Nontrivial quantum and quantum-like effects in biosystems: Unsolved questions and paradoxes

Unsolved morphogenesis problems and the hidden order

In this work, the morphogenesis mechanisms are considered from the complexity perspective. It is shown that both morphogenesis and the functioning of organs should be unstable in the case of short-range interaction potentials. The repeatability of forms during evolution is a strong argument for its directionality. The formation of organs during evolution can occur only in the presence of a priori information about the structure of such an organ. The focus of the discussion is not merely on constraining potential possibilities but on the concept of directed evolution itself. A morphogenesis model was constructed based on nontrivial quantum effects. These interaction effects between biologically important molecules ensure the accurate synthesis of cells, tissues, and organs.

Constrained disorder principle-based variability is fundamental for biological processes: Beyond biological relativity and physiological regulatory networks

The constrained disorder principle (CDP) defines systems based on their degree of disorder bounded by dynamic boundaries. The principle explains stochasticity in living and non-living systems. Denis Noble described the importance of stochasticity in biology, emphasizing stochastic processes at molecular, cellular, and higher levels in organisms as having a role beyond simple noise. The CDP and Noble's theories (NT) claim that biological systems use stochasticity. This paper presents the CDP and NT, discussing common notions and differences between the two theories. The paper presents the CDP-based concept of taking the disorder beyond its role in nature to correct malfunctions of systems and improve the efficiency of biological systems. The use of CDP-based algorithms embedded in second-generation artificial intelligence platforms is described. In summary, noise is inherent to complex systems and has a functional role. The CDP provides the option of using noise to improve functionality.

Quantum-like Data Modeling in Applied Sciences: Review

This work presents a brief review on the modern approaches to data modeling by the methods developed in the quantum physics during the last one hundred years. Quantum computers and computations have already been widely investigated theoretically and attempted in some practical implementations, but methods of quantum data modeling are not yet sufficiently established. A vast range of concepts and methods of quantum mechanics have been tried in many fields of information and behavior sciences, including communications and artificial intelligence, cognition and decision making, sociology and psychology, biology and economics, financial and political studies. The application of quantum methods in areas other than physics is called the quantum-like paradigm, meaning that such approaches may not be related to the physical processes but rather correspond to data modeling by the methods designed for operating in conditions of uncertainty. This review aims to attract attention to the possibilities of these methods of data modeling that can enrich theoretical consideration and be useful for practical purposes in various sciences and applications.

Semantic parsing of the life process by quantum biology

A fact that an ever-increasingly number of research attention has focused on quantum biology demonstrates that it is, by no means, new to works in physic and mathematics, but to molecular biologists, geneticists, and biochemists. This is owing to that quantum biology serves as a distinctive discipline, by using quantum theory to study life sciences in combination with physics, mechanics, mathematics, statistics, and modern biology. Notably, quantum mechanics and its fundamental principles have been employed to clarify complex biological processes and molecular homeostasis within the organic life. Consequently, using the principles of quantum mechanics to study dynamic changes and energy transfer of molecules at the quantum level in biology has been accepted as an unusually distinguishable way to a better explanation of many phenomena in life. It is plausible that a clear conceptual quantum theoretical event is also considered to generally occur for short-term picoseconds or femtoseconds on microscopic nano- and subnanometer scales in biology and biosciences. For instance, photosynthesis, enzyme -catalyzed reactions, magnetic perception, the capture of smell and vision, DNA fragmentation, cellular breathing, mitochondrial processing, as well as brain thinking and consciousness, are all manifested within quantum superposition, quantum coherence, quantum entanglement, quantum tunneling, and other effects. In this mini-review, we describe the recent progress in quantum biology, with a promising direction for further insights into this field.

UVC radiation intensity dependence of pathogen decontamination rate: semiclassical theory and experiment

A semiclassical (light classical and molecule quantum) model describing the dependence of DNA/RNA dimerization rate as function of the ultraviolet C (UVC) radiation's intensity is proposed. Particularly, a nonlinear model is developed based on the Raman-like processes in quantum optics. The main result of the theory shows that the process of dimerization in the DNA/RNA depends strongly on the UVC light's intensity, thus proving a possible quantum microscopical mechanism of the interaction of UV light with the DNA. To corroborate the theoretical findings, we realize some experiments, by which want to investigate how the inactivation rate of the yeast colonies depends on the intensity of the UVC irradiation. The experimental results evidence a nonlinear decreasing of the residual yeast colonies as a function of the intensity in the irradiation process. The possibilities to optimize the intensity of UVC radiation in the considered decontamination equipment by using metamaterials are studied. The application of such equipment in disinfection of fluids (air, water, droplets, etc.), as well for the SARS-CoV-2-infected aerosols, is discussed.

Neurons as hierarchies of quantum reference frames

Conceptual and mathematical models of neurons have lagged behind empirical understanding for decades. Here we extend previous work in modeling biological systems with fully scale-independent quantum information-theoretic tools to develop a uniform, scalable representation of synapses, dendritic and axonal processes, neurons, and local networks of neurons. In this representation, hierarchies of quantum reference frames act as hierarchical active-inference systems. The resulting model enables specific predictions of correlations between synaptic activity, dendritic remodeling, and trophic reward. We summarize how the model may be generalized to nonneural cells and tissues in developmental and regenerative contexts.

A free energy principle for generic quantum systems

The Free Energy Principle (FEP) states that under suitable conditions of weak coupling, random dynamical systems with sufficient degrees of freedom will behave so as to minimize an upper bound, formalized as a variational free energy, on surprisal (a.k.a., self-information). This upper bound can be read as a Bayesian prediction error. Equivalently, its negative is a lower bound on Bayesian model evidence (a.k.a., marginal likelihood). In short, certain random dynamical systems evince a kind of self-evidencing. Here, we reformulate the FEP in the formal setting of spacetime-background free, scale-free quantum information theory. We show how generic quantum systems can be regarded as observers, which with the standard freedom of choice assumption become agents capable of assigning semantics to observational outcomes. We show how such agents minimize Bayesian prediction error in environments characterized by uncertainty, insufficient learning, and quantum contextuality. We show that in its quantum-theoretic formulation, the FEP is asymptotically equivalent to the Principle of Unitarity. Based on these results, we suggest that biological systems employ quantum coherence as a computational resource and - implicitly - as a communication resource. We summarize a number of problems for future research, particularly involving the resources required for classical communication and for detecting and responding to quantum context switches.

Cell Responsiveness to Physical Energies: Paving the Way to Decipher a Morphogenetic Code

We discuss emerging views on the complexity of signals controlling the onset of biological shapes and functions, from the nanoarchitectonics arising from supramolecular interactions, to the cellular/multicellular tissue level, and up to the unfolding of complex anatomy. We highlight the fundamental role of physical forces in cellular decisions, stressing the intriguing similarities in early morphogenesis, tissue regeneration, and oncogenic drift. Compelling evidence is presented, showing that biological patterns are strongly embedded in the vibrational nature of the physical energies that permeate the entire universe. We describe biological dynamics as informational processes at which physics and chemistry converge, with nanomechanical motions, and electromagnetic waves, including light, forming an ensemble of vibrations, acting as a sort of control software for molecular patterning. Biomolecular recognition is approached within the establishment of coherent synchronizations among signaling players, whose physical nature can be equated to oscillators tending to the coherent synchronization of their vibrational modes. Cytoskeletal elements are now emerging as senders and receivers of physical signals, "shaping" biological identity from the cellular to the tissue/organ levels. We finally discuss the perspective of exploiting the diffusive features of physical energies to afford in situ stem/somatic cell reprogramming, and tissue regeneration, without stem cell transplantation.

Metabolic limits on classical information processing by biological cells

Biological information processing is generally assumed to be classical. Measured cellular energy budgets of both prokaryotes and eukaryotes, however, fall orders of magnitude short of the power required to maintain classical states of protein conformation and localization at the Å, fs scales predicted by single-molecule decoherence calculations and assumed by classical molecular dynamics models. We suggest that decoherence is limited to the immediate surroundings of the cell membrane and of intercompartmental boundaries within the cell, and that bulk cellular biochemistry implements quantum information processing. Detection of Bell-inequality violations in responses to perturbation of recently-separated sister cells would provide a sensitive test of this prediction. If it is correct, modeling both intra- and intercellular communication requires quantum theory.

Consciousness as an Emergent Phenomenon: A Tale of Different Levels of Description

One of the biggest queries in cognitive sciences is the emergence of consciousness from matter. Modern neurobiological theories of consciousness propose that conscious experience is the result of interactions between large-scale neuronal networks in the brain, traditionally described within the realm of classical physics. Here, we propose a generalized connectionist framework in which the emergence of "conscious networks" is not exclusive of large brain areas, but can be identified in subcellular networks exhibiting nontrivial quantum phenomena. The essential feature of such networks is the existence of strong correlations in the system (classical or quantum coherence) and the presence of an optimal point at which the system's complexity and energy dissipation are maximized, whereas free-energy is minimized. This is expressed either by maximization of the information content in large scale functional networks or by achieving optimal efficiency through the quantum Goldilock effect.

Biological Entanglement-Like Effect After Communication of Fish Prior to X-Ray Exposure

The phenomenon by which irradiated organisms including cells in vitro communicate with unirradiated neighbors is well established in biology as the radiation-induced bystander effect (RIBE). Generally, the purpose of this communication is thought to be protective and adaptive, reflecting a highly conserved evolutionary mechanism enabling rapid adjustment to stressors in the environment. Stressors known to induce the effect were recently shown to include chemicals and even pathological agents. The mechanism is unknown but our group has evidence that physical signals such as biophotons acting on cellular photoreceptors may be implicated. This raises the question of whether quantum biological processes may occur as have been demonstrated in plant photosynthesis. To test this hypothesis, we decided to see whether any form of entanglement was operational in the system. Fish from 2 completely separate locations were allowed to meet for 2 hours either before or after which fish from 1 location only (group A fish) were irradiated. The results confirm RIBE signal production in both skin and gill of fish, meeting both before and after irradiation of group A fish. The proteomic analysis revealed that direct irradiation resulted in pro-tumorigenic proteomic responses in rainbow trout. However, communication from these irradiated fish, both before and after they had been exposed to a 0.5 Gy X-ray dose, resulted in largely beneficial proteomic responses in completely nonirradiated trout. The results suggest that some form of anticipation of a stressor may occur leading to a preconditioning effect or temporally displaced awareness after the fish become entangled.

Automaton model of protein: Dynamics of conformational and functional states

In this conceptual paper we propose to explore the analogy between ontic/epistemic description of quantum phenomena and interrelation between dynamics of conformational and functional states of proteins. Another new idea is to apply theory of automata to model the latter dynamics. In our model protein's behavior is modeled with the aid of two dynamical systems, ontic and epistemic, which describe evolution of conformational and functional states of proteins, respectively. The epistemic automaton is constructed from the ontic automaton on the basis of functional (observational) equivalence relation on the space of ontic states. This reminds a few approaches to emergent quantum mechanics in which a quantum (epistemic) state is treated as representing a class of prequantum (ontic) states. This approach does not match to the standard protein structure-function paradigm. However, it is perfect for modeling of behavior of intrinsically disordered proteins. Mathematically space of protein's ontic states (conformational states) is modeled with the aid of p-adic numbers or more general ultrametric spaces encoding the internal hierarchical structure of proteins. Connection with theory of p-adic dynamical systems is briefly discussed.

Biological effects of the hypomagnetic field: An analytical review of experiments and theories

During interplanetary flights in the near future, a human organism will be exposed to prolonged periods of a hypomagnetic field that is 10,000 times weaker than that of Earth's. Attenuation of the geomagnetic field occurs in buildings with steel walls and in buildings with steel reinforcement. It cannot be ruled out also that a zero magnetic field might be interesting in biomedical studies and therapy. Further research in the area of hypomagnetic field effects, as shown in this article, is capable of shedding light on a fundamental problem in biophysics-the problem of primary magnetoreception. This review contains, currently, the most extensive bibliography on the biological effects of hypomagnetic field. This includes both a review of known experimental results and the putative mechanisms of magnetoreception and their explanatory power with respect to the hypomagnetic field effects. We show that the measured correlations of the HMF effect with HMF magnitude and inhomogeneity and type and duration of exposure are statistically absent. This suggests that there is no general biophysical MF target similar for different organisms. This also suggests that magnetoreception is not necessarily associated with evolutionary developed specific magnetoreceptors in migrating animals and magnetotactic bacteria. Independently, there is nonspecific magnetoreception that is common for all organisms, manifests itself in very different biological observables as mostly random reactions, and is a result of MF interaction with magnetic moments at a physical level-moments that are present everywhere in macromolecules and proteins and can sometimes transfer the magnetic signal at the level of downstream biochemical events. The corresponding universal mechanism of magnetoreception that has been given further theoretical analysis allows one to determine the parameters of magnetic moments involved in magnetoreception-their gyromagnetic ratio and thermal relaxation time-and so to better understand the nature of MF targets in organisms.

Outline of a unified Darwinian evolutionary theory for physical and biological systems

The scheme of a unified Darwinian evolutionary theory for physical and biological systems is described. Every physical system is methodologically endowed with a classical information processor, which turns every system into an agent being also susceptible to evolution. Biological systems retain this structure as natural extensions of physical systems from which they are built up. Optimization of information flows turns out to be the key element to study the possible emergence of quantum behavior and the unified Darwinian description of physical and biological systems. The Darwinian natural selection scheme is completed by the Lamarckian component in the form of the anticipation of states of surrounding bio-physical systems.

The quantum basis of spatiotemporality in perception and consciousness

Living systems inhabit the area of the world which is shaped by the predictable space-time of physical objects and forces that can be incorporated into their perception pattern. The process of selecting a "habitable" space-time is the internal quantum measurement in which living systems become embedded into the environment that supports their living state. This means that living organisms choose a coordinate system in which the influence of measurement is minimal. We discuss specific roles of biological macromolecules, in particular of the cytoskeleton, in shaping perception patterns formed in the internal measurement process. Operation of neuron is based on the transmission of signals via cytoskeleton where the digital output is generated that can be decoded through a reflective action of the perceiving agent. It is concluded that the principle of optimality in biology as formulated by Liberman et al. (BioSystems 22, 135-154, 1989) is related to the establishment of spatiotemporal patterns that are maximally predictable and can hold the living state for a prolonged time. This is achieved by the selection of a habitable space approximated to the conditions described by classical physics.

Distant Healing Intention Therapies: An Overview of the Scientific Evidence

This article provides a broad overview of “distant healing intention” (DHI) therapies, ie, intentional healing modalities claimed to transcend the usual constraints of distance through space or time. We provide a summary of previous reviews and meta-analyses that have explored a diverse array of DHI modalities, outcome measures, and experimental protocols. While some significant experimental effects have been observed, the evidence to date does not yet provide confidence in its clinical efficacy. The purported “nonlocal” nature of DHI raises significant methodological and theoretical challenges. We recommend several avenues for improving future research.