High performance cellular level agent-based simulation with FLAME for the GPU.

PubMed

Richmond, Paul; Walker, Dawn; Coakley, Simon; Romano, Daniela

2010-05-01

Driven by the availability of experimental data and ability to simulate a biological scale which is of immediate interest, the cellular scale is fast emerging as an ideal candidate for middle-out modelling. As with 'bottom-up' simulation approaches, cellular level simulations demand a high degree of computational power, which in large-scale simulations can only be achieved through parallel computing. The flexible large-scale agent modelling environment (FLAME) is a template driven framework for agent-based modelling (ABM) on parallel architectures ideally suited to the simulation of cellular systems. It is available for both high performance computing clusters (www.flame.ac.uk) and GPU hardware (www.flamegpu.com) and uses a formal specification technique that acts as a universal modelling format. This not only creates an abstraction from the underlying hardware architectures, but avoids the steep learning curve associated with programming them. In benchmarking tests and simulations of advanced cellular systems, FLAME GPU has reported massive improvement in performance over more traditional ABM frameworks. This allows the time spent in the development and testing stages of modelling to be drastically reduced and creates the possibility of real-time visualisation for simple visual face-validation.

Exploration of cellular reaction systems.

PubMed

Kirkilionis, Markus

2010-01-01

We discuss and review different ways to map cellular components and their temporal interaction with other such components to different non-spatially explicit mathematical models. The essential choices made in the literature are between discrete and continuous state spaces, between rule and event-based state updates and between deterministic and stochastic series of such updates. The temporal modelling of cellular regulatory networks (dynamic network theory) is compared with static network approaches in two first introductory sections on general network modelling. We concentrate next on deterministic rate-based dynamic regulatory networks and their derivation. In the derivation, we include methods from multiscale analysis and also look at structured large particles, here called macromolecular machines. It is clear that mass-action systems and their derivatives, i.e. networks based on enzyme kinetics, play the most dominant role in the literature. The tools to analyse cellular reaction networks are without doubt most complete for mass-action systems. We devote a long section at the end of the review to make a comprehensive review of related tools and mathematical methods. The emphasis is to show how cellular reaction networks can be analysed with the help of different associated graphs and the dissection into modules, i.e. sub-networks.

Agent-based models of cellular systems.

PubMed

Cannata, Nicola; Corradini, Flavio; Merelli, Emanuela; Tesei, Luca

2013-01-01

Software agents are particularly suitable for engineering models and simulations of cellular systems. In a very natural and intuitive manner, individual software components are therein delegated to reproduce "in silico" the behavior of individual components of alive systems at a given level of resolution. Individuals' actions and interactions among individuals allow complex collective behavior to emerge. In this chapter we first introduce the readers to software agents and multi-agent systems, reviewing the evolution of agent-based modeling of biomolecular systems in the last decade. We then describe the main tools, platforms, and methodologies available for programming societies of agents, possibly profiting also of toolkits that do not require advanced programming skills.

Modeling integrated cellular machinery using hybrid Petri-Boolean networks.

PubMed

Berestovsky, Natalie; Zhou, Wanding; Nagrath, Deepak; Nakhleh, Luay

2013-01-01

The behavior and phenotypic changes of cells are governed by a cellular circuitry that represents a set of biochemical reactions. Based on biological functions, this circuitry is divided into three types of networks, each encoding for a major biological process: signal transduction, transcription regulation, and metabolism. This division has generally enabled taming computational complexity dealing with the entire system, allowed for using modeling techniques that are specific to each of the components, and achieved separation of the different time scales at which reactions in each of the three networks occur. Nonetheless, with this division comes loss of information and power needed to elucidate certain cellular phenomena. Within the cell, these three types of networks work in tandem, and each produces signals and/or substances that are used by the others to process information and operate normally. Therefore, computational techniques for modeling integrated cellular machinery are needed. In this work, we propose an integrated hybrid model (IHM) that combines Petri nets and Boolean networks to model integrated cellular networks. Coupled with a stochastic simulation mechanism, the model simulates the dynamics of the integrated network, and can be perturbed to generate testable hypotheses. Our model is qualitative and is mostly built upon knowledge from the literature and requires fine-tuning of very few parameters. We validated our model on two systems: the transcriptional regulation of glucose metabolism in human cells, and cellular osmoregulation in S. cerevisiae. The model produced results that are in very good agreement with experimental data, and produces valid hypotheses. The abstract nature of our model and the ease of its construction makes it a very good candidate for modeling integrated networks from qualitative data. The results it produces can guide the practitioner to zoom into components and interconnections and investigate them using such more detailed mathematical models.

Modeling Integrated Cellular Machinery Using Hybrid Petri-Boolean Networks

PubMed Central

Berestovsky, Natalie; Zhou, Wanding; Nagrath, Deepak; Nakhleh, Luay

2013-01-01

The behavior and phenotypic changes of cells are governed by a cellular circuitry that represents a set of biochemical reactions. Based on biological functions, this circuitry is divided into three types of networks, each encoding for a major biological process: signal transduction, transcription regulation, and metabolism. This division has generally enabled taming computational complexity dealing with the entire system, allowed for using modeling techniques that are specific to each of the components, and achieved separation of the different time scales at which reactions in each of the three networks occur. Nonetheless, with this division comes loss of information and power needed to elucidate certain cellular phenomena. Within the cell, these three types of networks work in tandem, and each produces signals and/or substances that are used by the others to process information and operate normally. Therefore, computational techniques for modeling integrated cellular machinery are needed. In this work, we propose an integrated hybrid model (IHM) that combines Petri nets and Boolean networks to model integrated cellular networks. Coupled with a stochastic simulation mechanism, the model simulates the dynamics of the integrated network, and can be perturbed to generate testable hypotheses. Our model is qualitative and is mostly built upon knowledge from the literature and requires fine-tuning of very few parameters. We validated our model on two systems: the transcriptional regulation of glucose metabolism in human cells, and cellular osmoregulation in S. cerevisiae. The model produced results that are in very good agreement with experimental data, and produces valid hypotheses. The abstract nature of our model and the ease of its construction makes it a very good candidate for modeling integrated networks from qualitative data. The results it produces can guide the practitioner to zoom into components and interconnections and investigate them using such more detailed mathematical models. PMID:24244124

The 3-dimensional cellular automata for HIV infection

NASA Astrophysics Data System (ADS)

Mo, Youbin; Ren, Bin; Yang, Wencao; Shuai, Jianwei

2014-04-01

The HIV infection dynamics is discussed in detail with a 3-dimensional cellular automata model in this paper. The model can reproduce the three-phase development, i.e., the acute period, the asymptotic period and the AIDS period, observed in the HIV-infected patients in a clinic. We show that the 3D HIV model performs a better robustness on the model parameters than the 2D cellular automata. Furthermore, we reveal that the occurrence of a perpetual source to successively generate infectious waves to spread to the whole system drives the model from the asymptotic state to the AIDS state.

Cellular Automata Simulation for Wealth Distribution

NASA Astrophysics Data System (ADS)

Lo, Shih-Ching

2009-08-01

Wealth distribution of a country is a complicate system. A model, which is based on the Epstein & Axtell's "Sugars cape" model, is presented in Netlogo. The model considers the income, age, working opportunity and salary as control variables. There are still other variables should be considered while an artificial society is established. In this study, a more complicate cellular automata model for wealth distribution model is proposed. The effects of social welfare, tax, economical investment and inheritance are considered and simulated. According to the cellular automata simulation for wealth distribution, we will have a deep insight of financial policy of the government.

HSP90 Inhibition and Cellular Stress Elicits Phenotypic Plasticity in Hematopoietic Differentiation

PubMed Central

Lawag, Abdalla A.; Napper, Jennifer M.; Hunter, Caroline A.; Bacon, Nickolas A.; Deskins, Seth; El-hamdani, Manaf; Govender, Sarah-Leigh; Koc, Emine C.

2017-01-01

Abstract Cancer cells exist in a state of Darwinian selection using mechanisms that produce changes in gene expression through genetic and epigenetic alteration to facilitate their survival. Cellular plasticity, or the ability to alter cellular phenotype, can assist in survival of premalignant cells as they progress to full malignancy by providing another mechanism of adaptation. The connection between cellular stress and the progression of cancer has been established, although the details of the mechanisms have yet to be fully elucidated. The molecular chaperone HSP90 is often upregulated in cancers as they progress, presumably to allow cancer cells to deal with misfolded proteins and cellular stress associated with transformation. The objective of this work is to test the hypothesis that inhibition of HSP90 results in increased cell plasticity in mammalian systems that can confer a greater adaptability to selective pressures. The approach used is a murine in vitro model system of hematopoietic differentiation that utilizes a murine hematopoietic stem cell line, erythroid myeloid lymphoid (EML) clone 1, during their maturation from stem cells to granulocytic progenitors. During the differentiation protocol, 80%–90% of the cells die when placed in medium where the major growth factor is granulocyte–macrophage-colony stimulating factor. Using this selection point model, EML cells exhibit increases in cellular plasticity when they are better able to adapt to this medium and survive. Increases in cellular plasticity were found to occur upon exposure to geldanamycin to inhibit HSP90, when subjected to various forms of cellular stress, or inhibition of histone acetylation. Furthermore, we provide evidence that the cellular plasticity associated with inhibition of HSP90 in this model involves epigenetic mechanisms and is dependent upon high levels of stem cell factor signaling. This work provides evidence for a role of HSP90 and cellular stress in inducing phenotypic plasticity in mammalian systems that has new implications for cellular stress in progression and evolution of cancer. PMID:28910138

HSP90 Inhibition and Cellular Stress Elicits Phenotypic Plasticity in Hematopoietic Differentiation.

PubMed

Lawag, Abdalla A; Napper, Jennifer M; Hunter, Caroline A; Bacon, Nickolas A; Deskins, Seth; El-Hamdani, Manaf; Govender, Sarah-Leigh; Koc, Emine C; Sollars, Vincent E

2017-10-01

Cancer cells exist in a state of Darwinian selection using mechanisms that produce changes in gene expression through genetic and epigenetic alteration to facilitate their survival. Cellular plasticity, or the ability to alter cellular phenotype, can assist in survival of premalignant cells as they progress to full malignancy by providing another mechanism of adaptation. The connection between cellular stress and the progression of cancer has been established, although the details of the mechanisms have yet to be fully elucidated. The molecular chaperone HSP90 is often upregulated in cancers as they progress, presumably to allow cancer cells to deal with misfolded proteins and cellular stress associated with transformation. The objective of this work is to test the hypothesis that inhibition of HSP90 results in increased cell plasticity in mammalian systems that can confer a greater adaptability to selective pressures. The approach used is a murine in vitro model system of hematopoietic differentiation that utilizes a murine hematopoietic stem cell line, erythroid myeloid lymphoid (EML) clone 1, during their maturation from stem cells to granulocytic progenitors. During the differentiation protocol, 80%-90% of the cells die when placed in medium where the major growth factor is granulocyte-macrophage-colony stimulating factor. Using this selection point model, EML cells exhibit increases in cellular plasticity when they are better able to adapt to this medium and survive. Increases in cellular plasticity were found to occur upon exposure to geldanamycin to inhibit HSP90, when subjected to various forms of cellular stress, or inhibition of histone acetylation. Furthermore, we provide evidence that the cellular plasticity associated with inhibition of HSP90 in this model involves epigenetic mechanisms and is dependent upon high levels of stem cell factor signaling. This work provides evidence for a role of HSP90 and cellular stress in inducing phenotypic plasticity in mammalian systems that has new implications for cellular stress in progression and evolution of cancer.

Model-based design of experiments for cellular processes.

PubMed

Chakrabarty, Ankush; Buzzard, Gregery T; Rundell, Ann E

2013-01-01

Model-based design of experiments (MBDOE) assists in the planning of highly effective and efficient experiments. Although the foundations of this field are well-established, the application of these techniques to understand cellular processes is a fertile and rapidly advancing area as the community seeks to understand ever more complex cellular processes and systems. This review discusses the MBDOE paradigm along with applications and challenges within the context of cellular processes and systems. It also provides a brief tutorial on Fisher information matrix (FIM)-based and Bayesian experiment design methods along with an overview of existing software packages and computational advances that support MBDOE application and adoption within the Systems Biology community. As cell-based products and biologics progress into the commercial sector, it is anticipated that MBDOE will become an essential practice for design, quality control, and production. Copyright © 2013 Wiley Periodicals, Inc.

Computational modeling of single‐cell mechanics and cytoskeletal mechanobiology

PubMed Central

Holmes, William R.; Lee, Peter Vee Sin

2017-01-01

Cellular cytoskeletal mechanics plays a major role in many aspects of human health from organ development to wound healing, tissue homeostasis and cancer metastasis. We summarize the state‐of‐the‐art techniques for mathematically modeling cellular stiffness and mechanics and the cytoskeletal components and factors that regulate them. We highlight key experiments that have assisted model parameterization and compare the advantages of different models that have been used to recapitulate these experiments. An overview of feed‐forward mechanisms from signaling to cytoskeleton remodeling is provided, followed by a discussion of the rapidly growing niche of encapsulating feedback mechanisms from cytoskeletal and cell mechanics to signaling. We discuss broad areas of advancement that could accelerate research and understanding of cellular mechanobiology. A precise understanding of the molecular mechanisms that affect cell and tissue mechanics and function will underpin innovations in medical device technologies of the future. WIREs Syst Biol Med 2018, 10:e1407. doi: 10.1002/wsbm.1407 This article is categorized under: 1Models of Systems Properties and Processes > Mechanistic Models2Physiology > Mammalian Physiology in Health and Disease3Models of Systems Properties and Processes > Cellular Models PMID:29195023

The statistical mechanics of complex signaling networks: nerve growth factor signaling

NASA Astrophysics Data System (ADS)

Brown, K. S.; Hill, C. C.; Calero, G. A.; Myers, C. R.; Lee, K. H.; Sethna, J. P.; Cerione, R. A.

2004-10-01

The inherent complexity of cellular signaling networks and their importance to a wide range of cellular functions necessitates the development of modeling methods that can be applied toward making predictions and highlighting the appropriate experiments to test our understanding of how these systems are designed and function. We use methods of statistical mechanics to extract useful predictions for complex cellular signaling networks. A key difficulty with signaling models is that, while significant effort is being made to experimentally measure the rate constants for individual steps in these networks, many of the parameters required to describe their behavior remain unknown or at best represent estimates. To establish the usefulness of our approach, we have applied our methods toward modeling the nerve growth factor (NGF)-induced differentiation of neuronal cells. In particular, we study the actions of NGF and mitogenic epidermal growth factor (EGF) in rat pheochromocytoma (PC12) cells. Through a network of intermediate signaling proteins, each of these growth factors stimulates extracellular regulated kinase (Erk) phosphorylation with distinct dynamical profiles. Using our modeling approach, we are able to predict the influence of specific signaling modules in determining the integrated cellular response to the two growth factors. Our methods also raise some interesting insights into the design and possible evolution of cellular systems, highlighting an inherent property of these systems that we call 'sloppiness.'

Three-dimensional cellular automata as a model of a seismic fault

NASA Astrophysics Data System (ADS)

Gálvez, G.; Muñoz, A.

2017-01-01

The Earth's crust is broken into a series of plates, whose borders are the seismic fault lines and it is where most of the earthquakes occur. This plating system can in principle be described by a set of nonlinear coupled equations describing the motion of the plates, its stresses, strains and other characteristics. Such a system of equations is very difficult to solve, and nonlinear parts leads to a chaotic behavior, which is not predictable. In 1989, Bak and Tang presented an earthquake model based on the sand pile cellular automata. The model though simple, provides similar results to those observed in actual earthquakes. In this work the cellular automata in three dimensions is proposed as a best model to approximate a seismic fault. It is noted that the three-dimensional model reproduces similar properties to those observed in real seismicity, especially, the Gutenberg-Richter law.

Cellular Responses to Mechanical Stress Selected Contribution: A Three-Dimensional Model for Assessment of in Vitro Toxicity in Balaena Mysticetus Renal Tissue

NASA Technical Reports Server (NTRS)

Goodwin, T. J.; Coate-Li, L.; Linnehan, R. M.; Hammond, T. G.

2000-01-01

This study established two- and three-dimensional renal proximal tubular cell cultures of the endangered species bowhead whale (Balaena mysticetus), developed SV40-transfected cultures, and cloned the 61-amino acid open reading frame for the metallothionein protein, the primary binding site for heavy metal contamination in mammals. Microgravity research, modulations in mechanical culture conditions (modeled microgravity), and shear stress have spawned innovative approaches to understanding the dynamics of cellular interactions, gene expression, and differentiation in several cellular systems. These investigations have led to the creation of ex vivo tissue models capable of serving as physiological research analogs for three-dimensional cellular interactions. These models are enabling studies in immune function, tissue modeling for basic research, and neoplasia. Three-dimensional cellular models emulate aspects of in vivo cellular architecture and physiology and may facilitate environmental toxicological studies aimed at elucidating biological functions and responses at the cellular level. Marine mammals occupy a significant ecological niche (72% of the Earth's surface is water) in terms of the potential for information on bioaccumulation and transport of terrestrial and marine environmental toxins in high-order vertebrates. Few ex vivo models of marine mammal physiology exist in vitro to accomplish the aforementioned studies. Techniques developed in this investigation, based on previous tissue modeling successes, may serve to facilitate similar research in other marine mammals.

Bioengineered humanized livers as better three-dimensional drug testing model system.

PubMed

Vishwakarma, Sandeep Kumar; Bardia, Avinash; Lakkireddy, Chandrakala; Nagarapu, Raju; Habeeb, Md Aejaz; Khan, Aleem Ahmed

2018-01-27

To develop appropriate humanized three-dimensional ex-vivo model system for drug testing. Bioengineered humanized livers were developed in this study using human hepatic stem cells repopulation within the acellularized liver scaffolds which mimics with the natural organ anatomy and physiology. Six cytochrome P-450 probes were used to enable efficient identification of drug metabolism in bioengineered humanized livers. The drug metabolism study in bioengineered livers was evaluated to identify the absorption, distribution, metabolism, excretion and toxicity responses. The bioengineered humanized livers showed cellular and molecular characteristics of human livers. The bioengineered liver showed three-dimensional natural architecture with intact vasculature and extra-cellular matrix. Human hepatic cells were engrafted similar to the human liver. Drug metabolism studies provided a suitable platform alternative to available ex-vivo and in vivo models for identifying cellular and molecular dynamics of pharmacological drugs. The present study paves a way towards the development of suitable humanized preclinical model systems for pharmacological testing. This approach may reduce the cost and time duration of preclinical drug testing and further overcomes on the anatomical and physiological variations in xenogeneic systems.

Optical scatter imaging of cellular and mitochondrial swelling in brain tissue models of stroke

NASA Astrophysics Data System (ADS)

Johnson, Lee James

2001-08-01

The severity of brain edema resulting from a stroke can determine a patient's survival and the extent of their recovery. Cellular swelling is the microscopic source of a significant part of brain edema. Mitochondrial swelling also appears to be a determining event in the death or survival of the cells that are injured during a stroke. Therapies for reducing brain edema are not effective in many cases and current treatments of stroke do not address mitochondrial swelling at all. This dissertation is motivated by the lack of a complete understanding of cellular swelling resulting from stroke and the lack of a good method to begin to study mitochondrial swelling resulting from stroke in living brain tissue. In this dissertation, a novel method of detecting mitochondrial and cellular swelling in living hippocampal slices is developed and validated. The system is used to obtain spatial and temporal information about cellular and mitochondrial swelling resulting from various models of stroke. The effect of changes in water content on light scatter and absorption are examined in two models of brain edema. The results of this study demonstrate that optical techniques can be used to detect changes in water content. Mie scatter theory, the theoretical basis of the dual- angle scatter ratio imaging system, is presented. Computer simulations based on Mie scatter theory are used to determine the optimal angles for imaging. A detailed account of the early systems is presented to explain the motivations for the system design, especially polarization, wavelength and light path. Mitochondrial sized latex particles are used to determine the system response to changes in scattering particle size and concentration. The dual-angle scatter ratio imaging system is used to distinguish between osmotic and excitotoxic models of stroke injury. Such distinction cannot be achieved using the current techniques to study cellular swelling in hippocampal slices. The change in the scatter ratio is then shown to correlate to mitochondrial swelling, as observed with electron microscopy. The system is finally used to study mitochondrial and cellular swelling. Evidence of the susceptibility of certain hippocampal regions, CA1 and the dentate gyrus, to exhibit mitochondrial swelling as the result of oxygen and glucose deprivation is presented. In addition, for the first time, the time course of mitochondrial swelling is seen. Finally, experiments with scatter imaging and measurement of nitric oxide with carbon fiber electrodes demonstrate a clear link between nitric oxide and cellular swelling. A potential mechanism of the action of nitric oxide is evaluated. Nitric oxide appears to act to cause cellular swelling without the release of glutamate. The use of targeted nitric oxide inhibitors may be useful for the reduction of edema.

Drosophila cellular immunity: a story of migration and adhesion.

PubMed

Fauvarque, Marie-Odile; Williams, Michael J

2011-05-01

Research during the past 15 years has led to significant breakthroughs, providing evidence of a high degree of similarity between insect and mammalian innate immune responses, both humoural and cellular, and highlighting Drosophila melanogaster as a model system for studying the evolution of innate immunity. In a manner similar to cells of the mammalian monocyte and macrophage lineage, Drosophila immunosurveillance cells (haemocytes) have a number of roles. For example, they respond to wound signals, are involved in wound healing and contribute to the coagulation response. Moreover, they participate in the phagocytosis and encapsulation of invading pathogens, are involved in the removal of apoptotic bodies and produce components of the extracellular matrix. There are several reasons for using the Drosophila cellular immune response as a model to understand cell signalling during adhesion and migration in vivo: many genes involved in the regulation of Drosophila haematopoiesis and cellular immunity have been maintained across taxonomic groups ranging from flies to humans, many aspects of Drosophila and mammalian innate immunity seem to be conserved, and Drosophila is a simplified and well-studied genetic model system. In the present Commentary, we will discuss what is known about cellular adhesion and migration in the Drosophila cellular immune response, during both embryonic and larval development, and where possible compare it with related mechanisms in vertebrates.

Modeling and Analysis of Hybrid Cellular/WLAN Systems with Integrated Service-Based Vertical Handoff Schemes

NASA Astrophysics Data System (ADS)

Xia, Weiwei; Shen, Lianfeng

We propose two vertical handoff schemes for cellular network and wireless local area network (WLAN) integration: integrated service-based handoff (ISH) and integrated service-based handoff with queue capabilities (ISHQ). Compared with existing handoff schemes in integrated cellular/WLAN networks, the proposed schemes consider a more comprehensive set of system characteristics such as different features of voice and data services, dynamic information about the admitted calls, user mobility and vertical handoffs in two directions. The code division multiple access (CDMA) cellular network and IEEE 802.11e WLAN are taken into account in the proposed schemes. We model the integrated networks by using multi-dimensional Markov chains and the major performance measures are derived for voice and data services. The important system parameters such as thresholds to prioritize handoff voice calls and queue sizes are optimized. Numerical results demonstrate that the proposed ISHQ scheme can maximize the utilization of overall bandwidth resources with the best quality of service (QoS) provisioning for voice and data services.

Systems cell biology

PubMed Central

Mast, Fred D.; Ratushny, Alexander V.

2014-01-01

Systems cell biology melds high-throughput experimentation with quantitative analysis and modeling to understand many critical processes that contribute to cellular organization and dynamics. Recently, there have been several advances in technology and in the application of modeling approaches that enable the exploration of the dynamic properties of cells. Merging technology and computation offers an opportunity to objectively address unsolved cellular mechanisms, and has revealed emergent properties and helped to gain a more comprehensive and fundamental understanding of cell biology. PMID:25225336

The transition between immune and disease states in a cellular automaton model of clonal immune response

NASA Astrophysics Data System (ADS)

Bezzi, Michele; Celada, Franco; Ruffo, Stefano; Seiden, Philip E.

1997-02-01

In this paper we extend the Celada-Seiden (CS) model of the humoral immune response to include infections virus and killer T cells (cellular response). The model represents molecules and cells with bitstrings. The response of the system to virus involves a competition between the ability of the virus to kill the host cells and the host's ability to eliminate the virus. We find two basins of attraction in the dynamics of this system, one is identified with disease and the other with the immune state. There is also an oscillating state that exists on the border of these two stable states. Fluctuations in the population of virus or antibody can end the oscillation and drive the system into one of the stable states. The introduction of mechanisms of cross-regulation between the two responses can bias the system towards one of them. We also study a mean field model, based on coupled maps, to investigate virus-like infections. This simple model reproduces the attractors for average populations observed in the cellular automaton. All the dynamical behavior connected to spatial extension is lost, as is the oscillating feature. Thus the mean field approximation introduced with coupled maps destroys oscillations.

From single cells to tissue architecture-a bottom-up approach to modelling the spatio-temporal organisation of complex multi-cellular systems.

PubMed

Galle, J; Hoffmann, M; Aust, G

2009-01-01

Collective phenomena in multi-cellular assemblies can be approached on different levels of complexity. Here, we discuss a number of mathematical models which consider the dynamics of each individual cell, so-called agent-based or individual-based models (IBMs). As a special feature, these models allow to account for intracellular decision processes which are triggered by biomechanical cell-cell or cell-matrix interactions. We discuss their impact on the growth and homeostasis of multi-cellular systems as simulated by lattice-free models. Our results demonstrate that cell polarisation subsequent to cell-cell contact formation can be a source of stability in epithelial monolayers. Stroma contact-dependent regulation of tumour cell proliferation and migration is shown to result in invasion dynamics in accordance with the migrating cancer stem cell hypothesis. However, we demonstrate that different regulation mechanisms can equally well comply with present experimental results. Thus, we suggest a panel of experimental studies for the in-depth validation of the model assumptions.

Cellular signaling identifiability analysis: a case study.

PubMed

Roper, Ryan T; Pia Saccomani, Maria; Vicini, Paolo

2010-05-21

Two primary purposes for mathematical modeling in cell biology are (1) simulation for making predictions of experimental outcomes and (2) parameter estimation for drawing inferences from experimental data about unobserved aspects of biological systems. While the former purpose has become common in the biological sciences, the latter is less common, particularly when studying cellular and subcellular phenomena such as signaling-the focus of the current study. Data are difficult to obtain at this level. Therefore, even models of only modest complexity can contain parameters for which the available data are insufficient for estimation. In the present study, we use a set of published cellular signaling models to address issues related to global parameter identifiability. That is, we address the following question: assuming known time courses for some model variables, which parameters is it theoretically impossible to estimate, even with continuous, noise-free data? Following an introduction to this problem and its relevance, we perform a full identifiability analysis on a set of cellular signaling models using DAISY (Differential Algebra for the Identifiability of SYstems). We use our analysis to bring to light important issues related to parameter identifiability in ordinary differential equation (ODE) models. We contend that this is, as of yet, an under-appreciated issue in biological modeling and, more particularly, cell biology. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Drosophila as a genetic and cellular model for studies on axonal growth

PubMed Central

Sánchez-Soriano, Natalia; Tear, Guy; Whitington, Paul; Prokop, Andreas

2007-01-01

One of the most fascinating processes during nervous system development is the establishment of stereotypic neuronal networks. An essential step in this process is the outgrowth and precise navigation (pathfinding) of axons and dendrites towards their synaptic partner cells. This phenomenon was first described more than a century ago and, over the past decades, increasing insights have been gained into the cellular and molecular mechanisms regulating neuronal growth and navigation. Progress in this area has been greatly assisted by the use of simple and genetically tractable invertebrate model systems, such as the fruit fly Drosophila melanogaster. This review is dedicated to Drosophila as a genetic and cellular model to study axonal growth and demonstrates how it can and has been used for this research. We describe the various cellular systems of Drosophila used for such studies, insights into axonal growth cones and their cytoskeletal dynamics, and summarise identified molecular signalling pathways required for growth cone navigation, with particular focus on pathfinding decisions in the ventral nerve cord of Drosophila embryos. These Drosophila-specific aspects are viewed in the general context of our current knowledge about neuronal growth. PMID:17475018

Systems cell biology.

PubMed

Mast, Fred D; Ratushny, Alexander V; Aitchison, John D

2014-09-15

Systems cell biology melds high-throughput experimentation with quantitative analysis and modeling to understand many critical processes that contribute to cellular organization and dynamics. Recently, there have been several advances in technology and in the application of modeling approaches that enable the exploration of the dynamic properties of cells. Merging technology and computation offers an opportunity to objectively address unsolved cellular mechanisms, and has revealed emergent properties and helped to gain a more comprehensive and fundamental understanding of cell biology. © 2014 Mast et al.

Towards a virtual lung: multi-scale, multi-physics modelling of the pulmonary system.

PubMed

Burrowes, K S; Swan, A J; Warren, N J; Tawhai, M H

2008-09-28

The essential function of the lung, gas exchange, is dependent on adequate matching of ventilation and perfusion, where air and blood are delivered through complex branching systems exposed to regionally varying transpulmonary and transmural pressures. Structure and function in the lung are intimately related, yet computational models in pulmonary physiology usually simplify or neglect structure. The geometries of the airway and vascular systems and their interaction with parenchymal tissue have an important bearing on regional distributions of air and blood, and therefore on whole lung gas exchange, but this has not yet been addressed by modelling studies. Models for gas exchange have typically incorporated considerable detail at the level of chemical reactions, with little thought for the influence of structure. To date, relatively little attention has been paid to modelling at the cellular or subcellular level in the lung, or to linking information from the protein structure/interaction and cellular levels to the operation of the whole lung. We review previous work in developing anatomically based models of the lung, airways, parenchyma and pulmonary vasculature, and some functional studies in which these models have been used. Models for gas exchange at several spatial scales are briefly reviewed, and the challenges and benefits from modelling cellular function in the lung are discussed.

Controlled cellular energy conversion in brown adipose tissue thermogenesis

NASA Technical Reports Server (NTRS)

Horowitz, J. M.; Plant, R. E.

1978-01-01

Brown adipose tissue serves as a model system for nonshivering thermogenesis (NST) since a) it has as a primary physiological function the conversion of chemical energy to heat; and b) preliminary data from other tissues involved in NST (e.g., muscle) indicate that parallel mechanisms may be involved. Now that biochemical pathways have been proposed for brown fat thermogenesis, cellular models consistent with a thermodynamic representation can be formulated. Stated concisely, the thermogenic mechanism in a brown fat cell can be considered as an energy converter involving a sequence of cellular events controlled by signals over the autonomic nervous system. A thermodynamic description for NST is developed in terms of a nonisothermal system under steady-state conditions using network thermodynamics. Pathways simulated include mitochondrial ATP synthesis, a Na+/K+ membrane pump, and ionic diffusion through the adipocyte membrane.

Multi-scale continuum modeling of biological processes: from molecular electro-diffusion to sub-cellular signaling transduction

NASA Astrophysics Data System (ADS)

Cheng, Y.; Kekenes-Huskey, P.; Hake, J. E.; Holst, M. J.; McCammon, J. A.; Michailova, A. P.

2012-01-01

This paper presents a brief review of multi-scale modeling at the molecular to cellular scale, with new results for heart muscle cells. A finite element-based simulation package (SMOL) was used to investigate the signaling transduction at molecular and sub-cellular scales (http://mccammon.ucsd.edu/smol/, http://FETK.org) by numerical solution of the time-dependent Smoluchowski equations and a reaction-diffusion system. At the molecular scale, SMOL has yielded experimentally validated estimates of the diffusion-limited association rates for the binding of acetylcholine to mouse acetylcholinesterase using crystallographic structural data. The predicted rate constants exhibit increasingly delayed steady-state times, with increasing ionic strength, and demonstrate the role of an enzyme's electrostatic potential in influencing ligand binding. At the sub-cellular scale, an extension of SMOL solves a nonlinear, reaction-diffusion system describing Ca2+ ligand buffering and diffusion in experimentally derived rodent ventricular myocyte geometries. Results reveal the important role of mobile and stationary Ca2+ buffers, including Ca2+ indicator dye. We found that alterations in Ca2+-binding and dissociation rates of troponin C (TnC) and total TnC concentration modulate sub-cellular Ca2+ signals. The model predicts that reduced off-rate in the whole troponin complex (TnC, TnI, TnT) versus reconstructed thin filaments (Tn, Tm, actin) alters cytosolic Ca2+ dynamics under control conditions or in disease-linked TnC mutations. The ultimate goal of these studies is to develop scalable methods and theories for the integration of molecular-scale information into simulations of cellular-scale systems.

Selected contribution: a three-dimensional model for assessment of in vitro toxicity in balaena mysticetus renal tissue

NASA Technical Reports Server (NTRS)

Goodwin, T. J.; Coate-Li, L.; Linnehan, R. M.; Hammond, T. G.

2000-01-01

This study established two- and three-dimensional renal proximal tubular cell cultures of the endangered species bowhead whale (Balaena mysticetus), developed SV40-transfected cultures, and cloned the 61-amino acid open reading frame for the metallothionein protein, the primary binding site for heavy metal contamination in mammals. Microgravity research, modulations in mechanical culture conditions (modeled microgravity), and shear stress have spawned innovative approaches to understanding the dynamics of cellular interactions, gene expression, and differentiation in several cellular systems. These investigations have led to the creation of ex vivo tissue models capable of serving as physiological research analogs for three-dimensional cellular interactions. These models are enabling studies in immune function, tissue modeling for basic research, and neoplasia. Three-dimensional cellular models emulate aspects of in vivo cellular architecture and physiology and may facilitate environmental toxicological studies aimed at elucidating biological functions and responses at the cellular level. Marine mammals occupy a significant ecological niche (72% of the Earth's surface is water) in terms of the potential for information on bioaccumulation and transport of terrestrial and marine environmental toxins in high-order vertebrates. Few ex vivo models of marine mammal physiology exist in vitro to accomplish the aforementioned studies. Techniques developed in this investigation, based on previous tissue modeling successes, may serve to facilitate similar research in other marine mammals.

Genome Scale Modeling in Systems Biology: Algorithms and Resources

PubMed Central

Najafi, Ali; Bidkhori, Gholamreza; Bozorgmehr, Joseph H.; Koch, Ina; Masoudi-Nejad, Ali

2014-01-01

In recent years, in silico studies and trial simulations have complemented experimental procedures. A model is a description of a system, and a system is any collection of interrelated objects; an object, moreover, is some elemental unit upon which observations can be made but whose internal structure either does not exist or is ignored. Therefore, any network analysis approach is critical for successful quantitative modeling of biological systems. This review highlights some of most popular and important modeling algorithms, tools, and emerging standards for representing, simulating and analyzing cellular networks in five sections. Also, we try to show these concepts by means of simple example and proper images and graphs. Overall, systems biology aims for a holistic description and understanding of biological processes by an integration of analytical experimental approaches along with synthetic computational models. In fact, biological networks have been developed as a platform for integrating information from high to low-throughput experiments for the analysis of biological systems. We provide an overview of all processes used in modeling and simulating biological networks in such a way that they can become easily understandable for researchers with both biological and mathematical backgrounds. Consequently, given the complexity of generated experimental data and cellular networks, it is no surprise that researchers have turned to computer simulation and the development of more theory-based approaches to augment and assist in the development of a fully quantitative understanding of cellular dynamics. PMID:24822031

Transparent metal model study of the use of a cellular growth front to form aligned monotectic composite materials

NASA Technical Reports Server (NTRS)

Kaukler, William F.

1988-01-01

The purpose of this work was to resolve a scientific controversy in the understanding of how second phase particles become aligned during unidirectional growth of a monotectic alloy. A second aspect was to make the first systematic observations of the solidification behavior of a monotectic alloy during cellular growth in-situ. This research provides the first systematic transparent model study of cellular solidification. An interface stability diagram was developed for the planar to cellular transition of the succinonitrile glycerol (SNG) system. A method was developed utilizing Fourier Transform Infrared Spectroscopy which allows quantitative compositional analysis of directionally solidified SNG along the growth axis. To determine the influence of cellular growth front on alignment for directionally solidified monotectic alloys, the planar and cellular growth morphology was observed in-situ for SNG between 8 and 17 percent glycerol and for a range of over two orders of magnitude G/R.

Genomic signal processing: from matrix algebra to genetic networks.

PubMed

Alter, Orly

2007-01-01

DNA microarrays make it possible, for the first time, to record the complete genomic signals that guide the progression of cellular processes. Future discovery in biology and medicine will come from the mathematical modeling of these data, which hold the key to fundamental understanding of life on the molecular level, as well as answers to questions regarding diagnosis, treatment, and drug development. This chapter reviews the first data-driven models that were created from these genome-scale data, through adaptations and generalizations of mathematical frameworks from matrix algebra that have proven successful in describing the physical world, in such diverse areas as mechanics and perception: the singular value decomposition model, the generalized singular value decomposition model comparative model, and the pseudoinverse projection integrative model. These models provide mathematical descriptions of the genetic networks that generate and sense the measured data, where the mathematical variables and operations represent biological reality. The variables, patterns uncovered in the data, correlate with activities of cellular elements such as regulators or transcription factors that drive the measured signals and cellular states where these elements are active. The operations, such as data reconstruction, rotation, and classification in subspaces of selected patterns, simulate experimental observation of only the cellular programs that these patterns represent. These models are illustrated in the analyses of RNA expression data from yeast and human during their cell cycle programs and DNA-binding data from yeast cell cycle transcription factors and replication initiation proteins. Two alternative pictures of RNA expression oscillations during the cell cycle that emerge from these analyses, which parallel well-known designs of physical oscillators, convey the capacity of the models to elucidate the design principles of cellular systems, as well as guide the design of synthetic ones. In these analyses, the power of the models to predict previously unknown biological principles is demonstrated with a prediction of a novel mechanism of regulation that correlates DNA replication initiation with cell cycle-regulated RNA transcription in yeast. These models may become the foundation of a future in which biological systems are modeled as physical systems are today.

CELLULAR, BIOCHEMICAL, AND MOLECULAR TECHNIQUES IN DEVELOPMENTAL TOXICOLOGY

EPA Science Inventory

Cellular, molecular and biochemical approaches vastly expand the possibilities for revealing the underlying mechanisms of developmental toxicity. The increasing interest in embryonic development as a model system for the study of gene expression has resulted in a cornucopia of i...

Systems biology of cellular membranes: a convergence with biophysics.

PubMed

Chabanon, Morgan; Stachowiak, Jeanne C; Rangamani, Padmini

2017-09-01

Systems biology and systems medicine have played an important role in the last two decades in shaping our understanding of biological processes. While systems biology is synonymous with network maps and '-omics' approaches, it is not often associated with mechanical processes. Here, we make the case for considering the mechanical and geometrical aspects of biological membranes as a key step in pushing the frontiers of systems biology of cellular membranes forward. We begin by introducing the basic components of cellular membranes, and highlight their dynamical aspects. We then survey the functions of the plasma membrane and the endomembrane system in signaling, and discuss the role and origin of membrane curvature in these diverse cellular processes. We further give an overview of the experimental and modeling approaches to study membrane phenomena. We close with a perspective on the converging futures of systems biology and membrane biophysics, invoking the need to include physical variables such as location and geometry in the study of cellular membranes. WIREs Syst Biol Med 2017, 9:e1386. doi: 10.1002/wsbm.1386 For further resources related to this article, please visit the WIREs website. © 2017 Wiley Periodicals, Inc.

A quantitative image cytometry technique for time series or population analyses of signaling networks.

PubMed

Ozaki, Yu-ichi; Uda, Shinsuke; Saito, Takeshi H; Chung, Jaehoon; Kubota, Hiroyuki; Kuroda, Shinya

2010-04-01

Modeling of cellular functions on the basis of experimental observation is increasingly common in the field of cellular signaling. However, such modeling requires a large amount of quantitative data of signaling events with high spatio-temporal resolution. A novel technique which allows us to obtain such data is needed for systems biology of cellular signaling. We developed a fully automatable assay technique, termed quantitative image cytometry (QIC), which integrates a quantitative immunostaining technique and a high precision image-processing algorithm for cell identification. With the aid of an automated sample preparation system, this device can quantify protein expression, phosphorylation and localization with subcellular resolution at one-minute intervals. The signaling activities quantified by the assay system showed good correlation with, as well as comparable reproducibility to, western blot analysis. Taking advantage of the high spatio-temporal resolution, we investigated the signaling dynamics of the ERK pathway in PC12 cells. The QIC technique appears as a highly quantitative and versatile technique, which can be a convenient replacement for the most conventional techniques including western blot, flow cytometry and live cell imaging. Thus, the QIC technique can be a powerful tool for investigating the systems biology of cellular signaling.

Ciona intestinalis notochord as a new model to investigate the cellular and molecular mechanisms of tubulogenesis.

PubMed

Denker, Elsa; Jiang, Di

2012-05-01

Biological tubes are a prevalent structural design across living organisms. They provide essential functions during the development and adult life of an organism. Increasing progress has been made recently in delineating the cellular and molecular mechanisms underlying tubulogenesis. This review aims to introduce ascidian notochord morphogenesis as an interesting model system to study the cell biology of tube formation, to a wider cell and developmental biology community. We present fundamental morphological and cellular events involved in notochord morphogenesis, compare and contrast them with other more established tubulogenesis model systems, and point out some unique features, including bipolarity of the notochord cells, and using cell shape changes and cell rearrangement to connect lumens. We highlight some initial findings in the molecular mechanisms of notochord morphogenesis. Based on these findings, we present intriguing problems and put forth hypotheses that can be addressed in future studies. Copyright © 2012 Elsevier Ltd. All rights reserved.

Balancing Uplink and Downlink under Asymmetric Traffic Environments Using Distributed Receive Antennas

NASA Astrophysics Data System (ADS)

Sohn, Illsoo; Lee, Byong Ok; Lee, Kwang Bok

Recently, multimedia services are increasing with the widespread use of various wireless applications such as web browsers, real-time video, and interactive games, which results in traffic asymmetry between the uplink and downlink. Hence, time division duplex (TDD) systems which provide advantages in efficient bandwidth utilization under asymmetric traffic environments have become one of the most important issues in future mobile cellular systems. It is known that two types of intercell interference, referred to as crossed-slot interference, additionally arise in TDD systems; the performances of the uplink and downlink transmissions are degraded by BS-to-BS crossed-slot interference and MS-to-MS crossed-slot interference, respectively. The resulting performance unbalance between the uplink and downlink makes network deployment severely inefficient. Previous works have proposed intelligent time slot allocation algorithms to mitigate the crossed-slot interference problem. However, they require centralized control, which causes large signaling overhead in the network. In this paper, we propose to change the shape of the cellular structure itself. The conventional cellular structure is easily transformed into the proposed cellular structure with distributed receive antennas (DRAs). We set up statistical Markov chain traffic model and analyze the bit error performances of the conventional cellular structure and proposed cellular structure under asymmetric traffic environments. Numerical results show that the uplink and downlink performances of the proposed cellular structure become balanced with the proper number of DRAs and thus the proposed cellular structure is notably cost-effective in network deployment compared to the conventional cellular structure. As a result, extending the conventional cellular structure into the proposed cellular structure with DRAs is a remarkably cost-effective solution to support asymmetric traffic environments in future mobile cellular systems.

Point process models for localization and interdependence of punctate cellular structures.

PubMed

Li, Ying; Majarian, Timothy D; Naik, Armaghan W; Johnson, Gregory R; Murphy, Robert F

2016-07-01

Accurate representations of cellular organization for multiple eukaryotic cell types are required for creating predictive models of dynamic cellular function. To this end, we have previously developed the CellOrganizer platform, an open source system for generative modeling of cellular components from microscopy images. CellOrganizer models capture the inherent heterogeneity in the spatial distribution, size, and quantity of different components among a cell population. Furthermore, CellOrganizer can generate quantitatively realistic synthetic images that reflect the underlying cell population. A current focus of the project is to model the complex, interdependent nature of organelle localization. We built upon previous work on developing multiple non-parametric models of organelles or structures that show punctate patterns. The previous models described the relationships between the subcellular localization of puncta and the positions of cell and nuclear membranes and microtubules. We extend these models to consider the relationship to the endoplasmic reticulum (ER), and to consider the relationship between the positions of different puncta of the same type. Our results do not suggest that the punctate patterns we examined are dependent on ER position or inter- and intra-class proximity. With these results, we built classifiers to update previous assignments of proteins to one of 11 patterns in three distinct cell lines. Our generative models demonstrate the ability to construct statistically accurate representations of puncta localization from simple cellular markers in distinct cell types, capturing the complex phenomena of cellular structure interaction with little human input. This protocol represents a novel approach to vesicular protein annotation, a field that is often neglected in high-throughput microscopy. These results suggest that spatial point process models provide useful insight with respect to the spatial dependence between cellular structures. © 2016 International Society for Advancement of Cytometry. © 2016 International Society for Advancement of Cytometry.

A Game Theoretic Optimization Method for Energy Efficient Global Connectivity in Hybrid Wireless Sensor Networks

PubMed Central

Lee, JongHyup; Pak, Dohyun

2016-01-01

For practical deployment of wireless sensor networks (WSN), WSNs construct clusters, where a sensor node communicates with other nodes in its cluster, and a cluster head support connectivity between the sensor nodes and a sink node. In hybrid WSNs, cluster heads have cellular network interfaces for global connectivity. However, when WSNs are active and the load of cellular networks is high, the optimal assignment of cluster heads to base stations becomes critical. Therefore, in this paper, we propose a game theoretic model to find the optimal assignment of base stations for hybrid WSNs. Since the communication and energy cost is different according to cellular systems, we devise two game models for TDMA/FDMA and CDMA systems employing power prices to adapt to the varying efficiency of recent wireless technologies. The proposed model is defined on the assumptions of the ideal sensing field, but our evaluation shows that the proposed model is more adaptive and energy efficient than local selections. PMID:27589743

The brain as a system of nested but partially overlapping networks. Heuristic relevance of the model for brain physiology and pathology.

PubMed

Agnati, L F; Guidolin, D; Fuxe, K

2007-01-01

A new model of the brain organization is proposed. The model is based on the assumption that a global molecular network enmeshes the entire central nervous system. Thus, brain extra-cellular and intra-cellular molecular networks are proposed to communicate at the level of special plasma membrane regions (e.g., the lipid rafts) where horizontal molecular networks can represent input/output regions allowing the cell to have informational exchanges with the extracellular environment. Furthermore, some "pervasive signals" such as field potentials, pressure waves and thermal gradients that affect large parts of the brain cellular and molecular networks are discussed. Finally, at least two learning paradigms are analyzed taking into account the possible role of Volume Transmission: the so-called model of "temporal difference learning" and the "Turing B-unorganised machine". The relevance of this new view of brain organization for a deeper understanding of some neurophysiological and neuropathological aspects of its function is briefly discussed.

Building New Bridges between In Vitro and In Vivo in Early Drug Discovery: Where Molecular Modeling Meets Systems Biology.

PubMed

Pearlstein, Robert A; McKay, Daniel J J; Hornak, Viktor; Dickson, Callum; Golosov, Andrei; Harrison, Tyler; Velez-Vega, Camilo; Duca, José

2017-01-01

Cellular drug targets exist within networked function-generating systems whose constituent molecular species undergo dynamic interdependent non-equilibrium state transitions in response to specific perturbations (i.e.. inputs). Cellular phenotypic behaviors are manifested through the integrated behaviors of such networks. However, in vitro data are frequently measured and/or interpreted with empirical equilibrium or steady state models (e.g. Hill, Michaelis-Menten, Briggs-Haldane) relevant to isolated target populations. We propose that cells act as analog computers, "solving" sets of coupled "molecular differential equations" (i.e. represented by populations of interacting species)via "integration" of the dynamic state probability distributions among those populations. Disconnects between biochemical and functional/phenotypic assays (cellular/in vivo) may arise with targetcontaining systems that operate far from equilibrium, and/or when coupled contributions (including target-cognate partner binding and drug pharmacokinetics) are neglected in the analysis of biochemical results. The transformation of drug discovery from a trial-and-error endeavor to one based on reliable design criteria depends on improved understanding of the dynamic mechanisms powering cellular function/dysfunction at the systems level. Here, we address the general mechanisms of molecular and cellular function and pharmacological modulation thereof. We outline a first principles theory on the mechanisms by which free energy is stored and transduced into biological function, and by which biological function is modulated by drug-target binding. We propose that cellular function depends on dynamic counter-balanced molecular systems necessitated by the exponential behavior of molecular state transitions under non-equilibrium conditions, including positive versus negative mass action kinetics and solute-induced perturbations to the hydrogen bonds of solvating water versus kT. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Agent-Based Modeling of Mitochondria Links Sub-Cellular Dynamics to Cellular Homeostasis and Heterogeneity.

PubMed

Dalmasso, Giovanni; Marin Zapata, Paula Andrea; Brady, Nathan Ryan; Hamacher-Brady, Anne

2017-01-01

Mitochondria are semi-autonomous organelles that supply energy for cellular biochemistry through oxidative phosphorylation. Within a cell, hundreds of mobile mitochondria undergo fusion and fission events to form a dynamic network. These morphological and mobility dynamics are essential for maintaining mitochondrial functional homeostasis, and alterations both impact and reflect cellular stress states. Mitochondrial homeostasis is further dependent on production (biogenesis) and the removal of damaged mitochondria by selective autophagy (mitophagy). While mitochondrial function, dynamics, biogenesis and mitophagy are highly-integrated processes, it is not fully understood how systemic control in the cell is established to maintain homeostasis, or respond to bioenergetic demands. Here we used agent-based modeling (ABM) to integrate molecular and imaging knowledge sets, and simulate population dynamics of mitochondria and their response to environmental energy demand. Using high-dimensional parameter searches we integrated experimentally-measured rates of mitochondrial biogenesis and mitophagy, and using sensitivity analysis we identified parameter influences on population homeostasis. By studying the dynamics of cellular subpopulations with distinct mitochondrial masses, our approach uncovered system properties of mitochondrial populations: (1) mitochondrial fusion and fission activities rapidly establish mitochondrial sub-population homeostasis, and total cellular levels of mitochondria alter fusion and fission activities and subpopulation distributions; (2) restricting the directionality of mitochondrial mobility does not alter morphology subpopulation distributions, but increases network transmission dynamics; and (3) maintaining mitochondrial mass homeostasis and responding to bioenergetic stress requires the integration of mitochondrial dynamics with the cellular bioenergetic state. Finally, (4) our model suggests sources of, and stress conditions amplifying, cell-to-cell variability of mitochondrial morphology and energetic stress states. Overall, our modeling approach integrates biochemical and imaging knowledge, and presents a novel open-modeling approach to investigate how spatial and temporal mitochondrial dynamics contribute to functional homeostasis, and how subcellular organelle heterogeneity contributes to the emergence of cell heterogeneity.

Agent-Based Modeling of Mitochondria Links Sub-Cellular Dynamics to Cellular Homeostasis and Heterogeneity

PubMed Central

Dalmasso, Giovanni; Marin Zapata, Paula Andrea; Brady, Nathan Ryan; Hamacher-Brady, Anne

2017-01-01

Mitochondria are semi-autonomous organelles that supply energy for cellular biochemistry through oxidative phosphorylation. Within a cell, hundreds of mobile mitochondria undergo fusion and fission events to form a dynamic network. These morphological and mobility dynamics are essential for maintaining mitochondrial functional homeostasis, and alterations both impact and reflect cellular stress states. Mitochondrial homeostasis is further dependent on production (biogenesis) and the removal of damaged mitochondria by selective autophagy (mitophagy). While mitochondrial function, dynamics, biogenesis and mitophagy are highly-integrated processes, it is not fully understood how systemic control in the cell is established to maintain homeostasis, or respond to bioenergetic demands. Here we used agent-based modeling (ABM) to integrate molecular and imaging knowledge sets, and simulate population dynamics of mitochondria and their response to environmental energy demand. Using high-dimensional parameter searches we integrated experimentally-measured rates of mitochondrial biogenesis and mitophagy, and using sensitivity analysis we identified parameter influences on population homeostasis. By studying the dynamics of cellular subpopulations with distinct mitochondrial masses, our approach uncovered system properties of mitochondrial populations: (1) mitochondrial fusion and fission activities rapidly establish mitochondrial sub-population homeostasis, and total cellular levels of mitochondria alter fusion and fission activities and subpopulation distributions; (2) restricting the directionality of mitochondrial mobility does not alter morphology subpopulation distributions, but increases network transmission dynamics; and (3) maintaining mitochondrial mass homeostasis and responding to bioenergetic stress requires the integration of mitochondrial dynamics with the cellular bioenergetic state. Finally, (4) our model suggests sources of, and stress conditions amplifying, cell-to-cell variability of mitochondrial morphology and energetic stress states. Overall, our modeling approach integrates biochemical and imaging knowledge, and presents a novel open-modeling approach to investigate how spatial and temporal mitochondrial dynamics contribute to functional homeostasis, and how subcellular organelle heterogeneity contributes to the emergence of cell heterogeneity. PMID:28060865

Photobiomodulation on senescence

NASA Astrophysics Data System (ADS)

Liu, Timon Cheng-Yi; Cheng, Lei; Rong, Dong-Liang; Xu, Xiao-Yang; Cui, Li-Ping; Lu, Jian; Deng, Xiao-Yuan; Liu, Song-Hao

2006-09-01

Photobiomodulation (PBM) is an effect oflow intensity monochromatic light or laser irradiation (LIL) on biological systems. which stimulates or inhibits biological functions but does not result in irreducible damage. It has been observed that PBM can suppress cellular senescence, reverse skin photoageing and improve fibromyalgia. In this paper, the biological information model of photobiomodulation (BIMP) is used to discuss its mechanism. Cellular senescence can result from short, dysfunctional telomeres, oxidative stress, or oncogene expression, and may contribute to aging so that it can be seen as a decline of cellular function in which cAMP plays an important role, which provide a foundation for PBM on senescence since cellular senescence is a reasonable model of senescence and PBM is a cellular rehabilitation in which cAMP also plays an important role according to BIMP. The PBM in reversing skin photoageing and improving fibromyalgia are then discussed in detail.

Excellent approach to modeling urban expansion by fuzzy cellular automata: agent base model

NASA Astrophysics Data System (ADS)

Khajavigodellou, Yousef; Alesheikh, Ali A.; Mohammed, Abdulrazak A. S.; Chapi, Kamran

2014-09-01

Recently, the interaction between humans and their environment is the one of important challenges in the world. Landuse/ cover change (LUCC) is a complex process that includes actors and factors at different social and spatial levels. The complexity and dynamics of urban systems make the applicable practice of urban modeling very difficult. With the increased computational power and the greater availability of spatial data, micro-simulation such as the agent based and cellular automata simulation methods, has been developed by geographers, planners, and scholars, and it has shown great potential for representing and simulating the complexity of the dynamic processes involved in urban growth and land use change. This paper presents Fuzzy Cellular Automata in Geospatial Information System and remote Sensing to simulated and predicted urban expansion pattern. These FCA-based dynamic spatial urban models provide an improved ability to forecast and assess future urban growth and to create planning scenarios, allowing us to explore the potential impacts of simulations that correspond to urban planning and management policies. A fuzzy inference guided cellular automata approach. Semantic or linguistic knowledge on Land use change is expressed as fuzzy rules, based on which fuzzy inference is applied to determine the urban development potential for each pixel. The model integrates an ABM (agent-based model) and FCA (Fuzzy Cellular Automata) to investigate a complex decision-making process and future urban dynamic processes. Based on this model rapid development and green land protection under the influences of the behaviors and decision modes of regional authority agents, real estate developer agents, resident agents and non- resident agents and their interactions have been applied to predict the future development patterns of the Erbil metropolitan region.

Challenges in structural approaches to cell modeling

PubMed Central

Im, Wonpil; Liang, Jie; Olson, Arthur; Zhou, Huan-Xiang; Vajda, Sandor; Vakser, Ilya A.

2016-01-01

Computational modeling is essential for structural characterization of biomolecular mechanisms across the broad spectrum of scales. Adequate understanding of biomolecular mechanisms inherently involves our ability to model them. Structural modeling of individual biomolecules and their interactions has been rapidly progressing. However, in terms of the broader picture, the focus is shifting toward larger systems, up to the level of a cell. Such modeling involves a more dynamic and realistic representation of the interactomes in vivo, in a crowded cellular environment, as well as membranes and membrane proteins, and other cellular components. Structural modeling of a cell complements computational approaches to cellular mechanisms based on differential equations, graph models, and other techniques to model biological networks, imaging data, etc. Structural modeling along with other computational and experimental approaches will provide a fundamental understanding of life at the molecular level and lead to important applications to biology and medicine. A cross section of diverse approaches presented in this review illustrates the developing shift from the structural modeling of individual molecules to that of cell biology. Studies in several related areas are covered: biological networks; automated construction of three-dimensional cell models using experimental data; modeling of protein complexes; prediction of non-specific and transient protein interactions; thermodynamic and kinetic effects of crowding; cellular membrane modeling; and modeling of chromosomes. The review presents an expert opinion on the current state-of-the-art in these various aspects of structural modeling in cellular biology, and the prospects of future developments in this emerging field. PMID:27255863

Mammalian synthetic biology for studying the cell

PubMed Central

Mathur, Melina; Xiang, Joy S.

2017-01-01

Synthetic biology is advancing the design of genetic devices that enable the study of cellular and molecular biology in mammalian cells. These genetic devices use diverse regulatory mechanisms to both examine cellular processes and achieve precise and dynamic control of cellular phenotype. Synthetic biology tools provide novel functionality to complement the examination of natural cell systems, including engineered molecules with specific activities and model systems that mimic complex regulatory processes. Continued development of quantitative standards and computational tools will expand capacities to probe cellular mechanisms with genetic devices to achieve a more comprehensive understanding of the cell. In this study, we review synthetic biology tools that are being applied to effectively investigate diverse cellular processes, regulatory networks, and multicellular interactions. We also discuss current challenges and future developments in the field that may transform the types of investigation possible in cell biology. PMID:27932576

A new cellular automata model of traffic flow with negative exponential weighted look-ahead potential

NASA Astrophysics Data System (ADS)

Ma, Xiao; Zheng, Wei-Fan; Jiang, Bao-Shan; Zhang, Ji-Ye

2016-10-01

With the development of traffic systems, some issues such as traffic jams become more and more serious. Efficient traffic flow theory is needed to guide the overall controlling, organizing and management of traffic systems. On the basis of the cellular automata model and the traffic flow model with look-ahead potential, a new cellular automata traffic flow model with negative exponential weighted look-ahead potential is presented in this paper. By introducing the negative exponential weighting coefficient into the look-ahead potential and endowing the potential of vehicles closer to the driver with a greater coefficient, the modeling process is more suitable for the driver’s random decision-making process which is based on the traffic environment that the driver is facing. The fundamental diagrams for different weighting parameters are obtained by using numerical simulations which show that the negative exponential weighting coefficient has an obvious effect on high density traffic flux. The complex high density non-linear traffic behavior is also reproduced by numerical simulations. Project supported by the National Natural Science Foundation of China (Grant Nos. 11572264, 11172247, 11402214, and 61373009).

An implementation of cellular automaton model for single-line train working diagram

NASA Astrophysics Data System (ADS)

Hua, Wei; Liu, Jun

2006-04-01

According to the railway transportation system's characteristics, a new cellular automaton model for the single-line railway system is presented in this paper. Based on this model, several simulations were done to imitate the train operation under three working diagrams. From a different angle the results show how the organization of train operation impacts on the railway carrying capacity. By using the non-parallel train working diagram the influence of fast-train on slow-train is found to be the strongest. Many slow-trains have to wait in-between neighbouring stations to let the fast-train(s) pass through first. So the slow-train will advance like a wave propagating from the departure station to the arrival station. This also resembles the situation of a highway jammed traffic flow. Furthermore, the nonuniformity of travel times between the sections also greatly limits the railway carrying capacity. After converting the nonuniform sections into the sections with uniform travel times while the total travel time is kept unchanged, all three carrying capacities are improved greatly as shown by simulation. It also shows that the cellular automaton model is an effective and feasible way to investigate the railway transportation system.

Dynamic cellular manufacturing system considering machine failure and workload balance

NASA Astrophysics Data System (ADS)

Rabbani, Masoud; Farrokhi-Asl, Hamed; Ravanbakhsh, Mohammad

2018-02-01

Machines are a key element in the production system and their failure causes irreparable effects in terms of cost and time. In this paper, a new multi-objective mathematical model for dynamic cellular manufacturing system (DCMS) is provided with consideration of machine reliability and alternative process routes. In this dynamic model, we attempt to resolve the problem of integrated family (part/machine cell) formation as well as the operators' assignment to the cells. The first objective minimizes the costs associated with the DCMS. The second objective optimizes the labor utilization and, finally, a minimum value of the variance of workload between different cells is obtained by the third objective function. Due to the NP-hard nature of the cellular manufacturing problem, the problem is initially validated by the GAMS software in small-sized problems, and then the model is solved by two well-known meta-heuristic methods including non-dominated sorting genetic algorithm and multi-objective particle swarm optimization in large-scaled problems. Finally, the results of the two algorithms are compared with respect to five different comparison metrics.

Modeling cell adhesion and proliferation: a cellular-automata based approach.

PubMed

Vivas, J; Garzón-Alvarado, D; Cerrolaza, M

Cell adhesion is a process that involves the interaction between the cell membrane and another surface, either a cell or a substrate. Unlike experimental tests, computer models can simulate processes and study the result of experiments in a shorter time and lower costs. One of the tools used to simulate biological processes is the cellular automata, which is a dynamic system that is discrete both in space and time. This work describes a computer model based on cellular automata for the adhesion process and cell proliferation to predict the behavior of a cell population in suspension and adhered to a substrate. The values of the simulated system were obtained through experimental tests on fibroblast monolayer cultures. The results allow us to estimate the cells settling time in culture as well as the adhesion and proliferation time. The change in the cells morphology as the adhesion over the contact surface progress was also observed. The formation of the initial link between cell and the substrate of the adhesion was observed after 100 min where the cell on the substrate retains its spherical morphology during the simulation. The cellular automata model developed is, however, a simplified representation of the steps in the adhesion process and the subsequent proliferation. A combined framework of experimental and computational simulation based on cellular automata was proposed to represent the fibroblast adhesion on substrates and changes in a macro-scale observed in the cell during the adhesion process. The approach showed to be simple and efficient.

Cellular solidification in a monotectic system

NASA Technical Reports Server (NTRS)

Kaukler, W. F.; Curreri, P. A.

1987-01-01

Succinonitrile-glycerol, SN-G, transparent organic monotectic alloy is studied with particular attention to cellular growth. The phase diagram is determined, near the monotectic composition, with greater accuracy than previous studies. A solidification interface stability diagram is determined for planar growth. The planar-to-cellular transition is compared to predictions from the Burton, Primm, Schlichter theory. A new technique to determine the solute segregation by Fourier transform infrared spectroscopy is developed. Proposed models that involve the cellular interface for alignment of monotectic second-phase spheres or rods are compared with observations.

Cellular Manufacturing System with Dynamic Lot Size Material Handling

NASA Astrophysics Data System (ADS)

Khannan, M. S. A.; Maruf, A.; Wangsaputra, R.; Sutrisno, S.; Wibawa, T.

2016-02-01

Material Handling take as important role in Cellular Manufacturing System (CMS) design. In several study at CMS design material handling was assumed per pieces or with constant lot size. In real industrial practice, lot size may change during rolling period to cope with demand changes. This study develops CMS Model with Dynamic Lot Size Material Handling. Integer Linear Programming is used to solve the problem. Objective function of this model is minimizing total expected cost consisting machinery depreciation cost, operating costs, inter-cell material handling cost, intra-cell material handling cost, machine relocation costs, setup costs, and production planning cost. This model determines optimum cell formation and optimum lot size. Numerical examples are elaborated in the paper to ilustrate the characterictic of the model.

Computer modeling describes gravity-related adaptation in cell cultures.

PubMed

Alexandrov, Ludmil B; Alexandrova, Stoyana; Usheva, Anny

2009-12-16

Questions about the changes of biological systems in response to hostile environmental factors are important but not easy to answer. Often, the traditional description with differential equations is difficult due to the overwhelming complexity of the living systems. Another way to describe complex systems is by simulating them with phenomenological models such as the well-known evolutionary agent-based model (EABM). Here we developed an EABM to simulate cell colonies as a multi-agent system that adapts to hyper-gravity in starvation conditions. In the model, the cell's heritable characteristics are generated and transferred randomly to offspring cells. After a qualitative validation of the model at normal gravity, we simulate cellular growth in hyper-gravity conditions. The obtained data are consistent with previously confirmed theoretical and experimental findings for bacterial behavior in environmental changes, including the experimental data from the microgravity Atlantis and the Hypergravity 3000 experiments. Our results demonstrate that it is possible to utilize an EABM with realistic qualitative description to examine the effects of hypergravity and starvation on complex cellular entities.

SBML-SAT: a systems biology markup language (SBML) based sensitivity analysis tool

PubMed Central

Zi, Zhike; Zheng, Yanan; Rundell, Ann E; Klipp, Edda

2008-01-01

Background It has long been recognized that sensitivity analysis plays a key role in modeling and analyzing cellular and biochemical processes. Systems biology markup language (SBML) has become a well-known platform for coding and sharing mathematical models of such processes. However, current SBML compatible software tools are limited in their ability to perform global sensitivity analyses of these models. Results This work introduces a freely downloadable, software package, SBML-SAT, which implements algorithms for simulation, steady state analysis, robustness analysis and local and global sensitivity analysis for SBML models. This software tool extends current capabilities through its execution of global sensitivity analyses using multi-parametric sensitivity analysis, partial rank correlation coefficient, SOBOL's method, and weighted average of local sensitivity analyses in addition to its ability to handle systems with discontinuous events and intuitive graphical user interface. Conclusion SBML-SAT provides the community of systems biologists a new tool for the analysis of their SBML models of biochemical and cellular processes. PMID:18706080

SBML-SAT: a systems biology markup language (SBML) based sensitivity analysis tool.

PubMed

Zi, Zhike; Zheng, Yanan; Rundell, Ann E; Klipp, Edda

2008-08-15

It has long been recognized that sensitivity analysis plays a key role in modeling and analyzing cellular and biochemical processes. Systems biology markup language (SBML) has become a well-known platform for coding and sharing mathematical models of such processes. However, current SBML compatible software tools are limited in their ability to perform global sensitivity analyses of these models. This work introduces a freely downloadable, software package, SBML-SAT, which implements algorithms for simulation, steady state analysis, robustness analysis and local and global sensitivity analysis for SBML models. This software tool extends current capabilities through its execution of global sensitivity analyses using multi-parametric sensitivity analysis, partial rank correlation coefficient, SOBOL's method, and weighted average of local sensitivity analyses in addition to its ability to handle systems with discontinuous events and intuitive graphical user interface. SBML-SAT provides the community of systems biologists a new tool for the analysis of their SBML models of biochemical and cellular processes.

Simulation analysis of an integrated model for dynamic cellular manufacturing system

NASA Astrophysics Data System (ADS)

Hao, Chunfeng; Luan, Shichao; Kong, Jili

2017-05-01

Application of dynamic cellular manufacturing system (DCMS) is a well-known strategy to improve manufacturing efficiency in the production environment with high variety and low volume of production. Often, neither the trade-off of inter and intra-cell material movements nor the trade-off of hiring and firing of operators are examined in details. This paper presents simulation results of an integrated mixed-integer model including sensitivity analysis for several numerical examples. The comprehensive model includes cell formation, inter and intracellular materials handling, inventory and backorder holding, operator assignment (including resource adjustment) and flexible production routing. The model considers multi-production planning with flexible resources (machines and operators) where each period has different demands. The results verify the validity and sensitivity of the proposed model using a genetic algorithm.

Establishment of a translational endothelial cell model using directed differentiation of induced pluripotent stem cells from Cynomolgus monkey.

PubMed

Thoma, Eva C; Heckel, Tobias; Keller, David; Giroud, Nicolas; Leonard, Brian; Christensen, Klaus; Roth, Adrian; Bertinetti-Lapatki, Cristina; Graf, Martin; Patsch, Christoph

2016-10-25

Due to their broad differentiation potential, pluripotent stem cells (PSCs) offer a promising approach for generating relevant cellular models for various applications. While human PSC-based cellular models are already advanced, similar systems for non-human primates (NHPs) are still lacking. However, as NHPs are the most appropriate animals for evaluating the safety of many novel pharmaceuticals, the availability of in vitro systems would be extremely useful to bridge the gap between cellular and animal models. Here, we present a NHP in vitro endothelial cell system using induced pluripotent stem cells (IPSCs) from Cynomolgus monkey (Macaca fascicularis). Based on an adapted protocol for human IPSCs, we directly differentiated macaque IPSCs into endothelial cells under chemically defined conditions. The resulting endothelial cells can be enriched using immuno-magnetic cell sorting and display endothelial marker expression and function. RNA sequencing revealed that the differentiation process closely resembled vasculogenesis. Moreover, we showed that endothelial cells derived from macaque and human IPSCs are highly similar with respect to gene expression patterns and key endothelial functions, such as inflammatory responses. These data demonstrate the power of IPSC differentiation technology to generate defined cell types for use as translational in vitro models to compare cell type-specific responses across species.

Kinetic theory approach to modeling of cellular repair mechanisms under genome stress.

PubMed

Qi, Jinpeng; Ding, Yongsheng; Zhu, Ying; Wu, Yizhi

2011-01-01

Under acute perturbations from outer environment, a normal cell can trigger cellular self-defense mechanism in response to genome stress. To investigate the kinetics of cellular self-repair process at single cell level further, a model of DNA damage generating and repair is proposed under acute Ion Radiation (IR) by using mathematical framework of kinetic theory of active particles (KTAP). Firstly, we focus on illustrating the profile of Cellular Repair System (CRS) instituted by two sub-populations, each of which is made up of the active particles with different discrete states. Then, we implement the mathematical framework of cellular self-repair mechanism, and illustrate the dynamic processes of Double Strand Breaks (DSBs) and Repair Protein (RP) generating, DSB-protein complexes (DSBCs) synthesizing, and toxins accumulating. Finally, we roughly analyze the capability of cellular self-repair mechanism, cellular activity of transferring DNA damage, and genome stability, especially the different fates of a certain cell before and after the time thresholds of IR perturbations that a cell can tolerate maximally under different IR perturbation circumstances.

Phase separation and the formation of cellular bodies

NASA Astrophysics Data System (ADS)

Xu, Bin; Broedersz, Chase P.; Meir, Yigal; Wingreen, Ned S.

Cellular bodies in eukaryotic cells spontaneously assemble to form cellular compartments. Among other functions, these bodies carry out essential biochemical reactions. Cellular bodies form micron-sized structures, which, unlike canonical cell organelles, are not surrounded by membranes. A recent in vitro experiment has shown that phase separation of polymers in solution can explain the formation of cellular bodies. We constructed a lattice-polymer model to capture the essential mechanism leading to this phase separation. We used both analytical and numerical tools to predict the phase diagram of a system of two interacting polymers, including the concentration of each polymer type in the condensed and dilute phase.

On the phase space structure of IP3 induced Ca2+ signalling and concepts for predictive modeling

NASA Astrophysics Data System (ADS)

Falcke, Martin; Moein, Mahsa; TilÅ«naitÄ--, Agne; Thul, Rüdiger; Skupin, Alexander

2018-04-01

The correspondence between mathematical structures and experimental systems is the basis of the generalizability of results found with specific systems and is the basis of the predictive power of theoretical physics. While physicists have confidence in this correspondence, it is less recognized in cellular biophysics. On the one hand, the complex organization of cellular dynamics involving a plethora of interacting molecules and the basic observation of cell variability seem to question its possibility. The practical difficulties of deriving the equations describing cellular behaviour from first principles support these doubts. On the other hand, ignoring such a correspondence would severely limit the possibility of predictive quantitative theory in biophysics. Additionally, the existence of functional modules (like pathways) across cell types suggests also the existence of mathematical structures with comparable universality. Only a few cellular systems have been sufficiently investigated in a variety of cell types to follow up these basic questions. IP3 induced Ca2+signalling is one of them, and the mathematical structure corresponding to it is subject of ongoing discussion. We review the system's general properties observed in a variety of cell types. They are captured by a reaction diffusion system. We discuss the phase space structure of its local dynamics. The spiking regime corresponds to noisy excitability. Models focussing on different aspects can be derived starting from this phase space structure. We discuss how the initial assumptions on the set of stochastic variables and phase space structure shape the predictions of parameter dependencies of the mathematical models resulting from the derivation.

Mammalian synthetic biology for studying the cell.

PubMed

Mathur, Melina; Xiang, Joy S; Smolke, Christina D

2017-01-02

Synthetic biology is advancing the design of genetic devices that enable the study of cellular and molecular biology in mammalian cells. These genetic devices use diverse regulatory mechanisms to both examine cellular processes and achieve precise and dynamic control of cellular phenotype. Synthetic biology tools provide novel functionality to complement the examination of natural cell systems, including engineered molecules with specific activities and model systems that mimic complex regulatory processes. Continued development of quantitative standards and computational tools will expand capacities to probe cellular mechanisms with genetic devices to achieve a more comprehensive understanding of the cell. In this study, we review synthetic biology tools that are being applied to effectively investigate diverse cellular processes, regulatory networks, and multicellular interactions. We also discuss current challenges and future developments in the field that may transform the types of investigation possible in cell biology. © 2017 Mathur et al.

Dynamics of biological systems: role of systems biology in medical research.

PubMed

Assmus, Heike E; Herwig, Ralf; Cho, Kwang-Hyun; Wolkenhauer, Olaf

2006-11-01

Cellular systems are networks of interacting components that change with time in response to external and internal events. Studying the dynamic behavior of these networks is the basis for an understanding of cellular functions and disease mechanisms. Quantitative time-series data leading to meaningful models can improve our knowledge of human physiology in health and disease, and aid the search for earlier diagnoses, better therapies and a healthier life. The advent of systems biology is about to take the leap into clinical research and medical applications. This review emphasizes the importance of a dynamic view and understanding of cell function. We discuss the potential for computer-aided mathematical modeling of biological systems in medical research with examples from some of the major therapeutic areas: cancer, cardiovascular, diabetic and neurodegenerative medicine.

Evolution of Antibody-Drug Conjugate Tumor Disposition Model to Predict Preclinical Tumor Pharmacokinetics of Trastuzumab-Emtansine (T-DM1).

PubMed

Singh, Aman P; Maass, Katie F; Betts, Alison M; Wittrup, K Dane; Kulkarni, Chethana; King, Lindsay E; Khot, Antari; Shah, Dhaval K

2016-07-01

A mathematical model capable of accurately characterizing intracellular disposition of ADCs is essential for a priori predicting unconjugated drug concentrations inside the tumor. Towards this goal, the objectives of this manuscript were to: (1) evolve previously published cellular disposition model of ADC with more intracellular details to characterize the disposition of T-DM1 in different HER2 expressing cell lines, (2) integrate the improved cellular model with the ADC tumor disposition model to a priori predict DM1 concentrations in a preclinical tumor model, and (3) identify prominent pathways and sensitive parameters associated with intracellular activation of ADCs. The cellular disposition model was augmented by incorporating intracellular ADC degradation and passive diffusion of unconjugated drug across tumor cells. Different biomeasures and chemomeasures for T-DM1, quantified in the companion manuscript, were incorporated into the modified model of ADC to characterize in vitro pharmacokinetics of T-DM1 in three HER2+ cell lines. When the cellular model was integrated with the tumor disposition model, the model was able to a priori predict tumor DM1 concentrations in xenograft mice. Pathway analysis suggested different contribution of antigen-mediated and passive diffusion pathways for intracellular unconjugated drug exposure between in vitro and in vivo systems. Global and local sensitivity analyses revealed that non-specific deconjugation and passive diffusion of the drug across tumor cell membrane are key parameters for drug exposure inside a cell. Finally, a systems pharmacokinetic model for intracellular processing of ADCs has been proposed to highlight our current understanding about the determinants of ADC activation inside a cell.

Metabolic Adaptation to Muscle Ischemia

NASA Technical Reports Server (NTRS)

Cabrera, Marco E.; Coon, Jennifer E.; Kalhan, Satish C.; Radhakrishnan, Krishnan; Saidel, Gerald M.; Stanley, William C.

2000-01-01

Although all tissues in the body can adapt to varying physiological/pathological conditions, muscle is the most adaptable. To understand the significance of cellular events and their role in controlling metabolic adaptations in complex physiological systems, it is necessary to link cellular and system levels by means of mechanistic computational models. The main objective of this work is to improve understanding of the regulation of energy metabolism during skeletal/cardiac muscle ischemia by combining in vivo experiments and quantitative models of metabolism. Our main focus is to investigate factors affecting lactate metabolism (e.g., NADH/NAD) and the inter-regulation between carbohydrate and fatty acid metabolism during a reduction in regional blood flow. A mechanistic mathematical model of energy metabolism has been developed to link cellular metabolic processes and their control mechanisms to tissue (skeletal muscle) and organ (heart) physiological responses. We applied this model to simulate the relationship between tissue oxygenation, redox state, and lactate metabolism in skeletal muscle. The model was validated using human data from published occlusion studies. Currently, we are investigating the difference in the responses to sudden vs. gradual onset ischemia in swine by combining in vivo experimental studies with computational models of myocardial energy metabolism during normal and ischemic conditions.

Challenges in structural approaches to cell modeling.

PubMed

Im, Wonpil; Liang, Jie; Olson, Arthur; Zhou, Huan-Xiang; Vajda, Sandor; Vakser, Ilya A

2016-07-31

Computational modeling is essential for structural characterization of biomolecular mechanisms across the broad spectrum of scales. Adequate understanding of biomolecular mechanisms inherently involves our ability to model them. Structural modeling of individual biomolecules and their interactions has been rapidly progressing. However, in terms of the broader picture, the focus is shifting toward larger systems, up to the level of a cell. Such modeling involves a more dynamic and realistic representation of the interactomes in vivo, in a crowded cellular environment, as well as membranes and membrane proteins, and other cellular components. Structural modeling of a cell complements computational approaches to cellular mechanisms based on differential equations, graph models, and other techniques to model biological networks, imaging data, etc. Structural modeling along with other computational and experimental approaches will provide a fundamental understanding of life at the molecular level and lead to important applications to biology and medicine. A cross section of diverse approaches presented in this review illustrates the developing shift from the structural modeling of individual molecules to that of cell biology. Studies in several related areas are covered: biological networks; automated construction of three-dimensional cell models using experimental data; modeling of protein complexes; prediction of non-specific and transient protein interactions; thermodynamic and kinetic effects of crowding; cellular membrane modeling; and modeling of chromosomes. The review presents an expert opinion on the current state-of-the-art in these various aspects of structural modeling in cellular biology, and the prospects of future developments in this emerging field. Copyright © 2016 Elsevier Ltd. All rights reserved.

Effect of alternate energy substrates on mammalian brain metabolism during ischemic events.

PubMed

Koppaka, S S; Puchowicz; LaManna, J C; Gatica, J E

2008-01-01

Regulation of brain metabolism and cerebral blood flow involves complex control systems with several interacting variables at both cellular and organ levels. Quantitative understanding of the spatially and temporally heterogeneous brain control mechanisms during internal and external stimuli requires the development and validation of a computational (mathematical) model of metabolic processes in brain. This paper describes a computational model of cellular metabolism in blood-perfused brain tissue, which considers the astrocyte-neuron lactate-shuttle (ANLS) hypothesis. The model structure consists of neurons, astrocytes, extra-cellular space, and a surrounding capillary network. Each cell is further compartmentalized into cytosol and mitochondria. Inter-compartment interaction is accounted in the form of passive and carrier-mediated transport. Our model was validated against experimental data reported by Crumrine and LaManna, who studied the effect of ischemia and its recovery on various intra-cellular tissue substrates under standard diet conditions. The effect of ketone bodies on brain metabolism was also examined under ischemic conditions following cardiac resuscitation through our model simulations. The influence of ketone bodies on lactate dynamics on mammalian brain following ischemia is studied incorporating experimental data.

A hybrid parallel framework for the cellular Potts model simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jiang, Yi; He, Kejing; Dong, Shoubin

2009-01-01

The Cellular Potts Model (CPM) has been widely used for biological simulations. However, most current implementations are either sequential or approximated, which can't be used for large scale complex 3D simulation. In this paper we present a hybrid parallel framework for CPM simulations. The time-consuming POE solving, cell division, and cell reaction operation are distributed to clusters using the Message Passing Interface (MPI). The Monte Carlo lattice update is parallelized on shared-memory SMP system using OpenMP. Because the Monte Carlo lattice update is much faster than the POE solving and SMP systems are more and more common, this hybrid approachmore » achieves good performance and high accuracy at the same time. Based on the parallel Cellular Potts Model, we studied the avascular tumor growth using a multiscale model. The application and performance analysis show that the hybrid parallel framework is quite efficient. The hybrid parallel CPM can be used for the large scale simulation ({approx}10{sup 8} sites) of complex collective behavior of numerous cells ({approx}10{sup 6}).« less

Computational Systems Biology in Cancer: Modeling Methods and Applications

PubMed Central

Materi, Wayne; Wishart, David S.

2007-01-01

In recent years it has become clear that carcinogenesis is a complex process, both at the molecular and cellular levels. Understanding the origins, growth and spread of cancer, therefore requires an integrated or system-wide approach. Computational systems biology is an emerging sub-discipline in systems biology that utilizes the wealth of data from genomic, proteomic and metabolomic studies to build computer simulations of intra and intercellular processes. Several useful descriptive and predictive models of the origin, growth and spread of cancers have been developed in an effort to better understand the disease and potential therapeutic approaches. In this review we describe and assess the practical and theoretical underpinnings of commonly-used modeling approaches, including ordinary and partial differential equations, petri nets, cellular automata, agent based models and hybrid systems. A number of computer-based formalisms have been implemented to improve the accessibility of the various approaches to researchers whose primary interest lies outside of model development. We discuss several of these and describe how they have led to novel insights into tumor genesis, growth, apoptosis, vascularization and therapy. PMID:19936081

Theoretical Model for Cellular Shapes Driven by Protrusive and Adhesive Forces

PubMed Central

Kabaso, Doron; Shlomovitz, Roie; Schloen, Kathrin; Stradal, Theresia; Gov, Nir S.

2011-01-01

The forces that arise from the actin cytoskeleton play a crucial role in determining the cell shape. These include protrusive forces due to actin polymerization and adhesion to the external matrix. We present here a theoretical model for the cellular shapes resulting from the feedback between the membrane shape and the forces acting on the membrane, mediated by curvature-sensitive membrane complexes of a convex shape. In previous theoretical studies we have investigated the regimes of linear instability where spontaneous formation of cellular protrusions is initiated. Here we calculate the evolution of a two dimensional cell contour beyond the linear regime and determine the final steady-state shapes arising within the model. We find that shapes driven by adhesion or by actin polymerization (lamellipodia) have very different morphologies, as observed in cells. Furthermore, we find that as the strength of the protrusive forces diminish, the system approaches a stabilization of a periodic pattern of protrusions. This result can provide an explanation for a number of puzzling experimental observations regarding cellular shape dependence on the properties of the extra-cellular matrix. PMID:21573201

Estimating phase synchronization in dynamical systems using cellular nonlinear networks

NASA Astrophysics Data System (ADS)

Sowa, Robert; Chernihovskyi, Anton; Mormann, Florian; Lehnertz, Klaus

2005-06-01

We propose a method for estimating phase synchronization between time series using the parallel computing architecture of cellular nonlinear networks (CNN’s). Applying this method to time series of coupled nonlinear model systems and to electroencephalographic time series from epilepsy patients, we show that an accurate approximation of the mean phase coherence R —a bivariate measure for phase synchronization—can be achieved with CNN’s using polynomial-type templates.

Facilitating arrhythmia simulation: the method of quantitative cellular automata modeling and parallel running

PubMed Central

Zhu, Hao; Sun, Yan; Rajagopal, Gunaretnam; Mondry, Adrian; Dhar, Pawan

2004-01-01

Background Many arrhythmias are triggered by abnormal electrical activity at the ionic channel and cell level, and then evolve spatio-temporally within the heart. To understand arrhythmias better and to diagnose them more precisely by their ECG waveforms, a whole-heart model is required to explore the association between the massively parallel activities at the channel/cell level and the integrative electrophysiological phenomena at organ level. Methods We have developed a method to build large-scale electrophysiological models by using extended cellular automata, and to run such models on a cluster of shared memory machines. We describe here the method, including the extension of a language-based cellular automaton to implement quantitative computing, the building of a whole-heart model with Visible Human Project data, the parallelization of the model on a cluster of shared memory computers with OpenMP and MPI hybrid programming, and a simulation algorithm that links cellular activity with the ECG. Results We demonstrate that electrical activities at channel, cell, and organ levels can be traced and captured conveniently in our extended cellular automaton system. Examples of some ECG waveforms simulated with a 2-D slice are given to support the ECG simulation algorithm. A performance evaluation of the 3-D model on a four-node cluster is also given. Conclusions Quantitative multicellular modeling with extended cellular automata is a highly efficient and widely applicable method to weave experimental data at different levels into computational models. This process can be used to investigate complex and collective biological activities that can be described neither by their governing differentiation equations nor by discrete parallel computation. Transparent cluster computing is a convenient and effective method to make time-consuming simulation feasible. Arrhythmias, as a typical case, can be effectively simulated with the methods described. PMID:15339335

Surface tension and modeling of cellular intercalation during zebrafish gastrulation.

PubMed

Calmelet, Colette; Sepich, Diane

2010-04-01

In this paper we discuss a model of zebrafish embryo notochord development based on the effect of surface tension of cells at the boundaries. We study the process of interaction of mesodermal cells at the boundaries due to adhesion and cortical tension, resulting in cellular intercalation. From in vivo experiments, we obtain cell outlines of time-lapse images of cell movements during zebrafish embryo development. Using Cellular Potts Model, we calculate the total surface energy of the system of cells at different time intervals at cell contacts. We analyze the variations of total energy depending on nature of cell contacts. We demonstrate that our model can be viable by calculating the total surface energy value for experimentally observed configurations of cells and showing that in our model these configurations correspond to a decrease in total energy values in both two and three dimensions.

Particle acceleration in a complex solar active region modelled by a Cellular automata model

NASA Astrophysics Data System (ADS)

Dauphin, C.; Vilmer, N.; Anastasiadis, A.

2004-12-01

The models of cellular automat allowed to reproduce successfully several statistical properties of the solar flares. We use a cellular automat model based on the concept of self-organised critical system to model the evolution of the magnetic energy released in an eruptive active area. Each burst of magnetic energy released is assimilated to a process of magnetic reconnection. We will thus generate several current layers (RCS) where the particles are accelerated by a direct electric field. We calculate the energy gain of the particles (ions and electrons) for various types of magnetic configuration. We calculate the distribution function of the kinetic energy of the particles after their interactions with a given number of RCS for each type of configurations. We show that the relative efficiency of the acceleration of the electrons and the ions depends on the selected configuration.

Systems Biology for Organotypic Cell Cultures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grego, Sonia; Dougherty, Edward R.; Alexander, Francis J.

Translating in vitro biological data into actionable information related to human health holds the potential to improve disease treatment and risk assessment of chemical exposures. While genomics has identified regulatory pathways at the cellular level, translation to the organism level requires a multiscale approach accounting for intra-cellular regulation, inter-cellular interaction, and tissue/organ-level effects. Tissue-level effects can now be probed in vitro thanks to recently developed systems of three-dimensional (3D), multicellular, “organotypic” cell cultures, which mimic functional responses of living tissue. However, there remains a knowledge gap regarding interactions across different biological scales, complicating accurate prediction of health outcomes from molecular/genomicmore » data and tissue responses. Systems biology aims at mathematical modeling of complex, non-linear biological systems. We propose to apply a systems biology approach to achieve a computational representation of tissue-level physiological responses by integrating empirical data derived from organotypic culture systems with computational models of intracellular pathways to better predict human responses. Successful implementation of this integrated approach will provide a powerful tool for faster, more accurate and cost-effective screening of potential toxicants and therapeutics. On September 11, 2015, an interdisciplinary group of scientists, engineers, and clinicians gathered for a workshop in Research Triangle Park, North Carolina, to discuss this ambitious goal. Participants represented laboratory-based and computational modeling approaches to pharmacology and toxicology, as well as the pharmaceutical industry, government, non-profits, and academia. Discussions focused on identifying critical system perturbations to model, the computational tools required, and the experimental approaches best suited to generating key data. This consensus report summarizes the discussions held.« less

Workshop Report: Systems Biology for Organotypic Cell Cultures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grego, Sonia; Dougherty, Edward R.; Alexander, Francis Joseph

Translating in vitro biological data into actionable information related to human health holds the potential to improve disease treatment and risk assessment of chemical exposures. While genomics has identified regulatory pathways at the cellular level, translation to the organism level requires a multiscale approach accounting for intra-cellular regulation, inter-cellular interaction, and tissue/organ-level effects. Tissue-level effects can now be probed in vitro thanks to recently developed systems of three-dimensional (3D), multicellular, “organotypic” cell cultures, which mimic functional responses of living tissue. However, there remains a knowledge gap regarding interactions across different biological scales, complicating accurate prediction of health outcomes from molecular/genomicmore » data and tissue responses. Systems biology aims at mathematical modeling of complex, non-linear biological systems. We propose to apply a systems biology approach to achieve a computational representation of tissue-level physiological responses by integrating empirical data derived from organotypic culture systems with computational models of intracellular pathways to better predict human responses. Successful implementation of this integrated approach will provide a powerful tool for faster, more accurate and cost-effective screening of potential toxicants and therapeutics. On September 11, 2015, an interdisciplinary group of scientists, engineers, and clinicians gathered for a workshop in Research Triangle Park, North Carolina, to discuss this ambitious goal. Participants represented laboratory-based and computational modeling approaches to pharmacology and toxicology, as well as the pharmaceutical industry, government, non-profits, and academia. Discussions focused on identifying critical system perturbations to model, the computational tools required, and the experimental approaches best suited to generating key data.« less

Workshop Report: Systems Biology for Organotypic Cell Cultures

DOE PAGES

Grego, Sonia; Dougherty, Edward R.; Alexander, Francis Joseph; ...

2016-11-14

Translating in vitro biological data into actionable information related to human health holds the potential to improve disease treatment and risk assessment of chemical exposures. While genomics has identified regulatory pathways at the cellular level, translation to the organism level requires a multiscale approach accounting for intra-cellular regulation, inter-cellular interaction, and tissue/organ-level effects. Tissue-level effects can now be probed in vitro thanks to recently developed systems of three-dimensional (3D), multicellular, “organotypic” cell cultures, which mimic functional responses of living tissue. However, there remains a knowledge gap regarding interactions across different biological scales, complicating accurate prediction of health outcomes from molecular/genomicmore » data and tissue responses. Systems biology aims at mathematical modeling of complex, non-linear biological systems. We propose to apply a systems biology approach to achieve a computational representation of tissue-level physiological responses by integrating empirical data derived from organotypic culture systems with computational models of intracellular pathways to better predict human responses. Successful implementation of this integrated approach will provide a powerful tool for faster, more accurate and cost-effective screening of potential toxicants and therapeutics. On September 11, 2015, an interdisciplinary group of scientists, engineers, and clinicians gathered for a workshop in Research Triangle Park, North Carolina, to discuss this ambitious goal. Participants represented laboratory-based and computational modeling approaches to pharmacology and toxicology, as well as the pharmaceutical industry, government, non-profits, and academia. Discussions focused on identifying critical system perturbations to model, the computational tools required, and the experimental approaches best suited to generating key data.« less

Systems biology for organotypic cell cultures.

PubMed

Grego, Sonia; Dougherty, Edward R; Alexander, Francis J; Auerbach, Scott S; Berridge, Brian R; Bittner, Michael L; Casey, Warren; Cooley, Philip C; Dash, Ajit; Ferguson, Stephen S; Fennell, Timothy R; Hawkins, Brian T; Hickey, Anthony J; Kleensang, Andre; Liebman, Michael N J; Martin, Florian; Maull, Elizabeth A; Paragas, Jason; Qiao, Guilin Gary; Ramaiahgari, Sreenivasa; Sumner, Susan J; Yoon, Miyoung

2017-01-01

Translating in vitro biological data into actionable information related to human health holds the potential to improve disease treatment and risk assessment of chemical exposures. While genomics has identified regulatory pathways at the cellular level, translation to the organism level requires a multiscale approach accounting for intra-cellular regulation, inter-cellular interaction, and tissue/organ-level effects. Tissue-level effects can now be probed in vitro thanks to recently developed systems of three-dimensional (3D), multicellular, "organotypic" cell cultures, which mimic functional responses of living tissue. However, there remains a knowledge gap regarding interactions across different biological scales, complicating accurate prediction of health outcomes from molecular/genomic data and tissue responses. Systems biology aims at mathematical modeling of complex, non-linear biological systems. We propose to apply a systems biology approach to achieve a computational representation of tissue-level physiological responses by integrating empirical data derived from organotypic culture systems with computational models of intracellular pathways to better predict human responses. Successful implementation of this integrated approach will provide a powerful tool for faster, more accurate and cost-effective screening of potential toxicants and therapeutics. On September 11, 2015, an interdisciplinary group of scientists, engineers, and clinicians gathered for a workshop in Research Triangle Park, North Carolina, to discuss this ambitious goal. Participants represented laboratory-based and computational modeling approaches to pharmacology and toxicology, as well as the pharmaceutical industry, government, non-profits, and academia. Discussions focused on identifying critical system perturbations to model, the computational tools required, and the experimental approaches best suited to generating key data.

Potential Role of Lateral Gene Transfer in the Evolution of Biofilm Communities at the Lost City Hydrothermal Field and in the Earliest Stages of Cellular Evolution

NASA Astrophysics Data System (ADS)

Brazelton, W. J.; Mehta, M. P.; Baross, J. A.

2010-04-01

DNA sequencing and metabolic activity measurements show that lateral gene transfer promotes phenotypic diversity in single-species archaeal biofilms attached to hydrothermal chimneys. This system may be a useful model for early cellular evolution.

Predictive modeling of multicellular structure formation by using Cellular Particle Dynamics simulations

NASA Astrophysics Data System (ADS)

McCune, Matthew; Shafiee, Ashkan; Forgacs, Gabor; Kosztin, Ioan

2014-03-01

Cellular Particle Dynamics (CPD) is an effective computational method for describing and predicting the time evolution of biomechanical relaxation processes of multicellular systems. A typical example is the fusion of spheroidal bioink particles during post bioprinting structure formation. In CPD cells are modeled as an ensemble of cellular particles (CPs) that interact via short-range contact interactions, characterized by an attractive (adhesive interaction) and a repulsive (excluded volume interaction) component. The time evolution of the spatial conformation of the multicellular system is determined by following the trajectories of all CPs through integration of their equations of motion. CPD was successfully applied to describe and predict the fusion of 3D tissue construct involving identical spherical aggregates. Here, we demonstrate that CPD can also predict tissue formation involving uneven spherical aggregates whose volumes decrease during the fusion process. Work supported by NSF [PHY-0957914]. Computer time provided by the University of Missouri Bioinformatics Consortium.

Computational modelling of cellular level metabolism

NASA Astrophysics Data System (ADS)

Calvetti, D.; Heino, J.; Somersalo, E.

2008-07-01

The steady and stationary state inverse problems consist of estimating the reaction and transport fluxes, blood concentrations and possibly the rates of change of some of the concentrations based on data which are often scarce noisy and sampled over a population. The Bayesian framework provides a natural setting for the solution of this inverse problem, because a priori knowledge about the system itself and the unknown reaction fluxes and transport rates can compensate for the insufficiency of measured data, provided that the computational costs do not become prohibitive. This article identifies the computational challenges which have to be met when analyzing the steady and stationary states of multicompartment model for cellular metabolism and suggest stable and efficient ways to handle the computations. The outline of a computational tool based on the Bayesian paradigm for the simulation and analysis of complex cellular metabolic systems is also presented.

An improved cellular automata model for train operation simulation with dynamic acceleration

NASA Astrophysics Data System (ADS)

Li, Wen-Jun; Nie, Lei

2018-03-01

Urban rail transit plays an important role in the urban public traffic because of its advantages of fast speed, large transport capacity, high safety, reliability and low pollution. This study proposes an improved cellular automaton (CA) model by considering the dynamic characteristic of the train acceleration to analyze the energy consumption and train running time. Constructing an effective model for calculating energy consumption to aid train operation improvement is the basis for studying and analyzing energy-saving measures for urban rail transit system operation.

Simulation of the 1992 Tessina landslide by a cellular automata model and future hazard scenarios

NASA Astrophysics Data System (ADS)

Avolio, MV; Di Gregorio, Salvatore; Mantovani, Franco; Pasuto, Alessandro; Rongo, Rocco; Silvano, Sandro; Spataro, William

Cellular Automata are a powerful tool for modelling natural and artificial systems, which can be described in terms of local interactions of their constituent parts. Some types of landslides, such as debris/mud flows, match these requirements. The 1992 Tessina landslide has characteristics (slow mud flows) which make it appropriate for modelling by means of Cellular Automata, except for the initial phase of detachment, which is caused by a rotational movement that has no effect on the mud flow path. This paper presents the Cellular Automata approach for modelling slow mud/debris flows, the results of simulation of the 1992 Tessina landslide and future hazard scenarios based on the volumes of masses that could be mobilised in the future. They were obtained by adapting the Cellular Automata Model called SCIDDICA, which has been validated for very fast landslides. SCIDDICA was applied by modifying the general model to the peculiarities of the Tessina landslide. The simulations obtained by this initial model were satisfactory for forecasting the surface covered by mud. Calibration of the model, which was obtained from simulation of the 1992 event, was used for forecasting flow expansion during possible future reactivation. For this purpose two simulations concerning the collapse of about 1 million m 3 of material were tested. In one of these, the presence of a containment wall built in 1992 for the protection of the Tarcogna hamlet was inserted. The results obtained identified the conditions of high risk affecting the villages of Funes and Lamosano and show that this Cellular Automata approach can have a wide range of applications for different types of mud/debris flows.

Algorithm for cellular reprogramming.

PubMed

Ronquist, Scott; Patterson, Geoff; Muir, Lindsey A; Lindsly, Stephen; Chen, Haiming; Brown, Markus; Wicha, Max S; Bloch, Anthony; Brockett, Roger; Rajapakse, Indika

2017-11-07

The day we understand the time evolution of subcellular events at a level of detail comparable to physical systems governed by Newton's laws of motion seems far away. Even so, quantitative approaches to cellular dynamics add to our understanding of cell biology. With data-guided frameworks we can develop better predictions about, and methods for, control over specific biological processes and system-wide cell behavior. Here we describe an approach for optimizing the use of transcription factors (TFs) in cellular reprogramming, based on a device commonly used in optimal control. We construct an approximate model for the natural evolution of a cell-cycle-synchronized population of human fibroblasts, based on data obtained by sampling the expression of 22,083 genes at several time points during the cell cycle. To arrive at a model of moderate complexity, we cluster gene expression based on division of the genome into topologically associating domains (TADs) and then model the dynamics of TAD expression levels. Based on this dynamical model and additional data, such as known TF binding sites and activity, we develop a methodology for identifying the top TF candidates for a specific cellular reprogramming task. Our data-guided methodology identifies a number of TFs previously validated for reprogramming and/or natural differentiation and predicts some potentially useful combinations of TFs. Our findings highlight the immense potential of dynamical models, mathematics, and data-guided methodologies for improving strategies for control over biological processes. Copyright © 2017 the Author(s). Published by PNAS.

A Real Space Cellular Automaton Laboratory

NASA Astrophysics Data System (ADS)

Rozier, O.; Narteau, C.

2013-12-01

Investigations in geomorphology may benefit from computer modelling approaches that rely entirely on self-organization principles. In the vast majority of numerical models, instead, points in space are characterised by a variety of physical variables (e.g. sediment transport rate, velocity, temperature) recalculated over time according to some predetermined set of laws. However, there is not always a satisfactory theoretical framework from which we can quantify the overall dynamics of the system. For these reasons, we prefer to concentrate on interaction patterns using a basic cellular automaton modelling framework, the Real Space Cellular Automaton Laboratory (ReSCAL), a powerful and versatile generator of 3D stochastic models. The objective of this software suite released under a GNU license is to develop interdisciplinary research collaboration to investigate the dynamics of complex systems. The models in ReSCAL are essentially constructed from a small number of discrete states distributed on a cellular grid. An elementary cell is a real-space representation of the physical environment and pairs of nearest neighbour cells are called doublets. Each individual physical process is associated with a set of doublet transitions and characteristic transition rates. Using a modular approach, we can simulate and combine a wide range of physical, chemical and/or anthropological processes. Here, we present different ingredients of ReSCAL leading to applications in geomorphology: dune morphodynamics and landscape evolution. We also discuss how ReSCAL can be applied and developed across many disciplines in natural and human sciences.

Characterizing emergent properties of immunological systems with multi-cellular rule-based computational modeling.

PubMed

Chavali, Arvind K; Gianchandani, Erwin P; Tung, Kenneth S; Lawrence, Michael B; Peirce, Shayn M; Papin, Jason A

2008-12-01

The immune system is comprised of numerous components that interact with one another to give rise to phenotypic behaviors that are sometimes unexpected. Agent-based modeling (ABM) and cellular automata (CA) belong to a class of discrete mathematical approaches in which autonomous entities detect local information and act over time according to logical rules. The power of this approach lies in the emergence of behavior that arises from interactions between agents, which would otherwise be impossible to know a priori. Recent work exploring the immune system with ABM and CA has revealed novel insights into immunological processes. Here, we summarize these applications to immunology and, particularly, how ABM can help formulate hypotheses that might drive further experimental investigations of disease mechanisms.

Bi-SOC-states in one-dimensional random cellular automaton

NASA Astrophysics Data System (ADS)

Czechowski, Zbigniew; Budek, Agnieszka; Białecki, Mariusz

2017-10-01

Two statistically stationary states with power-law scaling of avalanches are found in a simple 1 D cellular automaton. Features of the fixed points, the spiral saddle and the saddle with index 1, are investigated. The migration of states of the automaton between these two self-organized criticality states is demonstrated during evolution of the system in computer simulations. The automaton, being a slowly driven system, can be applied as a toy model of earthquake supercycles.

GENERAL: A modified weighted probabilistic cellular automaton traffic flow model

NASA Astrophysics Data System (ADS)

Zhuang, Qian; Jia, Bin; Li, Xin-Gang

2009-08-01

This paper modifies the weighted probabilistic cellular automaton model (Li X L, Kuang H, Song T, et al 2008 Chin. Phys. B 17 2366) which considered a diversity of traffic behaviors under real traffic situations induced by various driving characters and habits. In the new model, the effects of the velocity at the last time step and drivers' desire for acceleration are taken into account. The fundamental diagram, spatial-temporal diagram, and the time series of one-minute data are analyzed. The results show that this model reproduces synchronized flow. Finally, it simulates the on-ramp system with the proposed model. Some characteristics including the phase diagram are studied.

Cellular cation transport studied by 6/7Li and 23Na NMR in a porous Mo132 Keplerate type nano-capsule as model system.

PubMed

Rehder, Dieter; Haupt, Erhard T K; Müller, Achim

2008-01-01

Li+ ions can interplay with other cations intrinsically present in the intra- and extra-cellular space (i.e. Na+, K+, Mg2+ and Ca2+) have therapeutic effects (e.g. in the treatment of bipolar disorder) or toxic effects (at higher doses), likely because Li+ interferes with the intra-/extra-cellular concentration gradients of the mentioned physiologically relevant cations. The cellular transmembrane transport can be modelled by molybdenum-oxide-based Keplerates, i.e. nano-sized porous capsules containing 132 Mo centres, monitored through 6/7Li as well as 23Na NMR spectroscopy. The effects on the transport of Li+ cations through the 'ion channels' of these model cells, caused by variations in water amount, temperature, and by the addition of organic cationic 'plugs' and the shift reagent [Dy(PPP)2](7-) are reported. In the investigated solvent systems, water acts as a transport mediator for Li+. Likewise, the counter-transport (Li+/Na+, Li+/K+, Li+/Cs+ and Li+/Ca2+) has been investigated by 7Li NMR and, in the case of Li+/Na+ exchange, by 23Na NMR, and it has been shown that most (in the case of Na+ and K+, all (Ca2+) or almost none (Cs+) of the Li cations is extruded from the internal sites of the artificial cell to the extra-cellular medium, while Na+, K+ and Ca2+ are partially incorporated.

Epigenetic regulation of cell fate reprogramming in aging and disease: A predictive computational model.

PubMed

Folguera-Blasco, Núria; Cuyàs, Elisabet; Menéndez, Javier A; Alarcón, Tomás

2018-03-01

Understanding the control of epigenetic regulation is key to explain and modify the aging process. Because histone-modifying enzymes are sensitive to shifts in availability of cofactors (e.g. metabolites), cellular epigenetic states may be tied to changing conditions associated with cofactor variability. The aim of this study is to analyse the relationships between cofactor fluctuations, epigenetic landscapes, and cell state transitions. Using Approximate Bayesian Computation, we generate an ensemble of epigenetic regulation (ER) systems whose heterogeneity reflects variability in cofactor pools used by histone modifiers. The heterogeneity of epigenetic metabolites, which operates as regulator of the kinetic parameters promoting/preventing histone modifications, stochastically drives phenotypic variability. The ensemble of ER configurations reveals the occurrence of distinct epi-states within the ensemble. Whereas resilient states maintain large epigenetic barriers refractory to reprogramming cellular identity, plastic states lower these barriers, and increase the sensitivity to reprogramming. Moreover, fine-tuning of cofactor levels redirects plastic epigenetic states to re-enter epigenetic resilience, and vice versa. Our ensemble model agrees with a model of metabolism-responsive loss of epigenetic resilience as a cellular aging mechanism. Our findings support the notion that cellular aging, and its reversal, might result from stochastic translation of metabolic inputs into resilient/plastic cell states via ER systems.

Emergent 1d Ising Behavior in AN Elementary Cellular Automaton Model

NASA Astrophysics Data System (ADS)

Kassebaum, Paul G.; Iannacchione, Germano S.

The fundamental nature of an evolving one-dimensional (1D) Ising model is investigated with an elementary cellular automaton (CA) simulation. The emergent CA simulation employs an ensemble of cells in one spatial dimension, each cell capable of two microstates interacting with simple nearest-neighbor rules and incorporating an external field. The behavior of the CA model provides insight into the dynamics of coupled two-state systems not expressible by exact analytical solutions. For instance, state progression graphs show the causal dynamics of a system through time in relation to the system's entropy. Unique graphical analysis techniques are introduced through difference patterns, diffusion patterns, and state progression graphs of the 1D ensemble visualizing the evolution. All analyses are consistent with the known behavior of the 1D Ising system. The CA simulation and new pattern recognition techniques are scalable (in both dimension, complexity, and size) and have many potential applications such as complex design of materials, control of agent systems, and evolutionary mechanism design.

Cellular automata and its applications in protein bioinformatics.

PubMed

Xiao, Xuan; Wang, Pu; Chou, Kuo-Chen

2011-09-01

With the explosion of protein sequences generated in the postgenomic era, it is highly desirable to develop high-throughput tools for rapidly and reliably identifying various attributes of uncharacterized proteins based on their sequence information alone. The knowledge thus obtained can help us timely utilize these newly found protein sequences for both basic research and drug discovery. Many bioinformatics tools have been developed by means of machine learning methods. This review is focused on the applications of a new kind of science (cellular automata) in protein bioinformatics. A cellular automaton (CA) is an open, flexible and discrete dynamic model that holds enormous potentials in modeling complex systems, in spite of the simplicity of the model itself. Researchers, scientists and practitioners from different fields have utilized cellular automata for visualizing protein sequences, investigating their evolution processes, and predicting their various attributes. Owing to its impressive power, intuitiveness and relative simplicity, the CA approach has great potential for use as a tool for bioinformatics.

2012 Gordon Research Conference on Cellular and Molecular Fungal Biology, Final Progress Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Berman, Judith

The Gordon Research Conference on Cellular and Molecular Fungal Biology was held at Holderness School, Holderness New Hampshire, June 17 - 22, 2012. The 2012 Gordon Conference on Cellular and Molecular Fungal Biology (CMFB) will present the latest, cutting-edge research on the exciting and growing field of molecular and cellular aspects of fungal biology. Topics will range from yeast to filamentous fungi, from model systems to economically important organisms, and from saprophytes and commensals to pathogens of plants and animals. The CMFB conference will feature a wide range of topics including systems biology, cell biology and morphogenesis, organismal interactions, genomemore » organisation and regulation, pathogenesis, energy metabolism, biomass production and population genomics. The Conference was well-attended with 136 participants. Gordon Research Conferences does not permit publication of meeting proceedings.« less

A pharma perspective on the systems medicine and pharmacology of inflammation.

PubMed

Lahoz-Beneytez, Julio; Schnizler, Katrin; Eissing, Thomas

2015-02-01

Biological systems are complex and comprehend multiple scales of organisation. Hence, holistic approaches are necessary to capture the behaviour of these entities from the molecular and cellular to the whole organism level. This also applies to the understanding and treatment of different diseases. Traditional systems biology has been successful in describing different biological phenomena at the cellular level, but it still lacks of a holistic description of the multi-scale interactions within the body. The importance of the physiological context is of particular interest in inflammation. Regulatory agencies have urged the scientific community to increase the translational power of bio-medical research and it has been recognised that modelling and simulation could be a path to follow. Interestingly, in pharma R&D, modelling and simulation has been employed since a long time ago. Systems pharmacology, and particularly physiologically based pharmacokinetic/pharmacodynamic models, serve as a suitable framework to integrate the available and emerging knowledge at different levels of the drug development process. Systems medicine and pharmacology of inflammation will potentially benefit from this framework in order to better understand inflammatory diseases and to help to transfer the vast knowledge on the molecular and cellular level into a more physiological context. Ultimately, this may lead to reliable predictions of clinical outcomes such as disease progression or treatment efficacy, contributing thereby to a better care of patients. Copyright © 2014 Elsevier Inc. All rights reserved.

Optimizing Cellular Networks Enabled with Renewal Energy via Strategic Learning.

PubMed

Sohn, Insoo; Liu, Huaping; Ansari, Nirwan

2015-01-01

An important issue in the cellular industry is the rising energy cost and carbon footprint due to the rapid expansion of the cellular infrastructure. Greening cellular networks has thus attracted attention. Among the promising green cellular network techniques, the renewable energy-powered cellular network has drawn increasing attention as a critical element towards reducing carbon emissions due to massive energy consumption in the base stations deployed in cellular networks. Game theory is a branch of mathematics that is used to evaluate and optimize systems with multiple players with conflicting objectives and has been successfully used to solve various problems in cellular networks. In this paper, we model the green energy utilization and power consumption optimization problem of a green cellular network as a pilot power selection strategic game and propose a novel distributed algorithm based on a strategic learning method. The simulation results indicate that the proposed algorithm achieves correlated equilibrium of the pilot power selection game, resulting in optimum green energy utilization and power consumption reduction.

Amyotrophic lateral sclerosis: cell vulnerability or system vulnerability?

PubMed

Talbot, Kevin

2014-01-01

Amyotrophic lateral sclerosis (ALS) is a complex neurodegenerative disease with clinical, pathological and genetic overlap with frontotemporal dementia (FTD). No longer viewed as one disease with a single unified cause, ALS is now considered to be a clinicopathological syndrome resulting from a complex convergence of genetic susceptibility, age-related loss of cellular homeostasis, and possible environmental influences. The rapid increase in recent years of the number of genes in which mutations have been associated with ALS has led to in vitro and in vivo models that have generated a wealth of data indicating disruption of specific biochemical pathways and sub-cellular compartments. Data implicating pathways including protein misfolding, mRNA splicing, oxidative stress, proteosome and mitochondrial dysfunction in the pathogenesis of ALS reinforce a disease model based on selective age-dependent vulnerability of a specific population of cells. To the clinical neurologist, however, ALS presents as a disease of focal onset and contiguous spread. Characteristic regional patterns of involvement and progression suggest that the disease does not proceed randomly but via a restricted number of anatomical pathways. These clinical observations combined with electrophysiological and brain-imaging studies underpin the concept of ALS at the macroscopic level as a 'system degeneration'. This dichotomy between cellular and systems neurobiology raises the fundamental questions of what initiates the disease process in a specific anatomical site and how the disease is propagated. Is the essence of ALS a cell-to-cell transmission of pathology with, for example, a 'prion-like' mechanism, or does the cellular pathology follow degeneration of specific synaptic networks? Elucidating the interaction between cellular degeneration and system level degeneration will aid modeling of the disease in the earliest phases, improve the development of sensitive markers of disease progression and response to therapy, and expand our understanding of the biological basis of clinical and pathological heterogeneity. © 2013 Anatomical Society.

A cellular automaton for the signed particle formulation of quantum mechanics

NASA Astrophysics Data System (ADS)

Sellier, J. M.; Kapanova, K. G.; Dimov, I.

2017-02-01

Recently, a new formulation of quantum mechanics, based on the concept of signed particles, has been suggested. In this paper, we introduce a cellular automaton which mimics the dynamics of quantum objects in the phase-space in a time-dependent fashion. This is twofold: it provides a simplified and accessible language to non-physicists who wants to simulate quantum mechanical systems, at the same time it enables a different way to explore the laws of Physics. Moreover, it opens the way towards hybrid simulations of quantum systems by combining full quantum models with cellular automata when the former fail. In order to show the validity of the suggested cellular automaton and its combination with the signed particle formalism, several numerical experiments are performed, showing very promising results. Being this article a preliminary study on quantum simulations in phase-space by means of cellular automata, some conclusions are drawn about the encouraging results obtained so far and the possible future developments.

Exploring Autophagy in Drosophila

PubMed Central

Juhász, Gábor

2017-01-01

Autophagy is a catabolic process in eukaryotic cells promoting bulk or selective degradation of cellular components within lysosomes. In recent decades, several model systems were utilized to dissect the molecular machinery of autophagy and to identify the impact of this cellular “self-eating” process on various physiological and pathological processes. Here we briefly discuss the advantages and limitations of using the fruit fly Drosophila melanogaster, a popular model in cell and developmental biology, to apprehend the main pathway of autophagy in a complete animal. PMID:28704946

CATS - A process-based model for turbulent turbidite systems at the reservoir scale

NASA Astrophysics Data System (ADS)

Teles, Vanessa; Chauveau, Benoît; Joseph, Philippe; Weill, Pierre; Maktouf, Fakher

2016-09-01

The Cellular Automata for Turbidite systems (CATS) model is intended to simulate the fine architecture and facies distribution of turbidite reservoirs with a multi-event and process-based approach. The main processes of low-density turbulent turbidity flow are modeled: downslope sediment-laden flow, entrainment of ambient water, erosion and deposition of several distinct lithologies. This numerical model, derived from (Salles, 2006; Salles et al., 2007), proposes a new approach based on the Rouse concentration profile to consider the flow capacity to carry the sediment load in suspension. In CATS, the flow distribution on a given topography is modeled with local rules between neighboring cells (cellular automata) based on potential and kinetic energy balance and diffusion concepts. Input parameters are the initial flow parameters and a 3D topography at depositional time. An overview of CATS capabilities in different contexts is presented and discussed.

Network representations of immune system complexity

PubMed Central

Subramanian, Naeha; Torabi-Parizi, Parizad; Gottschalk, Rachel A.; Germain, Ronald N.; Dutta, Bhaskar

2015-01-01

The mammalian immune system is a dynamic multi-scale system composed of a hierarchically organized set of molecular, cellular and organismal networks that act in concert to promote effective host defense. These networks range from those involving gene regulatory and protein-protein interactions underlying intracellular signaling pathways and single cell responses to increasingly complex networks of in vivo cellular interaction, positioning and migration that determine the overall immune response of an organism. Immunity is thus not the product of simple signaling events but rather non-linear behaviors arising from dynamic, feedback-regulated interactions among many components. One of the major goals of systems immunology is to quantitatively measure these complex multi-scale spatial and temporal interactions, permitting development of computational models that can be used to predict responses to perturbation. Recent technological advances permit collection of comprehensive datasets at multiple molecular and cellular levels while advances in network biology support representation of the relationships of components at each level as physical or functional interaction networks. The latter facilitate effective visualization of patterns and recognition of emergent properties arising from the many interactions of genes, molecules, and cells of the immune system. We illustrate the power of integrating ‘omics’ and network modeling approaches for unbiased reconstruction of signaling and transcriptional networks with a focus on applications involving the innate immune system. We further discuss future possibilities for reconstruction of increasingly complex cellular and organism-level networks and development of sophisticated computational tools for prediction of emergent immune behavior arising from the concerted action of these networks. PMID:25625853

A Mathematical Model to study the Dynamics of Epithelial Cellular Networks

PubMed Central

Abate, Alessandro; Vincent, Stéphane; Dobbe, Roel; Silletti, Alberto; Master, Neal; Axelrod, Jeffrey D.; Tomlin, Claire J.

2013-01-01

Epithelia are sheets of connected cells that are essential across the animal kingdom. Experimental observations suggest that the dynamical behavior of many single-layered epithelial tissues has strong analogies with that of specific mechanical systems, namely large networks consisting of point masses connected through spring-damper elements and undergoing the influence of active and dissipating forces. Based on this analogy, this work develops a modeling framework to enable the study of the mechanical properties and of the dynamic behavior of large epithelial cellular networks. The model is built first by creating a network topology that is extracted from the actual cellular geometry as obtained from experiments, then by associating a mechanical structure and dynamics to the network via spring-damper elements. This scalable approach enables running simulations of large network dynamics: the derived modeling framework in particular is predisposed to be tailored to study general dynamics (for example, morphogenesis) of various classes of single-layered epithelial cellular networks. In this contribution we test the model on a case study of the dorsal epithelium of the Drosophila melanogaster embryo during early dorsal closure (and, less conspicuously, germband retraction). PMID:23221083

Drosophila as a model system to study autophagy.

PubMed

Zirin, Jonathan; Perrimon, Norbert

2010-12-01

Originally identified as a response to starvation in yeast, autophagy is now understood to fulfill a variety of roles in higher eukaryotes, from the maintenance of cellular homeostasis to the cellular response to stress, starvation, and infection. Although genetics and biochemical studies in yeast have identified many components involved in autophagy, the findings that some of the essential components of the yeast pathway are missing in higher organisms underscore the need to study autophagy in more complex systems. This review focuses on the use of the fruitfly, Drosophila melanogaster as a model system for analysis of autophagy. Drosophila is an organism well-suited for genetic analysis and represents an intermediate between yeast and mammals with respect to conservation of the autophagy machinery. Furthermore, the complex biology and physiology of Drosophila presents an opportunity to model human diseases in a tissue specific and analogous context.

Study on queueing behavior in pedestrian evacuation by extended cellular automata model

NASA Astrophysics Data System (ADS)

Hu, Jun; You, Lei; Zhang, Hong; Wei, Juan; Guo, Yangyong

2018-01-01

This paper proposes a pedestrian evacuation model for effective simulation of evacuation efficiency based on extended cellular automata. In the model, pedestrians' momentary transition probability to a target position is defined in terms of the floor field and queueing time, and the critical time is defined as the waiting time threshold in a queue. Queueing time and critical time are derived using Fractal Brownian Motion through analysis of pedestrian arrival characteristics. Simulations using the platform and actual evacuations were conducted to study the relationships among system evacuation time, average system velocity, pedestrian density, flow rate, and critical time. The results demonstrate that at low pedestrian density, evacuation efficiency can be improved through adoption of the shortest route strategy, and critical time has an inverse relationship with average system velocity. Conversely, at higher pedestrian densities, it is better to adopt the shortest queueing time strategy, and critical time is inversely related to flow rate.

Soliton cellular automaton associated with Dn(1)-crystal B2,s

NASA Astrophysics Data System (ADS)

Misra, Kailash C.; Wilson, Evan A.

2013-04-01

A solvable vertex model in ferromagnetic regime gives rise to a soliton cellular automaton which is a discrete dynamical system in which site variables take on values in a finite set. We study the scattering of a class of soliton cellular automata associated with the U_q(D_n^{(1)})-perfect crystal B2, s. We calculate the combinatorial R matrix for all elements of B2, s ⊗ B2, 1. In particular, we show that the scattering rule for our soliton cellular automaton can be identified with the combinatorial R matrix for U_q(A_1^{(1)}) oplus U_q(D_{n-2}^{(1)})-crystals.

Interface Pattern Selection in Directional Solidification

NASA Technical Reports Server (NTRS)

Trivedi, Rohit; Tewari, Surendra N.

2001-01-01

The central focus of this research is to establish key scientific concepts that govern the selection of cellular and dendritic patterns during the directional solidification of alloys. Ground-based studies have established that the conditions under which cellular and dendritic microstructures form are precisely where convection effects are dominant in bulk samples. Thus, experimental data can not be obtained terrestrially under pure diffusive regime. Furthermore, reliable theoretical models are not yet possible which can quantitatively incorporate fluid flow in the pattern selection criterion. Consequently, microgravity experiments on cellular and dendritic growth are designed to obtain benchmark data under diffusive growth conditions that can be quantitatively analyzed and compared with the rigorous theoretical model to establish the fundamental principles that govern the selection of specific microstructure and its length scales. In the cellular structure, different cells in an array are strongly coupled so that the cellular pattern evolution is controlled by complex interactions between thermal diffusion, solute diffusion and interface effects. These interactions give infinity of solutions, and the system selects only a narrow band of solutions. The aim of this investigation is to obtain benchmark data and develop a rigorous theoretical model that will allow us to quantitatively establish the physics of this selection process.

Cellular and Molecular Mechanisms of Sexual Differentiation in the Mammalian Nervous System

PubMed Central

Forger, Nancy G.; Strahan, J. Alex; Castillo-Ruiz, Alexandra

2016-01-01

Neuroscientists are likely to discover new sex differences in the coming years, spurred by the National Institutes of Health initiative to include both sexes in preclinical studies. This review summarizes the current state of knowledge of the cellular and molecular mechanisms underlying sex differences in the mammalian nervous system, based primarily on work in rodents. Cellular mechanisms examined include neurogenesis, migration, the differentiation of neurochemical and morphological cell phenotype, and cell death. At the molecular level we discuss evolving roles for epigenetics, sex chromosome complement, the immune system, and newly identified cell signaling pathways. We review recent findings on the role of the environment, as well as genome-wide studies with some surprising results, causing us to rethink often-used models of sexual differentiation. We end by pointing to future directions, including an increased awareness of the important contributions of tissues outside of the nervous system to sexual differentiation of the brain. PMID:26790970

Ciona as a Simple Chordate Model for Heart Development and Regeneration

PubMed Central

Evans Anderson, Heather; Christiaen, Lionel

2016-01-01

Cardiac cell specification and the genetic determinants that govern this process are highly conserved among Chordates. Recent studies have established the importance of evolutionarily-conserved mechanisms in the study of congenital heart defects and disease, as well as cardiac regeneration. As a basal Chordate, the Ciona model system presents a simple scaffold that recapitulates the basic blueprint of cardiac development in Chordates. Here we will focus on the development and cellular structure of the heart of the ascidian Ciona as compared to other Chordates, principally vertebrates. Comparison of the Ciona model system to heart development in other Chordates presents great potential for dissecting the genetic mechanisms that underlie congenital heart defects and disease at the cellular level and might provide additional insight into potential pathways for therapeutic cardiac regeneration. PMID:27642586

Combining cellular automata and Lattice Boltzmann method to model multiscale avascular tumor growth coupled with nutrient diffusion and immune competition.

PubMed

Alemani, Davide; Pappalardo, Francesco; Pennisi, Marzio; Motta, Santo; Brusic, Vladimir

2012-02-28

In the last decades the Lattice Boltzmann method (LB) has been successfully used to simulate a variety of processes. The LB model describes the microscopic processes occurring at the cellular level and the macroscopic processes occurring at the continuum level with a unique function, the probability distribution function. Recently, it has been tried to couple deterministic approaches with probabilistic cellular automata (probabilistic CA) methods with the aim to model temporal evolution of tumor growths and three dimensional spatial evolution, obtaining hybrid methodologies. Despite the good results attained by CA-PDE methods, there is one important issue which has not been completely solved: the intrinsic stochastic nature of the interactions at the interface between cellular (microscopic) and continuum (macroscopic) level. CA methods are able to cope with the stochastic phenomena because of their probabilistic nature, while PDE methods are fully deterministic. Even if the coupling is mathematically correct, there could be important statistical effects that could be missed by the PDE approach. For such a reason, to be able to develop and manage a model that takes into account all these three level of complexity (cellular, molecular and continuum), we believe that PDE should be replaced with a statistic and stochastic model based on the numerical discretization of the Boltzmann equation: The Lattice Boltzmann (LB) method. In this work we introduce a new hybrid method to simulate tumor growth and immune system, by applying Cellular Automata Lattice Boltzmann (CA-LB) approach. Copyright © 2011 Elsevier B.V. All rights reserved.

Three-dimensional slice cultures from murine fetal gut for investigations of the enteric nervous system.

PubMed

Metzger, Marco; Bareiss, Petra M; Nikolov, Ivan; Skutella, Thomas; Just, Lothar

2007-01-01

Three-dimensional intestinal cultures offer new possibilities for the examination of growth potential, analysis of time specific gene expression, and spatial cellular arrangement of enteric nervous system in an organotypical environment. We present an easy to produce in vitro model of the enteric nervous system for analysis and manipulation of cellular differentiation processes. Slice cultures of murine fetal colon were cultured on membrane inserts for up to 2 weeks without loss of autonomous contractility. After slice preparation, cultured tissue reorganized within the first days in vitro. Afterward, the culture possessed more than 35 cell layers, including high prismatic epithelial cells, smooth muscle cells, glial cells, and neurons analyzed by immunohistochemistry. The contraction frequency of intestinal slice culture could be modulated by the neurotransmitter serotonin and the sodium channel blocker tetrodotoxin. Coculture experiments with cultured neurospheres isolated from enhanced green fluorescent protein (eGFP) transgenic mice demonstrated that differentiating eGFP-positive neurons were integrated into the intestinal tissue culture. This slice culture model of enteric nervous system proved to be useful for studying cell-cell interactions, cellular signaling, and cell differentiation processes in a three-dimensional cell arrangement.

Multi-Scale Modeling in Morphogenesis: A Critical Analysis of the Cellular Potts Model

PubMed Central

Voss-Böhme, Anja

2012-01-01

Cellular Potts models (CPMs) are used as a modeling framework to elucidate mechanisms of biological development. They allow a spatial resolution below the cellular scale and are applied particularly when problems are studied where multiple spatial and temporal scales are involved. Despite the increasing usage of CPMs in theoretical biology, this model class has received little attention from mathematical theory. To narrow this gap, the CPMs are subjected to a theoretical study here. It is asked to which extent the updating rules establish an appropriate dynamical model of intercellular interactions and what the principal behavior at different time scales characterizes. It is shown that the longtime behavior of a CPM is degenerate in the sense that the cells consecutively die out, independent of the specific interdependence structure that characterizes the model. While CPMs are naturally defined on finite, spatially bounded lattices, possible extensions to spatially unbounded systems are explored to assess to which extent spatio-temporal limit procedures can be applied to describe the emergent behavior at the tissue scale. To elucidate the mechanistic structure of CPMs, the model class is integrated into a general multiscale framework. It is shown that the central role of the surface fluctuations, which subsume several cellular and intercellular factors, entails substantial limitations for a CPM's exploitation both as a mechanistic and as a phenomenological model. PMID:22984409

ISD3: a particokinetic model for predicting the combined effects of particle sedimentation, diffusion and dissolution on cellular dosimetry for in vitro systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thomas, Dennis G.; Smith, Jordan N.; Thrall, Brian D.

The development of particokinetic models describing the delivery of insoluble or poorly soluble nanoparticles to cells in liquid cell culture systems has improved the basis for dose-response analysis, hazard ranking from high-throughput systems, and now allows for translation of exposures across in vitro and in vivo test systems. Complimentary particokinetic models that address processes controlling delivery of both particles and released ions to cells, and the influence of particle size changes from dissolution on particle delivery for cell-culture systems would help advance our understanding of the role of particles ion dosimetry on cellular toxicology. We developed ISD3, an extension ofmore » our previously published model for insoluble particles, by deriving a specific formulation of the Population Balance Equation for soluble particles. ISD3 describes the time, concentration and particle size dependent dissolution of particles, their delivery to cells, and the delivery and uptake of ions to cells in in vitro liquid test systems. The model is modular, and can be adapted by application of any empirical model of dissolution, alternative approaches to calculating sedimentation rates, and cellular uptake or treatment of boundary conditions. We apply the model to calculate the particle and ion dosimetry of nanosilver and silver ions in vitro after calibration of two empirical models, one for particle dissolution and one for ion uptake. The results demonstrate utility and accuracy of the ISD3 framework for dosimetry in these systems. Total media ion concentration, particle concentration and total cell-associated silver time-courses were well described by the model, across 2 concentrations of 20 and 110 nm particles. ISD3 was calibrated to dissolution data for 20 nm particles as a function of serum protein concentration, but successfully described the media and cell dosimetry time-course for both particles at all concentrations and time points. We also report the finding that protein content in media has effects both on the initial rate of dissolution and the resulting near-steady state ion concentration in solution.« less

Development of a Sox2 reporter system modeling cellular heterogeneity in glioma.

PubMed

Stoltz, Kevin; Sinyuk, Maksim; Hale, James S; Wu, Qiulian; Otvos, Balint; Walker, Kiera; Vasanji, Amit; Rich, Jeremy N; Hjelmeland, Anita B; Lathia, Justin D

2015-03-01

Malignant gliomas are complex systems containing a number of factors that drive tumor initiation and progression, including genetic aberrations that lead to extensive cellular heterogeneity within the neoplastic compartment. Mouse models recapitulate these genetic aberrations, but readily observable heterogeneity remains challenging. To interrogate cellular heterogeneity in mouse glioma models, we utilized a replication-competent avian sarcoma-leukosis virus long terminal repeat with splice acceptor/tumor virus A (RCAS-tva) system to generate spontaneous mouse gliomas that contained a Sox2-enhanced green fluorescent protein (EGFP) reporter. Glial fibrillary acidic protein-tva mice were crossed with Sox2-EGFP mice, and tumors were initiated that contained a subpopulation of Sox2-EGFP-high cells enriched for tumor-initiating cell properties such as self-renewal, multilineage differentiation potential, and perivascular localization. Following implantation into recipient mice, Sox2-EGFP-high cells generated tumors containing Sox2-EGFP-high and Sox2-EGFP-low cells. Kinomic analysis of Sox2-EGFP-high cells revealed activation of known glioma signaling pathways that are strongly correlated with patient survival including platelet-derived growth factor receptor beta, phosphoinositide-3 kinase, and vascular endothelial growth factor. Our functional analysis identified active feline sarcoma (Fes) signaling in Sox2-EGFP-high cells. Fes negatively correlated with glioma patient survival and was coexpressed with Sox2-positive cells in glioma xenografts and primary patient-derived tissue. Our RCAS-tva/Sox2-EGFP model will empower closer examination of cellular heterogeneity and will be useful for identifying novel glioma pathways as well as testing preclinical treatment efficacy. © The Author(s) 2014. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Rule-Based Simulation of Multi-Cellular Biological Systems—A Review of Modeling Techniques

PubMed Central

Hwang, Minki; Garbey, Marc; Berceli, Scott A.; Tran-Son-Tay, Roger

2011-01-01

Emergent behaviors of multi-cellular biological systems (MCBS) result from the behaviors of each individual cells and their interactions with other cells and with the environment. Modeling MCBS requires incorporating these complex interactions among the individual cells and the environment. Modeling approaches for MCBS can be grouped into two categories: continuum models and cell-based models. Continuum models usually take the form of partial differential equations, and the model equations provide insight into the relationship among the components in the system. Cell-based models simulate each individual cell behavior and interactions among them enabling the observation of the emergent system behavior. This review focuses on the cell-based models of MCBS, and especially, the technical aspect of the rule-based simulation method for MCBS is reviewed. How to implement the cell behaviors and the interactions with other cells and with the environment into the computational domain is discussed. The cell behaviors reviewed in this paper are division, migration, apoptosis/necrosis, and differentiation. The environmental factors such as extracellular matrix, chemicals, microvasculature, and forces are also discussed. Application examples of these cell behaviors and interactions are presented. PMID:21369345

Computational Neuroscience.

ERIC Educational Resources Information Center

Sejnowski, Terrence J.; And Others

1988-01-01

Describes the use of brain models to connect the microscopic level accessible by molecular and cellular techniques with the systems level accessible by the study of behavior. Discusses classes of brain models, and specific examples of such models. Evaluates the strengths and weaknesses of using brain modelling to understand human brain function.…

Development and Use of the Lens Epithelial Explant System to Study Lens Differentiation and Cataractogenesis

PubMed Central

West-Mays, Judith A.; Pino, Guiseppe; Lovicu, Frank J.

2010-01-01

Over the last two decades much progress has been made in identifying and characterizing many of the molecules involved in understanding normal lens biology and its pathology. Much of this has been made possible through the establishment and use of the lens epithelial explant system. This simplistic tissue culture model, comprised of a sheet of lens epithelium on its native substratum, has been used effectively to study many cellular processes, including lens epithelial cell proliferation, fiber cell differentiation, cell apoptosis as well as epithelial to mesenchymal transformation of cells. In doing so, a number of key growth factors and cytokines, including members of the FGF, Wnt and TGFβ family have been shown to play essential roles in many of these cellular events. This has led to further studies exploring the signaling pathways downstream of these molecules in the lens, paving the way for the development of a number of in situ models (primarily transgenic mouse lines) to further explore in more detail the nature of these molecular and cellular interactions. To reciprocate, the lens epithelial explant system is increasingly being used to further characterize the nature of many complex phenotypes and pathologies observed in these in situ models, allowing us to selectively isolate and examine the direct impact of an individual molecule on a specific cellular response in lens cells. There is no question that the lens epithelial explant system has served as a powerful tool to further our understanding of lens biology and pathology, and there is no doubt that it will continue to serve in such a capacity, as new developments are realized and putative treatments for aberrant lens cell behaviour are to be trialed. PMID:20006728

Feeding behavior of Aplysia: a model system for comparing cellular mechanisms of classical and operant conditioning.

PubMed

Baxter, Douglas A; Byrne, John H

2006-01-01

Feeding behavior of Aplysia provides an excellent model system for analyzing and comparing mechanisms underlying appetitive classical conditioning and reward operant conditioning. Behavioral protocols have been developed for both forms of associative learning, both of which increase the occurrence of biting following training. Because the neural circuitry that mediates the behavior is well characterized and amenable to detailed cellular analyses, substantial progress has been made toward a comparative analysis of the cellular mechanisms underlying these two forms of associative learning. Both forms of associative learning use the same reinforcement pathway (the esophageal nerve, En) and the same reinforcement transmitter (dopamine, DA). In addition, at least one cellular locus of plasticity (cell B51) is modified by both forms of associative learning. However, the two forms of associative learning have opposite effects on B51. Classical conditioning decreases the excitability of B51, whereas operant conditioning increases the excitability of B51. Thus, the approach of using two forms of associative learning to modify a single behavior, which is mediated by an analytically tractable neural circuit, is revealing similarities and differences in the mechanisms that underlie classical and operant conditioning.

A cardiac electrical activity model based on a cellular automata system in comparison with neural network model.

PubMed

Khan, Muhammad Sadiq Ali; Yousuf, Sidrah

2016-03-01

Cardiac Electrical Activity is commonly distributed into three dimensions of Cardiac Tissue (Myocardium) and evolves with duration of time. The indicator of heart diseases can occur randomly at any time of a day. Heart rate, conduction and each electrical activity during cardiac cycle should be monitor non-invasively for the assessment of "Action Potential" (regular) and "Arrhythmia" (irregular) rhythms. Many heart diseases can easily be examined through Automata model like Cellular Automata concepts. This paper deals with the different states of cardiac rhythms using cellular automata with the comparison of neural network also provides fast and highly effective stimulation for the contraction of cardiac muscles on the Atria in the result of genesis of electrical spark or wave. The specific formulated model named as "States of automaton Proposed Model for CEA (Cardiac Electrical Activity)" by using Cellular Automata Methodology is commonly shows the three states of cardiac tissues conduction phenomena (i) Resting (Relax and Excitable state), (ii) ARP (Excited but Absolutely refractory Phase i.e. Excited but not able to excite neighboring cells) (iii) RRP (Excited but Relatively Refractory Phase i.e. Excited and able to excite neighboring cells). The result indicates most efficient modeling with few burden of computation and it is Action Potential during the pumping of blood in cardiac cycle.

Time-spatial model on the dynamics of the proliferation of Aedes aegypti

NASA Astrophysics Data System (ADS)

Gouvêa, Maury Meirelles, Jr.

2017-03-01

Some complex physical systems, such as cellular regulation, ecosystems, and societies, can be represented by local interactions between agents. Then, complex behaviors may emerge. A cellular automaton is a discrete dynamic system with these features. Among the several complex systems, epidemic diseases are given special attention by researchers with respect to their dynamics. Understanding the behavior of an epidemic may well benefit a society. For instance, different proliferation scenarios may be produced and a prevention policy set. This paper presents a new simulation method of the time-spatial spread of the Dengue mosquito with a cellular automaton. Thus, it will be possible to create different dissemination scenarios and preventive policies for these in several regions. Simulations were performed with different initial conditions and parameters as a result of which the behavior of the proposed method was characterized.

Feeding Behavior of Aplysia: A Model System for Comparing Cellular Mechanisms of Classical and Operant Conditioning

ERIC Educational Resources Information Center

Baxter, Douglas A.; Byrne, John H.

2006-01-01

Feeding behavior of Aplysia provides an excellent model system for analyzing and comparing mechanisms underlying appetitive classical conditioning and reward operant conditioning. Behavioral protocols have been developed for both forms of associative learning, both of which increase the occurrence of biting following training. Because the neural…

Systems metabolic engineering: genome-scale models and beyond.

PubMed

Blazeck, John; Alper, Hal

2010-07-01

The advent of high throughput genome-scale bioinformatics has led to an exponential increase in available cellular system data. Systems metabolic engineering attempts to use data-driven approaches--based on the data collected with high throughput technologies--to identify gene targets and optimize phenotypical properties on a systems level. Current systems metabolic engineering tools are limited for predicting and defining complex phenotypes such as chemical tolerances and other global, multigenic traits. The most pragmatic systems-based tool for metabolic engineering to arise is the in silico genome-scale metabolic reconstruction. This tool has seen wide adoption for modeling cell growth and predicting beneficial gene knockouts, and we examine here how this approach can be expanded for novel organisms. This review will highlight advances of the systems metabolic engineering approach with a focus on de novo development and use of genome-scale metabolic reconstructions for metabolic engineering applications. We will then discuss the challenges and prospects for this emerging field to enable model-based metabolic engineering. Specifically, we argue that current state-of-the-art systems metabolic engineering techniques represent a viable first step for improving product yield that still must be followed by combinatorial techniques or random strain mutagenesis to achieve optimal cellular systems.

Path loss analysis in millimeter wave cellular systems for urban mobile communications

NASA Astrophysics Data System (ADS)

Rajagopalan, Ramesh; Hoffman, Mitchell

2016-09-01

The proliferation in the number of mobile devices and developments in cellular technology has led to an ever increasing demand for mobile data. The global bandwidth shortage facing wireless carriers today has motivated research for fifth generation (5G) cellular systems. In recent years, millimeter wave (mmW) frequencies between 30 and 300 GHz are being considered as a promising technology for 5G systems. Such systems can offer superior user experience by providing data rates that exceed one Gigabit per second and latencies lower than a millisecond. However, there is little research about cellular mmW propagation in densely populated urban environments. Understanding the radio channel is a primary requirement for optimal design of mmW systems. Radio propagation in mmW systems faces significant challenges due to rapidly varying channel conditions and intermittent connectivity. In this paper, we study the propagation of mmW spectrum in an urban environment. We use a statistical model to simulate an urban environment with diverse building distributions. We perform extensive simulations to analyze the path loss behavior for both line of sight (LOS) and non line of sight (NLOS) conditions for 28 GHZ and 73 GHZ mmW frequencies. We observe that the path loss approximates a logarithmic fit for both LOS and NLOS environments. Our simulations show that the omnidirectional free space path loss is approximately 30 dB higher for mmW systems compared to current 3G PP cellular systems. To address this challenge, we propose using highly directional horn antennas with beam forming for reducing the path loss.

47 CFR 90.672 - Unacceptable interference to non-cellular 800 MHz licensees from 800 MHz cellular systems or part...

Code of Federal Regulations, 2011 CFR

2011-10-01

... MHz licensees from 800 MHz cellular systems or part 22 Cellular Radiotelephone systems, and within the... COMMUNICATIONS COMMISSION (CONTINUED) SAFETY AND SPECIAL RADIO SERVICES PRIVATE LAND MOBILE RADIO SERVICES... licensees from 800 MHz cellular systems or part 22 Cellular Radiotelephone systems, and within the 900 MHz...

Engineering challenges of BioNEMS: the integration of microfluidics, micro- and nanodevices, models and external control for systems biology.

PubMed

Wikswo, J P; Prokop, A; Baudenbacher, F; Cliffel, D; Csukas, B; Velkovsky, M

2006-08-01

Systems biology, i.e. quantitative, postgenomic, postproteomic, dynamic, multiscale physiology, addresses in an integrative, quantitative manner the shockwave of genetic and proteomic information using computer models that may eventually have 10(6) dynamic variables with non-linear interactions. Historically, single biological measurements are made over minutes, suggesting the challenge of specifying 10(6) model parameters. Except for fluorescence and micro-electrode recordings, most cellular measurements have inadequate bandwidth to discern the time course of critical intracellular biochemical events. Micro-array expression profiles of thousands of genes cannot determine quantitative dynamic cellular signalling and metabolic variables. Major gaps must be bridged between the computational vision and experimental reality. The analysis of cellular signalling dynamics and control requires, first, micro- and nano-instruments that measure simultaneously multiple extracellular and intracellular variables with sufficient bandwidth; secondly, the ability to open existing internal control and signalling loops; thirdly, external BioMEMS micro-actuators that provide high bandwidth feedback and externally addressable intracellular nano-actuators; and, fourthly, real-time, closed-loop, single-cell control algorithms. The unravelling of the nested and coupled nature of cellular control loops requires simultaneous recording of multiple single-cell signatures. Externally controlled nano-actuators, needed to effect changes in the biochemical, mechanical and electrical environment both outside and inside the cell, will provide a major impetus for nanoscience.

Designing a mathematical model for integrating dynamic cellular manufacturing into supply chain system

NASA Astrophysics Data System (ADS)

Aalaei, Amin; Davoudpour, Hamid

2012-11-01

This article presents designing a new mathematical model for integrating dynamic cellular manufacturing into supply chain system with an extensive coverage of important manufacturing features consideration of multiple plants location, multi-markets allocation, multi-period planning horizons with demand and part mix variation, machine capacity, and the main constraints are demand of markets satisfaction in each period, machine availability, machine time-capacity, worker assignment, available time of worker, production volume for each plant and the amounts allocated to each market. The aim of the proposed model is to minimize holding and outsourcing costs, inter-cell material handling cost, external transportation cost, procurement & maintenance and overhead cost of machines, setup cost, reconfiguration cost of machines installation and removal, hiring, firing and salary worker costs. Aimed to prove the potential benefits of such a design, presented an example is shown using a proposed model.

Cellular automaton model for molecular traffic jams

NASA Astrophysics Data System (ADS)

Belitsky, V.; Schütz, G. M.

2011-07-01

We consider the time evolution of an exactly solvable cellular automaton with random initial conditions both in the large-scale hydrodynamic limit and on the microscopic level. This model is a version of the totally asymmetric simple exclusion process with sublattice parallel update and thus may serve as a model for studying traffic jams in systems of self-driven particles. We study the emergence of shocks from the microscopic dynamics of the model. In particular, we introduce shock measures whose time evolution we can compute explicitly, both in the thermodynamic limit and for open boundaries where a boundary-induced phase transition driven by the motion of a shock occurs. The motion of the shock, which results from the collective dynamics of the exclusion particles, is a random walk with an internal degree of freedom that determines the jump direction. This type of hopping dynamics is reminiscent of some transport phenomena in biological systems.

Systems Modeling in Developmental Toxicity

EPA Science Inventory

An individual starts off as a single cell, the progeny of which form complex structures that are themselves integrated into progressively larger systems. Developmental biology is concerned with how this cellular complexity and patterning arises through orchestration of cell divi...

Integrating Intracellular Dynamics Using CompuCell3D and Bionetsolver: Applications to Multiscale Modelling of Cancer Cell Growth and Invasion

PubMed Central

Andasari, Vivi; Roper, Ryan T.; Swat, Maciej H.; Chaplain, Mark A. J.

2012-01-01

In this paper we present a multiscale, individual-based simulation environment that integrates CompuCell3D for lattice-based modelling on the cellular level and Bionetsolver for intracellular modelling. CompuCell3D or CC3D provides an implementation of the lattice-based Cellular Potts Model or CPM (also known as the Glazier-Graner-Hogeweg or GGH model) and a Monte Carlo method based on the metropolis algorithm for system evolution. The integration of CC3D for cellular systems with Bionetsolver for subcellular systems enables us to develop a multiscale mathematical model and to study the evolution of cell behaviour due to the dynamics inside of the cells, capturing aspects of cell behaviour and interaction that is not possible using continuum approaches. We then apply this multiscale modelling technique to a model of cancer growth and invasion, based on a previously published model of Ramis-Conde et al. (2008) where individual cell behaviour is driven by a molecular network describing the dynamics of E-cadherin and -catenin. In this model, which we refer to as the centre-based model, an alternative individual-based modelling technique was used, namely, a lattice-free approach. In many respects, the GGH or CPM methodology and the approach of the centre-based model have the same overall goal, that is to mimic behaviours and interactions of biological cells. Although the mathematical foundations and computational implementations of the two approaches are very different, the results of the presented simulations are compatible with each other, suggesting that by using individual-based approaches we can formulate a natural way of describing complex multi-cell, multiscale models. The ability to easily reproduce results of one modelling approach using an alternative approach is also essential from a model cross-validation standpoint and also helps to identify any modelling artefacts specific to a given computational approach. PMID:22461894

Sig2GRN: a software tool linking signaling pathway with gene regulatory network for dynamic simulation.

PubMed

Zhang, Fan; Liu, Runsheng; Zheng, Jie

2016-12-23

Linking computational models of signaling pathways to predicted cellular responses such as gene expression regulation is a major challenge in computational systems biology. In this work, we present Sig2GRN, a Cytoscape plugin that is able to simulate time-course gene expression data given the user-defined external stimuli to the signaling pathways. A generalized logical model is used in modeling the upstream signaling pathways. Then a Boolean model and a thermodynamics-based model are employed to predict the downstream changes in gene expression based on the simulated dynamics of transcription factors in signaling pathways. Our empirical case studies show that the simulation of Sig2GRN can predict changes in gene expression patterns induced by DNA damage signals and drug treatments. As a software tool for modeling cellular dynamics, Sig2GRN can facilitate studies in systems biology by hypotheses generation and wet-lab experimental design. http://histone.scse.ntu.edu.sg/Sig2GRN/.

Cellular Automata

NASA Astrophysics Data System (ADS)

Gutowitz, Howard

1991-08-01

Cellular automata, dynamic systems in which space and time are discrete, are yielding interesting applications in both the physical and natural sciences. The thirty four contributions in this book cover many aspects of contemporary studies on cellular automata and include reviews, research reports, and guides to recent literature and available software. Chapters cover mathematical analysis, the structure of the space of cellular automata, learning rules with specified properties: cellular automata in biology, physics, chemistry, and computation theory; and generalizations of cellular automata in neural nets, Boolean nets, and coupled map lattices. Current work on cellular automata may be viewed as revolving around two central and closely related problems: the forward problem and the inverse problem. The forward problem concerns the description of properties of given cellular automata. Properties considered include reversibility, invariants, criticality, fractal dimension, and computational power. The role of cellular automata in computation theory is seen as a particularly exciting venue for exploring parallel computers as theoretical and practical tools in mathematical physics. The inverse problem, an area of study gaining prominence particularly in the natural sciences, involves designing rules that possess specified properties or perform specified task. A long-term goal is to develop a set of techniques that can find a rule or set of rules that can reproduce quantitative observations of a physical system. Studies of the inverse problem take up the organization and structure of the set of automata, in particular the parameterization of the space of cellular automata. Optimization and learning techniques, like the genetic algorithm and adaptive stochastic cellular automata are applied to find cellular automaton rules that model such physical phenomena as crystal growth or perform such adaptive-learning tasks as balancing an inverted pole. Howard Gutowitz is Collaborateur in the Service de Physique du Solide et Résonance Magnetique, Commissariat a I'Energie Atomique, Saclay, France.

Animal models to study microRNA function

PubMed Central

Pal, Arpita S.; Kasinski, Andrea L.

2018-01-01

The discovery of the microRNAs, lin-4 and let-7 as critical mediators of normal development in Caenorhabditis elegans and their conservation throughout evolution has spearheaded research towards identifying novel roles of microRNAs in other cellular processes. To accurately elucidate these fundamental functions, especially in the context of an intact organism various microRNA transgenic models have been generated and evaluated. Transgenic C. elegans (worms), Drosophila melanogaster (flies), Danio rerio (zebrafish), and Mus musculus (mouse) have contributed immensely towards uncovering the roles of multiple microRNAs in cellular processes such as proliferation, differentiation, and apoptosis, pathways that are severely altered in human diseases such as cancer. The simple model organisms, C. elegans, D. melanogaster and D. rerio do not develop cancers, but have proved to be convenient systesm in microRNA research, especially in characterizing the microRNA biogenesis machinery which is often dysregulated during human tumorigenesis. The microRNA-dependent events delineated via these simple in vivo systems have been further verified in vitro, and in more complex models of cancers, such as M. musculus. The focus of this review is to provide an overview of the important contributions made in the microRNA field using model organisms. The simple model systems provided the basis for the importance of microRNAs in normal cellular physiology, while the more complex animal systems provided evidence for the role of microRNAs dysregulation in cancers. Highlights include an overview of the various strategies used to generate transgenic organisms and a review of the use of transgenic mice for evaluating pre-clinical efficacy of microRNA-based cancer therapeutics. PMID:28882225

Modelling Spread of Oncolytic Viruses in Heterogeneous Cell Populations

NASA Astrophysics Data System (ADS)

Ellis, Michael; Dobrovolny, Hana

2014-03-01

One of the most promising areas in current cancer research and treatment is the use of viruses to attack cancer cells. A number of oncolytic viruses have been identified to date that possess the ability to destroy or neutralize cancer cells while inflicting minimal damage upon healthy cells. Formulation of predictive models that correctly describe the evolution of infected tumor systems is critical to the successful application of oncolytic virus therapy. A number of different models have been proposed for analysis of the oncolytic virus-infected tumor system, with approaches ranging from traditional coupled differential equations such as the Lotka-Volterra predator-prey models, to contemporary modeling frameworks based on neural networks and cellular automata. Existing models are focused on tumor cells and the effects of virus infection, and offer the potential for improvement by including effects upon normal cells. We have recently extended the traditional framework to a 2-cell model addressing the full cellular system including tumor cells, normal cells, and the impacts of viral infection upon both populations. Analysis of the new framework reveals complex interaction between the populations and potential inability to simultaneously eliminate the virus and tumor populations.

A cellular automation model accounting for bicycle's group behavior

NASA Astrophysics Data System (ADS)

Tang, Tie-Qiao; Rui, Ying-Xu; Zhang, Jian; Shang, Hua-Yan

2018-02-01

Recently, bicycle has become an important traffic tool in China, again. Due to the merits of bicycle, the group behavior widely exists in urban traffic system. However, little effort has been made to explore the impacts of the group behavior on bicycle flow. In this paper, we propose a CA (cellular automaton) model with group behavior to explore the complex traffic phenomena caused by shoulder group behavior and following group behavior on an open road. The numerical results illustrate that the proposed model can qualitatively describe the impacts of the two kinds of group behaviors on bicycle flow and that the effects are related to the mode and size of group behaviors. The results can help us to better understand the impacts of the bicycle's group behaviors on urban traffic system and effectively control the bicycle's group behavior.

Hierarchical random cellular neural networks for system-level brain-like signal processing.

PubMed

Kozma, Robert; Puljic, Marko

2013-09-01

Sensory information processing and cognition in brains are modeled using dynamic systems theory. The brain's dynamic state is described by a trajectory evolving in a high-dimensional state space. We introduce a hierarchy of random cellular automata as the mathematical tools to describe the spatio-temporal dynamics of the cortex. The corresponding brain model is called neuropercolation which has distinct advantages compared to traditional models using differential equations, especially in describing spatio-temporal discontinuities in the form of phase transitions. Phase transitions demarcate singularities in brain operations at critical conditions, which are viewed as hallmarks of higher cognition and awareness experience. The introduced Monte-Carlo simulations obtained by parallel computing point to the importance of computer implementations using very large-scale integration (VLSI) and analog platforms. Copyright © 2013 Elsevier Ltd. All rights reserved.

A closed-loop multi-level model of glucose homeostasis

PubMed Central

Uluseker, Cansu; Simoni, Giulia; Dauriz, Marco; Matone, Alice

2018-01-01

Background The pathophysiologic processes underlying the regulation of glucose homeostasis are considerably complex at both cellular and systemic level. A comprehensive and structured specification for the several layers of abstraction of glucose metabolism is often elusive, an issue currently solvable with the hierarchical description provided by multi-level models. In this study we propose a multi-level closed-loop model of whole-body glucose homeostasis, coupled with the molecular specifications of the insulin signaling cascade in adipocytes, under the experimental conditions of normal glucose regulation and type 2 diabetes. Methodology/Principal findings The ordinary differential equations of the model, describing the dynamics of glucose and key regulatory hormones and their reciprocal interactions among gut, liver, muscle and adipose tissue, were designed for being embedded in a modular, hierarchical structure. The closed-loop model structure allowed self-sustained simulations to represent an ideal in silico subject that adjusts its own metabolism to the fasting and feeding states, depending on the hormonal context and invariant to circadian fluctuations. The cellular level of the model provided a seamless dynamic description of the molecular mechanisms downstream the insulin receptor in the adipocytes by accounting for variations in the surrounding metabolic context. Conclusions/Significance The combination of a multi-level and closed-loop modeling approach provided a fair dynamic description of the core determinants of glucose homeostasis at both cellular and systemic scales. This model architecture is intrinsically open to incorporate supplementary layers of specifications describing further individual components influencing glucose metabolism. PMID:29420588

A Center of Excellence in the Mathematical Sciences - at Cornell University

DTIC Science & Technology

1992-03-01

of my recent efforts go in two directions. 1. Cellular Automata. The Greenberg Hastings model is a simple system that models the behavior of an... Greenberg -Hastings Model. We also obtained results concerning the crucial value for a threshold voter model. This resulted in the papers "Some Rigorous...Results for the Greenberg - Hastings Model" and "Fixation Results for Threshold Voter Systems." Together with Scot Adams, I wrote "An Application of the

Simulation of the Burridge-Knopoff model of earthquakes with variable range stress transfer.

PubMed

Xia, Junchao; Gould, Harvey; Klein, W; Rundle, J B

2005-12-09

Simple models of earthquake faults are important for understanding the mechanisms for their observed behavior, such as Gutenberg-Richter scaling and the relation between large and small events, which is the basis for various forecasting methods. Although cellular automaton models have been studied extensively in the long-range stress transfer limit, this limit has not been studied for the Burridge-Knopoff model, which includes more realistic friction forces and inertia. We find that the latter model with long-range stress transfer exhibits qualitatively different behavior than both the long-range cellular automaton models and the usual Burridge-Knopoff model with nearest-neighbor springs, depending on the nature of the velocity-weakening friction force. These results have important implications for our understanding of earthquakes and other driven dissipative systems.

Microfluidics-based in vivo mimetic systems for the study of cellular biology.

PubMed

Kim, Donghyuk; Wu, Xiaojie; Young, Ashlyn T; Haynes, Christy L

2014-04-15

The human body is a complex network of molecules, organelles, cells, tissues, and organs: an uncountable number of interactions and transformations interconnect all the system's components. In addition to these biochemical components, biophysical components, such as pressure, flow, and morphology, and the location of all of these interactions play an important role in the human body. Technical difficulties have frequently limited researchers from observing cellular biology as it occurs within the human body, but some state-of-the-art analytical techniques have revealed distinct cellular behaviors that occur only in the context of the interactions. These types of findings have inspired bioanalytical chemists to provide new tools to better understand these cellular behaviors and interactions. What blocks us from understanding critical biological interactions in the human body? Conventional approaches are often too naïve to provide realistic data and in vivo whole animal studies give complex results that may or may not be relevant for humans. Microfluidics offers an opportunity to bridge these two extremes: while these studies will not model the complexity of the in vivo human system, they can control the complexity so researchers can examine critical factors of interest carefully and quantitatively. In addition, the use of human cells, such as cells isolated from donated blood, captures human-relevant data and limits the use of animals in research. In addition, researchers can adapt these systems easily and cost-effectively to a variety of high-end signal transduction mechanisms, facilitating high-throughput studies that are also spatially, temporally, or chemically resolved. These strengths should allow microfluidic platforms to reveal critical parameters in the human body and provide insights that will help with the translation of pharmacological advances to clinical trials. In this Account, we describe selected microfluidic innovations within the last 5 years that focus on modeling both biophysical and biochemical interactions in cellular communication, such as flow and cell-cell networks. We also describe more advanced systems that mimic higher level biological networks, such as organ on-a-chip and animal on-a-chip models. Since the first papers in the early 1990s, interest in the bioanalytical use of microfluidics has grown significantly. Advances in micro-/nanofabrication technology have allowed researchers to produce miniaturized, biocompatible assay platforms suitable for microfluidic studies in biochemistry and chemical biology. Well-designed microfluidic platforms can achieve quick, in vitro analyses on pico- and femtoliter volume samples that are temporally, spatially, and chemically resolved. In addition, controlled cell culture techniques using a microfluidic platform have produced biomimetic systems that allow researchers to replicate and monitor physiological interactions. Pioneering work has successfully created cell-fluid, cell-cell, cell-tissue, tissue-tissue, even organ-like level interfaces. Researchers have monitored cellular behaviors in these biomimetic microfluidic environments, producing validated model systems to understand human pathophysiology and to support the development of new therapeutics.

Systems and Photosystems: Cellular Limits of Autotrophic Productivity in Cyanobacteria

PubMed Central

Burnap, Robert L.

2014-01-01

Recent advances in the modeling of microbial growth and metabolism have shown that growth rate critically depends upon the optimal allocation of finite proteomic resources among different cellular functions and that modeling growth rates becomes more realistic with the explicit accounting for the costs of macromolecular synthesis, most importantly, protein expression. The “proteomic constraint” is considered together with its application to understanding photosynthetic microbial growth. The central hypothesis is that physical limits of cellular space (and corresponding solvation capacity) in conjunction with cell surface-to-volume ratios represent the underlying constraints on the maximal rate of autotrophic microbial growth. The limitation of cellular space thus constrains the size the total complement of macromolecules, dissolved ions, and metabolites. To a first approximation, the upper limit in the cellular amount of the total proteome is bounded this space limit. This predicts that adaptation to osmotic stress will result in lower maximal growth rates due to decreased cellular concentrations of core metabolic proteins necessary for cell growth owing the accumulation of compatible osmolytes, as surmised previously. The finite capacity of membrane and cytoplasmic space also leads to the hypothesis that the species-specific differences in maximal growth rates likely reflect differences in the allocation of space to niche-specific proteins with the corresponding diminution of space devoted to other functions including proteins of core autotrophic metabolism, which drive cell reproduction. An optimization model for autotrophic microbial growth, the autotrophic replicator model, was developed based upon previous work investigating heterotrophic growth. The present model describes autotrophic growth in terms of the allocation protein resources among core functional groups including the photosynthetic electron transport chain, light-harvesting antennae, and the ribosome groups. PMID:25654078

Biological system interactions.

PubMed Central

Adomian, G; Adomian, G E; Bellman, R E

1984-01-01

Mathematical modeling of cellular population growth, interconnected subsystems of the body, blood flow, and numerous other complex biological systems problems involves nonlinearities and generally randomness as well. Such problems have been dealt with by mathematical methods often changing the actual model to make it tractable. The method presented in this paper (and referenced works) allows much more physically realistic solutions. PMID:6585837

An epidemiological modeling and data integration framework.

PubMed

Pfeifer, B; Wurz, M; Hanser, F; Seger, M; Netzer, M; Osl, M; Modre-Osprian, R; Schreier, G; Baumgartner, C

2010-01-01

In this work, a cellular automaton software package for simulating different infectious diseases, storing the simulation results in a data warehouse system and analyzing the obtained results to generate prediction models as well as contingency plans, is proposed. The Brisbane H3N2 flu virus, which has been spreading during the winter season 2009, was used for simulation in the federal state of Tyrol, Austria. The simulation-modeling framework consists of an underlying cellular automaton. The cellular automaton model is parameterized by known disease parameters and geographical as well as demographical conditions are included for simulating the spreading. The data generated by simulation are stored in the back room of the data warehouse using the Talend Open Studio software package, and subsequent statistical and data mining tasks are performed using the tool, termed Knowledge Discovery in Database Designer (KD3). The obtained simulation results were used for generating prediction models for all nine federal states of Austria. The proposed framework provides a powerful and easy to handle interface for parameterizing and simulating different infectious diseases in order to generate prediction models and improve contingency plans for future events.

Optimizing eukaryotic cell hosts for protein production through systems biotechnology and genome-scale modeling.

PubMed

Gutierrez, Jahir M; Lewis, Nathan E

2015-07-01

Eukaryotic cell lines, including Chinese hamster ovary cells, yeast, and insect cells, are invaluable hosts for the production of many recombinant proteins. With the advent of genomic resources, one can now leverage genome-scale computational modeling of cellular pathways to rationally engineer eukaryotic host cells. Genome-scale models of metabolism include all known biochemical reactions occurring in a specific cell. By describing these mathematically and using tools such as flux balance analysis, the models can simulate cell physiology and provide targets for cell engineering that could lead to enhanced cell viability, titer, and productivity. Here we review examples in which metabolic models in eukaryotic cell cultures have been used to rationally select targets for genetic modification, improve cellular metabolic capabilities, design media supplementation, and interpret high-throughput omics data. As more comprehensive models of metabolism and other cellular processes are developed for eukaryotic cell culture, these will enable further exciting developments in cell line engineering, thus accelerating recombinant protein production and biotechnology in the years to come. Copyright © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Current State-of-the-Art 3D Tissue Models and Their Compatibility with Live Cell Imaging.

PubMed

Bardsley, Katie; Deegan, Anthony J; El Haj, Alicia; Yang, Ying

2017-01-01

Mammalian cells grow within a complex three-dimensional (3D) microenvironment where multiple cells are organized and surrounded by extracellular matrix (ECM). The quantity and types of ECM components, alongside cell-to-cell and cell-to-matrix interactions dictate cellular differentiation, proliferation and function in vivo. To mimic natural cellular activities, various 3D tissue culture models have been established to replace conventional two dimensional (2D) culture environments. Allowing for both characterization and visualization of cellular activities within possibly bulky 3D tissue models presents considerable challenges due to the increased thickness and subsequent light scattering features of such 3D models. In this chapter, state-of-the-art methodologies used to establish 3D tissue models are discussed, first with a focus on both scaffold-free and scaffold-based 3D tissue model formation. Following on, multiple 3D live cell imaging systems, mainly optical imaging modalities, are introduced. Their advantages and disadvantages are discussed, with the aim of stimulating more research in this highly demanding research area.

A model for the kinetics of homotypic cellular aggregation under static conditions

NASA Technical Reports Server (NTRS)

Neelamegham, S.; Munn, L. L.; Zygourakis, K.; McIntire, L. V. (Principal Investigator)

1997-01-01

We present the formulation and testing of a mathematical model for the kinetics of homotypic cellular aggregation. The model considers cellular aggregation under no-flow conditions as a two-step process. Individual cells and cell aggregates 1) move on the tissue culture surface and 2) collide with other cells (or aggregates). These collisions lead to the formation of intercellular bonds. The aggregation kinetics are described by a system of coupled, nonlinear ordinary differential equations, and the collision frequency kernel is derived by extending Smoluchowski's colloidal flocculation theory to cell migration and aggregation on a two-dimensional surface. Our results indicate that aggregation rates strongly depend upon the motility of cells and cell aggregates, the frequency of cell-cell collisions, and the strength of intercellular bonds. Model predictions agree well with data from homotypic lymphocyte aggregation experiments using Jurkat cells activated by 33B6, an antibody to the beta 1 integrin. Since cell migration speeds and all the other model parameters can be independently measured, the aggregation model provides a quantitative methodology by which we can accurately evaluate the adhesivity and aggregation behavior of cells.

Understanding Biological Regulation Through Synthetic Biology.

PubMed

Bashor, Caleb J; Collins, James J

2018-05-20

Engineering synthetic gene regulatory circuits proceeds through iterative cycles of design, building, and testing. Initial circuit designs must rely on often-incomplete models of regulation established by fields of reductive inquiry-biochemistry and molecular and systems biology. As differences in designed and experimentally observed circuit behavior are inevitably encountered, investigated, and resolved, each turn of the engineering cycle can force a resynthesis in understanding of natural network function. Here, we outline research that uses the process of gene circuit engineering to advance biological discovery. Synthetic gene circuit engineering research has not only refined our understanding of cellular regulation but furnished biologists with a toolkit that can be directed at natural systems to exact precision manipulation of network structure. As we discuss, using circuit engineering to predictively reorganize, rewire, and reconstruct cellular regulation serves as the ultimate means of testing and understanding how cellular phenotype emerges from systems-level network function.

Rab protein evolution and the history of the eukaryotic endomembrane system

PubMed Central

Brighouse, Andrew; Dacks, Joel B.

2010-01-01

Spectacular increases in the quantity of sequence data genome have facilitated major advances in eukaryotic comparative genomics. By exploiting homology with classical model organisms, this makes possible predictions of pathways and cellular functions currently impossible to address in intractable organisms. Echoing realization that core metabolic processes were established very early following evolution of life on earth, it is now emerging that many eukaryotic cellular features, including the endomembrane system, are ancient and organized around near-universal principles. Rab proteins are key mediators of vesicle transport and specificity, and via the presence of multiple paralogues, alterations in interaction specificity and modification of pathways, contribute greatly to the evolution of complexity of membrane transport. Understanding system-level contributions of Rab proteins to evolutionary history provides insight into the multiple processes sculpting cellular transport pathways and the exciting challenges that we face in delving further into the origins of membrane trafficking specificity. PMID:20582450

Construction of living cellular automata using the Physarum plasmodium

NASA Astrophysics Data System (ADS)

Shirakawa, Tomohiro; Sato, Hiroshi; Ishiguro, Shinji

2015-04-01

The plasmodium of Physarum polycephalum is a unicellular and multinuclear giant amoeba that has an amorphous cell body. To clearly observe how the plasmodium makes decisions in its motile and exploratory behaviours, we developed a new experimental system to pseudo-discretize the motility of the organism. In our experimental space that has agar surfaces arranged in a two-dimensional lattice, the continuous and omnidirectional movement of the plasmodium was limited to the stepwise one, and the direction of the locomotion was also limited to four neighbours. In such an experimental system, a cellular automata-like system was constructed using the living cell. We further analysed the exploratory behaviours of the plasmodium by duplicating the experimental results in the simulation models of cellular automata. As a result, it was revealed that the behaviours of the plasmodium are not reproduced by only local state transition rules; and for the reproduction, a kind of historical rule setting is needed.

Simulation of a supersonic flow around a body with a frontal gas-permeable insert by using a skeleton model of a highly porous cellular material

NASA Astrophysics Data System (ADS)

Poplavskaya, T. V.; Kirilovskiy, S. V.; Mironov, S. G.

2017-10-01

Numerical simulation of supersonic flow past a cylinder with a frontal gas-permeable insert is performed using the skeleton model of a highly porous cellular material. Numerical simulation was carried out within the framework of two-dimensional RANS equations written in an axisymmetric form. The skeleton model is a system of coaxial rings of different diameters, arranged in staggered order. The calculations were carried out in a wide range of determining parameters: Mach numbers M∞ = 3, 4.85 and 7, unit Reynolds numbers Re1∞ = 13.8×105 ÷ 13.8×106 m-1, the cylinder diameter 6÷40mm, the length of the porous insert 3÷45mm, the cell diameter of 1 and 3 mm. The results of the calculations are consistent with the available experimental data. The applicability of the skeleton model for the description of supersonic flow around axisymmetric bodies with front inserts from cellular-porous materials is shown.

Simulating large-scale pedestrian movement using CA and event driven model: Methodology and case study

NASA Astrophysics Data System (ADS)

Li, Jun; Fu, Siyao; He, Haibo; Jia, Hongfei; Li, Yanzhong; Guo, Yi

2015-11-01

Large-scale regional evacuation is an important part of national security emergency response plan. Large commercial shopping area, as the typical service system, its emergency evacuation is one of the hot research topics. A systematic methodology based on Cellular Automata with the Dynamic Floor Field and event driven model has been proposed, and the methodology has been examined within context of a case study involving the evacuation within a commercial shopping mall. Pedestrians walking is based on Cellular Automata and event driven model. In this paper, the event driven model is adopted to simulate the pedestrian movement patterns, the simulation process is divided into normal situation and emergency evacuation. The model is composed of four layers: environment layer, customer layer, clerk layer and trajectory layer. For the simulation of movement route of pedestrians, the model takes into account purchase intention of customers and density of pedestrians. Based on evacuation model of Cellular Automata with Dynamic Floor Field and event driven model, we can reflect behavior characteristics of customers and clerks at the situations of normal and emergency evacuation. The distribution of individual evacuation time as a function of initial positions and the dynamics of the evacuation process is studied. Our results indicate that the evacuation model using the combination of Cellular Automata with Dynamic Floor Field and event driven scheduling can be used to simulate the evacuation of pedestrian flows in indoor areas with complicated surroundings and to investigate the layout of shopping mall.

47 CFR 22.901 - Cellular service requirements and limitations.

Code of Federal Regulations, 2011 CFR

2011-10-01

... SERVICES PUBLIC MOBILE SERVICES Cellular Radiotelephone Service § 22.901 Cellular service requirements and limitations. The licensee of each cellular system is responsible for ensuring that its cellular system operates in compliance with this section. (a) Each cellular system must provide either mobile service...

II. Model building: an electrical theory of control of growth and development in animals, prompted by studies of exogenous magnetic field effects (paper I), and evidence of DNA current conduction, in vitro.

PubMed

Elson, Edward

2009-01-01

A theory of control of cellular proliferation and differentiation in the early development of metazoan systems, postulating a system of electrical controls "parallel" to the processes of molecular biochemistry, is presented. It is argued that the processes of molecular biochemistry alone cannot explain how a developing organism defies a stochastic universe. The demonstration of current flow (charge transfer) along the long axis of DNA through the base-pairs (the "pi-way) in vitro raises the question of whether nature may employ such current flows for biological purposes. Such currents might be too small to be accessible to direct measurement in vivo but conduction has been measured in vitro, and the methods might well be extended to living systems. This has not been done because there is no reasonable model which could stimulate experimentation. We suggest several related, but detachable or independent, models for the biological utility of charge transfer, whose scope admittedly outruns current concepts of thinking about organization, growth, and development in eukaryotic, metazoan systems. The ideas are related to explanations proposed to explain the effects demonstrated on tumors and normal tissues described in Article I (this issue). Microscopic and mesoscopic potential fields and currents are well known at sub-cellular, cellular, and organ systems levels. Not only are such phenomena associated with internal cellular membranes in bioenergetics and information flow, but remarkable long-range fields over tissue interfaces and organs appear to play a role in embryonic development (Nuccitelli, 1992 ). The origin of the fields remains unclear and is the subject of active investigation. We are proposing that similar processes could play a vital role at a "sub-microscopic level," at the level of the chromosomes themselves, and could play a role in organizing and directing fundamental processes of growth and development, in parallel with the more discernible fields and currents described.

Cell Patterns Emerge from Coupled Chemical and Physical Fields with Cell Proliferation Dynamics: The Arabidopsis thaliana Root as a Study System

PubMed Central

Barrio, Rafael A.; Romero-Arias, José Roberto; Noguez, Marco A.; Azpeitia, Eugenio; Ortiz-Gutiérrez, Elizabeth; Hernández-Hernández, Valeria; Cortes-Poza, Yuriria; Álvarez-Buylla, Elena R.

2013-01-01

A central issue in developmental biology is to uncover the mechanisms by which stem cells maintain their capacity to regenerate, yet at the same time produce daughter cells that differentiate and attain their ultimate fate as a functional part of a tissue or an organ. In this paper we propose that, during development, cells within growing organs obtain positional information from a macroscopic physical field that is produced in space while cells are proliferating. This dynamical interaction triggers and responds to chemical and genetic processes that are specific to each biological system. We chose the root apical meristem of Arabidopsis thaliana to develop our dynamical model because this system is well studied at the molecular, genetic and cellular levels and has the key traits of multicellular stem-cell niches. We built a dynamical model that couples fundamental molecular mechanisms of the cell cycle to a tension physical field and to auxin dynamics, both of which are known to play a role in root development. We perform extensive numerical calculations that allow for quantitative comparison with experimental measurements that consider the cellular patterns at the root tip. Our model recovers, as an emergent pattern, the transition from proliferative to transition and elongation domains, characteristic of stem-cell niches in multicellular organisms. In addition, we successfully predict altered cellular patterns that are expected under various applied auxin treatments or modified physical growth conditions. Our modeling platform may be extended to explicitly consider gene regulatory networks or to treat other developmental systems. PMID:23658505

RTEMIS: Real-time Tumoroid and Environment Monitoring Using Impedance Spectroscopy and pH Sensing

NASA Astrophysics Data System (ADS)

Alexander, Frank A., Jr.

This research utilizes Electrical Impedance Spectroscopy, a technique classically used for electrochemical analysis and material characterization, as the basis for a non-destructive, label-free assay platform for three dimensional (3D) cellular spheroids. In this work, a linear array of microelectrodes is optimized to rapidly respond to changes located within a 3D multicellular model. In addition, this technique is coupled with an on chip micro-pH sensor for monitoring the environment around the cells. Finally, the responses of both impedance and pH are correlated with physical changes within the cellular model. The impedance analysis system realized through this work provides a foundation for the development of high-throughput drug screening systems that utilize multiple parallel sensing modalities including pH and impedance sensing in order to quickly assess the efficacy of specific drug candidates. The slow development of new drugs is mainly attributed to poor predictability of current chemosensitivity and resistivity assays, as well as genetic differences between the animal models used for tests and humans. In addition, monolayer cultures used in early experimentation are fundamentally different from the complex structure of organs in vivo. This requires the study of smaller 3D models (spheroids) that more efficiently replicate the conditions within the body. The main objective of this research was to develop a microfluidic system on a chip that is capable of deducing viability and morphology of 3D tumor spheroids by monitoring both the impedance of the cellular model and the pH of their local environment. This would provide a fast and reliable method for screening pharmaceutical compounds in a high-throughput system.

Failover in Cellular Automata

NASA Astrophysics Data System (ADS)

Kumar, Shailesh; Rao, Shrisha

This paper studies a phenomenon called failover, and shows that this phenomenon (in particular, stateless failover) can be modeled by Game of Life cellular automata. This is the first time that this sophisticated real-life system behavior has been modeled in abstract terms. A cellular automata (CA) configuration is constructed that exhibits emergent failover. The configuration is based on standard Game of Life rules. Gliders and glider-guns form the core messaging structure in the configuration. The blinker is represented as the basic computational unit, and it is shown how it can be recreated in case of a failure. Stateless failover using the primary-backup mechanism is demonstrated. The details of the CA components used in the configuration and its working are described, and a simulation of the complete configuration is also presented.

A computational study of liposome logic: towards cellular computing from the bottom up

PubMed Central

Smaldon, James; Romero-Campero, Francisco J.; Fernández Trillo, Francisco; Gheorghe, Marian; Alexander, Cameron

2010-01-01

In this paper we propose a new bottom-up approach to cellular computing, in which computational chemical processes are encapsulated within liposomes. This “liposome logic” approach (also called vesicle computing) makes use of supra-molecular chemistry constructs, e.g. protocells, chells, etc. as minimal cellular platforms to which logical functionality can be added. Modeling and simulations feature prominently in “top-down” synthetic biology, particularly in the specification, design and implementation of logic circuits through bacterial genome reengineering. The second contribution in this paper is the demonstration of a novel set of tools for the specification, modelling and analysis of “bottom-up” liposome logic. In particular, simulation and modelling techniques are used to analyse some example liposome logic designs, ranging from relatively simple NOT gates and NAND gates to SR-Latches, D Flip-Flops all the way to 3 bit ripple counters. The approach we propose consists of specifying, by means of P systems, gene regulatory network-like systems operating inside proto-membranes. This P systems specification can be automatically translated and executed through a multiscaled pipeline composed of dissipative particle dynamics (DPD) simulator and Gillespie’s stochastic simulation algorithm (SSA). Finally, model selection and analysis can be performed through a model checking phase. This is the first paper we are aware of that brings to bear formal specifications, DPD, SSA and model checking to the problem of modeling target computational functionality in protocells. Potential chemical routes for the laboratory implementation of these simulations are also discussed thus for the first time suggesting a potentially realistic physiochemical implementation for membrane computing from the bottom-up. PMID:21886681

Using Movies to Analyse Gene Circuit Dynamics in Single Cells

PubMed Central

Locke, James CW; Elowitz, Michael B

2010-01-01

Preface Many bacterial systems rely on dynamic genetic circuits to control critical processes. A major goal of systems biology is to understand these behaviours in terms of individual genes and their interactions. However, traditional techniques based on population averages wash out critical dynamics that are either unsynchronized between cells or driven by fluctuations, or ‘noise,’ in cellular components. Recently, the combination of time-lapse microscopy, quantitative image analysis, and fluorescent protein reporters has enabled direct observation of multiple cellular components over time in individual cells. In conjunction with mathematical modelling, these techniques are now providing powerful insights into genetic circuit behaviour in diverse microbial systems. PMID:19369953

High content image analysis for human H4 neuroglioma cells exposed to CuO nanoparticles.

PubMed

Li, Fuhai; Zhou, Xiaobo; Zhu, Jinmin; Ma, Jinwen; Huang, Xudong; Wong, Stephen T C

2007-10-09

High content screening (HCS)-based image analysis is becoming an important and widely used research tool. Capitalizing this technology, ample cellular information can be extracted from the high content cellular images. In this study, an automated, reliable and quantitative cellular image analysis system developed in house has been employed to quantify the toxic responses of human H4 neuroglioma cells exposed to metal oxide nanoparticles. This system has been proved to be an essential tool in our study. The cellular images of H4 neuroglioma cells exposed to different concentrations of CuO nanoparticles were sampled using IN Cell Analyzer 1000. A fully automated cellular image analysis system has been developed to perform the image analysis for cell viability. A multiple adaptive thresholding method was used to classify the pixels of the nuclei image into three classes: bright nuclei, dark nuclei, and background. During the development of our image analysis methodology, we have achieved the followings: (1) The Gaussian filtering with proper scale has been applied to the cellular images for generation of a local intensity maximum inside each nucleus; (2) a novel local intensity maxima detection method based on the gradient vector field has been established; and (3) a statistical model based splitting method was proposed to overcome the under segmentation problem. Computational results indicate that 95.9% nuclei can be detected and segmented correctly by the proposed image analysis system. The proposed automated image analysis system can effectively segment the images of human H4 neuroglioma cells exposed to CuO nanoparticles. The computational results confirmed our biological finding that human H4 neuroglioma cells had a dose-dependent toxic response to the insult of CuO nanoparticles.

Dirac Cellular Automaton from Split-step Quantum Walk

PubMed Central

Mallick, Arindam; Chandrashekar, C. M.

2016-01-01

Simulations of one quantum system by an other has an implication in realization of quantum machine that can imitate any quantum system and solve problems that are not accessible to classical computers. One of the approach to engineer quantum simulations is to discretize the space-time degree of freedom in quantum dynamics and define the quantum cellular automata (QCA), a local unitary update rule on a lattice. Different models of QCA are constructed using set of conditions which are not unique and are not always in implementable configuration on any other system. Dirac Cellular Automata (DCA) is one such model constructed for Dirac Hamiltonian (DH) in free quantum field theory. Here, starting from a split-step discrete-time quantum walk (QW) which is uniquely defined for experimental implementation, we recover the DCA along with all the fine oscillations in position space and bridge the missing connection between DH-DCA-QW. We will present the contribution of the parameters resulting in the fine oscillations on the Zitterbewegung frequency and entanglement. The tuneability of the evolution parameters demonstrated in experimental implementation of QW will establish it as an efficient tool to design quantum simulator and approach quantum field theory from principles of quantum information theory. PMID:27184159

From Complex to Simple: Interdisciplinary Stochastic Models

ERIC Educational Resources Information Center

Mazilu, D. A.; Zamora, G.; Mazilu, I.

2012-01-01

We present two simple, one-dimensional, stochastic models that lead to a qualitative understanding of very complex systems from biology, nanoscience and social sciences. The first model explains the complicated dynamics of microtubules, stochastic cellular highways. Using the theory of random walks in one dimension, we find analytical expressions…

A MODELING AND SIMULATION LANGUAGE FOR BIOLOGICAL CELLS WITH COUPLED MECHANICAL AND CHEMICAL PROCESSES

PubMed Central

Somogyi, Endre; Glazier, James A.

2017-01-01

Biological cells are the prototypical example of active matter. Cells sense and respond to mechanical, chemical and electrical environmental stimuli with a range of behaviors, including dynamic changes in morphology and mechanical properties, chemical uptake and secretion, cell differentiation, proliferation, death, and migration. Modeling and simulation of such dynamic phenomena poses a number of computational challenges. A modeling language describing cellular dynamics must naturally represent complex intra and extra-cellular spatial structures and coupled mechanical, chemical and electrical processes. Domain experts will find a modeling language most useful when it is based on concepts, terms and principles native to the problem domain. A compiler must then be able to generate an executable model from this physically motivated description. Finally, an executable model must efficiently calculate the time evolution of such dynamic and inhomogeneous phenomena. We present a spatial hybrid systems modeling language, compiler and mesh-free Lagrangian based simulation engine which will enable domain experts to define models using natural, biologically motivated constructs and to simulate time evolution of coupled cellular, mechanical and chemical processes acting on a time varying number of cells and their environment. PMID:29303160

A MODELING AND SIMULATION LANGUAGE FOR BIOLOGICAL CELLS WITH COUPLED MECHANICAL AND CHEMICAL PROCESSES.

PubMed

Somogyi, Endre; Glazier, James A

2017-04-01

Biological cells are the prototypical example of active matter. Cells sense and respond to mechanical, chemical and electrical environmental stimuli with a range of behaviors, including dynamic changes in morphology and mechanical properties, chemical uptake and secretion, cell differentiation, proliferation, death, and migration. Modeling and simulation of such dynamic phenomena poses a number of computational challenges. A modeling language describing cellular dynamics must naturally represent complex intra and extra-cellular spatial structures and coupled mechanical, chemical and electrical processes. Domain experts will find a modeling language most useful when it is based on concepts, terms and principles native to the problem domain. A compiler must then be able to generate an executable model from this physically motivated description. Finally, an executable model must efficiently calculate the time evolution of such dynamic and inhomogeneous phenomena. We present a spatial hybrid systems modeling language, compiler and mesh-free Lagrangian based simulation engine which will enable domain experts to define models using natural, biologically motivated constructs and to simulate time evolution of coupled cellular, mechanical and chemical processes acting on a time varying number of cells and their environment.

Multiscale modeling of the dynamics of multicellular systems

NASA Astrophysics Data System (ADS)

Kosztin, Ioan

2011-03-01

Describing the biomechanical properties of cellular systems, regarded as complex highly viscoelastic materials, is a difficult problem of great conceptual and practical value. Here we present a novel approach, referred to as the Cellular Particle Dynamics (CPD) method, for: (i) quantitatively relating biomechanical properties at the cell level to those at the multicellular and tissue level, and (ii) describing and predicting the time evolution of multicellular systems that undergo biomechanical relaxations. In CPD cells are modeled as an ensemble of cellular particles (CPs) that interact via short range contact interactions, characterized by an attractive (adhesive interaction) and a repulsive (excluded volume interaction) component. The time evolution of the spatial conformation of the multicellular system is determined by following the trajectories of all CPs through integration of their equations of motion. Cell and multicellular level biomechanical properties (e.g., viscosity, surface tension and shear modulus) are determined through the combined use of experiments and theory of continuum viscoelastic media. The same biomechanical properties are also ``measured'' computationally by employing the CPD method, the results being expressed in terms of CPD parameters. Once these parameters have been calibrated experimentally, the formalism provides a systematic framework to predict the time evolution of complex multicellular systems during shape-changing biomechanical transformations. By design, the CPD method is rather flexible and most suitable for multiscale modeling of multicellular system. The spatial level of detail of the system can be easily tuned by changing the number of CPs in a cell. Thus, CPD can be used equally well to describe both cell level processes (e.g., the adhesion of two cells) and tissue level processes (e.g., the formation of 3D constructs of millions of cells through bioprinting). Work supported by NSF [FIBR-0526854 and PHY-0957914]. Computer time provided by the University of Missouri Bioinformatics Consortium.

Synchronization, TIGoRS, and Information Flow in Complex Systems: Dispositional Cellular Automata.

PubMed

Sulis, William H

2016-04-01

Synchronization has a long history in physics where it refers to the phase matching of two identical oscillators. This notion has been extensively studied in physics as well as in biology, where it has been applied to such widely varying phenomena as the flashing of fireflies and firing of neurons in the brain. Human behavior, however, may be recurrent but it is not oscillatory even though many physiological systems do exhibit oscillatory tendencies. Moreover, much of human behaviour is collaborative and cooperative, where the individual behaviours may be distinct yet contemporaneous (if not simultaneous) and taken collectively express some functionality. In the context of behaviour, the important aspect is the repeated co-occurrence in time of behaviours that facilitate the propagation of information or of functionality, regardless of whether or not these behaviours are similar or identical. An example of this weaker notion of synchronization is transient induced global response synchronization (TIGoRS). Previous work has shown that TIGoRS is a ubiquitous phenomenon among complex systems, enabling them to stably parse environmental transients into salient units to which they stably respond. This leads to the notion of Sulis machines, which emergently generate a primitive linguistic structure through their dynamics. This article reviews the notion of TIGoRS and its expression in several complex systems models including tempered neural networks, driven cellular automata and cocktail party automata. The emergent linguistics of Sulis machines are discussed. A new class of complex systems model, the dispositional cellular automaton is introduced. A new metric for TIGoRS, the excess synchronization, is introduced and applied to the study of TIGoRS in dispositional cellular automata. It is shown that these automata exhibit a nonlinear synchronization response to certain perturbing transients.

Pattern-oriented modeling of agent-based complex systems: Lessons from ecology

USGS Publications Warehouse

Grimm, Volker; Revilla, Eloy; Berger, Uta; Jeltsch, Florian; Mooij, Wolf M.; Railsback, Steven F.; Thulke, Hans-Hermann; Weiner, Jacob; Wiegand, Thorsten; DeAngelis, Donald L.

2005-01-01

Agent-based complex systems are dynamic networks of many interacting agents; examples include ecosystems, financial markets, and cities. The search for general principles underlying the internal organization of such systems often uses bottom-up simulation models such as cellular automata and agent-based models. No general framework for designing, testing, and analyzing bottom-up models has yet been established, but recent advances in ecological modeling have come together in a general strategy we call pattern-oriented modeling. This strategy provides a unifying framework for decoding the internal organization of agent-based complex systems and may lead toward unifying algorithmic theories of the relation between adaptive behavior and system complexity.

Pattern-Oriented Modeling of Agent-Based Complex Systems: Lessons from Ecology

NASA Astrophysics Data System (ADS)

Grimm, Volker; Revilla, Eloy; Berger, Uta; Jeltsch, Florian; Mooij, Wolf M.; Railsback, Steven F.; Thulke, Hans-Hermann; Weiner, Jacob; Wiegand, Thorsten; DeAngelis, Donald L.

2005-11-01

Agent-based complex systems are dynamic networks of many interacting agents; examples include ecosystems, financial markets, and cities. The search for general principles underlying the internal organization of such systems often uses bottom-up simulation models such as cellular automata and agent-based models. No general framework for designing, testing, and analyzing bottom-up models has yet been established, but recent advances in ecological modeling have come together in a general strategy we call pattern-oriented modeling. This strategy provides a unifying framework for decoding the internal organization of agent-based complex systems and may lead toward unifying algorithmic theories of the relation between adaptive behavior and system complexity.

Understanding cellular architecture in cancer cells

NASA Astrophysics Data System (ADS)

Bianco, Simone; Tang, Chao

2011-03-01

Understanding the development of cancer is an important goal for today's science. The morphology of cellular organelles, such as the nucleus, the nucleoli and the mitochondria, which is referred to as cellular architecture or cytoarchitecture, is an important indicator of the state of the cell. In particular, there are striking difference between the cellular architecture of a healthy cell versus a cancer cell. In this work we present a dynamical model for the evolution of organelles morphology in cancer cells. Using a dynamical systems approach, we describe the evolution of a cell on its way to cancer as a trajectory in a multidimensional morphology state. The results provided by this work may increase our insight on the mechanism of tumorigenesis and help build new therapeutic strategies.

Integrating Cellular Metabolism into a Multiscale Whole-Body Model

PubMed Central

Krauss, Markus; Schaller, Stephan; Borchers, Steffen; Findeisen, Rolf; Lippert, Jörg; Kuepfer, Lars

2012-01-01

Cellular metabolism continuously processes an enormous range of external compounds into endogenous metabolites and is as such a key element in human physiology. The multifaceted physiological role of the metabolic network fulfilling the catalytic conversions can only be fully understood from a whole-body perspective where the causal interplay of the metabolic states of individual cells, the surrounding tissue and the whole organism are simultaneously considered. We here present an approach relying on dynamic flux balance analysis that allows the integration of metabolic networks at the cellular scale into standardized physiologically-based pharmacokinetic models at the whole-body level. To evaluate our approach we integrated a genome-scale network reconstruction of a human hepatocyte into the liver tissue of a physiologically-based pharmacokinetic model of a human adult. The resulting multiscale model was used to investigate hyperuricemia therapy, ammonia detoxification and paracetamol-induced toxication at a systems level. The specific models simultaneously integrate multiple layers of biological organization and offer mechanistic insights into pathology and medication. The approach presented may in future support a mechanistic understanding in diagnostics and drug development. PMID:23133351

Simulation of Arrhythmogenic Effect of Rogue RyRs in Failing Heart by Using a Coupled Model

PubMed Central

Lu, Luyao; Xia, Ling; Zhu, Xiuwei

2012-01-01

Cardiac cells with heart failure are usually characterized by impairment of Ca2+ handling with smaller SR Ca2+ store and high risk of triggered activities. In this study, we developed a coupled model by integrating the spatiotemporal Ca2+ reaction-diffusion system into the cellular electrophysiological model. With the coupled model, the subcellular Ca2+ dynamics and global cellular electrophysiology could be simultaneously traced. The proposed coupled model was then applied to study the effects of rogue RyRs on Ca2+ cycling and membrane potential in failing heart. The simulation results suggested that, in the presence of rogue RyRs, Ca2+ dynamics is unstable and Ca2+ waves are prone to be initiated spontaneously. These release events would elevate the membrane potential substantially which might induce delayed afterdepolarizations or triggered action potentials. Moreover, the variation of membrane potential depolarization is indicated to be dependent on the distribution density of rogue RyR channels. This study provides a new possible arrhythmogenic mechanism for heart failure from subcellular to cellular level. PMID:23056145

Determination of cellular strains by combined atomic force microscopy and finite element modeling.

PubMed Central

Charras, Guillaume T; Horton, Mike A

2002-01-01

Many organs adapt to their mechanical environment as a result of physiological change or disease. Cells are both the detectors and effectors of this process. Though many studies have been performed in vitro to investigate the mechanisms of detection and adaptation to mechanical strains, the cellular strains remain unknown and results from different stimulation techniques cannot be compared. By combining experimental determination of cell profiles and elasticities by atomic force microscopy with finite element modeling and computational fluid dynamics, we report the cellular strain distributions exerted by common whole-cell straining techniques and from micromanipulation techniques, hence enabling their comparison. Using data from our own analyses and experiments performed by others, we examine the threshold of activation for different signal transduction processes and the strain components that they may detect. We show that modulating cell elasticity, by increasing the F-actin content of the cytoskeleton, or cellular Poisson ratio are good strategies to resist fluid shear or hydrostatic pressure. We report that stray fluid flow in some substrate-stretch systems elicits significant cellular strains. In conclusion, this technique shows promise in furthering our understanding of the interplay among mechanical forces, strain detection, gene expression, and cellular adaptation in physiology and disease. PMID:12124270

Microfluidics-Based in Vivo Mimetic Systems for the Study of Cellular Biology

PubMed Central

2015-01-01

Conspectus The human body is a complex network of molecules, organelles, cells, tissues, and organs: an uncountable number of interactions and transformations interconnect all the system’s components. In addition to these biochemical components, biophysical components, such as pressure, flow, and morphology, and the location of all of these interactions play an important role in the human body. Technical difficulties have frequently limited researchers from observing cellular biology as it occurs within the human body, but some state-of-the-art analytical techniques have revealed distinct cellular behaviors that occur only in the context of the interactions. These types of findings have inspired bioanalytical chemists to provide new tools to better understand these cellular behaviors and interactions. What blocks us from understanding critical biological interactions in the human body? Conventional approaches are often too naïve to provide realistic data and in vivo whole animal studies give complex results that may or may not be relevant for humans. Microfluidics offers an opportunity to bridge these two extremes: while these studies will not model the complexity of the in vivo human system, they can control the complexity so researchers can examine critical factors of interest carefully and quantitatively. In addition, the use of human cells, such as cells isolated from donated blood, captures human-relevant data and limits the use of animals in research. In addition, researchers can adapt these systems easily and cost-effectively to a variety of high-end signal transduction mechanisms, facilitating high-throughput studies that are also spatially, temporally, or chemically resolved. These strengths should allow microfluidic platforms to reveal critical parameters in the human body and provide insights that will help with the translation of pharmacological advances to clinical trials. In this Account, we describe selected microfluidic innovations within the last 5 years that focus on modeling both biophysical and biochemical interactions in cellular communication, such as flow and cell–cell networks. We also describe more advanced systems that mimic higher level biological networks, such as organ on-a-chip and animal on-a-chip models. Since the first papers in the early 1990s, interest in the bioanalytical use of microfluidics has grown significantly. Advances in micro-/nanofabrication technology have allowed researchers to produce miniaturized, biocompatible assay platforms suitable for microfluidic studies in biochemistry and chemical biology. Well-designed microfluidic platforms can achieve quick, in vitro analyses on pico- and femtoliter volume samples that are temporally, spatially, and chemically resolved. In addition, controlled cell culture techniques using a microfluidic platform have produced biomimetic systems that allow researchers to replicate and monitor physiological interactions. Pioneering work has successfully created cell–fluid, cell–cell, cell–tissue, tissue–tissue, even organ-like level interfaces. Researchers have monitored cellular behaviors in these biomimetic microfluidic environments, producing validated model systems to understand human pathophysiology and to support the development of new therapeutics. PMID:24555566

Literature Mining and Knowledge Discovery Tools for Virtual Tissues

EPA Science Inventory

Virtual Tissues (VTs) are in silico models that simulate the cellular fabric of tissues to analyze complex relationships and predict multicellular behaviors in specific biological systems such as the mature liver (v-Liver™) or developing embryo (v-Embryo™). VT models require inpu...

47 CFR 22.970 - Unacceptable interference to part 90 non-cellular 800 MHz licensees from cellular radiotelephone...

Code of Federal Regulations, 2011 CFR

2011-10-01

...-cellular 800 MHz licensees from cellular radiotelephone or part 90-800 MHz cellular systems. 22.970 Section... MOBILE SERVICES Cellular Radiotelephone Service § 22.970 Unacceptable interference to part 90 non-cellular 800 MHz licensees from cellular radiotelephone or part 90-800 MHz cellular systems. (a) Definition...

Inducible and reversible phenotypes in a novel mouse model of Friedreich’s Ataxia

PubMed Central

Gao, Kun; Swarup, Vivek; Versano, Revital; Dong, Hongmei; Jordan, Maria C

2017-01-01

Friedreich's ataxia (FRDA), the most common inherited ataxia, is caused by recessive mutations that reduce the levels of frataxin (FXN), a mitochondrial iron binding protein. We developed an inducible mouse model of Fxn deficiency that enabled us to control the onset and progression of disease phenotypes by the modulation of Fxn levels. Systemic knockdown of Fxn in adult mice led to multiple phenotypes paralleling those observed in human patients across multiple organ systems. By reversing knockdown after clinical features appear, we were able to determine to what extent observed phenotypes represent reversible cellular dysfunction. Remarkably, upon restoration of near wild-type FXN levels, we observed significant recovery of function, associated pathology and transcriptomic dysregulation even after substantial motor dysfunction and pathology were observed. This model will be of broad utility in therapeutic development and in refining our understanding of the relative contribution of reversible cellular dysfunction at different stages in disease. PMID:29257745

Findings

MedlinePlus

... Issue All Issues Explore Findings by Topic Cell Biology Cellular Structures, Functions, Processes, Imaging, Stress Response Chemistry ... Glycobiology, Synthesis, Natural Products, Chemical Reactions Computers in Biology Bioinformatics, Modeling, Systems Biology, Data Visualization Diseases Cancer, ...

Disordered cellular automaton traffic flow model: phase separated state, density waves and self organized criticality

NASA Astrophysics Data System (ADS)

Fourrate, K.; Loulidi, M.

2006-01-01

We suggest a disordered traffic flow model that captures many features of traffic flow. It is an extension of the Nagel-Schreckenberg (NaSch) stochastic cellular automata for single line vehicular traffic model. It incorporates random acceleration and deceleration terms that may be greater than one unit. Our model leads under its intrinsic dynamics, for high values of braking probability pr, to a constant flow at intermediate densities without introducing any spatial inhomogeneities. For a system of fast drivers pr→0, the model exhibits a density wave behavior that was observed in car following models with optimal velocity. The gap of the disordered model we present exhibits, for high values of pr and random deceleration, at a critical density, a power law distribution which is a hall mark of a self organized criticality phenomena.

A Cellular Automata Model of Infection Control on Medical Implants

PubMed Central

Prieto-Langarica, Alicia; Kojouharov, Hristo; Chen-Charpentier, Benito; Tang, Liping

2011-01-01

S. epidermidis infections on medically implanted devices are a common problem in modern medicine due to the abundance of the bacteria. Once inside the body, S. epidermidis gather in communities called biofilms and can become extremely hard to eradicate, causing the patient serious complications. We simulate the complex S. epidermidis-Neutrophils interactions in order to determine the optimum conditions for the immune system to be able to contain the infection and avoid implant rejection. Our cellular automata model can also be used as a tool for determining the optimal amount of antibiotics for combating biofilm formation on medical implants. PMID:23543851

Logic-Based and Cellular Pharmacodynamic Modeling of Bortezomib Responses in U266 Human Myeloma Cells

PubMed Central

Chudasama, Vaishali L.; Ovacik, Meric A.; Abernethy, Darrell R.

2015-01-01

Systems models of biological networks show promise for informing drug target selection/qualification, identifying lead compounds and factors regulating disease progression, rationalizing combinatorial regimens, and explaining sources of intersubject variability and adverse drug reactions. However, most models of biological systems are qualitative and are not easily coupled with dynamical models of drug exposure-response relationships. In this proof-of-concept study, logic-based modeling of signal transduction pathways in U266 multiple myeloma (MM) cells is used to guide the development of a simple dynamical model linking bortezomib exposure to cellular outcomes. Bortezomib is a commonly used first-line agent in MM treatment; however, knowledge of the signal transduction pathways regulating bortezomib-mediated cell cytotoxicity is incomplete. A Boolean network model of 66 nodes was constructed that includes major survival and apoptotic pathways and was updated using responses to several chemical probes. Simulated responses to bortezomib were in good agreement with experimental data, and a reduction algorithm was used to identify key signaling proteins. Bortezomib-mediated apoptosis was not associated with suppression of nuclear factor κB (NFκB) protein inhibition in this cell line, which contradicts a major hypothesis of bortezomib pharmacodynamics. A pharmacodynamic model was developed that included three critical proteins (phospho-NFκB, BclxL, and cleaved poly (ADP ribose) polymerase). Model-fitted protein dynamics and cell proliferation profiles agreed with experimental data, and the model-predicted IC50 (3.5 nM) is comparable to the experimental value (1.5 nM). The cell-based pharmacodynamic model successfully links bortezomib exposure to MM cellular proliferation via protein dynamics, and this model may show utility in exploring bortezomib-based combination regimens. PMID:26163548

Addressing population heterogeneity and distribution in epidemics models using a cellular automata approach

PubMed Central

2014-01-01

Background The spread of an infectious disease is determined by biological and social factors. Models based on cellular automata are adequate to describe such natural systems consisting of a massive collection of simple interacting objects. They characterize the time evolution of the global system as the emergent behaviour resulting from the interaction of the objects, whose behaviour is defined through a set of simple rules that encode the individual behaviour and the transmission dynamic. Methods An epidemic is characterized trough an individual–based–model built upon cellular automata. In the proposed model, each individual of the population is represented by a cell of the automata. This way of modeling an epidemic situation allows to individually define the characteristic of each individual, establish different scenarios and implement control strategies. Results A cellular automata model to study the time evolution of a heterogeneous populations through the various stages of disease was proposed, allowing the inclusion of individual heterogeneity, geographical characteristics and social factors that determine the dynamic of the desease. Different assumptions made to built the classical model were evaluated, leading to following results: i) for low contact rate (like in quarantine process or low density population areas) the number of infective individuals is lower than other areas where the contact rate is higher, and ii) for different initial spacial distributions of infected individuals different epidemic dynamics are obtained due to its influence on the transition rate and the reproductive ratio of disease. Conclusions The contact rate and spatial distributions have a central role in the spread of a disease. For low density populations the spread is very low and the number of infected individuals is lower than in highly populated areas. The spacial distribution of the population and the disease focus as well as the geographical characteristic of the area play a central role in the dynamics of the desease. PMID:24725804

Addressing population heterogeneity and distribution in epidemics models using a cellular automata approach.

PubMed

López, Leonardo; Burguerner, Germán; Giovanini, Leonardo

2014-04-12

The spread of an infectious disease is determined by biological and social factors. Models based on cellular automata are adequate to describe such natural systems consisting of a massive collection of simple interacting objects. They characterize the time evolution of the global system as the emergent behaviour resulting from the interaction of the objects, whose behaviour is defined through a set of simple rules that encode the individual behaviour and the transmission dynamic. An epidemic is characterized trough an individual-based-model built upon cellular automata. In the proposed model, each individual of the population is represented by a cell of the automata. This way of modeling an epidemic situation allows to individually define the characteristic of each individual, establish different scenarios and implement control strategies. A cellular automata model to study the time evolution of a heterogeneous populations through the various stages of disease was proposed, allowing the inclusion of individual heterogeneity, geographical characteristics and social factors that determine the dynamic of the desease. Different assumptions made to built the classical model were evaluated, leading to following results: i) for low contact rate (like in quarantine process or low density population areas) the number of infective individuals is lower than other areas where the contact rate is higher, and ii) for different initial spacial distributions of infected individuals different epidemic dynamics are obtained due to its influence on the transition rate and the reproductive ratio of disease. The contact rate and spatial distributions have a central role in the spread of a disease. For low density populations the spread is very low and the number of infected individuals is lower than in highly populated areas. The spacial distribution of the population and the disease focus as well as the geographical characteristic of the area play a central role in the dynamics of the desease.

Systematic reconstruction of TRANSPATH data into Cell System Markup Language

PubMed Central

Nagasaki, Masao; Saito, Ayumu; Li, Chen; Jeong, Euna; Miyano, Satoru

2008-01-01

Background Many biological repositories store information based on experimental study of the biological processes within a cell, such as protein-protein interactions, metabolic pathways, signal transduction pathways, or regulations of transcription factors and miRNA. Unfortunately, it is difficult to directly use such information when generating simulation-based models. Thus, modeling rules for encoding biological knowledge into system-dynamics-oriented standardized formats would be very useful for fully understanding cellular dynamics at the system level. Results We selected the TRANSPATH database, a manually curated high-quality pathway database, which provides a plentiful source of cellular events in humans, mice, and rats, collected from over 31,500 publications. In this work, we have developed 16 modeling rules based on hybrid functional Petri net with extension (HFPNe), which is suitable for graphical representing and simulating biological processes. In the modeling rules, each Petri net element is incorporated with Cell System Ontology to enable semantic interoperability of models. As a formal ontology for biological pathway modeling with dynamics, CSO also defines biological terminology and corresponding icons. By combining HFPNe with the CSO features, it is possible to make TRANSPATH data to simulation-based and semantically valid models. The results are encoded into a biological pathway format, Cell System Markup Language (CSML), which eases the exchange and integration of biological data and models. Conclusion By using the 16 modeling rules, 97% of the reactions in TRANSPATH are converted into simulation-based models represented in CSML. This reconstruction demonstrates that it is possible to use our rules to generate quantitative models from static pathway descriptions. PMID:18570683

Systematic reconstruction of TRANSPATH data into cell system markup language.

PubMed

Nagasaki, Masao; Saito, Ayumu; Li, Chen; Jeong, Euna; Miyano, Satoru

2008-06-23

Many biological repositories store information based on experimental study of the biological processes within a cell, such as protein-protein interactions, metabolic pathways, signal transduction pathways, or regulations of transcription factors and miRNA. Unfortunately, it is difficult to directly use such information when generating simulation-based models. Thus, modeling rules for encoding biological knowledge into system-dynamics-oriented standardized formats would be very useful for fully understanding cellular dynamics at the system level. We selected the TRANSPATH database, a manually curated high-quality pathway database, which provides a plentiful source of cellular events in humans, mice, and rats, collected from over 31,500 publications. In this work, we have developed 16 modeling rules based on hybrid functional Petri net with extension (HFPNe), which is suitable for graphical representing and simulating biological processes. In the modeling rules, each Petri net element is incorporated with Cell System Ontology to enable semantic interoperability of models. As a formal ontology for biological pathway modeling with dynamics, CSO also defines biological terminology and corresponding icons. By combining HFPNe with the CSO features, it is possible to make TRANSPATH data to simulation-based and semantically valid models. The results are encoded into a biological pathway format, Cell System Markup Language (CSML), which eases the exchange and integration of biological data and models. By using the 16 modeling rules, 97% of the reactions in TRANSPATH are converted into simulation-based models represented in CSML. This reconstruction demonstrates that it is possible to use our rules to generate quantitative models from static pathway descriptions.

Multi-Cellular Logistics of Collective Cell Migration

PubMed Central

Yamao, Masataka; Naoki, Honda; Ishii, Shin

2011-01-01

During development, the formation of biological networks (such as organs and neuronal networks) is controlled by multicellular transportation phenomena based on cell migration. In multi-cellular systems, cellular locomotion is restricted by physical interactions with other cells in a crowded space, similar to passengers pushing others out of their way on a packed train. The motion of individual cells is intrinsically stochastic and may be viewed as a type of random walk. However, this walk takes place in a noisy environment because the cell interacts with its randomly moving neighbors. Despite this randomness and complexity, development is highly orchestrated and precisely regulated, following genetic (and even epigenetic) blueprints. Although individual cell migration has long been studied, the manner in which stochasticity affects multi-cellular transportation within the precisely controlled process of development remains largely unknown. To explore the general principles underlying multicellular migration, we focus on the migration of neural crest cells, which migrate collectively and form streams. We introduce a mechanical model of multi-cellular migration. Simulations based on the model show that the migration mode depends on the relative strengths of the noise from migratory and non-migratory cells. Strong noise from migratory cells and weak noise from surrounding cells causes “collective migration,” whereas strong noise from non-migratory cells causes “dispersive migration.” Moreover, our theoretical analyses reveal that migratory cells attract each other over long distances, even without direct mechanical contacts. This effective interaction depends on the stochasticity of the migratory and non-migratory cells. On the basis of these findings, we propose that stochastic behavior at the single-cell level works effectively and precisely to achieve collective migration in multi-cellular systems. PMID:22205934

Global stability and exact solution of an arbitrary-solute nonlinear cellular mass transport system.

PubMed

Benson, James D

2014-12-01

The prediction of the cellular state as a function of extracellular concentrations and temperatures has been of interest to physiologists for nearly a century. One of the most widely used models in the field is one where mass flux is linearly proportional to the concentration difference across the membrane. These fluxes define a nonlinear differential equation system for the intracellular state, which when coupled with appropriate initial conditions, define the intracellular state as a function of the extracellular concentrations of both permeating and nonpermeating solutes. Here we take advantage of a reparametrization scheme to extend existing stability results to a more general setting and to a develop analytical solutions to this model for an arbitrary number of extracellular solutes. Copyright © 2014 Elsevier Inc. All rights reserved.

Cellular neural network-based hybrid approach toward automatic image registration

NASA Astrophysics Data System (ADS)

Arun, Pattathal VijayaKumar; Katiyar, Sunil Kumar

2013-01-01

Image registration is a key component of various image processing operations that involve the analysis of different image data sets. Automatic image registration domains have witnessed the application of many intelligent methodologies over the past decade; however, inability to properly model object shape as well as contextual information has limited the attainable accuracy. A framework for accurate feature shape modeling and adaptive resampling using advanced techniques such as vector machines, cellular neural network (CNN), scale invariant feature transform (SIFT), coreset, and cellular automata is proposed. CNN has been found to be effective in improving feature matching as well as resampling stages of registration and complexity of the approach has been considerably reduced using coreset optimization. The salient features of this work are cellular neural network approach-based SIFT feature point optimization, adaptive resampling, and intelligent object modelling. Developed methodology has been compared with contemporary methods using different statistical measures. Investigations over various satellite images revealed that considerable success was achieved with the approach. This system has dynamically used spectral and spatial information for representing contextual knowledge using CNN-prolog approach. This methodology is also illustrated to be effective in providing intelligent interpretation and adaptive resampling.

Neurophysiology of Drosophila Models of Parkinson's Disease

PubMed Central

West, Ryan J. H.; Furmston, Rebecca; Williams, Charles A. C.; Elliott, Christopher J. H.

2015-01-01

We provide an insight into the role Drosophila has played in elucidating neurophysiological perturbations associated with Parkinson's disease- (PD-) related genes. Synaptic signalling deficits are observed in motor, central, and sensory systems. Given the neurological impact of disease causing mutations within these same genes in humans the phenotypes observed in fly are of significant interest. As such we observe four unique opportunities provided by fly nervous system models of Parkinson's disease. Firstly, Drosophila models are instrumental in exploring the mechanisms of neurodegeneration, with several PD-related mutations eliciting related phenotypes including sensitivity to energy supply and vesicular deformities. These are leading to the identification of plausible cellular mechanisms, which may be specific to (dopaminergic) neurons and synapses rather than general cellular phenotypes. Secondly, models show noncell autonomous signalling within the nervous system, offering the opportunity to develop our understanding of the way pathogenic signalling propagates, resembling Braak's scheme of spreading pathology in PD. Thirdly, the models link physiological deficits to changes in synaptic structure. While the structure-function relationship is complex, the genetic tractability of Drosophila offers the chance to separate fundamental changes from downstream consequences. Finally, the strong neuronal phenotypes permit relevant first in vivo drug testing. PMID:25960916

Introducing a simple model system for binding studies of known and novel inhibitors of AMPK: a therapeutic target for prostate cancer.

PubMed

Kumar, Rakesh; Maurya, Ranjana; Saran, Shweta

2018-02-23

Prostate cancer (PC) is one of the leading cancers in men, raising a serious health issue worldwide. Due to lack of suitable biomarker, their inhibitors and the platform for testing those inhibitors result in poor prognosis of PC. AMP-activated protein kinase (AMPK) is a highly conserved protein kinase found in eukaryotes that is involved in growth and development, and also acts as a therapeutic target for PC. The aim of the present study is to identify novel potent inhibitors of AMPK and propose a simple cellular model system for understanding its biology. Structural modelling and MD simulations were performed to construct and refine the 3D models of Dictyostelium and human AMPK. Binding mechanisms of different drug compounds were studied by performing molecular docking, molecular dynamics and MM-PBSA methods. Two novel drugs were isolated having higher binding affinity over the known drugs and hydrophobic forces that played a key role during protein-ligand interactions. The study also explored the simple cellular model system for drug screening and understanding the biology of a therapeutic target by performing in vitro experiments.

Realistic modeling of neurons and networks: towards brain simulation.

PubMed

D'Angelo, Egidio; Solinas, Sergio; Garrido, Jesus; Casellato, Claudia; Pedrocchi, Alessandra; Mapelli, Jonathan; Gandolfi, Daniela; Prestori, Francesca

2013-01-01

Realistic modeling is a new advanced methodology for investigating brain functions. Realistic modeling is based on a detailed biophysical description of neurons and synapses, which can be integrated into microcircuits. The latter can, in turn, be further integrated to form large-scale brain networks and eventually to reconstruct complex brain systems. Here we provide a review of the realistic simulation strategy and use the cerebellar network as an example. This network has been carefully investigated at molecular and cellular level and has been the object of intense theoretical investigation. The cerebellum is thought to lie at the core of the forward controller operations of the brain and to implement timing and sensory prediction functions. The cerebellum is well described and provides a challenging field in which one of the most advanced realistic microcircuit models has been generated. We illustrate how these models can be elaborated and embedded into robotic control systems to gain insight into how the cellular properties of cerebellar neurons emerge in integrated behaviors. Realistic network modeling opens up new perspectives for the investigation of brain pathologies and for the neurorobotic field.

Realistic modeling of neurons and networks: towards brain simulation

PubMed Central

D’Angelo, Egidio; Solinas, Sergio; Garrido, Jesus; Casellato, Claudia; Pedrocchi, Alessandra; Mapelli, Jonathan; Gandolfi, Daniela; Prestori, Francesca

Summary Realistic modeling is a new advanced methodology for investigating brain functions. Realistic modeling is based on a detailed biophysical description of neurons and synapses, which can be integrated into microcircuits. The latter can, in turn, be further integrated to form large-scale brain networks and eventually to reconstruct complex brain systems. Here we provide a review of the realistic simulation strategy and use the cerebellar network as an example. This network has been carefully investigated at molecular and cellular level and has been the object of intense theoretical investigation. The cerebellum is thought to lie at the core of the forward controller operations of the brain and to implement timing and sensory prediction functions. The cerebellum is well described and provides a challenging field in which one of the most advanced realistic microcircuit models has been generated. We illustrate how these models can be elaborated and embedded into robotic control systems to gain insight into how the cellular properties of cerebellar neurons emerge in integrated behaviors. Realistic network modeling opens up new perspectives for the investigation of brain pathologies and for the neurorobotic field. PMID:24139652

An insert-based enzymatic cell culture system to rapidly and reversibly induce hypoxia: investigations of hypoxia-induced cell damage, protein expression and phosphorylation in neuronal IMR-32 cells

PubMed Central

Huang, Ying; Zitta, Karina; Bein, Berthold; Steinfath, Markus; Albrecht, Martin

2013-01-01

SUMMARY Ischemia-reperfusion injury and tissue hypoxia are of high clinical relevance because they are associated with various pathophysiological conditions such as myocardial infarction and stroke. Nevertheless, the underlying mechanisms causing cell damage are still not fully understood, which is at least partially due to the lack of cell culture systems for the induction of rapid and transient hypoxic conditions. The aim of the study was to establish a model that is suitable for the investigation of cellular and molecular effects associated with transient and long-term hypoxia and to gain insights into hypoxia-mediated mechanisms employing a neuronal culture system. A semipermeable membrane insert system in combination with the hypoxia-inducing enzymes glucose oxidase and catalase was employed to rapidly and reversibly generate hypoxic conditions in the culture medium. Hydrogen peroxide assays, glucose measurements and western blotting were performed to validate the system and to evaluate the effects of the generated hypoxia on neuronal IMR-32 cells. Using the insert-based two-enzyme model, hypoxic conditions were rapidly induced in the culture medium. Glucose concentrations gradually decreased, whereas levels of hydrogen peroxide were not altered. Moreover, a rapid and reversible (onoff) generation of hypoxia could be performed by the addition and subsequent removal of the enzyme-containing inserts. Employing neuronal IMR-32 cells, we showed that 3 hours of hypoxia led to morphological signs of cellular damage and significantly increased levels of lactate dehydrogenase (a biochemical marker of cell damage). Hypoxic conditions also increased the amounts of cellular procaspase-3 and catalase as well as phosphorylation of the pro-survival kinase Akt, but not Erk1/2 or STAT5. In summary, we present a novel framework for investigating hypoxia-mediated mechanisms at the cellular level. We claim that the model, the first of its kind, enables researchers to rapidly and reversibly induce hypoxic conditions in vitro without unwanted interference of the hypoxia-inducing agent on the cultured cells. The system could help to further unravel hypoxia-associated mechanisms that are clinically relevant in various tissues and organs. PMID:24046359

New cellular automaton model for magnetohydrodynamics

NASA Technical Reports Server (NTRS)

Chen, Hudong; Matthaeus, William H.

1987-01-01

A new type of two-dimensional cellular automation method is introduced for computation of magnetohydrodynamic fluid systems. Particle population is described by a 36-component tensor referred to a hexagonal lattice. By appropriate choice of the coefficients that control the modified streaming algorithm and the definition of the macroscopic fields, it is possible to compute both Lorentz-force and magnetic-induction effects. The method is local in the microscopic space and therefore suited to massively parallel computations.

Parallel labeling experiments for pathway elucidation and (13)C metabolic flux analysis.

PubMed

Antoniewicz, Maciek R

2015-12-01

Metabolic pathway models provide the foundation for quantitative studies of cellular physiology through the measurement of intracellular metabolic fluxes. For model organisms metabolic models are well established, with many manually curated genome-scale model reconstructions, gene knockout studies and stable-isotope tracing studies. However, for non-model organisms a similar level of knowledge is often lacking. Compartmentation of cellular metabolism in eukaryotic systems also presents significant challenges for quantitative (13)C-metabolic flux analysis ((13)C-MFA). Recently, innovative (13)C-MFA approaches have been developed based on parallel labeling experiments, the use of multiple isotopic tracers and integrated data analysis, that allow more rigorous validation of pathway models and improved quantification of metabolic fluxes. Applications of these approaches open new research directions in metabolic engineering, biotechnology and medicine. Copyright © 2015 Elsevier Ltd. All rights reserved.

Agent-based modeling of autophagy reveals emergent regulatory behavior of spatio-temporal autophagy dynamics.

PubMed

Börlin, Christoph S; Lang, Verena; Hamacher-Brady, Anne; Brady, Nathan R

2014-09-10

Autophagy is a vesicle-mediated pathway for lysosomal degradation, essential under basal and stressed conditions. Various cellular components, including specific proteins, protein aggregates, organelles and intracellular pathogens, are targets for autophagic degradation. Thereby, autophagy controls numerous vital physiological and pathophysiological functions, including cell signaling, differentiation, turnover of cellular components and pathogen defense. Moreover, autophagy enables the cell to recycle cellular components to metabolic substrates, thereby permitting prolonged survival under low nutrient conditions. Due to the multi-faceted roles for autophagy in maintaining cellular and organismal homeostasis and responding to diverse stresses, malfunction of autophagy contributes to both chronic and acute pathologies. We applied a systems biology approach to improve the understanding of this complex cellular process of autophagy. All autophagy pathway vesicle activities, i.e. creation, movement, fusion and degradation, are highly dynamic, temporally and spatially, and under various forms of regulation. We therefore developed an agent-based model (ABM) to represent individual components of the autophagy pathway, subcellular vesicle dynamics and metabolic feedback with the cellular environment, thereby providing a framework to investigate spatio-temporal aspects of autophagy regulation and dynamic behavior. The rules defining our ABM were derived from literature and from high-resolution images of autophagy markers under basal and activated conditions. Key model parameters were fit with an iterative method using a genetic algorithm and a predefined fitness function. From this approach, we found that accurate prediction of spatio-temporal behavior required increasing model complexity by implementing functional integration of autophagy with the cellular nutrient state. The resulting model is able to reproduce short-term autophagic flux measurements (up to 3 hours) under basal and activated autophagy conditions, and to measure the degree of cell-to-cell variability. Moreover, we experimentally confirmed two model predictions, namely (i) peri-nuclear concentration of autophagosomes and (ii) inhibitory lysosomal feedback on mTOR signaling. Agent-based modeling represents a novel approach to investigate autophagy dynamics, function and dysfunction with high biological realism. Our model accurately recapitulates short-term behavior and cell-to-cell variability under basal and activated conditions of autophagy. Further, this approach also allows investigation of long-term behaviors emerging from biologically-relevant alterations to vesicle trafficking and metabolic state.

A Comparison of Three Approaches to Model Human Behavior

NASA Astrophysics Data System (ADS)

Palmius, Joel; Persson-Slumpi, Thomas

2010-11-01

One way of studying social processes is through the use of simulations. The use of simulations for this purpose has been established as its own field, social simulations, and has been used for studying a variety of phenomena. A simulation of a social setting can serve as an aid for thinking about that social setting, and for experimenting with different parameters and studying the outcomes caused by them. When using the simulation as an aid for thinking and experimenting, the chosen simulation approach will implicitly steer the simulationist towards thinking in a certain fashion in order to fit the model. To study the implications of model choice on the understanding of a setting where human anticipation comes into play, a simulation scenario of a coffee room was constructed using three different simulation approaches: Cellular Automata, Systems Dynamics and Agent-based modeling. The practical implementations of the models were done in three different simulation packages: Stella for Systems Dynamic, CaFun for Cellular automata and SesAM for Agent-based modeling. The models were evaluated both using Randers' criteria for model evaluation, and through introspection where the authors reflected upon how their understanding of the scenario was steered through the model choice. Further the software used for implementing the simulation models was evaluated, and practical considerations for the choice of software package are listed. It is concluded that the models have very different strengths. The Agent-based modeling approach offers the most intuitive support for thinking about and modeling a social setting where the behavior of the individual is in focus. The Systems Dynamics model would be preferable in situations where populations and large groups would be studied as wholes, but where individual behavior is of less concern. The Cellular Automata models would be preferable where processes need to be studied from the basis of a small set of very simple rules. It is further concluded that in most social simulation settings the Agent-based modeling approach would be the probable choice. This since the other models does not offer much in the way of supporting the modeling of the anticipatory behavior of humans acting in an organization.

Modeling the Land Use/Cover Change in an Arid Region Oasis City Constrained by Water Resource and Environmental Policy Change using Cellular Automata Model

NASA Astrophysics Data System (ADS)

Hu, X.; Li, X.; Lu, L.

2017-12-01

Land use/cover change (LUCC) is an important subject in the research of global environmental change and sustainable development, while spatial simulation on land use/cover change is one of the key content of LUCC and is also difficult due to the complexity of the system. The cellular automata (CA) model had an irreplaceable role in simulating of land use/cover change process due to the powerful spatial computing power. However, the majority of current CA land use/cover models were binary-state model that could not provide more general information about the overall spatial pattern of land use/cover change. Here, a multi-state logistic-regression-based Markov cellular automata (MLRMCA) model and a multi-state artificial-neural-network-based Markov cellular automata (MANNMCA) model were developed and were used to simulate complex land use/cover evolutionary process in an arid region oasis city constrained by water resource and environmental policy change, the Zhangye city during the period of 1990-2010. The results indicated that the MANNMCA model was superior to MLRMCA model in simulated accuracy. These indicated that by combining the artificial neural network with CA could more effectively capture the complex relationships between the land use/cover change and a set of spatial variables. Although the MLRMCA model were also some advantages, the MANNMCA model was more appropriate for simulating complex land use/cover dynamics. The two proposed models were effective and reliable, and could reflect the spatial evolution of regional land use/cover changes. These have also potential implications for the impact assessment of water resources, ecological restoration, and the sustainable urban development in arid areas.

Advances in molecular labeling, high throughput imaging and machine intelligence portend powerful functional cellular biochemistry tools.

PubMed

Price, Jeffrey H; Goodacre, Angela; Hahn, Klaus; Hodgson, Louis; Hunter, Edward A; Krajewski, Stanislaw; Murphy, Robert F; Rabinovich, Andrew; Reed, John C; Heynen, Susanne

2002-01-01

Cellular behavior is complex. Successfully understanding systems at ever-increasing complexity is fundamental to advances in modern science and unraveling the functional details of cellular behavior is no exception. We present a collection of prospectives to provide a glimpse of the techniques that will aid in collecting, managing and utilizing information on complex cellular processes via molecular imaging tools. These include: 1) visualizing intracellular protein activity with fluorescent markers, 2) high throughput (and automated) imaging of multilabeled cells in statistically significant numbers, and 3) machine intelligence to analyze subcellular image localization and pattern. Although not addressed here, the importance of combining cell-image-based information with detailed molecular structure and ligand-receptor binding models cannot be overlooked. Advanced molecular imaging techniques have the potential to impact cellular diagnostics for cancer screening, clinical correlations of tissue molecular patterns for cancer biology, and cellular molecular interactions for accelerating drug discovery. The goal of finally understanding all cellular components and behaviors will be achieved by advances in both instrumentation engineering (software and hardware) and molecular biochemistry. Copyright 2002 Wiley-Liss, Inc.

Adaptation in Living Systems

NASA Astrophysics Data System (ADS)

Tu, Yuhai; Rappel, Wouter-Jan

2018-03-01

Adaptation refers to the biological phenomenon where living systems change their internal states in response to changes in their environments in order to maintain certain key functions critical for their survival and fitness. Adaptation is one of the most ubiquitous and arguably one of the most fundamental properties of living systems. It occurs throughout all biological scales, from adaptation of populations of species over evolutionary time to adaptation of a single cell to different environmental stresses during its life span. In this article, we review some of the recent progress made in understanding molecular mechanisms of cellular-level adaptation. We take the minimalist (or the physicist) approach and study the simplest systems that exhibit generic adaptive behaviors, namely chemotaxis in bacterium cells (Escherichia coli) and eukaryotic cells (Dictyostelium). We focus on understanding the basic biochemical interaction networks that are responsible for adaptation dynamics. By combining theoretical modeling with quantitative experimentation, we demonstrate universal features in adaptation as well as important differences in different cellular systems. Future work in extending the modeling framework to study adaptation in more complex systems such as sensory neurons is also discussed.

A Novel Approach to Primary Cell Culture for Octopus vulgaris Neurons

PubMed Central

Maselli, Valeria; Xu, Fenglian; Syed, Naweed I.; Polese, Gianluca; Di Cosmo, Anna

2018-01-01

Octopus vulgaris is a unique model system for studying complex behaviors in animals. It has a large and centralized nervous system made up of lobes that are involved in controlling various sophisticated behaviors. As such, it may be considered as a model organism for untangling the neuronal mechanisms underlying behaviors—including learning and memory. However, despite considerable efforts, Octopus lags behind its other counterparts vis-à-vis its utility in deciphering the cellular, molecular and synaptic mechanisms underlying various behaviors. This study represents a novel approach designed to establish a neuronal cell culture protocol that makes this species amenable to further exploitation as a model system. Here we developed a protocol that enables dissociation of neurons from two specific Octopus' brain regions, the vertical-superior frontal system and the optic lobes, which are involved in memory, learning, sensory integration and adult neurogenesis. In particular, cells dissociated with enzyme papain and cultured on Poly-D-Lysine-coated dishes with L15-medium and fetal bovine serum yielded high neuronal survival, axon growth, and re-growth after injury. This model was also explored to define optimal culture conditions and to demonstrate the regenerative capabilities of adult Octopus neurons after axotomy. This study thus further underscores the importance of Octopus neurons as a model system for deciphering fundamental molecular and cellular mechanism of complex brain function and underlying behaviors. PMID:29666582

VISIBIOweb: visualization and layout services for BioPAX pathway models

PubMed Central

Dilek, Alptug; Belviranli, Mehmet E.; Dogrusoz, Ugur

2010-01-01

With recent advancements in techniques for cellular data acquisition, information on cellular processes has been increasing at a dramatic rate. Visualization is critical to analyzing and interpreting complex information; representing cellular processes or pathways is no exception. VISIBIOweb is a free, open-source, web-based pathway visualization and layout service for pathway models in BioPAX format. With VISIBIOweb, one can obtain well-laid-out views of pathway models using the standard notation of the Systems Biology Graphical Notation (SBGN), and can embed such views within one's web pages as desired. Pathway views may be navigated using zoom and scroll tools; pathway object properties, including any external database references available in the data, may be inspected interactively. The automatic layout component of VISIBIOweb may also be accessed programmatically from other tools using Hypertext Transfer Protocol (HTTP). The web site is free and open to all users and there is no login requirement. It is available at: http://visibioweb.patika.org. PMID:20460470

Linking actin networks and cell membrane via a reaction-diffusion-elastic description of nonlinear filopodia initiation.

PubMed

Ben Isaac, Eyal; Manor, Uri; Kachar, Bechara; Yochelis, Arik; Gov, Nir S

2013-08-01

Reaction-diffusion models have been used to describe pattern formation on the cellular scale, and traditionally do not include feedback between cellular shape changes and biochemical reactions. We introduce here a distinct reaction-diffusion-elasticity approach: The reaction-diffusion part describes bistability between two actin orientations, coupled to the elastic energy of the cell membrane deformations. This coupling supports spatially localized patterns, even when such solutions do not exist in the uncoupled self-inhibited reaction-diffusion system. We apply this concept to describe the nonlinear (threshold driven) initiation mechanism of actin-based cellular protrusions and provide support by several experimental observations.

Cell-to-Cell Communication Circuits: Quantitative Analysis of Synthetic Logic Gates

PubMed Central

Hoffman-Sommer, Marta; Supady, Adriana; Klipp, Edda

2012-01-01

One of the goals in the field of synthetic biology is the construction of cellular computation devices that could function in a manner similar to electronic circuits. To this end, attempts are made to create biological systems that function as logic gates. In this work we present a theoretical quantitative analysis of a synthetic cellular logic-gates system, which has been implemented in cells of the yeast Saccharomyces cerevisiae (Regot et al., 2011). It exploits endogenous MAP kinase signaling pathways. The novelty of the system lies in the compartmentalization of the circuit where all basic logic gates are implemented in independent single cells that can then be cultured together to perform complex logic functions. We have constructed kinetic models of the multicellular IDENTITY, NOT, OR, and IMPLIES logic gates, using both deterministic and stochastic frameworks. All necessary model parameters are taken from literature or estimated based on published kinetic data, in such a way that the resulting models correctly capture important dynamic features of the included mitogen-activated protein kinase pathways. We analyze the models in terms of parameter sensitivity and we discuss possible ways of optimizing the system, e.g., by tuning the culture density. We apply a stochastic modeling approach, which simulates the behavior of whole populations of cells and allows us to investigate the noise generated in the system; we find that the gene expression units are the major sources of noise. Finally, the model is used for the design of system modifications: we show how the current system could be transformed to operate on three discrete values. PMID:22934039

The mechanics of cellular compartmentalization as a model for tumor spreading

NASA Astrophysics Data System (ADS)

Fritsch, Anatol; Pawlizak, Steve; Zink, Mareike; Kaes, Josef A.

2012-02-01

Based on a recently developed surgical method of Michael H"ockel, which makes use of cellular confinement to compartments in the human body, we study the mechanics of the process of cell segregation. Compartmentalization is a fundamental process of cellular organization and occurs during embryonic development. A simple model system can demonstrate the process of compartmentalization: When two populations of suspended cells are mixed, this mixture will eventually segregate into two phases, whereas mixtures of the same cell type will not. In the 1960s, Malcolm S. Steinberg formulated the so-called differential adhesion hypothesis which explains the segregation in the model system and the process of compartmentalization by differences in surface tension and adhesiveness of the interacting cells. We are interested in to which extend the same physical principles affect tumor growth and spreading between compartments. For our studies, we use healthy and cancerous breast cell lines of different malignancy as well as primary cells from human cervix carcinoma. We apply a set of techniques to study their mechanical properties and interactions. The Optical Stretcher is used for whole cell rheology, while Cell-cell-adhesion forces are directly measured with a modified AFM. In combination with 3D segregation experiments in droplet cultures we try to clarify the role of surface tension in tumor spreading.

Systems Biology Approaches for Discovering Biomarkers for Traumatic Brain Injury

PubMed Central

Feala, Jacob D.; AbdulHameed, Mohamed Diwan M.; Yu, Chenggang; Dutta, Bhaskar; Yu, Xueping; Schmid, Kara; Dave, Jitendra; Tortella, Frank

2013-01-01

Abstract The rate of traumatic brain injury (TBI) in service members with wartime injuries has risen rapidly in recent years, and complex, variable links have emerged between TBI and long-term neurological disorders. The multifactorial nature of TBI secondary cellular response has confounded attempts to find cellular biomarkers for its diagnosis and prognosis or for guiding therapy for brain injury. One possibility is to apply emerging systems biology strategies to holistically probe and analyze the complex interweaving molecular pathways and networks that mediate the secondary cellular response through computational models that integrate these diverse data sets. Here, we review available systems biology strategies, databases, and tools. In addition, we describe opportunities for applying this methodology to existing TBI data sets to identify new biomarker candidates and gain insights about the underlying molecular mechanisms of TBI response. As an exemplar, we apply network and pathway analysis to a manually compiled list of 32 protein biomarker candidates from the literature, recover known TBI-related mechanisms, and generate hypothetical new biomarker candidates. PMID:23510232

Stochastic cellular automata model of neurosphere growth: Roles of proliferative potential, contact inhibition, cell death, and phagocytosis.

PubMed

Sipahi, Rifat; Zupanc, Günther K H

2018-05-14

Neural stem and progenitor cells isolated from the central nervous system form, under specific culture conditions, clonal cell clusters known as neurospheres. The neurosphere assay has proven to be a powerful in vitro system to study the behavior of such cells and the development of their progeny. However, the theory of neurosphere growth has remained poorly understood. To overcome this limitation, we have, in the present paper, developed a cellular automata model, with which we examined the effects of proliferative potential, contact inhibition, cell death, and clearance of dead cells on growth rate, final size, and composition of neurospheres. Simulations based on this model indicated that the proliferative potential of the founder cell and its progenitors has a major influence on neurosphere size. On the other hand, contact inhibition of proliferation limits the final size, and reduces the growth rate, of neurospheres. The effect of this inhibition is particularly dramatic when a stem cell becomes encapsulated by differentiated or other non-proliferating cells, thereby suppressing any further mitotic division - despite the existing proliferative potential of the stem cell. Conversely, clearance of dead cells through phagocytosis is predicted to accelerate growth by reducing contact inhibition. A surprising prediction derived from our model is that cell death, while resulting in a decrease in growth rate and final size of neurospheres, increases the degree of differentiation of neurosphere cells. It is likely that the cellular automata model developed as part of the present investigation is applicable to the study of tissue growth in a wide range of systems. Copyright © 2018 Elsevier Ltd. All rights reserved.

A Study on Cognitive Radio Coexisting with Cellular Systems

NASA Astrophysics Data System (ADS)

Tandai, Tomoya; Horiguchi, Tomoya; Deguchi, Noritaka; Tomizawa, Takeshi; Tomioka, Tazuko

Cognitive Radios (CRs) are expected to perform more significant role in the view of efficient utilization of the spectrum resources in the future wireless communication networks. In this paper, a cognitive radio coexisting with cellular systems is proposed. In the case that a cellular system adopts Frequency Division Duplex (FDD) as a multiplexing scheme, the proposed CR terminals communicate in local area on uplink channels of the cellular system with transmission powers that don't interfere with base stations of the cellular system. Alternatively, in the case that a cellular system adopts Time Division Duplex (TDD), the CR terminals communicate on uplink slots of the cellular system. However if mobile terminals in the cellular system are near the CR network, uplink signals from the mobile terminals may interfere with the CR communications. In order to avoid interference from the mobile terminals, the CR terminal performs carrier sense during a beginning part of uplink slot, and only when the level of detected signal is below a threshold, then the CR terminal transmits a signal during the remained period of the uplink slot. In this paper, both the single carrier CR network that uses one frequency channel of the cellular system and the multicarrier CR network that uses multiple frequency channels of the cellular system are considered. The probabilities of successful CR communications, the average throughputs of the CR communications according to the positions of the CR network, and the interference levels from cognitive radio network to base stations of the cellular system are evaluated in the computer simulation then the effectiveness of the proposed network is clarified.

SaeRS Is Responsive to Cellular Respiratory Status and Regulates Fermentative Biofilm Formation in Staphylococcus aureus.

PubMed

Mashruwala, Ameya A; Gries, Casey M; Scherr, Tyler D; Kielian, Tammy; Boyd, Jeffrey M

2017-08-01

Biofilms are multicellular communities of microorganisms living as a quorum rather than as individual cells. The bacterial human pathogen Staphylococcus aureus uses oxygen as a terminal electron acceptor during respiration. Infected human tissues are hypoxic or anoxic. We recently reported that impaired respiration elicits a p rogrammed c ell l ysis (PCL) phenomenon in S. aureus leading to the release of cellular polymers that are utilized to form biofilms. PCL is dependent upon the AtlA murein hydrolase and is regulated, in part, by the SrrAB two-component regulatory system (TCRS). In the current study, we report that the SaeRS TCRS also governs fermentative biofilm formation by positively influencing AtlA activity. The SaeRS-modulated factor fibronectin-binding protein A (FnBPA) also contributed to the fermentative biofilm formation phenotype. SaeRS-dependent biofilm formation occurred in response to changes in cellular respiratory status. Genetic evidence presented suggests that a high cellular titer of phosphorylated SaeR is required for biofilm formation. Epistasis analyses found that SaeRS and SrrAB influence biofilm formation independently of one another. Analyses using a mouse model of orthopedic implant-associated biofilm formation found that both SaeRS and SrrAB govern host colonization. Of these two TCRSs, SrrAB was the dominant system driving biofilm formation in vivo We propose a model wherein impaired cellular respiration stimulates SaeRS via an as yet undefined signal molecule(s), resulting in increasing expression of AtlA and FnBPA and biofilm formation. Copyright © 2017 American Society for Microbiology.

Thermodynamically consistent model calibration in chemical kinetics

PubMed Central

2011-01-01

Background The dynamics of biochemical reaction systems are constrained by the fundamental laws of thermodynamics, which impose well-defined relationships among the reaction rate constants characterizing these systems. Constructing biochemical reaction systems from experimental observations often leads to parameter values that do not satisfy the necessary thermodynamic constraints. This can result in models that are not physically realizable and may lead to inaccurate, or even erroneous, descriptions of cellular function. Results We introduce a thermodynamically consistent model calibration (TCMC) method that can be effectively used to provide thermodynamically feasible values for the parameters of an open biochemical reaction system. The proposed method formulates the model calibration problem as a constrained optimization problem that takes thermodynamic constraints (and, if desired, additional non-thermodynamic constraints) into account. By calculating thermodynamically feasible values for the kinetic parameters of a well-known model of the EGF/ERK signaling cascade, we demonstrate the qualitative and quantitative significance of imposing thermodynamic constraints on these parameters and the effectiveness of our method for accomplishing this important task. MATLAB software, using the Systems Biology Toolbox 2.1, can be accessed from http://www.cis.jhu.edu/~goutsias/CSS lab/software.html. An SBML file containing the thermodynamically feasible EGF/ERK signaling cascade model can be found in the BioModels database. Conclusions TCMC is a simple and flexible method for obtaining physically plausible values for the kinetic parameters of open biochemical reaction systems. It can be effectively used to recalculate a thermodynamically consistent set of parameter values for existing thermodynamically infeasible biochemical reaction models of cellular function as well as to estimate thermodynamically feasible values for the parameters of new models. Furthermore, TCMC can provide dimensionality reduction, better estimation performance, and lower computational complexity, and can help to alleviate the problem of data overfitting. PMID:21548948

47 CFR 22.923 - Cellular system configuration.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 47 Telecommunication 2 2013-10-01 2013-10-01 false Cellular system configuration. 22.923 Section 22.923 Telecommunication FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) COMMON CARRIER SERVICES PUBLIC MOBILE SERVICES Cellular Radiotelephone Service § 22.923 Cellular system configuration. Mobile stations...

47 CFR 22.923 - Cellular system configuration.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 47 Telecommunication 2 2014-10-01 2014-10-01 false Cellular system configuration. 22.923 Section 22.923 Telecommunication FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) COMMON CARRIER SERVICES PUBLIC MOBILE SERVICES Cellular Radiotelephone Service § 22.923 Cellular system configuration. Mobile stations...

Special Issue on Optochemical and Optogenetic Control of Cellular Processes.

PubMed

Deiters, Alexander

2018-06-06

Diverse optochemical and optobiological approaches are being developed and applied to the light-regulation of cellular processes with exquisite spatial and temporal resolution in cells and multicellular model organisms. In this special issue, experts report some of the latest progress in the expanding field of the optical control of biological systems and present an overview of the state of the art of select approaches. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Perceptual telerobotics

NASA Technical Reports Server (NTRS)

Ligomenides, Panos A.

1989-01-01

A sensory world modeling system, congruent with a human expert's perception, is proposed. The Experiential Knowledge Base (EKB) system can provide a highly intelligible communication interface for telemonitoring and telecontrol of a real time robotic system operating in space. Paradigmatic acquisition of empirical perceptual knowledge, and real time experiential pattern recognition and knowledge integration are reviewed. The cellular architecture and operation of the EKB system are also examined.

Simulating Microdosimetry of Environmental Chemicals for EPA’s Virtual Liver

EPA Science Inventory

US EPA Virtual Liver (v-Liver) is a cellular systems model of hepatic tissues aimed at predicting chemical-induced adverse effects through agent-based modeling. A primary objective of the project is to extrapolate in vitro data to in vivo outcomes. Agent-based approaches to tissu...

Probabilistic Cellular Automata

PubMed Central

Agapie, Alexandru; Giuclea, Marius

2014-01-01

Abstract Cellular automata are binary lattices used for modeling complex dynamical systems. The automaton evolves iteratively from one configuration to another, using some local transition rule based on the number of ones in the neighborhood of each cell. With respect to the number of cells allowed to change per iteration, we speak of either synchronous or asynchronous automata. If randomness is involved to some degree in the transition rule, we speak of probabilistic automata, otherwise they are called deterministic. With either type of cellular automaton we are dealing with, the main theoretical challenge stays the same: starting from an arbitrary initial configuration, predict (with highest accuracy) the end configuration. If the automaton is deterministic, the outcome simplifies to one of two configurations, all zeros or all ones. If the automaton is probabilistic, the whole process is modeled by a finite homogeneous Markov chain, and the outcome is the corresponding stationary distribution. Based on our previous results for the asynchronous case—connecting the probability of a configuration in the stationary distribution to its number of zero-one borders—the article offers both numerical and theoretical insight into the long-term behavior of synchronous cellular automata. PMID:24999557

Probabilistic cellular automata.

PubMed

Agapie, Alexandru; Andreica, Anca; Giuclea, Marius

2014-09-01

Cellular automata are binary lattices used for modeling complex dynamical systems. The automaton evolves iteratively from one configuration to another, using some local transition rule based on the number of ones in the neighborhood of each cell. With respect to the number of cells allowed to change per iteration, we speak of either synchronous or asynchronous automata. If randomness is involved to some degree in the transition rule, we speak of probabilistic automata, otherwise they are called deterministic. With either type of cellular automaton we are dealing with, the main theoretical challenge stays the same: starting from an arbitrary initial configuration, predict (with highest accuracy) the end configuration. If the automaton is deterministic, the outcome simplifies to one of two configurations, all zeros or all ones. If the automaton is probabilistic, the whole process is modeled by a finite homogeneous Markov chain, and the outcome is the corresponding stationary distribution. Based on our previous results for the asynchronous case-connecting the probability of a configuration in the stationary distribution to its number of zero-one borders-the article offers both numerical and theoretical insight into the long-term behavior of synchronous cellular automata.

[Computer simulation of thyroid regulatory mechanisms in health and malignancy].

PubMed

Abduvaliev, A A; Gil'dieva, M S; Khidirov, B N; Saĭdalieva, M; Saatov, T S

2010-07-01

The paper describes a computer model for regulation of the number of thyroid follicular cells in health and malignancy. The authors'computer program for mathematical simulation of the regulatory mechanisms of a thyroid follicular cellular community cannot be now referred to as good commercial products. For commercialization of this product, it is necessary to draw up a direct relation of the introduced corrected values from the actually existing normal values, such as the peripheral blood concentrations of thyroid hormones or the mean values of endocrine tissue mitotic activity. However, the described computer program has been also used in researches by our scientific group in the study of thyroid cancer. The available biological experimental data and theoretical provisions on thyroid structural and functional organization at the cellular level allow one to construct mathematical models for quantitative analysis of the regulation of the size of a cellular community of a thyroid follicle in health and abnormalities, by using the method for simulation of the regulatory mechanisms of living systems and the equations of cellular community regulatory communities.

Chemical combination effects predict connectivity in biological systems

PubMed Central

Lehár, Joseph; Zimmermann, Grant R; Krueger, Andrew S; Molnar, Raymond A; Ledell, Jebediah T; Heilbut, Adrian M; Short, Glenn F; Giusti, Leanne C; Nolan, Garry P; Magid, Omar A; Lee, Margaret S; Borisy, Alexis A; Stockwell, Brent R; Keith, Curtis T

2007-01-01

Efforts to construct therapeutically useful models of biological systems require large and diverse sets of data on functional connections between their components. Here we show that cellular responses to combinations of chemicals reveal how their biological targets are connected. Simulations of pathways with pairs of inhibitors at varying doses predict distinct response surface shapes that are reproduced in a yeast experiment, with further support from a larger screen using human tumour cells. The response morphology yields detailed connectivity constraints between nearby targets, and synergy profiles across many combinations show relatedness between targets in the whole network. Constraints from chemical combinations complement genetic studies, because they probe different cellular components and can be applied to disease models that are not amenable to mutagenesis. Chemical probes also offer increased flexibility, as they can be continuously dosed, temporally controlled, and readily combined. After extending this initial study to cover a wider range of combination effects and pathway topologies, chemical combinations may be used to refine network models or to identify novel targets. This response surface methodology may even apply to non-biological systems where responses to targeted perturbations can be measured. PMID:17332758

Pseudomonas aeruginosa RhlR is required to neutralize the cellular immune response in a Drosophila melanogaster oral infection model

PubMed Central

Limmer, Stefanie; Haller, Samantha; Drenkard, Eliana; Lee, Janice; Yu, Shen; Kocks, Christine; Ausubel, Frederick M.; Ferrandon, Dominique

2011-01-01

An in-depth mechanistic understanding of microbial infection necessitates a molecular dissection of host–pathogen relationships. Both Drosophila melanogaster and Pseudomonas aeruginosa have been intensively studied. Here, we analyze the infection of D. melanogaster by P. aeruginosa by using mutants in both host and pathogen. We show that orally ingested P. aeruginosa crosses the intestinal barrier and then proliferates in the hemolymph, thereby causing the infected flies to die of bacteremia. Host defenses against ingested P. aeruginosa included an immune deficiency (IMD) response in the intestinal epithelium, systemic Toll and IMD pathway responses, and a cellular immune response controlling bacteria in the hemocoel. Although the observed cellular and intestinal immune responses appeared to act throughout the course of the infection, there was a late onset of the systemic IMD and Toll responses. In this oral infection model, P. aeruginosa PA14 did not require its type III secretion system or other well-studied virulence factors such as the two-component response regulator GacA or the protease AprA for virulence. In contrast, the quorum-sensing transcription factor RhlR, but surprisingly not LasR, played a key role in counteracting the cellular immune response against PA14, possibly at an early stage when only a few bacteria are present in the hemocoel. These results illustrate the power of studying infection from the dual perspective of host and pathogen by revealing that RhlR plays a more complex role during pathogenesis than previously appreciated. PMID:21987808

Resonance, criticality, and emergence in city traffic investigated in cellular automaton models.

PubMed

Varas, A; Cornejo, M D; Toledo, B A; Muñoz, V; Rogan, J; Zarama, R; Valdivia, J A

2009-11-01

The complex behavior that occurs when traffic lights are synchronized is studied for a row of interacting cars. The system is modeled through a cellular automaton. Two strategies are considered: all lights in phase and a "green wave" with a propagating green signal. It is found that the mean velocity near the resonant condition follows a critical scaling law. For the green wave, it is shown that the mean velocity scaling law holds even for random separation between traffic lights and is not dependent on the density. This independence on car density is broken when random perturbations are considered in the car velocity. Random velocity perturbations also have the effect of leading the system to an emergent state, where cars move in clusters, but with an average velocity which is independent of traffic light switching for large injection rates.

An Asynchronous Cellular Automata-Based Adaptive Illumination Facility

NASA Astrophysics Data System (ADS)

Bandini, Stefania; Bonomi, Andrea; Vizzari, Giuseppe; Acconci, Vito

The term Ambient Intelligence refers to electronic environments that are sensitive and responsive to the presence of people; in the described scenario the environment itself is endowed with a set of sensors (to perceive humans or other physical entities such as dogs, bicycles, etc.), interacting with a set of actuators (lights) that choose their actions (i.e. state of illumination) in an attempt improve the overall experience of these users. The model for the interaction and action of sensors and actuators is an asynchronous Cellular Automata (CA) with memory, supporting a self-organization of the system as a response to the presence and movements of people inside it. The paper will introduce the model, as well as an ad hoc user interface for the specification of the relevant parameters of the CA transition rule that determines the overall system behaviour.

O-GlcNAc and the Cardiovascular System

PubMed Central

Dassanayaka, Sujith; Jones, Steven P.

2014-01-01

The cardiovascular system is capable of robust changes in response to physiologic and pathologic stimuli through intricate signaling mechanisms. The area of metabolism has witnessed a veritable renaissance in the cardiovascular system. In particular, the post-translational β-O-linkage of N-acetylglucosamine (O-GlcNAc) to cellular proteins represents one such signaling pathway that has been implicated in the pathophysiology of cardiovascular disease. This highly dynamic protein modification may induce functional changes in proteins and regulate key cellular processes including translation, transcription, and cell death. In addition, its potential interplay with phosphorylation provides an additional layer of complexity to post-translational regulation. The hexosamine biosynthetic pathway generally requires glucose to form the nucleotide sugar, UDP-GlcNAc. Accordingly, O-GlcNAcylation may be altered in response to nutrient availability and cellular stress. Recent literature supports O-GlcNAcylation as an autoprotective response in models of acute stress (hypoxia, ischemia, oxidative stress). Models of sustained stress, such as pressure overload hypertrophy, and infarct-induced heart failure, may also require protein O-GlcNAcylation as a partial compensatory mechanism. Yet, in models of Type II diabetes, O-GlcNAcylation has been implicated in the subsequent development of vascular, and even cardiac, dysfunction. This review will address this apparent paradox and discuss the potential mechanisms of O-GlcNAc-mediated cardioprotection and cardiovascular dysfunction. This discussion will also address potential targets for pharmacologic interventions and the unique considerations related to such targets. PMID:24287310

O-GlcNAc and the cardiovascular system.

PubMed

Dassanayaka, Sujith; Jones, Steven P

2014-04-01

The cardiovascular system is capable of robust changes in response to physiologic and pathologic stimuli through intricate signaling mechanisms. The area of metabolism has witnessed a veritable renaissance in the cardiovascular system. In particular, the post-translational β-O-linkage of N-acetylglucosamine (O-GlcNAc) to cellular proteins represents one such signaling pathway that has been implicated in the pathophysiology of cardiovascular disease. This highly dynamic protein modification may induce functional changes in proteins and regulate key cellular processes including translation, transcription, and cell death. In addition, its potential interplay with phosphorylation provides an additional layer of complexity to post-translational regulation. The hexosamine biosynthetic pathway generally requires glucose to form the nucleotide sugar, UDP-GlcNAc. Accordingly, O-GlcNAcylation may be altered in response to nutrient availability and cellular stress. Recent literature supports O-GlcNAcylation as an autoprotective response in models of acute stress (hypoxia, ischemia, oxidative stress). Models of sustained stress, such as pressure overload hypertrophy, and infarct-induced heart failure, may also require protein O-GlcNAcylation as a partial compensatory mechanism. Yet, in models of Type II diabetes, O-GlcNAcylation has been implicated in the subsequent development of vascular, and even cardiac, dysfunction. This review will address this apparent paradox and discuss the potential mechanisms of O-GlcNAc-mediated cardioprotection and cardiovascular dysfunction. This discussion will also address potential targets for pharmacologic interventions and the unique considerations related to such targets. Copyright © 2013 Elsevier Inc. All rights reserved.

The relationship between in vitro cellular aging and in vivo human age.

PubMed Central

Schneider, E L; Mitsui, Y

1976-01-01

Differences between early and late passage cell cultures on the organelle and macromolecular levels have been attributed to cellular "aging". However, concern has been expressed over whether changes in diploid cell populations after serial passage in vitro accurately reflect human cellular aging in vivo. Studies were therefore undertaken to determine if significant differences would be observed in the in vitro lifespans of skin fibroblast cultures from old and young normal, non-hospitalized volunteers and to examine if parameters that change with in vitro "aging" are altered as a function of age in vivo. Statistically signigificant (P less than 0.05) decreases were found in the rate of fibroblast migration, onset of cell culture senescence, in vitro lifespan, cell population replication rate, and cell number at confluency of fibroblast cultures derived from the old donor group when compared to parallel cultures from young donors. No significant differences were observed in modal cell volumes and cellular macromolecular contents. The differences observed in cell cultures from old and young donors were quantitatively and qualitatively distinct from those cellular alterations observed in early and late passage WI-38 cells (in vitro "aging"). Therefore, although early and late passage cultures of human diploid cells may provide an important cell system for examining loss of replicative potential, fibroblast cultures derived from old and young human donors may be a more appropriate model system for studying human cellular aging. PMID:1068470

The cellular and molecular mechanisms of tissue repair and regeneration as revealed by studies in Xenopus

PubMed Central

Li, Jingjing; Zhang, Siwei

2016-01-01

Abstract Survival of any living organism critically depends on its ability to repair and regenerate damaged tissues and/or organs during its lifetime following injury, disease, or aging. Various animal models from invertebrates to vertebrates have been used to investigate the molecular and cellular mechanisms of wound healing and tissue regeneration. It is hoped that such studies will form the framework for identifying novel clinical treatments that will improve the healing and regenerative capacity of humans. Amongst these models, Xenopus stands out as a particularly versatile and powerful system. This review summarizes recent findings using this model, which have provided fundamental knowledge of the mechanisms responsible for efficient and perfect tissue repair and regeneration. PMID:27800170

The acclimative biogeochemical model of the southern North Sea

NASA Astrophysics Data System (ADS)

Kerimoglu, Onur; Hofmeister, Richard; Maerz, Joeran; Riethmüller, Rolf; Wirtz, Kai W.

2017-10-01

Ecosystem models often rely on heuristic descriptions of autotrophic growth that fail to reproduce various stationary and dynamic states of phytoplankton cellular composition observed in laboratory experiments. Here, we present the integration of an advanced phytoplankton growth model within a coupled three-dimensional physical-biogeochemical model and the application of the model system to the southern North Sea (SNS) defined on a relatively high resolution (˜ 1.5-4.5 km) curvilinear grid. The autotrophic growth model, recently introduced by Wirtz and Kerimoglu (2016), is based on a set of novel concepts for the allocation of internal resources and operation of cellular metabolism. The coupled model system consists of the General Estuarine Transport Model (GETM) as the hydrodynamical driver, a lower-trophic-level model and a simple sediment diagenesis model. We force the model system with realistic atmospheric and riverine fluxes, background turbidity caused by suspended particulate matter (SPM) and open ocean boundary conditions. For a simulation for the period 2000-2010, we show that the model system satisfactorily reproduces the physical and biogeochemical states of the system within the German Bight characterized by steep salinity; nutrient and chlorophyll (Chl) gradients, as inferred from comparisons against observation data from long-term monitoring stations; sparse in situ measurements; continuous transects; and satellites. The model also displays skill in capturing the formation of thin chlorophyll layers at the pycnocline, which is frequently observed within the stratified regions during summer. A sensitivity analysis reveals that the vertical distributions of phytoplankton concentrations estimated by the model can be qualitatively sensitive to the description of the light climate and dependence of sinking rates on the internal nutrient reserves. A non-acclimative (fixed-physiology) version of the model predicted entirely different vertical profiles, suggesting that accounting for physiological flexibility might be relevant for a consistent representation of the vertical distribution of phytoplankton biomass. Our results point to significant variability in the cellular chlorophyll-to-carbon ratio (Chl : C) across seasons and the coastal to offshore transition. Up to 3-fold-higher Chl : C at the coastal areas in comparison to those at the offshore areas contribute to the steepness of the chlorophyll gradient. The model also predicts much higher phytoplankton concentrations at the coastal areas in comparison to its non-acclimative equivalent. Hence, findings of this study provide evidence for the relevance of physiological flexibility, here reflected by spatial and seasonal variations in Chl : C, for a realistic description of biogeochemical fluxes, particularly in the environments displaying strong resource gradients.

Agent-based modeling of the immune system: NetLogo, a promising framework.

PubMed

Chiacchio, Ferdinando; Pennisi, Marzio; Russo, Giulia; Motta, Santo; Pappalardo, Francesco

2014-01-01

Several components that interact with each other to evolve a complex, and, in some cases, unexpected behavior, represents one of the main and fascinating features of the mammalian immune system. Agent-based modeling and cellular automata belong to a class of discrete mathematical approaches in which entities (agents) sense local information and undertake actions over time according to predefined rules. The strength of this approach is characterized by the appearance of a global behavior that emerges from interactions among agents. This behavior is unpredictable, as it does not follow linear rules. There are a lot of works that investigates the immune system with agent-based modeling and cellular automata. They have shown the ability to see clearly and intuitively into the nature of immunological processes. NetLogo is a multiagent programming language and modeling environment for simulating complex phenomena. It is designed for both research and education and is used across a wide range of disciplines and education levels. In this paper, we summarize NetLogo applications to immunology and, particularly, how this framework can help in the development and formulation of hypotheses that might drive further experimental investigations of disease mechanisms.

Cellular Gauge Symmetry and the Li Organization Principle: A Mathematical Addendum. Quantifying energetic dynamics in physical and biological systems through a simple geometric tool and geodetic curves.

PubMed

Yurkin, Alexander; Tozzi, Arturo; Peters, James F; Marijuán, Pedro C

2017-12-01

The present Addendum complements the accompanying paper "Cellular Gauge Symmetry and the Li Organization Principle"; it illustrates a recently-developed geometrical physical model able to assess electronic movements and energetic paths in atomic shells. The model describes a multi-level system of circular, wavy and zigzag paths which can be projected onto a horizontal tape. This model ushers in a visual interpretation of the distribution of atomic electrons' energy levels and the corresponding quantum numbers through rather simple tools, such as compasses, rulers and straightforward calculations. Here we show how this geometrical model, with the due corrections, among them the use of geodetic curves, might be able to describe and quantify the structure and the temporal development of countless physical and biological systems, from Langevin equations for random paths, to symmetry breaks occurring ubiquitously in physical and biological phenomena, to the relationships among different frequencies of EEG electric spikes. Therefore, in our work we explore the possible association of binomial distribution and geodetic curves configuring a uniform approach for the research of natural phenomena, in biology, medicine or the neurosciences. Copyright © 2017 Elsevier Ltd. All rights reserved.

Cellular Models: HD Patient-Derived Pluripotent Stem Cells.

PubMed

Geater, Charlene; Hernandez, Sarah; Thompson, Leslie; Mattis, Virginia B

2018-01-01

Huntington's disease (HD) is an autosomal dominant neurodegenerative disorder caused by expanded polyglutamine (polyQ)-encoding repeats in the Huntingtin (HTT) gene. Traditionally, HD cellular models consisted of either patient cells not affected by disease or rodent neurons expressing expanded polyQ repeats in HTT. As these models can be limited in their disease manifestation or proper genetic context, respectively, human HD pluripotent stem cells (PSCs) are currently under investigation as a way to model disease in patient-derived neurons and other neural cell types. This chapter reviews embryonic stem cell (ESC) and induced pluripotent stem cell (iPSC) models of disease, including published differentiation paradigms for neurons and their associated phenotypes, as well as current challenges to the field such as validation of the PSCs and PSC-derived cells. Highlighted are potential future technical advances to HD PSC modeling, including transdifferentiation, complex in vitro multiorgan/system reconstruction, and personalized medicine. Using a human HD patient model of the central nervous system, hopefully one day researchers can tease out the consequences of mutant HTT (mHTT) expression on specific cell types within the brain in order to identify and test novel therapies for disease.

Potential large animal models for gene therapy of human genetic diseases of immune and blood cell systems.

PubMed

Bauer, Thomas R; Adler, Rima L; Hickstein, Dennis D

2009-01-01

Genetic mutations involving the cellular components of the hematopoietic system--red blood cells, white blood cells, and platelets--manifest clinically as anemia, infection, and bleeding. Although gene targeting has recapitulated many of these diseases in mice, these murine homologues are limited as translational models by their small size and brief life span as well as the fact that mutations induced by gene targeting do not always faithfully reflect the clinical manifestations of such mutations in humans. Many of these limitations can be overcome by identifying large animals with genetic diseases of the hematopoietic system corresponding to their human disease counterparts. In this article, we describe human diseases of the cellular components of the hematopoietic system that have counterparts in large animal species, in most cases carrying mutations in the same gene (CD18 in leukocyte adhesion deficiency) or genes in interacting proteins (DNA cross-link repair 1C protein and protein kinase, DNA-activated catalytic polypeptide in radiation-sensitive severe combined immunodeficiency). Furthermore, we describe the potential of these animal models to serve as disease-specific preclinical models for testing the efficacy and safety of clinical interventions such as hematopoietic stem cell transplantation or gene therapy before their use in humans with the corresponding disease.

DREW-UCLA Breast Cancer Research and Training Program: Molecular/Cellular Pathogenesis Model

DTIC Science & Technology

2007-03-01

system in bovine renal brush- border [13] and in a bovine renal epithelial cell line NBL -1 [14]. In order to highlight the substrate difference with an... NBL -1 expresses a broad specificity Na(+)-dependent neu- tral amino acid transport system (System B0) similar to that in bovine renal brush border

Simulation of glioblastoma multiforme (GBM) tumor cells using ising model on the Creutz Cellular Automaton

NASA Astrophysics Data System (ADS)

Züleyha, Artuç; Ziya, Merdan; Selçuk, Yeşiltaş; Kemal, Öztürk M.; Mesut, Tez

2017-11-01

Computational models for tumors have difficulties due to complexity of tumor nature and capacities of computational tools, however, these models provide visions to understand interactions between tumor and its micro environment. Moreover computational models have potential to develop strategies for individualized treatments for cancer. To observe a solid brain tumor, glioblastoma multiforme (GBM), we present a two dimensional Ising Model applied on Creutz cellular automaton (CCA). The aim of this study is to analyze avascular spherical solid tumor growth, considering transitions between non tumor cells and cancer cells are like phase transitions in physical system. Ising model on CCA algorithm provides a deterministic approach with discrete time steps and local interactions in position space to view tumor growth as a function of time. Our simulation results are given for fixed tumor radius and they are compatible with theoretical and clinic data.

Multiscale Systems Analysis of Root Growth and Development: Modeling Beyond the Network and Cellular Scales

PubMed Central

Band, Leah R.; Fozard, John A.; Godin, Christophe; Jensen, Oliver E.; Pridmore, Tony; Bennett, Malcolm J.; King, John R.

2012-01-01

Over recent decades, we have gained detailed knowledge of many processes involved in root growth and development. However, with this knowledge come increasing complexity and an increasing need for mechanistic modeling to understand how those individual processes interact. One major challenge is in relating genotypes to phenotypes, requiring us to move beyond the network and cellular scales, to use multiscale modeling to predict emergent dynamics at the tissue and organ levels. In this review, we highlight recent developments in multiscale modeling, illustrating how these are generating new mechanistic insights into the regulation of root growth and development. We consider how these models are motivating new biological data analysis and explore directions for future research. This modeling progress will be crucial as we move from a qualitative to an increasingly quantitative understanding of root biology, generating predictive tools that accelerate the development of improved crop varieties. PMID:23110897

Lab-On-Chip Clinorotation System for Live-Cell Microscopy Under Simulated Microgravity

NASA Technical Reports Server (NTRS)

Yew, Alvin G.; Atencia, Javier; Chinn, Ben; Hsieh, Adam H.

2013-01-01

Cells in microgravity are subject to mechanical unloading and changes to the surrounding chemical environment. How these factors jointly influence cellular function is not well understood. We can investigate their role using ground-based analogues to spaceflight, where mechanical unloading is simulated through the time-averaged nullification of gravity. The prevailing method for cellular microgravity simulation is to use fluid-filled containers called clinostats. However, conventional clinostats are not designed for temporally tracking cell response, nor are they able to establish dynamic fluid environments. To address these needs, we developed a Clinorotation Time-lapse Microscopy (CTM) system that accommodates lab-on- chip cell culture devices for visualizing time-dependent alterations to cellular behavior. For the purpose of demonstrating CTM, we present preliminary results showing time-dependent differences in cell area between human mesenchymal stem cells (hMSCs) under modeled microgravity and normal gravity.

Lab-On-Chip Clinorotation System for Live-Cell Microscopy Under Simulated Microgravity

NASA Technical Reports Server (NTRS)

Yew, Alvin G.; Atencia, Javier; Chinn, Ben; Hsieh, Adam H.

1980-01-01

Cells in microgravity are subject to mechanical unloading and changes to the surrounding chemical environment. How these factors jointly influence cellular function is not well understood. We can investigate their role using ground-based analogues to spaceflight, where mechanical unloading is simulated through the time-averaged nullification of gravity. The prevailing method for cellular microgravity simulation is to use fluid-filled containers called clinostats. However, conventional clinostats are not designed for temporally tracking cell response, nor are they able to establish dynamic fluid environments. To address these needs, we developed a Clinorotation Time-lapse Microscopy (CTM) system that accommodates lab-on- chip cell culture devices for visualizing time-dependent alterations to cellular behavior. For the purpose of demonstrating CTM, we present preliminary results showing time-dependent differences in cell area between human mesenchymal stem cells (hMSCs) under modeled microgravity and normal gravity.

Identification and characterization of a novel ISG15-ubiquitin mixed chain and its role in regulating protein homeostasis

PubMed Central

Fan, Jun-Bao; Arimoto, Kei-lchiro; Motamedchaboki, Khatereh; Yan, Ming; Wolf, Dieter A.; Zhang, Dong-Er

2015-01-01

As a ubiquitin-like modifier, ISG15 is conjugated to many cellular proteins in a process termed protein ISGylation. However, the crosstalk between protein ISGylation and the ubiquitin proteasome system is not fully understood. Here, we report that cellular ubiquitin is a substrate of ISG15 and Lys 29 on ubiquitin is the major ISG15 acceptor site. Using a model substrate, we demonstrate that ISG15 can modify ubiquitin, which is immobilized on its substrate, to form ISG15-ubiquitin mixed chains. Furthermore, our results indicate that ISG15-ubiquitin mixed chains do not serve as degradation signals for a ubiquitin fusion degradation substrate. Accordingly, an ISG15-ubiquitin fusion protein, which mimics an ISG15-ubiquitin mixed chain, negatively regulates cellular turnover of ubiquitylated proteins. In addition, ISG15-ubiquitin mixed chains, which are detectable on endogenously ubiquitylated proteins, dampen cellular turnover of these proteins. Thus, our studies unveil an unanticipated interplay between two protein modification systems and highlight its role in coordinating protein homeostasis. PMID:26226047

47 CFR 90.672 - Unacceptable interference to non-cellular 800 MHz licensees from 800 MHz cellular systems or part...

Code of Federal Regulations, 2010 CFR

2010-10-01

... 47 Telecommunication 5 2010-10-01 2010-10-01 false Unacceptable interference to non-cellular 800 MHz licensees from 800 MHz cellular systems or part 22 Cellular Radiotelephone systems, and within the 900 MHz Business/Industrial Land Transportation Pool. 90.672 Section 90.672 Telecommunication FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) SAFETY...

Two-threshold model for scaling laws of noninteracting snow avalanches

USGS Publications Warehouse

Faillettaz, J.; Louchet, F.; Grasso, J.-R.

2004-01-01

A two-threshold model was proposed for scaling laws of noninteracting snow avalanches. It was found that the sizes of the largest avalanches just preceding the lattice system were power-law distributed. The proposed model reproduced the range of power-law exponents observe for land, rock or snow avalanches, by tuning the maximum value of the ratio of the two failure thresholds. A two-threshold 2D cellular automation was introduced to study the scaling for gravity-driven systems.

Cellular telephone interference with medical equipment.

PubMed

Tri, Jeffrey L; Severson, Rodney P; Firl, Allen R; Hayes, David L; Abenstein, John P

2005-10-01

To assess the potential electromagnetic interference (EMI) effects that new or current-generation cellular telephones have on medical devices. For this study, performed at the Mayo Clinic in Rochester, Minn, between March 9, 2004, and April 24, 2004, we tested 16 different medical devices with 6 cellular telephones to assess the potential for EMI. Two of the medical devices were tested with both new and old interface modules. The 6 cellular telephones chosen represent the different cellular technology protocols in use: Code Division Multiple Access (2 models), Global System for Mobile communications, Integrated Digital Enhanced Network, Time Division Multiple Access, and analog. The cellular telephones were tested when operating at or near their maximum power output. The medical devices, connected to clinical simulators during testing, were monitored by observing the device displays and alarms. Of 510 tests performed, the incidence of clinically important interference was 1.2%; EMI was Induced in 108 tests (21.2%). Interference occurred in 7 (44%) of the 16 devices tested. Cellular telephones can interfere with medical equipment. Technology changes in both cellular telephones and medical equipment may continue to mitigate or may worsen clinically relevant interference. Compared with cellular telephones tested in previous studies, those currently in use must be closer to medical devices before any interference is noticed. However, periodic testing of cellular telephones to determine their effects on medical equipment will be required.

In Vitro Experimental Model for the Long-Term Analysis of Cellular Dynamics During Bronchial Tree Development from Lung Epithelial Cells

PubMed Central

Maruta, Naomichi; Marumoto, Moegi

2017-01-01

Lung branching morphogenesis has been studied for decades, but the underlying developmental mechanisms are still not fully understood. Cellular movements dynamically change during the branching process, but it is difficult to observe long-term cellular dynamics by in vivo or tissue culture experiments. Therefore, developing an in vitro experimental model of bronchial tree would provide an essential tool for developmental biology, pathology, and systems biology. In this study, we succeeded in reconstructing a bronchial tree in vitro by using primary human bronchial epithelial cells. A high concentration gradient of bronchial epithelial cells was required for branching initiation, whereas homogeneously distributed endothelial cells induced the formation of successive branches. Subsequently, the branches grew in size to the order of millimeter. The developed model contains only two types of cells and it facilitates the analysis of lung branching morphogenesis. By taking advantage of our experimental model, we carried out long-term time-lapse observations, which revealed self-assembly, collective migration with leader cells, rotational motion, and spiral motion of epithelial cells in each developmental event. Mathematical simulation was also carried out to analyze the self-assembly process and it revealed simple rules that govern cellular dynamics. Our experimental model has provided many new insights into lung development and it has the potential to accelerate the study of developmental mechanisms, pattern formation, left–right asymmetry, and disease pathogenesis of the human lung. PMID:28471293

A white-box model of S-shaped and double S-shaped single-species population growth

PubMed Central

Kalmykov, Lev V.

2015-01-01

Complex systems may be mechanistically modelled by white-box modeling with using logical deterministic individual-based cellular automata. Mathematical models of complex systems are of three types: black-box (phenomenological), white-box (mechanistic, based on the first principles) and grey-box (mixtures of phenomenological and mechanistic models). Most basic ecological models are of black-box type, including Malthusian, Verhulst, Lotka–Volterra models. In black-box models, the individual-based (mechanistic) mechanisms of population dynamics remain hidden. Here we mechanistically model the S-shaped and double S-shaped population growth of vegetatively propagated rhizomatous lawn grasses. Using purely logical deterministic individual-based cellular automata we create a white-box model. From a general physical standpoint, the vegetative propagation of plants is an analogue of excitation propagation in excitable media. Using the Monte Carlo method, we investigate a role of different initial positioning of an individual in the habitat. We have investigated mechanisms of the single-species population growth limited by habitat size, intraspecific competition, regeneration time and fecundity of individuals in two types of boundary conditions and at two types of fecundity. Besides that, we have compared the S-shaped and J-shaped population growth. We consider this white-box modeling approach as a method of artificial intelligence which works as automatic hyper-logical inference from the first principles of the studied subject. This approach is perspective for direct mechanistic insights into nature of any complex systems. PMID:26038717

Computer Modeling of the Earliest Cellular Structures and Functions

NASA Technical Reports Server (NTRS)

Pohorille, Andrew; Chipot, Christophe; Schweighofer, Karl

2000-01-01

In the absence of extinct or extant record of protocells (the earliest ancestors of contemporary cells). the most direct way to test our understanding of the origin of cellular life is to construct laboratory models of protocells. Such efforts are currently underway in the NASA Astrobiology Program. They are accompanied by computational studies aimed at explaining self-organization of simple molecules into ordered structures and developing designs for molecules that perform proto-cellular functions. Many of these functions, such as import of nutrients, capture and storage of energy. and response to changes in the environment are carried out by proteins bound to membrane< We will discuss a series of large-scale, molecular-level computer simulations which demonstrate (a) how small proteins (peptides) organize themselves into ordered structures at water-membrane interfaces and insert into membranes, (b) how these peptides aggregate to form membrane-spanning structures (eg. channels), and (c) by what mechanisms such aggregates perform essential proto-cellular functions, such as proton transport of protons across cell walls, a key step in cellular bioenergetics. The simulations were performed using the molecular dynamics method, in which Newton's equations of motion for each item in the system are solved iteratively. The problems of interest required simulations on multi-nanosecond time scales, which corresponded to 10(exp 6)-10(exp 8) time steps.

Cellular self-assembly and biomaterials-based organoid models of development and diseases.

PubMed

Shah, Shivem B; Singh, Ankur

2017-04-15

Organogenesis and morphogenesis have informed our understanding of physiology, pathophysiology, and avenues to create new curative and regenerative therapies. Thus far, this understanding has been hindered by the lack of a physiologically relevant yet accessible model that affords biological control. Recently, three-dimensional ex vivo cellular cultures created through cellular self-assembly under natural extracellular matrix cues or through biomaterial-based directed assembly have been shown to physically resemble and recapture some functionality of target organs. These "organoids" have garnered momentum for their applications in modeling human development and disease, drug screening, and future therapy design or even organ replacement. This review first discusses the self-organizing organoids as materials with emergent properties and their advantages and limitations. We subsequently describe biomaterials-based strategies used to afford more control of the organoid's microenvironment and ensuing cellular composition and organization. In this review, we also offer our perspective on how multifunctional biomaterials with precise spatial and temporal control could ultimately bridge the gap between in vitro organoid platforms and their in vivo counterparts. Several notable reviews have highlighted PSC-derived organoids and 3D aggregates, including embryoid bodies, from a development and cellular assembly perspective. The focus of this review is to highlight the materials-based approaches that cells, including PSCs and others, adopt for self-assembly and the controlled development of complex tissues, such as that of the brain, gut, and immune system. Copyright © 2017 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Investigation of the subcellular architecture of L7 neurons of Aplysia californica using magnetic resonance microscopy (MRM) at 7.8 microns.

PubMed

Lee, Choong H; Flint, Jeremy J; Hansen, Brian; Blackband, Stephen J

2015-06-10

Magnetic resonance microscopy (MRM) is a non-invasive diagnostic tool which is well-suited to directly resolve cellular structures in ex vivo and in vitro tissues without use of exogenous contrast agents. Recent advances in its capability to visualize mammalian cellular structure in intact tissues have reinvigorated analytical interest in aquatic cell models whose previous findings warrant up-to-date validation of subcellular components. Even if the sensitivity of MRM is less than other microscopic technologies, its strength lies in that it relies on the same image contrast mechanisms as clinical MRI which make it a unique tool for improving our ability to interpret human diagnostic imaging through high resolution studies of well-controlled biological model systems. Here, we investigate the subcellular MR signal characteristics of isolated cells of Aplysia californica at an in-plane resolution of 7.8 μm. In addition, direct correlation and positive identification of subcellular architecture in the cells is achieved through well-established histology. We hope this methodology will serve as the groundwork for studying pathophysiological changes through perturbation studies and allow for development of disease-specific cellular modeling tools. Such an approach promises to reveal the MR contrast changes underlying cellular mechanisms in various human diseases, for example in ischemic stroke.

Low-Intensity Pulsed Ultrasound Protects Retinal Ganglion Cell From Optic Nerve Injury Induced Apoptosis via Yes Associated Protein

PubMed Central

Zhou, Jia-Xing; Liu, Yun-Jia; Chen, Xi; Zhang, Xi; Xu, Jie; Yang, Ke; Wang, Dong; Lin, Sen; Ye, Jian

2018-01-01

Background: Low-intensity pulsed ultrasound (LIPUS) has been used in clinical studies. But little is known about its effects on the central nervous system (CNS), or its mechanism of action. Retinal ganglion cells (RGCs) are CNS neuronal cells that can be utilized as a classic model system to evaluate outcomes of LIPUS protection from external trauma-induced retinal injury. In this study, we aim to: (1) determine the pulse energy and the capability of LIPUS in RGC viability, (2) ascertain the protective role of LIPUS in optic nerve (ON) crush-induced retinal injury, and 3) explore the cellular mechanisms of RGC apoptosis prevention by LIPUS. Methods: An ON crush model was set up to induce RGC death. LIPUS was used to treat mice eyes daily, and the retina samples were dissected for immunostaining and Western blot. The expression of yes-associated protein (YAP) and apoptosis-related proteins was detected by immunostaining and Western blot in vitro and in vivo. Apoptosis of RGCs was evaluated by TUNEL staining, the survival of RGCs and retained axons were labeled by Fluoro-gold and Tuj1 antibody, respectively. Rotenone was used to set up an in vitro cellular degenerative model and siYAP was used to interfering the expression of YAP to detect the LIPUS protective function. Results: LIPUS protected RGC from loss and apoptosis in vivo and in vitro. The ratio of cleaved/pro-caspase3 also decreased significantly under LIPUS treatment. As a cellular mechanical sensor, YAP expression increased and YAP translocated to nucleus in LIPUS stimulation group, however, phospho-YAP was found to be decreased. When YAP was inhibited, the LIPUS could not protect RGC from caspase3-dependent apoptosis. Conclusion: LIPUS prevented RGCs from apoptosis in an ON crush model and in vitro cellular degenerative model, which indicates a potential treatment for further traumatic ON injury. The mechanism of protection is dependent on YAP activation and correlated with caspase-3 signaling.

BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models

PubMed Central

2010-01-01

Background Quantitative models of biochemical and cellular systems are used to answer a variety of questions in the biological sciences. The number of published quantitative models is growing steadily thanks to increasing interest in the use of models as well as the development of improved software systems and the availability of better, cheaper computer hardware. To maximise the benefits of this growing body of models, the field needs centralised model repositories that will encourage, facilitate and promote model dissemination and reuse. Ideally, the models stored in these repositories should be extensively tested and encoded in community-supported and standardised formats. In addition, the models and their components should be cross-referenced with other resources in order to allow their unambiguous identification. Description BioModels Database http://www.ebi.ac.uk/biomodels/ is aimed at addressing exactly these needs. It is a freely-accessible online resource for storing, viewing, retrieving, and analysing published, peer-reviewed quantitative models of biochemical and cellular systems. The structure and behaviour of each simulation model distributed by BioModels Database are thoroughly checked; in addition, model elements are annotated with terms from controlled vocabularies as well as linked to relevant data resources. Models can be examined online or downloaded in various formats. Reaction network diagrams generated from the models are also available in several formats. BioModels Database also provides features such as online simulation and the extraction of components from large scale models into smaller submodels. Finally, the system provides a range of web services that external software systems can use to access up-to-date data from the database. Conclusions BioModels Database has become a recognised reference resource for systems biology. It is being used by the community in a variety of ways; for example, it is used to benchmark different simulation systems, and to study the clustering of models based upon their annotations. Model deposition to the database today is advised by several publishers of scientific journals. The models in BioModels Database are freely distributed and reusable; the underlying software infrastructure is also available from SourceForge https://sourceforge.net/projects/biomodels/ under the GNU General Public License. PMID:20587024

Integrated cellular network of transcription regulations and protein-protein interactions

PubMed Central

2010-01-01

Background With the accumulation of increasing omics data, a key goal of systems biology is to construct networks at different cellular levels to investigate cellular machinery of the cell. However, there is currently no satisfactory method to construct an integrated cellular network that combines the gene regulatory network and the signaling regulatory pathway. Results In this study, we integrated different kinds of omics data and developed a systematic method to construct the integrated cellular network based on coupling dynamic models and statistical assessments. The proposed method was applied to S. cerevisiae stress responses, elucidating the stress response mechanism of the yeast. From the resulting integrated cellular network under hyperosmotic stress, the highly connected hubs which are functionally relevant to the stress response were identified. Beyond hyperosmotic stress, the integrated network under heat shock and oxidative stress were also constructed and the crosstalks of these networks were analyzed, specifying the significance of some transcription factors to serve as the decision-making devices at the center of the bow-tie structure and the crucial role for rapid adaptation scheme to respond to stress. In addition, the predictive power of the proposed method was also demonstrated. Conclusions We successfully construct the integrated cellular network which is validated by literature evidences. The integration of transcription regulations and protein-protein interactions gives more insight into the actual biological network and is more predictive than those without integration. The method is shown to be powerful and flexible and can be used under different conditions and for different species. The coupling dynamic models of the whole integrated cellular network are very useful for theoretical analyses and for further experiments in the fields of network biology and synthetic biology. PMID:20211003

Integrated cellular network of transcription regulations and protein-protein interactions.

PubMed

Wang, Yu-Chao; Chen, Bor-Sen

2010-03-08

With the accumulation of increasing omics data, a key goal of systems biology is to construct networks at different cellular levels to investigate cellular machinery of the cell. However, there is currently no satisfactory method to construct an integrated cellular network that combines the gene regulatory network and the signaling regulatory pathway. In this study, we integrated different kinds of omics data and developed a systematic method to construct the integrated cellular network based on coupling dynamic models and statistical assessments. The proposed method was applied to S. cerevisiae stress responses, elucidating the stress response mechanism of the yeast. From the resulting integrated cellular network under hyperosmotic stress, the highly connected hubs which are functionally relevant to the stress response were identified. Beyond hyperosmotic stress, the integrated network under heat shock and oxidative stress were also constructed and the crosstalks of these networks were analyzed, specifying the significance of some transcription factors to serve as the decision-making devices at the center of the bow-tie structure and the crucial role for rapid adaptation scheme to respond to stress. In addition, the predictive power of the proposed method was also demonstrated. We successfully construct the integrated cellular network which is validated by literature evidences. The integration of transcription regulations and protein-protein interactions gives more insight into the actual biological network and is more predictive than those without integration. The method is shown to be powerful and flexible and can be used under different conditions and for different species. The coupling dynamic models of the whole integrated cellular network are very useful for theoretical analyses and for further experiments in the fields of network biology and synthetic biology.

An Integrative Model of the Cardiovascular System Coupling Heart Cellular Mechanics with Arterial Network Hemodynamics

PubMed Central

Kim, Young-Tae; Lee, Jeong Sang; Youn, Chan-Hyun; Choi, Jae-Sung

2013-01-01

The current study proposes a model of the cardiovascular system that couples heart cell mechanics with arterial hemodynamics to examine the physiological role of arterial blood pressure (BP) in left ventricular hypertrophy (LVH). We developed a comprehensive multiphysics and multiscale cardiovascular model of the cardiovascular system that simulates physiological events, from membrane excitation and the contraction of a cardiac cell to heart mechanics and arterial blood hemodynamics. Using this model, we delineated the relationship between arterial BP or pulse wave velocity and LVH. Computed results were compared with existing clinical and experimental observations. To investigate the relationship between arterial hemodynamics and LVH, we performed a parametric study based on arterial wall stiffness, which was obtained in the model. Peak cellular stress of the left ventricle and systolic blood pressure (SBP) in the brachial and central arteries also increased; however, further increases were limited for higher arterial stiffness values. Interestingly, when we doubled the value of arterial stiffness from the baseline value, the percentage increase of SBP in the central artery was about 6.7% whereas that of the brachial artery was about 3.4%. It is suggested that SBP in the central artery is more critical for predicting LVH as compared with other blood pressure measurements. PMID:23960442

MCF-10A-NeoST: A New Cell System for Studying Cell-ECM and Cell-Cell Interactions in Breast Cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zantek, Nicole Dodge; Walker-Daniels, Jennifer; Stewart, Jane

2001-08-22

There is a continuing need for genetically matched cell systems to model cellular behaviors that are frequently observed in aggressive breast cancers. We report here the isolation and initial characterization of a spontaneously arising variant of MCF-10A cells, NeoST, which provides a new model to study cell adhesion and signal transduction in breast cancer. NeoST cells recapitulate important biological and biochemical features of metastatic breast cancer, including anchorage-independent growth, invasiveness in threedimensional reconstituted membranes, loss of E-cadherin expression, and increased tyrosine kinase activity. A comprehensive analysis of tyrosine kinase expression revealed overexpression or functional activation of the Axl, FAK, andmore » EphA2 tyrosine kinases in transformed MCF-10A cells. MCF-10A and these new derivatives provide a genetically matched model to study defects in cell adhesion and signaling that are relevant to cellular behaviors that often typify aggressive breast cancer cells.« less

Correlated receptor transport processes buffer single-cell heterogeneity

PubMed Central

Kallenberger, Stefan M.; Unger, Anne L.; Legewie, Stefan; Lymperopoulos, Konstantinos; Eils, Roland

2017-01-01

Cells typically vary in their response to extracellular ligands. Receptor transport processes modulate ligand-receptor induced signal transduction and impact the variability in cellular responses. Here, we quantitatively characterized cellular variability in erythropoietin receptor (EpoR) trafficking at the single-cell level based on live-cell imaging and mathematical modeling. Using ensembles of single-cell mathematical models reduced parameter uncertainties and showed that rapid EpoR turnover, transport of internalized EpoR back to the plasma membrane, and degradation of Epo-EpoR complexes were essential for receptor trafficking. EpoR trafficking dynamics in adherent H838 lung cancer cells closely resembled the dynamics previously characterized by mathematical modeling in suspension cells, indicating that dynamic properties of the EpoR system are widely conserved. Receptor transport processes differed by one order of magnitude between individual cells. However, the concentration of activated Epo-EpoR complexes was less variable due to the correlated kinetics of opposing transport processes acting as a buffering system. PMID:28945754

In situ sensing and modeling of molecular events at the cellular level

NASA Astrophysics Data System (ADS)

Yang, Ruiguo

We developed the Atomic Force Microscopy (AFM) based nanorobot in combination with other nanomechanical sensors for the investigation of cell signaling pathways. The AFM nanorobotics hinge on the superior spatial resolution of AFM in imaging and extends it into the measurement of biological processes and manipulation of biological matters. A multiple input single output control system was designed and implemented to solve the issues of nanomanipulation of biological materials, feedback, response frequency and nonlinearity. The AFM nanorobotic system therefore provide the human-directed position, velocity and force control with high frequency feedback, and more importantly it can feed the operator with the real-time imaging of manipulation result from the fast-imaging based local scanning. The use of the system has taken the study of cellular process at the molecular scale into a new level. The cellular response to the physiological conditions can be significantly manifested in cellular mechanics. Dynamic mechanical property has been regarded as biomarkers, sometimes even regulators of the signaling and physiological processes, thus the name mechanobiology. We sought to characterize the relationship between the structural dynamics and the molecular dynamics and the role of them in the regulation of cell behavior. We used the AFM nanorobotics to investigate the mechanical properties in real-time of cells that are stimulated by different chemical species. These reagents could result in similar ion channel responses but distinctive mechanical behaviors. We applied these measurement results to establish a model that describes the cellular stimulation and the mechanical property change, a "two-hit" model that comprises the loss of cell adhesion and the initiation of cell apoptosis. The first hit was verified by functional experiments: depletion of Calcium and nanosurgery to disrupt the cellular adhesion. The second hit was tested by a labeling of apoptotic markers that were revealed by flow cytometry. The model would then be able to decipher qualitatively the molecular dynamics infolded in the regulation of cell behavior. To decipher the signaling pathway quantitatively, we employed a nanomechanical sensor at the bottom of the cell, quartz crystal microbalance with energy dissipation monitoring (QCM-D) to monitor the change at the basal area of the cell. This would provide the real time focal adhesion information and would be used in accordance with the AFM measurement data on the top of the cell to build a more complete mechanical profile during the antibody induced signaling process. We developed a model from a systematic control perspective that considers the signaling cascade at certain stimulation as the controller and the mechanical and structural interaction of the cell as the plant. We firstly derived the plant model based on QCM-D and AFM measurement processes. A signaling pathway model was built on a grey box approach where part of the pathway map was delineated in detail while others were condensed into a single reaction. The model parameters were obtained by extracting the mechanical response from the experiment. The model refinements were conducted by testing a series of inhibition mechanisms and comparing the simulation data with the experimental data. The model was then used to predict the existences of certain reactions that are qualitatively reported in the literature.

A Compact Synchronous Cellular Model of Nonlinear Calcium Dynamics: Simulation and FPGA Synthesis Results.

PubMed

Soleimani, Hamid; Drakakis, Emmanuel M

2017-06-01

Recent studies have demonstrated that calcium is a widespread intracellular ion that controls a wide range of temporal dynamics in the mammalian body. The simulation and validation of such studies using experimental data would benefit from a fast large scale simulation and modelling tool. This paper presents a compact and fully reconfigurable cellular calcium model capable of mimicking Hopf bifurcation phenomenon and various nonlinear responses of the biological calcium dynamics. The proposed cellular model is synthesized on a digital platform for a single unit and a network model. Hardware synthesis, physical implementation on FPGA, and theoretical analysis confirm that the proposed cellular model can mimic the biological calcium behaviors with considerably low hardware overhead. The approach has the potential to speed up large-scale simulations of slow intracellular dynamics by sharing more cellular units in real-time. To this end, various networks constructed by pipelining 10 k to 40 k cellular calcium units are compared with an equivalent simulation run on a standard PC workstation. Results show that the cellular hardware model is, on average, 83 times faster than the CPU version.

A Multi-Paradigm Modeling Framework to Simulate Dynamic Reciprocity in a Bioreactor

PubMed Central

Kaul, Himanshu; Cui, Zhanfeng; Ventikos, Yiannis

2013-01-01

Despite numerous technology advances, bioreactors are still mostly utilized as functional black-boxes where trial and error eventually leads to the desirable cellular outcome. Investigators have applied various computational approaches to understand the impact the internal dynamics of such devices has on overall cell growth, but such models cannot provide a comprehensive perspective regarding the system dynamics, due to limitations inherent to the underlying approaches. In this study, a novel multi-paradigm modeling platform capable of simulating the dynamic bidirectional relationship between cells and their microenvironment is presented. Designing the modeling platform entailed combining and coupling fully an agent-based modeling platform with a transport phenomena computational modeling framework. To demonstrate capability, the platform was used to study the impact of bioreactor parameters on the overall cell population behavior and vice versa. In order to achieve this, virtual bioreactors were constructed and seeded. The virtual cells, guided by a set of rules involving the simulated mass transport inside the bioreactor, as well as cell-related probabilistic parameters, were capable of displaying an array of behaviors such as proliferation, migration, chemotaxis and apoptosis. In this way the platform was shown to capture not only the impact of bioreactor transport processes on cellular behavior but also the influence that cellular activity wields on that very same local mass transport, thereby influencing overall cell growth. The platform was validated by simulating cellular chemotaxis in a virtual direct visualization chamber and comparing the simulation with its experimental analogue. The results presented in this paper are in agreement with published models of similar flavor. The modeling platform can be used as a concept selection tool to optimize bioreactor design specifications. PMID:23555740

Stochastic simulations of fatty-acid proto-cell models

NASA Astrophysics Data System (ADS)

Mavelli, F.; Ruiz-Mirazo, K.

2007-06-01

In this contribution we tackle the problem of simulating the time behavior of self-assembling fatty acid vesicles in different experimental conditions. These systems have been (and are being) explored by various labs as possible precursor models of cellular compartments. By means of our recently developed stochastic simulation platform ('ENVIRONMENT') we are able to reproduce quite satisfactorily experimental data that have been reported on the different growth behavior of this type of proto-cellular systems, depending on the level of osmotic pressure they are under. The work here presented is part of a more general attempt to gain insight into the problem of how self-assembling vesicles (closed bilayer structures) could progressively turn into minimal self-producing and self-reproducing cells: i.e., into interesting candidates for (proto-)biological systems. This involves crossing the traditional gap between in silico and in vitro approaches, as we try to do here, convinced that major adavances in the field require the correct integration of both theoretical and experimental endeavors.

Kinetic Monte Carlo and cellular particle dynamics simulations of multicellular systems

NASA Astrophysics Data System (ADS)

Flenner, Elijah; Janosi, Lorant; Barz, Bogdan; Neagu, Adrian; Forgacs, Gabor; Kosztin, Ioan

2012-03-01

Computer modeling of multicellular systems has been a valuable tool for interpreting and guiding in vitro experiments relevant to embryonic morphogenesis, tumor growth, angiogenesis and, lately, structure formation following the printing of cell aggregates as bioink particles. Here we formulate two computer simulation methods: (1) a kinetic Monte Carlo (KMC) and (2) a cellular particle dynamics (CPD) method, which are capable of describing and predicting the shape evolution in time of three-dimensional multicellular systems during their biomechanical relaxation. Our work is motivated by the need of developing quantitative methods for optimizing postprinting structure formation in bioprinting-assisted tissue engineering. The KMC and CPD model parameters are determined and calibrated by using an original computational-theoretical-experimental framework applied to the fusion of two spherical cell aggregates. The two methods are used to predict the (1) formation of a toroidal structure through fusion of spherical aggregates and (2) cell sorting within an aggregate formed by two types of cells with different adhesivities.

Advances in the integration of transcriptional regulatory information into genome-scale metabolic models.

PubMed

Vivek-Ananth, R P; Samal, Areejit

2016-09-01

A major goal of systems biology is to build predictive computational models of cellular metabolism. Availability of complete genome sequences and wealth of legacy biochemical information has led to the reconstruction of genome-scale metabolic networks in the last 15 years for several organisms across the three domains of life. Due to paucity of information on kinetic parameters associated with metabolic reactions, the constraint-based modelling approach, flux balance analysis (FBA), has proved to be a vital alternative to investigate the capabilities of reconstructed metabolic networks. In parallel, advent of high-throughput technologies has led to the generation of massive amounts of omics data on transcriptional regulation comprising mRNA transcript levels and genome-wide binding profile of transcriptional regulators. A frontier area in metabolic systems biology has been the development of methods to integrate the available transcriptional regulatory information into constraint-based models of reconstructed metabolic networks in order to increase the predictive capabilities of computational models and understand the regulation of cellular metabolism. Here, we review the existing methods to integrate transcriptional regulatory information into constraint-based models of metabolic networks. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Mechano-logical model of C. elegans germ line suggests feedback on the cell cycle

PubMed Central

Atwell, Kathryn; Qin, Zhao; Gavaghan, David; Kugler, Hillel; Hubbard, E. Jane Albert; Osborne, James M.

2015-01-01

The Caenorhabditis elegans germ line is an outstanding model system in which to study the control of cell division and differentiation. Although many of the molecules that regulate germ cell proliferation and fate decisions have been identified, how these signals interact with cellular dynamics and physical forces within the gonad remains poorly understood. We therefore developed a dynamic, 3D in silico model of the C. elegans germ line, incorporating both the mechanical interactions between cells and the decision-making processes within cells. Our model successfully reproduces key features of the germ line during development and adulthood, including a reasonable ovulation rate, correct sperm count, and appropriate organization of the germ line into stably maintained zones. The model highlights a previously overlooked way in which germ cell pressure may influence gonadogenesis, and also predicts that adult germ cells might be subject to mechanical feedback on the cell cycle akin to contact inhibition. We provide experimental data consistent with the latter hypothesis. Finally, we present cell trajectories and ancestry recorded over the course of a simulation. The novel approaches and software described here link mechanics and cellular decision-making, and are applicable to modeling other developmental and stem cell systems. PMID:26428008

Toxicity evaluations of nanoclays and thermally degraded byproducts through spectroscopical and microscopical approaches

PubMed Central

Wagner, Alixandra; Eldawud, Reem; White, Andrew; Agarwal, Sushant; Stueckle, Todd A.; Sierros, Konstantinos A.; Rojanasakul, Yon; Gupta, Rakesh K.; Dinu, Cerasela Zoica

2016-01-01

Background Montmorillonite is a type of nanoclay that originates from the clay fraction of the soil and is incorporated into polymers to form nanocomposites with enhanced mechanical strength, barrier, and flammability properties used for food packaging, automotive, and medical devices. However, with implementation in such consumer applications, the interaction of montmorillonite-based composites or derived byproducts with biological systems needs to be investigated. Methods Herein we examined the potential of Cloisite Na+ (pristine) and Cloisite 30B (organically modified montmorillonite nanoclay) and their thermally degraded byproducts’ to induce toxicity in model human lung epithelial cells. The experimental set-up mimicked biological exposure in manufacturing and disposal areas and employed cellular treatments with occupationally relevant doses of nanoclays previously characterized using spectroscopical and microscopical approaches. For nanoclay-cellular interactions and for cellular analyses respectively, biosensorial-based analytical platforms were used, with induced cellular changes being confirmed via live cell counts, viability assays, and cell imaging. Results Our analysis of byproducts’ chemical and physical properties revealed both structural and functional changes. Real-time high throughput analyses of exposed cellular systems confirmed that nanoclay induced significant toxic effects, with Cloisite 30B showing time-dependent decreases in live cell count and cellular viability relative to control and pristine nanoclay, respectively. Byproducts produced less toxic effects; all treatments caused alterations in the cell morphology upon exposure. Conclusions Our morphological, behavioral, and viability cellular changes show that nanoclays have the potential to produce toxic effects when used both in manufacturing or disposal environments. General significance The reported toxicological mechanisms prove the extensibility of a biosensorial-based platform for cellular behavior analysis upon treatment with a variety of nanomaterials. PMID:27612663

PhosphoregDB: The tissue and sub-cellular distribution of mammalian protein kinases and phosphatases

PubMed Central

Forrest, Alistair RR; Taylor, Darrin F; Fink, J Lynn; Gongora, M Milena; Flegg, Cameron; Teasdale, Rohan D; Suzuki, Harukazu; Kanamori, Mutsumi; Kai, Chikatoshi; Hayashizaki, Yoshihide; Grimmond, Sean M

2006-01-01

Background Protein kinases and protein phosphatases are the fundamental components of phosphorylation dependent protein regulatory systems. We have created a database for the protein kinase-like and phosphatase-like loci of mouse that integrates protein sequence, interaction, classification and pathway information with the results of a systematic screen of their sub-cellular localization and tissue specific expression data mined from the GNF tissue atlas of mouse. Results The database lets users query where a specific kinase or phosphatase is expressed at both the tissue and sub-cellular levels. Similarly the interface allows the user to query by tissue, pathway or sub-cellular localization, to reveal which components are co-expressed or co-localized. A review of their expression reveals 30% of these components are detected in all tissues tested while 70% show some level of tissue restriction. Hierarchical clustering of the expression data reveals that expression of these genes can be used to separate the samples into tissues of related lineage, including 3 larger clusters of nervous tissue, developing embryo and cells of the immune system. By overlaying the expression, sub-cellular localization and classification data we examine correlations between class, specificity and tissue restriction and show that tyrosine kinases are more generally expressed in fewer tissues than serine/threonine kinases. Conclusion Together these data demonstrate that cell type specific systems exist to regulate protein phosphorylation and that for accurate modelling and for determination of enzyme substrate relationships the co-location of components needs to be considered. PMID:16504016

Issues in PCS interoperability and Internetworking

NASA Technical Reports Server (NTRS)

Dean, Richard A.; Estabrook, Polly

1995-01-01

This paper is an expansion of an earlier paper on Satellite/Terrestrial PCS which addressed issues for interoperability that included Networks, Services, Voice Coders and Mobility/Security. This paper focuses on the narrower topic of Network Reference Models and associated interfaces and protocols. The network reference models are addressed from the perspective of the User, the Cellular Carrier, the PSN Carrier, and the Radio Vendor. Each perspective is presented in the way these systems have evolved. The TIA TR46/GSM reference model will be reviewed. Variations in the use of this model that are prevalent in the industry will be discussed. These are the North American Cellular networks, the GSM networks, and the North American Carriers/Bellcore perspective. The paper concludes with the presentation of issues that develop from looking at merging satellite service into a world of many different networks.

Continuum-level modelling of cellular adhesion and matrix production in aggregates.

PubMed

Geris, Liesbet; Ashbourn, Joanna M A; Clarke, Tim

2011-05-01

Key regulators in tissue-engineering processes such as cell culture and cellular organisation are the cell-cell and cell-matrix interactions. As mathematical models are increasingly applied to investigate biological phenomena in the biomedical field, it is important, for some applications, that these models incorporate an adequate description of cell adhesion. This study describes the development of a continuum model that represents a cell-in-gel culture system used in bone-tissue engineering, namely that of a cell aggregate embedded in a hydrogel. Cell adhesion is modelled through the use of non-local (integral) terms in the partial differential equations. The simulation results demonstrate that the effects of cell-cell and cell-matrix adhesion are particularly important for the survival and growth of the cell population and the production of extracellular matrix by the cells, concurring with experimental observations in the literature.

Modeling of Receptor Tyrosine Kinase Signaling: Computational and Experimental Protocols.

PubMed

Fey, Dirk; Aksamitiene, Edita; Kiyatkin, Anatoly; Kholodenko, Boris N

2017-01-01

The advent of systems biology has convincingly demonstrated that the integration of experiments and dynamic modelling is a powerful approach to understand the cellular network biology. Here we present experimental and computational protocols that are necessary for applying this integrative approach to the quantitative studies of receptor tyrosine kinase (RTK) signaling networks. Signaling by RTKs controls multiple cellular processes, including the regulation of cell survival, motility, proliferation, differentiation, glucose metabolism, and apoptosis. We describe methods of model building and training on experimentally obtained quantitative datasets, as well as experimental methods of obtaining quantitative dose-response and temporal dependencies of protein phosphorylation and activities. The presented methods make possible (1) both the fine-grained modeling of complex signaling dynamics and identification of salient, course-grained network structures (such as feedback loops) that bring about intricate dynamics, and (2) experimental validation of dynamic models.

Using in vitro models for expression profiling studies on ethanol and drugs of abuse.

PubMed

Thibault, Christelle; Hassan, Sajida; Miles, Michael

2005-03-01

The use of expression profiling with microarrays offers great potential for studying the mechanisms of action of drugs of abuse. Studies with the intact nervous system seem likely to be most relevant to understanding the mechanisms of drug abuse-related behaviours. However, the use of expression profiling with in vitro culture models offers significant advantages for identifying details of cellular signalling actions and toxicity for drugs of abuse. This study discusses general issues of the use of microarrays and cell culture models for studies on drugs of abuse. Specific results from existing studies are also discussed, providing clear examples of relevance for in vitro studies on ethanol, nicotine, opiates, cannabinoids and hallucinogens such as LSD. In addition to providing details on signalling mechanisms relevant to the neurobiology of drugs of abuse, microarray studies on a variety of cell culture systems have also provided important information on mechanisms of cellular/organ toxicity with drugs of abuse. Efforts to integrate genomic studies on drugs of abuse with both in vivo and in vitro models offer the potential for novel mechanistic rigor and physiological relevance.

Shifts in growth strategies reflect tradeoffs in cellular economics

PubMed Central

Molenaar, Douwe; van Berlo, Rogier; de Ridder, Dick; Teusink, Bas

2009-01-01

The growth rate-dependent regulation of cell size, ribosomal content, and metabolic efficiency follows a common pattern in unicellular organisms: with increasing growth rates, cell size and ribosomal content increase and a shift to energetically inefficient metabolism takes place. The latter two phenomena are also observed in fast growing tumour cells and cell lines. These patterns suggest a fundamental principle of design. In biology such designs can often be understood as the result of the optimization of fitness. Here we show that in basic models of self-replicating systems these patterns are the consequence of maximizing the growth rate. Whereas most models of cellular growth consider a part of physiology, for instance only metabolism, the approach presented here integrates several subsystems to a complete self-replicating system. Such models can yield fundamentally different optimal strategies. In particular, it is shown how the shift in metabolic efficiency originates from a tradeoff between investments in enzyme synthesis and metabolic yields for alternative catabolic pathways. The models elucidate how the optimization of growth by natural selection shapes growth strategies. PMID:19888218

Cellular automata models for diffusion of information and highway traffic flow

NASA Astrophysics Data System (ADS)

Fuks, Henryk

In the first part of this work we study a family of deterministic models for highway traffic flow which generalize cellular automaton rule 184. This family is parameterized by the speed limit m and another parameter k that represents degree of 'anticipatory driving'. We compare two driving strategies with identical maximum throughput: 'conservative' driving with high speed limit and 'anticipatory' driving with low speed limit. Those two strategies are evaluated in terms of accident probability. We also discuss fundamental diagrams of generalized traffic rules and examine limitations of maximum achievable throughput. Possible modifications of the model are considered. For rule 184, we present exact calculations of the order parameter in a transition from the moving phase to the jammed phase using the method of preimage counting, and use this result to construct a solution to the density classification problem. In the second part we propose a probabilistic cellular automaton model for the spread of innovations, rumors, news, etc., in a social system. We start from simple deterministic models, for which exact expressions for the density of adopters are derived. For a more realistic model, based on probabilistic cellular automata, we study the influence of a range of interaction R on the shape of the adoption curve. When the probability of adoption is proportional to the local density of adopters, and individuals can drop the innovation with some probability p, the system exhibits a second order phase transition. Critical line separating regions of parameter space in which asymptotic density of adopters is positive from the region where it is equal to zero converges toward the mean-field line when the range of the interaction increases. In a region between R=1 critical line and the mean-field line asymptotic density of adopters depends on R, becoming zero if R is too small (smaller than some critical value). This result demonstrates the importance of connectivity in diffusion of information. We also define a new class of automata networks which incorporates non-local interactions, and discuss its applicability in modeling of diffusion of innovations.

Computational Model of Secondary Palate Fusion and Disruption

EPA Science Inventory

Morphogenetic events are driven by cell-generated physical forces and complex cellular dynamics. To improve our capacity to predict developmental effects from cellular alterations, we built a multi-cellular agent-based model in CompuCell3D that recapitulates the cellular networks...

Adaptive Control Model Reveals Systematic Feedback and Key Molecules in Metabolic Pathway Regulation

PubMed Central

Moffitt, Richard A.; Merrill, Alfred H.; Wang, May D.

2011-01-01

Abstract Robust behavior in metabolic pathways resembles stabilized performance in systems under autonomous control. This suggests we can apply control theory to study existing regulation in these cellular networks. Here, we use model-reference adaptive control (MRAC) to investigate the dynamics of de novo sphingolipid synthesis regulation in a combined theoretical and experimental case study. The effects of serine palmitoyltransferase over-expression on this pathway are studied in vitro using human embryonic kidney cells. We report two key results from comparing numerical simulations with observed data. First, MRAC simulations of pathway dynamics are comparable to simulations from a standard model using mass action kinetics. The root-sum-square (RSS) between data and simulations in both cases differ by less than 5%. Second, MRAC simulations suggest systematic pathway regulation in terms of adaptive feedback from individual molecules. In response to increased metabolite levels available for de novo sphingolipid synthesis, feedback from molecules along the main artery of the pathway is regulated more frequently and with greater amplitude than from other molecules along the branches. These biological insights are consistent with current knowledge while being new that they may guide future research in sphingolipid biology. In summary, we report a novel approach to study regulation in cellular networks by applying control theory in the context of robust metabolic pathways. We do this to uncover potential insight into the dynamics of regulation and the reverse engineering of cellular networks for systems biology. This new modeling approach and the implementation routines designed for this case study may be extended to other systems. Supplementary Material is available at www.liebertonline.com/cmb. PMID:21314456

Copper transport mediated by nanocarrier systems in a blood-brain barrier in vitro model.

PubMed

Fehse, Susanne; Nowag, Sabrina; Quadir, Mohiuddin; Kim, Kwang Sik; Haag, Rainer; Multhaup, Gerd

2014-05-12

Copper (Cu) is a cofactor of various metalloenzymes and has a role in neurodegenerative diseases with disturbed Cu homeostasis, for example, in Alzheimer's disease (AD) and Menkes disease. To address Cu imbalances, we synthesized two different dendritic nanoparticles (NP) for the transport of Cu(II) ions across the blood-brain barrier (BBB). The synthesized NPs show low toxicity and high water solubility and can stabilize high amounts of Cu(II). The Cu(II)-laden NPs crossed cellular membranes and increased the cellular Cu level. A human brain microvascular endothelial cell (HBMEC) model was established to investigate the permeability of the NPs through the BBB. By comparing the permeability × surface area product (PSe) of reference substances with those of NPs, we observed that NPs crossed the BBB model two times more effectively than (14)C-sucrose and sodium fluorescein (NaFl) and up to 60× better than Evans Blue labeled albumin (EBA). Our results clearly indicate that NPs cross the BBB model effectively. Furthermore, Cu was shielded by the NPs, which decreased the Cu toxicity. The novel design of the core-shell NP enabled the complexation of Cu(II) in the outer shell and therefore facilitated the pH-dependent release of Cu in contrast to core-multishell NPs, where the Cu(II) ions are encapsulated in the core. This allows a release of Cu into the cytoplasm. In addition, by using a cellular detection system based on a metal response element with green fluorescent protein (MRE-GFP), we demonstrated that Cu could also be released intracellularly from NPs and is accessible for biological processes. Our results indicate that NPs are potential candidates to rebalance metal-ion homeostasis in disease conditions affecting brain and neuronal systems.

Resolution of Infinite-Loop in Hyperincursive and Nonlocal Cellular Automata: Introduction to Slime Mold Computing

NASA Astrophysics Data System (ADS)

Aono, Masashi; Gunji, Yukio-Pegio

2004-08-01

How can non-algorithmic/non-deterministic computational syntax be computed? "The hyperincursive system" introduced by Dubois is an anticipatory system embracing the contradiction/uncertainty. Although it may provide a novel viewpoint for the understanding of complex systems, conventional digital computers cannot run faithfully as the hyperincursive computational syntax specifies, in a strict sense. Then is it an imaginary story? In this paper we try to argue that it is not. We show that a model of complex systems "Elementary Conflictable Cellular Automata (ECCA)" proposed by Aono and Gunji is embracing the hyperincursivity and the nonlocality. ECCA is based on locality-only type settings basically as well as other CA models, and/but at the same time, each cell is required to refer to globality-dominant regularity. Due to this contradictory locality-globality loop, the time evolution equation specifies that the system reaches the deadlock/infinite-loop. However, we show that there is a possibility of the resolution of these problems if the computing system has parallel and/but non-distributed property like an amoeboid organism. This paper is an introduction to "the slime mold computing" that is an attempt to cultivate an unconventional notion of computation.

In vivo cellular imaging with microscopes enabled by MEMS scanners

NASA Astrophysics Data System (ADS)

Ra, Hyejun

High-resolution optical imaging plays an important role in medical diagnosis and biomedical research. Confocal microscopy is a widely used imaging method for obtaining cellular and sub-cellular images of biological tissue in reflectance and fluorescence modes. Its characteristic optical sectioning capability also enables three-dimensional (3-D) image reconstruction. However, its use has mostly been limited to excised tissues due to the requirement of high numerical aperture (NA) lenses for cellular resolution. Microscope miniaturization can enable in vivo imaging to make possible early cancer diagnosis and biological studies in the innate environment. In this dissertation, microscope miniaturization for in vivo cellular imaging is presented. The dual-axes confocal (DAC) architecture overcomes limitations of the conventional single-axis confocal (SAC) architecture to allow for miniaturization with high resolution. A microelectromechanical systems (MEMS) scanner is the central imaging component that is key in miniaturization of the DAC architecture. The design, fabrication, and characterization of the two-dimensional (2-D) MEMS scanner are presented. The gimbaled MEMS scanner is fabricated on a double silicon-on-insulator (SOI) wafer and is actuated by self-aligned vertical electrostatic combdrives. The imaging performance of the MEMS scanner in a DAC configuration is shown in a breadboard microscope setup, where reflectance and fluorescence imaging is demonstrated. Then, the MEMS scanner is integrated into a miniature DAC microscope. The whole imaging system is integrated into a portable unit for research in small animal models of human biology and disease. In vivo 3-D imaging is demonstrated on mouse skin models showing gene transfer and siRNA silencing. The siRNA silencing process is sequentially imaged in one mouse over time.

ASSESSMENT OF CHEMICAL EFFECTS ON NEURONAL DIFFERENTIATION USING THE ARRAYSCAN HIGH CONTENT SCREENING SYSTEM

EPA Science Inventory

The development of alternative methods for toxicity testing is driven by the need for scientifically valid data that can be obtained in a rapid and cost-efficient manner. In vitro systems provide a model in which chemical effects on cellular events can be examined using technique...

The comparative immunology of wild and laboratory mice, Mus musculus domesticus

PubMed Central

Abolins, Stephen; King, Elizabeth C.; Lazarou, Luke; Weldon, Laura; Hughes, Louise; Drescher, Paul; Raynes, John G.; Hafalla, Julius C. R.; Viney, Mark E.; Riley, Eleanor M.

2017-01-01

The laboratory mouse is the workhorse of immunology, used as a model of mammalian immune function, but how well immune responses of laboratory mice reflect those of free-living animals is unknown. Here we comprehensively characterize serological, cellular and functional immune parameters of wild mice and compare them with laboratory mice, finding that wild mouse cellular immune systems are, comparatively, in a highly activated (primed) state. Associations between immune parameters and infection suggest that high level pathogen exposure drives this activation. Moreover, wild mice have a population of highly activated myeloid cells not present in laboratory mice. By contrast, in vitro cytokine responses to pathogen-associated ligands are generally lower in cells from wild mice, probably reflecting the importance of maintaining immune homeostasis in the face of intense antigenic challenge in the wild. These data provide a comprehensive basis for validating (or not) laboratory mice as a useful and relevant immunological model system. PMID:28466840

A cellular automaton model for neurogenesis in Drosophila

NASA Astrophysics Data System (ADS)

Luthi, Pascal O.; Chopard, Bastien; Preiss, Anette; Ramsden, Jeremy J.

1998-07-01

A cellular automaton (CA) is constructed for the formation of the central nervous system of the Drosophila embryo. This is an experimentally well-studied system in which complex interactions between neighbouring cells appear to drive their differentiation into different types. It appears that all the cells initially have the potential to become neuroblasts, and all strive to this end, but those which differentiate first block their as yet undifferentiated neighbours from doing so. The CA makes use of observational evidence for a lateral inhibition mechanism involving signalling products S of the ‘proneural’ or neuralizing genes. The key concept of the model is that cells are continuously producing S, but the production rate is lowered by inhibitory signals received from neighbouring cells which have advanced further along the developmental pathway. Comparison with experimental data shows that it well accounts for the observed proportion of neuroectodermal cells delaminating as neuroblasts.

ISDD: A computational model of particle sedimentation, diffusion and target cell dosimetry for in vitro toxicity studies

PubMed Central

2010-01-01

Background The difficulty of directly measuring cellular dose is a significant obstacle to application of target tissue dosimetry for nanoparticle and microparticle toxicity assessment, particularly for in vitro systems. As a consequence, the target tissue paradigm for dosimetry and hazard assessment of nanoparticles has largely been ignored in favor of using metrics of exposure (e.g. μg particle/mL culture medium, particle surface area/mL, particle number/mL). We have developed a computational model of solution particokinetics (sedimentation, diffusion) and dosimetry for non-interacting spherical particles and their agglomerates in monolayer cell culture systems. Particle transport to cells is calculated by simultaneous solution of Stokes Law (sedimentation) and the Stokes-Einstein equation (diffusion). Results The In vitro Sedimentation, Diffusion and Dosimetry model (ISDD) was tested against measured transport rates or cellular doses for multiple sizes of polystyrene spheres (20-1100 nm), 35 nm amorphous silica, and large agglomerates of 30 nm iron oxide particles. Overall, without adjusting any parameters, model predicted cellular doses were in close agreement with the experimental data, differing from as little as 5% to as much as three-fold, but in most cases approximately two-fold, within the limits of the accuracy of the measurement systems. Applying the model, we generalize the effects of particle size, particle density, agglomeration state and agglomerate characteristics on target cell dosimetry in vitro. Conclusions Our results confirm our hypothesis that for liquid-based in vitro systems, the dose-rates and target cell doses for all particles are not equal; they can vary significantly, in direct contrast to the assumption of dose-equivalency implicit in the use of mass-based media concentrations as metrics of exposure for dose-response assessment. The difference between equivalent nominal media concentration exposures on a μg/mL basis and target cell doses on a particle surface area or number basis can be as high as three to six orders of magnitude. As a consequence, in vitro hazard assessments utilizing mass-based exposure metrics have inherently high errors where particle number or surface areas target cells doses are believed to drive response. The gold standard for particle dosimetry for in vitro nanotoxicology studies should be direct experimental measurement of the cellular content of the studied particle. However, where such measurements are impractical, unfeasible, and before such measurements become common, particle dosimetry models such as ISDD provide a valuable, immediately useful alternative, and eventually, an adjunct to such measurements. PMID:21118529

Silver Nanoparticle-Mediated Cellular Responses in Various Cell Lines: An in Vitro Model

PubMed Central

Zhang, Xi-Feng; Shen, Wei; Gurunathan, Sangiliyandi

2016-01-01

Silver nanoparticles (AgNPs) have attracted increased interest and are currently used in various industries including medicine, cosmetics, textiles, electronics, and pharmaceuticals, owing to their unique physical and chemical properties, particularly as antimicrobial and anticancer agents. Recently, several studies have reported both beneficial and toxic effects of AgNPs on various prokaryotic and eukaryotic systems. To develop nanoparticles for mediated therapy, several laboratories have used a variety of cell lines under in vitro conditions to evaluate the properties, mode of action, differential responses, and mechanisms of action of AgNPs. In vitro models are simple, cost-effective, rapid, and can be used to easily assess efficacy and performance. The cytotoxicity, genotoxicity, and biocompatibility of AgNPs depend on many factors such as size, shape, surface charge, surface coating, solubility, concentration, surface functionalization, distribution of particles, mode of entry, mode of action, growth media, exposure time, and cell type. Cellular responses to AgNPs are different in each cell type and depend on the physical and chemical nature of AgNPs. This review evaluates significant contributions to the literature on biological applications of AgNPs. It begins with an introduction to AgNPs, with particular attention to their overall impact on cellular effects. The main objective of this review is to elucidate the reasons for different cell types exhibiting differential responses to nanoparticles even when they possess similar size, shape, and other parameters. Firstly, we discuss the cellular effects of AgNPs on a variety of cell lines; Secondly, we discuss the mechanisms of action of AgNPs in various cellular systems, and try to elucidate how AgNPs interact with different mammalian cell lines and produce significant effects; Finally, we discuss the cellular activation of various signaling molecules in response to AgNPs, and conclude with future perspectives on research into AgNPs. PMID:27669221

Cellular oxido-reductive proteins of Chlamydomonas reinhardtii control the biosynthesis of silver nanoparticles

PubMed Central

2011-01-01

Background Elucidation of molecular mechanism of silver nanoparticles (SNPs) biosynthesis is important to control its size, shape and monodispersity. The evaluation of molecular mechanism of biosynthesis of SNPs is of prime importance for the commercialization and methodology development for controlling the shape and size (uniform distribution) of SNPs. The unicellular algae Chlamydomonas reinhardtii was exploited as a model system to elucidate the role of cellular proteins in SNPs biosynthesis. Results The C. reinhardtii cell free extract (in vitro) and in vivo cells mediated synthesis of silver nanoparticles reveals SNPs of size range 5 ± 1 to 15 ± 2 nm and 5 ± 1 to 35 ± 5 nm respectively. In vivo biosynthesized SNPs were localized in the peripheral cytoplasm and at one side of flagella root, the site of pathway of ATP transport and its synthesis related enzymes. This provides an evidence for the involvement of oxidoreductive proteins in biosynthesis and stabilization of SNPs. Alteration in size distribution and decrease of synthesis rate of SNPs in protein-depleted fractions confirmed the involvement of cellular proteins in SNPs biosynthesis. Spectroscopic and SDS-PAGE analysis indicate the association of various proteins on C. reinhardtii mediated in vivo and in vitro biosynthesized SNPs. We have identified various cellular proteins associated with biosynthesized (in vivo and in vitro) SNPs by using MALDI-MS-MS, like ATP synthase, superoxide dismutase, carbonic anhydrase, ferredoxin-NADP+ reductase, histone etc. However, these proteins were not associated on the incubation of pre-synthesized silver nanoparticles in vitro. Conclusion Present study provides the indication of involvement of molecular machinery and various cellular proteins in the biosynthesis of silver nanoparticles. In this report, the study is mainly focused towards understanding the role of diverse cellular protein in the synthesis and capping of silver nanoparticles using C. reinhardtii as a model system. PMID:22152042

Acanthamoeba and Dictyostelium as Cellular Models for Legionella Infection

PubMed Central

Swart, A. Leoni; Harrison, Christopher F.; Eichinger, Ludwig; Steinert, Michael; Hilbi, Hubert

2018-01-01

Environmental bacteria of the genus Legionella naturally parasitize free-living amoebae. Upon inhalation of bacteria-laden aerosols, the opportunistic pathogens grow intracellularly in alveolar macrophages and can cause a life-threatening pneumonia termed Legionnaires' disease. Intracellular replication in amoebae and macrophages takes place in a unique membrane-bound compartment, the Legionella-containing vacuole (LCV). LCV formation requires the bacterial Icm/Dot type IV secretion system, which translocates literally hundreds of “effector” proteins into host cells, where they modulate crucial cellular processes for the pathogen's benefit. The mechanism of LCV formation appears to be evolutionarily conserved, and therefore, amoebae are not only ecologically significant niches for Legionella spp., but also useful cellular models for eukaryotic phagocytes. In particular, Acanthamoeba castellanii and Dictyostelium discoideum emerged over the last years as versatile and powerful models. Using genetic, biochemical and cell biological approaches, molecular interactions between amoebae and Legionella pneumophila have recently been investigated in detail with a focus on the role of phosphoinositide lipids, small and large GTPases, autophagy components and the retromer complex, as well as on bacterial effectors targeting these host factors. PMID:29552544

The anatomy of microbial cell state transitions in response to oxygen.

PubMed

Schmid, Amy K; Reiss, David J; Kaur, Amardeep; Pan, Min; King, Nichole; Van, Phu T; Hohmann, Laura; Martin, Daniel B; Baliga, Nitin S

2007-10-01

Adjustment of physiology in response to changes in oxygen availability is critical for the survival of all organisms. However, the chronology of events and the regulatory processes that determine how and when changes in environmental oxygen tension result in an appropriate cellular response is not well understood at a systems level. Therefore, transcriptome, proteome, ATP, and growth changes were analyzed in a halophilic archaeon to generate a temporal model that describes the cellular events that drive the transition between the organism's two opposing cell states of anoxic quiescence and aerobic growth. According to this model, upon oxygen influx, an initial burst of protein synthesis precedes ATP and transcription induction, rapidly driving the cell out of anoxic quiescence, culminating in the resumption of growth. This model also suggests that quiescent cells appear to remain actively poised for energy production from a variety of different sources. Dynamic temporal analysis of relationships between transcription and translation of key genes suggests several important mechanisms for cellular sustenance under anoxia as well as specific instances of post-transcriptional regulation.

The anatomy of microbial cell state transitions in response to oxygen

PubMed Central

Schmid, Amy K.; Reiss, David J.; Kaur, Amardeep; Pan, Min; King, Nichole; Van, Phu T.; Hohmann, Laura; Martin, Daniel B.; Baliga, Nitin S.

2007-01-01

Adjustment of physiology in response to changes in oxygen availability is critical for the survival of all organisms. However, the chronology of events and the regulatory processes that determine how and when changes in environmental oxygen tension result in an appropriate cellular response is not well understood at a systems level. Therefore, transcriptome, proteome, ATP, and growth changes were analyzed in a halophilic archaeon to generate a temporal model that describes the cellular events that drive the transition between the organism’s two opposing cell states of anoxic quiescence and aerobic growth. According to this model, upon oxygen influx, an initial burst of protein synthesis precedes ATP and transcription induction, rapidly driving the cell out of anoxic quiescence, culminating in the resumption of growth. This model also suggests that quiescent cells appear to remain actively poised for energy production from a variety of different sources. Dynamic temporal analysis of relationships between transcription and translation of key genes suggests several important mechanisms for cellular sustenance under anoxia as well as specific instances of post-transcriptional regulation. PMID:17785531

Conference on Correlations of Aging and Space Effects on Biosystems, Oct. 30-Nov. 1, 1989, Proceedings

NASA Technical Reports Server (NTRS)

Sprott, Richard L. (Editor); Combs, Carol A. (Editor)

1991-01-01

This volume includes papers on correlations between aging effects and space effects on biosystems, with particular attention given to the effects on the cardiovascular system, bone, sleep, cellular systems, immunological system, and genetics. Papers are presented on NASA and NIA plans and opportunities, the age effect on the posture and circulation, the cardiovascular physiology in space flight, and age-related bone changes. Attention is given to research on sleep, circulation rhythms, and aging and its applications to manned spaceflight; sleep and circadian rhythms; altered cell function in microgravity; and the heterogeneity of changes in lymphoproliferative ability with increasing age. Also included is a review of cellular immunosenescence, a paper on the immune response during space flight, and a paper on Caenorhabditis elegans as a model system for space biology studies.

Cross-talk between Rho and Rac GTPases drives deterministic exploration of cellular shape space and morphological heterogeneity.

PubMed

Sailem, Heba; Bousgouni, Vicky; Cooper, Sam; Bakal, Chris

2014-01-22

One goal of cell biology is to understand how cells adopt different shapes in response to varying environmental and cellular conditions. Achieving a comprehensive understanding of the relationship between cell shape and environment requires a systems-level understanding of the signalling networks that respond to external cues and regulate the cytoskeleton. Classical biochemical and genetic approaches have identified thousands of individual components that contribute to cell shape, but it remains difficult to predict how cell shape is generated by the activity of these components using bottom-up approaches because of the complex nature of their interactions in space and time. Here, we describe the regulation of cellular shape by signalling systems using a top-down approach. We first exploit the shape diversity generated by systematic RNAi screening and comprehensively define the shape space a migratory cell explores. We suggest a simple Boolean model involving the activation of Rac and Rho GTPases in two compartments to explain the basis for all cell shapes in the dataset. Critically, we also generate a probabilistic graphical model to show how cells explore this space in a deterministic, rather than a stochastic, fashion. We validate the predictions made by our model using live-cell imaging. Our work explains how cross-talk between Rho and Rac can generate different cell shapes, and thus morphological heterogeneity, in genetically identical populations.

Human breast cancer histoid: an in vitro 3-dimensional co-culture model that mimics breast cancer tissue.

PubMed

Kaur, Pavinder; Ward, Brenda; Saha, Baisakhi; Young, Lillian; Groshen, Susan; Techy, Geza; Lu, Yani; Atkinson, Roscoe; Taylor, Clive R; Ingram, Marylou; Imam, S Ashraf

2011-12-01

Progress in our understanding of heterotypic cellular interaction in the tumor microenvironment, which is recognized to play major roles in cancer progression, has been hampered due to unavailability of an appropriate in vitro co-culture model. The aim of this study was to generate an in vitro 3-dimensional human breast cancer model, which consists of cancer cells and fibroblasts. Breast cancer cells (UACC-893) and fibroblasts at various densities were co-cultured in a rotating suspension culture system to establish co-culture parameters. Subsequently, UACC-893, BT.20, or MDA.MB.453 were co-cultured with fibroblasts for 9 days. Co-cultures resulted in the generation of breast cancer histoid (BCH) with cancer cells showing the invasion of fibroblast spheroids, which were visualized by immunohistochemical (IHC) staining of sections (4 µm thick) of BCH. A reproducible quantitative expression of C-erbB.2 was detected in UACC-893 cancer cells in BCH sections by IHC staining and the Automated Cellular Imaging System. BCH sections also consistently exhibited qualitative expression of pancytokeratins, p53, Ki-67, or E-cadherin in cancer cells and that of vimentin or GSTPi in fibroblasts, fibronectin in the basement membrane and collagen IV in the extracellular matrix. The expression of the protein analytes and cellular architecture of BCH were markedly similar to those of breast cancer tissue.

Sordaria macrospora, a model organism to study fungal cellular development.

PubMed

Engh, Ines; Nowrousian, Minou; Kück, Ulrich

2010-12-01

During the development of multicellular eukaryotes, the processes of cellular growth and organogenesis are tightly coordinated. Since the 1940s, filamentous fungi have served as genetic model organisms to decipher basic mechanisms underlying eukaryotic cell differentiation. Here, we focus on Sordaria macrospora, a homothallic ascomycete and important model organism for developmental biology. During its sexual life cycle, S. macrospora forms three-dimensional fruiting bodies, a complex process involving the formation of different cell types. S. macrospora can be used for genetic, biochemical and cellular experimental approaches since diverse tools, including fluorescence microscopy, a marker recycling system and gene libraries, are available. Moreover, the genome of S. macrospora has been sequenced and allows functional genomics analyses. Over the past years, our group has generated and analysed a number of developmental mutants which has greatly enhanced our fundamental understanding about fungal morphogenesis. In addition, our recent research activities have established a link between developmental proteins and conserved signalling cascades, ultimately leading to a regulatory network controlling differentiation processes in a eukaryotic model organism. This review summarizes the results of our recent findings, thus advancing current knowledge of the general principles and paradigms underpinning eukaryotic cell differentiation and development. Copyright © 2010 Elsevier GmbH. All rights reserved.

Designing and implementing a regional urban modeling system using the SLEUTH cellular urban model

USGS Publications Warehouse

Jantz, Claire A.; Goetz, Scott J.; Donato, David I.; Claggett, Peter

2010-01-01

This paper presents a fine-scale (30 meter resolution) regional land cover modeling system, based on the SLEUTH cellular automata model, that was developed for a 257000 km2 area comprising the Chesapeake Bay drainage basin in the eastern United States. As part of this effort, we developed a new version of the SLEUTH model (SLEUTH-3r), which introduces new functionality and fit metrics that substantially increase the performance and applicability of the model. In addition, we developed methods that expand the capability of SLEUTH to incorporate economic, cultural and policy information, opening up new avenues for the integration of SLEUTH with other land-change models. SLEUTH-3r is also more computationally efficient (by a factor of 5) and uses less memory (reduced 65%) than the original software. With the new version of SLEUTH, we were able to achieve high accuracies at both the aggregate level of 15 sub-regional modeling units and at finer scales. We present forecasts to 2030 of urban development under a current trends scenario across the entire Chesapeake Bay drainage basin, and three alternative scenarios for a sub-region within the Chesapeake Bay watershed to illustrate the new ability of SLEUTH-3r to generate forecasts across a broad range of conditions.

Nonlinear mode interaction in equal-leg angle struts susceptible to cellular buckling.

PubMed

Bai, L; Wang, F; Wadee, M A; Yang, J

2017-11-01

A variational model that describes the interactive buckling of a thin-walled equal-leg angle strut under pure axial compression is presented. A formulation combining the Rayleigh-Ritz method and continuous displacement functions is used to derive a system of differential and integral equilibrium equations for the structural component. Solving the equations using numerical continuation reveals progressive cellular buckling (or snaking) arising from the nonlinear interaction between the weak-axis flexural buckling mode and the strong-axis flexural-torsional buckling mode for the first time-the resulting behaviour being highly unstable. Physical experiments conducted on 10 cold-formed steel specimens are presented and the results show good agreement with the variational model.

The Scientist as Illustrator.

PubMed

Iwasa, Janet H

2016-04-01

Proficiency in art and illustration was once considered an essential skill for biologists, because text alone often could not suffice to describe observations of biological systems. With modern imaging technology, it is no longer necessary to illustrate what we can see by eye. However, in molecular and cellular biology, our understanding of biological processes is dependent on our ability to synthesize diverse data to generate a hypothesis. Creating visual models of these hypotheses is important for generating new ideas and for communicating to our peers and to the public. Here, I discuss the benefits of creating visual models in molecular and cellular biology and consider steps to enable researchers to become more effective visual communicators. Copyright © 2016 Elsevier Ltd. All rights reserved.

Driving mechanisms of passive and active transport across cellular membranes as the mechanisms of cell metabolism and development as well as the mechanisms of cellular distance reactions on hormonal expression and the immune response.

PubMed

Ponisovskiy, M R

2011-01-01

The article presents mechanisms of cell metabolism, cell development, cell activity, and maintenance of cellular stability. The literature is reviewed from the point of view of these concepts. The balance between anabolic and catabolic processes induces chemical potentials in the extracellular and intracellular media. The chemical potentials of these media are defined as the driving forces of both passive and active transport of substances across cellular membranes. The driving forces of substance transport across cellular membranes as in cellular metabolism and in immune responses and hormonal expressions are considered in the biochemical and biophysical models, reflecting the mechanisms for maintenance of stability of the internal medium and internal energy of an organism. The interactions of passive transport and active transport of substances across cellular walls promote cell proliferation, as well as the mechanism of cellular capacitors, promoting remote reactions across distance for hormonal expression and immune responses. The offered concept of cellular capacitors has given the possibility to explain the mechanism of remote responses of cells to new situations, resulting in the appearance of additional agents. The biophysical model develops an explanation of some cellular functions: cellular membrane action have been identified with capacitor action, based on the similarity of the structures and as well as on similarity of biophysical properties of electric data that confirm the action of the compound-specific interactions of cells within an organism, promoting hormonal expressions and immune responses to stabilize the thermodynamic system of an organism. Comparison of a cellular membrane action to a capacitor has given the possibility for the explanations of exocytosis and endocytosis mechanisms, internalization of the receptor-ligand complex, selection as a receptor reaction to a ligand by immune responses or hormonal effects, reflecting cellular distance reactions on the hormonal expressions, immune responses, and specificity of the mechanisms of immune reactions. Reviewing current research of cell activity, explanations are presented of mechanisms of apoptosis, autophagy, hormonal expression, and immune responses from the point of view of described cellular mechanisms. Thermodynamic laws are used to confirm the importance of the actions of these mechanisms for maintenance of stability of the internal medium and internal energy of an organism.

Human systems immunology: hypothesis-based modeling and unbiased data-driven approaches.

PubMed

Arazi, Arnon; Pendergraft, William F; Ribeiro, Ruy M; Perelson, Alan S; Hacohen, Nir

2013-10-31

Systems immunology is an emerging paradigm that aims at a more systematic and quantitative understanding of the immune system. Two major approaches have been utilized to date in this field: unbiased data-driven modeling to comprehensively identify molecular and cellular components of a system and their interactions; and hypothesis-based quantitative modeling to understand the operating principles of a system by extracting a minimal set of variables and rules underlying them. In this review, we describe applications of the two approaches to the study of viral infections and autoimmune diseases in humans, and discuss possible ways by which these two approaches can synergize when applied to human immunology. Copyright © 2012 Elsevier Ltd. All rights reserved.

Systems Dynamic Modeling of the Stomatal Guard Cell Predicts Emergent Behaviors in Transport, Signaling, and Volume Control1[W][OA

PubMed Central

Chen, Zhong-Hua; Hills, Adrian; Bätz, Ulrike; Amtmann, Anna; Lew, Virgilio L.; Blatt, Michael R.

2012-01-01

The dynamics of stomatal movements and their consequences for photosynthesis and transpirational water loss have long been incorporated into mathematical models, but none have been developed from the bottom up that are widely applicable in predicting stomatal behavior at a cellular level. We previously established a systems dynamic model incorporating explicitly the wealth of biophysical and kinetic knowledge available for guard cell transport, signaling, and homeostasis. Here we describe the behavior of the model in response to experimentally documented changes in primary pump activities and malate (Mal) synthesis imposed over a diurnal cycle. We show that the model successfully recapitulates the cyclic variations in H+, K+, Cl−, and Mal concentrations in the cytosol and vacuole known for guard cells. It also yields a number of unexpected and counterintuitive outputs. Among these, we report a diurnal elevation in cytosolic-free Ca2+ concentration and an exchange of vacuolar Cl− with Mal, both of which find substantiation in the literature but had previously been suggested to require additional and complex levels of regulation. These findings highlight the true predictive power of the OnGuard model in providing a framework for systems analysis of stomatal guard cells, and they demonstrate the utility of the OnGuard software and HoTSig library in exploring fundamental problems in cellular physiology and homeostasis. PMID:22635112

Modems for emerging digital cellular-mobile radio system

NASA Technical Reports Server (NTRS)

Feher, Kamilo

1991-01-01

Digital modem techniques for emerging digital cellular telecommunications-mobile radio system applications are described and analyzed. In particular, theoretical performance, experimental results, principles of operation, and various architectures of pi/4-QPSK (pi/4-shifted coherent or differential QPSK) modems for second-generation US digital cellular radio system applications are presented. The spectral/power efficiency and performance of the pi/4-QPSK modems (American and Japanese digital cellular emerging standards) are studied and briefly compared to GMSK (Gaussian minimum-shift keying) modems (proposed for European DECT and GSM cellular standards). Improved filtering strategies and digital pilot-aided (digital channel sounding) techniques are also considered for pi/4-QPSK and other digital modems. These techniques could significantly improve the performance of digital cellular and other digital land mobile and satellite mobile radio systems. More spectrally efficient modem trends for future cellular/mobile (land mobile) and satellite communication systems applications are also highlighted.

Genetic Algorithm Calibration of Probabilistic Cellular Automata for Modeling Mining Permit Activity

USGS Publications Warehouse

Louis, S.J.; Raines, G.L.

2003-01-01

We use a genetic algorithm to calibrate a spatially and temporally resolved cellular automata to model mining activity on public land in Idaho and western Montana. The genetic algorithm searches through a space of transition rule parameters of a two dimensional cellular automata model to find rule parameters that fit observed mining activity data. Previous work by one of the authors in calibrating the cellular automaton took weeks - the genetic algorithm takes a day and produces rules leading to about the same (or better) fit to observed data. These preliminary results indicate that genetic algorithms are a viable tool in calibrating cellular automata for this application. Experience gained during the calibration of this cellular automata suggests that mineral resource information is a critical factor in the quality of the results. With automated calibration, further refinements of how the mineral-resource information is provided to the cellular automaton will probably improve our model.

Self-organized perturbations enhance class IV behavior and 1/f power spectrum in elementary cellular automata.

PubMed

Nakajima, Kohei; Haruna, Taichi

2011-09-01

In this paper, we propose a new class of cellular automata based on the modification of its state space. It is introduced to model a computation which is exposed to an environment. We formalized the computation as extension and projection processes of its state space and resulting misidentifications of the state. This is motivated to embed the role of an environment into the system itself, which naturally induces self-organized internal perturbations rather than the usual external perturbations. Implementing this structure into the elementary cellular automata, we characterized its effect by means of input entropy and power spectral analysis. As a result, the cellular automata with this structure showed robust class IV behavior and a 1/f power spectrum in a wide range of rule space comparative to the notion of the edge of chaos. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Low doses of ionizing radiation to mammalian cells may rather control than cause DNA damage

DOE Office of Scientific and Technical Information (OSTI.GOV)

Feinendegen, L.E.; Bond, V.P.; Sondhaus, C.A.

This report examines the origin of tissue effects that may follow from different cellular responses to low-dose irradiation, using published data. Two principal categories of cellular responses are considered. One response category relates to the probability of radiation-induced DNA damage. The other category consists of low-dose induced metabolic changes that induce mechanisms of DNA damage mitigation, which do not operate at high levels of exposure. Modeled in this way, tissue is treated as a complex adaptive system. The interaction of the various cellular responses results in a net tissue dose-effect relation that is likely to deviate from linearity in themore » low-dose region. This suggests that the LNT hypothesis should be reexamined. This paper aims at demonstrating tissue effects as an expression of cellular responses, both damaging and defensive, in relation to the energy deposited in cell mass, by use of microdosimetric concepts.« less

Quantitative computational models of molecular self-assembly in systems biology

PubMed Central

Thomas, Marcus; Schwartz, Russell

2017-01-01

Molecular self-assembly is the dominant form of chemical reaction in living systems, yet efforts at systems biology modeling are only beginning to appreciate the need for and challenges to accurate quantitative modeling of self-assembly. Self-assembly reactions are essential to nearly every important process in cell and molecular biology and handling them is thus a necessary step in building comprehensive models of complex cellular systems. They present exceptional challenges, however, to standard methods for simulating complex systems. While the general systems biology world is just beginning to deal with these challenges, there is an extensive literature dealing with them for more specialized self-assembly modeling. This review will examine the challenges of self-assembly modeling, nascent efforts to deal with these challenges in the systems modeling community, and some of the solutions offered in prior work on self-assembly specifically. The review concludes with some consideration of the likely role of self-assembly in the future of complex biological system models more generally. PMID:28535149

Quantitative computational models of molecular self-assembly in systems biology.

PubMed

Thomas, Marcus; Schwartz, Russell

2017-05-23

Molecular self-assembly is the dominant form of chemical reaction in living systems, yet efforts at systems biology modeling are only beginning to appreciate the need for and challenges to accurate quantitative modeling of self-assembly. Self-assembly reactions are essential to nearly every important process in cell and molecular biology and handling them is thus a necessary step in building comprehensive models of complex cellular systems. They present exceptional challenges, however, to standard methods for simulating complex systems. While the general systems biology world is just beginning to deal with these challenges, there is an extensive literature dealing with them for more specialized self-assembly modeling. This review will examine the challenges of self-assembly modeling, nascent efforts to deal with these challenges in the systems modeling community, and some of the solutions offered in prior work on self-assembly specifically. The review concludes with some consideration of the likely role of self-assembly in the future of complex biological system models more generally.

Mechanical perturbation control of cardiac alternans

NASA Astrophysics Data System (ADS)

Hazim, Azzam; Belhamadia, Youssef; Dubljevic, Stevan

2018-05-01

Cardiac alternans is a disturbance in heart rhythm that is linked to the onset of lethal cardiac arrhythmias. Mechanical perturbation control has been recently used to suppress alternans in cardiac tissue of relevant size. In this control strategy, cardiac tissue mechanics are perturbed via active tension generated by the heart's electrical activity, which alters the tissue's electric wave profile through mechanoelectric coupling. We analyze the effects of mechanical perturbation on the dynamics of a map model that couples the membrane voltage and active tension systems at the cellular level. Therefore, a two-dimensional iterative map of the heart beat-to-beat dynamics is introduced, and a stability analysis of the system of coupled maps is performed in the presence of a mechanical perturbation algorithm. To this end, a bidirectional coupling between the membrane voltage and active tension systems in a single cardiac cell is provided, and a discrete form of the proposed control algorithm, that can be incorporated in the coupled maps, is derived. In addition, a realistic electromechanical model of cardiac tissue is employed to explore the feasibility of suppressing alternans at cellular and tissue levels. Electrical activity is represented in two detailed ionic models, the Luo-Rudy 1 and the Fox models, while two active contractile tension models, namely a smooth variant of the Nash-Panfilov model and the Niederer-Hunter-Smith model, are used to represent mechanical activity in the heart. The Mooney-Rivlin passive elasticity model is employed to describe passive mechanical behavior of the myocardium.

Space-time dynamics of Stem Cell Niches: a unified approach for Plants.

PubMed

Pérez, Maria Del Carmen; López, Alejandro; Padilla, Pablo

2013-06-01

Many complex systems cannot be analyzed using traditional mathematical tools, due to their irreducible nature. This makes it necessary to develop models that can be implemented computationally to simulate their evolution. Examples of these models are cellular automata, evolutionary algorithms, complex networks, agent-based models, symbolic dynamics and dynamical systems techniques. We review some representative approaches to model the stem cell niche in Arabidopsis thaliana and the basic biological mechanisms that underlie its formation and maintenance. We propose a mathematical model based on cellular automata for describing the space-time dynamics of the stem cell niche in the root. By making minimal assumptions on the cell communication process documented in experiments, we classify the basic developmental features of the stem-cell niche, including the basic structural architecture, and suggest that they could be understood as the result of generic mechanisms given by short and long range signals. This could be a first step in understanding why different stem cell niches share similar topologies, not only in plants. Also the fact that this organization is a robust consequence of the way information is being processed by the cells and to some extent independent of the detailed features of the signaling mechanism.

Space-time dynamics of stem cell niches: a unified approach for plants.

PubMed

Pérez, Maria del Carmen; López, Alejandro; Padilla, Pablo

2013-04-02

Many complex systems cannot be analyzed using traditional mathematical tools, due to their irreducible nature. This makes it necessary to develop models that can be implemented computationally to simulate their evolution. Examples of these models are cellular automata, evolutionary algorithms, complex networks, agent-based models, symbolic dynamics and dynamical systems techniques. We review some representative approaches to model the stem cell niche in Arabidopsis thaliana and the basic biological mechanisms that underlie its formation and maintenance. We propose a mathematical model based on cellular automata for describing the space-time dynamics of the stem cell niche in the root. By making minimal assumptions on the cell communication process documented in experiments, we classify the basic developmental features of the stem-cell niche, including the basic structural architecture, and suggest that they could be understood as the result of generic mechanisms given by short and long range signals. This could be a first step in understanding why different stem cell niches share similar topologies, not only in plants. Also the fact that this organization is a robust consequence of the way information is being processed by the cells and to some extent independent of the detailed features of the signaling mechanism.

Modeling the lung: Design and development of tissue engineered macro- and micro-physiologic lung models for research use.

PubMed

Nichols, Joan E; Niles, Jean A; Vega, Stephanie P; Argueta, Lissenya B; Eastaway, Adriene; Cortiella, Joaquin

2014-09-01

Respiratory tract specific cell populations, or tissue engineered in vitro grown human lung, have the potential to be used as research tools to mimic physiology, toxicology, pathology, as well as infectious diseases responses of cells or tissues. Studies related to respiratory tract pathogenesis or drug toxicity testing in the past made use of basic systems where single cell populations were exposed to test agents followed by evaluations of simple cellular responses. Although these simple single-cell-type systems provided good basic information related to cellular responses, much more can be learned from cells grown in fabricated microenvironments which mimic in vivo conditions in specialized microfabricated chambers or by human tissue engineered three-dimensional (3D) models which allow for more natural interactions between cells. Recent advances in microengineering technology, microfluidics, and tissue engineering have provided a new approach to the development of 2D and 3D cell culture models which enable production of more robust human in vitro respiratory tract models. Complex models containing multiple cell phenotypes also provide a more reasonable approximation of what occurs in vivo without the confounding elements in the dynamic in vivo environment. The goal of engineering good 3D human models is the formation of physiologically functional respiratory tissue surrogates which can be used as pathogenesis models or in the case of 2D screening systems for drug therapy evaluation as well as human toxicity testing. We hope that this manuscript will serve as a guide for development of future respiratory tract model systems as well as a review of conventional models. © 2014 by the Society for Experimental Biology and Medicine.

vEmbryo In Silico Models: Predicting Vascular Developmental Toxicity

EPA Science Inventory

The cardiovascular system is the first to function in the vertebrate embryo, reflecting the critical need for nutrient delivery and waste removal during organogenesis. Blood vessel development occurs by complex interacting signaling networks, including extra-cellular matrix remod...

Measuring optical properties of a blood vessel model using optical coherence tomography

NASA Astrophysics Data System (ADS)

Levitz, David; Hinds, Monica T.; Tran, Noi; Vartanian, Keri; Hanson, Stephen R.; Jacques, Steven L.

2006-02-01

In this paper we develop the concept of a tissue-engineered optical phantom that uses engineered tissue as a phantom for calibration and optimization of biomedical optics instrumentation. With this method, the effects of biological processes on measured signals can be studied in a well controlled manner. To demonstrate this concept, we attempted to investigate how the cellular remodeling of a collagen matrix affected the optical properties extracted from optical coherence tomography (OCT) images of the samples. Tissue-engineered optical phantoms of the vascular system were created by seeding smooth muscle cells in a collagen matrix. Four different optical properties were evaluated by fitting the OCT signal to 2 different models: the sample reflectivity ρ and attenuation parameter μ were extracted from the single scattering model, and the scattering coefficient μ s and root-mean-square scattering angle θ rms were extracted from the extended Huygens-Fresnel model. We found that while contraction of the smooth muscle cells was clearly evident macroscopically, on the microscopic scale very few cells were actually embedded in the collagen. Consequently, no significant difference between the cellular and acellular samples in either set of measured optical properties was observed. We believe that further optimization of our tissue-engineering methods is needed in order to make the histology and biochemistry of the cellular samples sufficiently different from the acellular samples on the microscopic level. Once these methods are optimized, we can better verify whether the optical properties of the cellular and acellular collagen samples differ.

A Quantitative Study of Oxygen as a Metabolic Regulator

NASA Technical Reports Server (NTRS)

Radhakrishnan, Krishnan; LaManna, Joseph C.; Cabera, Marco E.

2000-01-01

An acute reduction in oxygen delivery to a tissue is associated with metabolic changes aimed at maintaining ATP homeostasis. However, given the complexity of the human bio-energetic system, it is difficult to determine quantitatively how cellular metabolic processes interact to maintain ATP homeostasis during stress (e.g., hypoxia, ischemia, and exercise). In particular, we are interested in determining mechanisms relating cellular oxygen concentration to observed metabolic responses at the cellular, tissue, organ, and whole body levels and in quantifying how changes in tissue oxygen availability affect the pathways of ATP synthesis and the metabolites that control these pathways. In this study; we extend a previously developed mathematical model of human bioenergetics, to provide a physicochemical framework that permits quantitative understanding of oxygen as a metabolic regulator. Specifically, the enhancement - sensitivity analysis - permits studying the effects of variations in tissue oxygenation and parameters controlling cellular respiration on glycolysis, lactate production, and pyruvate oxidation. The analysis can distinguish between parameters that must be determined accurately and those that require less precision, based on their effects on model predictions. This capability may prove to be important in optimizing experimental design, thus reducing use of animals.

Simulation of emotional contagion using modified SIR model: A cellular automaton approach

NASA Astrophysics Data System (ADS)

Fu, Libi; Song, Weiguo; Lv, Wei; Lo, Siuming

2014-07-01

Emotion plays an important role in the decision-making of individuals in some emergency situations. The contagion of emotion may induce either normal or abnormal consolidated crowd behavior. This paper aims to simulate the dynamics of emotional contagion among crowds by modifying the epidemiological SIR model to a cellular automaton approach. This new cellular automaton model, entitled the “CA-SIRS model”, captures the dynamic process ‘susceptible-infected-recovered-susceptible', which is based on SIRS contagion in epidemiological theory. Moreover, in this new model, the process is integrated with individual movement. The simulation results of this model show that multiple waves and dynamical stability around a mean value will appear during emotion spreading. It was found that the proportion of initial infected individuals had little influence on the final stable proportion of infected population in a given system, and that infection frequency increased with an increase in the average crowd density. Our results further suggest that individual movement accelerates the spread speed of emotion and increases the stable proportion of infected population. Furthermore, decreasing the duration of an infection and the probability of reinfection can markedly reduce the number of infected individuals. It is hoped that this study will be helpful in crowd management and evacuation organization.

A general method for radio spectrum efficiency defining

NASA Astrophysics Data System (ADS)

Ramadanovic, Ljubomir M.

1986-08-01

A general method for radio spectrum efficiency defining is proposed. Although simple it can be applied to various radio services. The concept of spectral elements, as information carriers, is introduced to enable the organization of larger spectral spaces - radio network models - characteristic for a particular radio network. The method is applied to some radio network models, concerning cellular radio telephone systems and digital radio relay systems, to verify its unified approach capability. All discussed radio services operate continuously.

Prediction of lung cells oncogenic transformation for induced radon progeny alpha particles using sugarscape cellular automata.

PubMed

Baradaran, Samaneh; Maleknasr, Niaz; Setayeshi, Saeed; Akbari, Mohammad Esmaeil

2014-01-01

Alpha particle irradiation from radon progeny is one of the major natural sources of effective dose in the public population. Oncogenic transformation is a biological effectiveness of radon progeny alpha particle hits. The biological effects which has caused by exposure to radon, were the main result of a complex series of physical, chemical, biological and physiological interactions. The cellular and molecular mechanisms for radon-induced carcinogenesis have not been clear yet. Various biological models, including cultured cells and animals, have been found useful for studying the carcinogenesis effects of radon progeny alpha particles. In this paper, sugars cape cellular automata have been presented for computational study of complex biological effect of radon progeny alpha particles in lung bronchial airways. The model has included mechanism of DNA damage, which has been induced alpha particles hits, and then formation of transformation in the lung cells. Biomarkers were an objective measure or evaluation of normal or abnormal biological processes. In the model, the metabolism rate of infected cell has been induced alpha particles traversals, as a biomarker, has been followed to reach oncogenic transformation. The model results have successfully validated in comparison with "in vitro oncogenic transformation data" for C3H 10T1/2 cells. This model has provided an opportunity to study the cellular and molecular changes, at the various stages in radiation carcinogenesis, involving human cells. It has become well known that simulation could be used to investigate complex biomedical systems, in situations where traditional methodologies were difficult or too costly to employ.

Light, heat, action: neural control of fruit fly behaviour.

PubMed

Owald, David; Lin, Suewei; Waddell, Scott

2015-09-19

The fruit fly Drosophila melanogaster has emerged as a popular model to investigate fundamental principles of neural circuit operation. The sophisticated genetics and small brain permit a cellular resolution understanding of innate and learned behavioural processes. Relatively recent genetic and technical advances provide the means to specifically and reproducibly manipulate the function of many fly neurons with temporal resolution. The same cellular precision can also be exploited to express genetically encoded reporters of neural activity and cell-signalling pathways. Combining these approaches in living behaving animals has great potential to generate a holistic view of behavioural control that transcends the usual molecular, cellular and systems boundaries. In this review, we discuss these approaches with particular emphasis on the pioneering studies and those involving learning and memory.

A Tissue Engineered Model of Aging: Interdependence and Cooperative Effects in Failing Tissues.

PubMed

Acun, A; Vural, D C; Zorlutuna, P

2017-07-11

Aging remains a fundamental open problem in modern biology. Although there exist a number of theories on aging on the cellular scale, nearly nothing is known about how microscopic failures cascade to macroscopic failures of tissues, organs and ultimately the organism. The goal of this work is to bridge microscopic cell failure to macroscopic manifestations of aging. We use tissue engineered constructs to control the cellular-level damage and cell-cell distance in individual tissues to establish the role of complex interdependence and interactions between cells in aging tissues. We found that while microscopic mechanisms drive aging, the interdependency between cells plays a major role in tissue death, providing evidence on how cellular aging is connected to its higher systemic consequences.

The extraction of simple relationships in growth factor-specific multiple-input and multiple-output systems in cell-fate decisions by backward elimination PLS regression.

PubMed

Akimoto, Yuki; Yugi, Katsuyuki; Uda, Shinsuke; Kudo, Takamasa; Komori, Yasunori; Kubota, Hiroyuki; Kuroda, Shinya

2013-01-01

Cells use common signaling molecules for the selective control of downstream gene expression and cell-fate decisions. The relationship between signaling molecules and downstream gene expression and cellular phenotypes is a multiple-input and multiple-output (MIMO) system and is difficult to understand due to its complexity. For example, it has been reported that, in PC12 cells, different types of growth factors activate MAP kinases (MAPKs) including ERK, JNK, and p38, and CREB, for selective protein expression of immediate early genes (IEGs) such as c-FOS, c-JUN, EGR1, JUNB, and FOSB, leading to cell differentiation, proliferation and cell death; however, how multiple-inputs such as MAPKs and CREB regulate multiple-outputs such as expression of the IEGs and cellular phenotypes remains unclear. To address this issue, we employed a statistical method called partial least squares (PLS) regression, which involves a reduction of the dimensionality of the inputs and outputs into latent variables and a linear regression between these latent variables. We measured 1,200 data points for MAPKs and CREB as the inputs and 1,900 data points for IEGs and cellular phenotypes as the outputs, and we constructed the PLS model from these data. The PLS model highlighted the complexity of the MIMO system and growth factor-specific input-output relationships of cell-fate decisions in PC12 cells. Furthermore, to reduce the complexity, we applied a backward elimination method to the PLS regression, in which 60 input variables were reduced to 5 variables, including the phosphorylation of ERK at 10 min, CREB at 5 min and 60 min, AKT at 5 min and JNK at 30 min. The simple PLS model with only 5 input variables demonstrated a predictive ability comparable to that of the full PLS model. The 5 input variables effectively extracted the growth factor-specific simple relationships within the MIMO system in cell-fate decisions in PC12 cells.

Simulating the effects of light intensity and carbonate system composition on particulate organic and inorganic carbon production in Emiliania huxleyi.

PubMed

Holtz, Lena-Maria; Wolf-Gladrow, Dieter; Thoms, Silke

2015-05-07

Coccolithophores play an important role in the marine carbon cycle. Variations in light intensity and external carbonate system composition alter intracellular carbon fluxes and therewith the production rates of particulate organic and inorganic carbon. Aiming to find a mechanistic explanation for the interrelation between dissolved inorganic carbon fluxes and particulate carbon production rates, we develop a numerical cell model for Emiliania huxleyi, one of the most abundant coccolithophore species. The model consists of four cellular compartments, for each of which the carbonate system is resolved dynamically. The compartments are connected to each other and to the external medium via substrate fluxes across the compartment-confining membranes. By means of the model we are able to explain several pattern observed in particulate organic and inorganic carbon production rates for different strains and under different acclimation conditions. Particulate organic and inorganic carbon production rates for instance decrease at very low external CO2 concentrations. Our model suggests that this effect is caused mainly by reduced HCO3(-) uptake rates, not by CO2 limitation. The often observed decrease in particulate inorganic carbon production rates under Ocean Acidification is explained by a downregulation of cellular HCO3(-) uptake. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Tensegrity I. Cell structure and hierarchical systems biology

NASA Technical Reports Server (NTRS)

Ingber, Donald E.

2003-01-01

In 1993, a Commentary in this journal described how a simple mechanical model of cell structure based on tensegrity architecture can help to explain how cell shape, movement and cytoskeletal mechanics are controlled, as well as how cells sense and respond to mechanical forces (J. Cell Sci. 104, 613-627). The cellular tensegrity model can now be revisited and placed in context of new advances in our understanding of cell structure, biological networks and mechanoregulation that have been made over the past decade. Recent work provides strong evidence to support the use of tensegrity by cells, and mathematical formulations of the model predict many aspects of cell behavior. In addition, development of the tensegrity theory and its translation into mathematical terms are beginning to allow us to define the relationship between mechanics and biochemistry at the molecular level and to attack the larger problem of biological complexity. Part I of this two-part article covers the evidence for cellular tensegrity at the molecular level and describes how this building system may provide a structural basis for the hierarchical organization of living systems--from molecule to organism. Part II, which focuses on how these structural networks influence information processing networks, appears in the next issue.

Using network biology to bridge pharmacokinetics and pharmacodynamics in oncology.

PubMed

Kirouac, D C; Onsum, M D

2013-09-04

If mathematical modeling is to be used effectively in cancer drug development, future models must take into account both the mechanistic details of cellular signal transduction networks and the pharmacokinetics (PK) of drugs used to inhibit their oncogenic activity. In this perspective, we present an approach to building multiscale models that capture systems-level architectural features of oncogenic signaling networks, and describe how these models can be used to design combination therapies and identify predictive biomarkers in silico.CPT: Pharmacometrics & Systems Pharmacology (2013) 2, e71; doi:10.1038/psp.2013.38; published online 4 September 2013.

"A Cellular Encounter": Constructing the Cell as a Whole System Using Illustrative Models

ERIC Educational Resources Information Center

Cohen, Joel I.

2014-01-01

A standard part of biology curricula is a project-based assessment of cell structure and function. However, these are often individual assignments that promote little problem-solving or group learning and avoid the subject of organelle chemical interactions. I evaluate a model-based cell project designed to foster group and individual guided…

In search of mitochondrial mechanisms: interfield excursions between cell biology and biochemistry.

PubMed

Bechtel, William; Abrahamsen, Adele

2007-01-01

Developing models of biological mechanisms, such as those involved in respiration in cells, often requires collaborative effort drawing upon techniques developed and information generated in different disciplines. Biochemists in the early decades of the 20th century uncovered all but the most elusive chemical operations involved in cellular respiration, but were unable to align the reaction pathways with particular structures in the cell. During the period 1940-1965 cell biology was emerging as a new discipline and made distinctive contributions to understanding the role of the mitochondrion and its component parts in cellular respiration. In particular, by developing techniques for localizing enzymes or enzyme systems in specific cellular components, cell biologists provided crucial information about the organized structures in which the biochemical reactions occurred. Although the idea that biochemical operations are intimately related to and depend on cell structures was at odds with the then-dominant emphasis on systems of soluble enzymes in biochemistry, a reconceptualization of energetic processes in the 1960s and 1970s made it clear why cell structure was critical to the biochemical account. This paper examines how numerous excursions between biochemistry and cell biology contributed a new understanding of the mechanism of cellular respiration.

Cellular characterization of compression induced-damage in live biological samples

NASA Astrophysics Data System (ADS)

Bo, Chiara; Balzer, Jens; Hahnel, Mark; Rankin, Sara M.; Brown, Katherine A.; Proud, William G.

2011-06-01

Understanding the dysfunctions that high-intensity compression waves induce in human tissues is critical to impact on acute-phase treatments and requires the development of experimental models of traumatic damage in biological samples. In this study we have developed an experimental system to directly assess the impact of dynamic loading conditions on cellular function at the molecular level. Here we present a confinement chamber designed to subject live cell cultures in liquid environment to compression waves in the range of tens of MPa using a split Hopkinson pressure bars system. Recording the loading history and collecting the samples post-impact without external contamination allow the definition of parameters such as pressure and duration of the stimulus that can be related to the cellular damage. The compression experiments are conducted on Mesenchymal Stem Cells from BALB/c mice and the damage analysis are compared to two control groups. Changes in Stem cell viability, phenotype and function are assessed flow cytometry and with in vitro bioassays at two different time points. Identifying the cellular and molecular mechanisms underlying the damage caused by dynamic loading in live biological samples could enable the development of new treatments for traumatic injuries.

Insights on Localized and Systemic Delivery of Redox-Based Therapeutics

PubMed Central

Batrakova, Elena V.; Mota, Roberto

2018-01-01

Reactive oxygen and nitrogen species are indispensable in cellular physiology and signaling. Overproduction of these reactive species or failure to maintain their levels within the physiological range results in cellular redox dysfunction, often termed cellular oxidative stress. Redox dysfunction in turn is at the molecular basis of disease etiology and progression. Accordingly, antioxidant intervention to restore redox homeostasis has been pursued as a therapeutic strategy for cardiovascular disease, cancer, and neurodegenerative disorders among many others. Despite preliminary success in cellular and animal models, redox-based interventions have virtually been ineffective in clinical trials. We propose the fundamental reason for their failure is a flawed delivery approach. Namely, systemic delivery for a geographically local disease limits the effectiveness of the antioxidant. We take a critical look at the literature and evaluate successful and unsuccessful approaches to translation of redox intervention to the clinical arena, including dose, patient selection, and delivery approach. We argue that when interpreting a failed antioxidant-based clinical trial, it is crucial to take into account these variables and importantly, whether the drug had an effect on the redox status. Finally, we propose that local and targeted delivery hold promise to translate redox-based therapies from the bench to the bedside. PMID:29636836

Random blebbing motion: A simple model linking cell structural properties to migration characteristics.

PubMed

Woolley, Thomas E; Gaffney, Eamonn A; Goriely, Alain

2017-07-01

If the plasma membrane of a cell is able to delaminate locally from its actin cortex, a cellular bleb can be produced. Blebs are pressure-driven protrusions, which are noteworthy for their ability to produce cellular motion. Starting from a general continuum mechanics description, we restrict ourselves to considering cell and bleb shapes that maintain approximately spherical forms. From this assumption, we obtain a tractable algebraic system for bleb formation. By including cell-substrate adhesions, we can model blebbing cell motility. Further, by considering mechanically isolated blebbing events, which are randomly distributed over the cell, we can derive equations linking the macroscopic migration characteristics to the microscopic structural parameters of the cell. This multiscale modeling framework is then used to provide parameter estimates, which are in agreement with current experimental data. In summary, the construction of the mathematical model provides testable relationships between the bleb size and cell motility.

Computational models for the nonlinear analysis of reinforced concrete plates

NASA Technical Reports Server (NTRS)

Hinton, E.; Rahman, H. H. A.; Huq, M. M.

1980-01-01

A finite element computational model for the nonlinear analysis of reinforced concrete solid, stiffened and cellular plates is briefly outlined. Typically, Mindlin elements are used to model the plates whereas eccentric Timoshenko elements are adopted to represent the beams. The layering technique, common in the analysis of reinforced concrete flexural systems, is incorporated in the model. The proposed model provides an inexpensive and reasonably accurate approach which can be extended for use with voided plates.

Generalized reconfigurable memristive dynamical system (MDS) for neuromorphic applications

PubMed Central

Bavandpour, Mohammad; Soleimani, Hamid; Linares-Barranco, Bernabé; Abbott, Derek; Chua, Leon O.

2015-01-01

This study firstly presents (i) a novel general cellular mapping scheme for two dimensional neuromorphic dynamical systems such as bio-inspired neuron models, and (ii) an efficient mixed analog-digital circuit, which can be conveniently implemented on a hybrid memristor-crossbar/CMOS platform, for hardware implementation of the scheme. This approach employs 4n memristors and no switch for implementing an n-cell system in comparison with 2n2 memristors and 2n switches of a Cellular Memristive Dynamical System (CMDS). Moreover, this approach allows for dynamical variables with both analog and one-hot digital values opening a wide range of choices for interconnections and networking schemes. Dynamical response analyses show that this circuit exhibits various responses based on the underlying bifurcation scenarios which determine the main characteristics of the neuromorphic dynamical systems. Due to high programmability of the circuit, it can be applied to a variety of learning systems, real-time applications, and analytically indescribable dynamical systems. We simulate the FitzHugh-Nagumo (FHN), Adaptive Exponential (AdEx) integrate and fire, and Izhikevich neuron models on our platform, and investigate the dynamical behaviors of these circuits as case studies. Moreover, error analysis shows that our approach is suitably accurate. We also develop a simple hardware prototype for experimental demonstration of our approach. PMID:26578867

Generalized reconfigurable memristive dynamical system (MDS) for neuromorphic applications.

PubMed

Bavandpour, Mohammad; Soleimani, Hamid; Linares-Barranco, Bernabé; Abbott, Derek; Chua, Leon O

2015-01-01

This study firstly presents (i) a novel general cellular mapping scheme for two dimensional neuromorphic dynamical systems such as bio-inspired neuron models, and (ii) an efficient mixed analog-digital circuit, which can be conveniently implemented on a hybrid memristor-crossbar/CMOS platform, for hardware implementation of the scheme. This approach employs 4n memristors and no switch for implementing an n-cell system in comparison with 2n (2) memristors and 2n switches of a Cellular Memristive Dynamical System (CMDS). Moreover, this approach allows for dynamical variables with both analog and one-hot digital values opening a wide range of choices for interconnections and networking schemes. Dynamical response analyses show that this circuit exhibits various responses based on the underlying bifurcation scenarios which determine the main characteristics of the neuromorphic dynamical systems. Due to high programmability of the circuit, it can be applied to a variety of learning systems, real-time applications, and analytically indescribable dynamical systems. We simulate the FitzHugh-Nagumo (FHN), Adaptive Exponential (AdEx) integrate and fire, and Izhikevich neuron models on our platform, and investigate the dynamical behaviors of these circuits as case studies. Moreover, error analysis shows that our approach is suitably accurate. We also develop a simple hardware prototype for experimental demonstration of our approach.

Ames Culture Chamber System: Enabling Model Organism Research Aboard the international Space Station

NASA Technical Reports Server (NTRS)

Steele, Marianne

2014-01-01

Understanding the genetic, physiological, and behavioral effects of spaceflight on living organisms and elucidating the molecular mechanisms that underlie these effects are high priorities for NASA. Certain organisms, known as model organisms, are widely studied to help researchers better understand how all biological systems function. Small model organisms such as nem-atodes, slime mold, bacteria, green algae, yeast, and moss can be used to study the effects of micro- and reduced gravity at both the cellular and systems level over multiple generations. Many model organisms have sequenced genomes and published data sets on their transcriptomes and proteomes that enable scientific investigations of the molecular mechanisms underlying the adaptations of these organisms to space flight.

A fuzzy-theory-based behavioral model for studying pedestrian evacuation from a single-exit room

NASA Astrophysics Data System (ADS)

Fu, Libi; Song, Weiguo; Lo, Siuming

2016-08-01

Many mass events in recent years have highlighted the importance of research on pedestrian evacuation dynamics. A number of models have been developed to analyze crowd behavior under evacuation situations. However, few focus on pedestrians' decision-making with respect to uncertainty, vagueness and imprecision. In this paper, a discrete evacuation model defined on the cellular space is proposed according to the fuzzy theory which is able to describe imprecise and subjective information. Pedestrians' percept information and various characteristics are regarded as fuzzy input. Then fuzzy inference systems with rule bases, which resemble human reasoning, are established to obtain fuzzy output that decides pedestrians' movement direction. This model is tested in two scenarios, namely in a single-exit room with and without obstacles. Simulation results reproduce some classic dynamics phenomena discovered in real building evacuation situations, and are consistent with those in other models and experiments. It is hoped that this study will enrich movement rules and approaches in traditional cellular automaton models for evacuation dynamics.

A New Cellular Automaton Method Coupled with a Rate-dependent (CARD) Model for Predicting Dynamic Recrystallization Behavior

NASA Astrophysics Data System (ADS)

Azarbarmas, M.; Aghaie-Khafri, M.

2018-03-01

A comprehensive cellular automaton (CA) model should be coupled with a rate-dependent (RD) model for analyzing the RD deformation of alloys at high temperatures. In the present study, a new CA technique coupled with an RD model—namely, CARD—was developed. The proposed CARD model was used to simulate the dynamic recrystallization phenomenon during the hot deformation of the Inconel 718 superalloy. This model is capable of calculating the mean grain size and volume fraction of dynamic recrystallized grains, and estimating the phenomenological flow behavior of the material. In the presented model, an actual orientation definition comprising three Euler angles was used by implementing the electron backscatter diffraction data. For calculating the lattice rotation of grains, it was assumed that all slip systems of grains are active during the high-temperature deformation because of the intrinsic rate dependency of the procedure. Moreover, the morphological changes in grains were obtained using a topological module.

Applications of amorphous track models in radiation biology

NASA Technical Reports Server (NTRS)

Cucinotta, F. A.; Nikjoo, H.; Goodhead, D. T.; Wilson, J. W. (Principal Investigator)

1999-01-01

The average or amorphous track model uses the response of a system to gamma-rays and the radial distribution of dose about an ion's path to describe survival and other cellular endpoints from proton, heavy ion, and neutron irradiation. This model has been used for over 30 years to successfully fit many radiobiology data sets. We review several extensions of this approach that address objections to the original model, and consider applications of interest in radiobiology and space radiation risk assessment. In the light of present views of important cellular targets, the role of target size as manifested through the relative contributions from ion-kill (intra-track) and gamma-kill (inter-track) remains a critical question in understanding the success of the amorphous track model. Several variations of the amorphous model are discussed, including ones that consider the radial distribution of event-sizes rather than average electron dose, damage clusters rather than multiple targets, and a role for repair or damage processing.

Combined optical resolution photoacoustic and fluorescence micro-endoscopy

NASA Astrophysics Data System (ADS)

Shao, Peng; Shi, Wei; Hajireza, Parsin; Zemp, Roger J.

2012-02-01

We present a new micro-endoscopy system combining real-time C-scan optical-resolution photoacoustic micro-endoscopy (OR-PAME), and a high-resolution fluorescence micro-endoscopy system for visualizing fluorescently labeled cellular components and optically absorbing microvasculature simultaneously. With a diode-pumped 532-nm fiber laser, the OR-PAM sub-system is capable of imaging with a resolution of ~ 7μm. The fluorescence sub-system consists of a diode laser with 445 nm-centered emissions as the light source, an objective lens and a CCD camera. Proflavine, a FDA approved drug for human use, is used as the fluorescent contrast agent by topical application. The fluorescence system does not require any mechanical scanning. The scanning laser and the diode laser light source share the same light path within an optical fiber bundle containing 30,000 individual single mode fibers. The absorption of Proflavine at 532 nm is low, which mitigates absorption bleaching of the contrast agent by the photoacoustic excitation source. We demonstrate imaging in live murine models. The system is able to provide cellular morphology with cellular resolution co-registered with the structural and functional information given by OR-PAM. Therefore, the system has the potential to serve as a virtual biopsy technique, helping researchers and clinicians visualize angiogenesis, effects of anti-cancer drugs on both cells and the microcirculation, as well as aid in the study of other diseases.

Virtual Embryo: Systems Modeling in Developmental Toxicity

EPA Science Inventory

High-throughput screening (HTS) studies are providing a rich source of data that can be applied to chemical profiling to address sensitivity and specificity of molecular targets, biological pathways, cellular and developmental processes. EPA’s ToxCast project is testing 960 uniq...

Cellular characterization of compression-induceddamage in live biological samples

NASA Astrophysics Data System (ADS)

Bo, Chiara; Balzer, Jens; Hahnel, Mark; Rankin, Sara M.; Brown, Katherine A.; Proud, William

2012-03-01

Understanding the damage that high intensity compression waves induce in human tissues is critical for developing improved therapies for patients suffering from blast injuries. Experimentally based models of blast injury using live biological samples are needed. In this study we have developed a system to directly assess the effects of dynamic loading conditions on live cells. Here, we describe a confinement chamber designed to subject live cell cultures in a liquid environment to high intensity compression waves using a split Hopkinson pressure bar system. Signals from the strain gauges mounted on the bars and the chamber allow the measurement of parameters such as pressure and duration of the stimulus. The chamber itself also allows recovery of cells subjected to compression for assessment of cellular damage. In these studies we present evidence of increased levels of damage and loss of cellular integrity in cultured mouse mesenchymal stem cells subjected to a high-intensity compression wave with a peak pressure of 7.6 ± 0.8 MPa.

PLAN2L: a web tool for integrated text mining and literature-based bioentity relation extraction.

PubMed

Krallinger, Martin; Rodriguez-Penagos, Carlos; Tendulkar, Ashish; Valencia, Alfonso

2009-07-01

There is an increasing interest in using literature mining techniques to complement information extracted from annotation databases or generated by bioinformatics applications. Here we present PLAN2L, a web-based online search system that integrates text mining and information extraction techniques to access systematically information useful for analyzing genetic, cellular and molecular aspects of the plant model organism Arabidopsis thaliana. Our system facilitates a more efficient retrieval of information relevant to heterogeneous biological topics, from implications in biological relationships at the level of protein interactions and gene regulation, to sub-cellular locations of gene products and associations to cellular and developmental processes, i.e. cell cycle, flowering, root, leaf and seed development. Beyond single entities, also predefined pairs of entities can be provided as queries for which literature-derived relations together with textual evidences are returned. PLAN2L does not require registration and is freely accessible at http://zope.bioinfo.cnio.es/plan2l.

DOE Office of Scientific and Technical Information (OSTI.GOV)

De Vos, Winnok H., E-mail: winnok.devos@uantwerpen.be; Cell Systems and Imaging Research Group, Department of Molecular Biotechnology, Ghent University, Ghent; Beghuin, Didier

As commercial space flights have become feasible and long-term extraterrestrial missions are planned, it is imperative that the impact of space travel and the space environment on human physiology be thoroughly characterized. Scrutinizing the effects of potentially detrimental factors such as ionizing radiation and microgravity at the cellular and tissue level demands adequate visualization technology. Advanced light microscopy (ALM) is the leading tool for non-destructive structural and functional investigation of static as well as dynamic biological systems. In recent years, technological developments and advances in photochemistry and genetic engineering have boosted all aspects of resolution, readout and throughput, rendering ALMmore » ideally suited for biological space research. While various microscopy-based studies have addressed cellular response to space-related environmental stressors, biological endpoints have typically been determined only after the mission, leaving an experimental gap that is prone to bias results. An on-board, real-time microscopical monitoring device can bridge this gap. Breadboards and even fully operational microscope setups have been conceived, but they need to be rendered more compact and versatile. Most importantly, they must allow addressing the impact of gravity, or the lack thereof, on physiologically relevant biological systems in space and in ground-based simulations. In order to delineate the essential functionalities for such a system, we have reviewed the pending questions in space science, the relevant biological model systems, and the state-of-the art in ALM. Based on a rigorous trade-off, in which we recognize the relevance of multi-cellular systems and the cellular microenvironment, we propose a compact, but flexible concept for space-related cell biological research that is based on light sheet microscopy.« less

Quantifying the correlation between spatially defined oxygen gradients and cell fate in an engineered three-dimensional culture model.

PubMed

Ardakani, Amir G; Cheema, Umber; Brown, Robert A; Shipley, Rebecca J

2014-09-06

A challenge in three-dimensional tissue culture remains the lack of quantitative information linking nutrient delivery and cellular distribution. Both in vivo and in vitro, oxygen is delivered by diffusion from its source (blood vessel or the construct margins). The oxygen level at a defined distance from its source depends critically on the balance of diffusion and cellular metabolism. Cells may respond to this oxygen environment through proliferation, death and chemotaxis, resulting in spatially resolved gradients in cellular density. This study extracts novel spatially resolved and simultaneous data on tissue oxygenation, cellular proliferation, viability and chemotaxis in three-dimensional spiralled, cellular collagen constructs. Oxygen concentration gradients drove preferential cellular proliferation rates and viability in the higher oxygen zones and induced chemotaxis along the spiral of the collagen construct; an oxygen gradient of 1.03 mmHg mm(-1) in the spiral direction induced a mean migratory speed of 1015 μm day(-1). Although this movement was modest, it was effective in balancing the system to a stable cell density distribution, and provided insights into the natural cell mechanism for adapting cell number and activity to a prevailing oxygen regime.

Integrated network analysis and effective tools in plant systems biology

PubMed Central

Fukushima, Atsushi; Kanaya, Shigehiko; Nishida, Kozo

2014-01-01

One of the ultimate goals in plant systems biology is to elucidate the genotype-phenotype relationship in plant cellular systems. Integrated network analysis that combines omics data with mathematical models has received particular attention. Here we focus on the latest cutting-edge computational advances that facilitate their combination. We highlight (1) network visualization tools, (2) pathway analyses, (3) genome-scale metabolic reconstruction, and (4) the integration of high-throughput experimental data and mathematical models. Multi-omics data that contain the genome, transcriptome, proteome, and metabolome and mathematical models are expected to integrate and expand our knowledge of complex plant metabolisms. PMID:25408696

Quantum cellular automata

NASA Astrophysics Data System (ADS)

Porod, Wolfgang; Lent, Craig S.; Bernstein, Gary H.

1994-06-01

The Notre Dame group has developed a new paradigm for ultra-dense and ultra-fast information processing in nanoelectronic systems. These Quantum Cellular Automata (QCA's) are the first concrete proposal for a technology based on arrays of coupled quantum dots. The basic building block of these cellular arrays is the Notre Dame Logic Cell, as it has been called in the literature. The phenomenon of Coulomb exclusion, which is a synergistic interplay of quantum confinement and Coulomb interaction, leads to a bistable behavior of each cell which makes possible their use in large-scale cellular arrays. The physical interaction between neighboring cells has been exploited to implement logic functions. New functionality may be achieved in this fashion, and the Notre Dame group invented a versatile majority logic gate. In a series of papers, the feasibility of QCA wires, wire crossing, inverters, and Boolean logic gates was demonstrated. A major finding is that all logic functions may be integrated in a hierarchial fashion which allows the design of complicated QCA structures. The most complicated system which was simulated to date is a one-bit full adder consisting of some 200 cells. In addition to exploring these new concepts, efforts are under way to physically realize such structures both in semiconductor and metal systems. Extensive modeling work of semiconductor quantum dot structures has helped identify optimum design parameters for QCA experimental implementations.

Endocannabinod Signal Dysregulation in Autism Spectrum Disorders: A Correlation Link between Inflammatory State and Neuro-Immune Alterations

PubMed Central

Brigida, Anna Lisa; Schultz, Stephen; Cascone, Mariana; Antonucci, Nicola; Siniscalco, Dario

2017-01-01

Several studies highlight a key involvement of endocannabinoid (EC) system in autism pathophysiology. The EC system is a complex network of lipid signaling pathways comprised of arachidonic acid-derived compounds (anandamide, AEA) and 2-arachidonoyl glycerol (2-AG), their G-protein-coupled receptors (cannabinoid receptors CB1 and CB2) and the associated enzymes. In addition to autism, the EC system is also involved in several other psychiatric disorders (i.e., anxiety, major depression, bipolar disorder and schizophrenia). This system is a key regulator of metabolic and cellular pathways involved in autism, such as food intake, energy metabolism and immune system control. Early studies in autism animal models have demonstrated alterations in the brain’s EC system. Autism is also characterized by immune system dysregulation. This alteration includes differential monocyte and macrophage responses, and abnormal cytokine and T cell levels. EC system dysfunction in a monocyte and macrophagic cellular model of autism has been demonstrated by showing that the mRNA and protein for CB2 receptor and EC enzymes were significantly dysregulated, further indicating the involvement of the EC system in autism-associated immunological disruptions. Taken together, these new findings offer a novel perspective in autism research and indicate that the EC system could represent a novel target option for autism pharmacotherapy. PMID:28671614

Discrete diffusion models to study the effects of Mg2+ concentration on the PhoPQ signal transduction system

PubMed Central

2010-01-01

Background The challenge today is to develop a modeling and simulation paradigm that integrates structural, molecular and genetic data for a quantitative understanding of physiology and behavior of biological processes at multiple scales. This modeling method requires techniques that maintain a reasonable accuracy of the biological process and also reduces the computational overhead. This objective motivates the use of new methods that can transform the problem from energy and affinity based modeling to information theory based modeling. To achieve this, we transform all dynamics within the cell into a random event time, which is specified through an information domain measure like probability distribution. This allows us to use the “in silico” stochastic event based modeling approach to find the molecular dynamics of the system. Results In this paper, we present the discrete event simulation concept using the example of the signal transduction cascade triggered by extra-cellular Mg2+ concentration in the two component PhoPQ regulatory system of Salmonella Typhimurium. We also present a model to compute the information domain measure of the molecular transport process by estimating the statistical parameters of inter-arrival time between molecules/ions coming to a cell receptor as external signal. This model transforms the diffusion process into the information theory measure of stochastic event completion time to get the distribution of the Mg2+ departure events. Using these molecular transport models, we next study the in-silico effects of this external trigger on the PhoPQ system. Conclusions Our results illustrate the accuracy of the proposed diffusion models in explaining the molecular/ionic transport processes inside the cell. Also, the proposed simulation framework can incorporate the stochasticity in cellular environments to a certain degree of accuracy. We expect that this scalable simulation platform will be able to model more complex biological systems with reasonable accuracy to understand their temporal dynamics. PMID:21143785

Discrete diffusion models to study the effects of Mg2+ concentration on the PhoPQ signal transduction system.

PubMed

Ghosh, Preetam; Ghosh, Samik; Basu, Kalyan; Das, Sajal K; Zhang, Chaoyang

2010-12-01

The challenge today is to develop a modeling and simulation paradigm that integrates structural, molecular and genetic data for a quantitative understanding of physiology and behavior of biological processes at multiple scales. This modeling method requires techniques that maintain a reasonable accuracy of the biological process and also reduces the computational overhead. This objective motivates the use of new methods that can transform the problem from energy and affinity based modeling to information theory based modeling. To achieve this, we transform all dynamics within the cell into a random event time, which is specified through an information domain measure like probability distribution. This allows us to use the "in silico" stochastic event based modeling approach to find the molecular dynamics of the system. In this paper, we present the discrete event simulation concept using the example of the signal transduction cascade triggered by extra-cellular Mg2+ concentration in the two component PhoPQ regulatory system of Salmonella Typhimurium. We also present a model to compute the information domain measure of the molecular transport process by estimating the statistical parameters of inter-arrival time between molecules/ions coming to a cell receptor as external signal. This model transforms the diffusion process into the information theory measure of stochastic event completion time to get the distribution of the Mg2+ departure events. Using these molecular transport models, we next study the in-silico effects of this external trigger on the PhoPQ system. Our results illustrate the accuracy of the proposed diffusion models in explaining the molecular/ionic transport processes inside the cell. Also, the proposed simulation framework can incorporate the stochasticity in cellular environments to a certain degree of accuracy. We expect that this scalable simulation platform will be able to model more complex biological systems with reasonable accuracy to understand their temporal dynamics.

C9ORF72 hexanucleotide repeat exerts toxicity in a stable, inducible motor neuronal cell model, which is rescued by partial depletion of Pten

PubMed Central

Stopford, Matthew J.; Higginbottom, Adrian; Hautbergue, Guillaume M.; Cooper-Knock, Johnathan; Mulcahy, Padraig J.; De Vos, Kurt J.; Renton, Alan E.; Pliner, Hannah; Calvo, Andrea; Chio, Adriano; Traynor, Bryan J.; Azzouz, Mimoun; Heath, Paul R.; Kirby, Janine

2017-01-01

Abstract Amyotrophic lateral sclerosis (ALS) is a devastating and incurable neurodegenerative disease, characterised by progressive failure of the neuromuscular system. A (G4C2)n repeat expansion in C9ORF72 is the most common genetic cause of ALS and frontotemporal dementia (FTD). To date, the balance of evidence indicates that the (G4C2)n repeat causes toxicity and neurodegeneration via a gain-of-toxic function mechanism; either through direct RNA toxicity or through the production of toxic aggregating dipeptide repeat proteins. Here, we have generated a stable and isogenic motor neuronal NSC34 cell model with inducible expression of a (G4C2)102 repeat, to investigate the gain-of-toxic function mechanisms. The expression of the (G4C2)102 repeat produces RNA foci and also undergoes RAN translation. In addition, the expression of the (G4C2)102 repeat shows cellular toxicity. Through comparison of transcriptomic data from the cellular model with laser-captured spinal motor neurons from C9ORF72-ALS cases, we also demonstrate that the PI3K/Akt cell survival signalling pathway is dysregulated in both systems. Furthermore, partial knockdown of Pten rescues the toxicity observed in the NSC34 (G4C2)102 cellular gain-of-toxic function model of C9ORF72-ALS. Our data indicate that PTEN may provide a potential therapeutic target to ameliorate toxic effects of the (G4C2)n repeat. PMID:28158451

Simulations of Forest Fires by the Cellular Automata Model "ABBAMPAU"

NASA Astrophysics Data System (ADS)

di Gregorio, S.; Bendicenti, E.

2003-04-01

Forest fires represent a serious environmental problem, whose negative impact is becoming day by day more worrisome. Forest fires are very complex phenomena; that need an interdisciplinary approach. The adopted method to modelling involves the definition of local rules, from which the global behaviour of the system can emerge. The paradigm of Cellular Automata was applied and the model ABBAMPAU was projected to simulate the evolution of forest fires. Cellular Automata features (parallelism and a-centrism) seem to match the system "forest fire"; the parameters, describing globally a forest fire, i.e. propagation rate, flame length and direction, fireline intensity, fire duration time et c. are mainly depending on some local characteristics i.e. vegetation type (live and dead fuel), relative humidity, fuel moisture, heat, territory morphology (altitude, slope), et c.. The only global characteristic is given by wind velocity and direction, but wind velocity and direction is locally altered according to the morphology; therefore wind has also to be considered at local level. ABBAMPAU accounts for the following aspects of the phenomenon: effects of combustion in surface and crown fire inside the cell, crown fire triggering off; surface and crown fire spread, determination of the local wind rate and direction. A validation of ABBAMPAU was tested on a real case of forest fire, in the territory of Villaputzu, Sardinia island, August 22nd, 1998. First simulations account for the main characteristics of the phenomenon and agree with the observations. The results show that the model could be applied for the forest fire preventions, the productions of risk scenarios and the evaluation of the forest fire environmental impact.

Linking micro- and macro-evolution at the cell type level: a view from the lophotrochozoan Platynereis dumerilii.

PubMed

Simakov, Oleg; Larsson, Tomas A; Arendt, Detlev

2013-09-01

Ever since the origin of the first metazoans over 600 million years ago, cell type diversification has been driven by micro-evolutionary processes at population level, leading to macro-evolution changes above species level. In this review, we introduce the marine annelid Platynereis dumerilii, a member of the lophotrochozoan clade (a key yet most understudied superphylum of bilaterians), as a suitable model system for the simultaneous study, at cellular resolution, of macro-evolutionary processes across phyla and of micro-evolutionary processes across highly polymorphic populations collected worldwide. Recent advances in molecular and experimental techniques, easy maintenance and breeding, and the fast, synchronous and stereotypical development have facilitated the establishment of Platynereis as one of the leading model species in the eco-evo-devo field. Most importantly, Platynereis allows the combination of expression profiling, morphological and physiological characterization at the single cell level. Here, we discuss recent advances in the collection of -omics data for the lab strain and for natural populations collected world-wide that can be integrated with population-specific cellular analyses to result in a cellular atlas integrating genetic, phenotypic and ecological variation. This makes Platynereis a tractable system to begin understanding the interplay between macro- and micro-evolutionary processes and cell type diversity.

Human Breast Cancer Histoid

PubMed Central

Kaur, Pavinder; Ward, Brenda; Saha, Baisakhi; Young, Lillian; Groshen, Susan; Techy, Geza; Lu, Yani; Atkinson, Roscoe; Taylor, Clive R.; Ingram, Marylou

2011-01-01

Progress in our understanding of heterotypic cellular interaction in the tumor microenvironment, which is recognized to play major roles in cancer progression, has been hampered due to unavailability of an appropriate in vitro co-culture model. The aim of this study was to generate an in vitro 3-dimensional human breast cancer model, which consists of cancer cells and fibroblasts. Breast cancer cells (UACC-893) and fibroblasts at various densities were co-cultured in a rotating suspension culture system to establish co-culture parameters. Subsequently, UACC-893, BT.20, or MDA.MB.453 were co-cultured with fibroblasts for 9 days. Co-cultures resulted in the generation of breast cancer histoid (BCH) with cancer cells showing the invasion of fibroblast spheroids, which were visualized by immunohistochemical (IHC) staining of sections (4 µm thick) of BCH. A reproducible quantitative expression of C-erbB.2 was detected in UACC-893 cancer cells in BCH sections by IHC staining and the Automated Cellular Imaging System. BCH sections also consistently exhibited qualitative expression of pancytokeratins, p53, Ki-67, or E-cadherin in cancer cells and that of vimentin or GSTPi in fibroblasts, fibronectin in the basement membrane and collagen IV in the extracellular matrix. The expression of the protein analytes and cellular architecture of BCH were markedly similar to those of breast cancer tissue. PMID:22034518

Modeling Cell and Tumor-Metastasis Dosimetry with the Particle and Heavy Ion Transport Code System (PHITS) Software for Targeted Alpha-Particle Radionuclide Therapy.

PubMed

Lee, Dongyoul; Li, Mengshi; Bednarz, Bryan; Schultz, Michael K

2018-06-26

The use of targeted radionuclide therapy for cancer is on the rise. While beta-particle-emitting radionuclides have been extensively explored for targeted radionuclide therapy, alpha-particle-emitting radionuclides are emerging as effective alternatives. In this context, fundamental understanding of the interactions and dosimetry of these emitted particles with cells in the tumor microenvironment is critical to ascertaining the potential of alpha-particle-emitting radionuclides. One important parameter that can be used to assess these metrics is the S-value. In this study, we characterized several alpha-particle-emitting radionuclides (and their associated radionuclide progeny) regarding S-values in the cellular and tumor-metastasis environments. The Particle and Heavy Ion Transport code System (PHITS) was used to obtain S-values via Monte Carlo simulation for cell and tumor metastasis resulting from interactions with the alpha-particle-emitting radionuclides, lead-212 ( 212 Pb), actinium-225 ( 225 Ac) and bismuth-213 ( 213 Bi); these values were compared to the beta-particle-emitting radionuclides yttrium-90 ( 90 Y) and lutetium-177 ( 177 Lu) and an Auger-electron-emitting radionuclide indium-111 ( 111 In). The effect of cellular internalization on S-value was explored at increasing degree of internalization for each radionuclide. This aspect of S-value determination was further explored in a cell line-specific fashion for six different cancer cell lines based on the cell dimensions obtained by confocal microscopy. S-values from PHITS were in good agreement with MIRDcell S-values (cellular S-values) and the values found by Hindié et al. (tumor S-values). In the cellular model, 212 Pb and 213 Bi decay series produced S-values that were 50- to 120-fold higher than 177 Lu, while 225 Ac decay series analysis suggested S-values that were 240- to 520-fold higher than 177 Lu. S-values arising with 100% cellular internalization were two- to sixfold higher for the nucleus when compared to 0% internalization. The tumor dosimetry model defines the relative merit of radionuclides and suggests alpha particles may be effective for large tumors as well as small tumor metastases. These results from PHITS modeling substantiate emerging evidence that alpha-particle-emitting radionuclides may be an effective alternative to beta-particle-emitting radionuclides for targeted radionuclide therapy due to preferred dose-deposition profiles in the cellular and tumor metastasis context. These results further suggest that internalization of alpha-particle-emitting radionuclides via radiolabeled ligands may increase the relative biological effectiveness of radiotherapeutics.

Steady-state kinetic modeling constrains cellular resting states and dynamic behavior.

PubMed

Purvis, Jeremy E; Radhakrishnan, Ravi; Diamond, Scott L

2009-03-01

A defining characteristic of living cells is the ability to respond dynamically to external stimuli while maintaining homeostasis under resting conditions. Capturing both of these features in a single kinetic model is difficult because the model must be able to reproduce both behaviors using the same set of molecular components. Here, we show how combining small, well-defined steady-state networks provides an efficient means of constructing large-scale kinetic models that exhibit realistic resting and dynamic behaviors. By requiring each kinetic module to be homeostatic (at steady state under resting conditions), the method proceeds by (i) computing steady-state solutions to a system of ordinary differential equations for each module, (ii) applying principal component analysis to each set of solutions to capture the steady-state solution space of each module network, and (iii) combining optimal search directions from all modules to form a global steady-state space that is searched for accurate simulation of the time-dependent behavior of the whole system upon perturbation. Importantly, this stepwise approach retains the nonlinear rate expressions that govern each reaction in the system and enforces constraints on the range of allowable concentration states for the full-scale model. These constraints not only reduce the computational cost of fitting experimental time-series data but can also provide insight into limitations on system concentrations and architecture. To demonstrate application of the method, we show how small kinetic perturbations in a modular model of platelet P2Y(1) signaling can cause widespread compensatory effects on cellular resting states.

Integration of mobile satellite and cellular systems

NASA Technical Reports Server (NTRS)

Drucker, Elliott H.; Estabrook, Polly; Pinck, Deborah; Ekroot, Laura

1993-01-01

By integrating the ground based infrastructure component of a mobile satellite system with the infrastructure systems of terrestrial 800 MHz cellular service providers, a seamless network of universal coverage can be established. Users equipped for both cellular and satellite service can take advantage of a number of features made possible by such integration, including seamless handoff and universal roaming. To provide maximum benefit at lowest posible cost, the means by which these systems are integrated must be carefully considered. Mobile satellite hub stations must be configured to efficiently interface with cellular Mobile Telephone Switching Offices (MTSO's), and cost effective mobile units that provide both cellular and satellite capability must be developed.

Integration of mobile satellite and cellular systems

NASA Astrophysics Data System (ADS)

Drucker, Elliott H.; Estabrook, Polly; Pinck, Deborah; Ekroot, Laura

By integrating the ground based infrastructure component of a mobile satellite system with the infrastructure systems of terrestrial 800 MHz cellular service providers, a seamless network of universal coverage can be established. Users equipped for both cellular and satellite service can take advantage of a number of features made possible by such integration, including seamless handoff and universal roaming. To provide maximum benefit at lowest posible cost, the means by which these systems are integrated must be carefully considered. Mobile satellite hub stations must be configured to efficiently interface with cellular Mobile Telephone Switching Offices (MTSO's), and cost effective mobile units that provide both cellular and satellite capability must be developed.

Erythrocyte sedimentation rate and fibrinogen concentration of whole blood influences the cellular composition of platelet-rich plasma obtained from centrifugation methods.

PubMed

Yin, Wenjing; Xu, Zhengliang; Sheng, Jiagen; Xie, Xuetao; Zhang, Changqing

2017-09-01

Erythrocyte sedimentation rate (ESR), which reflects the sedimentation rate of platelets, leukocytes and erythrocytes in response to centrifugal force, may influence the cellular composition of platelet-rich plasma (PRP) obtained via centrifugation methods. However, no relevant studies have substantiated this. In the present study, blood was collected from 40 healthy volunteers and used to prepare PRP with two plasma-based preparation systems [YinPRP and Plasma Rich in Growth Factor (PRGF) systems] and two buffy coat-based systems (RegenPRP and WEGOPRP systems) in a single-donor model. Volumes of PRP and platelet-poor plasma (PPP) that were removed in the preparation process were recorded. Analyses of ESR, haematocrit, C-reaction protein, coagulation, serum glucose and serum lipid of the whole blood used for PRP preparation were performed to evaluate the levels of ESR and the factors known to influence it. Whole blood analysis was performed to evaluate the cellular composition of PRP. Results demonstrated that there were marked positive correlations between the ESR of the whole blood used for PRP preparation and PPP removal efficiencies, platelet concentrations, platelet capture efficiencies and platelet enrichment factors of PRP formulations obtained from plasma-based systems, and PRP yield efficiency of RegenPRP and PPP removal efficiency of WEGOPRP. Furthermore, there were marked negative correlations between ESR and concentrations and enrichment factors of platelets, leukocytes and erythrocytes of RegenPRP. Fibrinogen concentration of the whole blood, which had a marked positive correlation with ESR, also influenced the cellular composition of PRP. These findings may increase the understanding of PRP preparation and provide substantial evidence for the individualised optimisation of PRP preparation systems used in clinical practice.

Investigation of Doppler Effects on high mobility OFDM-MIMO systems with the support of High Altitude Platforms (HAPs)

NASA Astrophysics Data System (ADS)

Mohammed, H. A.; Sibley, M. J. N.; Mather, P. J.

2012-05-01

The merging of Orthogonal Frequency Division Multiplexing (OFDM) with Multiple-input multiple-output (MIMO) is a promising mobile air interface solution for next generation wireless local area networks (WLANs) and 4G mobile cellular wireless systems. This paper details the design of a highly robust and efficient OFDM-MIMO system to support permanent accessibility and higher data rates to users moving at high speeds, such as users travelling on trains. It has high relevance for next generation wireless local area networks (WLANs) and 4G mobile cellular wireless systems. The paper begins with a comprehensive literature review focused on both technologies. This is followed by the modelling of the OFDM-MIMO physical layer based on Simulink/Matlab that takes into consideration high vehicular mobility. Then the entire system is simulated and analysed under different encoding and channel estimation algorithms. The use of High Altitude Platform system (HAPs) technology is considered and analysed.

Mitochondrial and Ubiquitin Proteasome System Dysfunction in Ageing and Disease: Two Sides of the Same Coin?

PubMed Central

Ross, Jaime M.; Olson, Lars; Coppotelli, Giuseppe

2015-01-01

Mitochondrial dysfunction and impairment of the ubiquitin proteasome system have been described as two hallmarks of the ageing process. Additionally, both systems have been implicated in the etiopathogenesis of many age-related diseases, particularly neurodegenerative disorders, such as Alzheimer’s and Parkinson’s disease. Interestingly, these two systems are closely interconnected, with the ubiquitin proteasome system maintaining mitochondrial homeostasis by regulating organelle dynamics, the proteome, and mitophagy, and mitochondrial dysfunction impairing cellular protein homeostasis by oxidative damage. Here, we review the current literature and argue that the interplay of the two systems should be considered in order to better understand the cellular dysfunction observed in ageing and age-related diseases. Such an approach may provide valuable insights into molecular mechanisms underlying the ageing process, and further discovery of treatments to counteract ageing and its associated diseases. Furthermore, we provide a hypothetical model for the heterogeneity described among individuals during ageing. PMID:26287188

A solution to the biodiversity paradox by logical deterministic cellular automata.

PubMed

Kalmykov, Lev V; Kalmykov, Vyacheslav L

2015-06-01

The paradox of biological diversity is the key problem of theoretical ecology. The paradox consists in the contradiction between the competitive exclusion principle and the observed biodiversity. The principle is important as the basis for ecological theory. On a relatively simple model we show a mechanism of indefinite coexistence of complete competitors which violates the known formulations of the competitive exclusion principle. This mechanism is based on timely recovery of limiting resources and their spatio-temporal allocation between competitors. Because of limitations of the black-box modeling there was a problem to formulate the exclusion principle correctly. Our white-box multiscale model of two-species competition is based on logical deterministic individual-based cellular automata. This approach provides an automatic deductive inference on the basis of a system of axioms, and gives a direct insight into mechanisms of the studied system. It is one of the most promising methods of artificial intelligence. We reformulate and generalize the competitive exclusion principle and explain why this formulation provides a solution of the biodiversity paradox. In addition, we propose a principle of competitive coexistence.

Learning and evolution in bacterial taxis: an operational amplifier circuit modeling the computational dynamics of the prokaryotic 'two component system' protein network.

PubMed

Di Paola, Vieri; Marijuán, Pedro C; Lahoz-Beltra, Rafael

2004-01-01

Adaptive behavior in unicellular organisms (i.e., bacteria) depends on highly organized networks of proteins governing purposefully the myriad of molecular processes occurring within the cellular system. For instance, bacteria are able to explore the environment within which they develop by utilizing the motility of their flagellar system as well as a sophisticated biochemical navigation system that samples the environmental conditions surrounding the cell, searching for nutrients or moving away from toxic substances or dangerous physical conditions. In this paper we discuss how proteins of the intervening signal transduction network could be modeled as artificial neurons, simulating the dynamical aspects of the bacterial taxis. The model is based on the assumption that, in some important aspects, proteins can be considered as processing elements or McCulloch-Pitts artificial neurons that transfer and process information from the bacterium's membrane surface to the flagellar motor. This simulation of bacterial taxis has been carried out on a hardware realization of a McCulloch-Pitts artificial neuron using an operational amplifier. Based on the behavior of the operational amplifier we produce a model of the interaction between CheY and FliM, elements of the prokaryotic two component system controlling chemotaxis, as well as a simulation of learning and evolution processes in bacterial taxis. On the one side, our simulation results indicate that, computationally, these protein 'switches' are similar to McCulloch-Pitts artificial neurons, suggesting a bridge between evolution and learning in dynamical systems at cellular and molecular levels and the evolutive hardware approach. On the other side, important protein 'tactilizing' properties are not tapped by the model, and this suggests further complexity steps to explore in the approach to biological molecular computing.

Physico-electrochemical Characterization of Pluripotent Stem Cells during Self-Renewal or Differentiation by a Multi-modal Monitoring System.

PubMed

Low, Karen; Wong, Lauren Y; Maldonado, Maricela; Manjunath, Chetas; Horner, Christopher B; Perez, Mark; Myung, Nosang V; Nam, Jin

2017-05-09

Monitoring pluripotent stem cell behaviors (self-renewal and differentiation to specific lineages/phenotypes) is critical for a fundamental understanding of stem cell biology and their translational applications. In this study, a multi-modal stem cell monitoring system was developed to quantitatively characterize physico-electrochemical changes of the cells in real time, in relation to cellular activities during self-renewal or lineage-specific differentiation, in a non-destructive, label-free manner. The system was validated by measuring physical (mass) and electrochemical (impedance) changes in human induced pluripotent stem cells undergoing self-renewal, or subjected to mesendodermal or ectodermal differentiation, and correlating them to morphological (size, shape) and biochemical changes (gene/protein expression). An equivalent circuit model was used to further dissect the electrochemical (resistive and capacitive) contributions of distinctive cellular features. Overall, the combination of the physico-electrochemical measurements and electrical circuit modeling collectively offers a means to longitudinally quantify the states of stem cell self-renewal and differentiation. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

LacI(Ts)-Regulated Expression as an In Situ Intracellular Biomolecular Thermometer▿

PubMed Central

McCabe, K. M.; Lacherndo, E. J.; Albino-Flores, I.; Sheehan, E.; Hernandez, M.

2011-01-01

In response to needs for in situ thermometry, a temperature-sensitive vector was adapted to report changes in the intracellular heat content of Escherichia coli in near-real time. This model system utilized vectors expressing increasing quantities of β-galactosidase in response to stepwise temperature increases through a biologically relevant range (22 to 45°C). As judged by calibrated fluorometric and colorimetric reporters, both whole E. coli cells and lysates expressed significant repeatable changes in β-galactosidase activity that were sensitive to temperature changes of less than 1°C (35 to 45°C). This model system suggests that changes in cellular heat content can be detected independently of the medium in which cells are maintained, a feature of particular importance where the medium is heterogeneous or nonaqueous, or otherwise has a low heat transfer capacity. We report here that the intracellular temperature can be reliably obtained in near-real time using reliable fluorescent reporting systems from cellular scales, with a 20°C range of detection and at least 0.7°C sensitivity between 35 and 45°C. PMID:21378059

Optimization and comprehensive characterization of a faithful tissue culture model of the benign and malignant human prostate.

PubMed

Maund, Sophia Lisette; Nolley, Rosalie; Peehl, Donna Mae

2014-02-01

Few preclinical models accurately depict normal human prostate tissue or primary prostate cancer (PCa). In vitro systems typically lack complex cellular interactions among structured prostatic epithelia and a stromal microenvironment, and genetic and molecular fidelity are concerns in both in vitro and in vivo models. 'Tissue slice cultures' (TSCs) provide realistic preclinical models of diverse tissues and organs, but have not been fully developed or widely utilized for prostate studies. Problems encountered include degeneration of differentiated secretory cells, basal cell hyperplasia, and poor survival of PCa. Here, we optimized, characterized, and applied a TSC model of primary human PCa and benign prostate tissue that overcomes many deficiencies of current in vitro models. Tissue cores from fresh prostatectomy specimens were precision-cut at 300 μm and incubated in a rotary culture apparatus. The ability of varied culture conditions to faithfully maintain benign and cancer cell and tissue structure and function over time was evaluated by immunohistological and biochemical assays. After optimization of the culture system, molecular and cellular responses to androgen ablation and to piperlongumine (PL), purported to specifically reduce androgen signaling in PCa, were investigated. Optimized culture conditions successfully maintained the structural and functional fidelity of both benign and PCa TSCs for 5 days. TSCs exhibited androgen dependence, appropriately undergoing ductal degeneration, reduced proliferation, and decreased prostate-specific antigen expression upon androgen ablation. Further, TSCs revealed cancer-specific reduction of androgen receptor and increased apoptosis upon treatment with PL, validating data from cell lines. We demonstrate a TSC model that authentically recapitulates the structural, cellular, and genetic characteristics of the benign and malignant human prostate, androgen dependence of the native tissue, and cancer-specific response to a potentially new therapeutic for PCa. The work described herein provides a basis for advancing the experimental utility of the TSC model.

Computation Modeling of Limb-bud Dysmorphogenesis: Predicting Cellular Dynamics and Key Events in Developmental Toxicity with a Multicellular Systems Model (FutureToxII)

EPA Science Inventory

Congenital limb malformations are among the most frequent malformation occurs in humans, with a frequency of about 1 in 500 to 1 in 1000 human live births. ToxCast is profiling the bioactivity of thousands of chemicals based on high-throughput (HTS) and computational methods that...

Reverse-engineering the genetic circuitry of a cancer cell with predicted intervention in chronic lymphocytic leukemia.

PubMed

Vallat, Laurent; Kemper, Corey A; Jung, Nicolas; Maumy-Bertrand, Myriam; Bertrand, Frédéric; Meyer, Nicolas; Pocheville, Arnaud; Fisher, John W; Gribben, John G; Bahram, Seiamak

2013-01-08

Cellular behavior is sustained by genetic programs that are progressively disrupted in pathological conditions--notably, cancer. High-throughput gene expression profiling has been used to infer statistical models describing these cellular programs, and development is now needed to guide orientated modulation of these systems. Here we develop a regression-based model to reverse-engineer a temporal genetic program, based on relevant patterns of gene expression after cell stimulation. This method integrates the temporal dimension of biological rewiring of genetic programs and enables the prediction of the effect of targeted gene disruption at the system level. We tested the performance accuracy of this model on synthetic data before reverse-engineering the response of primary cancer cells to a proliferative (protumorigenic) stimulation in a multistate leukemia biological model (i.e., chronic lymphocytic leukemia). To validate the ability of our method to predict the effects of gene modulation on the global program, we performed an intervention experiment on a targeted gene. Comparison of the predicted and observed gene expression changes demonstrates the possibility of predicting the effects of a perturbation in a gene regulatory network, a first step toward an orientated intervention in a cancer cell genetic program.

Simulating the conversion of rural settlements to town land based on multi-agent systems and cellular automata.

PubMed

Liu, Yaolin; Kong, Xuesong; Liu, Yanfang; Chen, Yiyun

2013-01-01

Rapid urbanization in China has triggered the conversion of land from rural to urban use, particularly the conversion of rural settlements to town land. This conversion is the result of the joint effects of the geographic environment and agents involving the government, investors, and farmers. To understand the dynamic interaction dominated by agents and to predict the future landscape of town expansion, a small town land-planning model is proposed based on the integration of multi-agent systems (MAS) and cellular automata (CA). The MAS-CA model links the decision-making behaviors of agents with the neighbor effect of CA. The interaction rules are projected by analyzing the preference conflicts among agents. To better illustrate the effects of the geographic environment, neighborhood, and agent behavior, a comparative analysis between the CA and MAS-CA models in three different towns is presented, revealing interesting patterns in terms of quantity, spatial characteristics, and the coordinating process. The simulation of rural settlements conversion to town land through modeling agent decision and human-environment interaction is very useful for understanding the mechanisms of rural-urban land-use change in developing countries. This process can assist town planners in formulating appropriate development plans.

Modifiers and mechanisms of multi-system polyglutamine neurodegenerative disorders: lessons from fly models.

PubMed

Mallik, Moushami; Lakhotia, Subhash C

2010-12-01

Polyglutamine (polyQ) diseases, resulting from a dynamic expansion of glutamine repeats in a polypeptide, are a class of genetically inherited late onset neurodegenerative disorders which, despite expression of the mutated gene widely in brain and other tissues, affect defined subpopulations of neurons in a disease-specific manner. We briefly review the different polyQ-expansion-induced neurodegenerative disorders and the advantages of modelling them in Drosophila. Studies using the fly models have successfully identified a variety of genetic modifiers and have helped in understanding some of the molecular events that follow expression of the abnormal polyQ proteins. Expression of the mutant polyQ proteins causes, as a consequence of intra-cellular and inter-cellular networking, mis-regulation at multiple steps like transcriptional and posttranscriptional regulations, cell signalling, protein quality control systems (protein folding and degradation networks), axonal transport machinery etc., in the sensitive neurons, resulting ultimately in their death. The diversity of genetic modifiers of polyQ toxicity identified through extensive genetic screens in fly and other models clearly reflects a complex network effect of the presence of the mutated protein. Such network effects pose a major challenge for therapeutic applications.

Quantitative modeling of clinical, cellular, and extracellular matrix variables suggest prognostic indicators in cancer: a model in neuroblastoma.

PubMed

Tadeo, Irene; Piqueras, Marta; Montaner, David; Villamón, Eva; Berbegall, Ana P; Cañete, Adela; Navarro, Samuel; Noguera, Rosa

2014-02-01

Risk classification and treatment stratification for cancer patients is restricted by our incomplete picture of the complex and unknown interactions between the patient's organism and tumor tissues (transformed cells supported by tumor stroma). Moreover, all clinical factors and laboratory studies used to indicate treatment effectiveness and outcomes are by their nature a simplification of the biological system of cancer, and cannot yet incorporate all possible prognostic indicators. A multiparametric analysis on 184 tumor cylinders was performed. To highlight the benefit of integrating digitized medical imaging into this field, we present the results of computational studies carried out on quantitative measurements, taken from stromal and cancer cells and various extracellular matrix fibers interpenetrated by glycosaminoglycans, and eight current approaches to risk stratification systems in patients with primary and nonprimary neuroblastoma. New tumor tissue indicators from both fields, the cellular and the extracellular elements, emerge as reliable prognostic markers for risk stratification and could be used as molecular targets of specific therapies. The key to dealing with personalized therapy lies in the mathematical modeling. The use of bioinformatics in patient-tumor-microenvironment data management allows a predictive model in neuroblastoma.

Supporting performance and configuration management of GTE cellular networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tan, Ming; Lafond, C.; Jakobson, G.

GTE Laboratories, in cooperation with GTE Mobilnet, has developed and deployed PERFFEX (PERFormance Expert), an intelligent system for performance and configuration management of cellular networks. PERFEX assists cellular network performance and radio engineers in the analysis of large volumes of cellular network performance and configuration data. It helps them locate and determine the probable causes of performance problems, and provides intelligent suggestions about how to correct them. The system combines an expert cellular network performance tuning capability with a map-based graphical user interface, data visualization programs, and a set of special cellular engineering tools. PERFEX is in daily use atmore » more than 25 GTE Mobile Switching Centers. Since the first deployment of the system in late 1993, PERFEX has become a major GTE cellular network performance optimization tool.« less

Systematic Computation of Nonlinear Cellular and Molecular Dynamics with Low-Power CytoMimetic Circuits: A Simulation Study

PubMed Central

Papadimitriou, Konstantinos I.; Stan, Guy-Bart V.; Drakakis, Emmanuel M.

2013-01-01

This paper presents a novel method for the systematic implementation of low-power microelectronic circuits aimed at computing nonlinear cellular and molecular dynamics. The method proposed is based on the Nonlinear Bernoulli Cell Formalism (NBCF), an advanced mathematical framework stemming from the Bernoulli Cell Formalism (BCF) originally exploited for the modular synthesis and analysis of linear, time-invariant, high dynamic range, logarithmic filters. Our approach identifies and exploits the striking similarities existing between the NBCF and coupled nonlinear ordinary differential equations (ODEs) typically appearing in models of naturally encountered biochemical systems. The resulting continuous-time, continuous-value, low-power CytoMimetic electronic circuits succeed in simulating fast and with good accuracy cellular and molecular dynamics. The application of the method is illustrated by synthesising for the first time microelectronic CytoMimetic topologies which simulate successfully: 1) a nonlinear intracellular calcium oscillations model for several Hill coefficient values and 2) a gene-protein regulatory system model. The dynamic behaviours generated by the proposed CytoMimetic circuits are compared and found to be in very good agreement with their biological counterparts. The circuits exploit the exponential law codifying the low-power subthreshold operation regime and have been simulated with realistic parameters from a commercially available CMOS process. They occupy an area of a fraction of a square-millimetre, while consuming between 1 and 12 microwatts of power. Simulations of fabrication-related variability results are also presented. PMID:23393550

Theoretical aspects and modelling of cellular decision making, cell killing and information-processing in photodynamic therapy of cancer.

PubMed

Gkigkitzis, Ioannis

2013-01-01

The aim of this report is to provide a mathematical model of the mechanism for making binary fate decisions about cell death or survival, during and after Photodynamic Therapy (PDT) treatment, and to supply the logical design for this decision mechanism as an application of rate distortion theory to the biochemical processing of information by the physical system of a cell. Based on system biology models of the molecular interactions involved in the PDT processes previously established, and regarding a cellular decision-making system as a noisy communication channel, we use rate distortion theory to design a time dependent Blahut-Arimoto algorithm where the input is a stimulus vector composed of the time dependent concentrations of three PDT related cell death signaling molecules and the output is a cell fate decision. The molecular concentrations are determined by a group of rate equations. The basic steps are: initialize the probability of the cell fate decision, compute the conditional probability distribution that minimizes the mutual information between input and output, compute the cell probability of cell fate decision that minimizes the mutual information and repeat the last two steps until the probabilities converge. Advance to the next discrete time point and repeat the process. Based on the model from communication theory described in this work, and assuming that the activation of the death signal processing occurs when any of the molecular stimulants increases higher than a predefined threshold (50% of the maximum concentrations), for 1800s of treatment, the cell undergoes necrosis within the first 30 minutes with probability range 90.0%-99.99% and in the case of repair/survival, it goes through apoptosis within 3-4 hours with probability range 90.00%-99.00%. Although, there is no experimental validation of the model at this moment, it reproduces some patterns of survival ratios of predicted experimental data. Analytical modeling based on cell death signaling molecules has been shown to be an independent and useful tool for prediction of cell surviving response to PDT. The model can be adjusted to provide important insights for cellular response to other treatments such as hyperthermia, and diseases such as neurodegeneration.

Translational Control in Bone Marrow Failure

DTIC Science & Technology

2016-07-01

been made in using new tools to model granulopoiesis, including generation of patient-derived iPSC and CRISPR -Cas9 genome-editing technology to...in cell lines in patient-derived iPSC gene models, including using CRISPR genome editing, as overall described in Tidwell et al. 2014 and Nayak et...proxy for neutropenia in this cellular model system. 3h. Use patient-derived iPSC models and CRISPR /Cas9 genome-editing to generate a range of ELANE

A simple 2D biofilm model yields a variety of morphological features.

PubMed

Hermanowicz, S W

2001-01-01

A two-dimensional biofilm model was developed based on the concept of cellular automata. Three simple, generic processes were included in the model: cell growth, internal and external mass transport and cell detachment (erosion). The model generated a diverse range of biofilm morphologies (from dense layers to open, mushroom-like forms) similar to those observed in real biofilm systems. Bulk nutrient concentration and external mass transfer resistance had a large influence on the biofilm structure.

Integrated micro-endoscopy system for simultaneous fluorescence and optical-resolution photoacoustic imaging.

PubMed

Shao, Peng; Shi, Wei; Hajireza, Parsin; Zemp, Roger J

2012-07-01

We present a new integrated micro-endoscopy system combining label-free, fiber-based, real-time C-scan optical-resolution photoacoustic microscopy (F-OR-PAM) and a high-resolution fluorescence micro-endoscopy system for visualizing fluorescently labeled cellular components and optically absorbing microvasculature simultaneously. With a diode-pumped 532-nm fiber laser, the F-OR-PAM sub-system is able to reach a resolution of ∼7  μm. The fluorescence subsystem, which does not require any mechanical scanning, consists of a 447.5-nm-centered diode laser as the light source, an objective lens, and a CCD camera. Proflavine is used as the fluorescent contrast agent by topical application. The scanning laser and the diode laser light source share the same light path within an optical fiber bundle containing 30,000 individual single-mode fibers. The absorption of proflavine at 532 nm is low, which mitigates absorption bleaching of the contrast agent by the photoacoustic excitation source. We demonstrate imaging in live murine models. The system is able to provide cellular morphology with cellular resolution co-registered with the structural information given by F-OR-PAM. Therefore, the system has the potential to serve as a virtual biopsy technique, helping visualize angiogenesis and the effects of anti-cancer drugs on both cells and the microcirculation, as well as aid in the study of other diseases.

Integrated micro-endoscopy system for simultaneous fluorescence and optical-resolution photoacoustic imaging

NASA Astrophysics Data System (ADS)

Shao, Peng; Shi, Wei; Hajireza, Parsin; Zemp, Roger J.

2012-07-01

We present a new integrated micro-endoscopy system combining label-free, fiber-based, real-time C-scan optical-resolution photoacoustic microscopy (F-OR-PAM) and a high-resolution fluorescence micro-endoscopy system for visualizing fluorescently labeled cellular components and optically absorbing microvasculature simultaneously. With a diode-pumped 532-nm fiber laser, the F-OR-PAM sub-system is able to reach a resolution of ~7 μm. The fluorescence subsystem, which does not require any mechanical scanning, consists of a 447.5-nm-centered diode laser as the light source, an objective lens, and a CCD camera. Proflavine is used as the fluorescent contrast agent by topical application. The scanning laser and the diode laser light source share the same light path within an optical fiber bundle containing 30,000 individual single-mode fibers. The absorption of proflavine at 532 nm is low, which mitigates absorption bleaching of the contrast agent by the photoacoustic excitation source. We demonstrate imaging in live murine models. The system is able to provide cellular morphology with cellular resolution co-registered with the structural information given by F-OR-PAM. Therefore, the system has the potential to serve as a virtual biopsy technique, helping visualize angiogenesis and the effects of anti-cancer drugs on both cells and the microcirculation, as well as aid in the study of other diseases.

Modeling molecular mechanisms in the axon

NASA Astrophysics Data System (ADS)

de Rooij, R.; Miller, K. E.; Kuhl, E.

2017-03-01

Axons are living systems that display highly dynamic changes in stiffness, viscosity, and internal stress. However, the mechanistic origin of these phenomenological properties remains elusive. Here we establish a computational mechanics model that interprets cellular-level characteristics as emergent properties from molecular-level events. We create an axon model of discrete microtubules, which are connected to neighboring microtubules via discrete crosslinking mechanisms that obey a set of simple rules. We explore two types of mechanisms: passive and active crosslinking. Our passive and active simulations suggest that the stiffness and viscosity of the axon increase linearly with the crosslink density, and that both are highly sensitive to the crosslink detachment and reattachment times. Our model explains how active crosslinking with dynein motors generates internal stresses and actively drives axon elongation. We anticipate that our model will allow us to probe a wide variety of molecular phenomena—both in isolation and in interaction—to explore emergent cellular-level features under physiological and pathological conditions.

Cellular solidification of transparent monotectics

NASA Technical Reports Server (NTRS)

Kaulker, W. F.

1986-01-01

Understanding how liquid phase particles are engulfed or pushed during freezing of a monotectic is addressed. The additional complication is that the solid-liquid interface is nonplanar due to constitutional undercooling. Some evidence of particle pushing where the particles are the liquid phase of the montectic was already observed. Cellular freezing of the succinonitrile-glycerol system also occurred. Only a few compositions were tested at that time. The starting materials were not especially pure so that cellular interface observed was likely due to the presence of unkown impurities, the major portion of which was water. Topics addressed include: the effort of modeling the particle pushing process using the computer, establishing an apparatus for the determination of phase diagrams, and the measurement of the temperature gradients with a specimen which will solidify on the temperature gradient microscope stage.

Light, heat, action: neural control of fruit fly behaviour

PubMed Central

Owald, David; Lin, Suewei; Waddell, Scott

2015-01-01

The fruit fly Drosophila melanogaster has emerged as a popular model to investigate fundamental principles of neural circuit operation. The sophisticated genetics and small brain permit a cellular resolution understanding of innate and learned behavioural processes. Relatively recent genetic and technical advances provide the means to specifically and reproducibly manipulate the function of many fly neurons with temporal resolution. The same cellular precision can also be exploited to express genetically encoded reporters of neural activity and cell-signalling pathways. Combining these approaches in living behaving animals has great potential to generate a holistic view of behavioural control that transcends the usual molecular, cellular and systems boundaries. In this review, we discuss these approaches with particular emphasis on the pioneering studies and those involving learning and memory. PMID:26240426

DIGE Proteome Analysis Reveals Suitability of Ischemic Cardiac In Vitro Model for Studying Cellular Response to Acute Ischemia and Regeneration

PubMed Central

Haas, Sina; Jahnke, Heinz-Georg; Moerbt, Nora; von Bergen, Martin; Aharinejad, Seyedhossein; Andrukhova, Olena; Robitzki, Andrea A.

2012-01-01

Proteomic analysis of myocardial tissue from patient population is suited to yield insights into cellular and molecular mechanisms taking place in cardiovascular diseases. However, it has been limited by small sized biopsies and complicated by high variances between patients. Therefore, there is a high demand for suitable model systems with the capability to simulate ischemic and cardiotoxic effects in vitro, under defined conditions. In this context, we established an in vitro ischemia/reperfusion cardiac disease model based on the contractile HL-1 cell line. To identify pathways involved in the cellular alterations induced by ischemia and thereby defining disease-specific biomarkers and potential target structures for new drug candidates we used fluorescence 2D-difference gel electrophoresis. By comparing spot density changes in ischemic and reperfusion samples we detected several protein spots that were differentially abundant. Using MALDI-TOF/TOF-MS and ESI-MS the proteins were identified and subsequently grouped by functionality. Most prominent were changes in apoptosis signalling, cell structure and energy-metabolism. Alterations were confirmed by analysis of human biopsies from patients with ischemic cardiomyopathy. With the establishment of our in vitro disease model for ischemia injury target identification via proteomic research becomes independent from rare human material and will create new possibilities in cardiac research. PMID:22384053

Feedback, Mass Conservation and Reaction Kinetics Impact the Robustness of Cellular Oscillations

PubMed Central

Baum, Katharina; Kofahl, Bente; Steuer, Ralf; Wolf, Jana

2016-01-01

Oscillations occur in a wide variety of cellular processes, for example in calcium and p53 signaling responses, in metabolic pathways or within gene-regulatory networks, e.g. the circadian system. Since it is of central importance to understand the influence of perturbations on the dynamics of these systems a number of experimental and theoretical studies have examined their robustness. The period of circadian oscillations has been found to be very robust and to provide reliable timing. For intracellular calcium oscillations the period has been shown to be very sensitive and to allow for frequency-encoded signaling. We here apply a comprehensive computational approach to study the robustness of period and amplitude of oscillatory systems. We employ different prototype oscillator models and a large number of parameter sets obtained by random sampling. This framework is used to examine the effect of three design principles on the sensitivities towards perturbations of the kinetic parameters. We find that a prototype oscillator with negative feedback has lower period sensitivities than a prototype oscillator relying on positive feedback, but on average higher amplitude sensitivities. For both oscillator types, the use of Michaelis-Menten instead of mass action kinetics in all degradation and conversion reactions leads to an increase in period as well as amplitude sensitivities. We observe moderate changes in sensitivities if replacing mass conversion reactions by purely regulatory reactions. These insights are validated for a set of established models of various cellular rhythms. Overall, our work highlights the importance of reaction kinetics and feedback type for the variability of period and amplitude and therefore for the establishment of predictive models. PMID:28027301

Cellular-based modeling of oscillatory dynamics in brain networks.

PubMed

Skinner, Frances K

2012-08-01

Oscillatory, population activities have long been known to occur in our brains during different behavioral states. We know that many different cell types exist and that they contribute in distinct ways to the generation of these activities. I review recent papers that involve cellular-based models of brain networks, most of which include theta, gamma and sharp wave-ripple activities. To help organize the modeling work, I present it from a perspective of three different types of cellular-based modeling: 'Generic', 'Biophysical' and 'Linking'. Cellular-based modeling is taken to encompass the four features of experiment, model development, theory/analyses, and model usage/computation. The three modeling types are shown to include these features and interactions in different ways. Copyright © 2012 Elsevier Ltd. All rights reserved.

UPF1 silenced cellular model systems for screening of read-through agents active on β039 thalassemia point mutation.

PubMed

Salvatori, Francesca; Pappadà, Mariangela; Breveglieri, Giulia; D'Aversa, Elisabetta; Finotti, Alessia; Lampronti, Ilaria; Gambari, Roberto; Borgatti, Monica

2018-05-15

Nonsense mutations promote premature translational termination, introducing stop codons within the coding region of mRNAs and causing inherited diseases, including thalassemia. For instance, in β 0 39 thalassemia the CAG (glutamine) codon is mutated to the UAG stop codon, leading to premature translation termination and to mRNA destabilization through the well described NMD (nonsense-mediated mRNA decay). In order to develop an approach facilitating translation and, therefore, protection from NMD, ribosomal read-through molecules, such as aminoglycoside antibiotics, have been tested on mRNAs carrying premature stop codons. These findings have introduced new hopes for the development of a pharmacological approach to the β 0 39 thalassemia therapy. While several strategies, designed to enhance translational read-through, have been reported to inhibit NMD efficiency concomitantly, experimental tools for systematic analysis of mammalian NMD inhibition by translational read-through are lacking. We developed a human cellular model of the β 0 39 thalassemia mutation with UPF-1 suppressed and showing a partial NMD suppression. This novel cellular model could be used for the screening of molecules exhibiting preferential read-through activity allowing a great rescue of the mutated transcripts.

Membrane-Based Functions in the Origin of Cellular Life

NASA Technical Reports Server (NTRS)

Chipot, Christophe; New, Michael H.; Schweighofer, Karl; Pohorille, Andrew; Wilson, Michael A.

1999-01-01

Our objective is to help explain how the earliest ancestors of contemporary cells (protocells) performed their essential functions employing only the molecules available in the protobiological milieu. Our hypothesis is that vesicles, built of amphiphilic, membrane-forming materials, emerged early in protobiological evolution and served as precursors to protocells. We further assume that the cellular functions associated with contemporary membranes, such as capturing and, transducing of energy, signaling, or sequestering organic molecules and ions, evolved in these membrane environments. An alternative hypothesis is that these functions evolved in different environments and were incorporated into membrane-bound structures at some later stage of evolution. We focus on the application of the fundamental principles of physics and chemistry to determine how they apply to the formation of a primitive, functional cell. Rather than attempting to develop specific models for cellular functions and to identify the origin of the molecules which perform these functions, our goal is to define the structural and energetic conditions that any successful model must fulfill, therefore providing physico-chemical boundaries for these models. We do this by carrying out large-scale, molecular level computer simulations on systems of interest.

Biological adaptive control model: a mechanical analogue of multi-factorial bone density adaptation.

PubMed

Davidson, Peter L; Milburn, Peter D; Wilson, Barry D

2004-03-21

The mechanism of how bone adapts to every day demands needs to be better understood to gain insight into situations in which the musculoskeletal system is perturbed. This paper offers a novel multi-factorial mathematical model of bone density adaptation which combines previous single-factor models in a single adaptation system as a means of gaining this insight. Unique aspects of the model include provision for interaction between factors and an estimation of the relative contribution of each factor. This interacting system is considered analogous to a Newtonian mechanical system and the governing response equation is derived as a linear version of the adaptation process. The transient solution to sudden environmental change is found to be exponential or oscillatory depending on the balance between cellular activation and deactivation frequencies.

Systems Epidemiology: What’s in a Name?

PubMed Central

Dammann, O.; Gray, P.; Gressens, P.; Wolkenhauer, O.; Leviton, A.

2014-01-01

Systems biology is an interdisciplinary effort to integrate molecular, cellular, tissue, organ, and organism levels of function into computational models that facilitate the identification of general principles. Systems medicine adds a disease focus. Systems epidemiology adds yet another level consisting of antecedents that might contribute to the disease process in populations. In etiologic and prevention research, systems-type thinking about multiple levels of causation will allow epidemiologists to identify contributors to disease at multiple levels as well as their interactions. In public health, systems epidemiology will contribute to the improvement of syndromic surveillance methods. We encourage the creation of computational simulation models that integrate information about disease etiology, pathogenetic data, and the expertise of investigators from different disciplines. PMID:25598870

Does Geophysics Need "A new kind of Science"?

NASA Astrophysics Data System (ADS)

Turcotte, D. L.; Rundle, J. B.

2002-12-01

Stephen Wolfram's book "A New Kind of Science" has received a great deal of attention in the last six months, both positive and negative. The theme of the book is that "cellular automata", which arise from spatial and temporal coarse-graining of equations of motion, provide the foundations for a new nonlinear science of "complexity". The old science is the science of partial differential equations. Some of the major contributions of this old science have been in geophysics, i.e. gravity, magnetics, seismic waves, heat flow. The basis of the new science is the use of massive computing and numerical simulations. The new science is motivated by the observations that many physical systems display a vast multiplicity of space and time scales, and have hidden dynamics that in many cases are impossible to directly observe. An example would be molecular dynamics. Statistical physics derives continuum equations from the discrete interactions between atoms and molecules, in the modern world the continuum equations are then discretized using finite differences, finite elements, etc. in order to obtain numerical solutions. Examples of widely used cellular automata models include diffusion limited aggregation and site percolation. Also the class of models that are said to exhibit self-organized criticality, the sand-pile model, the slider-block model, the forest-fire model. Applications of these models include drainage networks, seismicity, distributions of minerals,and the evolution of landforms and coastlines. Simple cellular automata models generate deterministic chaos, i.e. the logistic map.

Agent-based modeling of endotoxin-induced acute inflammatory response in human blood leukocytes.

PubMed

Dong, Xu; Foteinou, Panagiota T; Calvano, Steven E; Lowry, Stephen F; Androulakis, Ioannis P

2010-02-18

Inflammation is a highly complex biological response evoked by many stimuli. A persistent challenge in modeling this dynamic process has been the (nonlinear) nature of the response that precludes the single-variable assumption. Systems-based approaches offer a promising possibility for understanding inflammation in its homeostatic context. In order to study the underlying complexity of the acute inflammatory response, an agent-based framework is developed that models the emerging host response as the outcome of orchestrated interactions associated with intricate signaling cascades and intercellular immune system interactions. An agent-based modeling (ABM) framework is proposed to study the nonlinear dynamics of acute human inflammation. The model is implemented using NetLogo software. Interacting agents involve either inflammation-specific molecules or cells essential for the propagation of the inflammatory reaction across the system. Spatial orientation of molecule interactions involved in signaling cascades coupled with the cellular heterogeneity are further taken into account. The proposed in silico model is evaluated through its ability to successfully reproduce a self-limited inflammatory response as well as a series of scenarios indicative of the nonlinear dynamics of the response. Such scenarios involve either a persistent (non)infectious response or innate immune tolerance and potentiation effects followed by perturbations in intracellular signaling molecules and cascades. The ABM framework developed in this study provides insight on the stochastic interactions of the mediators involved in the propagation of endotoxin signaling at the cellular response level. The simulation results are in accordance with our prior research effort associated with the development of deterministic human inflammation models that include transcriptional dynamics, signaling, and physiological components. The hypothetical scenarios explored in this study would potentially improve our understanding of how manipulating the behavior of the molecular species could manifest into emergent behavior of the overall system.

Hybrid ODE/SSA methods and the cell cycle model

NASA Astrophysics Data System (ADS)

Wang, S.; Chen, M.; Cao, Y.

2017-07-01

Stochastic effect in cellular systems has been an important topic in systems biology. Stochastic modeling and simulation methods are important tools to study stochastic effect. Given the low efficiency of stochastic simulation algorithms, the hybrid method, which combines an ordinary differential equation (ODE) system with a stochastic chemically reacting system, shows its unique advantages in the modeling and simulation of biochemical systems. The efficiency of hybrid method is usually limited by reactions in the stochastic subsystem, which are modeled and simulated using Gillespie's framework and frequently interrupt the integration of the ODE subsystem. In this paper we develop an efficient implementation approach for the hybrid method coupled with traditional ODE solvers. We also compare the efficiency of hybrid methods with three widely used ODE solvers RADAU5, DASSL, and DLSODAR. Numerical experiments with three biochemical models are presented. A detailed discussion is presented for the performances of three ODE solvers.

Simulating complex intracellular processes using object-oriented computational modelling.

PubMed

Johnson, Colin G; Goldman, Jacki P; Gullick, William J

2004-11-01

The aim of this paper is to give an overview of computer modelling and simulation in cellular biology, in particular as applied to complex biochemical processes within the cell. This is illustrated by the use of the techniques of object-oriented modelling, where the computer is used to construct abstractions of objects in the domain being modelled, and these objects then interact within the computer to simulate the system and allow emergent properties to be observed. The paper also discusses the role of computer simulation in understanding complexity in biological systems, and the kinds of information which can be obtained about biology via simulation.

A Model of How Different Biology Experts Explain Molecular and Cellular Mechanisms

ERIC Educational Resources Information Center

Trujillo, Caleb M.; Anderson, Trevor R.; Pelaez, Nancy J.

2015-01-01

Constructing explanations is an essential skill for all science learners. The goal of this project was to model the key components of expert explanation of molecular and cellular mechanisms. As such, we asked: What is an appropriate model of the components of explanation used by biology experts to explain molecular and cellular mechanisms? Do…

An Evaluation of the Efficacy of a Laboratory Exercise on Cellular Respiration

ERIC Educational Resources Information Center

Scholer, Anne-Marie; Hatton, Mary

2008-01-01

This study is an analysis of the effectiveness of a faculty-designed laboratory experience about a difficult topic, cellular respiration. The activity involves a hands-on model of the cellular-respiration process, making use of wooden ball-and-stick chemistry models and small toy trucks on a table top model of the mitochondrion. Students…

Yeast: An Experimental Organism for Modern Biology.

ERIC Educational Resources Information Center

Botstein, David; Fink, Gerald R.

1988-01-01

Discusses the applicability and advantages of using yeasts as popular and ideal model systems for studying and understanding eukaryotic biology at the cellular and molecular levels. Cites experimental tractability and the cooperative tradition of the research community of yeast biologists as reasons for this success. (RT)

Space biosynthesis systems

NASA Technical Reports Server (NTRS)

Nyiri, L. K.; Toth, G. M.

1976-01-01

Model reactions based on chemical, enzymatic or cellular conversion of D glucose into d gluconic acid are designed to unequivocally define the advantages of microgravity on reaction mechanisms, mass-transfers and separation of organic chemicals and to serve as procedures to test the performance characteristics of space bioprocessing equipment.

Measurements and modelling of base station power consumption under real traffic loads.

PubMed

Lorincz, Josip; Garma, Tonko; Petrovic, Goran

2012-01-01

Base stations represent the main contributor to the energy consumption of a mobile cellular network. Since traffic load in mobile networks significantly varies during a working or weekend day, it is important to quantify the influence of these variations on the base station power consumption. Therefore, this paper investigates changes in the instantaneous power consumption of GSM (Global System for Mobile Communications) and UMTS (Universal Mobile Telecommunications System) base stations according to their respective traffic load. The real data in terms of the power consumption and traffic load have been obtained from continuous measurements performed on a fully operated base station site. Measurements show the existence of a direct relationship between base station traffic load and power consumption. According to this relationship, we develop a linear power consumption model for base stations of both technologies. This paper also gives an overview of the most important concepts which are being proposed to make cellular networks more energy-efficient.

Naringenin is a novel inhibitor of Dictyostelium cell proliferation and cell migration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Russ, Misty; Martinez, Raquel; Ali, Hind

2006-06-23

Naringenin is a flavanone compound that alters critical cellular processes such as cell multiplication, glucose uptake, and mitochondrial activity. In this study, we used the social amoeba, Dictyostelium discoideum, as a model system for examining the cellular processes and signaling pathways affected by naringenin. We found that naringenin inhibited Dictyostelium cell division in a dose-dependent manner (IC{sub 5} {approx} 20 {mu}M). Assays of Dictyostelium chemotaxis and multicellular development revealed that naringenin possesses a previously unrecognized ability to suppress amoeboid cell motility. We also found that naringenin, which is known to inhibit phosphatidylinositol 3-kinase activity, had no apparent effect on phosphatidylinositolmore » 3,4,5-trisphosphate synthesis in live Dictyostelium cells; suggesting that this compound suppresses cell growth and migration via alternative signaling pathways. In another context, the discoveries described here highlight the value of using the Dictyostelium model system for identifying and characterizing the mechanisms by which naringenin, and related compounds, exert their effects on eukaryotic cells.« less

Computer simulation of a cellular automata model for the immune response in a retrovirus system

NASA Astrophysics Data System (ADS)

Pandey, R. B.

1989-02-01

Immune response in a retrovirus system is modeled by a network of three binary cell elements to take into account some of the main functional features of T4 cells, T8 cells, and viruses. Two different intercell interactions are introduced, one of which leads to three fixed points while the other yields bistable fixed points oscillating between a healthy state and a sick state in a mean field treatment. Evolution of these cells is studied for quenched and annealed random interactions on a simple cubic lattice with a nearest neighbor interaction using inhomogenous cellular automata. Populations of T4 cells and viral cells oscillate together with damping (with constant amplitude) for annealed (quenched) interaction on increasing the value of mixing probability B from zero to a characteristic value B ca ( B cq). For higher B, the average number of T4 cells increases while that of the viral infected cells decreases monotonically on increasing B, suggesting a phase transition at B ca ( B cq).

Measurements and Modelling of Base Station Power Consumption under Real Traffic Loads †

PubMed Central

Lorincz, Josip; Garma, Tonko; Petrovic, Goran

2012-01-01

Base stations represent the main contributor to the energy consumption of a mobile cellular network. Since traffic load in mobile networks significantly varies during a working or weekend day, it is important to quantify the influence of these variations on the base station power consumption. Therefore, this paper investigates changes in the instantaneous power consumption of GSM (Global System for Mobile Communications) and UMTS (Universal Mobile Telecommunications System) base stations according to their respective traffic load. The real data in terms of the power consumption and traffic load have been obtained from continuous measurements performed on a fully operated base station site. Measurements show the existence of a direct relationship between base station traffic load and power consumption. According to this relationship, we develop a linear power consumption model for base stations of both technologies. This paper also gives an overview of the most important concepts which are being proposed to make cellular networks more energy-efficient. PMID:22666026

Cellerator: extending a computer algebra system to include biochemical arrows for signal transduction simulations

NASA Technical Reports Server (NTRS)

Shapiro, Bruce E.; Levchenko, Andre; Meyerowitz, Elliot M.; Wold, Barbara J.; Mjolsness, Eric D.

2003-01-01

Cellerator describes single and multi-cellular signal transduction networks (STN) with a compact, optionally palette-driven, arrow-based notation to represent biochemical reactions and transcriptional activation. Multi-compartment systems are represented as graphs with STNs embedded in each node. Interactions include mass-action, enzymatic, allosteric and connectionist models. Reactions are translated into differential equations and can be solved numerically to generate predictive time courses or output as systems of equations that can be read by other programs. Cellerator simulations are fully extensible and portable to any operating system that supports Mathematica, and can be indefinitely nested within larger data structures to produce highly scaleable models.

The role of the interaction network in the emergence of diversity of behavior

PubMed Central

Tabacof, Pedro; Von Zuben, Fernando J.

2017-01-01

How can systems in which individuals’ inner workings are very similar to each other, as neural networks or ant colonies, produce so many qualitatively different behaviors, giving rise to roles and specialization? In this work, we bring new perspectives to this question by focusing on the underlying network that defines how individuals in these systems interact. We applied a genetic algorithm to optimize rules and connections of cellular automata in order to solve the density classification task, a classical problem used to study emergent behaviors in decentralized computational systems. The networks used were all generated by the introduction of shortcuts in an originally regular topology, following the small-world model. Even though all cells follow the exact same rules, we observed the existence of different classes of cells’ behaviors in the best cellular automata found—most cells were responsible for memory and others for integration of information. Through the analysis of structural measures and patterns of connections (motifs) in successful cellular automata, we observed that the distribution of shortcuts between distant regions and the speed in which a cell can gather information from different parts of the system seem to be the main factors for the specialization we observed, demonstrating how heterogeneity in a network can create heterogeneity of behavior. PMID:28234962

Cellular senescence in the Penna model of aging

NASA Astrophysics Data System (ADS)

Periwal, Avikar

2013-11-01

Cellular senescence is thought to play a major role in age-related diseases, which cause nearly 67% of all human deaths worldwide. Recent research in mice showed that exercising mice had higher levels of telomerase, an enzyme that helps maintain telomere length, than nonexercising mice. A commonly used model for biological aging was proposed by Penna. I propose a modification of the Penna model that incorporates cellular senescence and find an analytical steady-state solution following Coe, Mao, and Cates [Phys. Rev. Lett.PRLTAO0031-900710.1103/PhysRevLett.89.288103 89, 288103 (2002)]. I find that models corresponding to delayed cellular senescence have younger populations that live longer. I fit the model to the United Kingdom's death distribution, which the original Penna model cannot do.

Perturbation Biology: Inferring Signaling Networks in Cellular Systems

PubMed Central

Miller, Martin L.; Gauthier, Nicholas P.; Jing, Xiaohong; Kaushik, Poorvi; He, Qin; Mills, Gordon; Solit, David B.; Pratilas, Christine A.; Weigt, Martin; Braunstein, Alfredo; Pagnani, Andrea; Zecchina, Riccardo; Sander, Chris

2013-01-01

We present a powerful experimental-computational technology for inferring network models that predict the response of cells to perturbations, and that may be useful in the design of combinatorial therapy against cancer. The experiments are systematic series of perturbations of cancer cell lines by targeted drugs, singly or in combination. The response to perturbation is quantified in terms of relative changes in the measured levels of proteins, phospho-proteins and cellular phenotypes such as viability. Computational network models are derived de novo, i.e., without prior knowledge of signaling pathways, and are based on simple non-linear differential equations. The prohibitively large solution space of all possible network models is explored efficiently using a probabilistic algorithm, Belief Propagation (BP), which is three orders of magnitude faster than standard Monte Carlo methods. Explicit executable models are derived for a set of perturbation experiments in SKMEL-133 melanoma cell lines, which are resistant to the therapeutically important inhibitor of RAF kinase. The resulting network models reproduce and extend known pathway biology. They empower potential discoveries of new molecular interactions and predict efficacious novel drug perturbations, such as the inhibition of PLK1, which is verified experimentally. This technology is suitable for application to larger systems in diverse areas of molecular biology. PMID:24367245

Modeling the Population Dynamics of Antibiotic-Resistant Bacteria:. AN Agent-Based Approach

NASA Astrophysics Data System (ADS)

Murphy, James T.; Walshe, Ray; Devocelle, Marc

The response of bacterial populations to antibiotic treatment is often a function of a diverse range of interacting factors. In order to develop strategies to minimize the spread of antibiotic resistance in pathogenic bacteria, a sound theoretical understanding of the systems of interactions taking place within a colony must be developed. The agent-based approach to modeling bacterial populations is a useful tool for relating data obtained at the molecular and cellular level with the overall population dynamics. Here we demonstrate an agent-based model, called Micro-Gen, which has been developed to simulate the growth and development of bacterial colonies in culture. The model also incorporates biochemical rules and parameters describing the kinetic interactions of bacterial cells with antibiotic molecules. Simulations were carried out to replicate the development of methicillin-resistant S. aureus (MRSA) colonies growing in the presence of antibiotics. The model was explored to see how the properties of the system emerge from the interactions of the individual bacterial agents in order to achieve a better mechanistic understanding of the population dynamics taking place. Micro-Gen provides a good theoretical framework for investigating the effects of local environmental conditions and cellular properties on the response of bacterial populations to antibiotic exposure in the context of a simulated environment.

A Stochastic Model of the Yeast Cell Cycle Reveals Roles for Feedback Regulation in Limiting Cellular Variability.

PubMed

Barik, Debashis; Ball, David A; Peccoud, Jean; Tyson, John J

2016-12-01

The cell division cycle of eukaryotes is governed by a complex network of cyclin-dependent protein kinases (CDKs) and auxiliary proteins that govern CDK activities. The control system must function reliably in the context of molecular noise that is inevitable in tiny yeast cells, because mistakes in sequencing cell cycle events are detrimental or fatal to the cell or its progeny. To assess the effects of noise on cell cycle progression requires not only extensive, quantitative, experimental measurements of cellular heterogeneity but also comprehensive, accurate, mathematical models of stochastic fluctuations in the CDK control system. In this paper we provide a stochastic model of the budding yeast cell cycle that accurately accounts for the variable phenotypes of wild-type cells and more than 20 mutant yeast strains simulated in different growth conditions. We specifically tested the role of feedback regulations mediated by G1- and SG2M-phase cyclins to minimize the noise in cell cycle progression. Details of the model are informed and tested by quantitative measurements (by fluorescence in situ hybridization) of the joint distributions of mRNA populations in yeast cells. We use the model to predict the phenotypes of ~30 mutant yeast strains that have not yet been characterized experimentally.

A Stochastic Model of the Yeast Cell Cycle Reveals Roles for Feedback Regulation in Limiting Cellular Variability

PubMed Central

Ball, David A.

2016-01-01

The cell division cycle of eukaryotes is governed by a complex network of cyclin-dependent protein kinases (CDKs) and auxiliary proteins that govern CDK activities. The control system must function reliably in the context of molecular noise that is inevitable in tiny yeast cells, because mistakes in sequencing cell cycle events are detrimental or fatal to the cell or its progeny. To assess the effects of noise on cell cycle progression requires not only extensive, quantitative, experimental measurements of cellular heterogeneity but also comprehensive, accurate, mathematical models of stochastic fluctuations in the CDK control system. In this paper we provide a stochastic model of the budding yeast cell cycle that accurately accounts for the variable phenotypes of wild-type cells and more than 20 mutant yeast strains simulated in different growth conditions. We specifically tested the role of feedback regulations mediated by G1- and SG2M-phase cyclins to minimize the noise in cell cycle progression. Details of the model are informed and tested by quantitative measurements (by fluorescence in situ hybridization) of the joint distributions of mRNA populations in yeast cells. We use the model to predict the phenotypes of ~30 mutant yeast strains that have not yet been characterized experimentally. PMID:27935947

Senescent intervertebral disc cells exhibit perturbed matrix homeostasis phenotype.

PubMed

Ngo, Kevin; Patil, Prashanti; McGowan, Sara J; Niedernhofer, Laura J; Robbins, Paul D; Kang, James; Sowa, Gwendolyn; Vo, Nam

2017-09-01

Aging greatly increases the risk for intervertebral disc degeneration (IDD) as a result of proteoglycan loss due to reduced synthesis and enhanced degradation of the disc matrix proteoglycan (PG). How disc matrix PG homeostasis becomes perturbed with age is not known. The goal of this study is to determine whether cellular senescence is a source of this perturbation. We demonstrated that disc cellular senescence is dramatically increased in the DNA repair-deficient Ercc1 -/Δ mouse model of human progeria. In these accelerated aging mice, increased disc cellular senescence is closely associated with the rapid loss of disc PG. We also directly examine PG homeostasis in oxidative damage-induced senescent human cells using an in vitro cell culture model system. Senescence of human disc cells treated with hydrogen peroxide was confirmed by growth arrest, senescence-associated β-galactosidase activity, γH2AX foci, and acquisition of senescence-associated secretory phenotype. Senescent human disc cells also exhibited perturbed matrix PG homeostasis as evidenced by their decreased capacity to synthesize new matrix PG and enhanced degradation of aggrecan, a major matrix PG. of the disc. Our in vivo and in vitro findings altogether suggest that disc cellular senescence is an important driver of PG matrix homeostatic perturbation and PG loss. Published by Elsevier B.V.

Towards self-correcting quantum memories

NASA Astrophysics Data System (ADS)

Michnicki, Kamil

This thesis presents a model of self-correcting quantum memories where quantum states are encoded using topological stabilizer codes and error correction is done using local measurements and local dynamics. Quantum noise poses a practical barrier to developing quantum memories. This thesis explores two types of models for suppressing noise. One model suppresses thermalizing noise energetically by engineering a Hamiltonian with a high energy barrier between code states. Thermalizing dynamics are modeled phenomenologically as a Markovian quantum master equation with only local generators. The second model suppresses stochastic noise with a cellular automaton that performs error correction using syndrome measurements and a local update rule. Several ways of visualizing and thinking about stabilizer codes are presented in order to design ones that have a high energy barrier: the non-local Ising model, the quasi-particle graph and the theory of welded stabilizer codes. I develop the theory of welded stabilizer codes and use it to construct a code with the highest known energy barrier in 3-d for spin Hamiltonians: the welded solid code. Although the welded solid code is not fully self correcting, it has some self correcting properties. It has an increased memory lifetime for an increased system size up to a temperature dependent maximum. One strategy for increasing the energy barrier is by mediating an interaction with an external system. I prove a no-go theorem for a class of Hamiltonians where the interaction terms are local, of bounded strength and commute with the stabilizer group. Under these conditions the energy barrier can only be increased by a multiplicative constant. I develop cellular automaton to do error correction on a state encoded using the toric code. The numerical evidence indicates that while there is no threshold, the model can extend the memory lifetime significantly. While of less theoretical importance, this could be practical for real implementations of quantum memories. Numerical evidence also suggests that the cellular automaton could function as a decoder with a soft threshold.

Generic framework for mining cellular automata models on protein-folding simulations.

PubMed

Diaz, N; Tischer, I

2016-05-13

Cellular automata model identification is an important way of building simplified simulation models. In this study, we describe a generic architectural framework to ease the development process of new metaheuristic-based algorithms for cellular automata model identification in protein-folding trajectories. Our framework was developed by a methodology based on design patterns that allow an improved experience for new algorithms development. The usefulness of the proposed framework is demonstrated by the implementation of four algorithms, able to obtain extremely precise cellular automata models of the protein-folding process with a protein contact map representation. Dynamic rules obtained by the proposed approach are discussed, and future use for the new tool is outlined.

The elasticity and failure of fluid-filled cellular solids: Theory and experiment

NASA Astrophysics Data System (ADS)

Warner, M.; Thiel, B. L.; Donald, A. M.

2000-02-01

We extend and apply theories of filled foam elasticity and failure to recently available data on foods. The predictions of elastic modulus and failure mode dependence on internal pressure and on wall integrity are borne out by photographic evidence of distortion and failure under compressive loading and under the localized stress applied by a knife blade, and by mechanical data on vegetables differing only in their turgor pressure. We calculate the dry modulus of plate-like cellular solids and the cross over between dry-like and fully fluid-filled elastic response. The bulk elastic properties of limp and aging cellular solids are calculated for model systems and compared with our mechanical data, which also show two regimes of response. The mechanics of an aged, limp beam is calculated, thus offering a practical procedure for comparing experiment and theory. This investigation also thereby offers explanations of the connection between turgor pressure and crispness and limpness of cellular materials.

The elasticity and failure of fluid-filled cellular solids: theory and experiment.

PubMed

Warner, M; Thiel, B L; Donald, A M

2000-02-15

We extend and apply theories of filled foam elasticity and failure to recently available data on foods. The predictions of elastic modulus and failure mode dependence on internal pressure and on wall integrity are borne out by photographic evidence of distortion and failure under compressive loading and under the localized stress applied by a knife blade, and by mechanical data on vegetables differing only in their turgor pressure. We calculate the dry modulus of plate-like cellular solids and the cross over between dry-like and fully fluid-filled elastic response. The bulk elastic properties of limp and aging cellular solids are calculated for model systems and compared with our mechanical data, which also show two regimes of response. The mechanics of an aged, limp beam is calculated, thus offering a practical procedure for comparing experiment and theory. This investigation also thereby offers explanations of the connection between turgor pressure and crispness and limpness of cellular materials.

The elasticity and failure of fluid-filled cellular solids: Theory and experiment

PubMed Central

Warner, M.; Thiel, B. L.; Donald, A. M.

2000-01-01

We extend and apply theories of filled foam elasticity and failure to recently available data on foods. The predictions of elastic modulus and failure mode dependence on internal pressure and on wall integrity are borne out by photographic evidence of distortion and failure under compressive loading and under the localized stress applied by a knife blade, and by mechanical data on vegetables differing only in their turgor pressure. We calculate the dry modulus of plate-like cellular solids and the cross over between dry-like and fully fluid-filled elastic response. The bulk elastic properties of limp and aging cellular solids are calculated for model systems and compared with our mechanical data, which also show two regimes of response. The mechanics of an aged, limp beam is calculated, thus offering a practical procedure for comparing experiment and theory. This investigation also thereby offers explanations of the connection between turgor pressure and crispness and limpness of cellular materials. PMID:10660680

Agent-based modeling of the interaction between CD8+ T cells and Beta cells in type 1 diabetes.

PubMed

Ozturk, Mustafa Cagdas; Xu, Qian; Cinar, Ali

2018-01-01

We propose an agent-based model for the simulation of the autoimmune response in T1D. The model incorporates cell behavior from various rules derived from the current literature and is implemented on a high-performance computing system, which enables the simulation of a significant portion of the islets in the mouse pancreas. Simulation results indicate that the model is able to capture the trends that emerge during the progression of the autoimmunity. The multi-scale nature of the model enables definition of rules or equations that govern cellular or sub-cellular level phenomena and observation of the outcomes at the tissue scale. It is expected that such a model would facilitate in vivo clinical studies through rapid testing of hypotheses and planning of future experiments by providing insight into disease progression at different scales, some of which may not be obtained easily in clinical studies. Furthermore, the modular structure of the model simplifies tasks such as the addition of new cell types, and the definition or modification of different behaviors of the environment and the cells with ease.

Murine Electrophysiological Models of Cardiac Arrhythmogenesis

PubMed Central

2016-01-01

Cardiac arrhythmias can follow disruption of the normal cellular electrophysiological processes underlying excitable activity and their tissue propagation as coherent wavefronts from the primary sinoatrial node pacemaker, through the atria, conducting structures and ventricular myocardium. These physiological events are driven by interacting, voltage-dependent, processes of activation, inactivation, and recovery in the ion channels present in cardiomyocyte membranes. Generation and conduction of these events are further modulated by intracellular Ca2+ homeostasis, and metabolic and structural change. This review describes experimental studies on murine models for known clinical arrhythmic conditions in which these mechanisms were modified by genetic, physiological, or pharmacological manipulation. These exemplars yielded molecular, physiological, and structural phenotypes often directly translatable to their corresponding clinical conditions, which could be investigated at the molecular, cellular, tissue, organ, and whole animal levels. Arrhythmogenesis could be explored during normal pacing activity, regular stimulation, following imposed extra-stimuli, or during progressively incremented steady pacing frequencies. Arrhythmic substrate was identified with temporal and spatial functional heterogeneities predisposing to reentrant excitation phenomena. These could arise from abnormalities in cardiac pacing function, tissue electrical connectivity, and cellular excitation and recovery. Triggering events during or following recovery from action potential excitation could thereby lead to sustained arrhythmia. These surface membrane processes were modified by alterations in cellular Ca2+ homeostasis and energetics, as well as cellular and tissue structural change. Study of murine systems thus offers major insights into both our understanding of normal cardiac activity and its propagation, and their relationship to mechanisms generating clinical arrhythmias. PMID:27974512

Physical biology of human brain development.

PubMed

Budday, Silvia; Steinmann, Paul; Kuhl, Ellen

2015-01-01

Neurodevelopment is a complex, dynamic process that involves a precisely orchestrated sequence of genetic, environmental, biochemical, and physical events. Developmental biology and genetics have shaped our understanding of the molecular and cellular mechanisms during neurodevelopment. Recent studies suggest that physical forces play a central role in translating these cellular mechanisms into the complex surface morphology of the human brain. However, the precise impact of neuronal differentiation, migration, and connection on the physical forces during cortical folding remains unknown. Here we review the cellular mechanisms of neurodevelopment with a view toward surface morphogenesis, pattern selection, and evolution of shape. We revisit cortical folding as the instability problem of constrained differential growth in a multi-layered system. To identify the contributing factors of differential growth, we map out the timeline of neurodevelopment in humans and highlight the cellular events associated with extreme radial and tangential expansion. We demonstrate how computational modeling of differential growth can bridge the scales-from phenomena on the cellular level toward form and function on the organ level-to make quantitative, personalized predictions. Physics-based models can quantify cortical stresses, identify critical folding conditions, rationalize pattern selection, and predict gyral wavelengths and gyrification indices. We illustrate that physical forces can explain cortical malformations as emergent properties of developmental disorders. Combining biology and physics holds promise to advance our understanding of human brain development and enable early diagnostics of cortical malformations with the ultimate goal to improve treatment of neurodevelopmental disorders including epilepsy, autism spectrum disorders, and schizophrenia.

Development of in-vitro models to elucidate mechanisms of intrinsic cellular and tissue fluorescence

NASA Astrophysics Data System (ADS)

Savage, Howard E.; Kolli, Venkateswara; Saha, Sanjoy; Zhang, Jian C.; Glasgold, Mark; Sacks, Peter G.; Alfano, Robert R.; Schantz, Stimson P.

1995-04-01

In vitro cell model systems have been used to study the mechanisms of intrinsic cellular and tissue fluorescence as a potential biomarker for cancer. Phenotypic characteristics of cancer that are different from normal tissue include changes in histoarchitecture, proliferation rates and differentiation. a nitrosmethlybenzylamine (NMBA)/rat esophageal carcinogenesis model (NMBA), a transforming growth factor beta (TGF- (beta) )/normal epithelial cell model, and a retinoic acid (RA)/multicellular tumor spheroid model (RAMTS) were used to assess fluorescence changes associated respectively with changes in histoarchitecture, proliferation rates and differentiation. A xenon based fluorescence spectrophotometer (Mediscience Corp.) was used to collect excitation and emission spectra. Two excitation scans ((lambda) Ex 200-360 nm, (lambda) Em 380 nm; (lambda) Ex 240-430 nm, (lambda) Em 450 nm) and two emission scans ((lambda) Ex 300 nm, (lambda) Em 320-580 nm; (lambda) Ex 340 nm, (lambda) Em 360-660 nm) were used to analyze the three model systems. Using the NMBA model. Differences were seen in the excitation scan ((lambda) Ex 200-360 nm, (lambda) Em 380 nm) and the emission scan ((lambda) Ex 340 nm, (lambda) Em 360-660 nm) when normal rat esophageal tissue was compared to hyperplastic and tumor tissue. In the (TGF-(beta) ) model, differences were seen in the excitation scan ((lambda) Ex 240-430 nm, (lambda) Em 450 nm) when comparing proliferation slowed (TGF-(beta) treated) epithelial cells to their untreated controls. In the RAMTS model, differences were seen with all four scans when RA treated multicellular tumor spheroids (nondifferentiating) were compared to untreated control cells (differentiating). The data indicate that fluorescence changes seen in these model systems may relate to changes in histoarchitecture, proliferation rates and differentiation. Their relationship to in vivo fluorescence changes seen in cancer patients remains to be elucidated.

Light on fluorescent lipids in rafts: a lesson from model membranes.

PubMed

Kahya, Nicoletta

2010-09-15

Tracking fluorescent lipids in cellular membranes has been applied for decades to shed light on membrane trafficking, sorting, endocytosis and exocytosis, viral entry, and to understand the functional relevance of membrane heterogeneity, phase separation and lipid rafts. However, fluorescent probes may display different organizing behaviour from their corresponding endogenous lipids. A full characterization of these probes is therefore required for proper interpretation of fluorescence microscopy data in complex membrane systems. Model membrane studies provide essential clues that guide us to design and interpret our experiments, help us to avoid pitfalls and resolve artefacts in complex cellular environments. In the present issue of the Biochemical Journal, Juhasz, Davis and Sharom demonstrate the importance of testing lipid probes systematically in heterogeneous model membranes of specific composition and well-defined thermodynamic properties. The phase-partitioning behaviour of fluorescent probes, alone and/or in combination, cannot simply be assumed, but has to be fully characterized.

Analyzing Single-Molecule Protein Transportation Experiments via Hierarchical Hidden Markov Models

PubMed Central

Chen, Yang; Shen, Kuang

2017-01-01

To maintain proper cellular functions, over 50% of proteins encoded in the genome need to be transported to cellular membranes. The molecular mechanism behind such a process, often referred to as protein targeting, is not well understood. Single-molecule experiments are designed to unveil the detailed mechanisms and reveal the functions of different molecular machineries involved in the process. The experimental data consist of hundreds of stochastic time traces from the fluorescence recordings of the experimental system. We introduce a Bayesian hierarchical model on top of hidden Markov models (HMMs) to analyze these data and use the statistical results to answer the biological questions. In addition to resolving the biological puzzles and delineating the regulating roles of different molecular complexes, our statistical results enable us to propose a more detailed mechanism for the late stages of the protein targeting process. PMID:28943680

Invited review article: Advanced light microscopy for biological space research.

PubMed

De Vos, Winnok H; Beghuin, Didier; Schwarz, Christian J; Jones, David B; van Loon, Jack J W A; Bereiter-Hahn, Juergen; Stelzer, Ernst H K

2014-10-01

As commercial space flights have become feasible and long-term extraterrestrial missions are planned, it is imperative that the impact of space travel and the space environment on human physiology be thoroughly characterized. Scrutinizing the effects of potentially detrimental factors such as ionizing radiation and microgravity at the cellular and tissue level demands adequate visualization technology. Advanced light microscopy (ALM) is the leading tool for non-destructive structural and functional investigation of static as well as dynamic biological systems. In recent years, technological developments and advances in photochemistry and genetic engineering have boosted all aspects of resolution, readout and throughput, rendering ALM ideally suited for biological space research. While various microscopy-based studies have addressed cellular response to space-related environmental stressors, biological endpoints have typically been determined only after the mission, leaving an experimental gap that is prone to bias results. An on-board, real-time microscopical monitoring device can bridge this gap. Breadboards and even fully operational microscope setups have been conceived, but they need to be rendered more compact and versatile. Most importantly, they must allow addressing the impact of gravity, or the lack thereof, on physiologically relevant biological systems in space and in ground-based simulations. In order to delineate the essential functionalities for such a system, we have reviewed the pending questions in space science, the relevant biological model systems, and the state-of-the art in ALM. Based on a rigorous trade-off, in which we recognize the relevance of multi-cellular systems and the cellular microenvironment, we propose a compact, but flexible concept for space-related cell biological research that is based on light sheet microscopy.

Invited Review Article: Advanced light microscopy for biological space research

NASA Astrophysics Data System (ADS)

De Vos, Winnok H.; Beghuin, Didier; Schwarz, Christian J.; Jones, David B.; van Loon, Jack J. W. A.; Bereiter-Hahn, Juergen; Stelzer, Ernst H. K.

2014-10-01

As commercial space flights have become feasible and long-term extraterrestrial missions are planned, it is imperative that the impact of space travel and the space environment on human physiology be thoroughly characterized. Scrutinizing the effects of potentially detrimental factors such as ionizing radiation and microgravity at the cellular and tissue level demands adequate visualization technology. Advanced light microscopy (ALM) is the leading tool for non-destructive structural and functional investigation of static as well as dynamic biological systems. In recent years, technological developments and advances in photochemistry and genetic engineering have boosted all aspects of resolution, readout and throughput, rendering ALM ideally suited for biological space research. While various microscopy-based studies have addressed cellular response to space-related environmental stressors, biological endpoints have typically been determined only after the mission, leaving an experimental gap that is prone to bias results. An on-board, real-time microscopical monitoring device can bridge this gap. Breadboards and even fully operational microscope setups have been conceived, but they need to be rendered more compact and versatile. Most importantly, they must allow addressing the impact of gravity, or the lack thereof, on physiologically relevant biological systems in space and in ground-based simulations. In order to delineate the essential functionalities for such a system, we have reviewed the pending questions in space science, the relevant biological model systems, and the state-of-the art in ALM. Based on a rigorous trade-off, in which we recognize the relevance of multi-cellular systems and the cellular microenvironment, we propose a compact, but flexible concept for space-related cell biological research that is based on light sheet microscopy.

Cellular, molecular, and epigenetic mechanisms in non-associative conditioning: implications for pain and memory.

PubMed

Rahn, Elizabeth J; Guzman-Karlsson, Mikael C; David Sweatt, J

2013-10-01

Sensitization is a form of non-associative conditioning in which amplification of behavioral responses can occur following presentation of an aversive or noxious stimulus. Understanding the cellular and molecular underpinnings of sensitization has been an overarching theme spanning the field of learning and memory as well as that of pain research. In this review we examine how sensitization, both in the context of learning as well as pain processing, shares evolutionarily conserved behavioral, cellular/synaptic, and epigenetic mechanisms across phyla. First, we characterize the behavioral phenomenon of sensitization both in invertebrates and vertebrates. Particular emphasis is placed on long-term sensitization (LTS) of withdrawal reflexes in Aplysia following aversive stimulation or injury, although additional invertebrate models are also covered. In the context of vertebrates, sensitization of mammalian hyperarousal in a model of post-traumatic stress disorder (PTSD), as well as mammalian models of inflammatory and neuropathic pain is characterized. Second, we investigate the cellular and synaptic mechanisms underlying these behaviors. We focus our discussion on serotonin-mediated long-term facilitation (LTF) and axotomy-mediated long-term hyperexcitability (LTH) in reduced Aplysia systems, as well as mammalian spinal plasticity mechanisms of central sensitization. Third, we explore recent evidence implicating epigenetic mechanisms in learning- and pain-related sensitization. This review illustrates the fundamental and functional overlay of the learning and memory field with the pain field which argues for homologous persistent plasticity mechanisms in response to sensitizing stimuli or injury across phyla. Copyright © 2013 Elsevier Inc. All rights reserved.

Mouse Models for Studying Oral Cancer: Impact in the Era of Cancer Immunotherapy.

PubMed

Luo, J J; Young, C D; Zhou, H M; Wang, X J

2018-04-01

Model systems for oral cancer research have progressed from tumor epithelial cell cultures to in vivo systems that mimic oral cancer genetics, pathological characteristics, and tumor-stroma interactions of oral cancer patients. In the era of cancer immunotherapy, it is imperative to use model systems to test oral cancer prevention and therapeutic interventions in the presence of an immune system and to discover mechanisms of stromal contributions to oral cancer carcinogenesis. Here, we review in vivo mouse model systems commonly used for studying oral cancer and discuss the impact these models are having in advancing basic mechanisms, chemoprevention, and therapeutic intervention of oral cancer while highlighting recent discoveries concerning the role of immune cells in oral cancer. Improvements to in vivo model systems that highly recapitulate human oral cancer hold the key to identifying features of oral cancer initiation, progression, and invasion as well as molecular and cellular targets for prevention, therapeutic response, and immunotherapy development.

Self-organized criticality in a two-dimensional cellular automaton model of a magnetic flux tube with background flow

NASA Astrophysics Data System (ADS)

Dănilă, B.; Harko, T.; Mocanu, G.

2015-11-01

We investigate the transition to self-organized criticality in a two-dimensional model of a flux tube with a background flow. The magnetic induction equation, represented by a partial differential equation with a stochastic source term, is discretized and implemented on a two-dimensional cellular automaton. The energy released by the automaton during one relaxation event is the magnetic energy. As a result of the simulations, we obtain the time evolution of the energy release, of the system control parameter, of the event lifetime distribution and of the event size distribution, respectively, and we establish that a self-organized critical state is indeed reached by the system. Moreover, energetic initial impulses in the magnetohydrodynamic flow can lead to one-dimensional signatures in the magnetic two-dimensional system, once the self-organized critical regime is established. The applications of the model for the study of gamma-ray bursts (GRBs) is briefly considered, and it is shown that some astrophysical parameters of the bursts, like the light curves, the maximum released energy and the number of peaks in the light curve can be reproduced and explained, at least on a qualitative level, by working in a framework in which the systems settles in a self-organized critical state via magnetic reconnection processes in the magnetized GRB fireball.

Gaseous VOCs rapidly modify particulate matter and its biological effects – Part 1: Simple VOCs and model PM

PubMed Central

Ebersviller, S.; Lichtveld, K.; Sexton, K. G.; Zavala, J.; Lin, Y-H.; Jaspers, I.; Jeffries, H. E.

2013-01-01

This is the first of a three-part study designed to demonstrate dynamic entanglements among gaseous organic compounds (VOC), particulate matter (PM), and their subsequent potential biological effects. We study these entanglements in increasingly complex VOC and PM mixtures in urban-like conditions in a large outdoor chamber. To the traditional chemical and physical characterizations of gas and PM, we added new measurements of gas-only- and PM-only-biological effects, using cultured human lung cells as model indicators. These biological effects are assessed here as increases in cellular damage or expressed irritation (i.e., cellular toxic effects) from cells exposed to chamber air relative to cells exposed to clean air. The exposure systems permit gas-only- or PM-only-exposures from the same air stream containing both gases and PM in equilibria, i.e., there are no extractive operations prior to cell exposure. Our simple experiments in this part of the study were designed to eliminate many competing atmospheric processes to reduce ambiguity in our results. Simple volatile and semi-volatile organic gases that have inherent cellular toxic properties were tested individually for biological effect in the dark (at constant humidity). Airborne mixtures were then created with each compound and PM that has no inherent cellular toxic properties for another cellular exposure. Acrolein and p-tolualdehyde were used as model VOCs and mineral oil aerosol (MOA) was selected as a surrogate for organic-containing PM. MOA is appropriately complex in composition to represent ambient PM, and it exhibits no inherent cellular toxic effects and thus did not contribute any biological detrimental effects on its own. Chemical measurements, combined with the responses of our biological exposures, clearly demonstrate that gas-phase pollutants can modify the composition of PM (and its resulting detrimental effects on lung cells) – even if the gas-phase pollutants are not considered likely to partition to the condensed phase: the VOC-modified-PM showed significantly more damage and inflammation to lung cells than did the original PM. Because gases and PM are transported and deposited differently within the atmosphere and the lungs, these results have significant consequences. For example, current US policies for research and regulation of PM do not recognize this “effect modification” phenomena (NAS, 2004). These results present an unambiguous demonstration that – even in these simple mixtures – physical and thermal interactions alone can cause a modification of the distribution of species among the phases of airborne pollution mixtures and can result in a non-toxic phase becoming toxic due to atmospheric thermal processes only. Subsequent work extends the simple results reported here to systems with photochemical transformations of complex urban mixtures and to systems with diesel exhaust produced by different fuels. PMID:23457430

Illuminating Cancer Systems With Genetically-Engineered Mouse Models and Coupled Luciferase Reporters In Vivo

PubMed Central

Kocher, Brandon; Piwnica-Worms, David

2013-01-01

Bioluminescent imaging (BLI) is a powerful non-invasive tool that has dramatically accelerated the in vivo interrogation of cancer systems and longitudinal analysis of mouse models of cancer over the past decade. Various luciferase enzymes have been genetically engineered into mouse models (GEMMs) of cancer which permit investigation of cellular and molecular events associated with oncogenic transcription, post-transcriptional processing, protein-protein interactions, transformation and oncogene addiction in live cells and animals. Luciferase-coupled GEMMs ultimately serve as a non-invasive, repetitive, longitudinal, and physiological means by which cancer systems and therapeutic responses can be investigated accurately within the autochthonous context of a living animal. PMID:23585416

An individual-based modeling approach to simulate the effects of cellular nutrient competition on Escherichia coli K-12 MG1655 colony behavior and interactions in aerobic structured food systems.

PubMed

Tack, Ignace L M M; Logist, Filip; Noriega Fernández, Estefanía; Van Impe, Jan F M

2015-02-01

Traditional kinetic models in predictive microbiology reliably predict macroscopic dynamics of planktonically-growing cell cultures in homogeneous liquid food systems. However, most food products have a semi-solid structure, where microorganisms grow locally in colonies. Individual colony cells exhibit strongly different and non-normally distributed behavior due to local nutrient competition. As a result, traditional models considering average population behavior in a homogeneous system do not describe colony dynamics in full detail. To incorporate local resource competition and individual cell differences, an individual-based modeling approach has been applied to Escherichia coli K-12 MG1655 colonies, considering the microbial cell as modeling unit. The first contribution of this individual-based model is to describe single colony growth under nutrient-deprived conditions. More specifically, the linear and stationary phase in the evolution of the colony radius, the evolution from a disk-like to branching morphology, and the emergence of a starvation zone in the colony center are simulated and compared to available experimental data. These phenomena occur earlier at more severe nutrient depletion conditions, i.e., at lower nutrient diffusivity and initial nutrient concentration in the medium. Furthermore, intercolony interactions have been simulated. Higher inoculum densities lead to stronger intercolony interactions, such as colony merging and smaller colony sizes, due to nutrient competition. This individual-based model contributes to the elucidation of characteristic experimentally observed colony behavior from mechanistic information about cellular physiology and interactions. Copyright © 2014 Elsevier Ltd. All rights reserved.

Fostering synergy between cell biology and systems biology.

PubMed

Eddy, James A; Funk, Cory C; Price, Nathan D

2015-08-01

In the shared pursuit of elucidating detailed mechanisms of cell function, systems biology presents a natural complement to ongoing efforts in cell biology. Systems biology aims to characterize biological systems through integrated and quantitative modeling of cellular information. The process of model building and analysis provides value through synthesizing and cataloging information about cells and molecules, predicting mechanisms and identifying generalizable themes, generating hypotheses and guiding experimental design, and highlighting knowledge gaps and refining understanding. In turn, incorporating domain expertise and experimental data is crucial for building towards whole cell models. An iterative cycle of interaction between cell and systems biologists advances the goals of both fields and establishes a framework for mechanistic understanding of the genome-to-phenome relationship. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.

Geometric Modeling of Cellular Materials for Additive Manufacturing in Biomedical Field: A Review

PubMed Central

Rosso, Stefano; Meneghello, Roberto; Concheri, Gianmaria

2018-01-01

Advances in additive manufacturing technologies facilitate the fabrication of cellular materials that have tailored functional characteristics. The application of solid freeform fabrication techniques is especially exploited in designing scaffolds for tissue engineering. In this review, firstly, a classification of cellular materials from a geometric point of view is proposed; then, the main approaches on geometric modeling of cellular materials are discussed. Finally, an investigation on porous scaffolds fabricated by additive manufacturing technologies is pointed out. Perspectives in geometric modeling of scaffolds for tissue engineering are also proposed. PMID:29487626

Geometric Modeling of Cellular Materials for Additive Manufacturing in Biomedical Field: A Review.

PubMed

Savio, Gianpaolo; Rosso, Stefano; Meneghello, Roberto; Concheri, Gianmaria

2018-01-01

Advances in additive manufacturing technologies facilitate the fabrication of cellular materials that have tailored functional characteristics. The application of solid freeform fabrication techniques is especially exploited in designing scaffolds for tissue engineering. In this review, firstly, a classification of cellular materials from a geometric point of view is proposed; then, the main approaches on geometric modeling of cellular materials are discussed. Finally, an investigation on porous scaffolds fabricated by additive manufacturing technologies is pointed out. Perspectives in geometric modeling of scaffolds for tissue engineering are also proposed.

In vivo imaging of skeletal muscle in mice highlights muscle defects in a model of myotubular myopathy

PubMed Central

Mercier, Luc; Böhm, Johann; Fekonja, Nina; Allio, Guillaume; Lutz, Yves; Koch, Marc; Goetz, Jacky G.; Laporte, Jocelyn

2016-01-01

ABSTRACT Skeletal muscle structure and function are altered in different myopathies. However, the understanding of the molecular and cellular mechanisms mainly rely on in vitro and ex vivo investigations in mammalian models. In order to monitor in vivo the intracellular structure of the neuromuscular system in its environment under normal and pathological conditions, we set-up and validated non-invasive imaging of ear and leg muscles in mice. This original approach allows simultaneous imaging of different cellular and intracellular structures such as neuromuscular junctions and sarcomeres, reconstruction of the 3D architecture of the neuromuscular system, and video recording of dynamic events such as spontaneous muscle fiber contraction. Second harmonic generation was combined with vital dyes and fluorescent-coupled molecules. Skin pigmentation, although limiting, did not prevent intravital imaging. Using this versatile toolbox on the Mtm1 knockout mouse, a model for myotubular myopathy which is a severe congenital myopathy in human, we identified several hallmarks of the disease such as defects in fiber size and neuromuscular junction shape. Intravital imaging of the neuromuscular system paves the way for the follow-up of disease progression or/and disease amelioration upon therapeutic tests. It has also the potential to reduce the number of animals needed to reach scientific conclusions. PMID:28243519

The zebrafish as a gerontology model in nervous system aging, disease, and repair.

PubMed

Van Houcke, Jessie; De Groef, Lies; Dekeyster, Eline; Moons, Lieve

2015-11-01

Considering the increasing number of elderly in the world's population today, developing effective treatments for age-related pathologies is one of the biggest challenges in modern medical research. Age-related neurodegeneration, in particular, significantly impacts important sensory, motor, and cognitive functions, seriously constraining life quality of many patients. Although our understanding of the causal mechanisms of aging has greatly improved in recent years, animal model systems still have much to tell us about this complex process. Zebrafish (Danio rerio) have gained enormous popularity for this research topic over the past decade, since their life span is relatively short but, like humans, they are still subject to gradual aging. In addition, the extensive characterization of its well-conserved molecular and cellular physiology makes the zebrafish an excellent model to unravel the underlying mechanisms of aging, disease, and repair. This review provides a comprehensive overview of the progress made in zebrafish gerontology, with special emphasis on nervous system aging. We review the evidence that classic hallmarks of aging can also be recognized within this small vertebrate, both at the molecular and cellular level. Moreover, we illustrate the high level of similarity with age-associated human pathologies through a survey of the functional deficits that arise as zebrafish age. Copyright © 2015 Elsevier B.V. All rights reserved.

47 CFR 22.923 - Cellular system configuration.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 22.923 Telecommunication FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) COMMON CARRIER SERVICES PUBLIC MOBILE SERVICES Cellular Radiotelephone Service § 22.923 Cellular system configuration. Mobile stations communicate with and through base transmitters only. Base transmitters communicate with mobile stations...

Emergence of tissue mechanics from cellular processes: shaping a fly wing

NASA Astrophysics Data System (ADS)

Merkel, Matthias; Etournay, Raphael; Popovic, Marko; Nandi, Amitabha; Brandl, Holger; Salbreux, Guillaume; Eaton, Suzanne; Jülicher, Frank

Nowadays, biologistsare able to image biological tissueswith up to 10,000 cells in vivowhere the behavior of each individual cell can be followed in detail.However, how precisely large-scale tissue deformation and stresses emerge from cellular behavior remains elusive. Here, we study this question in the developing wing of the fruit fly. To this end, we first establish a geometrical framework that exactly decomposes tissue deformation into contributions by different kinds of cellular processes. These processes comprise cell shape changes, cell neighbor exchanges, cell divisions, and cell extrusions. As the key idea, we introduce a tiling of the cellular network into triangles. This approach also reveals that tissue deformation can also be created by correlated cellular motion. Based on quantifications using these concepts, we developed a novel continuum mechanical model for the fly wing. In particular, our model includes active anisotropic stresses and a delay in the response of cell rearrangements to material stresses. A different approach to study the emergence of tissue mechanics from cellular behavior are cell-based models. We characterize the properties of a cell-based model for 3D tissues that is a hybrid between single particle models and the so-called vertex models.

Multiway modeling and analysis in stem cell systems biology

PubMed Central

2008-01-01

Background Systems biology refers to multidisciplinary approaches designed to uncover emergent properties of biological systems. Stem cells are an attractive target for this analysis, due to their broad therapeutic potential. A central theme of systems biology is the use of computational modeling to reconstruct complex systems from a wealth of reductionist, molecular data (e.g., gene/protein expression, signal transduction activity, metabolic activity, etc.). A number of deterministic, probabilistic, and statistical learning models are used to understand sophisticated cellular behaviors such as protein expression during cellular differentiation and the activity of signaling networks. However, many of these models are bimodal i.e., they only consider row-column relationships. In contrast, multiway modeling techniques (also known as tensor models) can analyze multimodal data, which capture much more information about complex behaviors such as cell differentiation. In particular, tensors can be very powerful tools for modeling the dynamic activity of biological networks over time. Here, we review the application of systems biology to stem cells and illustrate application of tensor analysis to model collagen-induced osteogenic differentiation of human mesenchymal stem cells. Results We applied Tucker1, Tucker3, and Parallel Factor Analysis (PARAFAC) models to identify protein/gene expression patterns during extracellular matrix-induced osteogenic differentiation of human mesenchymal stem cells. In one case, we organized our data into a tensor of type protein/gene locus link × gene ontology category × osteogenic stimulant, and found that our cells expressed two distinct, stimulus-dependent sets of functionally related genes as they underwent osteogenic differentiation. In a second case, we organized DNA microarray data in a three-way tensor of gene IDs × osteogenic stimulus × replicates, and found that application of tensile strain to a collagen I substrate accelerated the osteogenic differentiation induced by a static collagen I substrate. Conclusion Our results suggest gene- and protein-level models whereby stem cells undergo transdifferentiation to osteoblasts, and lay the foundation for mechanistic, hypothesis-driven studies. Our analysis methods are applicable to a wide range of stem cell differentiation models. PMID:18625054

Dynamical and Mechanistic Reconstructive Approaches of T Lymphocyte Dynamics: Using Visual Modeling Languages to Bridge the Gap between Immunologists, Theoreticians, and Programmers

PubMed Central

Thomas-Vaslin, Véronique; Six, Adrien; Ganascia, Jean-Gabriel; Bersini, Hugues

2013-01-01

Dynamic modeling of lymphocyte behavior has primarily been based on populations based differential equations or on cellular agents moving in space and interacting each other. The final steps of this modeling effort are expressed in a code written in a programing language. On account of the complete lack of standardization of the different steps to proceed, we have to deplore poor communication and sharing between experimentalists, theoreticians and programmers. The adoption of diagrammatic visual computer language should however greatly help the immunologists to better communicate, to more easily identify the models similarities and facilitate the reuse and extension of existing software models. Since immunologists often conceptualize the dynamical evolution of immune systems in terms of “state-transitions” of biological objects, we promote the use of unified modeling language (UML) state-transition diagram. To demonstrate the feasibility of this approach, we present a UML refactoring of two published models on thymocyte differentiation. Originally built with different modeling strategies, a mathematical ordinary differential equation-based model and a cellular automata model, the two models are now in the same visual formalism and can be compared. PMID:24101919

A multi-model approach to nucleic acid-based drug development.

PubMed

Gautherot, Isabelle; Sodoyer, Regís

2004-01-01

With the advent of functional genomics and the shift of interest towards sequence-based therapeutics, the past decades have witnessed intense research efforts on nucleic acid-mediated gene regulation technologies. Today, RNA interference is emerging as a groundbreaking discovery, holding promise for development of genetic modulators of unprecedented potency. Twenty-five years after the discovery of antisense RNA and ribozymes, gene control therapeutics are still facing developmental difficulties, with only one US FDA-approved antisense drug currently available in the clinic. Limited predictability of target site selection models is recognized as one major stumbling block that is shared by all of the so-called complementary technologies, slowing the progress towards a commercial product. Currently employed in vitro systems for target site selection include RNAse H-based mapping, antisense oligonucleotide microarrays, and functional screening approaches using libraries of catalysts with randomized target-binding arms to identify optimal ribozyme/DNAzyme cleavage sites. Individually, each strategy has its drawbacks from a drug development perspective. Utilization of message-modulating sequences as therapeutic agents requires that their action on a given target transcript meets criteria of potency and selectivity in the natural physiological environment. In addition to sequence-dependent characteristics, other factors will influence annealing reactions and duplex stability, as well as nucleic acid-mediated catalysis. Parallel consideration of physiological selection systems thus appears essential for screening for nucleic acid compounds proposed for therapeutic applications. Cellular message-targeting studies face issues relating to efficient nucleic acid delivery and appropriate analysis of response. For reliability and simplicity, prokaryotic systems can provide a rapid and cost-effective means of studying message targeting under pseudo-cellular conditions, but such approaches also have limitations. To streamline nucleic acid drug discovery, we propose a multi-model strategy integrating high-throughput-adapted bacterial screening, followed by reporter-based and/or natural cellular models and potentially also in vitro assays for characterization of the most promising candidate sequences, before final in vivo testing.

ChainMail based neural dynamics modeling of soft tissue deformation for surgical simulation.

PubMed

Zhang, Jinao; Zhong, Yongmin; Smith, Julian; Gu, Chengfan

2017-07-20

Realistic and real-time modeling and simulation of soft tissue deformation is a fundamental research issue in the field of surgical simulation. In this paper, a novel cellular neural network approach is presented for modeling and simulation of soft tissue deformation by combining neural dynamics of cellular neural network with ChainMail mechanism. The proposed method formulates the problem of elastic deformation into cellular neural network activities to avoid the complex computation of elasticity. The local position adjustments of ChainMail are incorporated into the cellular neural network as the local connectivity of cells, through which the dynamic behaviors of soft tissue deformation are transformed into the neural dynamics of cellular neural network. Experiments demonstrate that the proposed neural network approach is capable of modeling the soft tissues' nonlinear deformation and typical mechanical behaviors. The proposed method not only improves ChainMail's linear deformation with the nonlinear characteristics of neural dynamics but also enables the cellular neural network to follow the principle of continuum mechanics to simulate soft tissue deformation.

Bioprocess systems engineering: transferring traditional process engineering principles to industrial biotechnology.

PubMed

Koutinas, Michalis; Kiparissides, Alexandros; Pistikopoulos, Efstratios N; Mantalaris, Athanasios

2012-01-01

The complexity of the regulatory network and the interactions that occur in the intracellular environment of microorganisms highlight the importance in developing tractable mechanistic models of cellular functions and systematic approaches for modelling biological systems. To this end, the existing process systems engineering approaches can serve as a vehicle for understanding, integrating and designing biological systems and processes. Here, we review the application of a holistic approach for the development of mathematical models of biological systems, from the initial conception of the model to its final application in model-based control and optimisation. We also discuss the use of mechanistic models that account for gene regulation, in an attempt to advance the empirical expressions traditionally used to describe micro-organism growth kinetics, and we highlight current and future challenges in mathematical biology. The modelling research framework discussed herein could prove beneficial for the design of optimal bioprocesses, employing rational and feasible approaches towards the efficient production of chemicals and pharmaceuticals.

Bioprocess systems engineering: transferring traditional process engineering principles to industrial biotechnology

PubMed Central

Koutinas, Michalis; Kiparissides, Alexandros; Pistikopoulos, Efstratios N.; Mantalaris, Athanasios

2013-01-01

The complexity of the regulatory network and the interactions that occur in the intracellular environment of microorganisms highlight the importance in developing tractable mechanistic models of cellular functions and systematic approaches for modelling biological systems. To this end, the existing process systems engineering approaches can serve as a vehicle for understanding, integrating and designing biological systems and processes. Here, we review the application of a holistic approach for the development of mathematical models of biological systems, from the initial conception of the model to its final application in model-based control and optimisation. We also discuss the use of mechanistic models that account for gene regulation, in an attempt to advance the empirical expressions traditionally used to describe micro-organism growth kinetics, and we highlight current and future challenges in mathematical biology. The modelling research framework discussed herein could prove beneficial for the design of optimal bioprocesses, employing rational and feasible approaches towards the efficient production of chemicals and pharmaceuticals. PMID:24688682

Modeling transport across the running-sandpile cellular automaton by means of fractional transport equations

NASA Astrophysics Data System (ADS)

Sánchez, R.; Newman, D. E.; Mier, J. A.

2018-05-01

Fractional transport equations are used to build an effective model for transport across the running sandpile cellular automaton [Hwa et al., Phys. Rev. A 45, 7002 (1992), 10.1103/PhysRevA.45.7002]. It is shown that both temporal and spatial fractional derivatives must be considered to properly reproduce the sandpile transport features, which are governed by self-organized criticality, at least over sufficiently long or large scales. In contrast to previous applications of fractional transport equations to other systems, the specifics of sand motion require in this case that the spatial fractional derivatives used for the running sandpile must be of the completely asymmetrical Riesz-Feller type. Appropriate values for the fractional exponents that define these derivatives in the case of the running sandpile are obtained numerically.

47 CFR 22.877 - Unacceptable interference to part 90 non-cellular 800 MHz licensees from commercial aviation air...

Code of Federal Regulations, 2014 CFR

2014-10-01

...-cellular 800 MHz licensees from commercial aviation air-ground systems. 22.877 Section 22.877...-Ground Radiotelephone Service Commercial Aviation Air-Ground Systems § 22.877 Unacceptable interference to part 90 non-cellular 800 MHz licensees from commercial aviation air-ground systems. The definition...

47 CFR 22.877 - Unacceptable interference to Part 90 non-cellular 800 MHz licensees from commercial aviation air...

Code of Federal Regulations, 2012 CFR

2012-10-01

...-cellular 800 MHz licensees from commercial aviation air-ground systems. 22.877 Section 22.877...-Ground Radiotelephone Service Commercial Aviation Air-Ground Systems § 22.877 Unacceptable interference to Part 90 non-cellular 800 MHz licensees from commercial aviation air-ground systems. The definition...

47 CFR 22.877 - Unacceptable interference to Part 90 non-cellular 800 MHz licensees from commercial aviation air...

Code of Federal Regulations, 2011 CFR

2011-10-01

...-cellular 800 MHz licensees from commercial aviation air-ground systems. 22.877 Section 22.877...-Ground Radiotelephone Service Commercial Aviation Air-Ground Systems § 22.877 Unacceptable interference to Part 90 non-cellular 800 MHz licensees from commercial aviation air-ground systems. The definition...

47 CFR 22.877 - Unacceptable interference to Part 90 non-cellular 800 MHz licensees from commercial aviation air...

Code of Federal Regulations, 2013 CFR

2013-10-01

...-cellular 800 MHz licensees from commercial aviation air-ground systems. 22.877 Section 22.877...-Ground Radiotelephone Service Commercial Aviation Air-Ground Systems § 22.877 Unacceptable interference to Part 90 non-cellular 800 MHz licensees from commercial aviation air-ground systems. The definition...

47 CFR 22.947 - Five year build-out period.

Code of Federal Regulations, 2011 CFR

2011-10-01

... MOBILE SERVICES Cellular Radiotelephone Service § 22.947 Five year build-out period. Except for systems...-out period, the licensee of the first cellular system on each channel block in each market may enter...-out period begins on the date the initial authorization for the first cellular system is granted, and...

Simulation of Chronic Liver Injury Due to Environmental Chemicals

EPA Science Inventory

US EPA Virtual Liver (v-Liver) is a cellular systems model of hepatic tissues to predict the effects of chronic exposure to chemicals. Tens of thousands of chemicals are currently in commerce and hundreds more are introduced every year. Few of these chemicals have been adequate...

Use of High-Throughput Testing and Approaches for Evaluating Chemical Risk-Relevance to Humans

EPA Science Inventory

ToxCast is profiling the bioactivity of thousands of chemicals based on high-throughput screening (HTS) and computational models that integrate knowledge of biological systems and in vivo toxicities. Many of these assays probe signaling pathways and cellular processes critical to...

Tools for visually exploring biological networks.

PubMed

Suderman, Matthew; Hallett, Michael

2007-10-15

Many tools exist for visually exploring biological networks including well-known examples such as Cytoscape, VisANT, Pathway Studio and Patika. These systems play a key role in the development of integrative biology, systems biology and integrative bioinformatics. The trend in the development of these tools is to go beyond 'static' representations of cellular state, towards a more dynamic model of cellular processes through the incorporation of gene expression data, subcellular localization information and time-dependent behavior. We provide a comprehensive review of the relative advantages and disadvantages of existing systems with two goals in mind: to aid researchers in efficiently identifying the appropriate existing tools for data visualization; to describe the necessary and realistic goals for the next generation of visualization tools. In view of the first goal, we provide in the Supplementary Material a systematic comparison of more than 35 existing tools in terms of over 25 different features. Supplementary data are available at Bioinformatics online.

Dichotomy in the definition of prescriptive information suggests both prescribed data and prescribed algorithms: biosemiotics applications in genomic systems.

PubMed

D'Onofrio, David J; Abel, David L; Johnson, Donald E

2012-03-14

The fields of molecular biology and computer science have cooperated over recent years to create a synergy between the cybernetic and biosemiotic relationship found in cellular genomics to that of information and language found in computational systems. Biological information frequently manifests its "meaning" through instruction or actual production of formal bio-function. Such information is called prescriptive information (PI). PI programs organize and execute a prescribed set of choices. Closer examination of this term in cellular systems has led to a dichotomy in its definition suggesting both prescribed data and prescribed algorithms are constituents of PI. This paper looks at this dichotomy as expressed in both the genetic code and in the central dogma of protein synthesis. An example of a genetic algorithm is modeled after the ribosome, and an examination of the protein synthesis process is used to differentiate PI data from PI algorithms.

Modeling oscillatory dynamics in brain microcircuits as a way to help uncover neurological disease mechanisms: A proposal

DOE Office of Scientific and Technical Information (OSTI.GOV)

Skinner, F. K.; Department of Medicine; Department of Physiology, University of Toronto Medical Sciences Building, 3rd Floor, 1 King's College Circle, Toronto, Ontario M5S 1A8

There is an undisputed need and requirement for theoretical and computational studies in Neuroscience today. Furthermore, it is clear that oscillatory dynamical output from brain networks is representative of various behavioural states, and it is becoming clear that one could consider these outputs as measures of normal and pathological brain states. Although mathematical modeling of oscillatory dynamics in the context of neurological disease exists, it is a highly challenging endeavour because of the many levels of organization in the nervous system. This challenge is coupled with the increasing knowledge of cellular specificity and network dysfunction that is associated with disease.more » Recently, whole hippocampus in vitro preparations from control animals have been shown to spontaneously express oscillatory activities. In addition, when using preparations derived from animal models of disease, these activities show particular alterations. These preparations present an opportunity to address challenges involved with using models to gain insight because of easier access to simultaneous cellular and network measurements, and pharmacological modulations. We propose that by developing and using models with direct links to experiment at multiple levels, which at least include cellular and microcircuit, a cycling can be set up and used to help us determine critical mechanisms underlying neurological disease. We illustrate our proposal using our previously developed inhibitory network models in the context of these whole hippocampus preparations and show the importance of having direct links at multiple levels.« less

Toward Multiscale Models of Cyanobacterial Growth: A Modular Approach

PubMed Central

Westermark, Stefanie; Steuer, Ralf

2016-01-01

Oxygenic photosynthesis dominates global primary productivity ever since its evolution more than three billion years ago. While many aspects of phototrophic growth are well understood, it remains a considerable challenge to elucidate the manifold dependencies and interconnections between the diverse cellular processes that together facilitate the synthesis of new cells. Phototrophic growth involves the coordinated action of several layers of cellular functioning, ranging from the photosynthetic light reactions and the electron transport chain, to carbon-concentrating mechanisms and the assimilation of inorganic carbon. It requires the synthesis of new building blocks by cellular metabolism, protection against excessive light, as well as diurnal regulation by a circadian clock and the orchestration of gene expression and cell division. Computational modeling allows us to quantitatively describe these cellular functions and processes relevant for phototrophic growth. As yet, however, computational models are mostly confined to the inner workings of individual cellular processes, rather than describing the manifold interactions between them in the context of a living cell. Using cyanobacteria as model organisms, this contribution seeks to summarize existing computational models that are relevant to describe phototrophic growth and seeks to outline their interactions and dependencies. Our ultimate aim is to understand cellular functioning and growth as the outcome of a coordinated operation of diverse yet interconnected cellular processes. PMID:28083530

Adding dimension to cellular mechanotransduction: Advances in biomedical engineering of multiaxial cell-stretch systems and their application to cardiovascular biomechanics and mechano-signaling.

PubMed

Friedrich, O; Schneidereit, D; Nikolaev, Y A; Nikolova-Krstevski, V; Schürmann, S; Wirth-Hücking, A; Merten, A L; Fatkin, D; Martinac, B

2017-11-01

Hollow organs (e.g. heart) experience pressure-induced mechanical wall stress sensed by molecular mechano-biosensors, including mechanosensitive ion channels, to translate into intracellular signaling. For direct mechanistic studies, stretch devices to apply defined extensions to cells adhered to elastomeric membranes have stimulated mechanotransduction research. However, most engineered systems only exploit unilateral cellular stretch. In addition, it is often taken for granted that stretch applied by hardware translates 1:1 to the cell membrane. However, the latter crucially depends on the tightness of the cell-substrate junction by focal adhesion complexes and is often not calibrated for. In the heart, (increased) hemodynamic volume/pressure load is associated with (increased) multiaxial wall tension, stretching individual cardiomyocytes in multiple directions. To adequately study cellular models of chronic organ distension on a cellular level, biomedical engineering faces challenges to implement multiaxial cell stretch systems that allow observing cell reactions to stretch during live-cell imaging, and to calibrate for hardware-to-cell membrane stretch translation. Here, we review mechanotransduction, cell stretch technologies from uni-to multiaxial designs in cardio-vascular research, and the importance of the stretch substrate-cell membrane junction. We also present new results using our IsoStretcher to demonstrate mechanosensitivity of Piezo1 in HEK293 cells and stretch-induced Ca 2+ entry in 3D-hydrogel-embedded cardiomyocytes. Copyright © 2017 Elsevier Ltd. All rights reserved.

Toxicity potentials from waste cellular phones, and a waste management policy integrating consumer, corporate, and government responsibilities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lim, Seong-Rin; Schoenung, Julie M., E-mail: jmschoenung@ucdavis.ed

Cellular phones have high environmental impact potentials because of their heavy metal content and current consumer attitudes toward purchasing new phones with higher functionality and neglecting to return waste phones into proper take-back systems. This study evaluates human health and ecological toxicity potentials from waste cellular phones; highlights consumer, corporate, and government responsibilities for effective waste management; and identifies key elements needed for an effective waste management strategy. The toxicity potentials are evaluated by using heavy metal content, respective characterization factors, and a pathway and impact model for heavy metals that considers end-of-life disposal in landfills or by incineration. Cancermore » potentials derive primarily from Pb and As; non-cancer potentials primarily from Cu and Pb; and ecotoxicity potentials primarily from Cu and Hg. These results are not completely in agreement with previous work in which leachability thresholds were the metric used to establish priority, thereby indicating the need for multiple or revised metrics. The triple bottom line of consumer, corporate, and government responsibilities is emphasized in terms of consumer attitudes, design for environment (DfE), and establishment and implementation of waste management systems including recycling streams, respectively. The key strategic elements for effective waste management include environmental taxation and a deposit-refund system to motivate consumer responsibility, which is linked and integrated with corporate and government responsibilities. The results of this study can contribute to DfE and waste management policy for cellular phones.« less

Toxicity potentials from waste cellular phones, and a waste management policy integrating consumer, corporate, and government responsibilities.

PubMed

Lim, Seong-Rin; Schoenung, Julie M

2010-01-01

Cellular phones have high environmental impact potentials because of their heavy metal content and current consumer attitudes toward purchasing new phones with higher functionality and neglecting to return waste phones into proper take-back systems. This study evaluates human health and ecological toxicity potentials from waste cellular phones; highlights consumer, corporate, and government responsibilities for effective waste management; and identifies key elements needed for an effective waste management strategy. The toxicity potentials are evaluated by using heavy metal content, respective characterization factors, and a pathway and impact model for heavy metals that considers end-of-life disposal in landfills or by incineration. Cancer potentials derive primarily from Pb and As; non-cancer potentials primarily from Cu and Pb; and ecotoxicity potentials primarily from Cu and Hg. These results are not completely in agreement with previous work in which leachability thresholds were the metric used to establish priority, thereby indicating the need for multiple or revised metrics. The triple bottom line of consumer, corporate, and government responsibilities is emphasized in terms of consumer attitudes, design for environment (DfE), and establishment and implementation of waste management systems including recycling streams, respectively. The key strategic elements for effective waste management include environmental taxation and a deposit-refund system to motivate consumer responsibility, which is linked and integrated with corporate and government responsibilities. The results of this study can contribute to DfE and waste management policy for cellular phones. 2010 Elsevier Ltd. All rights reserved.

Monitoring Cellular Events in Living Mast Cells Stimulated with an Extremely Small Amount of Fluid on a Microchip

NASA Astrophysics Data System (ADS)

Munaka, Tatsuya; Abe, Hirohisa; Kanai, Masaki; Sakamoto, Takashi; Nakanishi, Hiroaki; Yamaoka, Tetsuji; Shoji, Shuichi; Murakami, Akira

2006-07-01

We successfully developed a measurement system for real-time analysis of cellular function using a newly designed microchip. This microchip was equipped with a micro cell incubation chamber (240 nl) and was stimulated by a very small amount of stimuli (as small as 24 nl). Using the microchip system, cultivation of mast cells was successfully carried out. Monitoring of the cellular events after stimulation with an extremely small amount of fluid on a microchip was performed. This system could be applicable for various types of cellular analysis including real-time monitoring of cellular response by stimulation.

Determination of Roles of Microgravity and Ionizing Radiation on the Reactivation of Epstein-Barr Virus In Vitro

NASA Technical Reports Server (NTRS)

Mehta, Satish K; Renner, Ashlie; Stowe, Raymond; Bloom, David; Pierson, Duane

2015-01-01

Astronauts experience symptomatic and asymptomatic herpes virus reactivation during spaceflight. We have shown increases in reactivation of Epstein-Barr virus (EBV), cytomegalovirus (CMV) and varicella zoster virus (VZV) and shedding in body fluids (saliva and urine) in astronauts during space travel. Alterations in immunity, increased stress hormone levels, microgravity, increased radiation, and other conditions unique to spaceflight may promote reactivation of latent herpes viruses. Unique mechanico-physico forces associated with spaceflight can have profound effects on cellular function, especially immune cells. In space flight analog studies such as Antarctica, bed rest studies, and NASA's undersea habitat (Aquarius), reactivation of these viruses occurred, but to a lesser extent than spaceflight. Spaceflight analogs model some spaceflight factors, but none of the analogs recreates all factors experienced in space. Most notably, microgravity and radiation are not included in many analogs. Stress, processed through the HPA axis and SAM systems, induces viral reactivation. However, the respective roles of microgravity and increased space radiation levels or if any synergy exists are not known. Therefore, we studied the effect of modeled space radiation and/or microgravity, independent of the immune system on the changes in cellular gene expression that results in viral (EBV) reactivation. The effects of modeled microgravity and low shear on EBV replication and cellular and EBV gene expression were studied in human B-lymphocyte cell cultures. Latently infected B-lymphocytes were propagated in the rotating wall bioreactor and irradiated with the various dosages of gamma irradiation. At specific time intervals following exposure to modeled microgravity, the cells and supernatant were harvested and reactivation of EBV were assessed by measuring EBV and gene expression, DNA methylation, and infectious virus production.

Three-dimensional Myoblast Aggregates--Effects of Modeled Microgravity

NASA Technical Reports Server (NTRS)

Byerly, Diane; Sognier, M. A.; Marquette, M. L.

2006-01-01

The overall objective of these studies is to elucidate the molecular and cellular alterations that contribute to muscle atrophy in astronauts caused by exposure to microgravity conditions in space. To accomplish this, a three-dimensional model test system was developed using mouse myoblast cells (C2C12). Myoblast cells were grown as three-dimensional aggregates (without scaffolding or other solid support structures) in both modeled microgravity (Rotary Cell Culture System, Synthecon, Inc.) and at unit gravity in coated Petri dishes. Evaluation of H&E stained thin sections of the aggregates revealed the absence of any necrosis. Confocal microscopy evaluations of cells stained with the Live/Dead assay (Molecular Probes) confirmed that viable cells were present throughout the aggregates with an average of only three dead cells observed per aggregate. Preliminary results from gene array analysis (Affymetrix chip U74Av2) showed that approximately 14% of the genes were down regulated (decreased more than 3 fold) and 4% were upregulated in cells exposed to modeled microgravity for 12 hours compared to unit gravity controls. Additional studies using fluorescent phallacidin revealed a decrease in F-actin in the cells exposed to modeled microgravity compared to unit gravity. Myoblast cells grown as aggregates in modeled microgravity exhibited spontaneous differentiation into syncitia while no differentiation was seen in the unit gravity controls. These studies show that 1)the model test system developed is suitable for assessing cellular and molecular alterations in myoblasts; 2) gene expression alterations occur rapidly (within 12 hours) following exposure to modeled microgravity; and 3) modeled microgravity conditions stimulated myoblast cell differentiation. Achieving a greater understanding of the molecular alterations leading to muscle atrophy will eventually enable the development of cell-based countermeasures, which may be valuable for treatment of muscle diseases on Earth and future space explorations.

Rat brain sagittal organotypic slice cultures as an ex vivo dopamine cell loss system.

PubMed

McCaughey-Chapman, Amy; Connor, Bronwen

2017-02-01

Organotypic brain slice cultures are a useful tool to study neurological function as they provide a more complex, 3-dimensional system than standard 2-dimensional in vitro cell cultures. Building on a previously developed mouse brain slice culture protocol, we have developed a rat sagittal brain slice culture system as an ex vivo model of dopamine cell loss. We show that rat brain organotypic slice cultures remain viable for up to 6 weeks in culture. Using Fluoro-Gold axonal tracing, we demonstrate that the slice 3-dimensional cytoarchitecture is maintained over a 4 week culturing period, with particular focus on the nigrostriatal pathway. Treatment of the cultures with 6-hydroxydopamine and desipramine induces a progressive loss of Fluoro-Gold-positive nigral cells with a sustained loss of tyrosine hydroxylase-positive nigral cells. This recapitulates the pattern of dopaminergic degeneration observed in the rat partial 6-hydroxydopamine lesion model and, most importantly, the progressive pathology of Parkinson's disease. Our slice culture platform provides an advance over other systems, as we demonstrate for the first time 3-dimensional cytoarchitecture maintenance of rat nigrostriatal sagittal slices for up to 6 weeks. Our ex vivo organotypic slice culture system provides a long term cellular platform to model Parkinson's disease, allowing for the elucidation of mechanisms involved in dopaminergic neuron degeneration and the capability to study cellular integration and plasticity ex vivo. Copyright © 2017 Elsevier B.V. All rights reserved.

A microfluidic co-culture system to monitor tumor-stromal interactions on a chip

PubMed Central

Menon, Nishanth V.; Cao, Bin; Lim, Mayasari; Kang, Yuejun

2014-01-01

The living cells are arranged in a complex natural environment wherein they interact with extracellular matrix and other neighboring cells. Cell-cell interactions, especially those between distinct phenotypes, have attracted particular interest due to the significant physiological relevance they can reveal for both fundamental and applied biomedical research. To study cell-cell interactions, it is necessary to develop co-culture systems, where different cell types can be cultured within the same confined space. Although the current advancement in lab-on-a-chip technology has allowed the creation of in vitro models to mimic the complexity of in vivo environment, it is still rather challenging to create such co-culture systems for easy control of different colonies of cells. In this paper, we have demonstrated a straightforward method for the development of an on-chip co-culture system. It involves a series of steps to selectively change the surface property for discriminative cell seeding and to induce cellular interaction in a co-culture region. Bone marrow stromal cells (HS5) and a liver tumor cell line (HuH7) have been used to demonstrate this co-culture model. The cell migration and cellular interaction have been analyzed using microscopy and biochemical assays. This co-culture system could be used as a disease model to obtain biological insight of pathological progression, as well as a tool to evaluate the efficacy of different drugs for pharmaceutical studies. PMID:25553194

Influence of TRAIL gene on biomechanical properties of the human leukemic cell line Jurkat.

PubMed

Yao, Weijuan; Chen, Kai; Wang, Xinjuan; Xie, Lide; Wen, Zongyao; Yan, Zongyi; Chien, Shu

2002-12-01

We cloned the cDNA fragment of human TNF-related apoptosis inducing ligand (TRAIL) into RevTet-On, a Tet-regulated and high-level gene expression system. Making use of the TRAIL gene expression system in Jurkat as a cell model, we studied the influence of TRAIL gene on the biomechanics properties of Jurkat through measuring changes of cellular biomechanics properties before and after the TRAIL gene expression, which was induced by adding tetracycline derivative doxycycline (Dox). The results indicated that the TRAIL gene expression led to significant changes in cellular biomechanics properties. The osmotic fragility increased and the cell stiffness increased after the expression of TRAIL gene. Thus, the apoptosis-inducing TRAIL gene caused significant changes in the biomechanics properties of Jurkat cells.

Modeling of the competition life cycle using the software complex of cellular automata PyCAlab

NASA Astrophysics Data System (ADS)

Berg, D. B.; Beklemishev, K. A.; Medvedev, A. N.; Medvedeva, M. A.

2015-11-01

The aim of the work is to develop a numerical model of the life cycle of competition on the basis of software complex cellular automata PyCAlab. The model is based on the general patterns of growth of various systems in resource-limited settings. At examples it is shown that the period of transition from an unlimited growth of the market agents to the stage of competitive growth takes quite a long time and may be characterized as monotonic. During this period two main strategies of competitive selection coexist: 1) capture of maximum market space with any reasonable costs; 2) saving by reducing costs. The obtained results allow concluding that the competitive strategies of companies must combine two mentioned types of behavior, and this issue needs to be given adequate attention in the academic literature on management. The created numerical model may be used for market research when developing of the strategies for promotion of new goods and services.

Multi-scale modeling in cell biology

PubMed Central

Meier-Schellersheim, Martin; Fraser, Iain D. C.; Klauschen, Frederick

2009-01-01

Biomedical research frequently involves performing experiments and developing hypotheses that link different scales of biological systems such as, for instance, the scales of intracellular molecular interactions to the scale of cellular behavior and beyond to the behavior of cell populations. Computational modeling efforts that aim at exploring such multi-scale systems quantitatively with the help of simulations have to incorporate several different simulation techniques due to the different time and space scales involved. Here, we provide a non-technical overview of how different scales of experimental research can be combined with the appropriate computational modeling techniques. We also show that current modeling software permits building and simulating multi-scale models without having to become involved with the underlying technical details of computational modeling. PMID:20448808

Nanostructured 2D cellular materials in silicon by sidewall transfer lithography NEMS

NASA Astrophysics Data System (ADS)

Syms, Richard R. A.; Liu, Dixi; Ahmad, Munir M.

2017-07-01

Sidewall transfer lithography (STL) is demonstrated as a method for parallel fabrication of 2D nanostructured cellular solids in single-crystal silicon. The linear mechanical properties of four lattices (perfect and defected diamond; singly and doubly periodic honeycomb) with low effective Young’s moduli and effective Poisson’s ratio ranging from positive to negative are modelled using analytic theory and the matrix stiffness method with an emphasis on boundary effects. The lattices are fabricated with a minimum feature size of 100 nm and an aspect ratio of 40:1 using single- and double-level STL and deep reactive ion etching of bonded silicon-on-insulator. Nanoelectromechanical systems (NEMS) containing cellular materials are used to demonstrate stretching, bending and brittle fracture. Predicted edge effects are observed, theoretical values of Poisson’s ratio are verified and failure patterns are described.

The topology of geology 1: Topological analysis

NASA Astrophysics Data System (ADS)

Thiele, Samuel T.; Jessell, Mark W.; Lindsay, Mark; Ogarko, Vitaliy; Wellmann, J. Florian; Pakyuz-Charrier, Evren

2016-10-01

Topology has been used to characterise and quantify the properties of complex systems in a diverse range of scientific domains. This study explores the concept and applications of topological analysis in geology. We have developed an automatic system for extracting first order 2D topological information from geological maps, and 3D topological information from models built with the Noddy kinematic modelling system, and equivalent analyses should be possible for other implicit modelling systems. A method is presented for describing the spatial and temporal topology of geological models using a set of adjacency relationships that can be expressed as a topology network, thematic adjacency matrix or hive diagram. We define three types of spatial topology (cellular, structural and lithological) that allow us to analyse different aspects of the geology, and then apply them to investigate the geology of the Hamersley Basin, Western Australia.

Reduced native state stability in crowded cellular environment due to protein-protein interactions.

PubMed

Harada, Ryuhei; Tochio, Naoya; Kigawa, Takanori; Sugita, Yuji; Feig, Michael

2013-03-06

The effect of cellular crowding environments on protein structure and stability is a key issue in molecular and cellular biology. The classical view of crowding emphasizes the volume exclusion effect that generally favors compact, native states. Here, results from molecular dynamics simulations and NMR experiments show that protein crowders may destabilize native states via protein-protein interactions. In the model system considered here, mixtures of villin head piece and protein G at high concentrations, villin structures become increasingly destabilized upon increasing crowder concentrations. The denatured states observed in the simulation involve partial unfolding as well as more subtle conformational shifts. The unfolded states remain overall compact and only partially overlap with unfolded ensembles at high temperature and in the presence of urea. NMR measurements on the same systems confirm structural changes upon crowding based on changes of chemical shifts relative to dilute conditions. An analysis of protein-protein interactions and energetic aspects suggests the importance of enthalpic and solvation contributions to the crowding free energies that challenge an entropic-centered view of crowding effects.

Geometric confinement influences cellular mechanical properties I -- adhesion area dependence.

PubMed

Su, Judith; Jiang, Xingyu; Welsch, Roy; Whitesides, George M; So, Peter T C

2007-06-01

Interactions between the cell and the extracellular matrix regulate a variety of cellular properties and functions, including cellular rheology. In the present study of cellular adhesion, area was controlled by confining NIH 3T3 fibroblast cells to circular micropatterned islands of defined size. The shear moduli of cells adhering to islands of well defined geometry, as measured by magnetic microrheometry, was found to have a significantly lower variance than those of cells allowed to spread on unpatterned surfaces. We observe that the area of cellular adhesion influences shear modulus. Rheological measurements further indicate that cellular shear modulus is a biphasic function of cellular adhesion area with stiffness decreasing to a minimum value for intermediate areas of adhesion, and then increasing for cells on larger patterns. We propose a simple hypothesis: that the area of adhesion affects cellular rheological properties by regulating the structure of the actin cytoskeleton. To test this hypothesis, we quantified the volume fraction of polymerized actin in the cytosol by staining with fluorescent phalloidin and imaging using quantitative 3D microscopy. The polymerized actin volume fraction exhibited a similar biphasic dependence on adhesion area. Within the limits of our simplifying hypothesis, our experimental results permit an evaluation of the ability of established, micromechanical models to predict the cellular shear modulus based on polymerized actin volume fraction. We investigated the "tensegrity", "cellular-solids", and "biopolymer physics" models that have, respectively, a linear, quadratic, and 5/2 dependence on polymerized actin volume fraction. All three models predict that a biphasic trend in polymerized actin volume fraction as a function of adhesion area will result in a biphasic behavior in shear modulus. Our data favors a higher-order dependence on polymerized actin volume fraction. Increasingly better experimental agreement is observed for the tensegrity, the cellular solids, and the biopolymer models respectively. Alternatively if we postulate the existence of a critical actin volume fraction below which the shear modulus vanishes, the experimental data can be equivalently described by a model with an almost linear dependence on polymerized actin volume fraction; this observation supports a tensegrity model with a critical actin volume fraction.

STEPS: efficient simulation of stochastic reaction-diffusion models in realistic morphologies.

PubMed

Hepburn, Iain; Chen, Weiliang; Wils, Stefan; De Schutter, Erik

2012-05-10

Models of cellular molecular systems are built from components such as biochemical reactions (including interactions between ligands and membrane-bound proteins), conformational changes and active and passive transport. A discrete, stochastic description of the kinetics is often essential to capture the behavior of the system accurately. Where spatial effects play a prominent role the complex morphology of cells may have to be represented, along with aspects such as chemical localization and diffusion. This high level of detail makes efficiency a particularly important consideration for software that is designed to simulate such systems. We describe STEPS, a stochastic reaction-diffusion simulator developed with an emphasis on simulating biochemical signaling pathways accurately and efficiently. STEPS supports all the above-mentioned features, and well-validated support for SBML allows many existing biochemical models to be imported reliably. Complex boundaries can be represented accurately in externally generated 3D tetrahedral meshes imported by STEPS. The powerful Python interface facilitates model construction and simulation control. STEPS implements the composition and rejection method, a variation of the Gillespie SSA, supporting diffusion between tetrahedral elements within an efficient search and update engine. Additional support for well-mixed conditions and for deterministic model solution is implemented. Solver accuracy is confirmed with an original and extensive validation set consisting of isolated reaction, diffusion and reaction-diffusion systems. Accuracy imposes upper and lower limits on tetrahedron sizes, which are described in detail. By comparing to Smoldyn, we show how the voxel-based approach in STEPS is often faster than particle-based methods, with increasing advantage in larger systems, and by comparing to MesoRD we show the efficiency of the STEPS implementation. STEPS simulates models of cellular reaction-diffusion systems with complex boundaries with high accuracy and high performance in C/C++, controlled by a powerful and user-friendly Python interface. STEPS is free for use and is available at http://steps.sourceforge.net/

STEPS: efficient simulation of stochastic reaction–diffusion models in realistic morphologies

PubMed Central

2012-01-01

Background Models of cellular molecular systems are built from components such as biochemical reactions (including interactions between ligands and membrane-bound proteins), conformational changes and active and passive transport. A discrete, stochastic description of the kinetics is often essential to capture the behavior of the system accurately. Where spatial effects play a prominent role the complex morphology of cells may have to be represented, along with aspects such as chemical localization and diffusion. This high level of detail makes efficiency a particularly important consideration for software that is designed to simulate such systems. Results We describe STEPS, a stochastic reaction–diffusion simulator developed with an emphasis on simulating biochemical signaling pathways accurately and efficiently. STEPS supports all the above-mentioned features, and well-validated support for SBML allows many existing biochemical models to be imported reliably. Complex boundaries can be represented accurately in externally generated 3D tetrahedral meshes imported by STEPS. The powerful Python interface facilitates model construction and simulation control. STEPS implements the composition and rejection method, a variation of the Gillespie SSA, supporting diffusion between tetrahedral elements within an efficient search and update engine. Additional support for well-mixed conditions and for deterministic model solution is implemented. Solver accuracy is confirmed with an original and extensive validation set consisting of isolated reaction, diffusion and reaction–diffusion systems. Accuracy imposes upper and lower limits on tetrahedron sizes, which are described in detail. By comparing to Smoldyn, we show how the voxel-based approach in STEPS is often faster than particle-based methods, with increasing advantage in larger systems, and by comparing to MesoRD we show the efficiency of the STEPS implementation. Conclusion STEPS simulates models of cellular reaction–diffusion systems with complex boundaries with high accuracy and high performance in C/C++, controlled by a powerful and user-friendly Python interface. STEPS is free for use and is available at http://steps.sourceforge.net/ PMID:22574658

Mapping human pluripotent stem cell differentiation pathways using high throughput single-cell RNA-sequencing.

PubMed

Han, Xiaoping; Chen, Haide; Huang, Daosheng; Chen, Huidong; Fei, Lijiang; Cheng, Chen; Huang, He; Yuan, Guo-Cheng; Guo, Guoji

2018-04-05

Human pluripotent stem cells (hPSCs) provide powerful models for studying cellular differentiations and unlimited sources of cells for regenerative medicine. However, a comprehensive single-cell level differentiation roadmap for hPSCs has not been achieved. We use high throughput single-cell RNA-sequencing (scRNA-seq), based on optimized microfluidic circuits, to profile early differentiation lineages in the human embryoid body system. We present a cellular-state landscape for hPSC early differentiation that covers multiple cellular lineages, including neural, muscle, endothelial, stromal, liver, and epithelial cells. Through pseudotime analysis, we construct the developmental trajectories of these progenitor cells and reveal the gene expression dynamics in the process of cell differentiation. We further reprogram primed H9 cells into naïve-like H9 cells to study the cellular-state transition process. We find that genes related to hemogenic endothelium development are enriched in naïve-like H9. Functionally, naïve-like H9 show higher potency for differentiation into hematopoietic lineages than primed cells. Our single-cell analysis reveals the cellular-state landscape of hPSC early differentiation, offering new insights that can be harnessed for optimization of differentiation protocols.

47 CFR 90.677 - Reconfiguration of the 806-824/851-869 MHz band in order to separate cellular systems from non...

Code of Federal Regulations, 2010 CFR

2010-10-01

... relocation agreement. Sprint Nextel and relocating incumbents may agree to conduct face-to-face negotiations...-55. Sprint Nextel and relocating incumbents may agree to conduct face-to-face negotiations or either... in order to separate cellular systems from non-cellular systems. 90.677 Section 90.677...

An engineering design approach to systems biology.

PubMed

Janes, Kevin A; Chandran, Preethi L; Ford, Roseanne M; Lazzara, Matthew J; Papin, Jason A; Peirce, Shayn M; Saucerman, Jeffrey J; Lauffenburger, Douglas A

2017-07-17

Measuring and modeling the integrated behavior of biomolecular-cellular networks is central to systems biology. Over several decades, systems biology has been shaped by quantitative biologists, physicists, mathematicians, and engineers in different ways. However, the basic and applied versions of systems biology are not typically distinguished, which blurs the separate aspirations of the field and its potential for real-world impact. Here, we articulate an engineering approach to systems biology, which applies educational philosophy, engineering design, and predictive models to solve contemporary problems in an age of biomedical Big Data. A concerted effort to train systems bioengineers will provide a versatile workforce capable of tackling the diverse challenges faced by the biotechnological and pharmaceutical sectors in a modern, information-dense economy.

Making classical ground-state spin computing fault-tolerant.

PubMed

Crosson, I J; Bacon, D; Brown, K R

2010-09-01

We examine a model of classical deterministic computing in which the ground state of the classical system is a spatial history of the computation. This model is relevant to quantum dot cellular automata as well as to recent universal adiabatic quantum computing constructions. In its most primitive form, systems constructed in this model cannot compute in an error-free manner when working at nonzero temperature. However, by exploiting a mapping between the partition function for this model and probabilistic classical circuits we are able to show that it is possible to make this model effectively error-free. We achieve this by using techniques in fault-tolerant classical computing and the result is that the system can compute effectively error-free if the temperature is below a critical temperature. We further link this model to computational complexity and show that a certain problem concerning finite temperature classical spin systems is complete for the complexity class Merlin-Arthur. This provides an interesting connection between the physical behavior of certain many-body spin systems and computational complexity.

Cellular Biochemistry and Cytogenetics in a Rat Lung Tumor Model

DTIC Science & Technology

1984-10-01

lung tumor system the specific aims are: 1. To conduct studies of the effect of 3-methylchlanthrene (MCA) on DNA synthesis and cell proliferation in...alkylation of nucleic acids of the rat by N-methyl-N- nitrosourea , dimethylnitrosamine, dimethylsulfate, and methylmethanesulfonate. Biochem. J. 110:39-47

Computational Systems Biology and Dose Response Modeling Workshop, September 22-26, 2008

EPA Science Inventory

The recently published National Academy of Sciences (NAS) report “Toxicity Testing in the 21st Century” recommends a new approach to toxicity testing, based on evaluating cellular responses in a suite of toxicity pathway assays in human cells or cells lines in vitro. Such a parad...

HIGH-THROUGHPUT CELLULAR ASSAYS FOR MODELING TOXICITY IN THE FISH REPRODUCTIVE SYSTEM

EPA Science Inventory

The most important benefit of this project is the experimental evaluation of all essential steps in the development and testing of adverse outcome pathways (AOP) for a diverse set of reproductive and non-reproductive toxicants. In contrast to human testing and the toxicity pat...

Comparative sensitivity of human and rat neural cultures to chemical-induced inhibition of neurite outgrowth

EPA Science Inventory

There is a need for rapid, efficient and cost effective alternatives to traditional in vivo developmental neurotoxicity testing. In vitro cell culture models can recapitulate many of the key cellular processes of nervous system development, including neurite outgrowth, and may be...

Cybernetics, Redux: An Outside-In Strategy for Unraveling Cellular Function.

PubMed

Malleshaiah, Mohan; Gunawardena, Jeremy

2016-01-11

A new paper in Science reveals how repetitive stimulation can identify and help to repair fragilities within a signaling network, while using linear mathematical models inspired by engineering, thereby suggesting how cybernetic methods can be integrated into systems and synthetic biology. Copyright © 2016 Elsevier Inc. All rights reserved.

Web-based applications for building, managing and analysing kinetic models of biological systems.

PubMed

Lee, Dong-Yup; Saha, Rajib; Yusufi, Faraaz Noor Khan; Park, Wonjun; Karimi, Iftekhar A

2009-01-01

Mathematical modelling and computational analysis play an essential role in improving our capability to elucidate the functions and characteristics of complex biological systems such as metabolic, regulatory and cell signalling pathways. The modelling and concomitant simulation render it possible to predict the cellular behaviour of systems under various genetically and/or environmentally perturbed conditions. This motivates systems biologists/bioengineers/bioinformaticians to develop new tools and applications, allowing non-experts to easily conduct such modelling and analysis. However, among a multitude of systems biology tools developed to date, only a handful of projects have adopted a web-based approach to kinetic modelling. In this report, we evaluate the capabilities and characteristics of current web-based tools in systems biology and identify desirable features, limitations and bottlenecks for further improvements in terms of usability and functionality. A short discussion on software architecture issues involved in web-based applications and the approaches taken by existing tools is included for those interested in developing their own simulation applications.

Comparison of mathematical models of fibrosis. Comment on "Towards a unified approach in the modeling of fibrosis: A review with research perspectives" by M. Ben Amar and C. Bianca

NASA Astrophysics Data System (ADS)

Kachapova, Farida

2016-07-01

Mathematical and computational models in biology and medicine help to improve diagnostics and medical treatments. Modeling of pathological fibrosis is reviewed by M. Ben Amar and C. Bianca in [4]. Pathological fibrosis is the process when excessive fibrous tissue is deposited on an organ or tissue during a wound healing and can obliterate their normal function. In [4] the phenomena of fibrosis are briefly explained including the causes, mechanism and management; research models of pathological fibrosis are described, compared and critically analyzed. Different models are suitable at different levels: molecular, cellular and tissue. The main goal of mathematical modeling of fibrosis is to predict long term behavior of the system depending on bifurcation parameters; there are two main trends: inhibition of fibrosis due to an active immune system and swelling of fibrosis because of a weak immune system.

System-level modeling of acetone-butanol-ethanol fermentation.

PubMed

Liao, Chen; Seo, Seung-Oh; Lu, Ting

2016-05-01

Acetone-butanol-ethanol (ABE) fermentation is a metabolic process of clostridia that produces bio-based solvents including butanol. It is enabled by an underlying metabolic reaction network and modulated by cellular gene regulation and environmental cues. Mathematical modeling has served as a valuable strategy to facilitate the understanding, characterization and optimization of this process. In this review, we highlight recent advances in system-level, quantitative modeling of ABE fermentation. We begin with an overview of integrative processes underlying the fermentation. Next we survey modeling efforts including early simple models, models with a systematic metabolic description, and those incorporating metabolism through simple gene regulation. Particular focus is given to a recent system-level model that integrates the metabolic reactions, gene regulation and environmental cues. We conclude by discussing the remaining challenges and future directions towards predictive understanding of ABE fermentation. © FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

cellPACK: A Virtual Mesoscope to Model and Visualize Structural Systems Biology

PubMed Central

Johnson, Graham T.; Autin, Ludovic; Al-Alusi, Mostafa; Goodsell, David S.; Sanner, Michel F.; Olson, Arthur J.

2014-01-01

cellPACK assembles computational models of the biological mesoscale, an intermediate scale (10−7–10−8m) between molecular and cellular biology. cellPACK’s modular architecture unites existing and novel packing algorithms to generate, visualize and analyze comprehensive 3D models of complex biological environments that integrate data from multiple experimental systems biology and structural biology sources. cellPACK is currently available as open source code, with tools for validation of models and with recipes and models for five biological systems: blood plasma, cytoplasm, synaptic vesicles, HIV and a mycoplasma cell. We have applied cellPACK to model distributions of HIV envelope protein to test several hypotheses for consistency with experimental observations. Biologists, educators, and outreach specialists can interact with cellPACK models, develop new recipes and perform packing experiments through scripting and graphical user interfaces at http://cellPACK.org. PMID:25437435

Network news: innovations in 21st century systems biology.

PubMed

Arkin, Adam P; Schaffer, David V

2011-03-18

A decade ago, seminal perspectives and papers set a strong vision for the field of systems biology, and a number of these themes have flourished. Here, we describe key technologies and insights that have elucidated the evolution, architecture, and function of cellular networks, ultimately leading to the first predictive genome-scale regulatory and metabolic models of organisms. Can systems approaches bridge the gap between correlative analysis and mechanistic insights? Copyright © 2011 Elsevier Inc. All rights reserved.

Developing the conceptual instructional design with inquiry-based instruction model of secondary students at the 10th grade level on digestion system and cellular degradation issue

NASA Astrophysics Data System (ADS)

Rotjanakunnatam, Boonthida; Chayaburakul, Kanokporn

2018-01-01

The aims of this research study was to develop the conceptual instructional design with the Inquiry-Based Instruction Model (IBIM) of secondary students at the 10th grade level on Digestion System and Cellular Degradation issue using both oxygen and oxygen-degrading cellular nutrients were designed instructional model with a sample size of 45 secondary students at the 10th Grade level. Data were collected by asking students to do a questionnaire pre and post learning processes. The questionnaire consists of two main parts that composed of students' perception questionnaire and the questionnaire that asked the question answer concept for the selected questionnaire. The 10-item Conceptual Thinking Test (CTT) was assessed students' conceptual thinking evaluation that it was covered in two main concepts, namely; Oxygen degradation nutrients and degradation nutrients without oxygen. The data by classifying students' answers into 5 groups and measuring them in frequency and a percentage of students' performances of their learning pre and post activities with the Inquiry-Based Instruction Model were analyzed as a tutorial. The results of this research found that: After the learning activities with the IBIM, most students developed concepts of both oxygen and oxygen-degrading cellular nutrients in the correct, complete and correct concept, and there are a number of students who have conceptual ideas in the wrong concept, and no concept was clearly reduced. However, the results are still found that; some students have some misconceptions, such as; the concept of direction of electron motion and formation of the ATP of bioactivities of life. This cause may come from the nature of the content, the complexity, the continuity, the movement, and the time constraints only in the classroom. Based on this research, it is suggested that some students may take some time, and the limited time in the classroom to their learning activity with content creation content binding and dramatic storytelling increases in a relaxed classroom learning environment.

Computational Modeling of Fluctuations in Energy and Metabolic Pathways of Methanogenic Archaea

DOE Office of Scientific and Technical Information (OSTI.GOV)

Luthey-Schulten, Zaida

The methanogenic archaea, anaerobic microbes that convert CO2 and H2 and/or other small organic fermentation products into methane, play an unusually large role in the global carbon cycle. As they perform the final step in the anaerobic breakdown of biomass, methanogens are a biogenic source of an estimated one billion tons methane each year. Depending on the location, produced methane can be considered as either a greenhouse gas (agricultural byproduct), sequestered carbon storage (methane hydrate deposits), or a potential energy source (organic wastewater treatment). These microbes therefore represent an important target for biotechnology applications. Computational models of methanogens with predictivemore » power are useful aids in the adaptation of methanogenic systems, but need to connect processes of wide-ranging time and length scales. In this project, we developed several computational methodologies for modeling the dynamic behavior of entire cells that connects stochastic reaction-diffusion dynamics of individual biochemical pathways with genome-scale modeling of metabolic networks. While each of these techniques were in the realm of well-defined computational methods, here we integrated them to develop several entirely new approaches to systems biology. The first scientific aim of the project was to model how noise in a biochemical pathway propagates into cellular phenotypes. Genetic circuits have been optimized by evolution to regulate molecular processes despite stochastic noise, but the effect of such noise on a cellular biochemical networks is currently unknown. An integrated stochastic/systems model of Escherichia coli species was created to analyze how noise in protein expression gives—and therefore noise in metabolic fluxes—gives rise to multiple cellular phenotype in isogenic population. After the initial work developing and validating methods that allow characterization of the heterogeneity in the model organism E. coli, the project shifted toward investigations of the methanogen Methanosarcina acetivorans. By integrating an unprecedented transcriptomics dataset for growth of the methanogen on many substrates with an in silico model, heterogeneity in metabolic pathway usage and methane production were examined. This lent insight into the physiological requirements of the organism under different environmental conditions and uncovered the unique regulatory role that mRNA half-life has in shaping metabolic flux distributions in this organism.« less

“Do-it-yourself in vitro vasculature that recapitulates in vivo geometries for investigating endothelial-blood cell interactions”

PubMed Central

Mannino, Robert G.; Myers, David R.; Ahn, Byungwook; Wang, Yichen; Margo Rollins; Gole, Hope; Lin, Angela S.; Guldberg, Robert E.; Giddens, Don P.; Timmins, Lucas H.; Lam, Wilbur A.

2015-01-01

Investigating biophysical cellular interactions in the circulation currently requires choosing between in vivo models, which are difficult to interpret due in part to the hemodynamic and geometric complexities of the vasculature; or in vitro systems, which suffer from non-physiologic assumptions and/or require specialized microfabrication facilities and expertise. To bridge that gap, we developed an in vitro “do-it-yourself” perfusable vasculature model that recapitulates in vivo geometries, such as aneurysms, stenoses, and bifurcations, and supports endothelial cell culture. These inexpensive, disposable devices can be created rapidly (<2 hours) with high precision and repeatability, using standard off-the-shelf laboratory supplies. Using these “endothelialized” systems, we demonstrate that spatial variation in vascular cell adhesion molecule (VCAM-1) expression correlates with the wall shear stress patterns of vascular geometries. We further observe that the presence of endothelial cells in stenoses reduces platelet adhesion but increases sickle cell disease (SCD) red blood cell (RBC) adhesion in bifurcations. Overall, our method enables researchers from all disciplines to study cellular interactions in physiologically relevant, yet simple-to-make, in vitro vasculature models. PMID:26202603

Coordination of frontline defense mechanisms under severe oxidative stress.

PubMed

Kaur, Amardeep; Van, Phu T; Busch, Courtney R; Robinson, Courtney K; Pan, Min; Pang, Wyming Lee; Reiss, David J; DiRuggiero, Jocelyne; Baliga, Nitin S

2010-07-01

Complexity of cellular response to oxidative stress (OS) stems from its wide-ranging damage to nucleic acids, proteins, carbohydrates, and lipids. We have constructed a systems model of OS response (OSR) for Halobacterium salinarum NRC-1 in an attempt to understand the architecture of its regulatory network that coordinates this complex response. This has revealed a multi-tiered OS-management program to transcriptionally coordinate three peroxidase/catalase enzymes, two superoxide dismutases, production of rhodopsins, carotenoids and gas vesicles, metal trafficking, and various other aspects of metabolism. Through experimental validation of interactions within the OSR regulatory network, we show that despite their inability to directly sense reactive oxygen species, general transcription factors have an important function in coordinating this response. Remarkably, a significant fraction of this OSR was accurately recapitulated by a model that was earlier constructed from cellular responses to diverse environmental perturbations--this constitutes the general stress response component. Notwithstanding this observation, comparison of the two models has identified the coordination of frontline defense and repair systems by regulatory mechanisms that are triggered uniquely by severe OS and not by other environmental stressors, including sub-inhibitory levels of redox-active metals, extreme changes in oxygen tension, and a sub-lethal dose of gamma rays.

Allosteric regulation of phosphofructokinase controls the emergence of glycolytic oscillations in isolated yeast cells.

PubMed

Gustavsson, Anna-Karin; van Niekerk, David D; Adiels, Caroline B; Kooi, Bob; Goksör, Mattias; Snoep, Jacky L

2014-06-01

Oscillations are widely distributed in nature and synchronization of oscillators has been described at the cellular level (e.g. heart cells) and at the population level (e.g. fireflies). Yeast glycolysis is the best known oscillatory system, although it has been studied almost exclusively at the population level (i.e. limited to observations of average behaviour in synchronized cultures). We studied individual yeast cells that were positioned with optical tweezers in a microfluidic chamber to determine the precise conditions for autonomous glycolytic oscillations. Hopf bifurcation points were determined experimentally in individual cells as a function of glucose and cyanide concentrations. The experiments were analyzed in a detailed mathematical model and could be interpreted in terms of an oscillatory manifold in a three-dimensional state-space; crossing the boundaries of the manifold coincides with the onset of oscillations and positioning along the longitudinal axis of the volume sets the period. The oscillatory manifold could be approximated by allosteric control values of phosphofructokinase for ATP and AMP. The mathematical models described here have been submitted to the JWS Online Cellular Systems Modelling Database and can be accessed at http://jjj.mib.ac.uk/webMathematica/UItester.jsp?modelName=gustavsson5. [Database section added 14 May 2014 after original online publication]. © 2014 FEBS.

Simulating the Conversion of Rural Settlements to Town Land Based on Multi-Agent Systems and Cellular Automata

PubMed Central

Liu, Yaolin; Kong, Xuesong; Liu, Yanfang; Chen, Yiyun

2013-01-01

Rapid urbanization in China has triggered the conversion of land from rural to urban use, particularly the conversion of rural settlements to town land. This conversion is the result of the joint effects of the geographic environment and agents involving the government, investors, and farmers. To understand the dynamic interaction dominated by agents and to predict the future landscape of town expansion, a small town land-planning model is proposed based on the integration of multi-agent systems (MAS) and cellular automata (CA). The MAS-CA model links the decision-making behaviors of agents with the neighbor effect of CA. The interaction rules are projected by analyzing the preference conflicts among agents. To better illustrate the effects of the geographic environment, neighborhood, and agent behavior, a comparative analysis between the CA and MAS-CA models in three different towns is presented, revealing interesting patterns in terms of quantity, spatial characteristics, and the coordinating process. The simulation of rural settlements conversion to town land through modeling agent decision and human-environment interaction is very useful for understanding the mechanisms of rural-urban land-use change in developing countries. This process can assist town planners in formulating appropriate development plans. PMID:24244472

Application of Petri Nets in Bone Remodeling

PubMed Central

Li, Lingxi; Yokota, Hiroki

2009-01-01

Understanding a mechanism of bone remodeling is a challenging task for both life scientists and model builders, since this highly interactive and nonlinear process can seldom be grasped by simple intuition. A set of ordinary differential equations (ODEs) have been built for simulating bone formation as well as bone resorption. Although solving ODEs numerically can provide useful predictions for dynamical behaviors in a continuous time frame, an actual bone remodeling process in living tissues is driven by discrete events of molecular and cellular interactions. Thus, an event-driven tool such as Petri nets (PNs), which may dynamically and graphically mimic individual molecular collisions or cellular interactions, seems to augment the existing ODE-based systems analysis. Here, we applied PNs to expand the ODE-based approach and examined discrete, dynamical behaviors of key regulatory molecules and bone cells. PNs have been used in many engineering areas, but their application to biological systems needs to be explored. Our PN model was based on 8 ODEs that described an osteoprotegerin linked molecular pathway consisting of 4 types of bone cells. The models allowed us to conduct both qualitative and quantitative evaluations and evaluate homeostatic equilibrium states. The results support that application of PN models assists understanding of an event-driven bone remodeling mechanism using PN-specific procedures such as places, transitions, and firings. PMID:19838338

Design mobile satellite system architecture as an integral part of the cellular access digital network

NASA Technical Reports Server (NTRS)

Chien, E. S. K.; Marinho, J. A.; Russell, J. E., Sr.

1988-01-01

The Cellular Access Digital Network (CADN) is the access vehicle through which cellular technology is brought into the mainstream of the evolving integrated telecommunications network. Beyond the integrated end-to-end digital access and per call network services provisioning of the Integrated Services Digital Network (ISDN), the CADN engenders the added capability of mobility freedom via wireless access. One key element of the CADN network architecture is the standard user to network interface that is independent of RF transmission technology. Since the Mobile Satellite System (MSS) is envisioned to not only complement but also enhance the capabilities of the terrestrial cellular telecommunications network, compatibility and interoperability between terrestrial cellular and mobile satellite systems are vitally important to provide an integrated moving telecommunications network of the future. From a network standpoint, there exist very strong commonalities between the terrestrial cellular system and the mobile satellite system. Therefore, the MSS architecture should be designed as an integral part of the CADN. This paper describes the concept of the CADN, the functional architecture of the MSS, and the user-network interface signaling protocols.

Bridging the gap between system and cell: The role of ultra-high field MRI in human neuroscience.

PubMed

Turner, Robert; De Haan, Daniel

2017-01-01

The volume of published research at the levels of systems and cellular neuroscience continues to increase at an accelerating rate. At the same time, progress in psychiatric medicine has stagnated and scientific confidence in cognitive psychology research is under threat due to careless analysis methods and underpowered experiments. With the advent of ultra-high field MRI, with submillimeter image voxels, imaging neuroscience holds the potential to bridge the cellular and systems levels. Use of these accurate and precisely localized quantitative measures of brain activity may go far in providing more secure foundations for psychology, and hence for more appropriate treatment and management of psychiatric illness. However, fundamental issues regarding the construction of testable mechanistic models using imaging data require careful consideration. This chapter summarizes the characteristics of acceptable models of brain function and provides concise descriptions of the relevant types of neuroimaging data that have recently become available. Approaches to data-driven experiments and analyses are described that may lead to more realistic conceptions of the competences of neural assemblages, as they vary across the brain's complex neuroanatomy. © 2017 Elsevier B.V. All rights reserved.

Systems-Level Analysis of Innate Immunity

PubMed Central

Zak, Daniel E.; Tam, Vincent C.; Aderem, Alan

2014-01-01

Systems-level analysis of biological processes strives to comprehensively and quantitatively evaluate the interactions between the relevant molecular components over time, thereby enabling development of models that can be employed to ultimately predict behavior. Rapid development in measurement technologies (omics), when combined with the accessible nature of the cellular constituents themselves, is allowing the field of innate immunity to take significant strides toward this lofty goal. In this review, we survey exciting results derived from systems biology analyses of the immune system, ranging from gene regulatory networks to influenza pathogenesis and systems vaccinology. PMID:24655298

Avians as a Model System of Vascular Development

PubMed Central

Bressan, Michael; Mikawa, Takashi

2015-01-01

Summary For more then 2000 years philosophers and scientists have turned to the avian embryo with questions of how life begins (Aristotle; Needham, 1959). Then, as now, the unique accessibility of the embryo both in terms of acquisition of eggs from domesticated fowl, and ease at which the embryo can be visualized by simply opening the shell, have made avians an appealing and powerful model system for the study of development. Thus, as the field of embryology has evolved through observational, comparative, and experimental embryology, into its current iteration as the cellular and molecular biology of development, avians have remained a useful and practical system of study. PMID:25468608

Toward metabolic engineering in the context of system biology and synthetic biology: advances and prospects.

PubMed

Liu, Yanfeng; Shin, Hyun-dong; Li, Jianghua; Liu, Long

2015-02-01

Metabolic engineering facilitates the rational development of recombinant bacterial strains for metabolite overproduction. Building on enormous advances in system biology and synthetic biology, novel strategies have been established for multivariate optimization of metabolic networks in ensemble, spatial, and dynamic manners such as modular pathway engineering, compartmentalization metabolic engineering, and metabolic engineering guided by genome-scale metabolic models, in vitro reconstitution, and systems and synthetic biology. Herein, we summarize recent advances in novel metabolic engineering strategies. Combined with advancing kinetic models and synthetic biology tools, more efficient new strategies for improving cellular properties can be established and applied for industrially important biochemical production.

Sub-cellular force microscopy in single normal and cancer cells.

PubMed

Babahosseini, H; Carmichael, B; Strobl, J S; Mahmoodi, S N; Agah, M

2015-08-07

This work investigates the biomechanical properties of sub-cellular structures of breast cells using atomic force microscopy (AFM). The cells are modeled as a triple-layered structure where the Generalized Maxwell model is applied to experimental data from AFM stress-relaxation tests to extract the elastic modulus, the apparent viscosity, and the relaxation time of sub-cellular structures. The triple-layered modeling results allow for determination and comparison of the biomechanical properties of the three major sub-cellular structures between normal and cancerous cells: the up plasma membrane/actin cortex, the mid cytoplasm/nucleus, and the low nuclear/integrin sub-domains. The results reveal that the sub-domains become stiffer and significantly more viscous with depth, regardless of cell type. In addition, there is a decreasing trend in the average elastic modulus and apparent viscosity of the all corresponding sub-cellular structures from normal to cancerous cells, which becomes most remarkable in the deeper sub-domain. The presented modeling in this work constitutes a unique AFM-based experimental framework to study the biomechanics of sub-cellular structures. Copyright © 2015 Elsevier Inc. All rights reserved.

A systemic approach to explore the flexibility of energy stores at the cellular scale: Examples from muscle cells.

PubMed

Taghipoor, Masoomeh; van Milgen, Jaap; Gondret, Florence

2016-09-07

Variations in energy storage and expenditure are key elements for animals adaptation to rapidly changing environments. Because of the multiplicity of metabolic pathways, metabolic crossroads and interactions between anabolic and catabolic processes within and between different cells, the flexibility of energy stores in animal cells is difficult to describe by simple verbal, textual or graphic terms. We propose a mathematical model to study the influence of internal and external challenges on the dynamic behavior of energy stores and its consequence on cell energy status. The role of the flexibility of energy stores on the energy equilibrium at the cellular level is illustrated through three case studies: variation in eating frequency (i.e., glucose input), level of physical activity (i.e., ATP requirement), and changes in cell characteristics (i.e., maximum capacity of glycogen storage). Sensitivity analysis has been performed to highlight the most relevant parameters of the model; model simulations have then been performed to illustrate how variation in these key parameters affects cellular energy balance. According to this analysis, glycogen maximum accumulation capacity and homeostatic energy demand are among the most important parameters regulating muscle cell metabolism to ensure its energy equilibrium. Copyright © 2016 Elsevier Ltd. All rights reserved.

LASSIE: simulating large-scale models of biochemical systems on GPUs.

PubMed

Tangherloni, Andrea; Nobile, Marco S; Besozzi, Daniela; Mauri, Giancarlo; Cazzaniga, Paolo

2017-05-10

Mathematical modeling and in silico analysis are widely acknowledged as complementary tools to biological laboratory methods, to achieve a thorough understanding of emergent behaviors of cellular processes in both physiological and perturbed conditions. Though, the simulation of large-scale models-consisting in hundreds or thousands of reactions and molecular species-can rapidly overtake the capabilities of Central Processing Units (CPUs). The purpose of this work is to exploit alternative high-performance computing solutions, such as Graphics Processing Units (GPUs), to allow the investigation of these models at reduced computational costs. LASSIE is a "black-box" GPU-accelerated deterministic simulator, specifically designed for large-scale models and not requiring any expertise in mathematical modeling, simulation algorithms or GPU programming. Given a reaction-based model of a cellular process, LASSIE automatically generates the corresponding system of Ordinary Differential Equations (ODEs), assuming mass-action kinetics. The numerical solution of the ODEs is obtained by automatically switching between the Runge-Kutta-Fehlberg method in the absence of stiffness, and the Backward Differentiation Formulae of first order in presence of stiffness. The computational performance of LASSIE are assessed using a set of randomly generated synthetic reaction-based models of increasing size, ranging from 64 to 8192 reactions and species, and compared to a CPU-implementation of the LSODA numerical integration algorithm. LASSIE adopts a novel fine-grained parallelization strategy to distribute on the GPU cores all the calculations required to solve the system of ODEs. By virtue of this implementation, LASSIE achieves up to 92× speed-up with respect to LSODA, therefore reducing the running time from approximately 1 month down to 8 h to simulate models consisting in, for instance, four thousands of reactions and species. Notably, thanks to its smaller memory footprint, LASSIE is able to perform fast simulations of even larger models, whereby the tested CPU-implementation of LSODA failed to reach termination. LASSIE is therefore expected to make an important breakthrough in Systems Biology applications, for the execution of faster and in-depth computational analyses of large-scale models of complex biological systems.

Parasitoid wasp venom SERCA regulates Drosophila calcium levels and inhibits cellular immunity.

PubMed

Mortimer, Nathan T; Goecks, Jeremy; Kacsoh, Balint Z; Mobley, James A; Bowersock, Gregory J; Taylor, James; Schlenke, Todd A

2013-06-04

Because parasite virulence factors target host immune responses, identification and functional characterization of these factors can provide insight into poorly understood host immune mechanisms. The fruit fly Drosophila melanogaster is a model system for understanding humoral innate immunity, but Drosophila cellular innate immune responses remain incompletely characterized. Fruit flies are regularly infected by parasitoid wasps in nature and, following infection, flies mount a cellular immune response culminating in the cellular encapsulation of the wasp egg. The mechanistic basis of this response is largely unknown, but wasps use a mixture of virulence proteins derived from the venom gland to suppress cellular encapsulation. To gain insight into the mechanisms underlying wasp virulence and fly cellular immunity, we used a joint transcriptomic/proteomic approach to identify venom genes from Ganaspis sp.1 (G1), a previously uncharacterized Drosophila parasitoid species, and found that G1 venom contains a highly abundant sarco/endoplasmic reticulum calcium ATPase (SERCA) pump. Accordingly, we found that fly immune cells termed plasmatocytes normally undergo a cytoplasmic calcium burst following infection, and that this calcium burst is required for activation of the cellular immune response. We further found that the plasmatocyte calcium burst is suppressed by G1 venom in a SERCA-dependent manner, leading to the failure of plasmatocytes to become activated and migrate toward G1 eggs. Finally, by genetically manipulating plasmatocyte calcium levels, we were able to alter fly immune success against G1 and other parasitoid species. Our characterization of parasitoid wasp venom proteins led us to identify plasmatocyte cytoplasmic calcium bursts as an important aspect of fly cellular immunity.

Engineering cellular fibers for musculoskeletal soft tissues using directed self-assembly.

PubMed

Schiele, Nathan R; Koppes, Ryan A; Chrisey, Douglas B; Corr, David T

2013-05-01

Engineering strategies guided by developmental biology may enhance and accelerate in vitro tissue formation for tissue engineering and regenerative medicine applications. In this study, we looked toward embryonic tendon development as a model system to guide our soft tissue engineering approach. To direct cellular self-assembly, we utilized laser micromachined, differentially adherent growth channels lined with fibronectin. The micromachined growth channels directed human dermal fibroblast cells to form single cellular fibers, without the need for a provisional three-dimensional extracellular matrix or scaffold to establish a fiber structure. Therefore, the resulting tissue structure and mechanical characteristics were determined solely by the cells. Due to the self-assembly nature of this approach, the growing fibers exhibit some key aspects of embryonic tendon development, such as high cellularity, the rapid formation (within 24 h) of a highly organized and aligned cellular structure, and the expression of cadherin-11 (indicating direct cell-to-cell adhesions). To provide a dynamic mechanical environment, we have also developed and characterized a method to apply precise cyclic tensile strain to the cellular fibers as they develop. After an initial period of cellular fiber formation (24 h postseeding), cyclic strain was applied for 48 h, in 8-h intervals, with tensile strain increasing from 0.7% to 1.0%, and at a frequency of 0.5 Hz. Dynamic loading dramatically increased cellular fiber mechanical properties with a nearly twofold increase in both the linear region stiffness and maximum load at failure, thereby demonstrating a mechanism for enhancing cellular fiber formation and mechanical properties. Tissue engineering strategies, designed to capture key aspects of embryonic development, may provide unique insight into accelerated maturation of engineered replacement tissue, and offer significant advances for regenerative medicine applications in tendon, ligament, and other fibrous soft tissues.