors during organism evolution.

The important question that arises during determining the evolution of organisms is whether evolution should be treated as a continuous process or whether groups of organisms fall into 'local' attractors during evolution. A similar question arises during considering the development of cells after cancer transformation. Answers to these questions can provide a better understanding of how normal and transformed organisms evolve. So far, no satisfactory answers have been found to these questions. To find the answers and demonstrate that organisms during evolution get trapped in 'local' attractors, an artificial neural network supported by a semihomologous approach and unified cell bioenergetics concept have been used in this work. A new universal model of cancer transformation and cancer development has been established and presented to highlight the differences between the development of transformed cells and normal organisms. An unequivocal explanation of cancer initialization and development has not been discovered so far, thus the proposed model should shed new light on the evolution of transformed cells.

Self-organization of whole-gene expression through coordinated chromatin structural transition.

The human DNA molecule is a 2-m-long polymer collapsed into the micrometer space of the cell nucleus. This simple consideration rules out any "Maxwell demon"-like explanation of regulation in which a single regulatory molecule (e.g., a transcription factor) finds autonomously its way to the particular target gene whose expression must be repressed or enhanced. A gene-by-gene regulation is still more contrasting with the physical reality when in the presence of cell state transitions involving the contemporary expression change of thousands of genes. This state of affair asks for a statistical mechanics inspired approach where specificity arises from a selective unfolding of chromatin driving the rewiring of gene expression pattern. The arising of "expression waves" marking state transitions related to chromatin structural reorganization through self-organized critical control of whole-genome expression will be described in the present paper. We adopt as a model system the gene expression time course of a cancer cell (MCF-7) population exposed to an efficient stimulus causing a state transition in comparison with an ineffective stimulus. The obtained results will be put into the perspective of biological adaptive systems living on the edge of chaos.

Bioenergetics of life, disease and death phenomena.

In this article, some new aspects of unified cell bioenergetics are presented. From the perspective of unified cell bioenergetics certain subsequent stages of cancer development, from initiation stage, through transformation to metastasis, are analyzed. Here we show that after transformation, cancer cells are permanently exposed to reactive oxygen species, that causes continual random DNA mutations and as a result genome and chromosomal destabilizations. The modern cancer attractor hypothesis has been extended in explaining cancer development. Discussion is conducted in light of current cancerogenesis research, including bioenergetic cancer initiation, the somatic mutation theory and the tissue organization field theory. In the article reasons complicating the discovery of patterns of cancer genome changes and cancer evolution are presented. In addition certain cancer therapeutic aspects are given attention to.

A new approach to the automatic identification of organism evolution using neural networks.

Automatic identification of organism evolution still remains a challenging task, which is especially exiting, when the evolution of human is considered. The main aim of this work is to present a new idea to allow organism evolution analysis using neural networks. Here we show that it is possible to identify evolution of any organisms in a fully automatic way using the designed EvolutionXXI program, which contains implemented neural network. The neural network has been taught using cytochrome b sequences of selected organisms. Then, analyses have been carried out for the various exemplary organisms in order to demonstrate capabilities of the EvolutionXXI program. It is shown that the presented idea allows supporting existing hypotheses, concerning evolutionary relationships between selected organisms, among others, Sirenia and elephants, hippopotami and whales, scorpions and spiders, dolphins and whales. Moreover, primate (including human), tree shrew and yeast evolution has been reconstructed.

Studies on generalized kinetic model and Pareto optimization of a product-driven self-cycling bioprocess.

The aim of this study is the optimization of a product-driven self-cycling bioprocess and presentation of a way to determine the best possible decision variables out of a set of alternatives based on the designed model. Initially, a product-driven generalized kinetic model, which allows a flexible choice of the most appropriate kinetics is designed and analysed. The optimization problem is given as the bi-objective one, where maximization of biomass productivity and minimization of unproductive loss of substrate are the objective functions. Then, the Pareto fronts are calculated for exemplary kinetics. It is found that in the designed bioprocess, a decrease of emptying/refilling fraction and an increase of substrate feeding concentration cause an increase of the biomass productivity. An increase of emptying/refilling fraction and a decrease of substrate feeding concentration cause a decrease of unproductive loss of substrate. The preferred solutions are calculated using the minimum distance from an ideal solution method, while giving proposals of their modifications derived from a decision maker's reactions to the generated solutions.

Theoretical approach to modelling and analysis of the bioprocess with product inhibition and impulse effect.

This work presents the first mathematical model of a bioprocess with product inhibition and impulse effect. To begin with, an exemplary mathematical bioprocess model with product inhibition and impulse effect is formulated. Then, according to the model, the analysis of bioprocess stability is presented. The article expresses the product oscillation period, which provides the precise feeding time frame for the regulator bioprocess to achieve an equivalent stable output as that of a bioprocess with impulse effect in the same production environment. Moreover, in this work, the optimization of the production process with respect to the tunable parameters is investigated, and analytical expressions of their optimal values are provided. Numerical simulations using biological data are presented to illustrate the main results.

Modelling of cells bioenergetics.

This paper presents an integrated model describing the control of Saccharomyces cerevisiae yeast cells bioenergetics. This model describes the oxidative and respirofermentative metabolism. The model assumes that the mitochondria of the Saccharomyces cerevisiae cells are charged with NADH during the tricarboxylic acid cycle, and NADH is discharged from mitochondria later in the electron transport system. Selected effects observed in the Saccharomyces cerevisiae eucaryotic cells, including the Pasteur's and Crabtree effects, are also modeled.