Answering Schrödinger's "What Is Life?"

Sleep disorders and risk of alzheimer's disease: A two-way road

Substantial sleep impairment in patients with Alzheimer's disease (AD) is one of the emerging points for continued efforts to better understand the disease. Individuals without cognitive decline, an important marker of the clinical phase of AD, may show early alterations in the sleep-wake cycle. The objective of this critical narrative review is to explore the bidirectional pathophysiological correlation between sleep disturbances and Alzheimer's Disease. Specifically, it examines how the disruption of sleep homeostasis in individuals without dementia could contribute to the pathogenesis of AD, and conversely, how neurodegeneration in individuals with Alzheimer's Disease might lead to dysregulation of the sleep-wake cycle. Recent scientific results indicate that sleep disturbances, particularly those related to impaired glymphatic clearance, may act as an important mechanism associated with the genesis of Alzheimer's Disease. Additionally, amyloid deposition and tau protein hyperphosphorylation, along with astrocytic hyperactivation, appear to trigger changes in neurotransmission dynamics in areas related to sleep, which may explain the onset of sleep disturbances in individuals with AD. Disruption of sleep homeostasis appears to be a modifiable risk factor in Alzheimer's disease. Whenever possible, the use of non-pharmacological strategies becomes important in this context. From a different perspective, additional research is needed to understand and treat the dysfunction of the sleep-wake cycle in individuals already affected by AD. Early recognition and correction of sleep disturbances in this population could potentially mitigate the progression of dementia and improve the quality of life for those with AD.

Life, its definition, origin, evolution, and four-dimensional hierarchical structure

The main unique features of biological systems are reviewed, and four necessary and sufficient attributes of life are formulated, based on the ideas of Ervin Bauer. The possibility of the occurrence of each of these attributes during the origin of life is analyzed. As a result, different scenarios for the origin of life are presented, with their pros and cons. Next, the mainstream of biological evolution is discussed, considering it as a special case of general complexification, and structuredness is defined as a quantitative measure of structural complexity. By introducing the concepts of post-dissipative structure and ratcheting process based on "frozen" patterns, their role in the generation of biological structures underlying biological evolution is demonstrated. Furthermore, it is proposed that all living things can be divided into micro- (unicellular) and macro- (multicellular) creatures, which differ from each other even more radically than the difference between prokaryotes and unicellular eukaryotes. Then the fifth, sufficient, but not necessary attribute of life, hierarchicality, is formulated, which is fully applicable only to macrolife. It is also shown that living organisms are primarily chemodynamic rather than thermodynamic systems, and three basic laws of biochemodynamics are formulated. Finally, fifteen basic features of living beings, grouped into four basic blocks, are summarized.

Toward the Relational Formulation of Biological Thermodynamics

Classical thermodynamics employs the state of thermodynamic equilibrium, characterized by maximal disorder of the constituent particles, as the reference frame from which the Second Law is formulated and the definition of entropy is derived. Non-equilibrium thermodynamics analyzes the fluxes of matter and energy that are generated in the course of the general tendency to achieve equilibrium. The systems described by classical and non-equilibrium thermodynamics may be heuristically useful within certain limits, but epistemologically, they have fundamental problems in the application to autopoietic living systems. We discuss here the paradigm defined as a relational biological thermodynamics. The standard to which this refers relates to the biological function operating within the context of particular environment and not to the abstract state of thermodynamic equilibrium. This is defined as the stable non-equilibrium state, following Ervin Bauer. Similar to physics, where abandoning the absolute space-time resulted in the application of non-Euclidean geometry, relational biological thermodynamics leads to revealing the basic iterative structures that are formed as a consequence of the search for an optimal coordinate system by living organisms to maintain stable non-equilibrium. Through this search, the developing system achieves the condition of maximization of its power via synergistic effects.

Perspective elucidating the physiology of a microbial cell: Neidhardt's Holy Grail

A living microbial cell represents a system of high complexity, integration, and extreme order. All processes within that cell interconvert free energy through a multitude of interconnected metabolic reactions that help to maintain the cell in a state of low entropy, which is a characteristic of all living systems. The study of macromolecular interactions outside this cellular environment yields valuable information about the molecular function of macromolecules but represents a system in comparative disorder. Consequently, care must always be taken in interpreting the information gleaned from such studies and must be compared with how the same macromolecules function in vivo, otherwise, discrepancies can arise. The importance of combining reductionist approaches with the study of whole-cell microbial physiology is discussed regarding the long-term aim of understanding how a cell functions in its entirety. This can only be achieved by the continued development of high-resolution structural and multi-omic technologies. It is only by studying the whole cell that we can ever hope to understand how living systems function.

A third transition in science?

Since Newton, classical and quantum physics depend upon the 'Newtonian paradigm'. The relevant variables of the system are identified. For example, we identify the position and momentum of classical particles. Laws of motion in differential form connecting the variables are formulated. An example is Newton's three laws of motion. The boundary conditions creating the phase space of all possible values of the variables are defined. Then, given any initial condition, the differential equations of motion are integrated to yield an entailed trajectory in the prestated phase space. It is fundamental to the Newtonian paradigm that the set of possibilities that constitute the phase space is always definable and fixed ahead of time. This fails for the diachronic evolution of ever-new adaptations in any biosphere. Living cells achieve constraint closure and construct themselves. Thus, living cells, evolving via heritable variation and natural selection, adaptively construct new-in-the-universe possibilities. We can neither define nor deduce the evolving phase space: we can use no mathematics based on set theory to do so. We cannot write or solve differential equations for the diachronic evolution of ever-new adaptations in a biosphere. Evolving biospheres are outside the Newtonian paradigm. There can be no theory of everything that entails all that comes to exist. We face a third major transition in science beyond the Pythagorean dream that 'all is number' echoed by Newtonian physics. However, we begin to understand the emergent creativity of an evolving biosphere: emergence is not engineering.

Free energy and inference in living systems

Organisms are non-equilibrium, stationary systems self-organized via spontaneous symmetry breaking and undergoing metabolic cycles with broken detailed balance in the environment. The thermodynamic free-energy (FE) principle describes an organism's homeostasis as the regulation of biochemical work constrained by the physical FE cost. By contrast, recent research in neuroscience and theoretical biology explains a higher organism's homeostasis and allostasis as Bayesian inference facilitated by the informational FE. As an integrated approach to living systems, this study presents an FE minimization theory overarching the essential features of both the thermodynamic and neuroscientific FE principles. Our results reveal that the perception and action of animals result from active inference entailed by FE minimization in the brain, and the brain operates as a Schrödinger's machine conducting the neural mechanics of minimizing sensory uncertainty. A parsimonious model suggests that the Bayesian brain develops the optimal trajectories in neural manifolds and induces a dynamic bifurcation between neural attractors in the process of active inference.

Mitochondria in photosynthetic cells: Coordinating redox control and energy balance

In photosynthetic tissues in the light, the function of energy production is associated primarily with chloroplasts, while mitochondrial metabolism adjusts to balance ATP supply, regulate the reduction level of pyridine nucleotides, and optimize major metabolic fluxes. The tricarboxylic acid cycle in the light transforms into a noncyclic open structure (hemicycle) maintained primarily by the influx of malate and the export of citrate to the cytosol. The exchange of malate and citrate forms the basis of feeding redox energy from the chloroplast into the cytosolic pathways. This supports the level of NADPH in different compartments, contributes to the biosynthesis of amino acids, and drives secondary metabolism via a supply of substrates for 2-oxoglutarate-dependent dioxygenase and for cytochrome P450-catalyzed monooxygenase reactions. This results in the maintenance of redox and energy balance in photosynthetic plant cells and in the formation of numerous bioactive compounds specific to any particular plant species. The noncoupled mitochondrial respiration operates in coordination with the malate and citrate valves and supports intensive fluxes of respiration and photorespiration. The metabolic system of plants has features associated with the remarkable metabolic plasticity of mitochondria that permit the use of energy accumulated during photosynthesis in a way that all anabolic and catabolic pathways become optimized and coordinated.

Is There a Fourth Law for Non-Ergodic Systems That Do Work to Construct Their Expanding Phase Space?

Substantial grounds exist to doubt the universal validity of the Newtonian Paradigm that requires a pre-stated, fixed phase space. Therefore, the Second Law of Thermodynamics, stated only for fixed phase spaces, is also in doubt. The validity of the Newtonian Paradigm may stop at the onset of evolving life. Living cells and organisms are Kantian Wholes that achieve constraint closure, so do thermodynamic work to construct themselves. Evolution constructs an ever-expanding phase space. Thus, we can ask the free energy cost per added degree of freedom. That cost is roughly linear or sublinear in the mass constructed. However, the resulting expansion of the phase space is exponential or even hyperbolic. Thus, the evolving biosphere does thermodynamic work to construct itself into an ever-smaller sub-domain of its ever-expanding phase space at ever less free energy cost per added degree of freedom. The universe is not correspondingly disordered. Entropy, remarkably, really does decrease. A testable implication of this, termed here the Fourth Law of Thermodynamics, is that at constant energy input, the biosphere will construct itself into an ever more localized subregion of its ever-expanding phase space. This is confirmed. The energy input from the sun has been roughly constant for the 4 billion years since life started to evolve. The localization of our current biosphere in its protein phase space is at least 10^-2540. The localization of our biosphere with respect to all possible molecules of CHNOPS comprised of up to 350,000 atoms is also extremely high. The universe has not been correspondingly disordered. Entropy has decreased. The universality of the Second Law fails.

Overcoming the limits of natural computation in biological evolution toward the maximization of system efficiency

The goal-directedness of biological evolution is realized via the anticipatory achievement of the final state of the system that corresponds to the condition of its perfection in self-maintenance and in adaptability. In the course of individual development, a biological system maximizes its power via synergistic effects and becomes able to perform external work most efficiently. In this state, defined as stasis, robust self-maintaining configurations act as attractors resistant to external and internal perturbations. This corresponds to the local energy–time constraints that most efficiently fit the integral optimization of the whole system. In evolution, major evolutionary transitions that establish new states of stasis are achieved via codepoiesis, a process in which the undecided statements of existing coding systems form the basis for the evolutionary unfolding of the system by assigning new values to them. The genetic fixation of this macroevolutionary process leads to new programmes of individual development representing the process of natural computation. The phenomenon of complexification in evolution represents a metasystem transition that results in maximization of a system’s power and in the ability to increase external work performed by the system.

What is consciousness? Artificial intelligence, real intelligence, quantum mind and qualia

We approach the question ‘What is consciousness?’ in a new way, not as Descartes’ ‘systematic doubt’, but as how organisms find their way in their world. Finding one’s way involves finding possible uses of features of the world that might be beneficial or avoiding those that might be harmful. ‘Possible uses of X to accomplish Y’ are ‘affordances’. The number of uses of X is indefinite (or unknown), the different uses are unordered, are not listable, and are not deducible from one another. All biological adaptations are either affordances seized by heritable variation and selection or, far faster, by the organism acting in its world finding uses of X to accomplish Y. Based on this, we reach rather astonishing conclusions:

1. Artificial general intelligence based on universal Turing machines (UTMs) is not possible, since UTMs cannot ‘find’ novel affordances.

2. Brain-mind is not purely classical physics for no classical physics system can be an analogue computer whose dynamical behaviour can be isomorphic to ‘possible uses’.

3. Brain-mind must be partly quantum—supported by increasing evidence at 6.0 to 7.3 sigma.

4. Based on Heisenberg’s interpretation of the quantum state as ‘potentia’ converted to ‘actuals’ by measurement, where this interpretation is not a substance dualism, a natural hypothesis is that mind actualizes potentia. This is supported at 5.2 sigma. Then mind’s actualizations of entangled brain-mind-world states are experienced as qualia and allow ‘seeing’ or ‘perceiving’ of uses of X to accomplish Y. We can and do jury-rig. Computers cannot.

5. Beyond familiar quantum computers, we discuss the potentialities of trans-Turing systems.

Start-Ups as Adaptable Stable Systems Based on Synchronous Business Models

Business models have been a popular topic in research and practice for more than twenty years. During this time, frameworks for formulating business models have been developed, such as the business model canvas. Moreover, different business model frameworks have been proposed for different sectors. Yet, these frameworks have the fundamental shortcoming of not addressing directly and persistently the primary objective of start-ups: to survive in changing environments. The aim of the action research reported in this paper is to overcome that fundamental shortcoming. This is an important topic because the majority of start-ups do not survive. In this paper, first principles for survival in changing environments are related to business models. In particular, action research to reframe start-ups as adaptable stable systems based on synchronous business models is reported. The paper provides three principal contributions. The contribution to business model theory building is to relate survival first principles revealed through natural science research to business models. Reference to first principles highlight that survival depends on maintaining both external adaptability and internal stability through synchronization with changing environments. The second contribution is to business model practice through describing a simple business modeling method that is based on the scientific first principles. The third contribution is to provide an example that bridges the rigor–relevance gap between scientific research and business practice.

How an information perspective helps overcome the challenge of biology to physics

Living systems have long been a puzzle to physics, leading some to claim that new laws of physics are needed to explain them. Separating physical reality into the general (laws) and the particular (location of particles in space and time), it is possible to see that the combination of these amounts to efficient causation, whereby forces are constrained by patterns that constitute embodied information which acts as formal cause. Embodied information can only be produced by correlation with existing patterns, but sets of patterns can be arranged to form reflexive relations in which constraints on force are themselves formed by the pattern that results from action of those same constrained forces. This inevitably produces a higher level of pattern which reflexively reinforces itself. From this, multi-level hierarchies and downward causation by information are seen to be patterns of patterns that constrain forces. Such patterns, when causally cyclical, are closed to efficient causation. But to be autonomous, a system must also have its formative information accumulated by repeated cycles of selection until sufficient is obtained to represent the information content of the whole (which is the essential purpose of information oligomers such as DNA). Living systems are the result of that process and therefore cannot exist unless they are both closed to efficient causation and capable of embodying an independent supply of information sufficient to constitute their causal structure. Understanding this is not beyond the scope of standard physics, but it does recognise the far greater importance of information accumulation in living than in non-living systems and, as a corollary, emphasises the dependence of biological systems on the whole history of life, leading up to the present state of any and all organisms.

Biological action at a distance: Correlated pattern formation in adjacent tessellation domains without communication

Tessellations emerge in many natural systems, and the constituent domains often contain regular patterns, raising the intriguing possibility that pattern formation within adjacent domains might be correlated by the geometry, without the direct exchange of information between parts comprising either domain. We confirm this paradoxical effect, by simulating pattern formation via reaction-diffusion in domains whose boundary shapes tessellate, and showing that correlations between adjacent patterns are strong compared to controls that self-organize in domains with equivalent sizes but unrelated shapes. The effect holds in systems with linear and non-linear diffusive terms, and for boundary shapes derived from regular and irregular tessellations. Based on the prediction that correlations between adjacent patterns should be bimodally distributed, we develop methods for testing whether a given set of domain boundaries constrained pattern formation within those domains. We then confirm such a prediction by analysing the development of ‘subbarrel’ patterns, which are thought to emerge via reaction-diffusion, and whose enclosing borders form a Voronoi tessellation on the surface of the rodent somatosensory cortex. In more general terms, this result demonstrates how causal links can be established between the dynamical processes through which biological patterns emerge and the constraints that shape them.

Patterns can form in biological systems as a net effect of dynamical interactions that are excitatory over short distances and inhibitory over larger distances. Patterns that form in this way are known to reflect the shape of the boundary conditions that contain them. But observing that a particular pattern is contained by a boundary is not enough to determine whether or not that boundary was a constraint on pattern formation. Here we develop a novel test for the influence of boundary shape on pattern formation, based on comparing patterns contained by boundaries whose shapes tessellate and thus are geometrically related. Applying this test to patterns of cell density measured in the developing neocortex confirms that cortical column boundaries constrain pattern formation during the first postnatal weeks. In more general terms, our analysis reveals that strong relationships between patterns that form in adjacent biological domains are to be expected based purely on geometrical effects, even if no information is exchanged between those domains during the process of pattern formation. Our analysis provides a means for testing current theories about the fundamental role that constraints play in organising biological systems.

Scaffolding layered control architectures through constraint closure: insights into brain evolution and development

The functional organization of the mammalian brain can be considered to form a layered control architecture, but how this complex system has emerged through evolution and is constructed during development remains a puzzle. Here we consider brain organization through the framework of constraint closure, viewed as a general characteristic of living systems, that they are composed of multiple sub-systems that constrain each other at different timescales. We do so by developing a new formalism for constraint closure, inspired by a previous model showing how within-lifetime dynamics can constrain between-lifetime dynamics, and we demonstrate how this interaction can be generalized to multi-layered systems. Through this model, we consider brain organization in the context of two major examples of constraint closure-physiological regulation and visual orienting. Our analysis draws attention to the capacity of layered brain architectures to scaffold themselves across multiple timescales, including the ability of cortical processes to constrain the evolution of sub-cortical processes, and of the latter to constrain the space in which cortical systems self-organize and refine themselves. This article is part of the theme issue 'Systems neuroscience through the lens of evolutionary theory'.

The Use of the Statistical Entropy in Some New Approaches for the Description of Biosystems

Some problems of describing biological systems with the use of entropy as a measure of the complexity of these systems are considered. Entropy is studied both for the organism as a whole and for its parts down to the molecular level. Correlation of actions of various parts of the whole organism, intercellular interactions and control, as well as cooperativity on the microlevel lead to a more complex structure and lower statistical entropy. For a multicellular organism, entropy is much lower than entropy for the same mass of a colony of unicellular organisms. Cooperativity always reduces the entropy of the system; a simple example of ligand binding to a macromolecule carrying two reaction centers shows how entropy is consistent with the ambiguity of the result in the Bernoulli test scheme. Particular attention is paid to the qualitative and quantitative relationship between the entropy of the system and the cooperativity of ligand binding to macromolecules. A kinetic model of metabolism. corresponding to Schrödinger's concept of the maintenance biosystems by "negentropy feeding", is proposed. This model allows calculating the nonequilibrium local entropy and comparing it with the local equilibrium entropy inherent in non-living matter.

The World Is Not a Theorem

The evolution of the biosphere unfolds as a luxuriant generative process of new living forms and functions. Organisms adapt to their environment, exploit novel opportunities that are created in this continuous blooming dynamics. Affordances play a fundamental role in the evolution of the biosphere, for organisms can exploit them for new morphological and behavioral adaptations achieved by heritable variations and selection. This way, the opportunities offered by affordances are then actualized as ever novel adaptations. In this paper, we maintain that affordances elude a formalization that relies on set theory: we argue that it is not possible to apply set theory to affordances; therefore, we cannot devise a set-based mathematical theory to deduce the diachronic evolution of the biosphere.

The biological Maxwell's demons: exploring ideas about the information processing in biological systems

This work is based on ideas supported by some of the biologists who discovered foundational facts of twentieth-century biology and who argued that Maxwell's demons are physically implemented by biological devices. In particular, JBS Haldane first, and later J. Monod, A, Lwoff and F. Jacob argued that enzymes and molecular receptors implemented Maxwell's demons that operate in systems far removed from thermodynamic equilibrium and that were responsible for creating the biological order. Later, these ideas were extended to other biological processes. In this article, we argue that these biological Maxwell's demons (BMD) are systems that have information processing capabilities that allow them to select their inputs and direct their outputs toward targets. In this context, we propose the idea that these BMD are information catalysts in which the processed information has broad thermodynamic consequences.

Constraint Closure Drove Major Transitions in the Origins of Life

Life is an epiphenomenon for which origins are of tremendous interest to explain. We provide a framework for doing so based on the thermodynamic concept of work cycles. These cycles can create their own closure events, and thereby provide a mechanism for engendering novelty. We note that three significant such events led to life as we know it on Earth: (1) the advent of collective autocatalytic sets (CASs) of small molecules; (2) the advent of CASs of reproducing informational polymers; and (3) the advent of CASs of polymerase replicases. Each step could occur only when the boundary conditions of the system fostered constraints that fundamentally changed the phase space. With the realization that these successive events are required for innovative forms of life, we may now be able to focus more clearly on the question of life's abundance in the universe.

Emergence of Organisms

Since early cybernetics studies by Wiener, Pask, and Ashby, the properties of living systems are subject to deep investigations. The goals of this endeavour are both understanding and building: abstract models and general principles are sought for describing organisms, their dynamics and their ability to produce adaptive behavior. This research has achieved prominent results in fields such as artificial intelligence and artificial life. For example, today we have robots capable of exploring hostile environments with high level of self-sufficiency, planning capabilities and able to learn. Nevertheless, the discrepancy between the emergence and evolution of life and artificial systems is still huge. In this paper, we identify the fundamental elements that characterize the evolution of the biosphere and open-ended evolution, and we illustrate their implications for the evolution of artificial systems. Subsequently, we discuss the most relevant issues and questions that this viewpoint poses both for biological and artificial systems.

The evolution of universal adaptations of life is driven by universal properties of matter: energy, entropy, and interaction

The evolution of multicellular eukaryotes expresses two sorts of adaptations: local adaptations like fur or feathers, which characterize species in particular environments, and universal adaptations like microbiomes or sexual reproduction, which characterize most multicellulars in any environment. We reason that the mechanisms driving the universal adaptations of multicellulars should themselves be universal, and propose a mechanism based on properties of matter and systems: energy, entropy, and interaction. Energy from the sun, earth and beyond creates new arrangements and interactions. Metabolic networks channel some of this energy to form cooperating, interactive arrangements. Entropy, used here as a term for all forces that dismantle ordered structures (rather than as a physical quantity), acts as a selective force. Entropy selects for arrangements that resist it long enough to replicate, and dismantles those that do not. Interactions, energy-charged and dynamic, restrain entropy and enable survival and propagation of integrated living systems. This fosters survival-of-the-fitted - those entities that resist entropic destruction - and not only of the fittest - the entities with the greatest reproductive success. The "unit" of evolution is not a discrete entity, such as a gene, individual, or species; what evolves are collections of related interactions at multiple scales. Survival-of-the-fitted explains universal adaptations, including resident microbiomes, sexual reproduction, continuous diversification, programmed turnover, seemingly wasteful phenotypes, altruism, co-evolving environmental niches, and advancing complexity. Indeed survival-of-the-fittest may be a particular case of the survival-of-the-fitted mechanism, promoting local adaptations that express reproductive advantages in addition to resisting entropy. Survival-of-the-fitted accounts for phenomena that have been attributed to neutral evolution: in the face of entropy, there is no neutrality; all variations are challenged by ubiquitous energy and entropy, retaining those that are "fit enough". We propose experiments to test predictions of the survival-of-the-fitted theory, and discuss implications for the wellbeing of humans and the biosphere.