Metabolism is a set of chemical reactions, used by living organisms to process chemical compounds in order to take energy and eliminate toxic compounds, for example. Its processes are referred as metabolic pathways. Understanding metabolism is imperative to biology, toxicology and medicine, but the number and complexity of metabolic pathways makes this a difficult task. In our paper, we investigate the use of causal Bayesian networks to model the pathways of yeast saccharomyces cerevisiae metabolism: such a network (...) can be used to draw predictions about the levels of metabolites and enzymes in a particular specimen. We propose a two-stage methodology for causal networks, as follows. First construct a causal network from the network of metabolic pathways. The viability of this causal network depends on the validity of the causal Markov condition. If this condition fails, however, the principle of the common cause motivates the addition of a new causal arrow or a new `hidden' common cause to the network (stage 2 of the model formation process). Algorithms for adding arrows or hidden nodes have been developed separately in a number of papers, and in this paper we combine them, showing how the resulting procedure can be applied to the metabolic pathway problem. Our general approach was tested on neural cell morphology data and demonstrated noticeable improvements in both prediction and network accuracy. (shrink)

Computational approaches in systems biology have become a powerful tool for understanding the fundamental mechanisms of cellular metabolism and regulation. However, the interplay between the regulatory and the metabolic system is still poorly understood. In particular, there is a need for formal mathematical frameworks that allow analyzing metabolism together with dynamic enzyme resources and regulatory events. Here, we introduce a metabolic-regulatory network model that allows integrating metabolism with transcriptional regulation, macromolecule production and enzyme resources. Using this model, we (...) show that the dynamic interplay between these different cellular processes can be formalized by a hybrid automaton, combining continuous dynamics and discrete control. (shrink)

Osmoregulation in insects is an essential process whereby changes in hemolymph osmotic pressure induce the release of diuretic or antidiuretic hormones to recruit individual osmoregulatory responses in a manner that optimizes overall homeostasis. However, the mechanisms by which different osmoregulatory circuits interact with other homeostatic networks to implement the correct homeostatic program remain largely unexplored. Surprisingly, recent advances in insect genetics have revealed several important metabolic functions are regulated by classic osmoregulatory pathways, suggesting that internal cues related to (...) osmotic and metabolic perturbations are integrated by the same hormonal networks. Here, we review our current knowledge on the network mechanisms that underpin systemic osmoregulation and discuss the remarkable parallels between the hormonal networks that regulate body fluid balance and those involved in energy homeostasis to provide a framework for understanding the polymodal optimization of homeostasis in insects. (shrink)

The co-occurrence of stress-induced posttraumatic stress disorder and obesity is common, particularly among military personnel but the link between these conditions is unclear. Individuals with comorbid PTSD and obesity manifest other physical and psychological problems, which significantly diminish their quality of life. Current understanding of the pathways connecting stress to PTSD and obesity is focused largely on behavioral mediators alone with little consideration of the biological regulatory mechanisms that underlie their co-occurrence. In this work, we leverage prior knowledge to systematically (...) highlight such bio-behavioral mechanisms and inform on the design of confirmatory pilot studies. We use natural language processing to extract documented regulatory interactions involved in the metabolic response to stress and its impact on obesity and PTSD from over 8 million peer-reviewed papers. The resulting network describes the propagation of stress to PTSD and obesity through 34 metabolic mediators using 302 documented regulatory interactions supported by over 10,000 citations. Stress jointly affected both conditions through 21 distinct pathways involving only two intermediate metabolic mediators out of a total of 76 available paths through this network. Moreover, oxytocin, Neuropeptide-Y, and cortisol supported an almost direct propagation of stress to PTSD and obesity with different net effects. Although stress upregulated both NPY and cortisol, the downstream effects of both markers are reported to relieve PTSD severity but exacerbate obesity. The stress-mediated release of oxytocin, however, was found to concurrently downregulate the severity of both conditions. These findings highlight how a network-informed approach that leverages prior knowledge might be used effectively in identifying key mediators like OXT though experimental verification of signal transmission dynamics through each path will be needed to determine the actual likelihood and extent of each marker’s participation. (shrink)

The Liver kinase B1 with its downstream target AMP activated protein kinase (LKB1‐AMPK), and the key nutrient sensor mammalian target of rapamycin complex 1 (mTORC1) form two signaling systems that coordinate metabolic and cellular activity with changes in the environment in order to preserve homeostasis. For example, nutritional fluctuations rapidly feed back on these signaling systems and thereby affect cell‐specific functions. Recent studies have started to reveal important roles of these strategic metabolic regulators in Schwann cells for the (...) trophic support and myelination of axons. Because aberrant intermediate metabolism along with mitochondrial dysfunction in Schwann cells is mechanistically linked to nerve abnormalities found in acquired and inherited peripheral neuropathies, manipulation of the LKB1‐AMPK, and mTORC1 signaling hubs may be a worthwhile therapeutic target to mitigate nerve damage in disease. Here, recent advances in our understanding of LKB1‐AMPK and mTORC1 functions in Schwann cells are covered, and future research areas for this key metabolic signaling network are proposed. (shrink)

We consider metabolic networks with reversible enzymatic reactions. The model is written as a system of ordinary differential equations, possibly with inputs and outputs. We prove the global stability of the equilibrium , using techniques of monotone systems and compartmental matrices. We show that the equilibrium does not always exist. Finally, we consider a metabolic system coupled with a genetic network, and we study the dependence of the metabolic equilibrium with respect to concentrations of enzymes. We (...) give some conclusions concerning the dynamical behavior of coupled genetic/metabolic systems. (shrink)

Metabolic pathways underlying brain function remain largely unexplored during neurodevelopment, predominantly due to the lack of feasible techniques for use with awake infants. Broadband near-infrared spectroscopy provides the opportunity to explore the relationship between cerebral energy metabolism and blood oxygenation/haemodynamics through the measurement of changes in the oxidation state of mitochondrial respiratory chain enzyme cytochrome-c-oxidase alongside haemodynamic changes. We used a bNIRS system to measure ΔoxCCO and haemodynamics during functional activation in a group of 42 typically developing infants aged (...) between 4 and 7 months. bNIRS measurements were made over the right hemisphere over temporal, parietal and central cortical regions, in response to social and non-social visual and auditory stimuli. Both ΔoxCCO and Δ[HbO2] displayed larger activation for the social condition in comparison to the non-social condition. Integration of haemodynamic and metabolic signals revealed networks of stimulus-selective cortical regions that were not apparent from analysis of the individual bNIRS signals. These results provide the first spatially resolved measures of cerebral metabolic activity alongside haemodynamics during functional activation in infants. Measuring synchronised changes in metabolism and haemodynamics have the potential for uncovering the development of cortical specialisation in early infancy. (shrink)

Recent research shows that a faulty or sub‐optimally operating metabolic network can often be rescued by the targeted removal of enzyme‐coding genes – the exact opposite of what traditional gene therapy would suggest. Predictions go as far as to assert that certain gene knockouts can restore the growth of otherwise nonviable gene‐deficient cells. Many questions follow from this discovery: What are the underlying mechanisms? How generalizable is this effect? What are the potential applications? Here, I approach these questions from (...) the perspective of compensatory perturbations on networks. Relations are drawn between such synthetic rescues and naturally occurring cascades of reaction inactivation, as well as their analogs in physical and other biological networks. I specially discuss how rescue interactions can lead to the rational design of antagonistic drug combinations that select against resistance and how they can illuminate medical research on cancer, antibiotics, and metabolic diseases. Editor's suggested further reading in BioEssaysThe evolutionary context of robust and redundant cell biological mechanisms AbstractReprogramming cell fates: reconciling rarity with robustness Abstract. (shrink)

Mitochondrial function is key for maintaining cellular health, while mitochondrial failure is associated with various pathologies, including inherited metabolic disorders and age‐related diseases. In order to maintain mitochondrial quality, several pathways of mitochondrial quality control have evolved. These systems monitor mitochondrial integrity through antioxidants, DNA repair systems, and chaperones and proteases involved in the mitochondrial unfolded protein response. Additional regulation of mitochondrial function involves dynamic exchange of components through mitochondrial fusion and fission. Sustained stress induces a selective autophagy – (...) termed mitophagy – and ultimately leads to apoptosis. Together, these systems form a network that acts on the molecular, organellar, and cellular level. In this review, we highlight how these systems are regulated in an integrated context‐ and time‐dependent network of mitochondrial quality control that is implicated in healthy aging. (shrink)

I hypothesize that re-occurring prior experience of complex systems mobilizes a fast response, whose attractor is encoded by their strongly connected network core. In contrast, responses to novel stimuli are often slow and require the weakly connected network periphery. Upon repeated stimulus, peripheral network nodes remodel the network core that encodes the attractor of the new response. This “core-periphery learning” theory reviews and generalizes the heretofore fragmented knowledge on attractor formation by neural networks, periphery-driven innovation, and a number of (...) recent reports on the adaptation of protein, neuronal, and social networks. The core-periphery learning theory may increase our understanding of signaling, memory formation, information encoding and decision-making processes. Moreover, the power of network periphery-related “wisdom of crowds” inventing creative, novel responses indicates that deliberative democracy is a slow yet efficient learning strategy developed as the success of a billion-year evolution. Also see the video abstract here: https://youtu.be/IIjP7zWGjVE. The network core triggers fast responses to previously experienced stimuli. Innovations require the network periphery that encodes a novel attractor by core-remodeling. This core-periphery learning theory is introduced as a general adaptation, learning, decision-making, and forgetting mechanism of all complex systems including protein, metabolic, signaling, neuronal, social networks, and ecosystems. (shrink)

The search for a systems‐level picture of metabolism as a web of molecular interactions provides a paradigmatic example of how the methods used to characterize a system can bias the interpretation of its functional meaning. Metabolic maps have been analyzed using novel techniques from network theory, revealing some non‐trivial, functionally relevant properties. These include a small‐world structure and hierarchical modularity. However, as discussed here, some of these properties might actually result from an inappropriate way of defining network interactions. Starting (...) from the so‐called bipartite organization of metabolism, where the two meaningful subsets (reactions and metabolites) are considered, most current works use only one of the subsets by means of so‐called graph projections. Unfortunately, projected graphs often ignore relevant biological and chemical constraints, thus leading to statistical artifacts. Some of these drawbacks and alternative approaches need to be properly addressed. (shrink)

Scale-free network models describe many natural and social phenomena. In particular, networks of interacting components of a living cell were shown to possess scale-free properties. A recent study(1) compares the system-level properties of metabolic and information networks in 43 archaeal, bacterial and eukaryal species and claims that the scale-free organization of these networks is more conserved during evolution than their content. BioEssays 24:105–109, 2002. Published 2002 Wiley Periodicals, Inc.

The vast majority (> 95%) of single-gene mutations in yeast affect not only the expression of the mutant gene, but also the expression of many other genes. These data suggest the presence of a previously uncharacterized ‘gene expression network’—a set of interactions between genes which dictate gene expression in the native cell environment. Here, we quantitatively analyze the gene expression network revealed by microarray expression data from 273 different yeast gene deletion mutants.(1) We find that gene expression interactions form a (...) robust, error-tolerant ‘scale-free’ network, similar to metabolic pathways(2) and artificial networks such as power grids and the internet.(3-5) Because the connectivity between genes in the gene expression network is unevenly distributed, a scale-free organization helps make organisms resistant to the deleterious effects of mutation, and is thus highly adaptive. The existence of a gene expression network poses practical considerations for the study of gene function, since most mutant phenotypes are the result of changes in the expression of many genes. Using principles of scale-free network topology, we propose that fragmenting the gene expression network via ‘genome-engineering’ may be a viable and practical approach to isolating gene function. BioEssays 24:267–274, 2002. © 2002 Wiley Periodicals, Inc.; DOI 10.1002/bies.10054. (shrink)

By investigating the status quo of the swimming training market in a certain area, we can obtain information on the current development of the swimming training market in a certain area and study the laws of the development of the market so as to provide a theoretical basis for the development of the market. This paper designs an evaluation algorithm suitable for swimming training based on the improved AlexNet network. The algorithm model uses a 3 × 3 size convolution kernel (...) to extract features, and the pooling layer uses a nonoverlapping pooling strategy. In order to accelerate the network convergence, the model introduces batch normalization technology. The algorithm uses data augmentation technology to expand the data set, including rotation and random erasure, to a certain extent alleviating the problem of overfitting. The results of the study showed that there were no significant differences in fat, minerals, protein, body mass index, basal metabolic rate, and total energy expenditure in the body composition ratios of children in the convolutional neural network assessment group and the control group, while muscle and total body water were not significantly different. However, there are significant differences in fat-free body weight and muscle strength of various segments of the body, among which there are very significant differences in muscle strength of lower limbs in each segment of the body. There were no significant differences in minerals, body mass index, basal metabolic rate, total energy expenditure, and lower limb muscle strength in the body composition ratios of men and women in the convolutional neural network assessment group. There are significant differences in body weight, upper limb muscle strength, and trunk muscle strength. There were no significant differences in the proportions of body composition between men and women in the control group, except for fat and protein. (shrink)

The new business opportunities and prospects emerging in Europe within the Common Market and other Western and European countries also raise important ethical challenges. This work comprises a collection of ethical insights to enhance the conduct of business in an evolving Europe.

The standard representation of the Central Dogma (CD) of Molecular Biology conspicuously ignores metabolism. However, both the metabolites and the biochemical fluxes behind any biological phenomenon are encrypted in the DNA sequence. Metabolism constrains and even changes the information flow when the DNA‐encoded instructions conflict with the homeostasis of the biochemical network. Inspection of adaptive virulence programs and emergence of xenobiotic‐biodegradation pathways in environmental bacteria suggest that their main evolutionary drive is the expansion of their metabolic networks towards (...) new chemical landscapes rather than perpetuation and spreading of their DNA sequences. Faulty enzymatic reactions on suboptimal substrates often produce reactive oxygen species (ROS), a process that fosters DNA diversification and ultimately couples catabolism of the new chemicals to growth. All this calls for a revision of the CD in which metabolism (rather than DNA) has the leading role. (shrink)

We hypothesize that life began not with the first self‐reproducing molecule or metabolic network, but as a prebiotic ecology of co‐evolving populations of macromolecular aggregates (composomes). Each composome species had a particular molecular composition resulting from molecular complementarity among environmentally available prebiotic compounds. Natural selection acted on composomal species that varied in properties and functions such as stability, catalysis, fission, fusion and selective accumulation of molecules from solution. Fission permitted molecular replication based on composition rather than linear structure, while (...) fusion created composomal variability. Catalytic functions provided additional chemical novelty resulting eventually in autocatalytic and mutually catalytic networks within composomal species. Composomal autocatalysis and interdependence allowed the Darwinian co‐evolution of content and control (metabolism). The existence of chemical interfaces within complex composomes created linear templates upon which self‐reproducing molecules (such as RNA) could be synthesized, permitting the evolution of informational replication by molecular templating. Mathematical and experimental tests are proposed. BioEssays 28: 399–412, 2006. © 2006 Wiley Periodicals, Inc. (shrink)

This paper deals with the application of the metabolic control theory, especially the measurement of control coefficients, to the threonine pathway inE. coli. The control coefficient of a step on a metabolic flux quantitatively assesses the flux response to the step variations. This concept is particularly relevant both in pathological situations (decrease in the activity of an enzymatic step in the metabolism) and in biotechnologies, where, on the contrary steps are amplified.Measurement of the control coefficients of the steps (...) of a metabolic network makes it possible to know those whose amplification should lead to a simultaneous increase in the fluxes. (shrink)

The role of evolutionary theory at the origin of life is an extensively debated topic. The origin and early development of life is usually separated into a prebiotic phase and a protocellular phase, ultimately leading to the Last Universal Common Ancestor. Most likely, the Last Universal Common Ancestor was subject to Darwinian evolution, but the question remains to what extent Darwinian evolution applies to the prebiotic and protocellular phases. In this review, we reflect on the current status of evolutionary theory (...) in origins of life research by bringing together philosophy of science, evolutionary biology, and empirical research in the origins field. We explore the various ways in which evolutionary theory has been extended beyond biology; we look at how these extensions apply to the prebiotic development of (proto)metabolism; and we investigate how the terminology from evolutionary theory is currently being employed in state-of-the-art origins of life research. In doing so, we identify some of the current obstacles to an evolutionary account of the origins of life, as well as open up new avenues of research. (shrink)

During the last few months, several pioneer genome‐wide transcriptomic, proteomic and metabolomic studies have revolutionised the understanding of bacterial biological processes, leading to a picture that resembles eukaryotic complexity. Technological advances such as next‐generation high‐throughput sequencing and high‐density oligonucleotide microarrays have allowed the determination, in several bacteria, of the entire boundaries of all expressed transcripts. Consequently, novel RNA‐mediated regulatory mechanisms have been discovered including multifunctional RNAs. Moreover, resolution of bacterial proteome organisation (interactome) and global protein localisation (localizome) have unveiled an (...) unanticipated complexity that highlights the significance of protein multifunctionality and localisation in the cell. Also, analysis of a complete bacterial metabolic network has again revealed a high fraction of multifunctional enzymes and an unexpectedly high level of metabolic responses and adaptation. Altogether, these novel approaches have permitted the deciphering of the entire physiological landscape of one of the smallest bacteria, Mycoplasma pneumoniae. Here, we summarise and discuss recent findings aimed at defining the blueprint of any prokaryote. (shrink)

This paper studies the information of big data in the digital publishing industry chain and adopts advanced algorithms for its fusion calculation. The basic theory of digital publishing ecological chain is dissected, the construction requirements, construction methods, and construction paths of digital publishing ecological chain are analysed, and feasible construction measures are proposed. It also defines the connotation of the fusion of knowledge services between publishing institutions and libraries in the digital era; then analyses the characteristics and principles of the (...) fusion of knowledge services between publishing institutions and libraries in the digital era; and finally sorts out the theoretical foundations such as synergy theory, information integration service theory, and game theory. Meanwhile, this paper also studies the flow of digital publishing resources and empirically analyses the eco-efficiency of digital publishing eco-chain by using metabolic network analysis, population analysis, and life cycle analysis, and it finds the eco-efficiency problems of the existing e-book eco-chain from its analysis. Finally, the imbalance in the digital publishing ecological chain and its hazards are analysed, and specific regulation and optimization measures are proposed. The research in this paper makes up for the deficiencies of related studies and can well solve the problems that exist in the previous and provide theoretical support for the healthy development of digital publishing enterprises. (shrink)

Synthetic genomics is a new field of research in which small DNA pieces are assembled in a series of steps into whole genomes. The highly reduced genomes of host‐associated bacteria are now being used as models for de novo synthesis of small genomes in the laboratory. Bacteria with the smallest genomes identified in nature provide nutrients to their hosts, such as amino acids, co‐factors and vitamins. Comparative genomics of these bacteria enables predictions to be made about the gene sets required (...) for core cellular functions and the associated metabolic network for the biosynthesis of host‐selected compounds. Synthetic biology may ultimately enable researchers to make customized cell‐specific organelles for the production and delivery of drugs to humans and domestic animals. Synthetic genomics may also become the method of choice for functional analyses of genes and genomes from bacteria that cannot be cultivated in the laboratory. (shrink)

The structuralist reconstruction of the metabolic biochemistry here presented is a more complete and revised version than the one presented in Donolo, Federico & Lorenzano (2006). This version, as the previous one, continues with the reconstructive task initiated by César Lorenzano (2002), but advances further on those elements which remained pendent of reconstruction: applications subsequent to the paradigmatic one, for being these “too diversified and numerous” (p. 210).In line with which is said before, the objective of this new reconstruction (...) is to make the theoretical network of the biochemistry wider, in order to be able to capture the many successful applications (paradigmatic examples or exemplars) which appear in modern university textbooks. In order to accomplish this, major conceptual precisions are being introduced which will have repercussions in a modification and increased complexity of the fundamental law implicit in the text books, but still conserving the previous basic idea. Because of all this we can say that the present article goes further into the reconstruction task of the metabolic biochemistry theory. (shrink)

The logic of genetic discovery has changed little over time, but the focus of biology is shifting from simple genotype–phenotype relationships to complex metabolic, physiological, developmental, and behavioral traits. In light of this, the traditional reductionist view of individual genes as privileged difference‐making causes of phenotypes is re‐examined. The scope and nature of genetic effects in complex regulatory systems, in which dynamics are driven by regulatory feedback and hierarchical interactions across levels of organization are considered. This review argues that (...) it is appropriate to treat genes as specific actual difference‐makers for the molecular regulation of gene expression. However, they are often neither stable, proportional, nor specific as causes of the overall dynamic behavior of regulatory networks. Dynamical models, properly formulated and validated, provide the tools to probe cause‐and‐effect relationships in complex biological systems, allowing to go beyond the limitations of genetic reductionism to gain an integrative understanding of the causal processes underlying complex phenotypes. (shrink)

Ageing causes progressive decline in metabolic, behavioural, and physiological functions, leading to a reduced health span. The extracellular matrix (ECM) is the three‐dimensional network of macromolecules that provides our tissues with structure and biomechanical resilience. Imbalance between damage and repair/regeneration causes the ECM to undergo structural deterioration with age, contributing to age‐associated pathology. The ECM ‘Ageing Across the Life Course’ interdisciplinary research network (ECMage) was established to bring together researchers in the United Kingdom, and internationally, working on the emerging (...) field of ECM ageing. Here we report on a consultation at a joint meeting of ECMage and the Medical Research Council / Versus Arthritis Centre for Integrated Research into Musculoskeletal Ageing, held in January 2023, in which delegates analysed the key questions and research opportunities in the field of ECM ageing. We examine fundamental biological questions, enabling technologies, systems of study and emerging in vitro and in silico models, alongside consideration of the broader challenges facing the field. (shrink)

Graphical AbstractGene regulatory networks, which are crucial for the proper development of organisms, are extensively studied. From these investigations, coordinative mechanisms are shown to be instructive for further development. Competitive mechanisms as well as environmental and metabolic influences, however, are widely ignored so far but appear to be important for the emergence of shape.

The inositol phosphate metabolism network has been found to be much more complex than previously thought, as more and more inositol phosphates and their metabolizing enzymes have been discovered. Some of the inositol phosphates have been shown to have biological activities, but little is known about their signal transduction mechanisms except for that of inositol 1,4,5‐trisphosphate. The recent discovery, however, of a number of binding proteins for inositol high polyphosphate [inositol 1,3,4,5‐tetrakisphosphate (IP4), inositol 1,3,4,5,6‐pentakisphosphate, or inositol hexakisphosphate] enables us to (...) speculate on the physiological function of these compounds. In this article we focus on two major issues: (1) the roles of inositol high polyphosphates in vesicular trafficking, especially exocytosis, and (2) pleckstrin homology domaincontaining IP4 binding proteins involved in the Ras signaling pathway. (shrink)

The aim of this paper is to provide a theoretical framework to understand how multicellular systems realize functionally integrated physiological entities by organizing their intercellular space. From a perspective centered on physiology and integration, biological systems are often characterized as organized in such a way that they realize metabolic self-production and self-maintenance. The existence and activity of their components rely on the network they realize and on the continuous management of the exchange of matter and energy with their environment. (...) One of the virtues of the organismic approach focused on organization is that it can provide an understanding of how biological systems are functionally integrated into coherent wholes. Organismic frameworks have been primarily developed by focusing on unicellular life. Multicellularity, however, presents additional challenges to our understanding of biological systems, related to how cells are capable to live together in higher-order entities, in such a way that some of their features and behaviors are constrained and controlled by the system they realize. Whereas most accounts of multicellularity focus on cell differentiation and increase in size as the main elements to understand biological systems at this level of organization, we argue that these factors are insufficient to provide an understanding of how cells are physically and functionally integrated in a coherent system. In this paper, we provide a new theoretical framework to understand multicellularity, capable to overcome these issues. Our thesis is that one of the fundamental theoretical principles to understand multicellularity, which is missing or underdeveloped in current accounts, is the functional organization of the intercellular space. In our view, the capability to be organized in space plays a central role in this context, as it enables (and allows to exploit all the implications of) cell differentiation and increase in size, and even specialized functions such as immunity. We argue that the extracellular matrix plays a crucial active role in this respect, as an evolutionary ancient and specific (non-cellular) control subsystem that contributes as a key actor to the functional specification of the multicellular space and to modulate cell fate and behavior. We also analyze how multicellular systems exert control upon internal movement and communication. Finally, we show how the organization of space is involved in some of the failures of multicellular organization, such as aging and cancer. (shrink)

Within the field of systems theory, the term robustness has typically been applied to different contexts such as automatic control, genetic networks, metabolic pathways, morphogenesis, and ecosystems. All these systems involve either man-made machines, or living organisms. In this chapter, we will consider music as a peculiar complex system, involving both the realm of machines and the realm of biology. We will discuss some of the properties of music experience in terms of different attributes of robustness, focusing in (...) particular on stability, the property enabling a complex system to maintain its function against a wide range of external and internal changes. We will provide examples of the human ability of isolating and maintaining stable information within the perceptual flow and despite changes in the external world that reach our perceptions, leading towards a characterization of robustness in music perception as referred both to the search for regularities and to the range of tolerance that perception admits to regularities. Finally, we will list four multiple interaction cycles that typically characterize music experience and that involve both internal properties of the organism and the environment. (shrink)

In searching for life in extraterrestrial space, it is essential to act based on an unequivocal definition of life. In the twentieth century, life was defined as cells that self-replicate, metabolize, and are open for mutations, without which genetic information would remain unchangeable, and evolution would be impossible. Current definitions of life derive from statistical mechanics, physics, and chemistry of the twentieth century in which life is considered to function machine like, ignoring a central role of communication. Recent observations show (...) that context-dependent meaningful communication and network formation (and control) are central to all life forms. Evolutionary relevant new nucleotide sequences now appear to have originated from social agents such as viruses, their parasitic relatives, and related RNA networks, not from errors. By applying the known features of natural languages and communication, a new twenty-first century definition of life can be reached in which communicative interactions are central to all processes of life. A new definition of life must integrate the current empirical knowledge about interactions between cells, viruses, and RNA networks to provide a better explanatory power than the twentieth century narrative. (shrink)

Cranial electrotherapy stimulation is a neuromodulation tool used for treating several clinical disorders, including insomnia, anxiety, and depression. More recently, a limited number of studies have examined CES for altering affect, physiology, and behavior in healthy, non-clinical samples. The physiological, neurochemical, and metabolic mechanisms underlying CES effects are currently unknown. Computational modeling suggests that electrical current administered with CES at the earlobes can reach cortical and subcortical regions at very low intensities associated with subthreshold neuromodulatory effects, and studies using (...) electroencephalography and functional magnetic resonance imaging show some effects on alpha band EEG activity, and modulation of the default mode network during CES administration. One theory suggests that CES modulates brain stem, limbic, and cortical regions and increases relative parasympathetic to sympathetic drive in the autonomic nervous system. There is no direct evidence supporting this theory, but one of its assumptions is that CES may induce its effects by stimulating afferent projections of the vagus nerve, which provides parasympathetic signals to the cardiorespiratory and digestive systems. In our critical review of studies using CES in clinical and non-clinical populations, we found severe methodological concerns, including potential conflicts of interest, risk of methodological and analytic biases, issues with sham credibility, lack of blinding, and a severe heterogeneity of CES parameters selected and employed across scientists, laboratories, institutions, and studies. These limitations make it difficult to derive consistent or compelling insights from the extant literature, tempering enthusiasm for CES and its potential to alter nervous system activity or behavior in meaningful or reliable ways. The lack of compelling evidence also motivates well-designed and relatively high-powered experiments to assess how CES might modulate the physiological, affective, and cognitive responses to stress. Establishing reliable empirical links between CES administration and human performance is critical for supporting its prospective use during occupational training, operations, or recovery, ensuring reliability and robustness of effects, characterizing if, when, and in whom such effects might arise, and ensuring that any benefits of CES outweigh the risks of adverse events. (shrink)

Let us start by some general definitions of the concept of complexity. We take a complex system to be one composed by a large number of parts, and whose properties are not fully explained by an understanding of its components parts. Studies of complex systems recognized the importance of “wholeness”, defined as problems of organization (and of regulation), phenomena non resolvable into local events, dynamics interactions in the difference of behaviour of parts when isolated or in higher configuration, etc., in (...) short, systems of various orders (or levels) not understandable by investigation of their respective parts in isolation. In a complex system it is essential to distinguish between ‘global’ and ‘local’ properties. Theoretical physicists in the last two decades have discovered that the collective behaviour of a macro-system, i.e. a system composed of many objects, does not change qualitatively when the behaviour of single components are modified slightly. Conversely, it has been also found that the behaviour of single components does change when the overall behaviour of the system is modified. There are many universal classes which describe the collective behaviour of the system, and each class has its own characteristics; the universal classes do not change when we perturb the system. The most interesting and rewarding work consists in finding these universal classes and in spelling out their properties. This conception has been followed in studies done in the last twenty years on second order phase transitions. The objective, which has been mostly achieved, was to classify all possible types of phase transitions in different universality classes and to compute the parameters that control the behaviour of the system near the transition (or critical or bifurcation) point as a function of the universality class. This point of view is not very different from the one expressed by Thom in the introduction of Structural Stability and Morphogenesis (1975). It differs from Thom’s program because there is no a priori idea of the mathematical framework which should be used. Indeed Thom considers only a restricted class of models (ordinary differential equations in low dimensional spaces) while we do not have any prejudice regarding which models should be accepted. One of the most interesting and surprising results obtained by studying complex systems is the possibility of classifying the configurations of the system taxonomically. It is well-known that a well founded taxonomy is possible only if the objects we want to classify have some unique properties, i.e. species may be introduced in an objective way only if it is impossible to go continuously from one specie to another; in a more mathematical language, we say that objects must have the property of ultrametricity. More precisely, it was discovered that there are conditions under which a class of complex systems may only exist in configurations that have the ultrametricity property and consequently they can be classified in a hierarchical way. Indeed, it has been found that only this ultrametricity property is shared by the near-optimal solutions of many optimization problems of complex functions, i.e. corrugated landscapes in Kauffman’s language. These results are derived from the study of spin glass model, but they have wider implications. It is possible that the kind of structures that arise in these cases is present in many other apparently unrelated problems. Before to go on with our considerations, we have to pick in mind two main complementary ideas about complexity. (i) According to the prevalent and usual point of view, the essence of complex systems lies in the emergence of complex structures from the non-linear interaction of many simple elements that obey simple rules. Typically, these rules consist of 0–1 alternatives selected in response to the input received, as in many prototypes like cellular automata, Boolean networks, spin systems, etc. Quite intricate patterns and structures can occur in such systems. However, what can be also said is that these are toy systems, and the systems occurring in reality rather consist of elements that individually are quite complex themselves. (ii) So, this bring a new aspect that seems essential and indispensable to the emergence and functioning of complex systems, namely the coordination of individual agents or elements that themselves are complex at their own scale of operation. This coordination dramatically reduces the degree of freedom of those participating agents. Even the constituents of molecules, i.e. the atoms, are rather complicated conglomerations of subatomic particles, perhaps ultimately excitations of patterns of superstrings. Genes, the elementary biochemical coding units, are very complex macromolecular strings, as are the metabolic units, the proteins. Neurons, the basic elements of cognitive networks, themselves are cells. In those mentioned and in other complex systems, it is an important feature that the potential complexity of the behaviour of the individual agents gets dramatically simplified through the global interactions within the system. The individual degrees of freedom are drastically reduced, or, in a more formal terminology, the factual space of the system is much smaller than the product of the state space of the individual elements. That is one key aspect. The other one is that on this basis, that is utilizing the coordination between the activities of its members, the system then becomes able to develop and express a coherent structure at a higher level, that is, an emergent behaviour (and emergent properties) that transcends what each element is individually capable of. (shrink)

Systems biology is largely tributary to genomics and other “omic” disciplines that generate vast amounts of structural data. “Omics”, however, lack a theoretical framework that would allow using these data sets as such (rather than just tiny bits that are extracted by advanced data-mining techniques) to build explanatory models that help understand physiological processes. Systems biology provides such a framework by adding a dynamic dimension to merely structural “omics”. It makes use of bottom-up and top-down models. The former are based (...) on data about systems components, the latter on systems-level data. We trace back both modeling strategies (which are often used to delineate two branches of the field) to the modeling of metabolic and signaling pathways in the bottom-up case, and to biological cybernetics and systems theory in the top-down case. We then argue that three roots of systems biology must be discerned to account adequately for the structure of the field: pathway modeling, biological cybernetics, and “omics”. We regard systems biology as merging modeling strategies (supplemented by new mathematical procedures) from data-poor fields with data supply from a field that is quite deficient in explanatory modeling. After characterizing the structure of the field, we address some epistemological and ontological issues regarding concepts on which the top-down approach relies and that seem to us to require clarification. This includes the consequences of identifying modules in large networks without relying on functional considerations, the question of the “holism” of systems biology, and the epistemic value of the “systeome” project that aspires to become the cutting edge of the field. (shrink)

In the past decades, an enormous amount of precious information has been collected about molecular and genetic characteristics of cancer. This knowledge is mainly based on a reductionistic approach, meanwhile cancer is widely recognized to be a ‘system biology disease’. The behavior of complex physiological processes cannot be understood simply by knowing how the parts work in isolation. There is not solely a matter how to integrate all available knowledge in such a way that we can still deal with complexity, (...) but we must be aware that a deeply transformation of the currently accepted oncologic paradigm is urgently needed. We have to think in terms of biological networks: understanding of complex functions may in fact be impossible without taking into consideration influences outside of the genome. Systems Biology involves connecting experimental unsupervised multivariate data to mathematical and computational approach than can simulate biologic systems for hypothesis testing or that can account for what it is not known from high-throughput data sets. Metabolomics could establish the requested link between genotype and phenotype, providing informations that ensure an integrated understanding of pathogenic mechanisms and metabolic phenotypes and provide a screening tool for new targeted drug. (shrink)

Design patterns are generalized solutions to frequently recurring problems. They were initially developed by architects and computer scientists to create a higher level of abstraction for their designs. Here, we extend these concepts to cell biology to lend a new perspective on the evolved designs of cells' underlying reaction networks. We present a catalog of 21 design patterns divided into three categories: creational patterns describe processes that build the cell, structural patterns describe the layouts of reaction networks, and (...) behavioral patterns describe reaction network function. Applying this pattern language to the E. coli central metabolic reaction network, the yeast pheromone response signaling network, and other examples lends new insights into these systems. (shrink)

Moonlighting – the performance of more than one function by a single protein – is becoming recognized as a common phenomenon with important implications for systems biology and human health. The different functions of a moonlighting protein may use different regions of the protein structure, or alternative structures that occur due to post-translational modifications and/or differences in binding partners. Often the different functions of moonlighting proteins are used at different times or in different places. The existence of moonlighting functions complicates (...) efforts to under- stand metabolic and regulatory networks, as well as physiological and pathological processes in organisms. Because moonlighting functions can play important roles in disease processes, an improved understanding of moonlighting proteins will provide new opportunities for pharmacological manipulations that specifically target a function involved in pathology while sparing physiologically important functions. (shrink)

Possible systemic effects of general anesthetic agents on neural information processing are discussed in the context of the thalamocortical suppression hypothesis presented by Drs. Alkire, Haier, and Fallon (this issue) in their PET study of the anesthetized state. Accounts of the neural requisites of consciousness fall into two broad categories. Neuronal-specificity theories postulate that activity in particular neural populations is sufficient for conscious awareness, while process-coherence theories postulate that particular organizations of neural activity are sufficient. Accounts of anesthetic narcosis, on (...) the other hand, explain losses of consciousness in terms of neural signal-suppressions, transmission blocks, and the disruptions of signal interpretation. While signal-suppression may account for the actions of some anesthetic agents, the existence of anesthetics, such as choralose, that cause both loss of consciousness and elevated discharge rates, is problematic for a general theory of narcosis that is based purely on signal suppression and transmission-block. However, anesthetic agents also alter relative firing rates and temporal discharge patterns that may disrupt the coherence of neural signals and the functioning of the neural networks that interpret them. It is difficult at present, solely on the basis of regional brain metabolic rates, to test process-coherence hypotheses regarding organizational requisites for conscious awareness. While these pioneering PET studies have great merit as panoramic windows of mind-brain correlates, wider ranges of theory and empirical evidence need to be brought into the formulation of truly comprehensive theories of consciousness and anesthesia. (shrink)

The human masticatory system is a complex functional unit characterized by a multitude of skeletal components, muscles, soft tissues, and teeth. Muscle activation dynamics cannot be directly measured on live human subjects due to ethical, safety, and accessibility limitations. Therefore, estimation of muscle activations and their resultant forces is a longstanding and active area of research. Reinforcement learning (RL) is an adaptive learning strategy which is inspired by the behavioral psychology and enables an agent to learn the dynamics of an (...) unknown system via policy-driven explorations. The RL framework is a well-formulated closed-loop system where high capacity neural networks are trained with the feedback mechanism of rewards to learn relatively complex actuation patterns. In this work, we are building on a deep RL algorithm, known as the Soft Actor-Critic, to learn the inverse dynamics of a simulated masticatory system, i.e., learn the activation patterns that drive the jaw to its desired location. The outcome of the proposed training procedure is a parametric neural model which acts as the brain of the biomechanical system. We demonstrate the model’s ability to navigate the feasible three-dimensional (3D) envelope of motion with sub-millimeter accuracies. We also introduce a performance analysis platform consisting of a set of quantitative metrics to assess the functionalities of a given simulated masticatory system. This platform assesses the range of motion, metabolic efficiency, the agility of motion, the symmetry of activations, and the accuracy of reaching the desired target positions. We demonstrate how the model learns more metabolically efficient policies by integrating a force regularization term in the RL reward. We also demonstrate the inverse correlation between the metabolic efficiency of the models and their agility and range of motion. The presented masticatory model and the proposed RL training mechanism are valuable tools for the analysis of mastication and other biomechanical systems. We see this framework’s potential in facilitating the functional analyses aspects of surgical treatment planning and predicting the rehabilitation performance in post-operative subjects. (shrink)

Synthetic biology is a field of research that concentrates on the design, construction, and modification of new biomolecular parts and metabolic pathways using engineering techniques and computational models. By employing knowledge of operational pathways from engineering and mathematics such as circuits, oscillators, and digital logic gates, it uses these to understand, model, rewire, and reprogram biological networks and modules. Standard biological parts with known functions are catalogued in a number of registries (e.g. Massachusetts Institute of Technology Registry of (...) Standard Biological Parts). Biological parts can then be selected from the catalogue and assembled in a variety of combinations to construct a system or pathway in a microbe. Through the innovative re-engineering of biological circuits and the optimization of certain metabolic pathways, biological modules can be designed to reprogram organisms to produce products or behaviors. Synthetic biology is what is known as a “platform technology”. That is, it generates highly transferrable theoretical models, engineering principles, and know-how that can be applied to create potential products in a wide variety of industries. Proponents suggest that applications of synthetic biology may be able to provide scientific and engineered solutions to a multitude of worldwide problems from health to energy. Synthetic biology research has already been successful in constructing microbial products which promise to offer cheaper pharmaceuticals such as the antimalarial synthetic drug artemisinin, engineered microbes capable of cleaning up oil spills, and the engineering of biosensors that can detect the presence of high concentrations of arsenic in drinking water. One of the potential benefits of synthetic biology research is in its application to biofuel production. It is this application which is the focus of this entry. The term “biofuel” has referred generally to all liquid fuels that are sourced from plant or plant byproducts and are used for energy necessary for transportation vehicles (Thompson 2012). Biofuels that are produced using synthetic biological techniques re-engineer microbes into biofuel factories are a subset of these. (shrink)

This article reformulates Stephan Helmreich´s the ¨microbiomisation of race¨ as the historiality of otherness in the foundations of human microbiome science. Through the lens of my ethnographic fieldwork of a transnational community of microbiome scientists that conducted a landmark human microbiome research on indigenous microbes and its affiliated and first personalised microbiome initiative, the American Gut Project, I follow and trace the key actors, experimental systems and onto-epistemic claims in the emergence of human microbiome science a decade ago. In doing (...) so, I show the links between the reinscription of race, comparative research on the microbial genetic variation of human populations and the remining of bioprospected data for personalised medicine. In these unpredictable research movements, the microbiome of non-Western peoples and territories is much more than a side project or a specific approach within the field: it constitutes the nucleus of its experimental system, opening towards subsequent and cumulative research processes and knowledge production in human microbiome science. The article demonstrates that while human microbiome science is articulated upon the microbial ‘makeup’ of non-wester(nised) communities, societies, and locales, its results and therapeutics are only applicable to medical conditions affecting rich nations (i.e., inflammatory, autoimmune, and metabolic diseases). My reformulation of ¨microbiomisation of race¨ as the condition of possibility of human microbiome science reveals that its individual dimension is sustained by microbial DNA data from human populations through bioprospecting practices and gains meaning through personalised medicine initiatives, informal online networks of pseudoscientific and commodified microbial-related evidence. (shrink)