Introduction

What good is a worldview if it does not explain the events around us in a meaningful and internally consistent manner that helps us to understand and resolve the problems that we continually face? This work proposes a worldview that conceives of everything as a process of interacting systems acting on hierarchical, evolving levels. This process is theorized to be fundamental to the evolution of the Universe. Thus, the Universe is seen as being built out of layers of complex dynamic systems, each layer consisting of the ‘emergent properties’ that are generated from the complex interactions of the systems in the level below it.

The Universe is everything we know and think—and probably more. It definitely includes particles, forces, and energy. The subject matter of physics, chemistry and biology as well as the abstract notions of forces, ideas and information are all aspects of the Universe. A truly universal ‘law’ describing the Universe must apply to them all. This article discusses a process that seems to be universal and accounts for the development and evolution of all that was—and will be—‘new’ in our Universe.

Hopefully, most of the ideas expressed in this article are not new. They have already been developed, discussed and published in the scientific literature by others. The uniqueness of this article lies in the emphasis on the relationship of emergence and the iterative process with the fractal patterns observed throughout Nature, and proposes that this relationship underlies the evolution of the Universe.

Systems, networks, emergent phenomena, iteration and evolution

A. Single entities (E) interact to form complex interacting systems. New behavior traits emerge (emergent phenomena) from the dynamic interplay of the components of the system…

B. The newly emerged properties define the system. The original system may no longer be viewed as a system, but rather as a single new unique entity (E1).

C. A detailed description of the characteristics of this new entity (E1) is a description of the emergent properties that define it.

Al.Single entities (E1) interact to form complex interacting systems. New behavior traits emerge (emergent phenomena) from the dynamic interplay of the components of the system.

B1. The newly emerged properties define the system. The original system may no longer be viewed as a system, but rather as a single new unique entity (E2).

C1. A detailed description of the characteristics of this new entity (E2) is a description of the emergent properties that define it.

A2.Single entities (E2) interact to form complex, etc., etc., etc.

The process of smaller systems interacting to create new ‘emergent’ properties that define new entities—and then these entities forming complex networks out of which newer ‘emergent phenomena’ arise is hypothesized to be the process by which the Universe evolved. It is an iterative process. The critical concept is that all single entities can be viewed as complex systems composed of their component parts, and these parts may be seen as smaller systems themselves. Since all single entities are systems, the identifiable characteristics of any single entity are the emergent properties that arise out of the interactions of the ‘lesser systems’ that comprise it.

In summary, a single entity on one level can be viewed as being the ‘emergent properties’ of a complex dynamic system of smaller entities existing at a lower level. Looking forward, we can predict that as our current systems form modules and interact in complex dynamic ways, new ‘emergent phenomena’ will arise and we will evolve, we just cannot predict what these emergent properties will be.

Systems/Emergence Theory is best explained by example. A very brief description of the evolution of the Universe will be given touching on the beginning of the eras of physics, chemistry and biology.

Era of particle physics

Based on the Standard Theory of Particle Physics it is theorized that by one trillionth of a second after the Big Bang fundamental particles were already interacting with each other in dynamic systems to create the building blocks of the Universe.

As conceptualized today, there are two major classes of matter, hadrons and leptons. Hadrons and leptons are distinguished by their behavior characteristics. They interact through the four Forces via the exchange of energy quanta. These packets of energy are best conceived as agents of interaction. The forces and their carriers of interaction are listed below:

Strong Force (gluons), Weak Force (bosons), Electro-magnetic Force (photons) and Gravity (gravitons?).

Hadrons are particles that participate in all four known types of interactions—strong, weak, electro-magnetic and gravitational.

Leptons are particles that do not participate in strong interactions.

Charged leptons participate in 3 interactions— weak, electromagnetic and gravitational.

Neutral leptons participate in 2 interactions— weak and gravitational.

Leptons are considered to be fundamental particles.

Hadrons are composed of the fundamental particles called quarks and gluons. Combinations of the six different ‘flavors’ of quarks produce hadrons with different properties (protons, anti-protons, neutrons, pi-mesons, k-mesons etc.).

“The quarks inside a baryon or meson (types of hadrons) are continually interacting with one another via the strong force field. At any instant in time, they may contain many virtual particles: gluons and additional quark/anti-quark pairs. The picture of a proton as made of three quarks is thus a gross simplification. For example, we know from measurements that in a high momentum proton only about half the momentum is carried by quarks, the rest is carried by gluons” (www2.slac.stanford.edu).

Paraphrasing the above in systems/ emergence terminology: the six different flavors of quarks and gluons interact to form dynamic systems of interacting fundamental particles. These dynamic networks develop behavior characteristics that we recognize as the various types of hadrons—protons, anti-protons, neutrons, anti-neutrons etc. The emergent characteristics define and become the particles of the Universe.

As the Universe expanded and the temperature cooled, hadrons (protons) and leptons (electrons) formed systems that displayed the emergent properties that we recognize as hydrogen atoms. Under the influence of gravity, hydrogen atoms coalesced to form stars. Conditions were suitable in these stars for hydrogen atoms to interact with each other, and out of these interactions came new systems of fused nuclei with the emergent qualities of the heavier elements.

In short, out of the interacting systems of quarks and gluons emerged protons, from the interactions of protons and electrons emerged hydrogen atoms, and in thefurnaces of stars the hydrogen atoms formed systems displaying the emergent properties of the heavier atoms found in the Periodic Table of the Elements.

The process—of fundamental particles interacting to form systems from which new behavior characteristics emerged that in turn defined new entities—was an ongoing process from the very beginning.

Era of chemistry

Once the formation of atoms has occurred, it is easy to trace the formation of systems of atoms as they form molecules. Each individual molecule may be viewed as a system composed of its constituent atoms. And of course, the myriad molecules that are formed interact with each other to form still larger molecular networks. The molecular systems manifest emergent properties that possess the attributes of the physical Universe. Thus the elements and compounds that form the earth and stars are created. Needless to say, the underpinnings of the chemical systems are based on the micro-systems of subatomic particles.

Era of biology

A very special branch of chemical evolution involves the complex, adaptive dynamic systems that are formed from the chemistry of carbon, hydrogen, oxygen, nitrogen and other trace elements. At least at one site in the Universe C, H, O and N formed molecules that interacted with one another in a very special way. Some of the molecules that were products of chemical reactions in the network not only served as substrates for additional reactions, but they also served as catalysts for reactions that were involved in their original synthesis. In this manner reactions became ‘autocatalytic’ and the systems, when provided with sufficient substrates, developed the ability to grow and replicate. As these autocatalytic, self-replicating systems increased in number, size and complexity they developed emergent characteristics that we now associate with Life. Thus, out of ‘emergent chemistry’ came ‘evolutionary biology’.

Under the evolutionary pressures of a coevolving environment, the systems became increasingly complex. Molecular pathways within simple bacteria increased in complexity and altered the phenotypes of the cells in which the systems were found. Simple prokaryotes developed complex relationships and became eukaryotes. Single cell eukaryotes formed systems with the emergent properties of colonies (sponges). Complex systems built upon underlying complex systems and the process continued until multi-cellular plants and animals with specialized organs evolved.

Skipping forward, it appears that arguably the highest level of systems/emergent integration found in Nature is the intelligent self-awareness emerging out of the network of trillions of interacting neurons in the human brain. This process continues and the future will predictably take us to the next level.

The key point is that everything has evolved by the same process—component parts interact to form complex systems that display new characteristics as a result of their complex interactions. The new and possibly unique emergent properties define new entities. These new entities may form complex systems performing on the next ‘higher’ evolutionary level. An iteration of this process explains the evolution of the Universe from its earliest moments, when all that existed was energy and a few subatomic particles, to the present.

Evidence for iterative emergence

The proposed iterative process is conceptually possible, but is there any evidence that the Universe really is built out of layers of interacting networks? Certainly the emergence of new entities occurs (the reader is referred to the numerous publications on this subject, e.g., Zukav, 1979; Casti 1994; Kauffman, 1995, 2000; Johnson, 2001; Morowitz, 2002; Laughlin, 2005) but does a repetition of this process account for the construction of everything in the Universe? Evidence for this hypothesis may be indirect and somewhat soft but it is nevertheless intriguing. The iterative process of interacting networks creating new entities on the smallest scales of space and time to the largest may be reflected in the fractal patterns found throughout Nature involving different time and space scales. Somehow these fractal patterns reflect similar tendencies for self-organization found in networks of all sizes as theorized in complexity theory.

Complex systems as a science

Reviewing the essential lessons of the science of Complexity will be helpful. There are several key observations that may not be intuitively obvious.

  1. Multi-variable complex adaptive dynamic systems display similar behavior characteristics. These similarities exist even though the systems may be composed of different components. This observation implies that the interactions of the components possess an importance independent of the nature of the components. The study of these similarities is the study of complexity.

  2. At a threshold of energy and complexity, systems develop new behavior characteristics that we call ‘emergent phenomena’. The emergent traits may be totally unpredictable from what is known about the component parts. This observation is summarized in the phrase “The whole is more than the sum of its parts.”

  3. Emergent phenomena appear at phase transitions occurring at the interface of conditions of extreme stability and conditions of excessive instability. This interface has been colorfully named the ‘edge of chaos’. Mathematical models predict bifurcation patterns—or a doubling- of the possible semi-stable states that can occur at these phase transitions.

  4. These observations are seen in systems composed of atoms, or molecules, or cells, or animals, or neurons, or mixtures of any independent ‘nodes’ all interacting with each other.

  5. Complex adaptive systems exist in different size scales and interact in different time scales. This brings us to one last interesting concept—the concept of fractals.

The science of Physics is built on the use of mathematical concepts and equations that construct models of the Universe. The mathematical concept of ‘fractals’ serves as a model for the systems/emergence theory. Fractals are entities that exhibit similar, but not necessarily identical, traits when examined on different measurement scales. They are said to display self-similarity and be invariant under length scale transformation. The wooden Babushka dolls that open up to reveal similar dolls within may serve as a concrete analogy. If our Universe is really built from emergent traits springing forth from layers of complex interacting systems and since complex systems all possess similarities, then the concept of fractals may model the most fundamental creative process in the Universe.

Mathematical model for complex systems behavior and fractal geometry

Song, Havlin and Makse published a letter in Nature that is particularly relevant to the premise put forth in this paper. They describe a mathematical process by which several different naturally occurring complex systems are shown to display self-similarity or invariance under a length scale transformation. Their work provides mathematical support for the idea that the self-similar fractal patterns found in nature may be related to the processes of networks and emergence described previously.

Interested readers must read their article but the abstract is as follows:

Complex networks have been studied extensively owing to their relevance to many real systems such as the world-wide web, the Internet, energy landscapes and biological and social networks. A large number of real networks are referred to as ‘scale-free’ because they show a power-law distribution of the number of links per node. However, it is widely believed that complex networks are not invariant or self-similar under a length-scale transformation. This conclusion originates from the ‘small-world’ property of these networks, which implies that the number of nodes increases exponentially with the ‘diameter’ of the network, rather than the power-law relation expected for a selfsimilar structure. Here we analyze a variety of real complex networks and find that, on the contrary, they consist of self-repeating patterns on all length scales. This result is achieved by the application ofa renormalization procedure that coarse-grains the system into boxes containing nodes within a given ‘size’. We identify a power-law relation between the number of boxes needed to cover the network and the size of the box, defining a finite self-similar exponent. These fundamental properties help to explain the scale-free nature of complex networks and suggest a common self-organization dynamics (Song, et al., 2005: 392).

The renormalization procedure that they use in which large boxes are drawn around numerous interacting nodes that are then considered to be a single new node represents the natural phenomena of the creation of a new entity out of the emergent qualities of an underlying complex system. The next step in their renormalization procedure involves connecting the larger boxes with one another to create a new network. This step represents the process of new networks that form using the newly created larger entities. In both cases the resultant relationship patterns are self-similar and independent of length-time transformation. Fractal patterns, by definition, display self-similarity and are independent of lengthtime transformation.

Complex adaptive dynamic systems in biology

Manifestations of Complexity Theory may be found throughout biology. The biosphere itself is a large complex adaptive dynamic system composed of all the interacting elements that comprise it. There are many smaller networks participating in different time and space scales found within the biosphere. Fractal patterns amongst these networks are self-evident. Examples are found in the inter-relationships of species within the global animal kingdom, the relationships of individual animals interacting in a defined ecosystem, the relationship of the bacterial microflora of the human colon and, if our hypothesis is correct, the relationship of key molecules with each other found in the metabolic pathways of human molecular biology. Similarities in the interactions of the components of these complex adaptive systems reflect fundamental attributes of Emergence and self-organization of complex adaptive dynamic systems.

Applying Complexity Theory to the field of human Medicine promises to provide new insights that may increase our ability to understand complex disease processes. Biologic networks exist at different levels. Molecules and organelles are the components of cells, cells are the components of the major organs, and the major organs form a physiologic network with the emergent properties manifested at the biologic level of the intact animal (humans). And, of course, individual humans form sociologic networks.

Health can be viewed as a state where there is the proper ‘homeostatic’ balance of the myriad biochemical networks, cellular networks and large organ networks that comprise the human body. All the involved complex adaptive dynamic systems are properly functioning around their correct attractors.

Disease, on the other hand, can be conceptualized as occurring when there is some disruptive influence that deviates the networks away from their homeostatic attractors. The clinical manifestations of a disease would be the altered emergent traits generated at the different biological levels.

Infection with Hepatitis A Virus (HAV) serves as a good example. HAV is ingested, absorbed through the intestinal mucosa and travels via the blood to the liver where it adheres to and invades the liver cell (hepatocytes). The virus synthesizes molecules that reproduce itself and also subvert molecular pathways of the hepatocyte. Homeostasis of the hepato-cyte’s molecular systems is perturbed resulting in ‘disease’ at the molecular level resulting in the emergence of disease traits at the cellular level. The human immune system has evolved mechanisms to sense and respond to microbial pathogens. Pattern Recognition Receptors sense the presence of HAV molecules and alter the host cell’s genetic networks such that molecular signals (cytokines) are synthesized and sent to activate the Innate Immune System. The host’s immune system (organ) is activated to respond to the viral infection. The immune system is another complex adaptive dynamic system. Immune activation can be conceptualized as a perturbation from its normal ‘healthy’ state to one associated with disease. The manufacture of myriad pro-inflammatory cytokines produces effects on the body that are associated with disease, i.e., fever, muscle aches, fatigue etc.

Thinking in terms of Complexity Theory can provide insight and help us to understand diseases that are currently poorly understood. Crohn’s Disease (CD) is a good example. CD is an inflammatory disorder of the gastrointestinal system associated with dysregulated immunity. The etiology of CD is highly controversial. Perhaps the controversy stems as much from our current linear approach to thinking about disease causality as from anything else. Applying Complexity Theory to the way we think about the multiple factors known to be associated with CD may simplify the problem and resolve the controversy.

Linear logic about causality implies that A causes B causes C etc. and is represented in Figure 1.

Non-linear approaches are much more complex and include positive and negative feedback and feed-forward loops that incorporate multiple variables (see Figure 2). The Emergent characteristics of a ‘Complexity Causal N etwork’ (etiology) may produce several

Fig. 1: Current linear approach to causality

Fig. 2: Complexity theory: Causality due to interactions of multiple variables

potential outcomes that Complexity Theory regards as semi-stable states. Such an approach allows us to conceptualize and comprehend the interacting influences of many different variables. Minor variations in any given variable could potentially drastically alter the resultant (semi-stable state) outcome. Thus, an etiologic agent when introduced into the mix may result in a disease state in one instance but may not cause any changes if the conditions are slightly different.

Factors thought to be associated with CD include the following: 32 known gene polymorphisms, prior exposure to other microbes, age, smoking, immune deficiency, use of corticosteroids, infection with Adhesive Invasive E. coli, infection with Mycobacterium avium paratuberculosis, other infections, unknown environmental factors.

The insight gained from applying the principles of Complexity Theory to contemplating the etiology of CD (and other diseases) is that no single factor is the causative agent; there must be a critical blend of factors that result in the emergence of a disease that is labeled as Crohn’s Disease.

Hierarchical control networks

“Nothing makes sense in biology except in the light of evolution”. When thinking about the evolution of multi-cellular organisms such as Man it is apparent that a system must have also evolved that can coordinate and integrate all the different molecular, cellular and organ activities that occur during life. This control system must be complex, adaptive and dynamic. It must respond to changes in the internal and external environment to modify the organisms global response in order to survive. This system must be hierarchical in that it must coordinate activities at the local as well as the global level. Our known evolved hierarchical control systems are fundamentally molecular. The nervous system functions via molecular neurotransmitters, the endocrine system utilizes peptide and steroid hormones to modulate cellular activity throughout the body, and individual cells communicate on a local basis with an array of peptide, carbohydrate, lipid and other molecules that bind to specific receptors or directly modulate enzyme function.

Using the Complexity paradigm to think about the command and control mechanisms may allow early recognition of some exciting new research developments. Given that all evolution is essentially molecular evolution, it is intriguing to think about the family of steroid molecules as playing a key role in the evolution of an integrating and coordinating hierarchical control system that allowed the development of higher multi-cellular organisms. Since we have sequenced the human genome we know that 46 steroid receptors are encoded within our DNA. Since these receptors have been preserved they must be there for a reason. We only know what the ligands are for a small number of these receptors (androgens, estrogens, corticosteroids, mineral corticoids, Vitamin D and possibly some others). Thus the ligands and function of the majority of these steroid receptors are unknown. Changing an OH group from any one of the carbon atoms on the steroid molecule can alter the binding to a receptor—and elicit profound down-stream biologic effects. An example would be the one hydroxyl group that differentiates testosterone from estrogen—and we all recognize the biologic effects that occur. Most importantly, the addition of an OH group may take only one metabolic step. It is intriguing to think that a mutation in a receptor may find a possible ligand only one metabolic step (mutation) away that opens up potential new pathways for evolution to explore.

If this hypothesis is in fact true (and it is only a hypothesis), then steroid molecules may have played a fundamental role in evolution and the current endocrine, paracrine and autocrine activities of the naturally occurring steroids may be key to the integration of the different metabolic pathways in our bodies.

Assuming that this hypothesis is correct, then research and development of steroids may provide mechanisms to modulate our metabolic pathways in an advantageous manner. Such research is currently being performed by a California biotech company that has molecules in clinical trials. If successful, their endeavors may bring a sea-change to the field of Medicine. Already their research is showing promising activity in the areas of immunology, inflammation, cancer, ageing, diabetes and others. The impact on medical care may surpass that of the entire antibiotic era— which of course only addressed infectious agents.

Applicability

So, even if this theory on the evolution of the Universe is correct, what good is it for us? It does not change anything; things are what they are regardless of how they got there. How does it help? There are two immediate answers to these questions. First, we have always sought to understand what things are, how they came to be and why they are what they are. Perhaps Systems-Emergence Theory can help answer these questions. Secondly, employing the systems-emergence approach may be a practical method for resolving problems. Perceiving things as being constructed of layers of interacting systems may provide insight into problems that still confuse us. Confusion often arises because it is unclear on which ‘level’ a given variable is functioning. Insight may be achieved by realizing that ‘reality’ is constructed from layers of complex systems. The concept of modules and new entities are related.

Summary

Systems/emergence theory emphasizes the importance of networks of interacting entities out of which new properties (entities) emerge. This process is fundamental to the creation and evolution of all things in the Universe. It is consistent with current theories of physics, chemistry and biology.

Acceptance of systems/ emergence theory does not change a thing; things are what they are. But, an appreciation of the systems/ emergence perspective may provide insight into the World around us and help us to resolve paradoxes and problems that we continually encounter. Utilization of this paradigm may be particularly useful when contemplating the relationships of the many networks found in the pyramidal levels of biological systems. This model allows us to more easily integrate our knowledge of molecular phenomena with cellular, organ and global function. It also allows medical scientists and physicians to better conceptualize the dynamic interactive relationships of the multiple factors that are involved in complex disease processes. Phenotypes are simply ‘emergent traits’ of underlying genetic, biochemical and cellular networks. Disturbances in these networks by whatever mechanism at any level may disturb the homeostatic balance, alter the emergent characteristics, and manifest as disease.