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• W2019938928 abstract "VIEWPOINTEmergent phenomena and the secrets of lifePeter T. MacklemPeter T. MacklemPublished Online:01 Jun 2008https://doi.org/10.1152/japplphysiol.00942.2007This is the final version - click for previous versionMoreSectionsPDF (109 KB)Download PDF ToolsExport citationAdd to favoritesGet permissionsTrack citations ShareShare onFacebookTwitterLinkedInWeChat in 1944 erwin schrodinger, the Nobelist in physics, presented biology with an unprecedented challenge. In his monograph “What Is Life?” (18), he stated that life had two secrets: the passage of an encoded molecule from parents to offspring to explain heritable characteristics, and the spontaneous emergence of self-organized order. Biochemistry and biophysics responded to the first challenge with stunning success, resulting in today's revolution in genetics and molecular biology. The second is a challenge to physiology. It is physiology's job to provide a deep understanding of life, not merely a description. If we fail to do so, physiology will become a science secondary to biochemistry and biophysics.Life's order is characterized by emergent phenomena. These I define as the spontaneous development of self-organized order among ensembles that can neither be predicted nor explained by examining component parts in isolation. Spontaneity and self-organization mean that no external agent is sculpting the organism: it sculpts itself. Ensembles mean that an emergent system is composed of many parts. And for the component parts to self-organize, they must intercommunicate, interact, and cooperate. Life provides many interconnections: hormones, nerves, gap junctions, cytokines, and so forth. Thus understanding emergence requires studying the behavior of integrated networks. Reductionism cannot solve the secrets of emergence.Consciousness is the most striking (and difficult) example of an emergent phenomenon. But to understand emergence it is better to start with simpler examples and, once they are solved, to progress to more complex ones.Understanding starts with the second law of thermodynamics because it is the only physical law dealing with order. It states that systems tend to evolve from improbable configurations to more probable ones. Order is improbable and disorder (called entropy) is more probable. A smoke ring illustrates this. When it emerges from a smoker's mouth it is in a highly ordered, improbable configuration. With time, the order disappears as the smoke particles diffuse and become randomly dispersed throughout the room. When dispersion is complete, entropy is maximal. This process is irreversible; left to itself, the improbable doughnut never spontaneously reforms.It takes energy to create improbable configurations from disordered ones. Ilya Prigogine won the Nobel Prize for discovering that the importation and dissipation of energy into chemical systems could reverse the inexorable disintegration into disorder predicted by the second law (15). The second law only applies to closed thermodynamic systems with no exchange of energy or entropy with the environment, whereas life is an open thermodynamic system, in which energy is imported as food and oxygen and utilized in a process we call metabolism. Entropy in the form of waste products is exported. As entropy decreases, order must increase. Thus the imported energy is used to create the spontaneous development of self-organized, emergent phenomena. This is how eons of Darwinian evolution and much shorter gestational times for fetal development create the stunning order of life.It is only when we die and stop importing energy that we obey the second law, with its inevitable decay into thermodynamic equilibrium when every chemical reaction goes equally in both directions, no thermal gradients exist, and all forces acting on us cancel so that movement is impossible. Life requires non-equilibrium thermodynamics.In the spontaneous development of order, Prigogine and Stengers (15) emphasized the importance of non-linear feedforward loops by which a molecule catalyzed itself. Linear systems are highly predictable. Life is not. Nonlinearity allows systems to explore new domains and what develops can only be predicted as probabilities, not certainties. Subsequently, Kauffman (9, 10) showed that in an ensemble of peptides, as the number of different peptides increases, the probability of one catalyzing the reaction between others to synthesize a new peptide becomes a virtual certainty. With further diversity of different peptides, the ratio of reactions to molecules increases until suddenly “a giant catalyzed reaction web forms” in which the original peptide reproduces itself spontaneously. Such autocatalytic sets have now been created in the laboratory (7).To further understand spontaneous self-organization it is instructive to examine a simple system, the formation of slime molds. The development of slime molds requires two emergent phenomena. The first is aggregation of previously independent amoebae into one large mass of densely packed cells. The second is the behavior of the aggregated mass as a single multi-celled organism. Here, I deal only with the first. Hopefully by understanding the simplest, we can describe features common to all emergent phenomena.Aggregation starts when amoebae are starved. One of them, at random, sends out a chemotactic signal. Those that are close aggregate around this individual and are induced to send out their own chemotactic substance, initiating a feedforward loop by increasing the chemotactic concentration, which acts at progressively greater distances to attract more and more amoebae from farther and farther away (15) until one large mass of aggregated amoebae form. How does this chemotactic agent work?Yanai et al. (23) measured intracellular pressure in starved amoebae, which are quasi-spherical, stable, and nonmotile. When food was put in the bath and a molecule came in contact with a hungry amoeba, the intracellular pressure abruptly rose without any change in the amoeba's shape. Then, over a small region of the cell membrane, a pseudopod extended and, as this occurred, the intracellular pressure fell.They suggested that the contact of a food molecule initiated a generalized polymerization of submembranous actin, increasing the amoeba's wall tension, its internal pressure, and its potential energy. Then, with a suitable delay, at the point of original contact, there was local depolymerization of actin with conversion of potential to kinetic energy, resulting in the pseudopod. Statistically, the contact of the amoeba with food probably occurred on the high side of the concentration gradient, so the pseudopod would extend toward more food particles and the process would repeat itself. Chemokinesis would become chemotaxis and the amoeba, by statistical probability and a quasi-random walk, would be drawn inexorably to the point of highest concentration where it would stay.A similar process presumably occurs with the aggregation of inflammatory cells in abscesses. Emergent phenomena not only characterize health but many diseases as well.Aggregation allows us to list the minimum requirements for emergent biologic phenomena. They are 1) an open thermodynamic system of ensembles; 2) a positive feedback loop causing non-linear dynamic behavior; 3) interconnections between component parts. Like all of life, amoebae are open thermodynamic systems that import energy and export entropy and aggregation involves a large number of them. The chemotactic agent secreted by one amoeba initiates the feedforward loop, inducing other amoebae to secrete more chemotactic agent. Chemotaxis supplies the interconnections required for aggregation. Although positive feedback is essential, all such loops must be controlled somehow, or else the system could run away with itself. In the case of slime molds and abscesses, dense packing of cells provides the control: they can not get any closer together. However, in most emergent phenomena, order is preserved by negative feedback loops that prevent the feedforward loops from reverberating throughout the system and changing it completely (9, 10).This brief sketch of the minimal requirements for emergence leads to a second important question. How much energy is needed to create order from disorder? There is a continuum of open thermodynamic systems from near-to-equilibrium to far-from-equilibrium systems. The former is characterized by crystals while the latter is characterized by weather. The amount of energy dissipated determines where a system is situated along the continuum. This is illustrated in the schematic shown in Fig. 1, which describes the continuum as a function of energy consumption. The ordinate describes another continuum from ordered through complex to chaotic systems. Crystals lie frozen and inadaptable deep within the ordered regimen. Deterministic chaos is found at the other extreme, characterized by weather-like instability and evanescence. Between crystals and weather a sudden phase transition occurs over a small range of energy consumption (5, 9, 10, 15). It is here that conditions necessary for life are found. We the living exist in a complex regimen in the phase transition between order and chaos. We are there because that is the only place we can be both ordered but adaptable, stable but able to evolve. Crystals are stable and ordered but cannot adapt or evolve. Weather evolves but is unstable and cannot survive. Darwinian selection allows both survival and evolution only in the phase transition. Survival requires adaptations, but it also requires that in adapting we must preserve our order by a mechanism we call homeostasis.Adaptability also results in continuous fluctuations of many homeostatically controlled physiological parameters (2, 8, 12, 13, 16, 17, 19, 21, 22). Homeostasis seems to be the wrong word for fluctuating systems. Instead, homeokinesis has been suggested (24) and tentatively defined as “the ability of an organism to utilize external energy sources to maintain a highly organized internal environment fluctuating within acceptable limits in a far from [thermodynamic] equilibrium state” (17).The narrow range of energy consumption over which the phase transition occurs suggests that global and local changes in metabolic rate might have profound consequences in both health and disease. This has been shown for individual cells in which the rheological behavior is in the phase transition between solids and liquid (4, 20). Fluidization of cells occurs when they are activated and their “effective” temperature increases. This has important consequences for their behavior (4). However, the thermodynamic consequences of increased metabolic rate during exercise in whole organisms is largely unexplored. In disease states when local metabolic rate is decreased, as in myocardial ischemia, heart rate fluctuations decrease often with serious consequences (12, 13). Conversely, in asthma, an inflammatory disease of the airways, the local increase in metabolic rate is associated with increased variability of respiratory impedance to flow (16, 17). As Kauffman (10) says “we are poised on the edge of chaos,” and disease states can take us into chaos or away from it depending on the energy dissipated. I believe we are on the threshold of a new theory of disease based on the consequences of living in a phase transition. Elements of such a theory have been published (1, 3, 6, 17, 20).Life and emergence obey the laws of physics and chemistry. But life has a third secret not mentioned by Schrodinger. The design of living organisms is not determined by physico-chemical laws (11, 14). As Polanyi (14) says, in a painting the physical and chemical properties of the paint determine what remains on the canvas, but the meaning of the painting is determined by the artist. Who is our artist? We sculpt ourselves; but our survival depends on Darwinian selection. Appropriate designs survive, inappropriate ones become extinct. Life is more than the properties of our paint. Understanding life requires knowledge of how the design of living creatures and emergent phenomena, appearing spontaneously in self-ordered, reproducing, interacting, energy-consuming, non-linear, dynamic ensembles makes us what we are. I believe this will be the next biological revolution. Fig. 1.Schematic illustrating the continuum of open thermodynamic systems from ordered, near-to-chaotic, far-from-equilibrium states. As energy consumption increases, systems move further from equilibrium and pass through a phase transition between order and deterministic chaos. Complex systems, like life, exist in this phase transition.Download figureDownload PowerPointFOOTNOTESThe costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked “advertisement” in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.REFERENCES1 Bates JHT, Davis GS, Majumdar A, Butnor KJ, Suki B. Linking parenchymal disease progression to changes in lung mechanical function by percolation. Am J Respir Crit Care Med 176: 617–623, 2007.Crossref | PubMed | ISI | Google Scholar2 Bruce E. Temporal variations in the pattern of breathing. J Appl Physiol 80: 1079–1087, 1996.Link | ISI | Google Scholar3 Costa M, Goldberger AL, Peng CK. Broken asymmetry of the human heartbeat: loss of time irreversibility in aging and disease. Phys Rev Lett 95: 198102, 2005.Crossref | PubMed | ISI | Google Scholar4 Fabry B, Maksym GN, Butler JP, Glogauer M, Navajas D, Taback NA, Millet EJ, Fredberg JJ. Time scale and other invariants of integrative mechanical behavior in living cells. Phys Rev E Stat Nonlin Soft Matter Phys 68: 041914, 2003.Crossref | PubMed | ISI | Google Scholar5 Fessler HE, Macklem PT. Percolation and phase transitions. Am J Respir Crit Care Med 176: 530–531, 2007.Crossref | ISI | Google Scholar6 Fredberg JJ. Lung impedance measurements are/are not more useful than simpler measurements of lung function in animal models of pulmonary disease. J Appl Physiol 103: 1909–1910, 2007.Link | ISI | Google Scholar7 Ghadiri MR, Granja JR, Milligan RA, McRee DE, Khazanovich N. Self-assembling organic nanotubes based on a cyclic peptide architecture. Nature 25: 324–327, 2007.Google Scholar8 Goldberger AL, Kobalter K, Bhargava V. 1/f-like scaling in normal neutrophil dynamics: implications for hematologic monitoring. IEEE Trans Biomed Eng 33: 874–878, 1986.Crossref | ISI | Google Scholar9 Kauffman S. Origins of Order. New York: Oxford University, 1993.Google Scholar10 Kauffman S. At Home in the Universe: The Search for Laws of Self-Organization and Complexity. New York: Oxford University Press, 1995.Google Scholar11 Kauffman S. Beyond reductionism. http://www.edge.org/3rd_culture/kauffman06/kauffman06_index.html.Google Scholar12 Kleiger RE, Muller JP, Bigger JT Jr, Moss AJ. Decreased heart rate variability and its association with increaser mortality after myocardial infarction. Am J Cardiol 59: 256–262, 1987.Crossref | PubMed | ISI | Google Scholar13 Kobayashi M, Krusha T. 1/f fluctuations of heartbeat period. IEEE Trans Biomed Eng 29: 456–457, 1982.Crossref | PubMed | ISI | Google Scholar14 Polanyi M. Life's irreducible structure. Science 160: 1308–1312, 1968.Crossref | PubMed | ISI | Google Scholar15 Prigogine I, Stengers I. Order Out of Chaos. New York: Bantam, 1984.Google Scholar16 Que C, Kenyon CM, Maksym G, Olivenstein R, Macklem PT. 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Nonlinear, chaotic dynamics of arterial blood pressure and renal blood flow. Am J Physiol Heart Circ Physiol 268: H621–H627, 1995.Link | ISI | Google Scholar23 Yanai M, Kenyon CM, Kelly SM, Macklem PT. Intracellular pressure in Amoeba proteus is a motive force for cell motion. Cell Motil Cytoskeleton 33: 22–29, 1996.Crossref | PubMed | ISI | Google Scholar24 Yates FE. Outline of a physical theory of physiological systems. Can J Physiol Pharmacol 60: 217–248, 1982.Crossref | ISI | Google ScholarAUTHOR NOTESAddress for reprint requests and other correspondence: P. T. Macklem, PO Box 250, Lansdowne ON Canada K0E 1L0 (e-mail: [email protected]) Download PDF Previous Back to Top Next FiguresReferencesRelatedInformationCited ByTemporal variations in the pattern of breathing: techniques, sources, and applications to translational sciences29 August 2022 | The Journal of Physiological Sciences, Vol. 72, No. 1Reactive Oxygen, Nitrogen, and Sulfur Species (RONSS) as a Metabolic Cluster for Signaling and Biostimulation of Plants: An Overview23 November 2022 | Plants, Vol. 11, No. 23Strong Emergence Arising from Weak EmergenceComplexity, Vol. 2022Systems Pharmacology: Enabling Multidimensional TherapeuticsUpdated Perspectives on the Role of Biomechanics in COPD: Considerations for the Clinician1 October 2022 | International Journal of Chronic Obstructive Pulmonary Disease, Vol. Volume 17Physiological complexity: influence of ageing, disease and neuromuscular fatigue on muscle force and torque fluctuations14 September 2021 | Experimental Physiology, Vol. 106, No. 10Physiological insight into the evolution of complex phenotypes: aerobic performance and the O2 transport pathway of vertebrates13 August 2021 | Journal of Experimental Biology, Vol. 224, No. 16Adaptive Capacities and Complexity of Heart Rate Variability in Patients With Chronic Obstructive Pulmonary Disease Throughout Pulmonary Rehabilitation28 July 2021 | Frontiers in Physiology, Vol. 12Inspiratory Efforts, Positive End-Expiratory Pressure, and External Resistances Influence Intraparenchymal Gas Redistribution in Mechanically Ventilated Injured Lungs9 February 2021 | Frontiers in Physiology, Vol. 11Outlook and Summary Remarks18 August 2021COPD Patients Have a Restricted Breathing Pattern That Persists with Increased Metabolic Demands17 April 2020 | COPD: Journal of Chronic Obstructive Pulmonary Disease, Vol. 17, No. 3Lung Function Variability in Children and Adolescents With and Without Asthma (LUV Study): Protocol for a Prospective, Nonrandomized, Clinical Trial7 August 2020 | JMIR Research Protocols, Vol. 9, No. 8Loss of adaptive capacity in asthmatic patients revealed by biomarker fluctuation dynamics after rhinovirus challenge5 November 2019 | eLife, Vol. 8Fostering Systems Thinking in Biological Education Using the Example of Plant Hormones21 October 2019 | BioEssays, Vol. 41, No. 11Refinements in the Organism as a Whole Rationale for Brain Death10 September 2019 | The Linacre Quarterly, Vol. 86, No. 4Relationship between muscle metabolic rate and muscle torque complexity during fatiguing intermittent isometric contractions in humans25 September 2019 | Physiological Reports, Vol. 7, No. 18Vagal contributions to fetal heart rate variability: an omics approach1 July 2019 | Physiological Measurement, Vol. 40, No. 6Health and Disease—Emergent States Resulting From Adaptive Social and Biological Network Interactions28 March 2019 | Frontiers in Medicine, Vol. 6Airway Transmural Pressures in an Airway Tree During Bronchoconstriction in Asthma13 February 2019 | Journal of Engineering and Science in Medical Diagnostics and Therapy, Vol. 2, No. 1A Puzzling Question: How Can Different Phenotypes Possibly Have Indistinguishable Disease Symptoms?17 May 2019Athletic Races Represent Complex Systems, and Pacing Behavior Should Be Viewed as an Emergent Phenomenon5 October 2018 | Frontiers in Physiology, Vol. 9From systems biology to P4 medicine: applications in respiratory medicine7 February 2018 | European Respiratory Review, Vol. 27, No. 147Epilogue2 February 2018Biomimicry, Biofabrication, and Biohybrid Systems: The Emergence and Evolution of Biological Design7 September 2017 | Advanced Healthcare Materials, Vol. 6, No. 20Review on biothermoydnamics applications: timeline, challenges, and opportunities26 January 2017 | International Journal of Energy Research, Vol. 41, No. 11Self-Assembly of Molecular Metal Oxide Nanoclusters9 August 2017Fluctuation Analysis of Peak Expiratory Flow and Its Association with Treatment Failure in AsthmaAmerican Journal of Respiratory and Critical Care Medicine, Vol. 195, No. 8Optogenetic skeletal muscle-powered adaptive biological machines14 March 2016 | Proceedings of the National Academy of Sciences, Vol. 113, No. 13A Biologically Inspired Approach to Collective Behaviors17 October 2015Crystals: animal, vegetable or mineral?6 August 2015 | Interface Focus, Vol. 5, No. 4What Long-Term Changes in Lung Function Can Tell Us About Asthma Control1 February 2015 | Current Allergy and Asthma Reports, Vol. 15, No. 3Fractal Structure and Entropy Production within the Central Nervous System12 August 2014 | Entropy, Vol. 16, No. 8Systems biology approach for subtyping asthma; 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Robbins1 June 2008 | Journal of Applied Physiology, Vol. 104, No. 6 More from this issue > Volume 104Issue 6June 2008Pages 1844-1846 Copyright & PermissionsCopyright © 2008 the American Physiological Societyhttps://doi.org/10.1152/japplphysiol.00942.2007PubMed18202170History Published online 1 June 2008 Published in print 1 June 2008 Metrics" @default.
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