269,710 research outputs found
Physical foundations of biological complexity
Biological systems reach hierarchical complexity that has no counterpart
outside the realm of biology. Undoubtedly, biological entities obey the
fundamental physical laws. Can today's physics provide an explanatory framework
for understanding the evolution of biological complexity? We argue here that
the physical foundation for understanding the origin and evolution of
complexity can be envisaged at the interface between the theory of frustrated
states resulting in pattern formation in glass-like media and the theory of
self-organized criticality (SOC). On the one hand, SOC has been shown to emerge
in spin glass systems of high dimensionality. On the other hand, SOC is often
viewed as the most appropriate physical description of evolutionary transitions
in biology. We unify these two faces of SOC by showing that emergence of
complex features in biological evolution typically if not always is triggered
by frustration that is caused by competing interactions at different
organizational levels. Competing interactions and frustrated states permeate
biology at all organizational levels and are tightly linked to the ubiquitous
competition for limiting resources. This perspective extends from the
comparatively simple phenomena occurring in glasses to large-scale events of
biological evolution, such as major evolutionary transitions. We therefore
submit that frustration caused by competing interactions in multidimensional
systems is the general driving force behind the emergence of complexity, within
and beyond the domain of biology.Comment: 27 pages, 2 figure
How do life, economy and other complex systems escape the heat death?
The primordial confrontation underlying the existence of our universe can be
conceived as the battle between entropy and complexity. The law of
ever-increasing entropy (Boltzmann H-theorem) evokes an irreversible,
one-directional evolution (or rather involution) going uniformly and
monotonically from birth to death. Since the 19th century, this concept is one
of the cornerstones and in the same time puzzles of statistical mechanics. On
the other hand, there is the empirical experience where one witnesses the
emergence, growth and diversification of new self-organized objects with
ever-increasing complexity. When modeling them in terms of simple discrete
elements one finds that the emergence of collective complex adaptive objects is
a rather generic phenomenon governed by a new type of laws. These 'emergence'
laws, not connected directly with the fundamental laws of the physical reality,
nor acting 'in addition' to them but acting through them were called by Phil
Anderson 'More is Different', 'das Maass' by Hegel etc. Even though the
'emergence laws' act through the intermediary of the fundamental laws that
govern the individual elementary agents, it turns out that different systems
apparently governed by very different fundamental laws: gravity, chemistry,
biology, economics, social psychology, end up often with similar emergence laws
and outcomes. In particular the emergence of adaptive collective objects endows
the system with a granular structure which in turn causes specific macroscopic
cycles of intermittent fluctuations.Comment: 42 pages, 18 figure
The Role of Philosophy as a Guide in Complex Scientific and Technological Processes
Probably the most challenging issue in science and advanced technology is the ever increasing complexity. The term complexity refers to the experience that the complex whole is more than the sum of the parts. Emergence of new properties is observed at all levels, from relatively simple physical systems up to high-end evolution in biology or state-of-the-art microprocessors in technology. In this study an effort is made to arrive at an understanding of the underlying ontological basis in terms of the classical philosophy of Aristotle and Aquinas. In addition, the value of philosophy is emphasized as a means to develop the capacity for intuition. Only with this capacity it is possible to acquire an understanding of the great variety of concepts needed in the multidisciplinary approach to complex systems
Categorical Ontology of Complex Systems, Meta-Systems and Theory of Levels: The Emergence of Life, Human Consciousness and Society
Single cell interactomics in simpler organisms, as well as somatic cell interactomics in multicellular organisms, involve biomolecular interactions in complex signalling pathways that were recently represented in modular terms by quantum automata with ‘reversible behavior’ representing normal cell cycling and division. Other implications of such quantum automata, modular modeling of signaling pathways and cell differentiation during development are in the fields of neural plasticity and brain development leading to quantum-weave dynamic patterns and specific molecular processes underlying extensive memory, learning, anticipation mechanisms and the emergence of human consciousness during the early brain development in children. Cell interactomics is here represented for the first time as a mixture of ‘classical’ states that determine molecular dynamics subject to Boltzmann statistics and ‘steady-state’, metabolic (multi-stable) manifolds, together with ‘configuration’ spaces of metastable quantum states emerging from complex quantum dynamics of interacting networks of biomolecules, such as proteins and nucleic acids that are now collectively defined as quantum interactomics. On the other hand, the time dependent evolution over several generations of cancer cells --that are generally known to undergo frequent and extensive genetic mutations and, indeed, suffer genomic transformations at the chromosome level (such as extensive chromosomal aberrations found in many colon cancers)-- cannot be correctly represented in the ‘standard’ terms of quantum automaton modules, as the normal somatic cells can. This significant difference at the cancer cell genomic level is therefore reflected in major changes in cancer cell interactomics often from one cancer cell ‘cycle’ to the next, and thus it requires substantial changes in the modeling strategies, mathematical tools and experimental designs aimed at understanding cancer mechanisms. Novel solutions to this important problem in carcinogenesis are proposed and experimental validation procedures are suggested. From a medical research and clinical standpoint, this approach has important consequences for addressing and preventing the development of cancer resistance to medical therapy in ongoing clinical trials involving stage III cancer patients, as well as improving the designs of future clinical trials for cancer treatments.\ud
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KEYWORDS: Emergence of Life and Human Consciousness;\ud
Proteomics; Artificial Intelligence; Complex Systems Dynamics; Quantum Automata models and Quantum Interactomics; quantum-weave dynamic patterns underlying human consciousness; specific molecular processes underlying extensive memory, learning, anticipation mechanisms and human consciousness; emergence of human consciousness during the early brain development in children; Cancer cell ‘cycling’; interacting networks of proteins and nucleic acids; genetic mutations and chromosomal aberrations in cancers, such as colon cancer; development of cancer resistance to therapy; ongoing clinical trials involving stage III cancer patients’ possible improvements of the designs for future clinical trials and cancer treatments. \ud
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Beyond multimorbidity:What can we learn from complexity science?
Multimorbidity - the occurrence of two or more long-term conditions in an individual - is a major global concern, placing a huge burden on healthcare systems, physicians, and patients. It challenges the current biomedical paradigm, in particular conventional evidence-based medicine's dominant focus on single-conditions. Patients' heterogeneous range of clinical presentations tend to escape characterization by traditional means of classification, and optimal management cannot be deduced from clinical practice guidelines. In this article, we argue that person-focused care based in complexity science may be a transformational lens through which to view multimorbidity, to complement the specialism focus on each particular disease. The approach offers an integrated and coherent perspective on the person's living environment, relationships, somatic, emotional and cognitive experiences and physiological function. The underlying principles include non-linearity, tipping points, emergence, importance of initial conditions, contextual factors and co-evolution, and the presence of patterned outcomes. From a clinical perspective, complexity science has important implications at the theoretical, practice and policy levels. Three essential questions emerge: (1) What matters to patients? (2) How can we integrate, personalize and prioritize care for whole people, given the constraints of their socio-ecological circumstances? (3) What needs to change at the practice and policy levels to deliver what matters to patients? These questions have no simple answers, but complexity science principles suggest a way to integrate understanding of biological, biographical and contextual factors, to guide an integrated approach to the care of people with multimorbidity
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