http://www.tbiomed.com The most accessed research articles published by Theoretical Biology and Medical Modelling 2010-03-15T00:00:00Z This is an RSS newsfeed from BioMed Central It is intended to be used with an RSS reader. For more information about RSS newsfeeds from BioMed Central, visit http://www.biomedcentral.com/info/about/rss/ A full accounting of biological robustness remains elusive; both in terms of the mechanisms by which robustness is achieved and the forces that have caused robustness to grow over evolutionary time. Although its importance to topics such as ecosystem services and resilience is well recognized, the broader relationship between robustness and evolution is only starting to be fully appreciated. A renewed interest in this relationship has been prompted by evidence that mutational robustness can play a positive role in the discovery of adaptive innovations (evolvability) and evidence of an intimate relationship between robustness and complexity in biology.This paper offers a new perspective on the mechanics of evolution and the origins of complexity, robustness, and evolvability. Here we explore the hypothesis that degeneracy, a partial overlap in the functioning of multi-functional components, plays a central role in the evolution and robustness of complex forms. In support of this hypothesis, we present evidence that degeneracy is a fundamental source of robustness, it is intimately tied to multi-scaled complexity, and it establishes conditions that are necessary for system evolvability. http://www.tbiomed.com/content/7/1/6 James Whitacre Theoretical Biology and Medical Modelling 2010, 7:6 2010-02-18T00:00:00Z doi:10.1186/1742-4682-7-6 Theoretical Biology and Medical Modelling 1742-4682 7 6 2010-02-18T00:00:00Z XML Background: The order retroviridae comprises viruses based on ribonucleic acids (RNA). Some, such as HIV and HTLV, are human pathogens. Newly emerged human retroviruses have zoonotic origins. As far as has been established, both repeated infections (themselves possibly responsible for the evolution of viral mutations (Vm) and host adaptability (Ha)); along with interplay between inhibitors and promoters of cell tropism, are needed to effect retroviral cross-species transmissions. However, the exact modus operadi of intertwine between these factors at molecular level remains to be established. Knowledge of such intertwine could lead to a better understanding of retrovirology and possibly other infectious processes. This study was conducted to derive the mathematical equation of a general theory of the origins of retroviruses.Methods and resultsOn the basis of an arbitrarily non-Euclidian geometrical "thought experiment" involving the cross-species transmission of simian foamy virus (sfv) from a non-primate species Xy to Homo sapiens (Hs), initially excluding all social factors, the following was derived. At the port of exit from Xy (where the species barrier, SB, is defined by the Index of Origin, IO), sfv shedding is (1) enhanced by two transmitting tensors (Tt), (i) virus-specific immunity (VSI) and (ii) evolutionary defenses such as APOBEC, RNA interference pathways, and (when present) expedited therapeutics (denoted e2D); and (2) opposed by the five accepting scalars (At): (a) genomic integration hot spots, gIHS, (b) nuclear envelope transit (NMt) vectors, (c) virus-specific cellular biochemistry, VSCB, (d) virus-specific cellular receptor repertoire, VSCR, and (e) pH-mediated cell membrane transit, (↓pH CMat). Assuming As and Tt to be independent variables, IO = Tt/As. The same forces acting in an opposing manner determine SB at the port of sfv entry (defined here by the Index of Entry, IE = As/Tt). Overall, If sfv encounters no unforeseen effects on transit between Xy and Hs, then the square root of the combined index of sfv transmissibility (√|RTI|) is proportional to the product IO* IE (or ~Vm* Ha* ∑Tt*∑As*Ω), where Ω is the retrovirological constant and ∑ is a function of the ratio Tt/As or As/Tt for sfv transmission from Xy to Hs. Conclusions: I present a mathematical formalism encapsulating the general theory of the origins of retroviruses. It summarizes the choreography for the intertwined interplay of factors influencing the probability of retroviral cross-species transmission: Vm, Ha, Tt, As, and Ω. http://www.tbiomed.com/content/7/1/5 Misaki Wayengera Theoretical Biology and Medical Modelling 2010, 7:5 2010-02-16T00:00:00Z doi:10.1186/1742-4682-7-5 Theoretical Biology and Medical Modelling 1742-4682 7 5 2010-02-16T00:00:00Z XML Background and PurposeA model for carcinoma and sarcoma induction was used to study the dependence of carcinogenesis after radiotherapy on fractionation.Materials and methodsA cancer induction model for radiotherapy doses including fractionation was used to model carcinoma and sarcoma induction after a radiation treatment. For different fractionation schemes the dose response relationships were obtained. Tumor induction was studied as a function of dose per fraction. Results: If it is assumed that the tumor is treated up to the same biologically equivalent dose it was found that large dose fractions could decrease second cancer induction. The risk decreases approximately linear with increasing fraction size and is more pronounced for sarcoma induction. Carcinoma induction decreases by around 10% per 1 Gy increase in fraction dose. Sarcoma risk is decreased by about 15% per 1 Gy increase in fractionation. It is also found that tissue which is irradiated using large dose fractions to dose levels lower than 10% of the target dose potentially develop less sarcomas when compared to tissues irradiated to all dose levels. This is not observed for carcinoma induction. Conclusions: It was found that carcinoma as well as sarcoma risk decreases with increasing fractionation dose. The reduction of sarcoma risk is even more pronounced than carcinoma risk. Hypofractionation is potentially beneficial with regard to second cancer induction. http://www.tbiomed.com/content/7/1/4 Uwe Schneider Jurgen Besserer Andreas Mack Theoretical Biology and Medical Modelling 2010, 7:4 2010-02-11T00:00:00Z doi:10.1186/1742-4682-7-4 Theoretical Biology and Medical Modelling 1742-4682 7 4 2010-02-11T00:00:00Z XML Background: Most cancer cells, in contrast to normal differentiated cells, rely on aerobic glycolysis instead of oxidative phosphorylation to generate metabolic energy, a phenomenon called the Warburg effect.ModelQuantum metabolism is an analytic theory of metabolic regulation which exploits the methodology of quantum mechanics to derive allometric rules relating cellular metabolic rate and cell size. This theory explains differences in the metabolic rates of cells utilizing OxPhos and cells utilizing glycolysis. This article appeals to an analytic relation between metabolic rate and evolutionary entropy - a demographic measure of Darwinian fitness - to: (a) provide an evolutionary rationale for the Warburg effect, and (b) propose methods based on entropic principles of natural selection for regulating the incidence of OxPhos and glycolysis in cancer cells. Conclusion: The regulatory interventions proposed on the basis of quantum metabolism have applications in therapeutic strategies to combat cancer. These procedures, based on metabolic regulation, are non-invasive, and complement the standard therapeutic methods involving radiation and chemotherapy http://www.tbiomed.com/content/7/1/2 Lloyd Demetrius Johannes Coy Jack Tuszynski Theoretical Biology and Medical Modelling 2010, 7:2 2010-01-19T00:00:00Z doi:10.1186/1742-4682-7-2 Theoretical Biology and Medical Modelling 1742-4682 7 2 2010-01-19T00:00:00Z XML Background: Portal hypertension is a clinical syndrome that manifests as ascites, portosystemic encephalopathy and variceal hemorrhage, and these alterations often lead to death.HypothesisSplanchnic and/or systemic responses to portal hypertension could have pathophysiological mechanisms similar to those involved in the post-traumatic inflammatory response.The splanchnic and systemic impairments produced throughout the evolution of experimental prehepatic portal hypertension could be considered to have an inflammatory origin. In portal vein ligated rats, portal hypertensive enteropathy, hepatic steatosis and portal hypertensive encephalopathy show phenotypes during their development that can be considered inflammatory, such as: ischemia-reperfusion (vasodilatory response), infiltration by inflammatory cells (mast cells) and bacteria (intestinal translocation of endotoxins and bacteria) and lastly, angiogenesis. Similar inflammatory phenotypes, worsened by chronic liver disease (with anti-oxidant and anti-enzymatic ability reduction) characterize the evolution of portal hypertension and its complications (hepatorenal syndrome, ascites and esophageal variceal hemorrhage) in humans. Conclusion: Low-grade inflammation, related to prehepatic portal hypertension, switches to high-grade inflammation with the development of severe and life-threatening complications when associated with chronic liver disease. http://www.tbiomed.com/content/4/1/44 Maria-Angeles Aller Jorge-Luis Arias Arturo Cruz Jaime Arias Theoretical Biology and Medical Modelling 2007, 4:44 2007-11-13T00:00:00Z doi:10.1186/1742-4682-4-44 Theoretical Biology and Medical Modelling 1742-4682 4 44 2007-11-13T00:00:00Z XML Background: The robust storage, updating and utilization of information are necessary for the maintenance and perpetuation of dynamic systems. These systems can exist as constructs of metal-oxide semiconductors and silicon, as in a digital computer, or in the "wetware" of organic compounds, proteins and nucleic acids that make up biological organisms. We propose that there are essential functional properties of centralized information-processing systems; for digital computers these properties reside in the computer's hard drive, and for eukaryotic cells they are manifest in the DNA and associated structures. Methods: Presented herein is a descriptive framework that compares DNA and its associated proteins and sub-nuclear structure with the structure and function of the computer hard drive. We identify four essential properties of information for a centralized storage and processing system: (1) orthogonal uniqueness, (2) low level formatting, (3) high level formatting and (4) translation of stored to usable form. The corresponding aspects of the DNA complex and a computer hard drive are categorized using this classification. This is intended to demonstrate a functional equivalence between the components of the two systems, and thus the systems themselves. Results: Both the DNA complex and the computer hard drive contain components that fulfill the essential properties of a centralized information storage and processing system. The functional equivalence of these components provides insight into both the design process of engineered systems and the evolved solutions addressing similar system requirements. However, there are points where the comparison breaks down, particularly when there are externally imposed information-organizing structures on the computer hard drive. A specific example of this is the imposition of the File Allocation Table (FAT) during high level formatting of the computer hard drive and the subsequent loading of an operating system (OS). Biological systems do not have an external source for a map of their stored information or for an operational instruction set; rather, they must contain an organizational template conserved within their intra-nuclear architecture that "manipulates" the laws of chemistry and physics into a highly robust instruction set. We propose that the epigenetic structure of the intra-nuclear environment and the non-coding RNA may play the roles of a Biological File Allocation Table (BFAT) and biological operating system (Bio-OS) in eukaryotic cells. Conclusions: The comparison of functional and structural characteristics of the DNA complex and the computer hard drive leads to a new descriptive paradigm that identifies the DNA as a dynamic storage system of biological information. This system is embodied in an autonomous operating system that inductively follows organizational structures, data hierarchy and executable operations that are well understood in the computer science industry. Characterizing the "DNA hard drive" in this fashion can lead to insights arising from discrepancies in the descriptive framework, particularly with respect to positing the role of epigenetic processes in an information-processing context. Further expansions arising from this comparison include the view of cells as parallel computing machines and a new approach towards characterizing cellular control systems. http://www.tbiomed.com/content/7/1/3 David D'Onofrio Gary An Theoretical Biology and Medical Modelling 2010, 7:3 2010-01-21T00:00:00Z doi:10.1186/1742-4682-7-3 Theoretical Biology and Medical Modelling 1742-4682 7 3 2010-01-21T00:00:00Z XML Background: Signal transduction networks represent the information processing systems that dictate which dynamical regimes of biochemical activity can be accessible to a cell under certain circumstances. One of the major concerns in molecular systems biology is centered on the elucidation of the robustness properties and information processing capabilities of signal transduction networks. Achieving this goal requires the establishment of causal relations between the design principle of biochemical reaction systems and their emergent dynamical behaviors. Methods: In this study, efforts were focused in the construction of a relatively well informed, deterministic, non-linear dynamic model, accounting for reaction mechanisms grounded on standard mass action and Hill saturation kinetics, of the canonical reaction topology underlying Toll-like receptor 4 (TLR4)-mediated signaling events. This signaling mechanism has been shown to be deployed in macrophages during a relatively short time window in response to lypopolysaccharyde (LPS) stimulation, which leads to a rapidly mounted innate immune response. An extensive computational exploration of the biochemical reaction space inhabited by this signal transduction network was performed via local and global perturbation strategies. Importantly, a broad spectrum of biologically plausible dynamical regimes accessible to the network in widely scattered regions of parameter space was reconstructed computationally. Additionally, experimentally reported transcriptional readouts of target pro-inflammatory genes, which are actively modulated by the network in response to LPS stimulation, were also simulated. This was done with the main goal of carrying out an unbiased statistical assessment of the intrinsic robustness properties of this canonical reaction topology. Results: Our simulation results provide convincing numerical evidence supporting the idea that a canonical reaction mechanism of the TLR4 signaling network is capable of performing information processing in a robust manner, a functional property that is independent of the signaling task required to be executed. Nevertheless, it was found that the robust performance of the network is not solely determined by its design principle (topology), but this may be heavily dependent on the network's current position in biochemical reaction space. Ultimately, our results enabled us the identification of key rate limiting steps which most effectively control the performance of the system under diverse dynamical regimes. Conclusions: Overall, our in silico study suggests that biologically relevant and non-intuitive aspects on the general behavior of a complex biomolecular network can be elucidated only when taking into account a wide spectrum of dynamical regimes attainable by the system. Most importantly, this strategy provides the means for a suitable assessment of the inherent variational constraints imposed by the structure of the system when systematically probing its parameter space. http://www.tbiomed.com/content/7/1/7 Jayson Gutierrez Georges St Laurent Silvio Urcuqui-Inchima Theoretical Biology and Medical Modelling 2010, 7:7 2010-03-15T00:00:00Z doi:10.1186/1742-4682-7-7 Theoretical Biology and Medical Modelling 1742-4682 7 7 2010-03-15T00:00:00Z PDF Background: Regular, "moderate", physical exercise is an established non-pharmacological form of treatment for depressive disorders. Brain lateralization has a significant role in the progress of depression. External stimuli such as various stressors or exercise influence the higher functions of the brain (cognition and affect). These effects often do not follow a linear course. Therefore, nonlinear dynamics seem best suited for modeling many of the phenomena, and putative global pathways in the brain, attributable to such external influences.HypothesisThe general hypothesis presented here considers only the nonlinear aspects of the effects produced by "moderate" exercise and "chronic" stressors, but does not preclude the possibility of linear responses. In reality, both linear and nonlinear mechanisms may be involved in the final outcomes. The well-known neurotransmitters serotonin (5-HT), dopamine (D) and norepinephrine (NE) all have various receptor subtypes. The article hypothesizes that 'Stress' increases the activity/concentration of some particular subtypes of receptors (designated nts) for each of the known (and unknown) neurotransmitters in the right anterior (RA) and left posterior (LP) regions (cortical and subcortical) of the brain, and has the converse effects on a different set of receptor subtypes (designated nth). In contrast, 'Exercise' increases nth activity/concentration and/or reduces nts activity/concentration in the LA and RP areas of the brain. These effects may be initiated by the activation of Brain Derived Neurotrophic Factor (BDNF) (among others) in exercise and its suppression in stress. Conclusion: On the basis of this hypothesis, a better understanding of brain neurodynamics might be achieved by considering the oscillations caused by single neurotransmitters acting on their different receptor subtypes, and the temporal pattern of recruitment of these subtypes. Further, appropriately designed and planned experiments will not only corroborate such theoretical models, but also shed more light on the underlying brain dynamics. http://www.tbiomed.com/content/3/1/33 Suptendra Sarbadhikari Asit Saha Theoretical Biology and Medical Modelling 2006, 3:33 2006-09-23T00:00:00Z doi:10.1186/1742-4682-3-33 Theoretical Biology and Medical Modelling 1742-4682 3 33 2006-09-23T00:00:00Z XML Background: Modeling of molecular networks is necessary to understand their dynamical properties. While a wealth of information on molecular connectivity is available, there are still relatively few data regarding the precise stoichiometry and kinetics of the biochemical reactions underlying most molecular networks. This imbalance has limited the development of dynamical models of biological networks to a small number of well-characterized systems. To overcome this problem, we wanted to develop a methodology that would systematically create dynamical models of regulatory networks where the flow of information is known but the biochemical reactions are not. There are already diverse methodologies for modeling regulatory networks, but we aimed to create a method that could be completely standardized, i.e. independent of the network under study, so as to use it systematically. Results: We developed a set of equations that can be used to translate the graph of any regulatory network into a continuous dynamical system. Furthermore, it is also possible to locate its stable steady states. The method is based on the construction of two dynamical systems for a given network, one discrete and one continuous. The stable steady states of the discrete system can be found analytically, so they are used to locate the stable steady states of the continuous system numerically. To provide an example of the applicability of the method, we used it to model the regulatory network controlling T helper cell differentiation. Conclusion: The proposed equations have a form that permit any regulatory network to be translated into a continuous dynamical system, and also find its steady stable states. We showed that by applying the method to the T helper regulatory network it is possible to find its known states of activation, which correspond the molecular profiles observed in the precursor and effector cell types. http://www.tbiomed.com/content/3/1/13 Luis Mendoza Ioannis Xenarios Theoretical Biology and Medical Modelling 2006, 3:13 2006-03-16T00:00:00Z doi:10.1186/1742-4682-3-13 Theoretical Biology and Medical Modelling 1742-4682 3 13 2006-03-16T00:00:00Z XML Background: In many parts of the world, the exponential growth rate of infections during the initial epidemic phase has been used to make statistical inferences on the reproduction number, R, a summary measure of the transmission potential for the novel influenza A (H1N1) 2009. The growth rate at the initial stage of the epidemic in Japan led to estimates for R in the range 2.0 to 2.6, capturing the intensity of the initial outbreak among school-age children in May 2009. Methods: An updated estimate of R that takes into account the epidemic data from 29 May to 14 July is provided. An age-structured renewal process is employed to capture the age-dependent transmission dynamics, jointly estimating the reproduction number, the age-dependent susceptibility and the relative contribution of imported cases to secondary transmission. Pitfalls in estimating epidemic growth rates are identified and used for scrutinizing and re-assessing the results of our earlier estimate of R. Results: Maximum likelihood estimates of R using the data from 29 May to 14 July ranged from 1.21 to 1.35. The next-generation matrix, based on our age-structured model, predicts that only 17.5% of the population will experience infection by the end of the first pandemic wave. Our earlier estimate of R did not fully capture the population-wide epidemic in quantifying the next-generation matrix from the estimated growth rate during the initial stage of the pandemic in Japan. Conclusions: In order to quantify R from the growth rate of cases, it is essential that the selected model captures the underlying transmission dynamics embedded in the data. Exploring additional epidemiological information will be useful for assessing the temporal dynamics. Although the simple concept of R is more easily grasped by the general public than that of the next-generation matrix, the matrix incorporating detailed information (e.g., age-specificity) is essential for reducing the levels of uncertainty in predictions and for assisting public health policymaking. Model-based prediction and policymaking are best described by sharing fundamental notions of heterogeneous risks of infection and death with non-experts to avoid potential confusion and/or possible misuse of modelling results. http://www.tbiomed.com/content/7/1/1 Hiroshi Nishiura Gerardo Chowell Muntaser Safan Carlos Castillo-Chavez Theoretical Biology and Medical Modelling 2010, 7:1 2010-01-07T00:00:00Z doi:10.1186/1742-4682-7-1 Theoretical Biology and Medical Modelling 1742-4682 7 1 2010-01-07T00:00:00Z XML