(logo) Natural Genesis (logo text)
A Sourcebook for the Worldwide Discovery of a Creative Organic Universe
Table of Contents
Genesis Vision
Learning Planet
Organic Universe
Earth Life Emerge
Genesis Future
Recent Additions

III. Ecosmos: A Revolutionary Fertile, Habitable, Solar-Bioplanet, Incubator Lifescape

2. A Consilience as Physics and Biology Grow Together: Active Matter

Diaz, Jorge and Roberto Mulet. Statistical Mechanics of Interacting Metabolic Networks. Physical Review E. 101/042401, 2020. A University of Havana systems biologist and a physicist discern an array of affinities between cellular processes and condensed matter as life’s complexity and animate cosmos proceed to reunite and grow together. See also Characterizing Steady States of Genome Scale Metabolic Networks in PLoS Computational Biology (November 2017) and A Physical Model of Cell Metabolism in Nature Scientific Reports (8/8349, 2018) by the authors and colleagues.

We cast the metabolism of interacting cells within a statistical mechanics framework with regard to the phenotypic capacities of each cell and its interaction with its neighbors. Reaction fluxes will be the components of spin vectors, whose values are constrained by stochiometry and energy requirements of the metabolism. Within this picture, the phenotypic states of the population are equivalent to the equilibrium states of a disordered spin model. We apply this solution to a simplified model of metabolism and a complex metabolic network, the central core of Escherichia coli, to demonstrate that the combination of selective pressure and interactions defines a complex phenotypic space. Cells may specialize in producing or consuming metabolites, which is described by an equilibrium phase space akin to a spin-glass model. (Abstract excerpt)

Dorogovtsev, Sergei, et al. Critical Phenomena in Complex Networks. Reviews of Modern Physics. 80/4, 2008. Universidade de Aveiro, Portugal physicists provide a detailed tutorial for the evident ubiquity of scale-free nets to persist in a state of self-organized criticality.

Critical phenomena in networks include a wide range of issues: structural changes in networks, the emergence of critical—scale-free—network architectures, various percolation phenomena, epidemic thresholds, phase transitions in cooperative models defined on networks, critical points of diverse optimization problems, transitions in co-evolving couples—a cooperative model and its network substrate, transitions between different regimes in processes taking place on networks, and many others. We will show that many of these critical effects are closely related and universal for different models and may be described and explained in the framework of a unified approach. (1277)

Eckmann, Jean-Pierre, et al. Proteins: The Physics of Amorphous Evolving Matter. Reviews of Modern Physics. 91/031001, 2019. J-P E and Jacques Rougemont, University of Geneva and Tsvi Tlusty, Ulsan National Institute of Science and Technology, post a tutorial paper which traces a pathway by which to join and root life’s biochemical processes within fundamental condensed matter principles. In this computational view, proteins arise from collective many-body interactions in amino acid matter as the outcome of an evolutionary search in a high-dimensional space of gene sequences. In regard, an evolutionary learning process is seen to act as a combinatorial search within an optimization process. See also Physical Model of the Genotype to Phenotype Map of Proteins by the authors with Albert Libchaber in Physical Review X (7/021037, 2017). These and many other insightful efforts are presently revealing a unified, lively ovoGenesis uniVerse.

Proteins are a matter of dual nature. As a physical object, a protein molecule is a folded chain of amino acids with multifarious biochemistry. But it is also an instantiation along an evolutionary trajectory determined by the function performed by the protein within a hierarchy of interwoven interaction networks of the cell, the organism and the population. A physical theory of proteins therefore needs to unify both the biophysical and the evolutionary. We review physical approaches by way of a mechanical framework which treats proteins as evolvable condensed matter: Mutations introduce localized perturbations in the gene, which are similarly translated into the protein matter. A natural tool seems to be Green's functions (Wikipedia)as they map the evolutionary linkage among mutations in the gene to cooperative physical interactions among the amino acids. (Abstract excerpt)

Elaiw, Ahmed, et al. On Entropy Dynamics for Active “Living” Particles. Entropy. Online October, 2017. King Abdulaziz University, Saudi Arabia system physicists including Nicola Bellomo (search) consider this newly perceived feature of physical materiality to inherently self-organize into animate assemblies. If to consider this work, and e.g., a cosmology paper by the Iranian physicists Khanpour and Yusofi (search), might a palliative 21st century renaissance of Islamic science be actually be underway? See also these concurrent books by the authors: A Quest Towards a Mathematical Theory of Living Systems and Active Particles: Advances in theory, Models, and Applications, see second quote, both from Springer/Birkhauser.

This paper presents a modeling approach, followed by entropy calculations of the dynamics of large systems of interacting active particles viewed as living—hence, complex—systems. Active particles are partitioned into functional subsystems, while their state is modeled by a discrete scalar variable, while the state of the overall system is defined by a probability distribution function over the state of the particles. The aim of this paper consists of contributing to a further development of the mathematical kinetic theory of active particles. (Abstract)

This volume collects ten surveys on the modeling, simulation, and applications of active particles using methods ranging from mathematical kinetic theory to nonequilibrium statistical mechanics. The contributing authors are leading experts working in this challenging field, and each of their chapters provides a review of the most recent results in their areas and looks ahead to future research directions. The approaches to studying active matter are presented here from many different perspectives, such as individual-based models, evolutionary games, Brownian motion, and continuum theories, as well as various combinations of these. Applications covered include biological network formation and network theory; opinion formation and social systems; control theory of sparse systems; theory and applications of mean field games; population learning; dynamics of flocking systems; vehicular traffic flow; and stochastic particles and mean field approximation. (AP summary)

England, Jeremy. Statistical Physics of Self-Replication. Journal of Chemical Physics. 139/121923, 2013. A young MIT physicist forges ahead with the persuasion that living systems must be sourced in and explained by nature’s far-from-equilibrium phenomena via thermodynamic energies and entropies. His project received much notice in the online Quanta Magazine in a January 2014 article “A New Physics Theory of Life” by Natalie Wolchover. See also an endorsement Biology and Nonequilibrium by the mathematician David Ruelle in European Physical Journal Special Topics, (224/935, 2015). I heard Jeremy speak at the University of Massachusetts, Amherst in April 2016 on the Statistical Physics of Adaptation (second quote) where he saw his work as a continuance of Ilya Prigogine’s theories, and more recently of Gavin Crooks (search) and other colleagues.

Self-replication is a capacity common to every species of living thing, and simple physical intuition dictates that such a process must invariably be fueled by the production of entropy. Here, we undertake to make this intuition rigorous and quantitative by deriving a lower bound for the amount of heat that is produced during a process of self-replication in a system coupled to a thermal bath. We find that the minimum value for the physically allowed rate of heat production is determined by the growth rate, internal entropy, and durability of the replicator, and we discuss the implications of this finding for bacterial cell division, as well as for the pre-biotic emergence of self-replicating nucleic acids. (Article Abstract)

Many-body systems that are driven far from thermal equilibrium can exhibit a seemingly endless range of different "self-organization" phenomena, whether during long periods of transient relaxation over a hierarchy of timescales, or in an ergodic steady-state. Indeed, the range of possible behaviors is so diverse that it includes (but is not limited to) everything that living things do! In the face of such phenomenological diversity, it is difficult to articulate any thermodynamic commonality that might be analogous to the tendency to minimize free energy observed in equilibrated systems. Here, we try to exploit recent fundamental progress in our understanding of far-from-equilibrium dynamics to develop predictive thermodynamic principles for a general class of driven self-organized systems. We find there is a language in which Darwinian selection in biological systems may be thought of as a special case of a more general physical tendency for "dissipative adaptation" that arises from the correlation between irreversible changes in shape and the absorption of external work. (Talk Abstract)

Fleming, Graham, chair. Quantum Effects in Chemistry and Biology. Procedia Chemistry. 3/1, 2011. As the proceedings of this 22nd Solvay Conference on Chemistry, after the 1911 Solvay Conference on Physics that initiated the legendary series. A century later quantum phenomena is being assimilated into these macro domains, at the same time it si rooting, informing and expanding their essence. Notable papers are Quantum Effects in Biology by Fleming, et al, Quantum Effects in Chemistry by Mark Ratner and Ronnie Kosloff, and Quantum Correlations in Biomolecules by Vlatko Vedral.

Fodor, Etienne and M. Cristina Marchetti. The Statistical Physics of Active Matter: From Self-Catalytic Colloids to Living Cells. arXiv:1708.08652. Some seven years since Sriram Ramaswamy (search) recognized and named this facility of organic physiologies to exhibit spontaneous formations traceable to physical forces, Cambridge University and Cornell University researchers provide a tutorial overview with 101 references of the now popular field, aka Soft Matter. I enter a day after hearing Dr. Marchetti speak at the University of Massachusetts, Amherst, second quote, where she reported on their common recurrence over a range of lively movements from tissue cultures and embryogenesis to starling flocks. An independent, universal source thus seems to be implied as interactive elements proceed to dynamically cooperate and self-organize. The third quote is a capsule for her Soft Matter Laboratory.

These lecture notes are designed to provide a brief introduction into the phenomenology of active matter and to present some of the analytical tools used to rationalize the emergent behavior of active systems. Such systems are made of interacting agents able to extract energy stored in the environment to produce sustained directed motion. The local conversion of energy into mechanical work drives the system far from equilibrium, yielding new dynamics and phases. The emerging phenomena can be classified depending on the symmetry of the active particles and on the type of microscopic interactions. We focus here on steric and aligning interactions, as well as interactions driven by shape changes. The models that we present are all inspired by experimental realizations of either synthetic, biomimetic or living systems. Based on minimal ingredients, they are meant to bring a simple and synthetic understanding of the complex phenomenology of active matter. (Abstract)

Collections of self-propelled entities, from living cells to engineered microswimmers, organize in a rich variety of active fluid and solid states, with unusual properties. For instance, active fluids can flow with no externally applied driving forces and active gases do not fill their container. In this talk I will describe the behavior of such “active materials” and highlight two examples of active phase transitions. The first is the formation of cohesive matter with no cohesive forces in collections of purely repulsive active colloids. The second is a new density-independent solid-liquid transition in epithelial tissues controlled by cell motility and a cell-shape parameter measuring the interplay of cortical tension and cell-cell adhesion. An important insight of this work is that cell shape correlates with the mechanical properties of living tissues. (MCM Presentation – U Mass Amherst, Sept. 13, 2017)

Our (MCM) group is interested in the emergent behavior of soft and biological materials that are driven out of equilibrium by an external drive, internal activity or quenched disorder. We use theory and computation to investigate the rich dynamics of a broad range of systems, from vibrated granular matter to bacterial suspensions, the cell cytoskeleton and living tissues. Our work makes complementary use of bottom-up modeling and top-down phenomenology to highlight the role of physical interactions relative to genetically and biochemically- regulated signaling in controlling the large scale structural organization and the mechanical properties of these complex systems. (https://mcmarche.expressions.syr.edu/)

Fort, Hugo. Statistical Mechanics Ideas and Techniques Applied to Selected Problems in Ecology. Entropy. Online December, 2013. A Universidad de la República, Uruguay, physicist and Complex Systems Group leader with international collaborations such as Marten Scheffer, contributes to a recent, growing trend to uncover deep consistencies between condensed matter principles and all areas of life’s organic and social evolution (e.g., search Moretti). In this case, three ecosystem features, as the Abstract explains, can be seen to take on quite similar forms to physical phenomena. By this overdue merger a worldwide systems project begins to reassemble the sciences and a common natural cosmos.

Ecosystem dynamics provides an interesting arena for the application of a plethora concepts and techniques from statistical mechanics. Here I review three examples corresponding each one to an important problem in ecology. First, I start with an analytical derivation of clumpy patterns for species relative abundances (SRA) empirically observed in several ecological communities involving a high number n of species, a phenomenon which have puzzled ecologists for decades. An interesting point is that this derivation uses results obtained from a statistical mechanics model for ferromagnets. Second, going beyond the mean field approximation, I study the spatial version of a popular ecological model involving just one species representing vegetation.

It is shown that different quantities—like the variance, the two-point correlation function and the patchiness—may serve as early warnings for the desertification of arid lands. Remarkably, in the onset of a desertification transition the distribution of vegetation patches exhibits scale invariance typical of many physical systems in the vicinity a phase transition. I comment on similarities of and differences between these catastrophic shifts and paradigmatic thermodynamic phase transitions like the liquid-vapor change of state for a fluid. Third, I analyze the case of many species interacting in space. I choose tropical forests, which are mega-diverse ecosystems that exhibit remarkable dynamics. Therefore these ecosystems represent a research paradigm both for studies of complex systems dynamics as well as to unveil the mechanisms responsible for the assembly of species-rich communities. The more classical equilibrium approaches are compared versus non-equilibrium ones and in particular I discuss a recently introduced cellular automaton model in which species compete both locally in physical space and along a niche axis. (Abstract excerpts)

Freeman, Walter, et al. Brain Dynamics, Chaos and Bessel Functions. Journal of Physics: Conference Series. 626/012069, 2015. A paper presented at the 7th International Workshop on Spacetime – Matter – Quantum Mechanics, September 2014, Castiglioncello, Italy. Walter Freeman is a UC Berkeley systems neuroscientist, now 88 years young, a third generation of a legendary family of brain researchers and physicians. Coauthors are Antonio Capolupo, Robert Kozma, Andres Olivares del Campo and Giuseppe Vitiello. (Bessel functions are complex differential equations, please Google.) We cite in this section for its representation of neural qualities in statistical physics and mathematical terms, which can show how much our own brains and thought are rooted in and a continuance of this cosmic cerebral essence. See also arXiv:1506.04393 for more.

A paper presented at the 7th International Workshop on Spacetime – Matter – Quantum Mechanics, September 2014, Castiglioncello, Italy. Walter Freeman is a UC Berkeley systems neuroscientist, now 88 years young, a third generation of a legendary family of brain researchers and physicians. Coauthors are Antonio Capolupo, Robert Kozma, Andres Olivares del Campo and Giuseppe Vitiello. (Bessel functions are complex differential equations, please Google.) We cite in this section for its representation of neural qualities in statistical physics and mathematical terms, which can show how much our own brains and thought are rooted in and a continuance of this cosmic cerebral essence. See also arXiv:1506.04393 for more.

Frey, Erwin and Tobias Reichenbach. Bacterial Games. Meyer-Ortmanns, Hildegard and Stefan Thurner, eds. Principles of Evolution: From the Planck Epoch to Complex Multicellular Life. Berlin: Springer, 2011. Ludwig-Maximilians-Universitat biophysicists view communal bacteria as an exemplar of interactive agent, nonlinear self-organization, to which an “evolutionary game theory” such as public goods games can then contribute. All this on-going phenomena is further seen as a facet of a “nonequilibrium physics.”

Microbial laboratory communities have become model systems for studying the complex interplay between nonlinear dynamics of evolutionary selection forces, stochastic fluctuations arising from the probabilistic nature of interactions, and spatial organization. Major research goals are to identify and understand mechanisms that ensure viability of microbial colonies by allowing for species diversity, cooperative behavior and other kinds of “social” behavior. A synthesis of evolutionary game theory, nonlinear dynamics, and the theory of stochastic processes provides the mathematical tools and conceptual framework for a deeper understanding of these ecological systems. We give an introduction to the modern formulation of these theories and illustrate their effectiveness, focusing on selected examples of microbial systems. (297)

Microbial systems are complex assemblies of large numbers of individuals, interacting competitively under multifaceted environmental conditions. Bacteria often grow in complex, dynamical communities, pervading the earth’s ecological systems, from hot springs to rivers and the human body. (298) The ensuing complexity of bacterial communities has conveyed the idea that they constitute “social groups,” where the coordinated action of individuals leads to various kinds of system-level functionalities. (298)

Gadiyaram, Vasundhara, et al. From Quantum Chemistry to Networks in Biology: A Graph Spectral Approach to Protein Structure Analyses. arXiv:1912.11609. Indian Institute of Science, Karnataka and University of Illinois, Urbana researchers provide a good example of the present integrative frontiers as 2020 science fulfills its stage of common unification from universe to humankinder.

This perspective presents a multidisciplinary characterization of protein structure networks. Our approach will be to synthesize concepts from quantum chemistry, polymer conformations, matrix mathematics, and percolation theory. We then construct protein networks in terms of non-covalently interacting amino acid side chains and to distill information from their graph spectra such as structural integrity. In conclusion, we suggest a further unifying approach to protein structure analyses for larger, more complex networks, such as metabolic and disease networks. (Abstract excerpt)

Garcia-Ojalvo, Jordi and Alfonso Martinex Arias. Towards a Statistical Mechanics of Cell Fate Decisions. Current Opinion in Genetics and Development. 22/6, 2012. In a special issue on the Genetics of System Biology (Briscoe), Pompeu Fabra University, Barcelona, and Cambridge University, UK biomedical researchers offer another example of affinities between biological and physical phenomena. By these insights, cellular dynamics can take on the guise of universal, critical phase transitions. A graphic image is used to depict parallels between the title domains. A notable surmise is that in both cases a stochastic variability on a micro level – say molecules or cells – will average out to a predictable macroscopic order. See also a cited paper Origin and Function of Fluctuations in Cell Behaviour and the Emergence of Patterns by Ana Mateus, et al in Seminars in Cell & Developmental Biology (20/877, 2009).

The spatiotemporal organization of a developing organism requires carefully orchestrated sequences of cellular differentiation events. These events are triggered by decisions made by individual cells about their fate, which are in turn controlled by gene and protein regulation processes. While these cell fate decisions are subject to stochasticity and are not reproducible at the single-cell level, they result in highly consistent, almost deterministic patterns at the level of the whole cell population. The question of how this macroscopic order arises from a disordered microscopic behaviour is still outstanding, and is reminiscent of problems in physical systems that are readily addressed by statistical mechanics. (Abstract)

Previous   1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10  Next  [More Pages]