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

2. A Consilience as Physics, Biology and People Become One: Active Matter

Center for the Physics of Biological Function.. biophysics.princeton.edu. This is a joint effort between The CUNY Graduate Center and Princeton University and one of eleven Physics Frontier Centers established by the Physics Division of the National Science Foundation Directorate for Mathematical and Physical Sciences. We are a collection of scientists working at the interface of physics and biology with the goal of creating a physicist’s understanding of living systems: a physics of biological function that connects the myriad details of life, across all scales, to fundamental and universal physical principles. Our center focuses on new scientific opportunities and educational programs, integrating theory and experiment, research and education. Its director and long time mentor is Professor William Bialek (search).

International Centre for Theoretical Physics: Quantitative Life Sciences. www.ictp.it/research/qls.aspx. A 2017 website for this research area at the global institute in Trieste founded by the Nobel laureate physicist Abdus Salam which has become a vital home for many third-world students. On the ICTP main site, other programs such as Statistical Physics, Earth System Physics, and Sustainable Energy can be viewed.

Quantitative Life Sciences: In the last decade, the progressive integration of a wide range of different disciplines - including physics, statistics, information theory, biochemistry, genetics and medicine, population genetics and game theory - and increased availability of quantitative data has led to major advances in most diverse domains of life sciences, from molecular and cell biology to terrestrial and oceanic ecology, economics and quantitative finance. The integration process between disciplines has led to the consolidation of a new research domain, which we describe as ‘quantitative life sciences’ to provide a sense of its breadth.

Third Infinity 2013. www.thirdinfinity.mpg.de. A Conference on Physics of Biological and Complex Systems held in October in Gottingen, arranged by the International Max Planck Research School, a joint endeavor of the University of Gottingen, MPI Biophysical Chemistry, and MPI Dynamics and Self-Organization. It is of special interest for its reference to science’s historic infinities of cosmos, atom, and life, which was first noted by Pierre Teilhard de Chardin in his The Phenomenon of Man. Keynote speakers were the British neuroscientist Karl Friston, and Eytan Domany, Computational Systems Biology, Weizmann Institute of Science. A public panel on The Practice of Science was chaired by Ahmed El Hady, MPI Biological Chemistry.

And as we record in mid 2014, the new phase of integral science and animate nature these worldwide meetings achieve seem as a parallel universe far removed from worsening barbaric conflicts and carnage, the guns of August a century later. However, one might ask, could such common revolutionary knowledge unto discovery, a future light age over an return to a new darker age, be able to turn the world from perpetual war to natural wisdom and sustainable peace. We try to note this work and progress going on, but however can it become revelation?

The Third Infinity: The field of Physics may be divided today in three sub-categories: infinitely big (relativity and astronomy), infinitely small (quantum mechanics and particle physics) and infinitely complex (complex systems and biophysics). The conference Third Infinity focuses on the latter and most recently addressed infinities (such as) the diverse fields of non-linear dynamical systems, brain as a complex system, experimental biophysics and robotics.

Building upon the increasingly strong links between physics, chemistry and the life sciences, the program aims at advancing the quantitative and molecular understanding of life processes while at the same time exploring new frontiers of physics. Research topics include biomolecular structure and dynamics, biological membranes, motor proteins and pattern formation in systems of interacting cells, neuronal information processing, and hydrodynamics and pattern formation of complex fluids. (MPI Research School)

Turbulence in clouds, neuronal fireworks in the brain, the physics of individual cells and the flow of water and oil through porous stone – these, and other particularly complex systems, are the focus of the research carried out by scientists at the Max Planck Institute for Dynamics and Self-Organization. Here, “complex” means that many individual systems combine to form a whole, the dynamics of which cannot necessarily be identified through the behaviour of the individual systems. Scientists say that these systems “organise themselves”. This holds true for the interaction of neurons in the brain (for example during learning) as well as for the numerous swirls that combine to form a turbulent cloud. There is reason to hope that a better understanding of the latter will enable a more accurate prediction of the future influence of clouds on global climate. (MPI for Dynamics and Self-Organization)

Agliari, Elena, et al. Collective Behaviours: From Biochemical Kinetics to Electronic Circuits. Nature Scientific Reports. 3/3458, 2013. University of Parma, and Sapienza University of Rome, physicists join the increasing witness of a wholly repetitive reality across every stratified realm. As the second quote notes, a good part of the work going forward is to translate terminologies from the various approaches and schools into an agreed, accessible description upon the same elephantine creation. For example, it is interesting to see a “cooperativity” being attributed even to chemical domains. And “cybernetics” is just another take on this naturally active materiality. See also posted herein on this same December 10th “Simple Mathematical Law Benchmarks Human Confrontations” whence it would be great to learn the programs that drive day and night, so we might behave better.

In this work we aim to highlight a close analogy between cooperative behaviors in chemical kinetics and cybernetics; this is realized by using a common language for their description, that is mean-field statistical mechanics. First, we perform a one-to-one mapping between paradigmatic behaviors in chemical kinetics (i.e., non-cooperative, cooperative, ultra-sensitive, anti-cooperative) and in mean-field statistical mechanics (i.e., paramagnetic, high and low temperature ferromagnetic, anti-ferromagnetic). Interestingly, the statistical mechanics approach allows a unified, broad theory for all scenarios. (Abstract)

In this work, we describe collective behaviors in chemical kinetics through mean-field statistical mechanics. Stimulated by the successes of the latter in formalizing classical cybernetic subjects, as neural networks in artificial intelligence or NP-completeness problems in logic, we successfully tested the statistical mechanics framework as a common language to read from a cybernetic perspective chemical kinetic reactions, whose complex features are at the very basis of several biological devices. (9)

Agrawal, Adyant and Sujin Babu. Self-organization in a Bimotility Mixture of Model Microswimmers. Physical Review E. 97/020401, 2018. Within the new APS Physics Subject Headings directory (Google), the Research Areas are collective behavior and self-organized systems, Physical Systems are Active Matter and Multi-Organism Systems, and Techniques is Theories of collective dynamics & active matter, an example of how physical science has lately come to life. Specifically Indian Institute of Technology, New Delhi physicists find such nonlinear, cooperative phenomena to innately manifest itself within mobile microbial populations.

Agrawal, Ankit, et al. Chromatin as Active Matter. Journal of Statistical Mechanics. 014001, 2017. Indian biophysicists pursue a better understanding of genetic phenomena by way of perceiving it as a phase of natural self-activity.

Alexandrov, Dmitri and Andrey Zubarev. Patterns in Soft and Biological Matters. Philosophical Transactions of the Royal Society A. April, 2020. Ural Federal University, Russia bioresearchers introduce a special edition with this title. Papers such as Stochastic Phenomena in Pattern Formation for Distributed Nonlinear Systems, On the Theory of Magnetic Hyperthermia, and Constructive Role of Noise and Diffusion in an Excitable Slow-Fast Population System describe many ways that material substance can come alive, and while showing how living systems arise from physical principles. In each case the manifest presence of an immaterial mathematical realm is evident.

This issue is devoted to theoretical, computer and experimental studies of internal heterogeneous patterns, their morphology and evolution in various soft physical, organic and inorganic materials. Their importance is due to the significant role of internal structures on the macroscopic properties and behaviour of natural and manufactured tissues and materials. Modern methods of computer modelling, statistical physics, heat and mass transfer, statistical hydrodynamics, nonlinear dynamics and experimental methods are presented. Special attention is paid to biological systems such as drug transport, hydrodynamic patterns in blood, protein, insulin crystals and more. (Abstract excerpt)

Armengol-Collado, Joseh-Maria, et al. Epithelia are multiscale active liquid crystals. Nature Physics. September, 2023. University of Leiden biophysicists including Luca Giomi post another current contribution that combines new understandings of complex living systems while proceeding on to ground their features in a conducive physical ground. See also Hexanematic crossover in epithelial monolayers depends on cell adhesion and cell density by Julia Eckert, et al in Nature Communications. (14/5762, 2023) and Biophysicists Uncover Powerful Symmetries in Living Tissue by Elise Cutts in Quanta (October 26, 2023) for an extensive news review.


Biological processes such as embryogenesis, wound healing and cancer rely on the ability of epithelial cells to coordinate their mechanical activity over length scales that are orders of magnitude larger than the cellular size. Although this process is regulated by signalling pathways, it has recently become evident that this coordination can be understood using physics tools, of which liquid crystal order is a prominent example. In this Letter, we combine in vitro experiments, numerical simulations and analysis to show that both nematic and hexatic order are present in epithelial layers. Our work provides a method to decipher epithelial structure and lead to a predictive mesoscopic theory of tissues. (Abstract)

If there’s one central idea in tissue biophysics, coauthor (Luca) Giomi said, it’s that structure gives rise to forces, and forces give rise to functions. In other words, controlling multiscale symmetry could be part of how tissues add up to more than the sum of their cells. There’s “a triangle of form, force and function.”. Cells use their shape to regulate forces, and these in turn serve mechanical functionality.” (Quanta)

Nematic: relating to or denoting a state of a liquid crystal in which the molecules are oriented in parallel but not arranged in well-defined planes. The hexatic phase is a state of matter that is between the solid and the isotropic liquid phases in two dimensional systems of particles.

Asano, Masanari, et al. Towards Modeling of Epigenetic Evolution with the Aid of Theory of Open Quantum Systems. AIP Conference Proceedings. 1508, December, 2013. A paper from a Quantum Theory: Reconsiderations of Foundations 6 meeting held in Vaxjo, Sweden, 2012. In a Quantum-Like Decision Making: From Biology to Behavioral Economics session, six information, mathematical, and biological specialists from Tokyo University of Science and Linnaeus University, Vaxjo, offer another example of the nascent confluence of foundational physics with life’s innate genetic, organismic development and vitality.

We apply theory of open quantum systems to modeling of epigenetic evolution. This is an attempt to unify Darwinian and Lamarckian viewpoints on evolution on the basis of a quantum-like model. The state of uncertainty of cell's epigenome is resolved to a stable and inherited epigenetic configuration. This process of evolution and stabilization is described by the quantum master equation (the Gorini-Kossakowski-Sudarshan-Lindblad equation). The initial state of epigenome starting interaction with a new environment is represented as a pure quantum state. It evolves to a steady state solution of the quantum master equation given by a diagonal density matrix. The latter represents the state resulting from a series of epimutations induced by the environment. (Abstract)

Recently Lamarckism was strongly supported by studies of epigenetic mutations and their inheritance. Instead of the (neo-)Darwinian natural selection model by which mutations in genome occur randomly and then the environment selects the “best organisms” (or cells populations), by the (neo)-Lamarckian model changes in the structure of the epigenome are directly “driven” by the environment and this environmental design is enherited already by the next generation. One of the main distinguishing features of (neo)Lamarckian evolution is that changes are generated and inherited very quickly. Instead of a long series of generations with random mutations in genes and the corresponding natural selection, experimenters observe direct “translation” of the environmental pressure to the structure of cells’ epigenomes: epimutations are “selected” very quickly. (75)

Attanasi, Alessandro, et al. Information Transfer and Behavioral Inertia in Starling Flocks. Nature Physics. Online August, 2014. A team of University of Rome, Sapienza, and Universidad Nacional de La Plata, Argentina, researchers including Andrea Cavagna and Irene Giardina, achieve a most sophisticated analysis of these startling formations. A prime factor is the relative rate of information transfer – the faster it is, the more coherent the group. Its significance was noted in a July 27 Science news item How Bird Flocks are Like Liquid Helium by Marcus Woo because the paper goes on to compare the phenomena with liquid helium dynamics.

The new model also predicts that information travels faster if the flock is well aligned—something else the team observed, Cavagna says. Other models don’t predict or explain that relationship. "This could be the evolutionary drive to have an ordered flock," he says, because the birds would be able to maneuver more rapidly and elude potential predators, among other things. Interestingly, Cavagna adds, the new model is mathematically identical to the equations that describe superfluid helium. When helium is cooled close to absolute zero, it becomes a liquid with no viscosity at all, as dictated by the laws of quantum physics. Every atom in the superfluid is in the same quantum state, exhibiting a cohesion that's mathematically similar to a starling flock. The similarities are an example of how deep principles in physics and math apply to many physical systems, Cavagna says.(Woo, Science)

Attanasi, Alessandro, et al. Superfluid Transport of Information in Turning Flocks of Starlings. arXiv:1303.7097. As the Abstract describes, an eleven member team from Italy and Argentina, including Andrea Cavagna and Irene Giardina, by way of sophisticated video instrumentation and mathematical analysis, are able to quantify such a consistent formation of dynamic group patterns. The great leap is then to realize it is akin to phenomena found in superfluid flows of super cold (4 degrees Kelvin) liquid helium. Once again, to observe, across widely disparate realms a genomic nature draws upon and repeats the same patterns and processes. As physics and biology interweave and become one (as Nigel Goldenfeld predicts), as this knowledge passes to our humanity, what wondrous discovery might await?

Collective decision-making in biological systems requires all individuals in the group to go through a behavioural change of state. During this transition, the efficiency of information transport is a key factor to prevent cohesion loss and preserve robustness. We propose a novel theory whose cornerstone is the existence of a conserved spin current generated by the gauge symmetry of the system. The theory turns out to be mathematically identical to that of superfluid transport in liquid helium and it explains the dissipationless propagating mode observed in turning flocks. Superfluidity also provides a quantitative expression for the speed of propagation of the information, according to which transport must be swifter the stronger the group's orientational order. We argue that the link between strong order and efficient decision-making required by superfluidity may be the adaptive drive for the high degree of behavioural polarization observed in many living groups. The mathematical equivalence between superfluid liquids and turning flocks is a compelling demonstration of the far-reaching consequences of symmetry and conservation laws across different natural systems. (Abstract)

Azaele, Sandro, et al. Statistical Mechanics of Ecological Systems. arXiv:1506.01721. Akin to Ehud Meron’s Nonlinear Physics of Ecosystems, (2015), six mathematicians with postings in the UK, USA, and Italy, including Jayanth Banavar and Amos Maritan, contribute to this growing scientific integration across living nature’s widest expanse. See Reviews of Modern Physics (88/035003, 2016) for its journal publication.

Just as statistical mechanics provides a framework to relate the microscopic properties of individual atoms and molecules to the macroscopic or bulk properties of materials, ecology needs a theory to relate key biological properties at the individual scale, with macro-ecological properties at the community scale. Nevertheless, this step is more than a mere generalization of the standard statistical mechanics approach. Indeed, in contrast to inanimate matter, for which particles have a given identity with known interactions that are always at play, in ecosystems we deal with entities that evolve, mutate and change, and that can turn on or off as well as tune their interactions with partners. Thus the problem at the core of the statistical physics of ecological systems is to identify the key elements one needs to incorporate in models in order to reproduce the known emergent patterns and eventually discover new ones. (1)

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