Is there a "molecular Nirvana Principle"? Towards a unified resolutional model of the biological symbol-matter dichotomy

In the present paper, the metapsychological "Nirvana Principle" is investigated evolutionarily at the earliest forms of life in a highly tentative way. A corresponding "molecular Nirvana Principle" is proposed, where the recent suggestions of the "internal measurement" biophysical quantum-molecular research programme of modern quantum biology are introduced, in relation to the former metapsychological theory, conceived to be valid in the entire realm of living systems (just as it was intended by the original author). By an appropriate introduction of a special primordeal dynamical time inversion symmetry breaking, originating in a premeval self-measurement in a composite nucleic acid-protein system, a special internal symmetry restoration time series is defined. In this way, a strictly physically defined self-identity ("molecular Nirvana," special physical symmetry restored) is derived, which is put equal to the quantum physical equivalent and root of the goals of evolutionarily higher level fundamental drives (the "Nirvana Principle"). It is shown that it is a natural requirement that the following internal regressive time (-reversal) physical molecular relations (and so the ultimate time symmetry) is mapped onto space, as is also suggested by some symbol-theoretical propositions.     

Some thoughts on quantum non-demolition measurements in biological systems

A brief review of measurement theory in quantum mechanical and biological systems is made, the concept of quantum nondemolition experiments is discussed and a possible resolution to a previous discussion on the existence of nonrepeatable experiments is presented.     

Perspectives on the landscape and flux theory for describing emergent behaviors of the biological systems

We give a review on the landscape theory of the equilibrium biological systems and landscape-flux theory of the nonequilibrium biological systems as the global driving force. The emergences of the behaviors, the associated thermodynamics in terms of the entropy and free energy and dynamics in terms of the rate and paths have been quantitatively demonstrated. The hierarchical organization structures have been discussed. The biological applications ranging from protein folding, biomolecular recognition, specificity, biomolecular evolution and design for equilibrium systems as well as cell cycle, differentiation and development, cancer, neural networks and brain function, and evolution for nonequilibrium systems, cross-scale studies of genome structural dynamics and experimental quantifications/verifications of the landscape and flux are illustrated. Together, this gives an overall global physical and quantitative picture in terms of the landscape and flux for the behaviors, dynamics and functions of biological systems.

     

Robustness as a non‐localizable relational phenomenon

A current challenge in neuroscience, systems and theoretical biology is to understand what properties allow organisms to exhibit and sustain behaviours despite perturbations (behavioural robustness). Indeed, there are still significant theoretical difficulties in this endeavour due to the context‐dependent nature of the problem. Contrary to the common view of biological robustness as a phenomenon that emerges internally, this article discusses the hypothesis that behavioural robustness is rooted in dynamical processes that distribute between internal controls, the organism body and the environment. This review highlights the varied perspectives and how they have led to the current focus on robustness as a relational phenomenon. A new perspective is proposed in which robustness is better understood in the context of agent‐environment dynamical couplings, in which such couplings are not always the full determinants of robustness. The challenges and limitations of the proposed approach are identified.     

Some introductory formalizations on the affine Hilbert spaces model of the origin of life. I. On quantum mechanical measurement and the origin of the genetic code: a general physical framework theory

A physical (affine Hilbert spaces) frame is developed for the discussion of the interdependence of the problem of the origin (symbolic assignment) of the genetic code and a possible endophysical (a kind of "internal") quantum measurement in an explicite way, following the general considerations of Balázs (Balázs, A., 2003. BioSystems 70, 43-54; Balázs, A., 2004a. BioSystems 73, 1-11). Using the Everett (a dynamic) interpretation of quantum mechanics, both the individual code assignment and the concatenated linear symbolism is discussed. It is concluded that there arises a skewed quantal probability field, with a natural dynamic non-linearity in codon assignment within the physical model adopted (essentially corresponding to a much discussed biochemical frame of self-catalyzed binding (charging) of t RNA like proto RNAs (ribozymes) with amino acids). This dynamic specific molecular complex assumption of individual code assignment, and the divergence of the code in relation to symbol concatenation, are discussed: our frame supports the former and interpret the latter as single-type codon (triplet), also unambiguous and extended assignment, selection in molecular evolution, corresponding to converging towards the fixedpoint of the internal dynamics of measurement, either in a protein- or RNA-world. In this respect, the general physical consequence is the introduction of a fourth rank semidiagonal energy tensor (see also Part II) ruling the internal dynamics as a non-linear in principle second-order one. It is inferred, as a summary, that if the problem under discussion could be expressed by the concepts of the Copenhagen interpretation of quantum mechanics in some yet not quite specified way, the matter would be particularly interesting with respect to both the origin of life and quantum mechanics, as a dynamically supported natural measurement-theoretical split between matter ("hardware") and (internal) symbolism ("software") aspects of living matter.     

Novel metaheuristic for parameter estimation in nonlinear dynamic biological systems

Background  

We consider the problem of parameter estimation (model calibration) in nonlinear dynamic models of biological systems. Due to the frequent ill-conditioning and multi-modality of many of these problems, traditional local methods usually fail (unless initialized with very good guesses of the parameter vector). In order to surmount these difficulties, global optimization (GO) methods have been suggested as robust alternatives. Currently, deterministic GO methods can not solve problems of realistic size within this class in reasonable computation times. In contrast, certain types of stochastic GO methods have shown promising results, although the computational cost remains large. Rodriguez-Fernandez and coworkers have presented hybrid stochastic-deterministic GO methods which could reduce computation time by one order of magnitude while guaranteeing robustness. Our goal here was to further reduce the computational effort without loosing robustness.     

Coherent phenomena in photosynthetic light harvesting: part two—observations in biological systems

Considerable debate surrounds the question of whether or not quantum mechanics plays a significant, non-trivial role in photosynthetic light harvesting. Many have proposed that quantum superpositions and/or quantum transport phenomena may be responsible for the efficiency and robustness of energy transport present in biological systems. The critical experimental observations comprise the observation of coherent oscillations or “quantum beats” via femtosecond laser spectroscopy, which have been observed in many different light harvesting systems. Part Two of this review aims to provide an overview of experimental observations of energy transfer in the most studied light harvesting systems. Length scales, derived from crystallographic studies, are combined with energy and time scales of the beats observed via spectroscopy. A consensus is emerging that most long-lived (hundreds of femtoseconds) coherent phenomena are of vibrational or vibronic origin, where the latter may result in coherent excitation transport within a protein complex. In contrast, energy transport between proteins is likely to be incoherent in nature. The question of whether evolution has selected for these non-trivial quantum phenomena may be an unanswerable question, as dense packings of chromophores will lead to strong coupling and hence non-trivial quantum phenomena. As such, one cannot discern whether evolution has optimised light harvesting systems for high chromophore density or for the ensuing quantum effects as these are inextricably linked and cannot be switched off.     

Challenges for the identification of biological systems from in vivo time series data

Modern methods of high-throughput molecular biology render it possible to generate time series of metabolite concentrations and the expression of genes and proteins in vivo. These time profiles contain valuable information about the structure and dynamics of the underlying biological system. This information is implicit and its extraction is a challenging but ultimately very rewarding task for the mathematical modeler. Using a well-suited modeling framework, such as Biochemical Systems Theory (BST), it is possible to formulate the extraction of information as an inverse problem that in principle may be solved with a genetic algorithm or nonlinear regression. However, two types of issues associated with this inverse problem make the extraction task difficult. One type pertains to the algorithmic difficulties encountered in nonlinear regressions with moderate and large systems. The other type is of an entirely different nature. It is a consequence of assumptions that are often taken for granted in the design and analysis of mathematical models of biological systems and that need to be revisited in the context of inverse analyses. The article describes the extraction process and some of its challenges and proposes partial solutions.     

生物鲁棒性的研究进展

生物鲁棒性是指在受到外部扰动或内部参数摄动等不确定因素干扰时,生物系统保持其结构和功能稳定的一种特性。目前已经发现生物鲁棒性普遍存在于生物系统整体、器官、细胞、分子等各种层次,如细菌趋化、细胞周期、细胞信号通讯、基因突变、生物发育、基因网络等等。产生生物鲁棒性的作用机制主要是生物系统的反馈、冗余、模块和结构稳定等。稳定鲁棒性和品质鲁棒性是生物鲁棒性研究的两个重要命题,数学模型是生物鲁棒性研究的重要手段。认识生物鲁棒性对癌症、MDS、糖尿病等疾病的发生、发展和治疗有重要意义。丈章从上述几个方面综述了生物鲁棒性的研究进展。     

The measurement process in biological systems: a new phenomenology.

A quantum theoretic approach to the problem of specific biological interactions at the molecular level, is presented. The concept of a “measuring system” in analogy with the enzyme macromolecule is used. The main hypothesis is that in the course of an enzymic reaction, the enzyme will specify the eigenvalues of the observables associated with the substrate, on some particular quantum states. Then, any “perturbation” induced in the substrate, will also be specified by the enzyme. In this context, the enzymic substrate is “perturbed” by an electromagnetic field and the physical transition S → S¹ thus induced is “measured” in the E_(S) + S¹ enzyme reaction, as compared with the control E_(S) + S reaction. The effect on the enzyme reaction is manifested by an enhancement of the reaction rate appearing periodically at well defined substrate irradiation times. The minimum substrate irradiation time inducing the first effect, termed t_m and the fixed time period that always appears to delimit two successive rate effects, termed the τ-parameter, are enzyme dependent. The same idea was used to devise an experimental model for the study of some more general interactions, within cellular systems. The growth of auxotrophic micro-organisms in minimal media supplemented with irradiated growth factors was followed. The pattern of growth stimulations obtained with this model, displays a similarity with the periodic enhancements of enzymic rates, obtained with irradiated substrates. This new type of evidence may suggest a characteristic of biological specificity, previously unrecognized.     

The kinetics of diffused substances in some biological systems

The purpose of this paper is to present a method for the determination of a solution for a coupled system of first order initial boundary-value problems arising from some biological systems. The physical problem is to determine the suspended and the superficial molecular concentrations of a traced substance passing through an organ containing a tangle of vessels, such as the kidney-ureter system. The approach to the problem is by successive approximation which leads to a recursion formula for the determination of the solution as well as error estimates for the approximations. The recursion formula involves only direct integration which indicates a promising possibility in obtaining numerical results by using a computer. In addition to the determination of a solution, some qualitative analysis of the solution is given. This includes the existence of a unique solution, the continuous dependency of the solution on the data, and the stability problem of a steady-state solution.     

Dynamic optimization of distributed biological systems using robust and efficient numerical techniques

ABSTRACT: BACKGROUND: Systems biology allows the analysis of biological systems behavior under different conditions through in silico experimentation. The possibility of perturbing biological systems in different manners calls for the design of perturbations to achieve particular goals. Examples would include, the design of a chemical stimulation to maximize the amplitude of a given cellular signal or to achieve a desired pattern in pattern formation systems, etc. Such design problems can be mathematically formulated as dynamic optimization problems which are particularly challenging when the system is described by partial differential equations. This work addresses the numerical solution of such dynamic optimization problems for spatially distributed biological systems. The usual nonlinear and large scale nature of the mathematical models related to this class of systems and the presence of constraints on the optimization problems, impose a number of difficulties, such as the presence of suboptimal solutions, which call for robust and efficient numerical techniques. RESULTS: Here, the use of a control vector parameterization approach combined with efficient and robust hybrid global optimization methods and a reduced order model methodology is proposed. The capabilities of this strategy are illustrated considering the solution of a two challenging problems: bacterial chemotaxis and the FitzHugh-Nagumo model. CONCLUSIONS: In the process of chemotaxis the objective was to efficiently compute the time-varying optimal concentration of chemotractant in one of the spatial boundaries in order to achieve predefined cell distribution profiles. Results are in agreement with those previously published in the literature. The FitzHugh-Nagumo problem is also efficiently solved and it illustrates very well how dynamic optimization may be used to force a system to evolve from an undesired to a desired pattern with a reduced number of actuators. The presented methodology can be used for the efficient dynamic optimization of generic distributed biological systems.     

The organization of time in biological systems

A notion of organization of time similar to the notion of organization of space in architecture has been introduced. The level and pattern of organization of time in biological systems differs from that in physical and chemical systems, which presents an independent problem. Analysis of the problem leads to a new definition of life as a process of renormalization of possibilities described by a Bayes formula. This definition leads to the notion of self-monitoring as a property of every biological system, and of complicated structure of the biological present, including the physical past and physical future. This is naturally followed by determination by far past, and, hence, memory, and determination by future, i.e. preadaptation, surpassing reflection, aim-setting etc. A direct dependence of a number of elements of a complex system on its stability has been demonstrated. The self-monitoring and organization of time can be traced at various levels of biological hierarchy from intracellular to biosphere level.     

Analysing hierarchy in the organization of biological and physical systems

A structured approach is discussed for analysing hierarchy in the organization of biological and physical systems. The need for a structured approach follows from the observation that many hierarchies in the literature apply conflicting hierarchy rules and include ill-defined systems. As an alternative, we suggest a framework that is based on the following analytical steps: determination of the succession stage of the universe, identification of a specific system as part of the universe, specification of external influences on a system's creation and analysis of a system's internal organization. At the end, the paper discusses practical implications of the proposed method for the analysis of system organization and hierarchy in biology, ecology and physics.     

Heterarchy in biological systems: a logic-based dynamical model of abstract biological network derived from time-state-scale re-entrant form

Heterarchical structure is important for understanding robustness and evolvability in a wide variety of levels of biological systems. Although many studies emphasize the heterarchical nature of biological systems, only a few computational representations of heterarchy have been created thus far. We propose here the time-state-scale re-entrant form to address the self-referential property derived from setting heterarchical structure. In this paper, we apply the time-state-scale re-entrant form to abstract self-referential modeling for a functional manifestation of biological network presented by [Tsuda, I., Tadaki, K., 1997. A logic-based dynamical theory for a genesis of biological threshold. BioSystems 42, 45-64]. The numerical results of this system show different intermittent phase transitions and power-law distribution of time spent in activating functional manifestation. The Hierarchically separated time-scales obtained from spectrum analysis imply that the reactions at different levels simultaneously appear in a dynamical system. The results verify the mutual inter-relationship between heterarchical structure in biological systems and the self-referential property of computational heterarchical systems.     

A realist approach to biological events

In this paper, I aim to show that the multiple realisability and the causal efficacy of biological events can best be explained by construing biological events as determinables of more determinate physical events. The determination relation itself is spelled out in terms of inclusive essence. In order to secure actual causation for biological events (in contrast to causal influence), two conditions are introduced such that for some events, biological events qualify as their cause. Finally, certain consequences of the presented theory are discussed, such as the question of how the biological token event can retain its identity across modal modifications of its realiser, and such as how the presented solution bears on the classical problem of biological causation.     

Problems with dimensionless measurement models of synchrony in biological systems

Synchrony is surprisingly complex even in the simplest cases. One strategy for simplifying complex phenomena is to define a dimensionless measurement model with the aim of (1) finding order, (2) comparing complex phenomena, and (3) making decisions about statistical significance. However, a model is only as good as its assumptions. In this paper, several types of dimensionless measurement models of synchrony among biological states are evaluated using the preceding criteria. These dimensionless measurement models are found to be inadequate even in the simplest cases of N individuals cycling through k non-overlapping states. Moreover, independent of their adequacy as measures of synchrony, there is the additional problem of the applicability of biological-state measurement models to rhythmic biological processes. Biological states are often just quantized observations of the phases of rhythmic biological processes. With the help of a concrete example, it is shown that quantizing the phases of a process into discrete states can lead to serious errors. These conclusions do not imply that the study of synchrony in biological systems is intractable. There are statistical approaches for detecting synchrony in groups and researchers are making progress towards understanding the general mechanisms of rhythmic phenomena in biological systems. Am. J. Primatol. 41:65–85, 1997. © 1997 Wiley-Liss, Inc.     

Abstract representations of biological systems in supercategories

An abstract representation of biological systems from the standpoint of the theory of supercategories is presented. The relevance of such representations forG-relational biologies is suggested. In section A the basic concepts of our representation, that is class, system, supercategory and measure are introduced. Section B is concerned with the mathematical representation starting with some axioms and principles which are natural extensions of the current abstract representations in biology. Likewise, some extensions of the principle of adequate design are introduced in section C. Two theorems which present the connection between categories and supercategories are proved. Two other theorems concerning the dynamical behavior of biological and biophysical systems are derived on the basis of the previous considerations. Section D is devoted to a general study of oscillatory behavior in enzymic systems, some general quantitative relations being derived from our representation. Finally, the relevance of these results for a quantum theoretic approach to biology is discussed.