Cellular Particle Dynamics simulation of biomechanical relaxation processes of multi-cellular systems

Science.gov (United States)

McCune, Matthew; Kosztin, Ioan

2013-03-01

Cellular Particle Dynamics (CPD) is a theoretical-computational-experimental framework for describing and predicting the time evolution of biomechanical relaxation processes of multi-cellular systems, such as fusion, sorting and compression. 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 numerical integration of their equations of motion. Here we present CPD simulation results for the fusion of both spherical and cylindrical multi-cellular aggregates. First, we calibrate the relevant CPD model parameters for a given cell type by comparing the CPD simulation results for the fusion of two spherical aggregates to the corresponding experimental results. Next, CPD simulations are used to predict the time evolution of the fusion of cylindrical aggregates. The latter is relevant for the formation of tubular multi-cellular structures (i.e., primitive blood vessels) created by the novel bioprinting technology. Work supported by NSF [PHY-0957914]. Computer time provided by the University of Missouri Bioinformatics Consortium.

Cellular modelling of river catchments and reaches: Advantages, limitations and prospects

Science.gov (United States)

Coulthard, T. J.; Hicks, D. M.; Van De Wiel, M. J.

2007-10-01

The last decade has witnessed the development of a series of cellular models that simulate the processes operating within river channels and drive their geomorphic evolution. Their proliferation can be partly attributed to the relative simplicity of cellular models and their ability to address some of the shortcomings of other numerical models. By using relaxed interpretations of the equations determining fluid flow, cellular models allow rapid solutions of water depths and velocities. These can then be used to drive (usually) conventional sediment transport relations to determine erosion and deposition and alter the channel form. The key advance of using these physically based yet simplified approaches is that they allow us to apply models to a range of spatial scales (1-100 km 2) and time periods (1-100 years) that are especially relevant to contemporary management and fluvial studies. However, these approaches are not without their limitations and technical problems. This paper reviews the findings of nearly 10 years of research into modelling fluvial systems with cellular techniques, principally focusing on improvements in routing water and how fluvial erosion and deposition (including lateral erosion) are represented. These ideas are illustrated using sample simulations of the River Teifi, Wales. A detailed case study is then presented, demonstrating how cellular models can explore the interactions between vegetation and the morphological dynamics of the braided Waitaki River, New Zealand. Finally, difficulties associated with model validation and the problems, prospects and future issues important to the further development and application of these cellular fluvial models are outlined.

CELLULAR INTERACTIONS MEDIATED BY GLYCONECTIDS

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O.Popescu

1999-01-01

Full Text Available Cellular interactions involve many types of cell surface molecules and operate via homophilic and/or heterophilic protein-protein and protein-carbohydrate binding. Our investigations in different model-systems (marine invertebrates and mammals have provided direct evidence that a novel class of primordial proteoglycans, named by us gliconectins, can mediate cell adhesion via a new alternative molecular mechanism of polyvalent carbohydrate-carbohydrate binding. Biochemical characterization of isolated and purified glyconectins revealed the presence of specific carbohydrate structures, acidic glycans, different from classical glycosaminoglycans. Such acidic glycans of high molecular weight containing fucose, glucuronic or galacturonic acids, and sulfate groups, originally found in sponges and sea urchin embryos, may represent a new class of carbohydrate carcino-embryonal antigens in mice and humans. Such interactions between biological macromolecules are usually investigated by kinetic binding studies, calorimetric methods, X-ray diffraction, nuclear magnetic resonance, and other spectroscopic analyses. However, these methods do not supply a direct estimation of the intermolecular binding forces that are fundamental for the function of the ligand-receptor association. Recently, we have introduced atomic force microscopy to quantify the binding strength between cell adhesion proteoglycans. Measurement of binding forces intrinsic to cell adhesion proteoglycans is necessary to assess their contribution to the maintenance of the anatomical integrity of multicellular organisms. As a model, we selected the glyconectin 1, a cell adhesion proteoglycan isolated from the marine sponge Microciona prolifera. This glyconectin mediates in vivo cell recognition and aggregation via homophilic, species-specific, polyvalent, and calcium ion-dependent carbohydrate-carbohydrate interactions. Under physiological conditions, an adhesive force of up to 400 piconewtons

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

Science.gov (United States)

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.

Non-Chemical Distant Cellular Interactions as a potential confounder of Cell Biology Experiments

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Ashkan eFarhadi

2014-10-01

Full Text Available Distant cells can communicate with each other through a variety of methods. Two such methods involve electrical and/or chemical mechanisms. Non-chemical, distant cellular interactions may be another method of communication that cells can use to modify the behavior of other cells that are mechanically separated. Moreover, non-chemical, distant cellular interactions may explain some cases of confounding effects in Cell Biology experiments. In this article, we review non-chemical, distant cellular interactions studies to try to shed light on the mechanisms in this highly unconventional field of cell biology. Despite the existence of several theories that try to explain the mechanism of non-chemical, distant cellular interactions, this phenomenon is still speculative. Among candidate mechanisms, electromagnetic waves appear to have the most experimental support. In this brief article, we try to answer a few key questions that may further clarify this mechanism.

Effects of multiple enzyme–substrate interactions in basic units of cellular signal processing

International Nuclear Information System (INIS)

Seaton, D D; Krishnan, J

2012-01-01

Covalent modification cycles are a ubiquitous feature of cellular signalling networks. In these systems, the interaction of an active enzyme with the unmodified form of its substrate is essential for signalling to occur. However, this interaction is not necessarily the only enzyme–substrate interaction possible. In this paper, we analyse the behaviour of a basic model of signalling in which additional, non-essential enzyme–substrate interactions are possible. These interactions include those between the inactive form of an enzyme and its substrate, and between the active form of an enzyme and its product. We find that these additional interactions can result in increased sensitivity and biphasic responses, respectively. The dynamics of the responses are also significantly altered by the presence of additional interactions. Finally, we evaluate the consequences of these interactions in two variations of our basic model, involving double modification of substrate and scaffold-mediated signalling, respectively. We conclude that the molecular details of protein–protein interactions are important in determining the signalling properties of enzymatic signalling pathways. (paper)

Biomechanics and Thermodynamics of Nanoparticle Interactions with Plasma and Endosomal Membrane Lipids in Cellular Uptake and Endosomal Escape

Science.gov (United States)

2015-01-01

To be effective for cytoplasmic delivery of therapeutics, nanoparticles (NPs) taken up via endocytic pathways must efficiently transport across the cell membrane and subsequently escape from the secondary endosomes. We hypothesized that the biomechanical and thermodynamic interactions of NPs with plasma and endosomal membrane lipids are involved in these processes. Using model plasma and endosomal lipid membranes, we compared the interactions of cationic NPs composed of poly(d,l-lactide-co-glycolide) modified with the dichain surfactant didodecyldimethylammonium bromide (DMAB) or the single-chain surfactant cetyltrimethylammonium bromide (CTAB) vs anionic unmodified NPs of similar size. We validated our hypothesis in doxorubicin-sensitive (MCF-7, with relatively fluid membranes) and resistant breast cancer cells (MCF-7/ADR, with rigid membranes). Despite their cationic surface charges, DMAB- and CTAB-modified NPs showed different patterns of biophysical interaction: DMAB-modified NPs induced bending of the model plasma membrane, whereas CTAB-modified NPs condensed the membrane, thereby resisted bending. Unmodified NPs showed no effects on bending. DMAB-modified NPs also induced thermodynamic instability of the model endosomal membrane, whereas CTAB-modified and unmodified NPs had no effect. Since bending of the plasma membrane and destabilization of the endosomal membrane are critical biophysical processes in NP cellular uptake and endosomal escape, respectively, we tested these NPs for cellular uptake and drug efficacy. Confocal imaging showed that in both sensitive and resistant cells DMAB-modified NPs exhibited greater cellular uptake and escape from endosomes than CTAB-modified or unmodified NPs. Further, paclitaxel-loaded DMAB-modified NPs induced greater cytotoxicity even in resistant cells than CTAB-modified or unmodified NPs or drug in solution, demonstrating the potential of DMAB-modified NPs to overcome the transport barrier in resistant cells. In

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

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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. �

Multi-scale modeling in morphogenesis: a critical analysis of the cellular Potts model.

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Anja Voss-Böhme

Full Text Available 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.

Modeling cellular effects of coal pollutants

International Nuclear Information System (INIS)

Anon.

1981-01-01

The goal of this project is to develop and test models for the dose and dose-rate dependence of biological effects of coal pollutants on mammalian cells in tissue culture. Particular attention is given to the interaction of pollutants with the genetic material (deoxyribonucleic acid, or NDA) in the cell. Unlike radiation, which can interact directly with chromatin, chemical pollutants undergo numerous changes before the ultimate carcinogen becomes covalently bound to the DNA. Synthetic vesicles formed from a phospholipid bilayer are being used to investigate chemical transformations that may occur during the transport of pollutants across cellular membranes. The initial damage to DNA is rapidly modified by enzymatic repair systems in most living organisms. A model has been developed for predicting the effects of excision repair on the survival of human cells exposed to chemical carcinogens. In addition to the excision system, normal human cells also have tolerance mechanisms that permit continued growth and division of cells without removal of the damage. We are investigating the biological effect of damage passed to daughter cells by these tolerance mechanisms

A dynamic cellular vertex model of growing epithelial tissues

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Lin, Shao-Zhen; Li, Bo; Feng, Xi-Qiao

2017-04-01

Intercellular interactions play a significant role in a wide range of biological functions and processes at both the cellular and tissue scales, for example, embryogenesis, organogenesis, and cancer invasion. In this paper, a dynamic cellular vertex model is presented to study the morphomechanics of a growing epithelial monolayer. The regulating role of stresses in soft tissue growth is revealed. It is found that the cells originating from the same parent cell in the monolayer can orchestrate into clustering patterns as the tissue grows. Collective cell migration exhibits a feature of spatial correlation across multiple cells. Dynamic intercellular interactions can engender a variety of distinct tissue behaviors in a social context. Uniform cell proliferation may render high and heterogeneous residual compressive stresses, while stress-regulated proliferation can effectively release the stresses, reducing the stress heterogeneity in the tissue. The results highlight the critical role of mechanical factors in the growth and morphogenesis of epithelial tissues and help understand the development and invasion of epithelial tumors.

Interactive instruction of cellular physiology for remote learning.

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Huang, C; Huang, H K

2003-12-01

The biomedical sciences are a rapidly changing discipline that have adapted to innovative technological advances. Despite these many advances, we face two major challenges: a) the number of experts in the field is vastly outnumbered by the number of students, many of whom are separated geographically or temporally and b) the teaching methods used to instruct students and learners have not changed. Today's students have adapted to technology--they use the web as a source of information and communicate via email and chat rooms. Teaching in the biomedical sciences should adopt these new information technologies (IT), but has thus far failed to capitalize on technological opportunity. Creating a "digital textbook" of the traditional learning material is not sufficient for dynamic processes such as cellular physiology. This paper describes innovative teaching techniques that incorporate familiar IT and high-quality interactive learning content with user-centric instruction design models. The Virtual Labs Project from Stanford University has created effective interactive online teaching modules in physiology (simPHYSIO) and delivered them over broadband networks to their undergraduate and medical students. Evaluation results of the modules are given as a measure of success of such innovative teaching method. This learning media strategically merges IT innovations with pedagogy to produce user-driven animations of processes and engaging interactive simulations.

Cosserat modeling of cellular solids

NARCIS (Netherlands)

Onck, P.R.

Cellular solids inherit their macroscopic mechanical properties directly from the cellular microstructure. However, the characteristic material length scale is often not small compared to macroscopic dimensions, which limits the applicability of classical continuum-type constitutive models. Cosserat

Generation and comprehensive analysis of an influenza virus polymerase cellular interaction network.

Science.gov (United States)

Tafforeau, Lionel; Chantier, Thibault; Pradezynski, Fabrine; Pellet, Johann; Mangeot, Philippe E; Vidalain, Pierre-Olivier; Andre, Patrice; Rabourdin-Combe, Chantal; Lotteau, Vincent

2011-12-01

The influenza virus transcribes and replicates its genome inside the nucleus of infected cells. Both activities are performed by the viral RNA-dependent RNA polymerase that is composed of the three subunits PA, PB1, and PB2, and recent studies have shown that it requires host cell factors to transcribe and replicate the viral genome. To identify these cellular partners, we generated a comprehensive physical interaction map between each polymerase subunit and the host cellular proteome. A total of 109 human interactors were identified by yeast two-hybrid screens, whereas 90 were retrieved by literature mining. We built the FluPol interactome network composed of the influenza virus polymerase (PA, PB1, and PB2) and the nucleoprotein NP and 234 human proteins that are connected through 279 viral-cellular protein interactions. Analysis of this interactome map revealed enriched cellular functions associated with the influenza virus polymerase, including host factors involved in RNA polymerase II-dependent transcription and mRNA processing. We confirmed that eight influenza virus polymerase-interacting proteins are required for virus replication and transcriptional activity of the viral polymerase. These are involved in cellular transcription (C14orf166, COPS5, MNAT1, NMI, and POLR2A), translation (EIF3S6IP), nuclear transport (NUP54), and DNA repair (FANCG). Conversely, we identified PRKRA, which acts as an inhibitor of the viral polymerase transcriptional activity and thus is required for the cellular antiviral response.

Cellular modeling of fault-tolerant multicomputers

Energy Technology Data Exchange (ETDEWEB)

Morgan, G

1987-01-01

Work described was concerned with a novel method for investigation of fault tolerance in large regular networks of computers. Motivation was to provide a technique useful in rapid evaluation of highly reliable systems that exploit the low cost and ease of volume production of simple microcomputer components. First, a system model and simulator based upon cellular automata are developed. This model is characterized by its simplicity and ease of modification when adapting to new types of network. Second, in order to test and verify the predictive capabilities of the cellular system, a more-detailed simulation is performed based upon an existing computational model, that of the Transputer. An example application is used to exercise various systems designed using the cellular model. Using this simulator, experimental results are obtained both for existing well-understood configurations and for more novel types also developed here. In all cases it was found that the cellular model and simulator successfully predicted the ranking in reliability improvement of the systems studied.

Protein-protein interactions within the ensemble, eukaryotic V-ATPase, and its concerted interactions with cellular machineries.

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Balakrishna, Asha Manikkoth; Manimekalai, Malathy Sony Subramanian; Grüber, Gerhard

2015-10-01

The V1VO-ATPase (V-ATPase) is the important proton-pump in eukaryotic cells, responsible for pH-homeostasis, pH-sensing and amino acid sensing, and therefore essential for cell growths and metabolism. ATP-cleavage in the catalytic A3B3-hexamer of V1 has to be communicated via several so-called central and peripheral stalk units to the proton-pumping VO-part, which is membrane-embedded. A unique feature of V1VO-ATPase regulation is its reversible disassembly of the V1 and VO domain. Actin provides a network to hold the V1 in proximity to the VO, enabling effective V1VO-assembly to occur. Besides binding to actin, the 14-subunit V-ATPase interacts with multi-subunit machineries to form cellular sensors, which regulate the pH in cellular compartments or amino acid signaling in lysosomes. Here we describe a variety of subunit-subunit interactions within the V-ATPase enzyme during catalysis and its protein-protein assembling with key cellular machineries, essential for cellular function. Copyright © 2015 Elsevier Ltd. All rights reserved.

Cellular and molecular interaction in HIV infection: A review | Timbo ...

African Journals Online (AJOL)

Objective: To review the cellular and molecular interactions between HIV and the host immune system that lead to full-blown AIDS. Data Sources: Published reports on HIV/host interaction during a fifteen year period beginning from 1987. Study selection: Only those studies involving humans and non-human primates were ...

Species as Stressors: Heterospecific Interactions and the Cellular Stress Response under Global Change.

Science.gov (United States)

Gunderson, Alex R; King, Emily E; Boyer, Kirsten; Tsukimura, Brian; Stillman, Jonathon H

2017-07-01

Anthropogenic global change is predicted to increase the physiological stress of organisms through changes in abiotic conditions such as temperature, pH, and pollution. However, organisms can also experience physiological stress through interactions with other species, especially parasites, predators, and competitors. The stress of species interactions could be an important driver of species' responses to global change as the composition of biological communities change through factors such as distributional and phenological shifts. Interactions between biotic and abiotic stressors could also induce non-linear physiological stress responses under global change. One of the primary means by which organisms deal with physiological stress is through the cellular stress response (CSR), which is broadly the upregulation of a conserved set of genes that facilitate the removal and repair of damaged macromolecules. Here, we present data on behavioral interactions and CSR gene expression for two competing species of intertidal zone porcelain crab (Petrolisthes cinctipes and Petrolisthes manimaculis). We found that P. cinctipes and P. manimaculis engage in more agonistic behaviors when interacting with heterospecifics than conspecifics; however, we found no evidence that heterospecific interactions induced a CSR in these species. In addition to our new data, we review the literature with respect to CSR induction via species interactions, focusing on predator-prey systems and heterospecific competition. We find extensive evidence for predators to induce cellular stress and aspects of the CSR in prey, even in the absence of direct physical contact between species. Effects of heterospecific competition on the CSR have been studied far less, but we do find evidence that agonistic interactions with heterospecifics can induce components of the CSR. Across all published studies, there is clear evidence that species interactions can lead to cellular stress and induction of the CSR

Cellular automata models for diffusion of information and highway traffic flow

Science.gov (United States)

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

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

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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.

Fractal growth of tumors and other cellular populations: Linking the mechanistic to the phenomenological modeling and vice versa

International Nuclear Information System (INIS)

D'Onofrio, Alberto

2009-01-01

In this paper we study and extend the mechanistic mean field theory of growth of cellular populations proposed by Mombach et al. [Mombach JCM, Lemke N, Bodmann BEJ, Idiart MAP. A mean-field theory of cellular growth. Europhys Lett 2002;59:923-928] (MLBI model), and we demonstrate that the original model and our generalizations lead to inferences of biological interest. In the first part of this paper, we show that the model in study is widely general since it admits, as particular cases, the main phenomenological models of cellular growth. In the second part of this work, we generalize the MLBI model to a wider family of models by allowing the cells to have a generic unspecified biologically plausible interaction. Then, we derive a relationship between this generic microscopic interaction function and the growth rate of the corresponding macroscopic model. Finally, we propose to use this relationship in order to help the investigation of the biological plausibility of phenomenological models of cancer growth.

Guided Inquiry and Consensus-Building Used to Construct Cellular Models

Directory of Open Access Journals (Sweden)

Joel I. Cohen

2015-02-01

Full Text Available Using models helps students learn from a “whole systems” perspective when studying the cell. This paper describes a model that employs guided inquiry and requires consensus building among students for its completion. The model is interactive, meaning that it expands upon a static model which, once completed, cannot be altered and additionally relates various levels of biological organization (molecular, organelle, and cellular to define cell and organelle function and interaction. Learning goals are assessed using data summed from final grades and from images of the student’s final cell model (plant, bacteria, and yeast taken from diverse seventh grade classes. Instructional figures showing consensus-building pathways and seating arrangements are discussed. Results suggest that the model leads to a high rate of participation, facilitates guided inquiry, and fosters group and individual exploration by challenging student understanding of the living cell.

Modelling the structure of a ceRNA-theoretical, bipartite microRNA-mRNA interaction network regulating intestinal epithelial cellular pathways using R programming.

Science.gov (United States)

Robinson, J M; Henderson, W A

2018-01-12

We report a method using functional-molecular databases and network modelling to identify hypothetical mRNA-miRNA interaction networks regulating intestinal epithelial barrier function. The model forms a data-analysis component of our cell culture experiments, which produce RNA expression data from Nanostring Technologies nCounter ® system. The epithelial tight-junction (TJ) and actin cytoskeleton interact as molecular components of the intestinal epithelial barrier. Upstream regulation of TJ-cytoskeleton interaction is effected by the Rac/Rock/Rho signaling pathway and other associated pathways which may be activated or suppressed by extracellular signaling from growth factors, hormones, and immune receptors. Pathway activations affect epithelial homeostasis, contributing to degradation of the epithelial barrier associated with osmotic dysregulation, inflammation, and tumor development. The complexity underlying miRNA-mRNA interaction networks represents a roadblock for prediction and validation of competing-endogenous RNA network function. We developed a network model to identify hypothetical co-regulatory motifs in a miRNA-mRNA interaction network related to epithelial function. A mRNA-miRNA interaction list was generated using KEGG and miRWalk2.0 databases. R-code was developed to quantify and visualize inherent network structures. We identified a sub-network with a high number of shared, targeting miRNAs, of genes associated with cellular proliferation and cancer, including c-MYC and Cyclin D.

The Bioavailability of Soluble Cigarette Smoke Extract Is Reduced through Interactions with Cells and Affects the Cellular Response to CSE Exposure.

Science.gov (United States)

Bourgeois, Jeffrey S; Jacob, Jeeva; Garewal, Aram; Ndahayo, Renata; Paxson, Julia

2016-01-01

Cellular exposure to cigarette smoke leads to an array of complex responses including apoptosis, cellular senescence, telomere dysfunction, cellular aging, and neoplastic transformation. To study the cellular response to cigarette smoke, a common in vitro model exposes cultured cells to a nominal concentration (i.e. initial concentration) of soluble cigarette smoke extract (CSE). However, we report that use of the nominal concentration of CSE as the only measure of cellular exposure is inadequate. Instead, we demonstrate that cellular response to CSE exposure is dependent not only on the nominal concentration of CSE, but also on specific experimental variables, including the total cell number, and the volume of CSE solution used. As found in other similar xenobiotic assays, our work suggests that the effective dose of CSE is more accurately related to the amount of bioavailable chemicals per cell. In particular, interactions of CSE components both with cells and other physical factors limit CSE bioavailability, as demonstrated by a quantifiably reduced cellular response to CSE that is first modified by such interactions. This has broad implications for the nature of cellular response to CSE exposure, and for the design of in vitro assays using CSE.

Parallel Genetic Algorithms for calibrating Cellular Automata models: Application to lava flows

International Nuclear Information System (INIS)

D'Ambrosio, D.; Spataro, W.; Di Gregorio, S.; Calabria Univ., Cosenza; Crisci, G.M.; Rongo, R.; Calabria Univ., Cosenza

2005-01-01

Cellular Automata are highly nonlinear dynamical systems which are suitable far simulating natural phenomena whose behaviour may be specified in terms of local interactions. The Cellular Automata model SCIARA, developed far the simulation of lava flows, demonstrated to be able to reproduce the behaviour of Etnean events. However, in order to apply the model far the prediction of future scenarios, a thorough calibrating phase is required. This work presents the application of Genetic Algorithms, general-purpose search algorithms inspired to natural selection and genetics, far the parameters optimisation of the model SCIARA. Difficulties due to the elevated computational time suggested the adoption a Master-Slave Parallel Genetic Algorithm far the calibration of the model with respect to the 2001 Mt. Etna eruption. Results demonstrated the usefulness of the approach, both in terms of computing time and quality of performed simulations

Cellular Automata for Modeling the field-scale erosion

International Nuclear Information System (INIS)

Diaz Suarez, Jorge; Bagarotti Marin, Angel; Ruiz Perez, Maria Elena

2008-01-01

Full text: The Cellular Automaton (CA) is a system used discrete dynamic modeling of many physical systems. Their fundamental properties are the interaction at the local level, homogeneity and parallelism. It has been used as a secondary for the simulation of large systems where the use of equations in partial derivatives is complex and costly from the computational point of view. On the other hand, the high complexity of spatial interaction in the processes involved in the erosion-transport-deposition of sediments at field level, considerably limiting the use of base models physics. The objective of this study is to model the main processes involved in erosion water supply of soils through the use of the CAMELot system, based on an extension of the original paradigm of the CA. The CAMELot system has been used in the simulation of systems of large spatial extent, where the laws of local interaction between automata have a deep physical sense. This system guarantees both the input of the necessary specifications and simulation in parallel, as the visualization and the general management of the system. They are exposed to each of the submodels used in it and the overall dynamics of the system is analyzed. (author)

Dynamic behavior of cellular materials and cellular structures: Experiments and modeling

Science.gov (United States)

Gao, Ziyang

Cellular solids, including cellular materials and cellular structures (CMS), have attracted people's great interests because of their low densities and novel physical, mechanical, thermal, electrical and acoustic properties. They offer potential for lightweight structures, energy absorption, thermal management, etc. Therefore, the studies of cellular solids have become one of the hottest research fields nowadays. From energy absorption point of view, any plastically deformed structures can be divided into two types (called type I and type II), and the basic cells of the CMS may take the configurations of these two types of structures. Accordingly, separated discussions are presented in this thesis. First, a modified 1-D model is proposed and numerically solved for a typical type II structure. Good agreement is achieved with the previous experimental data, hence is used to simulate the dynamic behavior of a type II chain. Resulted from different load speeds, interesting collapse modes are observed, and the parameters which govern the cell's post-collapse behavior are identified through a comprehensive non-dimensional analysis on general cellular chains. Secondly, the MHS specimens are chosen as an example of type I foam materials because of their good uniformity of the cell geometry. An extensive experimental study was carried out, where more attention was paid to their responses to dynamic loadings. Great enhancement of the stress-strain curve was observed in dynamic cases, and the energy absorption capacity is found to be several times higher than that of the commercial metal foams. Based on the experimental study, finite elemental simulations and theoretical modeling are also conducted, achieving good agreements and demonstrating the validities of those models. It is believed that the experimental, numerical and analytical results obtained in the present study will certainly deepen the understanding of the unsolved fundamental issues on the mechanical behavior of

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

Science.gov (United States)

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 potts models multiscale extensions and biological applications

CERN Document Server

Scianna, Marco

2013-01-01

A flexible, cell-level, and lattice-based technique, the cellular Potts model accurately describes the phenomenological mechanisms involved in many biological processes. Cellular Potts Models: Multiscale Extensions and Biological Applications gives an interdisciplinary, accessible treatment of these models, from the original methodologies to the latest developments. The book first explains the biophysical bases, main merits, and limitations of the cellular Potts model. It then proposes several innovative extensions, focusing on ways to integrate and interface the basic cellular Potts model at the mesoscopic scale with approaches that accurately model microscopic dynamics. These extensions are designed to create a nested and hybrid environment, where the evolution of a biological system is realistically driven by the constant interplay and flux of information between the different levels of description. Through several biological examples, the authors demonstrate a qualitative and quantitative agreement with t...

Generation and Comprehensive Analysis of an Influenza Virus Polymerase Cellular Interaction Network▿†§

Science.gov (United States)

Tafforeau, Lionel; Chantier, Thibault; Pradezynski, Fabrine; Pellet, Johann; Mangeot, Philippe E.; Vidalain, Pierre-Olivier; Andre, Patrice; Rabourdin-Combe, Chantal; Lotteau, Vincent

2011-01-01

The influenza virus transcribes and replicates its genome inside the nucleus of infected cells. Both activities are performed by the viral RNA-dependent RNA polymerase that is composed of the three subunits PA, PB1, and PB2, and recent studies have shown that it requires host cell factors to transcribe and replicate the viral genome. To identify these cellular partners, we generated a comprehensive physical interaction map between each polymerase subunit and the host cellular proteome. A total of 109 human interactors were identified by yeast two-hybrid screens, whereas 90 were retrieved by literature mining. We built the FluPol interactome network composed of the influenza virus polymerase (PA, PB1, and PB2) and the nucleoprotein NP and 234 human proteins that are connected through 279 viral-cellular protein interactions. Analysis of this interactome map revealed enriched cellular functions associated with the influenza virus polymerase, including host factors involved in RNA polymerase II-dependent transcription and mRNA processing. We confirmed that eight influenza virus polymerase-interacting proteins are required for virus replication and transcriptional activity of the viral polymerase. These are involved in cellular transcription (C14orf166, COPS5, MNAT1, NMI, and POLR2A), translation (EIF3S6IP), nuclear transport (NUP54), and DNA repair (FANCG). Conversely, we identified PRKRA, which acts as an inhibitor of the viral polymerase transcriptional activity and thus is required for the cellular antiviral response. PMID:21994455

Cationic liposome/DNA complexes: from structure to interactions with cellular membranes.

Science.gov (United States)

Caracciolo, Giulio; Amenitsch, Heinz

2012-10-01

Gene-based therapeutic approaches are based upon the concept that, if a disease is caused by a mutation in a gene, then adding back the wild-type gene should restore regular function and attenuate the disease phenotype. To deliver the gene of interest, both viral and nonviral vectors are used. Viruses are efficient, but their application is impeded by detrimental side-effects. Among nonviral vectors, cationic liposomes are the most promising candidates for gene delivery. They form stable complexes with polyanionic DNA (lipoplexes). Despite several advantages over viral vectors, the transfection efficiency (TE) of lipoplexes is too low compared with those of engineered viral vectors. This is due to lack of knowledge about the interactions between complexes and cellular components. Rational design of efficient lipoplexes therefore requires deeper comprehension of the interactions between the vector and the DNA as well as the cellular pathways and mechanisms involved. The importance of the lipoplex structure in biological function is revealed in the application of synchrotron small-angle X-ray scattering in combination with functional TE measurements. According to current understanding, the structure of lipoplexes can change upon interaction with cellular membranes and such changes affect the delivery efficiency. Recently, a correlation between the mechanism of gene release from complexes, the structure, and the physical and chemical parameters of the complexes has been established. Studies aimed at correlating structure and activity of lipoplexes are reviewed herein. This is a fundamental step towards rational design of highly efficient lipid gene vectors.

Extended Cellular Automata Models of Particles and Space-Time

Science.gov (United States)

Beedle, Michael

2005-04-01

Models of particles and space-time are explored through simulations and theoretical models that use Extended Cellular Automata models. The expanded Cellular Automata Models consist go beyond simple scalar binary cell-fields, into discrete multi-level group representations like S0(2), SU(2), SU(3), SPIN(3,1). The propagation and evolution of these expanded cellular automatas are then compared to quantum field theories based on the "harmonic paradigm" i.e. built by an infinite number of harmonic oscillators, and with gravitational models.

Modeling mechanical interactions in growing populations of rod-shaped bacteria

Science.gov (United States)

Winkle, James J.; Igoshin, Oleg A.; Bennett, Matthew R.; Josić, Krešimir; Ott, William

2017-10-01

Advances in synthetic biology allow us to engineer bacterial collectives with pre-specified characteristics. However, the behavior of these collectives is difficult to understand, as cellular growth and division as well as extra-cellular fluid flow lead to complex, changing arrangements of cells within the population. To rationally engineer and control the behavior of cell collectives we need theoretical and computational tools to understand their emergent spatiotemporal dynamics. Here, we present an agent-based model that allows growing cells to detect and respond to mechanical interactions. Crucially, our model couples the dynamics of cell growth to the cell’s environment: Mechanical constraints can affect cellular growth rate and a cell may alter its behavior in response to these constraints. This coupling links the mechanical forces that influence cell growth and emergent behaviors in cell assemblies. We illustrate our approach by showing how mechanical interactions can impact the dynamics of bacterial collectives growing in microfluidic traps.

Cellular automaton model of coupled mass transport and chemical reactions

International Nuclear Information System (INIS)

Karapiperis, T.

1994-01-01

Mass transport, coupled with chemical reactions, is modelled as a cellular automaton in which solute molecules perform a random walk on a lattice and react according to a local probabilistic rule. Assuming molecular chaos and a smooth density function, we obtain the standard reaction-transport equations in the continuum limit. The model is applied to the reactions a + b ↔c and a + b →c, where we observe interesting macroscopic effects resulting from microscopic fluctuations and spatial correlations between molecules. We also simulate autocatalytic reaction schemes displaying spontaneous formation of spatial concentration patterns. Finally, we propose and discuss the limitations of a simple model for mineral-solute interaction. (author) 5 figs., 20 refs

Acanthamoeba and Dictyostelium as Cellular Models for Legionella Infection

Science.gov (United States)

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

Acanthamoeba and Dictyostelium as Cellular Models for Legionella Infection

Directory of Open Access Journals (Sweden)

A. Leoni Swart

2018-03-01

Full Text Available 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.

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

Science.gov (United States)

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

Cellular-automata supercomputers for fluid-dynamics modeling

International Nuclear Information System (INIS)

Margolus, N.; Toffoli, T.; Vichniac, G.

1986-01-01

We report recent developments in the modeling of fluid dynamics, and give experimental results (including dynamical exponents) obtained using cellular automata machines. Because of their locality and uniformity, cellular automata lend themselves to an extremely efficient physical realization; with a suitable architecture, an amount of hardware resources comparable to that of a home computer can achieve (in the simulation of cellular automata) the performance of a conventional supercomputer

Cellular mechanisms in drug - radiation interaction

International Nuclear Information System (INIS)

Trott, K.R.

1979-01-01

Some cytotoxic drugs, especially those belonging to the group of antibiotics and antimetabolites, sensitize the cells having survived drug treatment to the subsequent irradiation by either increasing the slope of the radiation dose response curves or by decreasing extrapolation number. Bleomycin was found to interact with radiation in L-cells and FM3A cells, but not in HeLa-cells. The data with EMT-6 cells suggest that the interaction depends on drug dose: no interaction occurred after the exposure to bleomycin which killed only 20 - 40% of the cells; yet the exposure to bleomycin which killed 90% of the cells in addition sensitized the surviving cells by the DMF of 1.3. The sensitization found 24 hr after the exposure of HeLa cells to methotrexate was due to cell synchronization. Other cytostatic drugs were found to synchronize proliferating cells even better. Therefore, the fluctuation of radiosensitivity has been commonly observed after the termination of exposure to these drugs. Preirradiation may lead to the change in drug dose response curves. The recruitment of resting cells into cycle occurs hours or days later, in some irradiated normal and malignant tissues. Since many cytostatic drugs are far more active in proliferating cells than in resting cells, the recruitment after irradiation may lead to the sudden increase in drug sensitivity, days after the irradiation. No single, simple theory seems to exist to classify and predict the cellular response to combined modality treatment. (Yamashita, S.)

An integrated approach to elucidate the intra-viral and viral-cellular protein interaction networks of a gamma-herpesvirus.

Directory of Open Access Journals (Sweden)

Shaoying Lee

2011-10-01

Full Text Available Genome-wide yeast two-hybrid (Y2H screens were conducted to elucidate the molecular functions of open reading frames (ORFs encoded by murine γ-herpesvirus 68 (MHV-68. A library of 84 MHV-68 genes and gene fragments was generated in a Gateway entry plasmid and transferred to Y2H vectors. All possible pair-wise interactions between viral proteins were tested in the Y2H assay, resulting in the identification of 23 intra-viral protein-protein interactions (PPIs. Seventy percent of the interactions between viral proteins were confirmed by co-immunoprecipitation experiments. To systematically investigate virus-cellular protein interactions, the MHV-68 Y2H constructs were screened against a cellular cDNA library, yielding 243 viral-cellular PPIs involving 197 distinct cellar proteins. Network analyses indicated that cellular proteins targeted by MHV-68 had more partners in the cellular PPI network and were located closer to each other than expected by chance. Taking advantage of this observation, we scored the cellular proteins based on their network distances from other MHV-68-interacting proteins and segregated them into high (Y2H-HP and low priority/not-scored (Y2H-LP/NS groups. Significantly more genes from Y2H-HP altered MHV-68 replication when their expression was inhibited with siRNAs (53% of genes from Y2H-HP, 21% of genes from Y2H-LP/NS, and 16% of genes randomly chosen from the human PPI network; p<0.05. Enriched Gene Ontology (GO terms in the Y2H-HP group included regulation of apoptosis, protein kinase cascade, post-translational protein modification, transcription from RNA polymerase II promoter, and IκB kinase/NFκB cascade. Functional validation assays indicated that PCBP1, which interacted with MHV-68 ORF34, may be involved in regulating late virus gene expression in a manner consistent with the effects of its viral interacting partner. Our study integrated Y2H screening with multiple functional validation approaches to create �

Simulasi Tumbukan Partikel Gas Ideal Dengan Model Cellular Automata Dua Dimensi

OpenAIRE

Abdul Basid, Annisa Mujriati

2010-01-01

Telah dilakukan simulasi tumbukan partikel gas ideal dengan menggunakan  model cellular automata dua dimensi untuk memvisualisasikan tumbukan partikel gas ideal. Tumbukan partikel  disimulasikan  dengan  menggunakan  model  cellular  automata  dua  dimensi.  Di  dalam cellular automata, pergerakan partikel diatur dengan suatu aturan  yaitu aturan delapan tetangga yang merupakan aturan acak. Hasil program simulasi tumbukan partikel gas ideal dengan model cellular automata dua dimensi  mengguna...

A Cellular Automata Model of Infection Control on Medical Implants

Science.gov (United States)

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

[Reparative and neoplastic spheroid cellular structures and their mathematical model].

Science.gov (United States)

Kogan, E A; Namiot, V A; Demura, T A; Faĭzullina, N M; Sukhikh, G T

2014-01-01

Spheroid cell structures in the cell cultures have been described and are used for studying cell-cell and cell- matrix interactions. At the same time, spheroid cell structure participation in the repair and development of cancer in vivo remains unexplored. The aim of this study was to investigate the cellular composition of spherical structures and their functional significance in the repair of squamous epithelium in human papilloma virus-associated cervical pathology--chronic cervicitis and cervical intraepithelial neoplasia 1-3 degree, and also construct a mathematical model to explain the development and behavior of such spheroid cell structure.

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

Directory of Open Access Journals (Sweden)

Giovanni Dalmasso

Full Text Available 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

Cellular automaton model for hydrogen transport dynamics through metallic surface

International Nuclear Information System (INIS)

Shimura, K.; Yamaguchi, K.; Terai, T.; Yamawaki, M.

2002-01-01

Hydrogen re-emission and re-combination at the surface of first wall materials are a crucial issue for the understanding of the fuel recycling and for the tritium inventory in plasma facing materials. It is know to be difficult to model the transient behaviour of those processes due to their complex time-transient nature. However, cellular automata (CA) are powerful tools to model such complex systems because of their nature of discreteness in both dependent and independent variables. Then the system can be represented by the fully local interactions between cells. For that reason, complex physical and chemical systems can be described by fairly simple manner. In this study, the kinetics of desorption of adsorbed hydrogen from an ideal metallic surface is modelled in CA. Thermal desorption is simulated with this model and the comparison with the theory of rate processes is performed to identify the validity of this model. The overall results show that this model is reasonable to express the desorption kinetics

The "resident's dilemma"? Values and strategies of medical residents for education interactions: a cellular automata simulation.

Science.gov (United States)

Heckerling, P S; Gerber, B S; Weiner, S J

2006-01-01

Medical residents engage in formal and informal education interactions with fellow residents during the working day, and can choose whether to spend time and effort on such interactions. Time and effort spent on such interactions can bring learning and personal satisfaction to residents, but may also delay completion of clinical work. Using hypothetical cases, we assessed the values and strategies of internal medicine residents at one hospital for both cooperative and non-cooperative education interactions with fellow residents. We then used these data and cellular automata models of two-person games to simulate repeated interactions between residents, and to determine which strategies resulted in greatest accrued value. We conducted sensitivity analyses on several model parameters, to test the robustness of dominant strategies to model assumptions. Twenty-nine of the 57 residents (50.9%) valued cooperation more than non-cooperation no matter what the other resident did during the current interaction. Similarly, thirty-six residents (63.2%) endorsed an unconditional always-cooperate strategy no matter what the other resident had done during their previous interaction. In simulations, an always-cooperate strategy accrued more value (776.42 value units) than an aggregate of strategies containing non-cooperation components (675.0 value units, p = 0.052). Only when the probability of strategy errors reached 50%, or when values were re-ordered to match those of a Prisoner's Dilemma, did non-cooperation-based strategies accrue the most value. Cooperation-based values and strategies were most frequent among our residents, and dominated in simulations of repeated education interactions between them.

[Cell signaling pathways interaction in cellular proliferation: Potential target for therapeutic interventionism].

Science.gov (United States)

Valdespino-Gómez, Víctor Manuel; Valdespino-Castillo, Patricia Margarita; Valdespino-Castillo, Víctor Edmundo

2015-01-01

Nowadays, cellular physiology is best understood by analysing their interacting molecular components. Proteins are the major components of the cells. Different proteins are organised in the form of functional clusters, pathways or networks. These molecules are ordered in clusters of receptor molecules of extracellular signals, transducers, sensors and biological response effectors. The identification of these intracellular signaling pathways in different cellular types has required a long journey of experimental work. More than 300 intracellular signaling pathways have been identified in human cells. They participate in cell homeostasis processes for structural and functional maintenance. Some of them participate simultaneously or in a nearly-consecutive progression to generate a cellular phenotypic change. In this review, an analysis is performed on the main intracellular signaling pathways that take part in the cellular proliferation process, and the potential use of some components of these pathways as target for therapeutic interventionism are also underlined. Copyright © 2015 Academia Mexicana de Cirugía A.C. Published by Masson Doyma México S.A. All rights reserved.

A survey on the modeling and applications of cellular automata theory

Science.gov (United States)

Gong, Yimin

2017-09-01

The Cellular Automata Theory is a discrete model which is now widely used in scientific researches and simulations. The model is comprised of some cells which changes according to a specific rule over time. This paper provides a survey of the Modeling and Applications of Cellular Automata Theory, which focus on the program realization of Cellular Automata Theory and the application of Cellular Automata in each field, such as road traffic, land use, and cutting machines. Each application is further explained, and several related main models are briefly introduced. This research aims to help decision-makers formulate appropriate development plans.

Modeling integrated cellular machinery using hybrid Petri-Boolean networks.

Directory of Open Access Journals (Sweden)

Natalie Berestovsky

Full Text Available 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

Modeling and cellular studies

International Nuclear Information System (INIS)

Anon.

1982-01-01

Testing the applicability of mathematical models with carefully designed experiments is a powerful tool in the investigations of the effects of ionizing radiation on cells. The modeling and cellular studies complement each other, for modeling provides guidance for designing critical experiments which must provide definitive results, while the experiments themselves provide new input to the model. Based on previous experimental results the model for the accumulation of damage in Chlamydomonas reinhardi has been extended to include various multiple two-event combinations. Split dose survival experiments have shown that models tested to date predict most but not all the observed behavior. Stationary-phase mammalian cells, required for tests of other aspects of the model, have been shown to be at different points in the cell cycle depending on how they were forced to stop proliferating. These cultures also demonstrate different capacities for repair of sublethal radiation damage

Modeling evolution and immune system by cellular automata

International Nuclear Information System (INIS)

Bezzi, M.

2001-01-01

In this review the behavior of two different biological systems is investigated using cellular automata. Starting from this spatially extended approach it is also tried, in some cases, to reduce the complexity of the system introducing mean-field approximation, and solving (or trying to solve) these simplified systems. It is discussed the biological meaning of the results, the comparison with experimental data (if available) and the different features between spatially extended and mean-field versions. The biological systems considered in this review are the following: Darwinian evolution in simple ecosystems and immune system response. In the first section the main features of molecular evolution are introduced, giving a short survey of genetics for physicists and discussing some models for prebiotic systems and simple ecosystems. It is also introduced a cellular automaton model for studying a set of evolving individuals in a general fitness landscape, considering also the effects of co-evolution. In particular the process of species formation (speciation) is described in sect. 5. The second part deals with immune system modeling. The biological features of immune response are discussed, as well as it is introduced the concept of shape space and of idiotypic network. More detailed reviews which deal with immune system models (mainly focused on idiotypic network models) can be found. Other themes here discussed: the applications of CA to immune system modeling, two complex cellular automata for humoral and cellular immune response. Finally, it is discussed the biological data and the general conclusions are drawn in the last section

Social interactions of eating behaviour among high school students: a cellular automata approach

Science.gov (United States)

2012-01-01

Background Overweight and obesity in children and adolescents is a global epidemic posing problems for both developed and developing nations. The prevalence is particularly alarming in developed nations, such as the United States, where approximately one in three school-aged adolescents (ages 12-19) are overweight or obese. Evidence suggests that weight gain in school-aged adolescents is related to energy imbalance exacerbated by the negative aspects of the school food environment, such as presence of unhealthy food choices. While a well-established connection exists between the food environment, presently there is a lack of studies investigating the impact of the social environment and associated interactions of school-age adolescents. This paper uses a mathematical modelling approach to explore how social interactions among high school adolescents can affect their eating behaviour and food choice. Methods In this paper we use a Cellular Automata (CA) modelling approach to explore how social interactions among school-age adolescents can affect eating behaviour, and food choice. Our CA model integrates social influences and transition rules to simulate the way individuals would interact in a social community (e.g., school cafeteria). To replicate these social interactions, we chose the Moore neighbourhood which allows all neighbours (eights cells in a two-dimensional square lattice) to influence the central cell. Our assumption is that individuals belong to any of four states; Bring Healthy, Bring Unhealthy, Purchase Healthy, and Purchase Unhealthy, and will influence each other according to parameter settings and transition rules. Simulations were run to explore how the different states interact under varying parameter settings. Results This study, through simulations, illustrates that students will change their eating behaviour from unhealthy to healthy as a result of positive social and environmental influences. In general, there is one common characteristic of

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

Science.gov (United States)

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.

Cellular automata model for traffic flow at intersections in internet of vehicles

Science.gov (United States)

Zhao, Han-Tao; Liu, Xin-Ru; Chen, Xiao-Xu; Lu, Jian-Cheng

2018-03-01

Considering the effect of the front vehicle's speed, the influence of the brake light and the conflict of the traffic flow, we established a cellular automata model called CE-NS for traffic flow at the intersection in the non-vehicle networking environment. According to the information interaction of Internet of Vehicles (IoV), introducing parameters describing the congestion and the accurate speed of the front vehicle into the CE-NS model, we improved the rules of acceleration, deceleration and conflict, and finally established a cellular automata model for traffic flow at intersections of IoV. The relationship between traffic parameters such as vehicle speed, flow and average travel time is obtained by numerical simulation of two models. Based on this, we compared the traffic situation of the non-vehicle networking environment with conditions of IoV environment, and analyzed the influence of the different degree of IoV on the traffic flow. The results show that the traffic speed is increased, the travel time is reduced, the flux of intersections is increased and the traffic flow is more smoothly under IoV environment. After the vehicle which achieves IoV reaches a certain proportion, the operation effect of the traffic flow begins to improve obviously.

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

Science.gov (United States)

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.

A generalized cellular automata approach to modeling first order ...

Indian Academy of Sciences (India)

system, consisting of space, time and state, structured with simple local rules without ... Sensitivity analysis of a stochastic cellular automata model. 413 ..... Baetens J M and De Baets B 2011 Design and parameterization of a stochastic cellular.

Cellular-automation fluids: A model for flow in porous media

International Nuclear Information System (INIS)

Rothman, D.H.

1987-01-01

Because the intrinsic inhomogeneity of porous media makes the application of proper boundary conditions difficult, fluid flow through microgeometric models has typically been achieved with idealized arrays of geometrically simple pores, throats, and cracks. The author proposes here an attractive alternative, capable of freely and accurately modeling fluid flow in grossly irregular geometries. This new method numerically solves the Navier-Stokes equations using the cellular-automation fluid model introduced by Frisch, Hasslacher, and Pomeau. The cellular-automation fluid is extraordinarily simple - particles of unit mass traveling with unit velocity reside on a triangular lattice and obey elementary collisions rules - but capable of modeling much of the rich complexity of real fluid flow. The author shows how cellular-automation fluids are applied to the study of porous media. In particular, he discusses issues of scale on the cellular-automation lattice and present the results of 2-D simulations, including numerical estimation of permeability and verification of Darcy's law

Plant-herbivore interaction: dissection of the cellular pattern of Tetranychus urticae feeding on the host plant

Directory of Open Access Journals (Sweden)

Nicolas Bensoussan

2016-07-01

Full Text Available The two-spotted spider mite, Tetranychus urticae Koch (Acari: Tetranychidae, is one of the most polyphagous herbivores feeding on cell contents of over 1,100 plant species including more than 150 crops. It is being established as a model for chelicerate herbivores with tools that enable tracking of reciprocal responses in plant-spider mite interactions. However, despite their important pest status and a growing understanding of the molecular basis of interactions with plant hosts, knowledge of the way mites interface with the plant while feeding and the plant damage directly inflicted by mites is lacking. Here, utilizing histology and microscopy methods, we uncovered several key features of T. urticae feeding. By following the stylet path within the plant tissue, we determined that the stylet penetrates the leaf either in between epidermal pavement cells or through a stomatal opening, without damaging the epidermal cellular layer. Our recordings of mite feeding established that duration of the feeding event ranges from several minutes to more than half an hour, during which time mites consume a single mesophyll cell in a pattern that is common to both bean and Arabidopsis plant hosts. In addition, this study determined that leaf chlorotic spots, a common symptom of mite herbivory, do not form as an immediate consequence of mite feeding. Our results establish a cellular context for the plant-spider mite interaction that will support our understanding of the molecular mechanisms and cell signaling associated with spider mite feeding.

Combined modeling of cell aggregation and adhesion mediated by receptor–ligand interactions under shear flow

Directory of Open Access Journals (Sweden)

Yu Du

2015-11-01

Full Text Available Blood cell aggregation and adhesion to endothelial cells under shear flow are crucial to many biological processes such as thrombi formation, inflammatory cascade, and tumor metastasis, in which these cellular interactions are mainly mediated by the underlying receptor–ligand bindings. While theoretical modeling of aggregation dynamics and adhesion kinetics of interacting cells have been well studied separately, how to couple these two processes remains unclear. Here we develop a combined model that couples cellular aggregation dynamics and adhesion kinetics under shear flow. The impacts of shear rate (or shear stress and molecular binding affinity were elucidated. This study provides a unified model where the action of a fluid flow drives cell aggregation and adhesion under the modulations of the mechanical shear flow and receptor–ligand interaction kinetics. It offers an insight into understanding the relevant biological processes and functions.

Modeling of time dependent localized flow shear stress and its impact on cellular growth within additive manufactured titanium implants.

Science.gov (United States)

Zhang, Ziyu; Yuan, Lang; Lee, Peter D; Jones, Eric; Jones, Julian R

2014-11-01

Bone augmentation implants are porous to allow cellular growth, bone formation and fixation. However, the design of the pores is currently based on simple empirical rules, such as minimum pore and interconnects sizes. We present a three-dimensional (3D) transient model of cellular growth based on the Navier-Stokes equations that simulates the body fluid flow and stimulation of bone precursor cellular growth, attachment, and proliferation as a function of local flow shear stress. The model's effectiveness is demonstrated for two additive manufactured (AM) titanium scaffold architectures. The results demonstrate that there is a complex interaction of flow rate and strut architecture, resulting in partially randomized structures having a preferential impact on stimulating cell migration in 3D porous structures for higher flow rates. This novel result demonstrates the potential new insights that can be gained via the modeling tool developed, and how the model can be used to perform what-if simulations to design AM structures to specific functional requirements. © 2014 Wiley Periodicals, Inc.

Cellular automata a parallel model

CERN Document Server

Mazoyer, J

1999-01-01

Cellular automata can be viewed both as computational models and modelling systems of real processes. This volume emphasises the first aspect. In articles written by leading researchers, sophisticated massive parallel algorithms (firing squad, life, Fischer's primes recognition) are treated. Their computational power and the specific complexity classes they determine are surveyed, while some recent results in relation to chaos from a new dynamic systems point of view are also presented. Audience: This book will be of interest to specialists of theoretical computer science and the parallelism challenge.

PASSENGER TRAFFIC MOVEMENT MODELLING BY THE CELLULAR-AUTOMAT APPROACH

Directory of Open Access Journals (Sweden)

T. Mikhaylovskaya

2009-01-01

Full Text Available The mathematical model of passenger traffic movement developed on the basis of the cellular-automat approach is considered. The program realization of the cellular-automat model of pedastrians streams movement in pedestrian subways at presence of obstacles, at subway structure narrowing is presented. The optimum distances between the obstacles and the angle of subway structure narrowing providing pedastrians stream safe movement and traffic congestion occurance are determined.

Development of a formalism of movable cellular automaton method for numerical modeling of fracture of heterogeneous elastic-plastic materials

Directory of Open Access Journals (Sweden)

S. Psakhie

2013-04-01

Full Text Available A general approach to realization of models of elasticity, plasticity and fracture of heterogeneous materials within the framework of particle-based numerical methods is proposed in the paper. It is based on building many-body forces of particle interaction, which provide response of particle ensemble correctly conforming to the response (including elastic-plastic behavior and fracture of simulated solids. Implementation of proposed approach within particle-based methods is demonstrated by the example of the movable cellular automaton (MCA method, which integrates the possibilities of particle-based discrete element method (DEM and cellular automaton methods. Emergent advantages of the developed approach to formulation of many-body interaction are discussed. Main of them are its applicability to various realizations of the concept of discrete elements and a possibility to realize various rheological models (including elastic-plastic or visco-elastic-plastic and models of fracture to study deformation and fracture of solid-phase materials and media. Capabilities of particle-based modeling of heterogeneous solids are demonstrated by the problem of simulation of deformation and fracture of particle-reinforced metal-ceramic composites.

Effect of self-interaction on the phase diagram of a Gibbs-like measure derived by a reversible Probabilistic Cellular Automata

International Nuclear Information System (INIS)

Cirillo, Emilio N.M.; Louis, Pierre-Yves; Ruszel, Wioletta M.; Spitoni, Cristian

2014-01-01

Cellular Automata are discrete-time dynamical systems on a spatially extended discrete space which provide paradigmatic examples of nonlinear phenomena. Their stochastic generalizations, i.e., Probabilistic Cellular Automata (PCA), are discrete time Markov chains on lattice with finite single-cell states whose distinguishing feature is the parallel character of the updating rule. We study the ground states of the Hamiltonian and the low-temperature phase diagram of the related Gibbs measure naturally associated with a class of reversible PCA, called the cross PCA. In such a model the updating rule of a cell depends indeed only on the status of the five cells forming a cross centered at the original cell itself. In particular, it depends on the value of the center spin (self-interaction). The goal of the paper is that of investigating the role played by the self-interaction parameter in connection with the ground states of the Hamiltonian and the low-temperature phase diagram of the Gibbs measure associated with this particular PCA

Overview of cellular automaton models for corrosion

International Nuclear Information System (INIS)

Perez-Brokate, Cristian Felipe; De Lamare, Jacques; Dung di Caprio; Feron, Damien; Chausse, Annie

2014-01-01

A review of corrosion process modeling using cellular automata methods is presented. This relatively new and growing approach takes into account the stochastic nature of the phenomena and uses physico-chemical rules to make predictions at a mesoscopic scale. Milestone models are analyzed and perspectives are established. (authors)

A Mathematical Model for Cisplatin Cellular Pharmacodynamics

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Ardith W. El-Kareh

2003-03-01

Full Text Available A simple theoretical model for the cellular pharmacodynamics of cisplatin is presented. The model, which takes into account the kinetics of cisplatin uptake by cells and the intracellular binding of the drug, can be used to predict the dependence of survival (relative to controls on the time course of extracellular exposure. Cellular pharmacokinetic parameters are derived from uptake data for human ovarian and head and neck cancer cell lines. Survival relative to controls is assumed to depend on the peak concentration of DNA-bound intracellular platinum. Model predictions agree well with published data on cisplatin cytotoxicity for three different cancer cell lines, over a wide range of exposure times. In comparison with previously published mathematical models for anticancer drug pharmacodynamics, the present model provides a better fit to experimental data sets including long exposure times (∼100 hours. The model provides a possible explanation for the fact that cell kill correlates well with area under the extracellular concentration-time curve in some data sets, but not in others. The model may be useful for optimizing delivery schedules and for the dosing of cisplatin for cancer therapy.

Multiplicity of Mathematical Modeling Strategies to Search for Molecular and Cellular Insights into Bacteria Lung Infection.

Science.gov (United States)

Cantone, Martina; Santos, Guido; Wentker, Pia; Lai, Xin; Vera, Julio

2017-01-01

Even today two bacterial lung infections, namely pneumonia and tuberculosis, are among the 10 most frequent causes of death worldwide. These infections still lack effective treatments in many developing countries and in immunocompromised populations like infants, elderly people and transplanted patients. The interaction between bacteria and the host is a complex system of interlinked intercellular and the intracellular processes, enriched in regulatory structures like positive and negative feedback loops. Severe pathological condition can emerge when the immune system of the host fails to neutralize the infection. This failure can result in systemic spreading of pathogens or overwhelming immune response followed by a systemic inflammatory response. Mathematical modeling is a promising tool to dissect the complexity underlying pathogenesis of bacterial lung infection at the molecular, cellular and tissue levels, and also at the interfaces among levels. In this article, we introduce mathematical and computational modeling frameworks that can be used for investigating molecular and cellular mechanisms underlying bacterial lung infection. Then, we compile and discuss published results on the modeling of regulatory pathways and cell populations relevant for lung infection and inflammation. Finally, we discuss how to make use of this multiplicity of modeling approaches to open new avenues in the search of the molecular and cellular mechanisms underlying bacterial infection in the lung.

Multi-cellular logistics of collective cell migration.

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Masataka Yamao

Full Text Available 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.

Intracellular Localization and Cellular Factors Interaction of HTLV-1 and HTLV-2 Tax Proteins: Similarities and Functional Differences

Directory of Open Access Journals (Sweden)

Maria Grazia Romanelli

2011-05-01

Full Text Available Human T-lymphotropic viruses type 1 (HTLV-1 and type 2 (HTLV-2 present very similar genomic structures but HTLV-1 is more pathogenic than HTLV-2. Is this difference due to their transactivating Tax proteins, Tax-1 and Tax-2, which are responsible for viral and cellular gene activation? Do Tax-1 and Tax-2 differ in their cellular localization and in their interaction pattern with cellular factors? In this review, we summarize Tax-1 and Tax-2 structural and phenotypic properties, their interaction with factors involved in signal transduction and their localization-related behavior within the cell. Special attention will be given to the distinctions between Tax-1 and Tax-2 that likely play an important role in their transactivation activity.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Generic framework for mining cellular automata models on protein-folding simulations.

Science.gov (United States)

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.

Empirical study on entropy models of cellular manufacturing systems

Institute of Scientific and Technical Information of China (English)

Zhifeng Zhang; Renbin Xiao

2009-01-01

From the theoretical point of view,the states of manufacturing resources can be monitored and assessed through the amount of information needed to describe their technological structure and operational state.The amount of information needed to describe cellular manufacturing systems is investigated by two measures:the structural entropy and the operational entropy.Based on the Shannon entropy,the models of the structural entropy and the operational entropy of cellular manufacturing systems are developed,and the cognizance of the states of manufacturing resources is also illustrated.Scheduling is introduced to measure the entropy models of cellular manufacturing systems,and the feasible concepts of maximum schedule horizon and schedule adherence are advanced to quantitatively evaluate the effectiveness of schedules.Finally,an example is used to demonstrate the validity of the proposed methodology.

A cellular automata model for ant trails

Indian Academy of Sciences (India)

In this study, the unidirectional ant traffic flow with U-turn in an ant trail was investigated using one-dimensional cellular automata model. It is known that ants communicate with each other by dropping a chemical, called pheromone, on the substrate. Apart from the studies in the literature, it was considered in the model that ...

Fuzzy cellular automata models in immunology

International Nuclear Information System (INIS)

Ahmed, E.

1996-01-01

The self-nonself character of antigens is considered to be fuzzy. The Chowdhury et al. cellular automata model is generalized accordingly. New steady states are found. The first corresponds to a below-normal help and suppression and is proposed to be related to autoimmune diseases. The second corresponds to a below-normal B-cell level

Optimal cellular mobility for synchronization arising from the gradual recovery of intercellular interactions

International Nuclear Information System (INIS)

Uriu, Koichiro; Ares, Saúl; Oates, Andrew C; Morelli, Luis G

2012-01-01

Cell movement and intercellular signaling occur simultaneously during the development of tissues, but little is known about how movement affects signaling. Previous theoretical studies have shown that faster moving cells favor synchronization across a population of locally coupled genetic oscillators. An important assumption in these studies is that cells can immediately interact with their new neighbors after arriving at a new location. However, intercellular interactions in cellular systems may need some time to become fully established. How movement affects synchronization in this situation has not been examined. Here, we develop a coupled phase oscillator model in which we consider cell movement and the gradual recovery of intercellular coupling experienced by a cell after movement, characterized by a moving rate and a coupling recovery rate, respectively. We find (1) an optimal moving rate for synchronization and (2) a critical moving rate above which achieving synchronization is not possible. These results indicate that the extent to which movement enhances synchrony is limited by a gradual recovery of coupling. These findings suggest that the ratio of time scales of movement and signaling recovery is critical for information transfer between moving cells. (paper)

Two Phase Flow Simulation Using Cellular Automata

International Nuclear Information System (INIS)

Marcel, C.P.

2002-01-01

The classical mathematical treatment of two-phase flows is based on the average of the conservation equations for each phase.In this work, a complementary approach to the modeling of these systems based on statistical population balances of aut omata sets is presented.Automata are entities defined by mathematical states that change following iterative rules representing interactions with the neighborhood.A model of automata for two-phase flow simulation is presented.This model consists of fie lds of virtual spheres that change their volumes and move around a certain environment.The model is more general than the classical cellular automata in two respects: the grid of cellular automata is dismissed in favor of a trajectory generator, and the rules of interaction involve parameters representing the actual physical interactions between phases.Automata simulation was used to study unsolved two-phase flow problems involving high heat flux rates. One system described in this work consists of a vertical channel with saturated water at normal pressure heated from the lower surface.The heater causes water to boil and starts the bubble production.We used cellular automata to describe two-phase flows and the interaction with the heater.General rule s for such cellular automata representing bubbles moving in stagnant liquid were used, with special attention to correct modeling of different mechanisms of heat transfer.The results of the model were compared to previous experiments and correlations finding good agreement.One of the most important findings is the confirmation of Kutateladze's idea about a close relation between the start of critical heat flux and a change in the flow's topology.This was analyzed using a control volume located in the upper surface of the heater.A strong decrease in the interfacial surface just before the CHF start was encountered.The automata describe quite well some characteristic parameters such as the shape of the local void fraction in the

Cellular automata and statistical mechanical models

International Nuclear Information System (INIS)

Rujan, P.

1987-01-01

The authors elaborate on the analogy between the transfer matrix of usual lattice models and the master equation describing the time development of cellular automata. Transient and stationary properties of probabilistic automata are linked to surface and bulk properties, respectively, of restricted statistical mechanical systems. It is demonstrated that methods of statistical physics can be successfully used to describe the dynamic and the stationary behavior of such automata. Some exact results are derived, including duality transformations, exact mappings, disorder, and linear solutions. Many examples are worked out in detail to demonstrate how to use statistical physics in order to construct cellular automata with desired properties. This approach is considered to be a first step toward the design of fully parallel, probabilistic systems whose computational abilities rely on the cooperative behavior of their components

Bayesian network model for identification of pathways by integrating protein interaction with genetic interaction data.

Science.gov (United States)

Fu, Changhe; Deng, Su; Jin, Guangxu; Wang, Xinxin; Yu, Zu-Guo

2017-09-21

Molecular interaction data at proteomic and genetic levels provide physical and functional insights into a molecular biosystem and are helpful for the construction of pathway structures complementarily. Despite advances in inferring biological pathways using genetic interaction data, there still exists weakness in developed models, such as, activity pathway networks (APN), when integrating the data from proteomic and genetic levels. It is necessary to develop new methods to infer pathway structure by both of interaction data. We utilized probabilistic graphical model to develop a new method that integrates genetic interaction and protein interaction data and infers exquisitely detailed pathway structure. We modeled the pathway network as Bayesian network and applied this model to infer pathways for the coherent subsets of the global genetic interaction profiles, and the available data set of endoplasmic reticulum genes. The protein interaction data were derived from the BioGRID database. Our method can accurately reconstruct known cellular pathway structures, including SWR complex, ER-Associated Degradation (ERAD) pathway, N-Glycan biosynthesis pathway, Elongator complex, Retromer complex, and Urmylation pathway. By comparing N-Glycan biosynthesis pathway and Urmylation pathway identified from our approach with that from APN, we found that our method is able to overcome its weakness (certain edges are inexplicable). According to underlying protein interaction network, we defined a simple scoring function that only adopts genetic interaction information to avoid the balance difficulty in the APN. Using the effective stochastic simulation algorithm, the performance of our proposed method is significantly high. We developed a new method based on Bayesian network to infer detailed pathway structures from interaction data at proteomic and genetic levels. The results indicate that the developed method performs better in predicting signaling pathways than previously

Station Model for Rail Transit System Using Cellular Automata

International Nuclear Information System (INIS)

Xun Jing; Ning Bin; Li Keping

2009-01-01

In this paper, we propose a new cellular automata model to simulate the railway traffic at station. Based on NaSch model, the proposed station model is composed of the main track and the siding track. Two different schemes for trains passing through station are considered. One is the scheme of 'pass by the main track, start and stop by the siding track'. The other is the scheme of 'two tracks play the same role'. We simulate the train movement using the proposed model and analyze the traffic flow at station. The simulation results demonstrate that the proposed cellular automata model can be successfully used for the simulations of railway traffic. Some characteristic behaviors of railway traffic flow can be reproduced. Moreover, the simulation values of the minimum headway are close to the theoretical values. This result demonstrates the dependability and availability of the proposed model. (general)

Simulating physics with cellular automata

Energy Technology Data Exchange (ETDEWEB)

Vichniac, G Y

1984-01-01

Cellular automata are dynamical systems where space, time, and variables are discrete. They are shown on two-dimensional examples to be capable of non-numerical simulations of physics. They are useful for faithful parallel processing of lattice models. At another level, they exhibit behaviours and illustrate concepts that are unmistakably physical, such as non-ergodicity and order parameters, frustration, relaxation to chaos through period doublings, a conspicuous arrow of time in reversible microscopic dynamics, causality and light-cone, and non-separability. In general, they constitute exactly computable models for complex phenomena and large-scale correlations that result from very simple short-range interactions. The author studies their space, time, and intrinsic symmetries and the corresponding conservation laws, with an emphasis on the conservation of information obeyed by reversible cellular automata. 60 references.

Multi-scale modeling with cellular automata: The complex automata approach

NARCIS (Netherlands)

Hoekstra, A.G.; Falcone, J.-L.; Caiazzo, A.; Chopard, B.

2008-01-01

Cellular Automata are commonly used to describe complex natural phenomena. In many cases it is required to capture the multi-scale nature of these phenomena. A single Cellular Automata model may not be able to efficiently simulate a wide range of spatial and temporal scales. It is our goal to

Modeling and Analysis of Cellular CDMA Forward Channel

National Research Council Canada - National Science Library

Tighe, Jan

2001-01-01

In this thesis, we develop the forward channel model for a DS-CDMA cellular system operating in a slow-flat Rayleigh fading and log normal shadowing environment, which incorporates the extended Hata...

Simulating Urban Growth Using a Random Forest-Cellular Automata (RF-CA Model

Directory of Open Access Journals (Sweden)

Courage Kamusoko

2015-04-01

Full Text Available Sustainable urban planning and management require reliable land change models, which can be used to improve decision making. The objective of this study was to test a random forest-cellular automata (RF-CA model, which combines random forest (RF and cellular automata (CA models. The Kappa simulation (KSimulation, figure of merit, and components of agreement and disagreement statistics were used to validate the RF-CA model. Furthermore, the RF-CA model was compared with support vector machine cellular automata (SVM-CA and logistic regression cellular automata (LR-CA models. Results show that the RF-CA model outperformed the SVM-CA and LR-CA models. The RF-CA model had a Kappa simulation (KSimulation accuracy of 0.51 (with a figure of merit statistic of 47%, while SVM-CA and LR-CA models had a KSimulation accuracy of 0.39 and −0.22 (with figure of merit statistics of 39% and 6%, respectively. Generally, the RF-CA model was relatively accurate at allocating “non-built-up to built-up” changes as reflected by the correct “non-built-up to built-up” components of agreement of 15%. The performance of the RF-CA model was attributed to the relatively accurate RF transition potential maps. Therefore, this study highlights the potential of the RF-CA model for simulating urban growth.

Super-resolution imaging and tracking of protein-protein interactions in sub-diffraction cellular space

Science.gov (United States)

Liu, Zhen; Xing, Dong; Su, Qian Peter; Zhu, Yun; Zhang, Jiamei; Kong, Xinyu; Xue, Boxin; Wang, Sheng; Sun, Hao; Tao, Yile; Sun, Yujie

2014-07-01

Imaging the location and dynamics of individual interacting protein pairs is essential but often difficult because of the fluorescent background from other paired and non-paired molecules, particularly in the sub-diffraction cellular space. Here we develop a new method combining bimolecular fluorescence complementation and photoactivated localization microscopy for super-resolution imaging and single-molecule tracking of specific protein-protein interactions. The method is used to study the interaction of two abundant proteins, MreB and EF-Tu, in Escherichia coli cells. The super-resolution imaging shows interesting distribution and domain sizes of interacting MreB-EF-Tu pairs as a subpopulation of total EF-Tu. The single-molecule tracking of MreB, EF-Tu and MreB-EF-Tu pairs reveals intriguing localization-dependent heterogonous dynamics and provides valuable insights to understanding the roles of MreB-EF-Tu interactions.

Super-resolution imaging and tracking of protein–protein interactions in sub-diffraction cellular space

Science.gov (United States)

Liu, Zhen; Xing, Dong; Su, Qian Peter; Zhu, Yun; Zhang, Jiamei; Kong, Xinyu; Xue, Boxin; Wang, Sheng; Sun, Hao; Tao, Yile; Sun, Yujie

2014-01-01

Imaging the location and dynamics of individual interacting protein pairs is essential but often difficult because of the fluorescent background from other paired and non-paired molecules, particularly in the sub-diffraction cellular space. Here we develop a new method combining bimolecular fluorescence complementation and photoactivated localization microscopy for super-resolution imaging and single-molecule tracking of specific protein–protein interactions. The method is used to study the interaction of two abundant proteins, MreB and EF-Tu, in Escherichia coli cells. The super-resolution imaging shows interesting distribution and domain sizes of interacting MreB–EF-Tu pairs as a subpopulation of total EF-Tu. The single-molecule tracking of MreB, EF-Tu and MreB–EF-Tu pairs reveals intriguing localization-dependent heterogonous dynamics and provides valuable insights to understanding the roles of MreB–EF-Tu interactions. PMID:25030837

On the spatial dynamics and oscillatory behavior of a predator-prey model based on cellular automata and local particle swarm optimization.

Science.gov (United States)

Molina, Mario Martínez; Moreno-Armendáriz, Marco A; Carlos Seck Tuoh Mora, Juan

2013-11-07

A two-dimensional lattice model based on Cellular Automata theory and swarm intelligence is used to study the spatial and population dynamics of a theoretical ecosystem. It is found that the social interactions among predators provoke the formation of clusters, and that by increasing the mobility of predators the model enters into an oscillatory behavior. © 2013 Elsevier Ltd. All rights reserved.

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

Science.gov (United States)

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.

Cell activation and cellular-cellular interactions during hemodialysis: effect of dialyzer membrane.

Science.gov (United States)

Sirolli, V; Ballone, E; Di Stante, S; Amoroso, L; Bonomini, M

2002-06-01

During hemodialysis (HD), circulating blood cells can be activated and also engage in dynamic interplay. These phenomena may be important factors behind dialysis membrane bio(in)compatibility. In the present prospective cross-over study, we have used flow cytometry to evaluate the influence of different dialysis membranes on the activation of circulating blood cells (leukocytes, platelets) and their dynamic interactions (formation of circulating platelet-leukocyte and platelet-erythrocyte aggregates) during in vivo HD. Each patient (n = 10) was treated with dialyzers containing membranes of cellulose diacetate, polysulfone and ethylenevinylalcohol (EVAL) in a randomized order. Upregulation of adhesion receptor expression (CD15s, CD11b/CD18) occurred mainly with the cellulosic membrane, though an increase in CD11b/CD18 circulating on neutrophils was also found with both synthetic membranes. Circulating activated platelets (P-selectin/CD63-positive platelets) increased during HD sessions with cellulose diacetate and polysulfone. An increased formation of platelet-neutrophil aggregates was found at 15 and 30 min during dialysis with cellulose diacetate and polysulfone but not with EVAL. Platelet-erythrocyte aggregates also increased with cellulose diacetate and at 15 min with polysulfone as well. Generally in concomitance with the increase in platelet-neutrophil coaggregates, there was an increased hydrogen peroxide production by neutrophils. The results of this study indicate that cellular mechanisms can be activated during HD largely depending on the membrane material, EVAL causing less reactivity than the other two membranes. It appears that each dialysis membrane has multiple and different characteristics that may contribute to interactions with blood components. Our results also indicate that derivatizing cellulose (cellulose diacetate) may be a useful way to improve the biocompatibility of the cellulose polymer and that there may be great variability in the

Emergent 1d Ising Behavior in AN Elementary Cellular Automaton Model

Science.gov (United States)

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.

A Model of How Different Biology Experts Explain Molecular and Cellular Mechanisms

Science.gov (United States)

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…

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

Directory of Open Access Journals (Sweden)

Xi-Feng Zhang

2016-09-01

Full Text Available 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

Combinatorial approaches to evaluate nanodiamond uptake and induced cellular fate

Science.gov (United States)

Eldawud, Reem; Reitzig, Manuela; Opitz, Jörg; Rojansakul, Yon; Jiang, Wenjuan; Nangia, Shikha; Zoica Dinu, Cerasela

2016-02-01

Nanodiamonds (NDs) are an emerging class of engineered nanomaterials that hold great promise for the next generation of bionanotechnological products to be used for drug and gene delivery, or for bio-imaging and biosensing. Previous studies have shown that upon their cellular uptake, NDs exhibit high biocompatibility in various in vitro and in vivo set-ups. Herein we hypothesized that the increased NDs biocompatibility is a result of minimum membrane perturbations and their reduced ability to induce disruption or damage during cellular translocation. Using multi-scale combinatorial approaches that simulate ND-membrane interactions, we correlated NDs real-time cellular uptake and kinetics with the ND-induced membrane fluctuations to derive energy requirements for the uptake to occur. Our discrete and real-time analyses showed that the majority of NDs internalization occurs within 2 h of cellular exposure, however, with no effects on cellular viability, proliferation or cellular behavior. Furthermore, our simulation analyses using coarse-grained models identified key changes in the energy profile, membrane deformation and recovery time, all functions of the average ND or ND-based agglomerate size. Understanding the mechanisms responsible for ND-cell membrane interactions could possibly advance their implementation in various biomedical applications.

Combinatorial approaches to evaluate nanodiamond uptake and induced cellular fate

Science.gov (United States)

Eldawud, Reem; Reitzig, Manuela; Opitz, Jörg; Rojansakul, Yon; Jiang, Wenjuan; Nangia, Shikha; Dinu, Cerasela Zoica

2016-01-01

Nanodiamonds (NDs) are an emerging class of engineered nanomaterials that hold great promise for the next generation of bionanotechnological products to be used for drug and gene delivery, or for bio-imaging and biosensing. Previous studies have shown that upon their cellular uptake, NDs exhibit high biocompatibility in various in vitro and in vivo set-ups. Herein we hypothesized that the increased NDs biocompatibility is a result of minimum membrane perturbations and their reduced ability to induce disruption or damage during cellular translocation. Using multi-scale combinatorial approaches that simulate ND-membrane interactions, we correlated NDs real-time cellular uptake and kinetics with the ND-induced membrane fluctuations to derive energy requirements for the uptake to occur. Our discrete and real-time analyses showed that the majority of NDs internalization occurs within 2 h of cellular exposure, however, with no effects on cellular viability, proliferation or cellular behavior. Furthermore, our simulation analyses using coarse-grained models identified key changes in the energy profile, membrane deformation and recovery time, all functions of the average ND or ND-based agglomerate size. Understanding the mechanisms responsible for ND-cell membrane interactions could possibly advance their implementation in various biomedical applications. PMID:26820775

Combinatorial approaches to evaluate nanodiamond uptake and induced cellular fate

International Nuclear Information System (INIS)

Eldawud, Reem; Dinu, Cerasela Zoica; Reitzig, Manuela; Opitz, Jörg; Rojansakul, Yon; Jiang, Wenjuan; Nangia, Shikha

2016-01-01

Nanodiamonds (NDs) are an emerging class of engineered nanomaterials that hold great promise for the next generation of bionanotechnological products to be used for drug and gene delivery, or for bio-imaging and biosensing. Previous studies have shown that upon their cellular uptake, NDs exhibit high biocompatibility in various in vitro and in vivo set-ups. Herein we hypothesized that the increased NDs biocompatibility is a result of minimum membrane perturbations and their reduced ability to induce disruption or damage during cellular translocation. Using multi-scale combinatorial approaches that simulate ND-membrane interactions, we correlated NDs real-time cellular uptake and kinetics with the ND-induced membrane fluctuations to derive energy requirements for the uptake to occur. Our discrete and real-time analyses showed that the majority of NDs internalization occurs within 2 h of cellular exposure, however, with no effects on cellular viability, proliferation or cellular behavior. Furthermore, our simulation analyses using coarse-grained models identified key changes in the energy profile, membrane deformation and recovery time, all functions of the average ND or ND-based agglomerate size. Understanding the mechanisms responsible for ND-cell membrane interactions could possibly advance their implementation in various biomedical applications. (paper)

Combinatorial approaches to evaluate nanodiamond uptake and induced cellular fate.

Science.gov (United States)

Eldawud, Reem; Reitzig, Manuela; Opitz, Jörg; Rojansakul, Yon; Jiang, Wenjuan; Nangia, Shikha; Dinu, Cerasela Zoica

2016-02-26

Nanodiamonds (NDs) are an emerging class of engineered nanomaterials that hold great promise for the next generation of bionanotechnological products to be used for drug and gene delivery, or for bio-imaging and biosensing. Previous studies have shown that upon their cellular uptake, NDs exhibit high biocompatibility in various in vitro and in vivo set-ups. Herein we hypothesized that the increased NDs biocompatibility is a result of minimum membrane perturbations and their reduced ability to induce disruption or damage during cellular translocation. Using multi-scale combinatorial approaches that simulate ND-membrane interactions, we correlated NDs real-time cellular uptake and kinetics with the ND-induced membrane fluctuations to derive energy requirements for the uptake to occur. Our discrete and real-time analyses showed that the majority of NDs internalization occurs within 2 h of cellular exposure, however, with no effects on cellular viability, proliferation or cellular behavior. Furthermore, our simulation analyses using coarse-grained models identified key changes in the energy profile, membrane deformation and recovery time, all functions of the average ND or ND-based agglomerate size. Understanding the mechanisms responsible for ND-cell membrane interactions could possibly advance their implementation in various biomedical applications.

Simulations of living cell origins using a cellular automata model.

Science.gov (United States)

Ishida, Takeshi

2014-04-01

Understanding the generalized mechanisms of cell self-assembly is fundamental for applications in various fields, such as mass producing molecular machines in nanotechnology. Thus, the details of real cellular reaction networks and the necessary conditions for self-organized cells must be elucidated. We constructed a 2-dimensional cellular automata model to investigate the emergence of biological cell formation, which incorporated a looped membrane and a membrane-bound information system (akin to a genetic code and gene expression system). In particular, with an artificial reaction system coupled with a thermal system, the simultaneous formation of a looped membrane and an inner reaction process resulted in a more stable structure. These double structures inspired the primitive biological cell formation process from chemical evolution stage. With a model to simulate cellular self-organization in a 2-dimensional cellular automata model, 3 phenomena could be realized: (1) an inner reaction system developed as an information carrier precursor (akin to DNA); (2) a cell border emerged (akin to a cell membrane); and (3) these cell structures could divide into 2. This double-structured cell was considered to be a primary biological cell. The outer loop evolved toward a lipid bilayer membrane, and inner polymeric particles evolved toward precursor information carriers (evolved toward DNA). This model did not completely clarify all the necessary and sufficient conditions for biological cell self-organization. Further, our virtual cells remained unstable and fragile. However, the "garbage bag model" of Dyson proposed that the first living cells were deficient; thus, it would be reasonable that the earliest cells were more unstable and fragile than the simplest current unicellular organisms.

A cellular automata model of Ebola virus dynamics

Science.gov (United States)

Burkhead, Emily; Hawkins, Jane

2015-11-01

We construct a stochastic cellular automaton (SCA) model for the spread of the Ebola virus (EBOV). We make substantial modifications to an existing SCA model used for HIV, introduced by others and studied by the authors. We give a rigorous analysis of the similarities between models due to the spread of virus and the typical immune response to it, and the differences which reflect the drastically different timing of the course of EBOV. We demonstrate output from the model and compare it with clinical data.

Effects of temperature and cellular interactions on the mechanics and morphology of human cancer cells investigated by atomic force microscopy.

Science.gov (United States)

Li, Mi; Liu, LianQing; Xi, Ning; Wang, YueChao; Xiao, XiuBin; Zhang, WeiJing

2015-09-01

Cell mechanics plays an important role in cellular physiological activities. Recent studies have shown that cellular mechanical properties are novel biomarkers for indicating the cell states. In this article, temperature-controllable atomic force microscopy (AFM) was applied to quantitatively investigate the effects of temperature and cellular interactions on the mechanics and morphology of human cancer cells. First, AFM indenting experiments were performed on six types of human cells to investigate the changes of cellular Young's modulus at different temperatures and the results showed that the mechanical responses to the changes of temperature were variable for different types of cancer cells. Second, AFM imaging experiments were performed to observe the morphological changes in living cells at different temperatures and the results showed the significant changes of cell morphology caused by the alterations of temperature. Finally, by co-culturing human cancer cells with human immune cells, the mechanical and morphological changes in cancer cells were investigated. The results showed that the co-culture of cancer cells and immune cells could cause the distinct mechanical changes in cancer cells, but no significant morphological differences were observed. The experimental results improved our understanding of the effects of temperature and cellular interactions on the mechanics and morphology of cancer cells.

Geometric Modeling of Cellular Materials for Additive Manufacturing in Biomedical Field: A Review.

Science.gov (United States)

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.

Spatiotemporal Stochastic Modeling of IoT Enabled Cellular Networks: Scalability and Stability Analysis

KAUST Repository

Gharbieh, Mohammad; Elsawy, Hesham; Bader, Ahmed; Alouini, Mohamed-Slim

2017-01-01

The Internet of Things (IoT) is large-scale by nature, which is manifested by the massive number of connected devices as well as their vast spatial existence. Cellular networks, which provide ubiquitous, reliable, and efficient wireless access, will play fundamental rule in delivering the first-mile access for the data tsunami to be generated by the IoT. However, cellular networks may have scalability problems to provide uplink connectivity to massive numbers of connected things. To characterize the scalability of cellular uplink in the context of IoT networks, this paper develops a traffic-aware spatiotemporal mathematical model for IoT devices supported by cellular uplink connectivity. The developed model is based on stochastic geometry and queueing theory to account for the traffic requirement per IoT device, the different transmission strategies, and the mutual interference between the IoT devices. To this end, the developed model is utilized to characterize the extent to which cellular networks can accommodate IoT traffic as well as to assess and compare three different transmission strategies that incorporate a combination of transmission persistency, backoff, and power-ramping. The analysis and the results clearly illustrate the scalability problem imposed by IoT on cellular network and offer insights into effective scenarios for each transmission strategy.

Spatiotemporal Stochastic Modeling of IoT Enabled Cellular Networks: Scalability and Stability Analysis

KAUST Repository

Gharbieh, Mohammad

2017-05-02

The Internet of Things (IoT) is large-scale by nature, which is manifested by the massive number of connected devices as well as their vast spatial existence. Cellular networks, which provide ubiquitous, reliable, and efficient wireless access, will play fundamental rule in delivering the first-mile access for the data tsunami to be generated by the IoT. However, cellular networks may have scalability problems to provide uplink connectivity to massive numbers of connected things. To characterize the scalability of cellular uplink in the context of IoT networks, this paper develops a traffic-aware spatiotemporal mathematical model for IoT devices supported by cellular uplink connectivity. The developed model is based on stochastic geometry and queueing theory to account for the traffic requirement per IoT device, the different transmission strategies, and the mutual interference between the IoT devices. To this end, the developed model is utilized to characterize the extent to which cellular networks can accommodate IoT traffic as well as to assess and compare three different transmission strategies that incorporate a combination of transmission persistency, backoff, and power-ramping. The analysis and the results clearly illustrate the scalability problem imposed by IoT on cellular network and offer insights into effective scenarios for each transmission strategy.

Cytoscape: a software environment for integrated models of biomolecular interaction networks.

Science.gov (United States)

Shannon, Paul; Markiel, Andrew; Ozier, Owen; Baliga, Nitin S; Wang, Jonathan T; Ramage, Daniel; Amin, Nada; Schwikowski, Benno; Ideker, Trey

2003-11-01

Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.

Simulation Modeling by Classification of Problems: A Case of Cellular Manufacturing

International Nuclear Information System (INIS)

Afiqah, K N; Mahayuddin, Z R

2016-01-01

Cellular manufacturing provides good solution approach to manufacturing area by applying Group Technology concept. The evolution of cellular manufacturing can enhance performance of the cell and to increase the quality of the product manufactured but it triggers other problem. Generally, this paper highlights factors and problems which emerge commonly in cellular manufacturing. The aim of the research is to develop a thorough understanding of common problems in cellular manufacturing. A part from that, in order to find a solution to the problems exist using simulation technique, this classification framework is very useful to be adapted during model building. Biology evolution tool was used in the research in order to classify the problems emerge. The result reveals 22 problems and 25 factors using cladistic technique. In this research, the expected result is the cladogram established based on the problems in cellular manufacturing gathered. (paper)

Predictive model to describe water migration in cellular solid foods during storage

NARCIS (Netherlands)

Voogt, J.A.; Hirte, A.; Meinders, M.B.J.

2011-01-01

BACKGROUND: Water migration in cellular solid foods during storage causes loss of crispness. To improve crispness retention, physical understanding of this process is needed. Mathematical models are suitable tools to gain this physical knowledge. RESULTS: Water migration in cellular solid foods

Predictive model to describe water migration in cellular solid foods during storage

NARCIS (Netherlands)

Voogt, J.A.; Hirte, A.; Meinders, M.B.J.

2011-01-01

Background: Water migration in cellular solid foods during storage causes loss of crispness. To improve crispness retention, physical understanding of this process is needed. Mathematical models are suitable tools to gain this physical knowledge. Results: Water migration in cellular solid foods

Lattice gas cellular automata and lattice Boltzmann models an introduction

CERN Document Server

Wolf-Gladrow, Dieter A

2000-01-01

Lattice-gas cellular automata (LGCA) and lattice Boltzmann models (LBM) are relatively new and promising methods for the numerical solution of nonlinear partial differential equations. The book provides an introduction for graduate students and researchers. Working knowledge of calculus is required and experience in PDEs and fluid dynamics is recommended. Some peculiarities of cellular automata are outlined in Chapter 2. The properties of various LGCA and special coding techniques are discussed in Chapter 3. Concepts from statistical mechanics (Chapter 4) provide the necessary theoretical background for LGCA and LBM. The properties of lattice Boltzmann models and a method for their construction are presented in Chapter 5.

Geometric Modeling of Cellular Materials for Additive Manufacturing in Biomedical Field: A Review

Directory of Open Access Journals (Sweden)

Gianpaolo Savio

2018-01-01

Full Text Available 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.

Geometric Modeling of Cellular Materials for Additive Manufacturing in Biomedical Field: A Review

Science.gov (United States)

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

Integrating Cellular Metabolism into a Multiscale Whole-Body Model

Science.gov (United States)

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

iGPCR-drug: a web server for predicting interaction between GPCRs and drugs in cellular networking.

Directory of Open Access Journals (Sweden)

Xuan Xiao

Full Text Available Involved in many diseases such as cancer, diabetes, neurodegenerative, inflammatory and respiratory disorders, G-protein-coupled receptors (GPCRs are among the most frequent targets of therapeutic drugs. It is time-consuming and expensive to determine whether a drug and a GPCR are to interact with each other in a cellular network purely by means of experimental techniques. Although some computational methods were developed in this regard based on the knowledge of the 3D (dimensional structure of protein, unfortunately their usage is quite limited because the 3D structures for most GPCRs are still unknown. To overcome the situation, a sequence-based classifier, called "iGPCR-drug", was developed to predict the interactions between GPCRs and drugs in cellular networking. In the predictor, the drug compound is formulated by a 2D (dimensional fingerprint via a 256D vector, GPCR by the PseAAC (pseudo amino acid composition generated with the grey model theory, and the prediction engine is operated by the fuzzy K-nearest neighbour algorithm. Moreover, a user-friendly web-server for iGPCR-drug was established at http://www.jci-bioinfo.cn/iGPCR-Drug/. For the convenience of most experimental scientists, a step-by-step guide is provided on how to use the web-server to get the desired results without the need to follow the complicated math equations presented in this paper just for its integrity. The overall success rate achieved by iGPCR-drug via the jackknife test was 85.5%, which is remarkably higher than the rate by the existing peer method developed in 2010 although no web server was ever established for it. It is anticipated that iGPCR-Drug may become a useful high throughput tool for both basic research and drug development, and that the approach presented here can also be extended to study other drug - target interaction networks.

Simulation of root forms using cellular automata model

International Nuclear Information System (INIS)

Winarno, Nanang; Prima, Eka Cahya; Afifah, Ratih Mega Ayu

2016-01-01

This research aims to produce a simulation program for root forms using cellular automata model. Stephen Wolfram in his book entitled “A New Kind of Science” discusses the formation rules based on the statistical analysis. In accordance with Stephen Wolfram’s investigation, the research will develop a basic idea of computer program using Delphi 7 programming language. To best of our knowledge, there is no previous research developing a simulation describing root forms using the cellular automata model compared to the natural root form with the presence of stone addition as the disturbance. The result shows that (1) the simulation used four rules comparing results of the program towards the natural photographs and each rule had shown different root forms; (2) the stone disturbances prevent the root growth and the multiplication of root forms had been successfully modeled. Therefore, this research had added some stones, which have size of 120 cells placed randomly in the soil. Like in nature, stones cannot be penetrated by plant roots. The result showed that it is very likely to further develop the program of simulating root forms by 50 variations

Simulation of root forms using cellular automata model

Energy Technology Data Exchange (ETDEWEB)

Winarno, Nanang, E-mail: nanang-winarno@upi.edu; Prima, Eka Cahya [International Program on Science Education, Universitas Pendidikan Indonesia, Jl. Dr. Setiabudi no 229, Bandung40154 (Indonesia); Afifah, Ratih Mega Ayu [Department of Physics Education, Post Graduate School, Universitas Pendidikan Indonesia, Jl. Dr. Setiabudi no 229, Bandung40154 (Indonesia)

2016-02-08

This research aims to produce a simulation program for root forms using cellular automata model. Stephen Wolfram in his book entitled “A New Kind of Science” discusses the formation rules based on the statistical analysis. In accordance with Stephen Wolfram’s investigation, the research will develop a basic idea of computer program using Delphi 7 programming language. To best of our knowledge, there is no previous research developing a simulation describing root forms using the cellular automata model compared to the natural root form with the presence of stone addition as the disturbance. The result shows that (1) the simulation used four rules comparing results of the program towards the natural photographs and each rule had shown different root forms; (2) the stone disturbances prevent the root growth and the multiplication of root forms had been successfully modeled. Therefore, this research had added some stones, which have size of 120 cells placed randomly in the soil. Like in nature, stones cannot be penetrated by plant roots. The result showed that it is very likely to further develop the program of simulating root forms by 50 variations.

A generalized cellular automata approach to modeling first order ...

Indian Academy of Sciences (India)

... inhibitors deforming the allosteric site or inhibitors changing the structure of active ... Cell-based models with discrete state variables, such as Cellular Automata ... capture the essential features of a discrete real system, consisting of space, ...

Qualitative and Computational Analysis of a Mathematical Model for Tumor-Immune Interactions

Directory of Open Access Journals (Sweden)

F. A. Rihan

2012-01-01

Full Text Available We provide a family of ordinary and delay differential equations to model the dynamics of tumor-growth and immunotherapy interactions. We explore the effects of adoptive cellular immunotherapy on the model and describe under what circumstances the tumor can be eliminated. The possibility of clearing the tumor, with a strategy, is based on two parameters in the model: the rate of influx of the effector cells and the rate of influx of IL-2. The critical tumor-growth rate, below which endemic tumor does not exist, has been found. One can use the model to make predictions about tumor dormancy.

Computer Modeling of the Earliest Cellular Structures and Functions

Science.gov (United States)

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 membranestructures 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.

Unified Stochastic Geometry Model for MIMO Cellular Networks with Retransmissions

KAUST Repository

Afify, Laila H.

2016-10-11

This paper presents a unified mathematical paradigm, based on stochastic geometry, for downlink cellular networks with multiple-input-multiple-output (MIMO) base stations (BSs). The developed paradigm accounts for signal retransmission upon decoding errors, in which the temporal correlation among the signal-to-interference-plus-noise-ratio (SINR) of the original and retransmitted signals is captured. In addition to modeling the effect of retransmission on the network performance, the developed mathematical model presents twofold analysis unification for MIMO cellular networks literature. First, it integrates the tangible decoding error probability and the abstracted (i.e., modulation scheme and receiver type agnostic) outage probability analysis, which are largely disjoint in the literature. Second, it unifies the analysis for different MIMO configurations. The unified MIMO analysis is achieved by abstracting unnecessary information conveyed within the interfering signals by Gaussian signaling approximation along with an equivalent SISO representation for the per-data stream SINR in MIMO cellular networks. We show that the proposed unification simplifies the analysis without sacrificing the model accuracy. To this end, we discuss the diversity-multiplexing tradeoff imposed by different MIMO schemes and shed light on the diversity loss due to the temporal correlation among the SINRs of the original and retransmitted signals. Finally, several design insights are highlighted.

Unified Stochastic Geometry Model for MIMO Cellular Networks with Retransmissions

KAUST Repository

Afify, Laila H.; Elsawy, Hesham; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim

2016-01-01

This paper presents a unified mathematical paradigm, based on stochastic geometry, for downlink cellular networks with multiple-input-multiple-output (MIMO) base stations (BSs). The developed paradigm accounts for signal retransmission upon decoding errors, in which the temporal correlation among the signal-to-interference-plus-noise-ratio (SINR) of the original and retransmitted signals is captured. In addition to modeling the effect of retransmission on the network performance, the developed mathematical model presents twofold analysis unification for MIMO cellular networks literature. First, it integrates the tangible decoding error probability and the abstracted (i.e., modulation scheme and receiver type agnostic) outage probability analysis, which are largely disjoint in the literature. Second, it unifies the analysis for different MIMO configurations. The unified MIMO analysis is achieved by abstracting unnecessary information conveyed within the interfering signals by Gaussian signaling approximation along with an equivalent SISO representation for the per-data stream SINR in MIMO cellular networks. We show that the proposed unification simplifies the analysis without sacrificing the model accuracy. To this end, we discuss the diversity-multiplexing tradeoff imposed by different MIMO schemes and shed light on the diversity loss due to the temporal correlation among the SINRs of the original and retransmitted signals. Finally, several design insights are highlighted.

Referent 3D tumor model at cellular level in radionuclide therapy

International Nuclear Information System (INIS)

Spaic, R.; Ilic, R.D.; Petrovic, B.J.

2002-01-01

Aim Conventional internal dosimetry has a lot of limitations because of tumor dose nonuniformity. The best approach for absorbed dose at cellular level for different tumors in radionuclide therapy calculation is Monte Carlo method. The purpose of this study is to introduce referent tumor 3D model at cellular level for Monte Carlo simulation study in radionuclide therapy. Material and Methods The moment when tumor is detectable and when same therapy can start is time period in which referent 3D tumor model at cellular level was defined. In accordance with tumor growth rate at that moment he was a sphere with same radius (10 000 μm). In that tumor there are cells or cluster of cells, which are randomly distributed spheres. Distribution of cells/cluster of cells can be calculated from histology data but it was assumed that this distribution is normal with the same mean value and standard deviation (100±50 mm). Second parameter, which was selected to define referent tumor, is volume density of cells (30%). In this referent tumor there are no necroses. Stroma is defined as space between spheres with same concentration of materials as in spheres. Results: Referent tumor defined on this way have about 2,2 10 5 cells or cluster of cells random distributed. Using this referent 3D tumor model and for same concentration of radionuclides (1:100) and energy of beta emitters (1000 keV) which are homogeneously distributed in labeled cells absorbed dose for all cells was calculated. Simulations are done using FOTELP Monte Carlo code, which is modified for this purposes. Results of absorbed dose in cells are given in numerical values (1D distribution) and as the images (2D or 3D distributions). Conclusion Geometrical module for Monte Carlo simulation study can be standardized by introducing referent 3D tumor model at cellular level. This referent 3D tumor model gives most realistic presentation of different tumors at the moment of their detectability. Referent 3D tumor model at

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

Directory of Open Access Journals (Sweden)

Mondry Adrian

2004-08-01

Full Text Available Abstract 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

Modeling chemical systems using cellular automata a textbook and laboratory manual

CERN Document Server

Kier, Lemont B; Cheng, Chao-Kun

2005-01-01

There are few publications on Cellular Automata and certainly no direct competition Insight into a new modeling paradigm Novel approach to the use of in silico modeling to replace or supplement costly labs.

Interaction of E2 glycoprotein with heparan sulfate is crucial for cellular infection of Sindbis virus.

Directory of Open Access Journals (Sweden)

Wuyang Zhu

Full Text Available Cell culture-adapted strains of Sindbis virus (SINV initially attach to cells by the ability to interact with heparan sulfate (HS through selective mutation for positively charged amino acid (aa scattered in E2 glycoprotein (W. B. Klimstra, K. D. Ryman, and R. E. Johnston, J. Virol. 72: 7357-7366, 1998. Here we have further confirmed that interaction of E2 protein with HS is crucial for cellular infection of SINV based on the reverse genetic system of XJ-160 virus, a Sindbis-like virus (SINLV. Both SINV YN87448 and SINLV XJ-160 displayed similar infectivity on BHK-21, Vero, or C6/36 cells, but XJ-160 failed to infect mouse embryonic fibroblast (MEF cells. The molecular mechanisms underlying the selective infectivity of XJ-160 were approached by substituting the E1, E2, or both genes of XJ-160 with that of YN87448, and the chimeric virus was denominated as XJ-160/E1, XJ-160/E2, or XJ-160/E1E2, respectively. In contrast to the parental XJ-160, all chimeric viruses became infectious to wild-type MEF cells (MEF-wt. While MEF-Ext(-/- cells, producing shortened HS chains, were resistant not only to XJ-160, but also to YN87448 as well as the chimeric viruses, indicating that the inability of XJ-160 to infect MEF-wt cells likely due to its incompetent discrimination of cellular HS. Treatment with heparin or HS-degrading enzyme resulted in a substantial decrease in plaque formation by YN87448, XJ-160/E2, and XJ-160/E1E2, but had marginal effect on XJ-160 and XJ-160/E1, suggesting that E2 glycoprotein from YN87448 plays a more important role than does E1 in mediating cellular HS-related cell infection. In addition, the peptide containing 145-150 aa from E2 gene of YN87448 specifically bound to heparin, while the corresponding peptide from the E2 gene of XJ-160 essentially showed no binding to heparin. As a new dataset, these results clearly confirm an essential role of E2 glycoprotein, especially the domain of 145-150 aa, in SINV cellular infection

Modeling of coupled differential equations for cellular chemical signaling pathways: Implications for assay protocols utilized in cellular engineering.

Science.gov (United States)

O'Clock, George D

2016-08-01

Cellular engineering involves modification and control of cell properties, and requires an understanding of fundamentals and mechanisms of action for cellular derived product development. One of the keys to success in cellular engineering involves the quality and validity of results obtained from cell chemical signaling pathway assays. The accuracy of the assay data cannot be verified or assured if the effect of positive feedback, nonlinearities, and interrelationships between cell chemical signaling pathway elements are not understood, modeled, and simulated. Nonlinearities and positive feedback in the cell chemical signaling pathway can produce significant aberrations in assay data collection. Simulating the pathway can reveal potential instability problems that will affect assay results. A simulation, using an electrical analog for the coupled differential equations representing each segment of the pathway, provides an excellent tool for assay validation purposes. With this approach, voltages represent pathway enzyme concentrations and operational amplifier feedback resistance and input resistance values determine pathway gain and rate constants. The understanding provided by pathway modeling and simulation is strategically important in order to establish experimental controls for assay protocol structure, time frames specified between assays, and assay concentration variation limits; to ensure accuracy and reproducibility of results.

Enteropathogenic Escherichia coli, Samonella, Shigella and Yersinia: cellular aspects of host-bacteria interactions in enteric diseases

Directory of Open Access Journals (Sweden)

Reis Roberta

2010-07-01

Full Text Available Abstract A successful infection of the human intestine by enteropathogenic bacteria depends on the ability of bacteria to attach and colonize the intestinal epithelium and, in some cases, to invade the host cell, survive intracellularly and disseminate from cell to cell. To accomplish these processes bacteria have evolved an arsenal of molecules that are mostly secreted by dedicated type III secretion systems, and that interact with the host, subverting normal cellular functions. Here we overview the most important molecular strategies developed by enteropathogenic Escherichia coli, Salmonella enterica, Shigella flexneri, and Yersinia enterocolitica to cause enteric infections. Despite having evolved different effectors, these four microorganisms share common host cellular targets.

Mathematical Modeling and Experimental Validation of Nanoemulsion-Based Drug Transport across Cellular Barriers.

Science.gov (United States)

Kadakia, Ekta; Shah, Lipa; Amiji, Mansoor M

2017-07-01

Nanoemulsions have shown potential in delivering drug across epithelial and endothelial cell barriers, which express efflux transporters. However, their transport mechanisms are not entirely understood. Our goal was to investigate the cellular permeability of nanoemulsion-encapsulated drugs and apply mathematical modeling to elucidate transport mechanisms and sensitive nanoemulsion attributes. Transport studies were performed in Caco-2 cells, using fish oil nanoemulsions and a model substrate, rhodamine-123. Permeability data was modeled using a semi-mechanistic approach, capturing the following cellular processes: endocytotic uptake of the nanoemulsion, release of rhodamine-123 from the nanoemulsion, efflux and passive permeability of rhodamine-123 in aqueous solution. Nanoemulsions not only improved the permeability of rhodamine-123, but were also less sensitive to efflux transporters. The model captured bidirectional permeability results and identified sensitive processes, such as the release of the nanoemulsion-encapsulated drug and cellular uptake of the nanoemulsion. Mathematical description of cellular processes, improved our understanding of transport mechanisms, such as nanoemulsions don't inhibit efflux to improve drug permeability. Instead, their endocytotic uptake, results in higher intracellular drug concentrations, thereby increasing the concentration gradient and transcellular permeability across biological barriers. Modeling results indicated optimizing nanoemulsion attributes like the droplet size and intracellular drug release rate, may further improve drug permeability.

Spatial evolutionary games of interaction among generic cancer cells

DEFF Research Database (Denmark)

Bach, L.A.; Sumpter, D.J.T.; Alsner, J.

2003-01-01

Evolutionary game models of cellular interactions have shown that heterogeneity in the cellular genotypic composition is maintained through evolution to stable coexistence of growth-promoting and non-promoting cell types. We generalise these mean-field models and relax the assumption of perfect m...... at a cellular level. This study thus points a new direction towards more plausible spatial tumour modelling and the understanding of cancerous growth....

A Fluid Model for Performance Analysis in Cellular Networks

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Coupechoux Marceau

2010-01-01

Full Text Available We propose a new framework to study the performance of cellular networks using a fluid model and we derive from this model analytical formulas for interference, outage probability, and spatial outage probability. The key idea of the fluid model is to consider the discrete base station (BS entities as a continuum of transmitters that are spatially distributed in the network. This model allows us to obtain simple analytical expressions to reveal main characteristics of the network. In this paper, we focus on the downlink other-cell interference factor (OCIF, which is defined for a given user as the ratio of its outer cell received power to its inner cell received power. A closed-form formula of the OCIF is provided in this paper. From this formula, we are able to obtain the global outage probability as well as the spatial outage probability, which depends on the location of a mobile station (MS initiating a new call. Our analytical results are compared to Monte Carlo simulations performed in a traditional hexagonal network. Furthermore, we demonstrate an application of the outage probability related to cell breathing and densification of cellular networks.

Integrating cellular metabolism into a multiscale whole-body model.

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Markus Krauss

Full Text Available 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.

Effects of Mechanical Properties on Tumor Invasion: Insights from a Cellular Model

KAUST Repository

Li, YZ

2014-08-01

Understanding the regulating mechanism of tumor invasion is of crucial importance for both fundamental cancer research and clinical applications. Previous in vivo experiments have shown that invasive cancer cells dissociate from the primary tumor and invade into the stroma, forming an irregular invasive morphology. Although cell movements involved in tumor invasion are ultimately driven by mechanical forces of cell-cell interactions and tumor-host interactions, how these mechanical properties affect tumor invasion is still poorly understood. In this study, we use a recently developed two-dimensional cellular model to study the effects of mechanical properties on tumor invasion. We study the effects of cell-cell adhesions as well as the degree of degradation and stiffness of extracellular matrix (ECM). Our simulation results show that cell-cell adhesion relationship must be satisfied for tumor invasion. Increased adhesion to ECM and decreased adhesion among tumor cells result in invasive tumor behaviors. When this invasive behavior occurs, ECM plays an important role for both tumor morphology and the shape of invasive cancer cells. Increased stiffness and stronger degree of degradation of ECM promote tumor invasion, generating more aggressive tumor invasive morphologies. It can also generate irregular shape of invasive cancer cells, protruding towards ECM. The capability of our model suggests it a useful tool to study tumor invasion and might be used to propose optimal treatment in clinical applications.

Modeling cellular networks in fading environments with dominant specular components

KAUST Repository

AlAmmouri, Ahmad

2016-07-26

Stochastic geometry (SG) has been widely accepted as a fundamental tool for modeling and analyzing cellular networks. However, the fading models used with SG analysis are mainly confined to the simplistic Rayleigh fading, which is extended to the Nakagami-m fading in some special cases. However, neither the Rayleigh nor the Nakagami-m accounts for dominant specular components (DSCs) which may appear in realistic fading channels. In this paper, we present a tractable model for cellular networks with generalized two-ray (GTR) fading channel. The GTR fading explicitly accounts for two DSCs in addition to the diffuse components and offers high flexibility to capture diverse fading channels that appear in realistic outdoor/indoor wireless communication scenarios. It also encompasses the famous Rayleigh and Rician fading as special cases. To this end, the prominent effect of DSCs is highlighted in terms of average spectral efficiency. © 2016 IEEE.

Modeling and Analysis of Cellular Networks using Stochastic Geometry: A Tutorial

KAUST Repository

Elsawy, Hesham; Salem, Ahmed Sultan; Alouini, Mohamed-Slim; Win, Moe Z.

2016-01-01

This paper presents a tutorial on stochastic geometry (SG) based analysis for cellular networks. This tutorial is distinguished by its depth with respect to wireless communication details and its focus on cellular networks. The paper starts by modeling and analyzing the baseband interference in a baseline single-tier downlink cellular network with single antenna base stations and universal frequency reuse. Then, it characterizes signal-to-interference-plus-noise-ratio (SINR) and its related performance metrics. In particular, a unified approach to conduct error probability, outage probability, and transmission rate analysis is presented. Although the main focus of the paper is on cellular networks, the presented unified approach applies for other types of wireless networks that impose interference protection around receivers. The paper then extends the unified approach to capture cellular network characteristics (e.g., frequency reuse, multiple antenna, power control, etc.). It also presents numerical examples associated with demonstrations and discussions. To this end, the paper highlights the state-of-the- art research and points out future research directions.

Modeling and Analysis of Cellular Networks using Stochastic Geometry: A Tutorial

KAUST Repository

Elsawy, Hesham

2016-11-03

This paper presents a tutorial on stochastic geometry (SG) based analysis for cellular networks. This tutorial is distinguished by its depth with respect to wireless communication details and its focus on cellular networks. The paper starts by modeling and analyzing the baseband interference in a baseline single-tier downlink cellular network with single antenna base stations and universal frequency reuse. Then, it characterizes signal-to-interference-plus-noise-ratio (SINR) and its related performance metrics. In particular, a unified approach to conduct error probability, outage probability, and transmission rate analysis is presented. Although the main focus of the paper is on cellular networks, the presented unified approach applies for other types of wireless networks that impose interference protection around receivers. The paper then extends the unified approach to capture cellular network characteristics (e.g., frequency reuse, multiple antenna, power control, etc.). It also presents numerical examples associated with demonstrations and discussions. To this end, the paper highlights the state-of-the- art research and points out future research directions.

An agent-based model of cellular dynamics and circadian variability in human endotoxemia.

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Tung T Nguyen

Full Text Available As cellular variability and circadian rhythmicity play critical roles in immune and inflammatory responses, we present in this study an agent-based model of human endotoxemia to examine the interplay between circadian controls, cellular variability and stochastic dynamics of inflammatory cytokines. The model is qualitatively validated by its ability to reproduce circadian dynamics of inflammatory mediators and critical inflammatory responses after endotoxin administration in vivo. Novel computational concepts are proposed to characterize the cellular variability and synchronization of inflammatory cytokines in a population of heterogeneous leukocytes. Our results suggest that there is a decrease in cell-to-cell variability of inflammatory cytokines while their synchronization is increased after endotoxin challenge. Model parameters that are responsible for IκB production stimulated by NFκB activation and for the production of anti-inflammatory cytokines have large impacts on system behaviors. Additionally, examining time-dependent systemic responses revealed that the system is least vulnerable to endotoxin in the early morning and most vulnerable around midnight. Although much remains to be explored, proposed computational concepts and the model we have pioneered will provide important insights for future investigations and extensions, especially for single-cell studies to discover how cellular variability contributes to clinical implications.

The adaptive cruise control vehicles in the cellular automata model

International Nuclear Information System (INIS)

Jiang Rui; Wu Qingsong

2006-01-01

This Letter presented a cellular automata model where the adaptive cruise control vehicles are modelled. In this model, the constant time headway policy is adopted. The fundamental diagram is presented. The simulation results are in good agreement with the analytical ones. The mixture of ACC vehicles with manually driven vehicles is investigated. It is shown that with the introduction of ACC vehicles, the jam can be suppressed

Quantum features of natural cellular automata

International Nuclear Information System (INIS)

Elze, Hans-Thomas

2016-01-01

Cellular automata can show well known features of quantum mechanics, such as a linear rule according to which they evolve and which resembles a discretized version of the Schrödinger equation. This includes corresponding conservation laws. The class of “natural” Hamiltonian cellular automata is based exclusively on integer-valued variables and couplings and their dynamics derives from an Action Principle. They can be mapped reversibly to continuum models by applying Sampling Theory. Thus, “deformed” quantum mechanical models with a finite discreteness scale l are obtained, which for l → 0 reproduce familiar continuum results. We have recently demonstrated that such automata can form “multipartite” systems consistently with the tensor product structures of nonrelativistic many-body quantum mechanics, while interacting and maintaining the linear evolution. Consequently, the Superposition Principle fully applies for such primitive discrete deterministic automata and their composites and can produce the essential quantum effects of interference and entanglement. (paper)

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

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Jinpeng Qi

Full Text Available 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.

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

Science.gov (United States)

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.

A dynamic genetic-hormonal regulatory network model explains multiple cellular behaviors of the root apical meristem of Arabidopsis thaliana.

Science.gov (United States)

García-Gómez, Mónica L; Azpeitia, Eugenio; Álvarez-Buylla, Elena R

2017-04-01

The study of the concerted action of hormones and transcription factors is fundamental to understand cell differentiation and pattern formation during organ development. The root apical meristem of Arabidopsis thaliana is a useful model to address this. It has a stem cell niche near its tip conformed of a quiescent organizer and stem or initial cells around it, then a proliferation domain followed by a transition domain, where cells diminish division rate before transiting to the elongation zone; here, cells grow anisotropically prior to their final differentiation towards the plant base. A minimal model of the gene regulatory network that underlies cell-fate specification and patterning at the root stem cell niche was proposed before. In this study, we update and couple such network with both the auxin and cytokinin hormone signaling pathways to address how they collectively give rise to attractors that correspond to the genetic and hormonal activity profiles that are characteristic of different cell types along A. thaliana root apical meristem. We used a Boolean model of the genetic-hormonal regulatory network to integrate known and predicted regulatory interactions into alternative models. Our analyses show that, after adding some putative missing interactions, the model includes the necessary and sufficient components and regulatory interactions to recover attractors characteristic of the root cell types, including the auxin and cytokinin activity profiles that correlate with different cellular behaviors along the root apical meristem. Furthermore, the model predicts the existence of activity configurations that could correspond to the transition domain. The model also provides a possible explanation for apparently paradoxical cellular behaviors in the root meristem. For example, how auxin may induce and at the same time inhibit WOX5 expression. According to the model proposed here the hormonal regulation of WOX5 might depend on the cell type. Our results

A dynamic genetic-hormonal regulatory network model explains multiple cellular behaviors of the root apical meristem of Arabidopsis thaliana.

Directory of Open Access Journals (Sweden)

Mónica L García-Gómez

2017-04-01

Full Text Available The study of the concerted action of hormones and transcription factors is fundamental to understand cell differentiation and pattern formation during organ development. The root apical meristem of Arabidopsis thaliana is a useful model to address this. It has a stem cell niche near its tip conformed of a quiescent organizer and stem or initial cells around it, then a proliferation domain followed by a transition domain, where cells diminish division rate before transiting to the elongation zone; here, cells grow anisotropically prior to their final differentiation towards the plant base. A minimal model of the gene regulatory network that underlies cell-fate specification and patterning at the root stem cell niche was proposed before. In this study, we update and couple such network with both the auxin and cytokinin hormone signaling pathways to address how they collectively give rise to attractors that correspond to the genetic and hormonal activity profiles that are characteristic of different cell types along A. thaliana root apical meristem. We used a Boolean model of the genetic-hormonal regulatory network to integrate known and predicted regulatory interactions into alternative models. Our analyses show that, after adding some putative missing interactions, the model includes the necessary and sufficient components and regulatory interactions to recover attractors characteristic of the root cell types, including the auxin and cytokinin activity profiles that correlate with different cellular behaviors along the root apical meristem. Furthermore, the model predicts the existence of activity configurations that could correspond to the transition domain. The model also provides a possible explanation for apparently paradoxical cellular behaviors in the root meristem. For example, how auxin may induce and at the same time inhibit WOX5 expression. According to the model proposed here the hormonal regulation of WOX5 might depend on the cell

Radio Channel Modelling for UAV Communication over Cellular Networks

DEFF Research Database (Denmark)

Amorim, Rafhael Medeiros de; Nguyen, Huan Cong; Mogensen, Preben Elgaard

2017-01-01

The main goal of this paper is to obtain models for path loss exponents and shadowing for the radio channel between airborne Unmanned Aerial Vehicles (UAVs) and cellular networks. In this pursuit, field measurements were conducted in live LTE networks at the 800 MHz frequency band, using a commer...

Stochastic processes, multiscale modeling, and numerical methods for computational cellular biology

CERN Document Server

2017-01-01

This book focuses on the modeling and mathematical analysis of stochastic dynamical systems along with their simulations. The collected chapters will review fundamental and current topics and approaches to dynamical systems in cellular biology. This text aims to develop improved mathematical and computational methods with which to study biological processes. At the scale of a single cell, stochasticity becomes important due to low copy numbers of biological molecules, such as mRNA and proteins that take part in biochemical reactions driving cellular processes. When trying to describe such biological processes, the traditional deterministic models are often inadequate, precisely because of these low copy numbers. This book presents stochastic models, which are necessary to account for small particle numbers and extrinsic noise sources. The complexity of these models depend upon whether the biochemical reactions are diffusion-limited or reaction-limited. In the former case, one needs to adopt the framework of s...

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

International Nuclear Information System (INIS)

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. (paper)

Interaction of HSP20 with a viral RdRp changes its sub-cellular localization and distribution pattern in plants.

Science.gov (United States)

Li, Jing; Xiang, Cong-Ying; Yang, Jian; Chen, Jian-Ping; Zhang, Heng-Mu

2015-09-11

Small heat shock proteins (sHSPs) perform a fundamental role in protecting cells against a wide array of stresses but their biological function during viral infection remains unknown. Rice stripe virus (RSV) causes a severe disease of rice in Eastern Asia. OsHSP20 and its homologue (NbHSP20) were used as baits in yeast two-hybrid (YTH) assays to screen an RSV cDNA library and were found to interact with the viral RNA-dependent RNA polymerase (RdRp) of RSV. Interactions were confirmed by pull-down and BiFC assays. Further analysis showed that the N-terminus (residues 1-296) of the RdRp was crucial for the interaction between the HSP20s and viral RdRp and responsible for the alteration of the sub-cellular localization and distribution pattern of HSP20s in protoplasts of rice and epidermal cells of Nicotiana benthamiana. This is the first report that a plant virus or a viral protein alters the expression pattern or sub-cellular distribution of sHSPs.

Evolution of altruism in spatial prisoner's dilemma: Intra- and inter-cellular interactions

Science.gov (United States)

Yokoi, Hiroki; Uehara, Takashi; Sakata, Tomoyuki; Naito, Hiromi; Morita, Satoru; Tainaka, Kei-ichi

2014-12-01

Iterated prisoner's dilemma game is carried out on lattice with “colony” structure. Each cell is regarded as a colony which contains plural players with an identical strategy. Both intra- and inter-cellular interactions are assumed. In the former a player plays with all other players in the same colony, while in the latter he plays with one player each from adjacent colonies. Spatial patterns among four typical strategies exhibit various dynamics and winners. Both theory and simulation reveal that All Cooperation (AC) wins, when the members of colony or the intensity of noise increases. This result explains the evolution of altruism in animal societies, even though errors easily occur in animal communications.

On the derivation of approximations to cellular automata models and the assumption of independence.

Science.gov (United States)

Davies, K J; Green, J E F; Bean, N G; Binder, B J; Ross, J V

2014-07-01

Cellular automata are discrete agent-based models, generally used in cell-based applications. There is much interest in obtaining continuum models that describe the mean behaviour of the agents in these models. Previously, continuum models have been derived for agents undergoing motility and proliferation processes, however, these models only hold under restricted conditions. In order to narrow down the reason for these restrictions, we explore three possible sources of error in deriving the model. These sources are the choice of limiting arguments, the use of a discrete-time model as opposed to a continuous-time model and the assumption of independence between the state of sites. We present a rigorous analysis in order to gain a greater understanding of the significance of these three issues. By finding a limiting regime that accurately approximates the conservation equation for the cellular automata, we are able to conclude that the inaccuracy between our approximation and the cellular automata is completely based on the assumption of independence. Copyright © 2014 Elsevier Inc. All rights reserved.

Fire and Heat Spreading Model Based on Cellular Automata Theory

Science.gov (United States)

Samartsev, A. A.; Rezchikov, A. F.; Kushnikov, V. A.; Ivashchenko, V. A.; Bogomolov, A. S.; Filimonyuk, L. Yu; Dolinina, O. N.; Kushnikov, O. V.; Shulga, T. E.; Tverdokhlebov, V. A.; Fominykh, D. S.

2018-05-01

The distinctive feature of the proposed fire and heat spreading model in premises is the reduction of the computational complexity due to the use of the theory of cellular automata with probability rules of behavior. The possibilities and prospects of using this model in practice are noted. The proposed model has a simple mechanism of integration with agent-based evacuation models. The joint use of these models could improve floor plans and reduce the time of evacuation from premises during fires.

A cellular automata intraurban model with prices and income-differentiated actors

NARCIS (Netherlands)

Furtado, B.A.; Ettema, D.F.; Ruiz, R.M.; Hurkens, J.; Delden, H. van

2012-01-01

This paper presents an intraurban cellular automata model that is an extension to White and Engelen’s pioneering model. The paper’s main contribution is to distinguish between agglomerative eff ects, determined by the attraction of the neighbourhood, and disagglomerative eff ects, driven by land

System-level insights into the cellular interactome of a non-model organism: inferring, modelling and analysing functional gene network of soybean (Glycine max.

Directory of Open Access Journals (Sweden)

Yungang Xu

Full Text Available Cellular interactome, in which genes and/or their products interact on several levels, forming transcriptional regulatory-, protein interaction-, metabolic-, signal transduction networks, etc., has attracted decades of research focuses. However, such a specific type of network alone can hardly explain the various interactive activities among genes. These networks characterize different interaction relationships, implying their unique intrinsic properties and defects, and covering different slices of biological information. Functional gene network (FGN, a consolidated interaction network that models fuzzy and more generalized notion of gene-gene relations, have been proposed to combine heterogeneous networks with the goal of identifying functional modules supported by multiple interaction types. There are yet no successful precedents of FGNs on sparsely studied non-model organisms, such as soybean (Glycine max, due to the absence of sufficient heterogeneous interaction data. We present an alternative solution for inferring the FGNs of soybean (SoyFGNs, in a pioneering study on the soybean interactome, which is also applicable to other organisms. SoyFGNs exhibit the typical characteristics of biological networks: scale-free, small-world architecture and modularization. Verified by co-expression and KEGG pathways, SoyFGNs are more extensive and accurate than an orthology network derived from Arabidopsis. As a case study, network-guided disease-resistance gene discovery indicates that SoyFGNs can provide system-level studies on gene functions and interactions. This work suggests that inferring and modelling the interactome of a non-model plant are feasible. It will speed up the discovery and definition of the functions and interactions of other genes that control important functions, such as nitrogen fixation and protein or lipid synthesis. The efforts of the study are the basis of our further comprehensive studies on the soybean functional

A Cellular Automata-based Model for Simulating Restitution Property in a Single Heart Cell.

Science.gov (United States)

Sabzpoushan, Seyed Hojjat; Pourhasanzade, Fateme

2011-01-01

Ventricular fibrillation is the cause of the most sudden mortalities. Restitution is one of the specific properties of ventricular cell. The recent findings have clearly proved the correlation between the slope of restitution curve with ventricular fibrillation. This; therefore, mandates the modeling of cellular restitution to gain high importance. A cellular automaton is a powerful tool for simulating complex phenomena in a simple language. A cellular automaton is a lattice of cells where the behavior of each cell is determined by the behavior of its neighboring cells as well as the automata rule. In this paper, a simple model is depicted for the simulation of the property of restitution in a single cardiac cell using cellular automata. At first, two state variables; action potential and recovery are introduced in the automata model. In second, automata rule is determined and then recovery variable is defined in such a way so that the restitution is developed. In order to evaluate the proposed model, the generated restitution curve in our study is compared with the restitution curves from the experimental findings of valid sources. Our findings indicate that the presented model is not only capable of simulating restitution in cardiac cell, but also possesses the capability of regulating the restitution curve.

Modeling virtualized downlink cellular networks with ultra-dense small cells

KAUST Repository

Ibrahim, Hazem

2015-09-11

The unrelenting increase in the mobile users\\' populations and traffic demand drive cellular network operators to densify their infrastructure. Network densification increases the spatial frequency reuse efficiency while maintaining the signal-to-interference-plus-noise-ratio (SINR) performance, hence, increases the spatial spectral efficiency and improves the overall network performance. However, control signaling in such dense networks consumes considerable bandwidth and limits the densification gain. Radio access network (RAN) virtualization via control plane (C-plane) and user plane (U-plane) splitting has been recently proposed to lighten the control signaling burden and improve the network throughput. In this paper, we present a tractable analytical model for virtualized downlink cellular networks, using tools from stochastic geometry. We then apply the developed modeling framework to obtain design insights for virtualized RANs and quantify associated performance improvement. © 2015 IEEE.

Complex Automata: Multi-scale Modeling with Coupled Cellular Automata

NARCIS (Netherlands)

Hoekstra, A.G.; Caiazzo, A.; Lorenz, E.; Falcone, J.-L.; Chopard, B.; Hoekstra, A.G.; Kroc, J.; Sloot, P.M.A.

2010-01-01

Cellular Automata (CA) are generally acknowledged to be a powerful way to describe and model natural phenomena [1-3]. There are even tempting claims that nature itself is one big (quantum) information processing system, e.g. [4], and that CA may actually be nature’s way to do this processing [5-7].

Uniform and localized corrosion modelling by means of probabilistic cellular automata

International Nuclear Information System (INIS)

Perez-Brokate, Cristian

2016-01-01

Numerical modelling is complementary tool for corrosion prediction. The objective of this work is to develop a corrosion model by means of a probabilistic cellular automata approach at a mesoscopic scale. In this work, we study the morphological evolution and kinetics of corrosion. This model couples electrochemical oxidation and reduction reactions. Regarding kinetics, cellular automata models are able to describe current as a function of the applied potential for a redox reaction on an inert electrode. The inclusion of probabilities allows the description of the stochastic nature of anodic and cathodic reactions. Corrosion morphology has been studied in different context: generalised corrosion, pitting corrosion and corrosion in an occluded environment. a general tendency of two regimes is found. a first regime of uniform corrosion where the anodic and cathodic reactions occur homogeneously over the surface. a second regime of localized corrosion when there is a spatial separation of anodic and cathodic zones, with an increase of anodic reaction rate. (author) [fr

MODELING OF FUTURE LAND COVER LAND USE CHANGE IN NORTH CAROLINA USING MARKOV CHAIN AND CELLULAR AUTOMATA MODEL

OpenAIRE

Mohammad Sayemuzzaman; Manoj K. Jha

2014-01-01

State wide variant topographic features in North Carolina attract the hydro-climatologist. There is none modeling study found that predict future Land Cover Land Use (LCLU) change for whole North Carolina. In this study, satellite-derived land cover maps of year 1992, 2001 and 2006 of North Carolina were integrated within the framework of the Markov-Cellular Automata (Markov-CA) model which combines the Markov chain and Cellular Automata (CA) techniques. A Multi-Criteria Evaluation (MCE) was ...

Cellular retention of radioactivity and increased radiation dose. Model experiments with EGF-dextran

International Nuclear Information System (INIS)

Sundberg, Aasa Liljegren; Blomquist, Erik; Carlsson, Joergen; Steffen, Ann-Charlott; Gedda, Lars

2003-01-01

Targeting of tumor cells with radiolabeled biomolecules is a possible approach to inactivate disseminated tumor cells. However, rapid degradation of the biomolecules after cellular internalization and subsequent excretion of the radioactivity is a problem. We studied the possibility of using dextran as a carrier of radionuclides to improve the intracellular retention. An EGF-dextran conjugate, aimed for targeting of tumor cells overexpressing the EGF-receptor, was used as model. Retention tests were performed with 125 I on different parts: [ 125 I]-EGF-dextran-[ 125 I], [ 125 I]-EGF-dextran and EGF-dextran-[ 125 I]. Comparisons were made with [ 125 I]-EGF. The radiolabeled compounds were incubated with cultured glioma cells for different times. The cellular retention of radioactivity was then measured for up to 24 h. Expected radiation doses at the cellular level were calculated assuming that 131 I, instead of 125 I, was coupled to EGF and EGF-dextran. The results indicated that the EGF-part of the conjugate was degraded and the EGF-attached radioactivity was rapidly excreted, whereas radioactivity on dextran was retained intracellularly to a high degree, i.e. 70-80% of the radioactivity bound to dextran was still cell-associated after 24 h. The retention after 24 h was significantly higher (p < 0.001) when the radioactivity was on the dextran instead of the EGF-part. The radiolabeled EGF-dextran had a notably high specific radioactivity; up to 11 MBq/μg. There was potential for at least hundred times increased radiation dose per receptor interaction when the radioactivity was on the dextran part. The advantage with radioactivity on the dextran part was the high cellular retention and the high specific radioactivity (higher than previously reported for other residualizing labels) without severe loss of receptor specific binding. Thus, dextran seems suitable as a carrier of radionuclides aimed for therapy and gives potential for a highly increased radiation dose

Quantitative Analysis of Intra Urban Growth Modeling using socio economic agents by combining cellular automata model with agent based model

Science.gov (United States)

Singh, V. K.; Jha, A. K.; Gupta, K.; Srivastav, S. K.

2017-12-01

Recent studies indicate that there is a significant improvement in the urban land use dynamics through modeling at finer spatial resolutions. Geo-computational models such as cellular automata and agent based model have given evident proof regarding the quantification of the urban growth pattern with urban boundary. In recent studies, socio- economic factors such as demography, education rate, household density, parcel price of the current year, distance to road, school, hospital, commercial centers and police station are considered to the major factors influencing the Land Use Land Cover (LULC) pattern of the city. These factors have unidirectional approach to land use pattern which makes it difficult to analyze the spatial aspects of model results both quantitatively and qualitatively. In this study, cellular automata model is combined with generic model known as Agent Based Model to evaluate the impact of socio economic factors on land use pattern. For this purpose, Dehradun an Indian city is selected as a case study. Socio economic factors were collected from field survey, Census of India, Directorate of economic census, Uttarakhand, India. A 3X3 simulating window is used to consider the impact on LULC. Cellular automata model results are examined for the identification of hot spot areas within the urban area and agent based model will be using logistic based regression approach where it will identify the correlation between each factor on LULC and classify the available area into low density, medium density, high density residential or commercial area. In the modeling phase, transition rule, neighborhood effect, cell change factors are used to improve the representation of built-up classes. Significant improvement is observed in the built-up classes from 84 % to 89 %. However after incorporating agent based model with cellular automata model the accuracy improved from 89 % to 94 % in 3 classes of urban i.e. low density, medium density and commercial classes

Modeling cellular networks in fading environments with dominant specular components

KAUST Repository

Alammouri, Ahmad; Elsawy, Hesham; Salem, Ahmed Sultan; Di Renzo, Marco; Alouini, Mohamed-Slim

2016-01-01

to the Nakagami-m fading in some special cases. However, neither the Rayleigh nor the Nakagami-m accounts for dominant specular components (DSCs) which may appear in realistic fading channels. In this paper, we present a tractable model for cellular networks

The emergence of extracellular matrix mechanics and cell traction forces as important regulators of cellular self-organization.

Science.gov (United States)

Checa, Sara; Rausch, Manuel K; Petersen, Ansgar; Kuhl, Ellen; Duda, Georg N

2015-01-01

Physical cues play a fundamental role in a wide range of biological processes, such as embryogenesis, wound healing, tumour invasion and connective tissue morphogenesis. Although it is well known that during these processes, cells continuously interact with the local extracellular matrix (ECM) through cell traction forces, the role of these mechanical interactions on large scale cellular and matrix organization remains largely unknown. In this study, we use a simple theoretical model to investigate cellular and matrix organization as a result of mechanical feedback signals between cells and the surrounding ECM. The model includes bi-directional coupling through cellular traction forces to deform the ECM and through matrix deformation to trigger cellular migration. In addition, we incorporate the mechanical contribution of matrix fibres and their reorganization by the cells. We show that a group of contractile cells will self-polarize at a large scale, even in homogeneous environments. In addition, our simulations mimic the experimentally observed alignment of cells in the direction of maximum stiffness and the building up of tension as a consequence of cell and fibre reorganization. Moreover, we demonstrate that cellular organization is tightly linked to the mechanical feedback loop between cells and matrix. Cells with a preference for stiff environments have a tendency to form chains, while cells with a tendency for soft environments tend to form clusters. The model presented here illustrates the potential of simple physical cues and their impact on cellular self-organization. It can be used in applications where cell-matrix interactions play a key role, such as in the design of tissue engineering scaffolds and to gain a basic understanding of pattern formation in organogenesis or tissue regeneration.

Modeling Adsorption-Desorption Processes at the Intermolecular Interactions Level

Science.gov (United States)

Varfolomeeva, Vera V.; Terentev, Alexey V.

2018-01-01

Modeling of the surface adsorption and desorption processes, as well as the diffusion, are of considerable interest for the physical phenomenon under study in ground tests conditions. When imitating physical processes and phenomena, it is important to choose the correct parameters to describe the adsorption of gases and the formation of films on the structural materials surface. In the present research the adsorption-desorption processes on the gas-solid interface are modeled with allowance for diffusion. Approaches are proposed to describe the adsorbate distribution on the solid body surface at the intermolecular interactions level. The potentials of the intermolecular interaction of water-water, water-methane and methane-methane were used to adequately modeling the real physical and chemical processes. The energies calculated by the B3LYP/aug-cc-pVDZ method. Computational algorithms for determining the average molecule area in a dense monolayer, are considered here. Differences in modeling approaches are also given: that of the proposed in this work and the previously approved probabilistic cellular automaton (PCA) method. It has been shown that the main difference is due to certain limitations of the PCA method. The importance of accounting the intermolecular interactions via hydrogen bonding has been indicated. Further development of the adsorption-desorption processes modeling will allow to find the conditions for of surface processes regulation by means of quantity adsorbed molecules control. The proposed approach to representing the molecular system significantly shortens the calculation time in comparison with the use of atom-atom potentials. In the future, this will allow to modeling the multilayer adsorption at a reasonable computational cost.

A hybrid parallel framework for the cellular Potts model simulations

Energy Technology Data Exchange (ETDEWEB)

Jiang, Yi [Los Alamos National Laboratory; He, Kejing [SOUTH CHINA UNIV; Dong, Shoubin [SOUTH CHINA UNIV

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 approach 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}).

Cellular interaction of a layer-by-layer based drug delivery system depending on material properties and cell types.

Science.gov (United States)

Brueckner, Mandy; Jankuhn, Steffen; Jülke, Eva-Maria; Reibetanz, Uta

2018-01-01

Drug delivery systems (DDS) and their interaction with cells are a controversial topic in the development of therapeutic concepts and approaches. On one hand, DDS are very useful for protected and targeted transport of defined dosages of active agents. On the other hand, their physicochemical properties such as material, size, shape, charge, or stiffness have a huge impact on cellular uptake and intracellular processing. Additionally, even identical DDS can undergo a completely diverse interaction with different cell types. However, quite often in in vitro DDS/cell interaction experiments, those aspects are not considered and DDS and cells are randomly chosen. Hence, our investigations provide an insight into layer-by-layer designed microcarriers with modifications of only some of the most important parameters (surface charge, stiffness, and applied microcarrier/cell ratio) and their influence on cellular uptake and viability. We also considered the interaction of these differently equipped DDS with several cell types and investigated professional phagocytes (neutrophil granulocytes; macrophages) as well as non-professional phagocytes (epithelial cells) under comparable conditions. We found that even small modifications such as layer-by-layer (LbL)-microcarriers with positive or negative surface charge, or LbL-microcarriers with solid core or as hollow capsules but equipped with the same surface properties, show significant differences in interaction and viability, and several cell types react very differently to the offered DDS. As a consequence, the properties of the DDS have to be carefully chosen with respect to the addressed cell type with the aim to efficiently transport a desired agent.

Load-aware modeling for uplink cellular networks in a multi-channel environment

KAUST Repository

Alammouri, Ahmad; Elsawy, Hesham; Alouini, Mohamed-Slim

2014-01-01

We exploit tools from stochastic geometry to develop a tractable analytical approach for modeling uplink cellular networks. The developed model is load aware and accounts for per-user power control as well as the limited transmit power constraint

Thymocyte migration: an affair of multiple cellular interactions?

Directory of Open Access Journals (Sweden)

Savino W.

2003-01-01

Full Text Available Cell migration is a crucial event in the general process of thymocyte differentiation. The cellular interactions involved in the control of this migration are beginning to be defined. At least chemokines and extracellular matrix proteins appear to be part of the game. Cells of the thymic microenvironment produce these two groups of molecules, whereas developing thymocytes express the corresponding receptors. Moreover, although chemokines and extracellular matrix can drive thymocyte migration per se, a combined role for these molecules appears to contribute to the resulting migration patterns of thymocytes in their various stages of differentiation. The dynamics of chemokine and extracellular matrix production and degradation is not yet well understood. However, matrix metalloproteinases are likely to play a role in the breakdown of intrathymic extracellular matrix contents. Thus, the physiological migration of thymocytes should be envisioned as a resulting vector of multiple, simultaneous and/or sequential stimuli involving chemokines, adhesive and de-adhesive extracellular matrix proteins, as well as matrix metalloproteinases. Accordingly, it is conceivable that any pathological change in any of these loops may result in the alteration of normal thymocyte migration. This seems to be the case in murine infection by the protozoan parasite Trypanosoma cruzi, the causative agent of Chagas' disease. A better knowledge of the physiological mechanisms governing thymocyte migration will provide new clues for designing therapeutic strategies targeting developing T cells.

Frequency-dependent micromechanics of cellularized biopolymer networks

Science.gov (United States)

Jones, Chris; Kim, Jihan; McIntyre, David; Sun, Bo

Mechanical interactions between cells and the extracellular matrix (ECM) influence many cellular behaviors such as growth, differentiation, and migration. These are dynamic processes in which the cells actively remodel the ECM. Reconstituted collagen gel is a common model ECM for studying cell-ECM interactions in vitro because collagen is the most abundant component of mammalian ECM and gives the ECM its material stiffness. We embed micron-sized particles in collagen and use holographic optical tweezers to apply forces to the particles in multiple directions and over a range of frequencies up to 10 Hz. We calculate the local compliance and show that it is dependent on both the direction and frequency of the applied force. Performing the same measurement on many particles allows us to characterize the spatial inhomogeneity of the mechanical properties and shows that the compliance decreases at higher frequencies. Performing these measurements on cell-populated collagen gels shows that cellular remodeling of the ECM changes the mechanical properties of the collagen and we investigate whether this change is dependent on the local strain and distance from nearby cells.

Interacting factors and cellular localization of SR protein-specific kinase Dsk1

International Nuclear Information System (INIS)

Tang, Zhaohua; Luca, Maria; Taggart-Murphy, Laura; Portillio, Jessica; Chang, Cathey; Guven, Ayse; Lin, Ren-Jang; Murray, Johanne; Carr, Antony

2012-01-01

Schizosaccharomyces pombe Dsk1 is an SR protein-specific kinase (SRPK), whose homologs have been identified in every eukaryotic organism examined. Although discovered as a mitotic regulator with protein kinase activity toward SR splicing factors, it remains largely unknown about what and how Dsk1 contributes to cell cycle and pre-mRNA splicing. In this study, we investigated the Dsk1 function by determining interacting factors and cellular localization of the kinase. Consistent with its reported functions, we found that pre-mRNA processing and cell cycle factors are prominent among the proteins co-purified with Dsk1. The identification of these factors led us to find Rsd1 as a novel Dsk1 substrate, as well as the involvement of Dsk1 in cellular distribution of poly(A) + RNA. In agreement with its role in nuclear events, we also found that Dsk1 is mainly localized in the nucleus during G 2 phase and at mitosis. Furthermore, we revealed the oscillation of Dsk1 protein in a cell cycle-dependent manner. This paper marks the first comprehensive analysis of in vivo Dsk1-associated proteins in fission yeast. Our results reflect the conserved role of SRPK family in eukaryotic organisms, and provide information about how Dsk1 functions in pre-mRNA processing and cell-division cycle.

Interacting factors and cellular localization of SR protein-specific kinase Dsk1

Energy Technology Data Exchange (ETDEWEB)

Tang, Zhaohua, E-mail: ztang@jsd.claremont.edu [W.M. Keck Science Center, The Claremont Colleges, Claremont, CA 91711 (United States); Luca, Maria; Taggart-Murphy, Laura; Portillio, Jessica; Chang, Cathey; Guven, Ayse [W.M. Keck Science Center, The Claremont Colleges, Claremont, CA 91711 (United States); Lin, Ren-Jang [Department of Molecular and Cellular Biology, Beckman Research Institute of the City of Hope, Duarte, CA 91010 (United States); Murray, Johanne; Carr, Antony [Genome Damage and Stability Center, University of Sussex, Falmer, BN1 9RQ (United Kingdom)

2012-10-01

Schizosaccharomyces pombe Dsk1 is an SR protein-specific kinase (SRPK), whose homologs have been identified in every eukaryotic organism examined. Although discovered as a mitotic regulator with protein kinase activity toward SR splicing factors, it remains largely unknown about what and how Dsk1 contributes to cell cycle and pre-mRNA splicing. In this study, we investigated the Dsk1 function by determining interacting factors and cellular localization of the kinase. Consistent with its reported functions, we found that pre-mRNA processing and cell cycle factors are prominent among the proteins co-purified with Dsk1. The identification of these factors led us to find Rsd1 as a novel Dsk1 substrate, as well as the involvement of Dsk1 in cellular distribution of poly(A){sup +} RNA. In agreement with its role in nuclear events, we also found that Dsk1 is mainly localized in the nucleus during G{sub 2} phase and at mitosis. Furthermore, we revealed the oscillation of Dsk1 protein in a cell cycle-dependent manner. This paper marks the first comprehensive analysis of in vivo Dsk1-associated proteins in fission yeast. Our results reflect the conserved role of SRPK family in eukaryotic organisms, and provide information about how Dsk1 functions in pre-mRNA processing and cell-division cycle.

Platinum nanozymes recover cellular ROS homeostasis in an oxidative stress-mediated disease model

Science.gov (United States)

Moglianetti, Mauro; de Luca, Elisa; Pedone, Deborah; Marotta, Roberto; Catelani, Tiziano; Sartori, Barbara; Amenitsch, Heinz; Retta, Saverio Francesco; Pompa, Pier Paolo

2016-02-01

In recent years, the use of nanomaterials as biomimetic enzymes has attracted great interest. In this work, we show the potential of biocompatible platinum nanoparticles (Pt NPs) as antioxidant nanozymes, which combine abundant cellular internalization and efficient scavenging activity of cellular reactive oxygen species (ROS), thus simultaneously integrating the functions of nanocarriers and antioxidant drugs. Careful toxicity assessment and intracellular tracking of Pt NPs proved their cytocompatibility and high cellular uptake, with compartmentalization within the endo/lysosomal vesicles. We have demonstrated that Pt NPs possess strong and broad antioxidant properties, acting as superoxide dismutase, catalase, and peroxidase enzymes, with similar or even superior performance than natural enzymes, along with higher adaptability to the changes in environmental conditions. We then exploited their potent activity as radical scavenging materials in a cellular model of an oxidative stress-related disorder, namely human Cerebral Cavernous Malformation (CCM) disease, which is associated with a significant increase in intracellular ROS levels. Noteworthily, we found that Pt nanozymes can efficiently reduce ROS levels, completely restoring the cellular physiological homeostasis.In recent years, the use of nanomaterials as biomimetic enzymes has attracted great interest. In this work, we show the potential of biocompatible platinum nanoparticles (Pt NPs) as antioxidant nanozymes, which combine abundant cellular internalization and efficient scavenging activity of cellular reactive oxygen species (ROS), thus simultaneously integrating the functions of nanocarriers and antioxidant drugs. Careful toxicity assessment and intracellular tracking of Pt NPs proved their cytocompatibility and high cellular uptake, with compartmentalization within the endo/lysosomal vesicles. We have demonstrated that Pt NPs possess strong and broad antioxidant properties, acting as superoxide

Phase transitions and hysteresis in a cellular automata-based model of opinion formation

International Nuclear Information System (INIS)

Kacperski, K.; Holyst, J.A.

1996-01-01

A particular case of a cellular automata-based model of two-state opinion formation in social groups with a strong leader is studied. We consider a 2D Euclidian geometry of open-quotes social spaceclose quotes and mutual interactions ∝ 1/r n . The model shows an interesting dynamics which can be analytically calculated. There are two stable states of the system: a cluster around the leader and unification. Unstable clusters may also appear. A variation in parameters such as the leader's strength or the open-quotes social temperatureclose quotes can change the size of a cluster or, when they reach some critical values, make the system jump into another state. For a certain range of parameters the system exhibits bistability and hysteresis phenomena. We obtained explicit formulas for the cluster size, critical values, make the system jump into another state. For a certain range of parameters the system exhibits bistability and hysteresis phenomena. We obtained explicit formulas for the cluster size, critical leader's strength, and critical open-quotes social temperature.close quotes These analytical results are verified by computer simulations

Cellular Automata Based Modeling for Evaluating Different Bus Stop Designs in China

Directory of Open Access Journals (Sweden)

Haoyang Ding

2015-01-01

Full Text Available A cellular automaton model is proposed to simulate mixed traffic flow composed of motor vehicles and bicycles near bus stops. Three typical types of bus stops which are common in China are considered in the model, including two types of curbside bus stops and one type of bus bay stops. Passenger transport capacity of three types of bus stops, which is applied to evaluate the bus stop design, is calculated based on the corresponding traffic flow rate. According to the simulation results, the flow rates of both motor vehicles and bicycles exhibit phase transition from free flow to the saturation one at the critical point. The results also show that the larger the interaction between motor vehicle and bicycle flow is near curbside bus stops, the more the value of saturated flows drops. Curbside bus stops are more suitable when the conflicts between two flows are small and the inflow rate of motor vehicles is low. On the contrary, bus bay stops should be applied due to their ability to reduce traffic conflicts. Findings of this study can provide useful suggestions on bus stop selection considering different inflow rate of motor vehicles and bicycles simultaneously.

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

Science.gov (United States)

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.

An improved multi-value cellular automata model for heterogeneous bicycle traffic flow

Energy Technology Data Exchange (ETDEWEB)

Jin, Sheng [College of Civil Engineering and Architecture, Zhejiang University, Hangzhou, 310058 China (China); Qu, Xiaobo [Griffith School of Engineering, Griffith University, Gold Coast, 4222 Australia (Australia); Xu, Cheng [Department of Transportation Management Engineering, Zhejiang Police College, Hangzhou, 310053 China (China); College of Transportation, Jilin University, Changchun, 130022 China (China); Ma, Dongfang, E-mail: mdf2004@zju.edu.cn [Ocean College, Zhejiang University, Hangzhou, 310058 China (China); Wang, Dianhai [College of Civil Engineering and Architecture, Zhejiang University, Hangzhou, 310058 China (China)

2015-10-16

This letter develops an improved multi-value cellular automata model for heterogeneous bicycle traffic flow taking the higher maximum speed of electric bicycles into consideration. The update rules of both regular and electric bicycles are improved, with maximum speeds of two and three cells per second respectively. Numerical simulation results for deterministic and stochastic cases are obtained. The fundamental diagrams and multiple states effects under different model parameters are analyzed and discussed. Field observations were made to calibrate the slowdown probabilities. The results imply that the improved extended Burgers cellular automata (IEBCA) model is more consistent with the field observations than previous models and greatly enhances the realism of the bicycle traffic model. - Highlights: • We proposed an improved multi-value CA model with higher maximum speed. • Update rules are introduced for heterogeneous bicycle traffic with maximum speed 2 and 3 cells/s. • Simulation results of the proposed model are consistent with field bicycle data. • Slowdown probabilities of both regular and electric bicycles are calibrated.

An improved multi-value cellular automata model for heterogeneous bicycle traffic flow

International Nuclear Information System (INIS)

Jin, Sheng; Qu, Xiaobo; Xu, Cheng; Ma, Dongfang; Wang, Dianhai

2015-01-01

This letter develops an improved multi-value cellular automata model for heterogeneous bicycle traffic flow taking the higher maximum speed of electric bicycles into consideration. The update rules of both regular and electric bicycles are improved, with maximum speeds of two and three cells per second respectively. Numerical simulation results for deterministic and stochastic cases are obtained. The fundamental diagrams and multiple states effects under different model parameters are analyzed and discussed. Field observations were made to calibrate the slowdown probabilities. The results imply that the improved extended Burgers cellular automata (IEBCA) model is more consistent with the field observations than previous models and greatly enhances the realism of the bicycle traffic model. - Highlights: • We proposed an improved multi-value CA model with higher maximum speed. • Update rules are introduced for heterogeneous bicycle traffic with maximum speed 2 and 3 cells/s. • Simulation results of the proposed model are consistent with field bicycle data. • Slowdown probabilities of both regular and electric bicycles are calibrated

Interaction between cellular retinoic acid-binding protein II and histone hypoacetylation in renal cell carcinoma

OpenAIRE

Viroj Wiwanitkit

2008-01-01

Renal cell carcinoma is a rare but serious malignancy. Since a reduction in the level of retinoic acid receptor beta 2 (RARbeta2) expression in cancer cells due in part to histone hypoacetylation which is controlled by histone deacetylase (HD), the study on the interaction between cellular retinoic acid-binding proteins II (CRABP II), which is proposed to have its potential influence on retinoic acid (RA) response, and HD can be useful. Comparing to CARBP II and HD, the CARBP II-HD poses the ...

Unified tractable model for downlink MIMO cellular networks using stochastic geometry

KAUST Repository

Afify, Laila H.

2016-07-26

Several research efforts are invested to develop stochastic geometry models for cellular networks with multiple antenna transmission and reception (MIMO). On one hand, there are models that target abstract outage probability and ergodic rate for simplicity. On the other hand, there are models that sacrifice simplicity to target more tangible performance metrics such as the error probability. Both types of models are completely disjoint in terms of the analytic steps to obtain the performance measures, which makes it challenging to conduct studies that account for different performance metrics. This paper unifies both techniques and proposes a unified stochastic-geometry based mathematical paradigm to account for error probability, outage probability, and ergodic rates in MIMO cellular networks. The proposed model is also unified in terms of the antenna configurations and leads to simpler error probability analysis compared to existing state-of-the-art models. The core part of the analysis is based on abstracting unnecessary information conveyed within the interfering signals by assuming Gaussian signaling. To this end, the accuracy of the proposed framework is verified against state-of-the-art models as well as system level simulations. We provide via this unified study insights on network design by reflecting system parameters effect on different performance metrics. © 2016 IEEE.

Designing beauty the art of cellular automata

CERN Document Server

Martínez, Genaro

2016-01-01

This fascinating, colourful book offers in-depth insights and first-hand working experiences in the production of art works, using simple computational models with rich morphological behaviour, at the edge of mathematics, computer science, physics and biology. It organically combines ground breaking scientific discoveries in the theory of computation and complex systems with artistic representations of the research results. In this appealing book mathematicians, computer scientists, physicists, and engineers brought together marvelous and esoteric patterns generated by cellular automata, which are arrays of simple machines with complex behavior. Configurations produced by cellular automata uncover mechanics of dynamic patterns formation, their propagation and interaction in natural systems: heart pacemaker, bacterial membrane proteins, chemical rectors, water permeation in soil, compressed gas, cell division, population dynamics, reaction-diffusion media and self-organisation. The book inspires artists to tak...

Analyses of Dynein Heavy Chain Mutations Reveal Complex Interactions Between Dynein Motor Domains and Cellular Dynein Functions

Science.gov (United States)

Sivagurunathan, Senthilkumar; Schnittker, Robert R.; Razafsky, David S.; Nandini, Swaran; Plamann, Michael D.; King, Stephen J.

2012-01-01

Cytoplasmic dynein transports cargoes for a variety of crucial cellular functions. However, since dynein is essential in most eukaryotic organisms, the in-depth study of the cellular function of dynein via genetic analysis of dynein mutations has not been practical. Here, we identify and characterize 34 different dynein heavy chain mutations using a genetic screen of the ascomycete fungus Neurospora crassa, in which dynein is nonessential. Interestingly, our studies show that these mutations segregate into five different classes based on the in vivo localization of the mutated dynein motors. Furthermore, we have determined that the different classes of dynein mutations alter vesicle trafficking, microtubule organization, and nuclear distribution in distinct ways and require dynactin to different extents. In addition, biochemical analyses of dynein from one mutant strain show a strong correlation between its in vitro biochemical properties and the aberrant intracellular function of that altered dynein. When the mutations were mapped to the published dynein crystal structure, we found that the three-dimensional structural locations of the heavy chain mutations were linked to particular classes of altered dynein functions observed in cells. Together, our data indicate that the five classes of dynein mutations represent the entrapment of dynein at five separate points in the dynein mechanochemical and transport cycles. We have developed N. crassa as a model system where we can dissect the complexities of dynein structure, function, and interaction with other proteins with genetic, biochemical, and cell biological studies. PMID:22649085

On two integrable cellular automata

Energy Technology Data Exchange (ETDEWEB)

Bobenko, A [Technische Univ. Berlin (Germany). Fachbereich Mathematik; Bordemann, M [Freiburg Univ. (Germany). Fachbereich Physik; Gunn, C [Technische Univ. Berlin (Germany). Fachbereich Mathematik; Pinkall, U [Technische Univ. Berlin (Germany). Fachbereich Mathematik

1993-11-01

We describe two simple cellular automata (CA) models which exhibit the essential attributes of soliton systems. The first one is an invertible, 2-state, 1-dimensional CA or, in other words, a nonlinear Z[sub 2]-valued dynamical system with discrete space and time. Against a vacuum state of 0, the system exhibits light cone particles in both spatial directions, which interact in a soliton-like fashion. A complete solution of this system is obtained. We also consider another CA, which is described by the Hirota equation over a finite field, and present a Lax representation for it. (orig.)

Network models provide insights into how oriens–lacunosum-moleculare and bistratified cell interactions influence the power of local hippocampal CA1 theta oscillations

Directory of Open Access Journals (Sweden)

Katie A Ferguson

2015-08-01

Full Text Available Hippocampal theta is a 4-12 Hz rhythm associated with episodic memory, and although it has been studied extensively, the cellular mechanisms underlying its generation are unclear. The complex interactions between different interneuron types, such as those between oriens--lacunosum-moleculare (OLM interneurons and bistratified cells (BiCs, make their contribution to network rhythms difficult to determine experimentally. We created network models that are tied to experimental work at both cellular and network levels to explore how these interneuron interactions affect the power of local oscillations. Our cellular models were constrained with properties from patch clamp recordings in the CA1 region of an intact hippocampus preparation in vitro. Our network models are composed of three different types of interneurons: parvalbumin-positive (PV+ basket and axo-axonic cells (BC/AACs, PV+ BiCs, and somatostatin-positive OLM cells. Also included is a spatially extended pyramidal cell model to allow for a simplified local field potential representation, as well as experimentally-constrained, theta frequency synaptic inputs to the interneurons. The network size, connectivity, and synaptic properties were constrained with experimental data. To determine how the interactions between OLM cells and BiCs could affect local theta power, we explored a number of OLM-BiC connections and connection strengths.We found that our models operate in regimes in which OLM cells minimally or strongly affected the power of network theta oscillations due to balances that, respectively, allow compensatory effects or not. Inactivation of OLM cells could result in no change or even an increase in theta power. We predict that the dis-inhibitory effect of OLM cells to BiCs to pyramidal cell interactions plays a critical role in the power of network theta oscillations. Our network models reveal a dynamic interplay between different classes of interneurons in influencing local theta

Cellular and molecular modifier pathways in tauopathies: the big picture from screening invertebrate models.

Science.gov (United States)

Hannan, Shabab B; Dräger, Nina M; Rasse, Tobias M; Voigt, Aaron; Jahn, Thomas R

2016-04-01

Abnormal tau accumulations were observed and documented in post-mortem brains of patients affected by Alzheimer's disease (AD) long before the identification of mutations in the Microtubule-associated protein tau (MAPT) gene, encoding the tau protein, in a different neurodegenerative disease called Frontotemporal dementia and Parkinsonism linked to chromosome 17 (FTDP-17). The discovery of mutations in the MAPT gene associated with FTDP-17 highlighted that dysfunctions in tau alone are sufficient to cause neurodegeneration. Invertebrate models have been diligently utilized in investigating tauopathies, contributing to the understanding of cellular and molecular pathways involved in disease etiology. An important discovery came with the demonstration that over-expression of human tau in Drosophila leads to premature mortality and neuronal dysfunction including neurodegeneration, recapitulating some key neuropathological features of the human disease. The simplicity of handling invertebrate models combined with the availability of a diverse range of experimental resources make these models, in particular Drosophila a powerful invertebrate screening tool. Consequently, several large-scale screens have been performed using Drosophila, to identify modifiers of tau toxicity. The screens have revealed not only common cellular and molecular pathways, but in some instances the same modifier has been independently identified in two or more screens suggesting a possible role for these modifiers in regulating tau toxicity. The purpose of this review is to discuss the genetic modifier screens on tauopathies performed in Drosophila and C. elegans models, and to highlight the common cellular and molecular pathways that have emerged from these studies. Here, we summarize results of tau toxicity screens providing mechanistic insights into pathological alterations in tauopathies. Key pathways or modifiers that have been identified are associated with a broad range of processes

How students learn to coordinate knowledge of physical and mathematical models in cellular physiology

Science.gov (United States)

Lira, Matthew

This dissertation explores the Knowledge in Pieces (KiP) theory to account for how students learn to coordinate knowledge of mathematical and physical models in biology education. The KiP approach characterizes student knowledge as a fragmented collection of knowledge elements as opposed to stable and theory-like knowledge. This dissertation sought to use this theoretical lens to account for how students understand and learn with mathematical models and representations, such as equations. Cellular physiology provides a quantified discipline that leverages concepts from mathematics, physics, and chemistry to understand cellular functioning. Therefore, this discipline provides an exemplary context for assessing how biology students think and learn with mathematical models. In particular, the resting membrane potential provides an exemplary concept well defined by models of dynamic equilibrium borrowed from physics and chemistry. In brief, membrane potentials, or voltages, "rest" when the electrical and chemical driving forces for permeable ionic species are equal in magnitude but opposite in direction. To assess students' understandings of this concept, this dissertation employed three studies: the first study employed the cognitive clinical interview to assess student thinking in the absence and presence of equations. The second study employed an intervention to assess student learning and the affordances of an innovative assessment. The third student employed a human-computer-interaction paradigm to assess how students learn with a novel multi-representational technology. Study 1 revealed that students saw only one influence--the chemical gradient--and that students coordinated knowledge of only this gradient with the related equations. Study 2 revealed that students benefited from learning with the multi-representational technology and that the assessment detected performance gains across both calculation and explanation tasks. Last, Study 3 revealed how students

Car Deceleration Considering Its Own Velocity in Cellular Automata Model

International Nuclear Information System (INIS)

Li Keping

2006-01-01

In this paper, we propose a new cellular automaton model, which is based on NaSch traffic model. In our method, when a car has a larger velocity, if the gap between the car and its leading car is not enough large, it will decrease. The aim is that the following car has a buffer space to decrease its velocity at the next time, and then avoid to decelerate too high. The simulation results show that using our model, the car deceleration is realistic, and is closer to the field measure than that of NaSch model.

Cellular Protein WDR11 Interacts with Specific Herpes Simplex Virus Proteins at the trans-Golgi Network To Promote Virus Replication

Science.gov (United States)

Taylor, Kathryne E.

2015-01-01

ABSTRACT It has recently been proposed that the herpes simplex virus (HSV) protein ICP0 has cytoplasmic roles in blocking antiviral signaling and in promoting viral replication in addition to its well-known proteasome-dependent functions in the nucleus. However, the mechanisms through which it produces these effects remain unclear. While investigating this further, we identified a novel cytoplasmic interaction between ICP0 and the poorly characterized cellular protein WDR11. During an HSV infection, WDR11 undergoes a dramatic change in localization at late times in the viral replication cycle, moving from defined perinuclear structures to a dispersed cytoplasmic distribution. While this relocation was not observed during infection with viruses other than HSV-1 and correlated with efficient HSV-1 replication, the redistribution was found to occur independently of ICP0 expression, instead requiring viral late gene expression. We demonstrate for the first time that WDR11 is localized to the trans-Golgi network (TGN), where it interacts specifically with some, but not all, HSV virion components, in addition to ICP0. Knockdown of WDR11 in cultured human cells resulted in a modest but consistent decrease in yields of both wild-type and ICP0-null viruses, in the supernatant and cell-associated fractions, without affecting viral gene expression. Although further study is required, we propose that WDR11 participates in viral assembly and/or secondary envelopment. IMPORTANCE While the TGN has been proposed to be the major site of HSV-1 secondary envelopment, this process is incompletely understood, and in particular, the role of cellular TGN components in this pathway is unknown. Additionally, little is known about the cellular functions of WDR11, although the disruption of this protein has been implicated in multiple human diseases. Therefore, our finding that WDR11 is a TGN-resident protein that interacts with specific viral proteins to enhance viral yields improves both

[A Cellular Automata Model for a Community Comprising Two Plant Species of Different Growth Forms].

Science.gov (United States)

Frolov, P V; Zubkova, E V; Komarov, A S

2015-01-01

A cellular automata computer model for the interactions between two plant species of different growth forms--the lime hairgrass Deschampsia caespitosa (L.) P. Beauv., a sod cereal, and the moneywort Lysimachia nummularia L., a ground creeping perennial herb--is considered. Computer experiments on the self-maintenance of the populations of each species against the background of a gradual increase in the share of randomly eliminated individuals, coexistence of the populations of two species, and the effect of the phytogenous field have been conducted. As has been shown, all the studied factors determine the number of individuals and self-sustainability of the simulated populations by the degree of their impact. The limits of action have been determined for individual factors; within these limits, the specific features in plant reproduction and dispersal provide sustainable coexistence of the simulated populations. It has been demonstrated that the constructed model allows for studying the long-term developmental dynamics of the plants belonging to the selected growth forms.

A Markov Process Inspired Cellular Automata Model of Road Traffic

OpenAIRE

Wang, Fa; Li, Li; Hu, Jianming; Ji, Yan; Yao, Danya; Zhang, Yi; Jin, Xuexiang; Su, Yuelong; Wei, Zheng

2008-01-01

To provide a more accurate description of the driving behaviors in vehicle queues, a namely Markov-Gap cellular automata model is proposed in this paper. It views the variation of the gap between two consequent vehicles as a Markov process whose stationary distribution corresponds to the observed distribution of practical gaps. The multiformity of this Markov process provides the model enough flexibility to describe various driving behaviors. Two examples are given to show how to specialize i...

Propagation Path Loss Models for 5G Urban Micro- and Macro-Cellular Scenarios

DEFF Research Database (Denmark)

Sun, Shu; Rappaport, Theodore S.; Rangan, Sundeep

2016-01-01

This paper presents and compares two candidate large-scale propagation path loss models, the alpha-beta-gamma (ABG) model and the close-in (CI) free space reference distance model, for the design of fifth generation (5G) wireless communication systems in urban micro- and macro-cellular scenarios....

Safety impacts of red light cameras at signalized intersections based on cellular automata models.

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Chai, C; Wong, Y D; Lum, K M

2015-01-01

This study applies a simulation technique to evaluate the hypothesis that red light cameras (RLCs) exert important effects on accident risks. Conflict occurrences are generated by simulation and compared at intersections with and without RLCs to assess the impact of RLCs on several conflict types under various traffic conditions. Conflict occurrences are generated through simulating vehicular interactions based on an improved cellular automata (CA) model. The CA model is calibrated and validated against field observations at approaches with and without RLCs. Simulation experiments are conducted for RLC and non-RLC intersections with different geometric layouts and traffic demands to generate conflict occurrences that are analyzed to evaluate the hypothesis that RLCs exert important effects on road safety. The comparison of simulated conflict occurrences show favorable safety impacts of RLCs on crossing conflicts and unfavorable impacts for rear-end conflicts during red/amber phases. Corroborative results are found from broad analysis of accident occurrence. RLCs are found to have a mixed effect on accident risk at signalized intersections: crossing collisions are reduced, whereas rear-end collisions may increase. The specially developed CA model is found to be a feasible safety assessment tool.

The Study Of Properties Of The Word Of Mouth Marketing Using Cellular Automata

Directory of Open Access Journals (Sweden)

Kowalska-Styczeń Agnieszka

2014-02-01

Full Text Available This article presents the possibility of using cellular automata, to study the properties of word of mouth (w-o-m marketing. Cellular automata allow to analyze the dynamics of changes in views and attitudes in social groups based on local interactions between people in small groups of friends, family members etc. The proposed paper shows the possibility of modelling the dynamics of word of mouth mechanism, if the basic assumptions of this process are: different size groups where this phenomenon occurs, and varied access to information. On the competing firms market, the dependence of the w-o-m mechanism dynamics on the model parameters is shown

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

Science.gov (United States)

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.

a Predator-Prey Model Based on the Fully Parallel Cellular Automata

Science.gov (United States)

He, Mingfeng; Ruan, Hongbo; Yu, Changliang

We presented a predator-prey lattice model containing moveable wolves and sheep, which are characterized by Penna double bit strings. Sexual reproduction and child-care strategies are considered. To implement this model in an efficient way, we build a fully parallel Cellular Automata based on a new definition of the neighborhood. We show the roles played by the initial densities of the populations, the mutation rate and the linear size of the lattice in the evolution of this model.

Low-energy-electron interactions with DNA: approaching cellular conditions with atmospheric experiments

International Nuclear Information System (INIS)

Alizadeh, E.; Sanche, L.

2014-01-01

A novel technique has been developed to investigate low energy electron (LEE)-DNA interactions in the presence of small biomolecules (e.g., N 2 , O 2 , H 2 O) found near DNA in the cell nucleus, in order to simulate cellular conditions. In this technique, LEEs are emitted from a metallic surface exposed by soft X-rays and interact with DNA thin films at standard ambient temperature and pressure (SATP). Whereas atmospheric N 2 had little effect on the yields of LEE-induced single and double strand breaks, both O 2 and H 2 O considerably modified and increased such damage. The highest yields were obtained when DNA is embedded in a combined O 2 and H 2 O atmosphere. In this case, the amount of additional double strand breaks was supper-additive. The effect of modifying the chemical and physical stability of DNA by platinum-based chemotherapeutic agents (Pt-drugs) including cisplatin, carboplatin and oxaliplatin was also investigated with this technique. The results obtained provide information on the role played by subexcitation-energy electrons and dissociative electron attachment in the radiosensitization of DNA by Pt-drugs, which is an important step to unravel the mechanisms of radiosensitization of these agents in chemo-radiation cancer therapy. (authors)

Low-energy-electron interactions with DNA: approaching cellular conditions with atmospheric experiments

Science.gov (United States)

Alizadeh, Elahe; Sanche, Léon

2014-04-01

A novel technique has been developed to investigate low energy electron (LEE)-DNA interactions in the presence of small biomolecules (e.g., N2, O2, H2O) found near DNA in the cell nucleus, in order to simulate cellular conditions. In this technique, LEEs are emitted from a metallic surface exposed by soft X-rays and interact with DNA thin films at standard ambient temperature and pressure (SATP). Whereas atmospheric N2 had little effect on the yields of LEE-induced single and double strand breaks, both O2 and H2O considerably modified and increased such damage. The highest yields were obtained when DNA is embedded in a combined O2 and H2O atmosphere. In this case, the amount of additional double strand breaks was supper-additive. The effect of modifying the chemical and physical stability of DNA by platinum-based chemotherapeutic agents (Pt-drugs) including cisplatin, carboplatin and oxaliplatin was also investigated with this technique. The results obtained provide information on the role played by subexcitation-energy electrons and dissociative electron attachment in the radiosensitization of DNA by Pt-drugs, which is an important step to unravel the mechanisms of radiosensitisation of these agents in chemoradiation cancer therapy.

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

Science.gov (United States)

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.

Programmable cellular arrays. Faults testing and correcting in cellular arrays

International Nuclear Information System (INIS)

Cercel, L.

1978-03-01

A review of some recent researches about programmable cellular arrays in computing and digital processing of information systems is presented, and includes both combinational and sequential arrays, with full arbitrary behaviour, or which can realize better implementations of specialized blocks as: arithmetic units, counters, comparators, control systems, memory blocks, etc. Also, the paper presents applications of cellular arrays in microprogramming, in implementing of a specialized computer for matrix operations, in modeling of universal computing systems. The last section deals with problems of fault testing and correcting in cellular arrays. (author)

Probabilistic cellular automata: Some statistical mechanical considerations

International Nuclear Information System (INIS)

Lebowitz, J.L.; Maes, C.; Speer, E.R.

1990-01-01

Spin systems evolving in continuous or discrete time under the action of stochastic dynamics are used to model phenomena as diverse as the structure of alloys and the functioning of neural networks. While in some cases the dynamics are secondary, designed to produce a specific stationary measure whose properties one is interested in studying, there are other cases in which the only available information is the dynamical rule. Prime examples of the former are computer simulations, via Glauber dynamics, of equilibrium Gibbs measures with a specified interaction potential. Examples of the latter include various types of majority rule dynamics used as models for pattern recognition and for error-tolerant computations. The present note discusses ways in which techniques found useful in equilibrium statistical mechanics can be applied to a particular class of models of the latter types. These are cellular automata with noise: systems in which the spins are updated stochastically at integer times, simultaneously at all sites of some regular lattice. These models were first investigated in detail in the Soviet literature of the late sixties and early seventies. They are now generally referred to as Stochastic or Probabilistic Cellular Automata (PCA), and may be considered to include deterministic automata (CA) as special limits. 16 refs., 3 figs

A spatiotemporal model for the LTE uplink: Spatially interacting tandem queues approach

KAUST Repository

Gharbieh, Mohammad

2017-07-31

With the proliferation of the Internet-of-things (IoT), there is an undeniable consensus that cellular LTE networks will have to support a dramatically larger number of uplink connections. This is true since most of the devices to be added incur machine-type communications which is dominantly upstream. Can current LTE network withstand this challenge? To answer this question, the joint performance of random access process and the uplink data transmission should be investigated. These two problems have been classically treated in the literature in a disjoint fashion. In this paper, they are jointly analyzed as an inseparable couple. To do that, a tandem queuing model is adopted whereby devices are represented as spatially interacting queues. The interaction between queues is governed by the mutual inter-cell and intra-cell interference. To that end, a joint stochastic geometry and queueing theory model is exploited to study this problem and a spatiotemporal analytical model is developed accordingly. Network stability and scalability are two prime performance criteria for performance assessment. In light of these two criteria, the developed model is poised to offer valuable insights into efficient access and resource allocation strategies.

DP 71 AND BETA DYSTROGLYCAN INTERACTION: A MOLECULAR MODELING APPROACH TO UNDERSTAND DUCHENNE MUSCULAR DYSTROPHY

Directory of Open Access Journals (Sweden)

Simanti Bhattacharya,

2013-12-01

Full Text Available Dp 71 is the most prevalent and widely expressed non muscle isoform of dystrophin (Dp and its mutations are associated with Duchenne muscular dystrophy, a severe form of muscular disorder. Dp 71 deviates from the canonical Dp by means of its truncated N terminal which also has abolished certain amino acids that comprise WW domain in the canonical form. This WW domain is very crucial for Dp’s interaction with partner proteins to establish a bridge between extra cellular matrices and cellular cytoskeleton. In our current study we have employed molecular modeling technique to understand the structural architecture of the N terminal region of Dp 71 and its deviation from the canonical form. We have further extended our studies to analyze the interaction probabilities between Dp 71 and β-DG applying molecular docking. Our studies for the first time have revealed that in spite of the underlying differences in terms of amino acids and structural organization, Dp 71 can interact with β-DG with its N terminal region which shares the similar molecular surface with the canonical form of Dp. These findings have opened up a platform to investigate the molecular interactions, spatio temporal orientations of the amino acids of Dp 71 and β-DG to understand the onset of DMD in much more greater detail

Cellular Automata Models Applied to the Study of Landslide Dynamics

Science.gov (United States)

Liucci, Luisa; Melelli, Laura; Suteanu, Cristian

2015-04-01

Landslides are caused by complex processes controlled by the interaction of numerous factors. Increasing efforts are being made to understand the spatial and temporal evolution of this phenomenon, and the use of remote sensing data is making significant contributions in improving forecast. This paper studies landslides seen as complex dynamic systems, in order to investigate their potential Self Organized Critical (SOC) behavior, and in particular, scale-invariant aspects of processes governing the spatial development of landslides and their temporal evolution, as well as the mechanisms involved in driving the system and keeping it in a critical state. For this purpose, we build Cellular Automata Models, which have been shown to be capable of reproducing the complexity of real world features using a small number of variables and simple rules, thus allowing for the reduction of the number of input parameters commonly used in the study of processes governing landslide evolution, such as those linked to the geomechanical properties of soils. This type of models has already been successfully applied in studying the dynamics of other natural hazards, such as earthquakes and forest fires. The basic structure of the model is composed of three modules: (i) An initialization module, which defines the topographic surface at time zero as a grid of square cells, each described by an altitude value; the surface is acquired from real Digital Elevation Models (DEMs). (ii) A transition function, which defines the rules used by the model to update the state of the system at each iteration. The rules use a stability criterion based on the slope angle and introduce a variable describing the weakening of the material over time, caused for example by rainfall. The weakening brings some sites of the system out of equilibrium thus causing the triggering of landslides, which propagate within the system through local interactions between neighboring cells. By using different rates of

Efficient Analysis of Systems Biology Markup Language Models of Cellular Populations Using Arrays.

Science.gov (United States)

Watanabe, Leandro; Myers, Chris J

2016-08-19

The Systems Biology Markup Language (SBML) has been widely used for modeling biological systems. Although SBML has been successful in representing a wide variety of biochemical models, the core standard lacks the structure for representing large complex regular systems in a standard way, such as whole-cell and cellular population models. These models require a large number of variables to represent certain aspects of these types of models, such as the chromosome in the whole-cell model and the many identical cell models in a cellular population. While SBML core is not designed to handle these types of models efficiently, the proposed SBML arrays package can represent such regular structures more easily. However, in order to take full advantage of the package, analysis needs to be aware of the arrays structure. When expanding the array constructs within a model, some of the advantages of using arrays are lost. This paper describes a more efficient way to simulate arrayed models. To illustrate the proposed method, this paper uses a population of repressilator and genetic toggle switch circuits as examples. Results show that there are memory benefits using this approach with a modest cost in runtime.

Calibrating cellular automaton models for pedestrians walking through corners

Science.gov (United States)

Dias, Charitha; Lovreglio, Ruggiero

2018-05-01

Cellular Automata (CA) based pedestrian simulation models have gained remarkable popularity as they are simpler and easier to implement compared to other microscopic modeling approaches. However, incorporating traditional floor field representations in CA models to simulate pedestrian corner navigation behavior could result in unrealistic behaviors. Even though several previous studies have attempted to enhance CA models to realistically simulate pedestrian maneuvers around bends, such modifications have not been calibrated or validated against empirical data. In this study, two static floor field (SFF) representations, namely 'discrete representation' and 'continuous representation', are calibrated for CA-models to represent pedestrians' walking behavior around 90° bends. Trajectory data collected through a controlled experiment are used to calibrate these model representations. Calibration results indicate that although both floor field representations can represent pedestrians' corner navigation behavior, the 'continuous' representation fits the data better. Output of this study could be beneficial for enhancing the reliability of existing CA-based models by representing pedestrians' corner navigation behaviors more realistically.

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

Science.gov (United States)

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.

A Model of How Different Biology Experts Explain Molecular and Cellular Mechanisms

Science.gov (United States)

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 explanations made by experts from different biology subdisciplines at a university support the validity of this model? Guided by the modeling framework of R. S. Justi and J. K. Gilbert, the validity of an initial model was tested by asking seven biologists to explain a molecular mechanism of their choice. Data were collected from interviews, artifacts, and drawings, and then subjected to thematic analysis. We found that biologists explained the specific activities and organization of entities of the mechanism. In addition, they contextualized explanations according to their biological and social significance; integrated explanations with methods, instruments, and measurements; and used analogies and narrated stories. The derived methods, analogies, context, and how themes informed the development of our final MACH model of mechanistic explanations. Future research will test the potential of the MACH model as a guiding framework for instruction to enhance the quality of student explanations. PMID:25999313

Special Issue: Redox Active Natural Products and Their Interaction with Cellular Signalling Pathways

Directory of Open Access Journals (Sweden)

Claus Jacob

2014-11-01

Full Text Available During the last decade, research into natural products has experienced a certain renaissance. The urgent need for more and more effective antibiotics in medicine, the demand for ecologically friendly plant protectants in agriculture, “natural” cosmetics and the issue of a sustainable and healthy nutrition in an ageing society have fuelled research into Nature’s treasure chest of “green gold”. Here, redox active secondary metabolites from plants, fungi, bacteria and other (micro-organisms often have been at the forefront of the most interesting developments. These agents provide powerful means to interfere with many, probably most cellular signaling pathways in humans, animals and lower organisms, and therefore can be used to protect, i.e., in form of antioxidants, and to frighten off or even kill, i.e., in form of repellants, antibiotics, fungicides and selective, often catalytic “sensor/effector” anticancer agents. Interestingly, whilst natural product research dates back many decades, in some cases even centuries, and compounds such as allicin and various flavonoids have been investigated thoroughly in the past, it has only recently become possible to investigate their precise interactions and mode(s of action inside living cells. Here, fluorescent staining and labelling on the one side, and appropriate detection, either qualitatively under the microscope or quantitatively in flow cytometers and plate readers, on the other, enable researchers to obtain the various pieces of information necessary to construct a fairly complete puzzle of how such compounds act and interact in living cells. Complemented by the more traditional activity assays and Western Blots, and increasingly joined by techniques such as proteomics, chemogenetic screening and mRNA profiling, these cell based bioanalytical techniques form a powerful platform for “intracellular diagnostics”. In the case of redox active compounds, especially of Reactive Sulfur

A Geometrical-Based Model for Cochannel Interference Analysis and Capacity Estimation of CDMA Cellular Systems

Directory of Open Access Journals (Sweden)

Konstantinos B. Baltzis

2008-10-01

Full Text Available A common assumption in cellular communications is the circular-cell approximation. In this paper, an alternative analysis based on the hexagonal shape of the cells is presented. A geometrical-based stochastic model is proposed to describe the angle of arrival of the interfering signals in the reverse link of a cellular system. Explicit closed form expressions are derived, and simulations performed exhibit the characteristics and validate the accuracy of the proposed model. Applications in the capacity estimation of WCDMA cellular networks are presented. Dependence of system capacity of the sectorization of the cells and the base station antenna radiation pattern is explored. Comparisons with data in literature validate the accuracy of the proposed model. The degree of error of the hexagonal and the circular-cell approaches has been investigated indicating the validity of the proposed model. Results have also shown that, in many cases, the two approaches give similar results when the radius of the circle equals to the hexagon inradius. A brief discussion on how the proposed technique may be applied to broadband access networks is finally made.

A Local Land Use Competition Cellular Automata Model and Its Application

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Jun Yang

2016-06-01

Full Text Available Cellular automaton (CA is an important method in land use and cover change studies, however, the majority of research focuses on the discovery of macroscopic factors affecting LUCC, which results in ignoring the local effects within the neighborhoods. This paper introduces a Local Land Use Competition Cellular Automata (LLUC-CA model, based on local land use competition, land suitability evaluation, demand analysis of the different land use types, and multi-target land use competition allocation algorithm to simulate land use change at a micro level. The model is applied to simulate land use changes at Jinshitan National Tourist Holiday Resort from 1988 to 2012. The results show that the simulation accuracies were 64.46%, 77.21%, 85.30% and 99.14% for the agricultural land, construction land, forestland and water, respectively. In addition, comparing the simulation results of the LLUC-CA and CA-Markov model with the real land use data, their overall spatial accuracies were found to be 88.74% and 86.82%, respectively. In conclusion, the results from this study indicated that the model was an acceptable method for the simulation of large-scale land use changes, and the approach used here is applicable to analyzing the land use change driven forces and assist in decision-making.

An attempt of modelling debris flows characterised by strong inertial effects through Cellular Automata

Science.gov (United States)

Iovine, G.; D'Ambrosio, D.

2003-04-01

Cellular Automata models do represent a valid method for the simulation of complex phenomena, when these latter can be described in "a-centric" terms - i.e. through local interactions within a discrete time-space. In particular, flow-type landslides (such as debris flows) can be viewed as a-centric dynamical system. SCIDDICA S4b, the last release of a family of two-dimensional hexagonal Cellular Automata models, has recently been developed for simulating debris flows characterised by strong inertial effects. It has been derived by progressively enriching an initial simplified CA model, originally derived for simulating very simple cases of slow-moving flow-type landslides. In S4b, by applying an empirical strategy, the inertial characters of the flowing mass have been translated into CA terms. In the transition function of the model, the distribution of landslide debris among the cells is computed by considering the momentum of the debris which move among the cells of the neighbourhood, and privileging the flow direction. By properly setting the value of one of the global parameters of the model (the "inertial factor"), the mechanism of distribution of the landslide debris among the cells can be influenced in order to emphasise the inertial effects, according to the energy of the flowing mass. Moreover, the high complexity of both the model and of the phenomena to be simulated (e.g. debris flows characterised by severe erosion along their path, and by strong inertial effects) suggested to employ an automated technique of evaluation, for the determination of the best set of global parameters. Accordingly, the calibration of the model has been performed through Genetic Algorithms, by considering several real cases of study: these latter have been selected among the population of landslides triggered in Campania (Southern Italy) in May 1998 and December 1999. Obtained results are satisfying: errors computed by comparing the simulations with the map of the real

An Asynchronous Cellular Automata-Based Adaptive Illumination Facility

Science.gov (United States)

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.

Exploiting conformational ensembles in modeling protein-protein interactions on the proteome scale

Science.gov (United States)

Kuzu, Guray; Gursoy, Attila; Nussinov, Ruth; Keskin, Ozlem

2013-01-01

Cellular functions are performed through protein-protein interactions; therefore, identification of these interactions is crucial for understanding biological processes. Recent studies suggest that knowledge-based approaches are more useful than ‘blind’ docking for modeling at large scales. However, a caveat of knowledge-based approaches is that they treat molecules as rigid structures. The Protein Data Bank (PDB) offers a wealth of conformations. Here, we exploited ensemble of the conformations in predictions by a knowledge-based method, PRISM. We tested ‘difficult’ cases in a docking-benchmark dataset, where the unbound and bound protein forms are structurally different. Considering alternative conformations for each protein, the percentage of successfully predicted interactions increased from ~26% to 66%, and 57% of the interactions were successfully predicted in an ‘unbiased’ scenario, in which data related to the bound forms were not utilized. If the appropriate conformation, or relevant template interface, is unavailable in the PDB, PRISM could not predict the interaction successfully. The pace of the growth of the PDB promises a rapid increase of ensemble conformations emphasizing the merit of such knowledge-based ensemble strategies for higher success rates in protein-protein interaction predictions on an interactome-scale. We constructed the structural network of ERK interacting proteins as a case study. PMID:23590674

Cellular-automata model of the dwarf shrubs populations and communities dynamics

Directory of Open Access Journals (Sweden)

A. S. Komarov

2015-06-01

Full Text Available The probabilistic cellular-automata model of development and long-time dynamics of dwarf shrub populations and communities is developed. It is based on the concept of discrete description of the plant ontogenesis and joint model approaches in terms of probabilistic cellular automata and L-systems by Lindenmayer. Short representation of the basic model allows evaluation of the approach and software implementation. The main variables of the model are a number of partial bushes in clones or area projective cover. The model allows us to investigate the conditions of self-maintenance and sustainability population under different environmental conditions (inaccessibility of the territory for settlement, mosaic moisture conditions of soil and wealth. The model provides a forecast of the total biomass dynamics shrubs and their fractions (stems, leaves, roots, fine roots, fruits on the basis of the data obtained in the discrete description of ontogenesis and further information on the productivity of the plant fractions. The inclusion of the joint dynamics of biomass of shrubs and soil in EFIMOD models cycle of carbon and nitrogen to evaluate the role of shrubs in these circulations, especially at high impact, such as forest fires and clear cutting, allow forecasting of the dynamics of populations and ecosystem functions of shrubs (regulation of biogeochemical cycles maintaining biodiversity, participation in the creation of non-wood products with changing climatic conditions and strong damaging effects (logging, fires; and application of the models developed to investigate the stability and productivity of shrubs and their participation in the cycle of carbon and nitrogen in different climatic and edaphic conditions.

Modelling land-use effects of future urbanization using cellular automata

DEFF Research Database (Denmark)

Fuglsang, Morten; Münier, B.; Hansen, H.S.

2013-01-01

project PASHMINA (Paradigm Shift modelling and innovative approaches), three storylines of future transportation paradigm shifts towards 2040 are created. These storylines are translated into spatial planning strategies and modelled using the cellular automata model LUCIA. For the modelling, an Eastern......The modelling of land use change is a way to analyse future scenarios by modelling different pathways. Application of spatial data of different scales coupled with socio-economic data makes it possible to explore and test the understanding of land use change relations. In the EU-FP7 research...... Danish case area was selected, comprising of the Copenhagen metropolitan area and its hinterland. The different scenarios are described using a range of different descriptive GIS datasets. These include mapping of accessibility based on public and private transportation, urban density and structure...

Effect of Water Flows on Ship Traffic in Narrow Water Channels Based on Cellular Automata

Directory of Open Access Journals (Sweden)

Hu Hongtao

2017-11-01

Full Text Available In narrow water channels, ship traffic may be affected by water flows and ship interactions. Studying their effects can help maritime authorities to establish appropriate management strategies. In this study, a two-lane cellular automation model is proposed. Further, the behavior of ship traffic is analyzed by setting different water flow velocities and considering ship interactions. Numerical experiment results show that the ship traffic density-flux relation is significantly different from the results obtained by classical models. Furthermore, due to ship interactions, the ship lane-change rate is influenced by the water flow to a certain degree.

Cellular automata analysis and applications

CERN Document Server

Hadeler, Karl-Peter

2017-01-01

This book focuses on a coherent representation of the main approaches to analyze the dynamics of cellular automata. Cellular automata are an inevitable tool in mathematical modeling. In contrast to classical modeling approaches as partial differential equations, cellular automata are straightforward to simulate but hard to analyze. In this book we present a review of approaches and theories that allow the reader to understand the behavior of cellular automata beyond simulations. The first part consists of an introduction of cellular automata on Cayley graphs, and their characterization via the fundamental Cutis-Hedlund-Lyndon theorems in the context of different topological concepts (Cantor, Besicovitch and Weyl topology). The second part focuses on classification results: What classification follows from topological concepts (Hurley classification), Lyapunov stability (Gilman classification), and the theory of formal languages and grammars (Kůrka classification). These classifications suggest to cluster cel...

Mapping of immunogenic and protein-interacting regions at the surface of the seven-bladed β-propeller domain of the HIV-1 cellular interactor EED

Directory of Open Access Journals (Sweden)

Gouet Patrice

2008-02-01

Full Text Available Abstract Background The human EED protein, a member of the superfamily of Polycomb group proteins, is involved in multiple cellular protein complexes. Its C-terminal domain, which is common to the four EED isoforms, contains seven repeats of a canonical WD-40 motif. EED is an interactor of three HIV-1 proteins, matrix (MA, integrase (IN and Nef. An antiviral activity has been found to be associated with isoforms EED3 and EED4 at the late stage of HIV-1 replication, due to a negative effect on virus assembly and genomic RNA packaging. The aim of the present study was to determine the regions of the EED C-terminal core domain which were accessible and available to protein interactions, using three-dimensional (3D protein homology modelling with a WD-40 protein of known structure, and epitope mapping of anti-EED antibodies. Results Our data suggested that the C-terminal domain of EED was folded as a seven-bladed β-propeller protein. During the completion of our work, crystallographic data of EED became available from co-crystals of the EED C-terminal core with the N-terminal domain of its cellular partner EZH2. Our 3D-model was in good congruence with the refined structural model determined from crystallographic data, except for a unique α-helix in the fourth β-blade. More importantly, the position of flexible loops and accessible β-strands on the β-propeller was consistent with our mapping of immunogenic epitopes and sites of interaction with HIV-1 MA and IN. Certain immunoreactive regions were found to overlap with the EZH2, MA and IN binding sites, confirming their accessibility and reactivity at the surface of EED. Crystal structure of EED showed that the two discrete regions of interaction with MA and IN did not overlap with each other, nor with the EZH2 binding pocket, but were contiguous, and formed a continuous binding groove running along the lateral face of the β-propeller. Conclusion Identification of antibody-, MA-, IN- and EZH2

Modeling and boundary force control of microcantilevers utilized in atomic force microscopy for cellular imaging and characterization

Science.gov (United States)

Eslami, Sohrab

This dissertation undertakes the theoretical and experimental developments microcantilevers utilized in Atomic Force Microscopy (AFM) with applications to cellular imaging and characterization. The capability of revealing the inhomogeneties or interior of ultra-small materials has been of most interest to many researchers. However, the fundamental concept of signal and image formation remains unexplored and not fully understood. For his, a semi-empirical nonlinear force model is proposed to show that virtual frequency generation, regarded as the simplest synthesized subsurface probe, occurs optimally when the force is tuned to the van der Waals form. This is the first-time observation of a novel theoretical dynamic multi-frequency force microscopy that has not been already reported. Owing to the broad applications of microcantilevers in the nanoscale imaging and microscopic techniques, there is an essential feeling to study and propose a comprehensive model of such systems. Therefore, in the theoretical part of this dissertation, a distributed-parameters representation modeling of the microcantilever along with a general interaction force comprising of two attractive and repulsive components with general amplitude and power terms is studied. This model is investigated in a general 2D Cartesian coordinate to consider the motions of the probe with a tip mass. There is an excitation at the microcantilever's base such that the end of the beam is subject to the proposed general force. These forces are very sensitive to the amplitude and power terms of these parts; on the other hand, atomic intermolecular force is a function of the distance such that this distance itself is also a function of the interaction force that will result in a nonlinear implicit equation. From a parametric study in the probe-sample excitation, it is shown that the predicted behavior of the generated difference-frequency oscillation amplitude agrees well with experimental measurements. Following

Boundary Induced Phase Transition in Cellular Automata Models of Pedestrian Flow

Czech Academy of Sciences Publication Activity Database

Bukáček, M.; Hrabák, Pavel

2016-01-01

Roč. 11, č. 4 (2016), s. 327-338 ISSN 1557-5969 R&D Projects: GA ČR GA13-13502S Institutional support: RVO:67985556 Keywords : Adaptive time-span * Cellular automata model * Floor-field * Pedestrian flow * Phase transition * Principle of bonds Subject RIV: BD - Theory of Information Impact factor: 0.696, year: 2016

Cellular Targets of Dietary Polyphenol Resveratrol

National Research Council Canada - National Science Library

Wu, Joseph M

2006-01-01

To test the hypothesis that resveratrol, a grape derived polyphenol, exerts its chemopreventive properties against prostate cancer by interacting with specific cellular targets, denoted resveratrol targeting proteins (RTPs...

Force control for mechanoinduction of impedance variation in cellular organisms

International Nuclear Information System (INIS)

Nam, Joo Hoo; Chen, Peter C Y; Lu, Zhe; Luo, Hong; Lin, Wei; Ge, Ruowen

2010-01-01

Constantly exposed to various forms of mechanical forces inherent in their physical environment (such as gravity, stress induced by fluid flow or cell–cell interactions, etc), cellular organisms sense such forces and convert them into biochemical signals through the processes of mechanosensing and mechanotransduction that eventually lead to biological changes. The effect of external forces on the internal structures and activities in a cellular organism may manifest in changes its physical properties, such as impedance. Studying variation in the impedance of a cellular organism induced by the application of an external mechanical force represents a meaningful endeavor (from a biosystems perspective) in exploring the complex mechanosensing and mechanotransduction mechanisms that govern the behavior of a cellular organism under the influence of external mechanical stimuli. In this paper we describe the development of an explicit force-feedback control system for exerting an indentation force on a cellular organism while simultaneously measuring its impedance. To demonstrate the effectiveness of this force-control system, we have conducted experiments using zebrafish embryos as a test model of a cellular organism. We report experimental results demonstrating that the application of a properly controlled external force leads to a significant change in the impedance of a zebrafish embryo. These results offer support for a plausible explanation that activities of pore canals in the chorion are responsible for the observed change in impedance.

Cellular automaton modelling of ductile iron microstructure in the thin wall casting

International Nuclear Information System (INIS)

Burbelko, A A; Gurgul, D; Kapturkiewicz, W; Górny, M

2012-01-01

The mathematical model of the globular eutectic solidification in 2D was designed. Proposed model is based on the Cellular Automaton Finite Differences (CA-FD) calculation method. Model has been used for studies of the primary austenite and of globular eutectic grains growth during the ductile iron solidification in the thin wall casting. Model takes into account, among other things, non-uniform temperature distribution in the casting wall cross-section, kinetics of the austenite and graphite grains nucleation, and non-equilibrium nature of the interphase boundary migration.

The relationship between office type and job satisfaction: Testing a multiple mediation model through ease of interaction and well-being.

Science.gov (United States)

Otterbring, Tobias; Pareigis, Jörg; Wästlund, Erik; Makrygiannis, Alexander; Lindström, Anton

2018-05-01

Objectives This cross-sectional study investigated the associations between office type (cellular, shared-room, small open-plan, and medium-sized open-plan) and employees' ease of interaction with coworkers, subjective well-being, and job satisfaction. Methods A brief survey including measures of office type, ease of interaction with coworkers, subjective well-being, and job satisfaction was sent electronically to 1500 Swedish real-estate agents, 271 of whom returned usable surveys. The data were analyzed using a regression-based serial multiple mediation model (PROCESS Model 6), which tested whether the relationship between office type and job satisfaction would be mediated by ease of interaction and, in turn, subjective well-being. Results A negative relationship was found between the number of coworkers sharing an office and employees' job satisfaction. This association was serially mediated by ease of interaction with coworkers and subjective well-being, with employees working in small and medium-sized open-plan offices reporting lower levels of both these aspects than employees who work in either cellular or shared-room offices. Conclusions Open-plan offices may have short-term financial benefits, but these benefits may be lower than the costs associated with decreased job satisfaction and well-being. Therefore, decision-makers should consider the impact of office type on employees rather than focusing solely on cost-effective office layout, flexibility, and productivity.

Train flow chaos analysis based on an improved cellular automata model

International Nuclear Information System (INIS)

Meng, Xuelei; Xiang, Wanli; Jia, Limin; Xu, Jie

2015-01-01

To control the chaos in the railway traffic flow and offer valuable information for the dispatchers of the railway system, an improved cellular model is presented to detect and analyze the chaos in the traffic flow. We first introduce the working mechanism of moving block system, analyzing the train flow movement characteristics. Then we improve the cellular model on the evolution rules to adjust the train flow movement. We give the train operation steps from three cases: the trains running on a railway section, a train will arrive in a station and a train will departure from a station. We simulate 4 trains to run on a high speed section fixed with moving block system and record the distances between the neighbor trains and draw the Poincare section to analyze the chaos in the train operation. It is concluded that there is not only chaos but order in the train operation system with moving blocking system and they can interconvert to each other. The findings have the potential value in train dispatching system construction and offer supporting information for the daily dispatching work.

The AAA+ ATPase p97, a cellular multitool.

Science.gov (United States)

Stach, Lasse; Freemont, Paul S

2017-08-17

The AAA+ (ATPases associated with diverse cellular activities) ATPase p97 is essential to a wide range of cellular functions, including endoplasmic reticulum-associated degradation, membrane fusion, NF-κB (nuclear factor kappa-light-chain-enhancer of activated B cells) activation and chromatin-associated processes, which are regulated by ubiquitination. p97 acts downstream from ubiquitin signaling events and utilizes the energy from ATP hydrolysis to extract its substrate proteins from cellular structures or multiprotein complexes. A multitude of p97 cofactors have evolved which are essential to p97 function. Ubiquitin-interacting domains and p97-binding domains combine to form bi-functional cofactors, whose complexes with p97 enable the enzyme to interact with a wide range of ubiquitinated substrates. A set of mutations in p97 have been shown to cause the multisystem proteinopathy inclusion body myopathy associated with Paget's disease of bone and frontotemporal dementia. In addition, p97 inhibition has been identified as a promising approach to provoke proteotoxic stress in tumors. In this review, we will describe the cellular processes governed by p97, how the cofactors interact with both p97 and its ubiquitinated substrates, p97 enzymology and the current status in developing p97 inhibitors for cancer therapy. © 2017 The Author(s).

Prisoner's Dilemma in One-Dimensional Cellular Automata: Visualization of Evolutionary Patterns

OpenAIRE

Pereira, Marcelo Alves; Martinez, Alexandre Souto; Espindola, Aquino Lauri

2007-01-01

The spatial Prisoner's Dilemma is a prototype model to show the emergence of cooperation in very competitive environments. It considers players, at site of lattices, that can either cooperate or defect when playing the Prisoner's Dilemma with other z players. This model presents a rich phase diagram. Here we consider players in cells of one-dimensional cellular automata. Each player interacts with other z players. This geometry allows us to vary, in a simple manner, the number of neighbors ra...

Treatment Analysis in a Cancer Stem Cell Context Using a Tumor Growth Model Based on Cellular Automata.

Science.gov (United States)

Monteagudo, Ángel; Santos, José

2015-01-01

Cancer can be viewed as an emergent behavior in terms of complex system theory and artificial life, Cellular Automata (CA) being the tool most used for studying and characterizing the emergent behavior. Different approaches with CA models were used to model cancer growth. The use of the abstract model of acquired cancer hallmarks permits the direct modeling at cellular level, where a cellular automaton defines the mitotic and apoptotic behavior of cells, and allows for an analysis of different dynamics of the cellular system depending on the presence of the different hallmarks. A CA model based on the presence of hallmarks in the cells, which includes a simulation of the behavior of Cancer Stem Cells (CSC) and their implications for the resultant growth behavior of the multicellular system, was employed. This modeling of cancer growth, in the avascular phase, was employed to analyze the effect of cancer treatments in a cancer stem cell context. The model clearly explains why, after treatment against non-stem cancer cells, the regrowth capability of CSCs generates a faster regrowth of tumor behavior, and also shows that a continuous low-intensity treatment does not favor CSC proliferation and differentiation, thereby allowing an unproblematic control of future tumor regrowth. The analysis performed indicates that, contrary to the current attempts at CSC control, trying to make CSC proliferation more difficult is an important point to consider, especially in the immediate period after a standard treatment for controlling non-stem cancer cell proliferation.

Application of a novel cellular automaton porosity prediction model to aluminium castings

International Nuclear Information System (INIS)

Atwood, R.C.; Chirazi, A.; Lee, P.D.

2002-01-01

A multiscale model was developed to predict the formation of porosity within a solidifying aluminium-silicon alloy. The diffusion of silicon and dissolved gas was simulated on a microscopic scale combined with cellular automaton models of gas porosity formation within the growing three-dimensional solidification microstructure. However, due to high computational cost, the modelled volume is limited to the millimetre range. This renders the application of direct modelling of complex shape castings unfeasible. Combining the microstructural modelling with a statistical response-surface prediction method allows application of the microstructural model results to industrial scale casts by incorporating them in commercial solidification software. (author)

Full-length cellular β-secretase has a trimeric subunit stoichiometry, and its sulfur-rich transmembrane interaction site modulates cytosolic copper compartmentalization.

Science.gov (United States)

Liebsch, Filip; Aurousseau, Mark R P; Bethge, Tobias; McGuire, Hugo; Scolari, Silvia; Herrmann, Andreas; Blunck, Rikard; Bowie, Derek; Multhaup, Gerd

2017-08-11

The β-secretase (BACE1) initiates processing of the amyloid precursor protein (APP) into Aβ peptides, which have been implicated as central players in the pathology of Alzheimer disease. BACE1 has been described as a copper-binding protein and its oligomeric state as being monomeric, dimeric, and/or multimeric, but the native cellular stoichiometry has remained elusive. Here, by using single-molecule fluorescence and in vitro cross-linking experiments with photo-activatable unnatural amino acids, we show that full-length BACE1, independently of its subcellular localization, exists as trimers in human cells. We found that trimerization requires the BACE1 transmembrane sequences (TMSs) and cytoplasmic domains, with residues Ala 463 and Cys 466 buried within the trimer interface of the sulfur-rich core of the TMSs. Our 3D model predicts that the sulfur-rich core of the trimeric BACE1 TMS is accessible to metal ions, but copper ions did not trigger trimerization. The results of functional assays of endogenous BACE1 suggest that it has a role in intracellular copper compartmentalization by transferring cytosolic copper to intracellular compartments, while leaving the overall cellular copper concentration unaltered. Adding to existing physiological models, our results provide novel insight into the atypical interactions between copper and BACE1 and into its non-enzymatic activities. In conclusion, therapeutic Alzheimer disease prevention strategies aimed at decreasing BACE1 protein levels should be regarded with caution, because adverse effects in copper homeostasis may occur. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Simulation of a plane wavefront propagating in cardiac tissue using a cellular automata model

International Nuclear Information System (INIS)

Barbosa, Carlos R Hall

2003-01-01

We present a detailed description of a cellular automata model for the propagation of action potential in a planar cardiac tissue, which is very fast and easy to use. The model incorporates anisotropy in the electrical conductivity and a spatial variation of the refractory time. The transmembrane potential distribution is directly derived from the cell states, and the intracellular and extracellular potential distributions are calculated for the particular case of a plane wavefront. Once the potential distributions are known, the associated current densities are calculated by Ohm's law, and the magnetic field is determined at a plane parallel to the cardiac tissue by applying the law of Biot and Savart. The results obtained for propagation speed and for magnetic field amplitude with the cellular automata model are compared with values predicted by the bidomain formulation, for various angles between wavefront propagation and fibre direction, characterizing excellent agreement between the models

Predicting Variation of DNA Shape Preferences in Protein-DNA Interaction in Cancer Cells with a New Biophysical Model.

Science.gov (United States)

Batmanov, Kirill; Wang, Junbai

2017-09-18

DNA shape readout is an important mechanism of transcription factor target site recognition, in addition to the sequence readout. Several machine learning-based models of transcription factor-DNA interactions, considering DNA shape features, have been developed in recent years. Here, we present a new biophysical model of protein-DNA interactions by integrating the DNA shape properties. It is based on the neighbor dinucleotide dependency model BayesPI2, where new parameters are restricted to a subspace spanned by the dinucleotide form of DNA shape features. This allows a biophysical interpretation of the new parameters as a position-dependent preference towards specific DNA shape features. Using the new model, we explore the variation of DNA shape preferences in several transcription factors across various cancer cell lines and cellular conditions. The results reveal that there are DNA shape variations at FOXA1 (Forkhead Box Protein A1) binding sites in steroid-treated MCF7 cells. The new biophysical model is useful for elucidating the finer details of transcription factor-DNA interaction, as well as for predicting cancer mutation effects in the future.

Two Phase Flow Simulation Using Cellular Automata; Simulacion de Flujos de dos Fases con Automatas Celulares

Energy Technology Data Exchange (ETDEWEB)

Marcel, C P [Instituto Balseiro, Universidad Nacional de Cuyo, Centro Atomico Bariloche (Argentina)

2002-07-01

The classical mathematical treatment of two-phase flows is based on the average of the conservation equations for each phase.In this work, a complementary approach to the modeling of these systems based on statistical population balances of aut omata sets is presented.Automata are entities defined by mathematical states that change following iterative rules representing interactions with the neighborhood.A model of automata for two-phase flow simulation is presented.This model consists of fie lds of virtual spheres that change their volumes and move around a certain environment.The model is more general than the classical cellular automata in two respects: the grid of cellular automata is dismissed in favor of a trajectory generator, and the rules of interaction involve parameters representing the actual physical interactions between phases.Automata simulation was used to study unsolved two-phase flow problems involving high heat flux rates. One system described in this work consists of a vertical channel with saturated water at normal pressure heated from the lower surface.The heater causes water to boil and starts the bubble production.We used cellular automata to describe two-phase flows and the interaction with the heater.General rule s for such cellular automata representing bubbles moving in stagnant liquid were used, with special attention to correct modeling of different mechanisms of heat transfer.The results of the model were compared to previous experiments and correlations finding good agreement.One of the most important findings is the confirmation of Kutateladze's idea about a close relation between the start of critical heat flux and a change in the flow's topology.This was analyzed using a control volume located in the upper surface of the heater.A strong decrease in the interfacial surface just before the CHF start was encountered.The automata describe quite well some characteristic parameters such as the shape of the local void fraction in the

Cellular metabolism

International Nuclear Information System (INIS)

Hildebrand, C.E.; Walters, R.A.

1977-01-01

Progress is reported on the following research projects: chromatin structure; the use of circular synthetic polydeoxynucleotides as substrates for the study of DNA repair enzymes; human cellular kinetic response following exposure to DNA-interactive compounds; histone phosphorylation and chromatin structure in cell proliferation; photoaddition products induced in chromatin by uv light; pollutants and genetic information transfer; altered RNA metabolism as a function of cadmium accumulation and intracellular distribution in cultured cells; and thymidylate chromophore destruction by water free radicals

A cellular stress response (CSR) that interacts with NADPH-P450 reductase (NPR) is a new regulator of hypoxic response.

Science.gov (United States)

Oguro, Ami; Koyama, Chika; Xu, Jing; Imaoka, Susumu

2014-02-28

NADPH-P450 reductase (NPR) was previously found to contribute to the hypoxic response of cells, but the mechanism was not clarified. In this study, we identified a cellular stress response (CSR) as a new factor interacting with NPR by a yeast two-hybrid system. Overexpression of CSR enhanced the induction of erythropoietin and hypoxia response element (HRE) activity under hypoxia in human hepatocarcinoma cell lines (Hep3B), while knockdown of CSR suppressed them. This new finding regarding the interaction of NPR with CSR provides insight into the function of NPR in hypoxic response. Copyright © 2014 Elsevier Inc. All rights reserved.

Identification of Redox and Glucose-Dependent Txnip Protein Interactions

Directory of Open Access Journals (Sweden)

Benjamin J. Forred

2016-01-01

Full Text Available Thioredoxin-interacting protein (Txnip acts as a negative regulator of thioredoxin function and is a critical modulator of several diseases including, but not limited to, diabetes, ischemia-reperfusion cardiac injury, and carcinogenesis. Therefore, Txnip has become an attractive therapeutic target to alleviate disease pathologies. Although Txnip has been implicated with numerous cellular processes such as proliferation, fatty acid and glucose metabolism, inflammation, and apoptosis, the molecular mechanisms underlying these processes are largely unknown. The objective of these studies was to identify Txnip interacting proteins using the proximity-based labeling method, BioID, to understand differential regulation of pleiotropic Txnip cellular functions. The BioID transgene fused to Txnip expressed in HEK293 identified 31 interacting proteins. Many protein interactions were redox-dependent and were disrupted through mutation of a previously described reactive cysteine (C247S. Furthermore, we demonstrate that this model can be used to identify dynamic Txnip interactions due to known physiological regulators such as hyperglycemia. These data identify novel Txnip protein interactions and demonstrate dynamic interactions dependent on redox and glucose perturbations, providing clarification to the pleiotropic cellular functions of Txnip.

An antiviral disulfide compound blocks interaction between arenavirus Z protein and cellular promyelocytic leukemia protein

International Nuclear Information System (INIS)

Garcia, C.C.; Topisirovic, I.; Djavani, M.; Borden, K.L.B.; Damonte, E.B.; Salvato, M.S.

2010-01-01

The promyelocytic leukemia protein (PML) forms nuclear bodies (NB) that can be redistributed by virus infection. In particular, lymphocytic choriomeningitis virus (LCMV) influences disruption of PML NB through the interaction of PML with the arenaviral Z protein. In a previous report, we have shown that the disulfide compound NSC20625 has antiviral and virucidal properties against arenaviruses, inducing unfolding and oligomerization of Z without affecting cellular RING-containing proteins such as the PML. Here, we further studied the effect of the zinc-finger-reactive disulfide NSC20625 on PML-Z interaction. In HepG2 cells infected with LCMV or transiently transfected with Z protein constructs, treatment with NSC20625 restored PML distribution from a diffuse-cytoplasmic pattern to punctate, discrete NB which appeared identical to NB found in control, uninfected cells. Similar results were obtained in cells transfected with a construct expressing a Z mutant in zinc-binding site 2 of the RING domain, confirming that this Z-PML interaction requires the integrity of only one zinc-binding site. Altogether, these results show that the compound NSC20625 suppressed Z-mediated PML NB disruption and may be used as a tool for designing novel antiviral strategies against arenavirus infection.

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

Science.gov (United States)

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

Characterizing Protein Interactions Employing a Genome-Wide siRNA Cellular Phenotyping Screen

Science.gov (United States)

Suratanee, Apichat; Schaefer, Martin H.; Betts, Matthew J.; Soons, Zita; Mannsperger, Heiko; Harder, Nathalie; Oswald, Marcus; Gipp, Markus; Ramminger, Ellen; Marcus, Guillermo; Männer, Reinhard; Rohr, Karl; Wanker, Erich; Russell, Robert B.; Andrade-Navarro, Miguel A.; Eils, Roland; König, Rainer

2014-01-01

Characterizing the activating and inhibiting effect of protein-protein interactions (PPI) is fundamental to gain insight into the complex signaling system of a human cell. A plethora of methods has been suggested to infer PPI from data on a large scale, but none of them is able to characterize the effect of this interaction. Here, we present a novel computational development that employs mitotic phenotypes of a genome-wide RNAi knockdown screen and enables identifying the activating and inhibiting effects of PPIs. Exemplarily, we applied our technique to a knockdown screen of HeLa cells cultivated at standard conditions. Using a machine learning approach, we obtained high accuracy (82% AUC of the receiver operating characteristics) by cross-validation using 6,870 known activating and inhibiting PPIs as gold standard. We predicted de novo unknown activating and inhibiting effects for 1,954 PPIs in HeLa cells covering the ten major signaling pathways of the Kyoto Encyclopedia of Genes and Genomes, and made these predictions publicly available in a database. We finally demonstrate that the predicted effects can be used to cluster knockdown genes of similar biological processes in coherent subgroups. The characterization of the activating or inhibiting effect of individual PPIs opens up new perspectives for the interpretation of large datasets of PPIs and thus considerably increases the value of PPIs as an integrated resource for studying the detailed function of signaling pathways of the cellular system of interest. PMID:25255318

Matrix metalloproteinase 3 promotes cellular anti-dengue virus response via interaction with transcription factor NFκB in cell nucleus.

Science.gov (United States)

Zuo, Xiangyang; Pan, Wen; Feng, Tingting; Shi, Xiaohong; Dai, Jianfeng

2014-01-01

Dengue virus (DENV), the causative agent of human Dengue hemorrhagic fever, is a mosquito-borne virus of immense global health importance. Characterization of cellular factors promoting or inhibiting DENV infection is important for understanding the mechanism of DENV infection. In this report, MMP3 (stromelysin-1), a secretory endopeptidase that degrades extracellular matrices, has been shown promoting cellular antiviral response against DENV infection. Quantitative RT-PCR and Western Blot showed that the expression of MMP3 was upregulated in DENV-infected RAW264.7 cells. The intracellular viral loads were significantly higher in MMP3 silenced cells compared with controls. The expression level of selective anti-viral cytokines were decreased in MMP3 siRNA treated cells, and the transcription factor activity of NFκB was significantly impaired upon MMP3 silencing during DENV infection. Further, we found that MMP3 moved to cell nucleus upon DENV infection and colocalized with NFκB P65 in nucleus. Co-immunoprecipitation analysis suggested that MMP3 directly interacted with NFκB in nucleus during DENV infection and the C-terminal hemopexin-like domain of MMP3 was required for the interaction. This study suggested a novel role of MMP3 in nucleus during viral infection and provided new evidence for MMPs in immunomodulation.

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

Science.gov (United States)

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.

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

Energy Technology Data Exchange (ETDEWEB)

Berman, Judith [Univ. of Minnesota, Minneapolis, MN (United States)

2012-06-22

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, genome 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.

Treatment Analysis in a Cancer Stem Cell Context Using a Tumor Growth Model Based on Cellular Automata.

Directory of Open Access Journals (Sweden)

Ángel Monteagudo

Full Text Available Cancer can be viewed as an emergent behavior in terms of complex system theory and artificial life, Cellular Automata (CA being the tool most used for studying and characterizing the emergent behavior. Different approaches with CA models were used to model cancer growth. The use of the abstract model of acquired cancer hallmarks permits the direct modeling at cellular level, where a cellular automaton defines the mitotic and apoptotic behavior of cells, and allows for an analysis of different dynamics of the cellular system depending on the presence of the different hallmarks. A CA model based on the presence of hallmarks in the cells, which includes a simulation of the behavior of Cancer Stem Cells (CSC and their implications for the resultant growth behavior of the multicellular system, was employed. This modeling of cancer growth, in the avascular phase, was employed to analyze the effect of cancer treatments in a cancer stem cell context. The model clearly explains why, after treatment against non-stem cancer cells, the regrowth capability of CSCs generates a faster regrowth of tumor behavior, and also shows that a continuous low-intensity treatment does not favor CSC proliferation and differentiation, thereby allowing an unproblematic control of future tumor regrowth. The analysis performed indicates that, contrary to the current attempts at CSC control, trying to make CSC proliferation more difficult is an important point to consider, especially in the immediate period after a standard treatment for controlling non-stem cancer cell proliferation.

Structural requirements for the assembly of LINC complexes and their function in cellular mechanical stiffness

International Nuclear Information System (INIS)

Stewart-Hutchinson, P.J.; Hale, Christopher M.; Wirtz, Denis; Hodzic, Didier

2008-01-01

The evolutionary-conserved interactions between KASH and SUN domain-containing proteins within the perinuclear space establish physical connections, called LINC complexes, between the nucleus and the cytoskeleton. Here, we show that the KASH domains of Nesprins 1, 2 and 3 interact promiscuously with luminal domains of Sun1 and Sun2. These constructs disrupt endogenous LINC complexes as indicated by the displacement of endogenous Nesprins from the nuclear envelope. We also provide evidence that KASH domains most probably fit a pocket provided by SUN domains and that post-translational modifications are dispensable for that interaction. We demonstrate that the disruption of endogenous LINC complexes affect cellular mechanical stiffness to an extent that compares to the loss of mechanical stiffness previously reported in embryonic fibroblasts derived from mouse lacking A-type lamins, a mouse model of muscular dystrophies and cardiomyopathies. These findings support a model whereby physical connections between the nucleus and the cytoskeleton are mediated by interactions between diverse combinations of Sun proteins and Nesprins through their respective evolutionary-conserved domains. Furthermore, they emphasize, for the first time, the relevance of LINC complexes in cellular mechanical stiffness suggesting a possible involvement of their disruption in various laminopathies, a group of human diseases linked to mutations of A-type lamins

Organ Culture as a Model System for Studies on Enterotoxin Interactions with the Intestinal Epithelium

DEFF Research Database (Denmark)

Lorenzen, Ulver Spangsberg; Hansen, Gert H; Danielsen, E Michael

2015-01-01

Studies on bacterial enterotoxin-epithelium interactions require model systems capable of mimicking the events occurring at the molecular and cellular levels during intoxication. In this chapter, we describe organ culture as an often neglected alternative to whole-animal experiments or enterocyte......-like cell lines. Like cell culture, organ culture is versatile and suitable for studying rapidly occurring events, such as enterotoxin binding and uptake. In addition, it is advantageous in offering an epithelium with more authentic permeability/barrier properties than any cell line, as well...

Cellular automaton modeling of ductile iron microstructure in the thin wall

Directory of Open Access Journals (Sweden)

A.A. Burbelko

2011-10-01

Full Text Available The mathematical model of the globular eutectic solidification in 2D was designed. Proposed model is based on the Cellular Automaton Finite Differences (CA-FD calculation method. Model has been used for studies of the primary austenite and of globular eutectic grains growth during the solidification of the ductile iron with different carbon equivalent in the thin wall casting. Model takes into account, among other things, non-uniform temperature distribution in the casting wall cross-section, kinetics of the austenite and graphite grains nucleation, and non-equilibrium nature of the interphase boundary migration. Solidification of the DI with different carbon equivalents was analyzed. Obtained results were compared with the solidification path calculated by CALPHAD method.

Cellular Interactions and Biological Responses to Titanium Dioxide Nanoparticles in HepG2 and BEAS-2B Cells: Role of Cell Culture Media

Science.gov (United States)

ABSTRACT We have shown previously that the composition of the biological medium used in vitro can affect the cellular interaction and biological response of titanium dioxide nanoparticles (nano-TiO2) in human lung epithelial cells. However, it is unclear if these effects are co...

Probing Cellular Dynamics with Mesoscopic Simulations

DEFF Research Database (Denmark)

Shillcock, Julian C.

2010-01-01

Cellular processes span a huge range of length and time scales from the molecular to the near-macroscopic. Understanding how effects on one scale influence, and are themselves influenced by, those on lower and higher scales is a critical issue for the construction of models in Systems Biology....... Advances in computing hardware and software now allow explicit simulation of some aspects of cellular dynamics close to the molecular scale. Vesicle fusion is one example of such a process. Experiments, however, typically probe cellular behavior from the molecular scale up to microns. Standard particle...... soon be coupled to Mass Action models allowing the parameters in such models to be continuously tuned according to the finer resolution simulation. This will help realize the goal of a computational cellular simulation that is able to capture the dynamics of membrane-associated processes...

Maternal nutrient restriction in baboon programs later-life cellular growth and respiration of cultured skin fibroblasts: a potential model for the study of aging-programming interactions.

Science.gov (United States)

Salmon, Adam B; Dorigatti, Jonathan; Huber, Hillary F; Li, Cun; Nathanielsz, Peter W

2018-05-25

Compelling data exist for programming of chronic later-life diseases and longevity by perinatal developmental programming challenges. Understanding mechanisms by which life course health trajectory and longevity are set is fundamental to understanding aging. Appropriate approaches are needed to determine programming effects on cellular function. We have developed a baboon model in which control mothers eat ad libitum while a second group eat 70% of the global diet fed controls, leading to male and female offspring intrauterine growth restriction (IUGR). We have shown that IUGR suffer from acceleration of several age-related physiological declines. Here, we report on a skin-derived fibroblast model with potential relevance for mechanistic studies on how IUGR impacts aging. Fibroblasts were cultured from the skin biopsies taken from adult baboons from control and IUGR cohorts. IUGR-derived fibroblasts grew in culture less well than controls and those derived from male, but not female, IUGR baboons had a significant reduction in maximum respiration rate compared to control-derived fibroblasts. We also show that relative levels of several mitochondrial protein subunits, including NDUFB8 and cytochrome c oxidase subunit IV, were reduced in IUGR-derived fibroblasts even after serial passaging in culture. The lower levels of electron transport system components provide potential mechanisms for accelerated life course aging in the setting of programmed IUGR. This observation fits with the greater sensitivity of males compared with females to many, but not all, outcomes in response to programming challenges. These approaches will be powerful in the determination of programming-aging interactions.

Building synthetic cellular organization

OpenAIRE

Polka, Jessica K.; Silver, Pamela A.

2013-01-01

The elaborate spatial organization of cells enhances, restricts, and regulates protein–protein interactions. However, the biological significance of this organization has been difficult to study without ways of directly perturbing it. We highlight synthetic biology tools for engineering novel cellular organization, describing how they have been, and can be, used to advance cell biology.

fA cellular automaton model of crystalline cellulose hydrolysis by cellulases

Directory of Open Access Journals (Sweden)

Little Bryce A

2011-10-01

Full Text Available Abstract Background Cellulose from plant biomass is an abundant, renewable material which could be a major feedstock for low emissions transport fuels such as cellulosic ethanol. Cellulase enzymes that break down cellulose into fermentable sugars are composed of different types - cellobiohydrolases I and II, endoglucanase and β-glucosidase - with separate functions. They form a complex interacting network between themselves, soluble hydrolysis product molecules, solution and solid phase substrates and inhibitors. There have been many models proposed for enzymatic saccharification however none have yet employed a cellular automaton approach, which allows important phenomena, such as enzyme crowding on the surface of solid substrates, denaturation and substrate inhibition, to be considered in the model. Results The Cellulase 4D model was developed de novo taking into account the size and composition of the substrate and surface-acting enzymes were ascribed behaviors based on their movements, catalytic activities and rates, affinity for, and potential for crowding of, the cellulose surface, substrates and inhibitors, and denaturation rates. A basic case modeled on literature-derived parameters obtained from Trichoderma reesei cellulases resulted in cellulose hydrolysis curves that closely matched curves obtained from published experimental data. Scenarios were tested in the model, which included variation of enzyme loadings, adsorption strengths of surface acting enzymes and reaction periods, and the effect on saccharide production over time was assessed. The model simulations indicated an optimal enzyme loading of between 0.5 and 2 of the base case concentrations where a balance was obtained between enzyme crowding on the cellulose crystal, and that the affinities of enzymes for the cellulose surface had a large effect on cellulose hydrolysis. In addition, improvements to the cellobiohydrolase I activity period substantially improved overall

A Computational model for compressed sensing RNAi cellular screening

Directory of Open Access Journals (Sweden)

Tan Hua

2012-12-01

Full Text Available Abstract Background RNA interference (RNAi becomes an increasingly important and effective genetic tool to study the function of target genes by suppressing specific genes of interest. This system approach helps identify signaling pathways and cellular phase types by tracking intensity and/or morphological changes of cells. The traditional RNAi screening scheme, in which one siRNA is designed to knockdown one specific mRNA target, needs a large library of siRNAs and turns out to be time-consuming and expensive. Results In this paper, we propose a conceptual model, called compressed sensing RNAi (csRNAi, which employs a unique combination of group of small interfering RNAs (siRNAs to knockdown a much larger size of genes. This strategy is based on the fact that one gene can be partially bound with several small interfering RNAs (siRNAs and conversely, one siRNA can bind to a few genes with distinct binding affinity. This model constructs a multi-to-multi correspondence between siRNAs and their targets, with siRNAs much fewer than mRNA targets, compared with the conventional scheme. Mathematically this problem involves an underdetermined system of equations (linear or nonlinear, which is ill-posed in general. However, the recently developed compressed sensing (CS theory can solve this problem. We present a mathematical model to describe the csRNAi system based on both CS theory and biological concerns. To build this model, we first search nucleotide motifs in a target gene set. Then we propose a machine learning based method to find the effective siRNAs with novel features, such as image features and speech features to describe an siRNA sequence. Numerical simulations show that we can reduce the siRNA library to one third of that in the conventional scheme. In addition, the features to describe siRNAs outperform the existing ones substantially. Conclusions This csRNAi system is very promising in saving both time and cost for large-scale RNAi

Regular cellular distribution of plasmids by oscillating and filament-forming ParA ATPase of plasmid pB171

DEFF Research Database (Denmark)

Ebersbach, Gitte; Ringgaard, Simon; Møller-Jensen, Jakob

2006-01-01

with each other in a bacterial two-hybrid assay but do not interact with FtsZ, eight other essential cell division proteins or MreB actin. Based on these observations, we propose a simple model for how oscillating ParA filaments can mediate regular cellular distribution of plasmids. The model functions...

Interacting boson model with surface delta interaction between nucleons: Structure and interaction of bosons

International Nuclear Information System (INIS)

Druce, C.H.; Moszkowski, S.A.

1986-01-01

The surface delta interaction is used as an effective nucleon-nucleon interaction to investigate the structure and interaction of the bosons in the interacting boson model. We have obtained analytical expressions for the coefficients of a multipole expansion of the neutron-boson-proton-boson interaction for the case of degenerate orbits. A connection is made between these coefficients and the parameters of the interaction boson model Hamiltonian. A link between the latter parameters and the single boson energies is suggested

Interacting boson model with surface delta interaction between nucleons: Structure and interaction of bosons

Energy Technology Data Exchange (ETDEWEB)

Druce, C.H.; Moszkowski, S.A.

1986-01-01

The surface delta interaction is used as an effective nucleon-nucleon interaction to investigate the structure and interaction of the bosons in the interacting boson model. We have obtained analytical expressions for the coefficients of a multipole expansion of the neutron-boson-proton-boson interaction for the case of degenerate orbits. A connection is made between these coefficients and the parameters of the interaction boson model Hamiltonian. A link between the latter parameters and the single boson energies is suggested.

Interactive Dimensioning of Parametric Models

KAUST Repository

Kelly, T.

2015-06-22

We propose a solution for the dimensioning of parametric and procedural models. Dimensioning has long been a staple of technical drawings, and we present the first solution for interactive dimensioning: A dimension line positioning system that adapts to the view direction, given behavioral properties. After proposing a set of design principles for interactive dimensioning, we describe our solution consisting of the following major components. First, we describe how an author can specify the desired interactive behavior of a dimension line. Second, we propose a novel algorithm to place dimension lines at interactive speeds. Third, we introduce multiple extensions, including chained dimension lines, controls for different parameter types (e.g. discrete choices, angles), and the use of dimension lines for interactive editing. Our results show the use of dimension lines in an interactive parametric modeling environment for architectural, botanical, and mechanical models.

Interacting boson model with surface delta interaction between nucleons

International Nuclear Information System (INIS)

Druce, C.; Moszkowski, S.A.

1984-01-01

The surface delta interaction is used as an effective nucleon-nucleon interaction to investigate the structure and interaction of the bosons in the interacting boson model. The authors have obtained analytical expressions for the coefficients of a multipole expansion of the neutron-boson proton-boson interaction for the case of degenerate orbits

Stochastic cellular automata model of cell migration, proliferation and differentiation: validation with in vitro cultures of muscle satellite cells.

Science.gov (United States)

Garijo, N; Manzano, R; Osta, R; Perez, M A

2012-12-07

Cell migration and proliferation has been modelled in the literature as a process similar to diffusion. However, using diffusion models to simulate the proliferation and migration of cells tends to create a homogeneous distribution in the cell density that does not correlate to empirical observations. In fact, the mechanism of cell dispersal is not diffusion. Cells disperse by crawling or proliferation, or are transported in a moving fluid. The use of cellular automata, particle models or cell-based models can overcome this limitation. This paper presents a stochastic cellular automata model to simulate the proliferation, migration and differentiation of cells. These processes are considered as completely stochastic as well as discrete. The model developed was applied to predict the behaviour of in vitro cell cultures performed with adult muscle satellite cells. Moreover, non homogeneous distribution of cells has been observed inside the culture well and, using the above mentioned stochastic cellular automata model, we have been able to predict this heterogeneous cell distribution and compute accurate quantitative results. Differentiation was also incorporated into the computational simulation. The results predicted the myotube formation that typically occurs with adult muscle satellite cells. In conclusion, we have shown how a stochastic cellular automata model can be implemented and is capable of reproducing the in vitro behaviour of adult muscle satellite cells. Copyright © 2012 Elsevier Ltd. All rights reserved.

Antiproliferative Activity and Cellular Uptake of Evodiamine and Rutaecarpine Based on 3D Tumor Models

Directory of Open Access Journals (Sweden)

Hui Guo

2016-07-01

Full Text Available Evodiamine (EVO and rutaecarpine (RUT are promising anti-tumor drug candidates. The evaluation of the anti-proliferative activity and cellular uptake of EVO and RUT in 3D multicellular spheroids of cancer cells would better recapitulate the native situation and thus better reflect an in vivo response to the treatment. Herein, we employed the 3D culture of MCF-7 and SMMC-7721 cells based on hanging drop method and evaluated the anti-proliferative activity and cellular uptake of EVO and RUT in 3D multicellular spheroids, and compared the results with those obtained from 2D monolayers. The drugs’ IC50 values were significantly increased from the range of 6.4–44.1 μM in 2D monolayers to 21.8–138.0 μM in 3D multicellular spheroids, which may be due to enhanced mass barrier and reduced drug penetration in 3D models. The fluorescence of EVO and RUT was measured via fluorescence spectroscopy and the cellular uptake of both drugs was characterized in 2D tumor models. The results showed that the cellular uptake concentrations of RUT increased with increasing drug concentrations. However, the EVO concentrations uptaken by the cells showed only a small change with increasing drug concentrations, which may be due to the different solubility of EVO and Rut in solvents. Overall, this study provided a new vision of the anti-tumor activity of EVO and RUT via 3D multicellular spheroids and cellular uptake through the fluorescence of compounds.

IRESPred: Web Server for Prediction of Cellular and Viral Internal Ribosome Entry Site (IRES)

Science.gov (United States)

Kolekar, Pandurang; Pataskar, Abhijeet; Kulkarni-Kale, Urmila; Pal, Jayanta; Kulkarni, Abhijeet

2016-01-01

Cellular mRNAs are predominantly translated in a cap-dependent manner. However, some viral and a subset of cellular mRNAs initiate their translation in a cap-independent manner. This requires presence of a structured RNA element, known as, Internal Ribosome Entry Site (IRES) in their 5′ untranslated regions (UTRs). Experimental demonstration of IRES in UTR remains a challenging task. Computational prediction of IRES merely based on sequence and structure conservation is also difficult, particularly for cellular IRES. A web server, IRESPred is developed for prediction of both viral and cellular IRES using Support Vector Machine (SVM). The predictive model was built using 35 features that are based on sequence and structural properties of UTRs and the probabilities of interactions between UTR and small subunit ribosomal proteins (SSRPs). The model was found to have 75.51% accuracy, 75.75% sensitivity, 75.25% specificity, 75.75% precision and Matthews Correlation Coefficient (MCC) of 0.51 in blind testing. IRESPred was found to perform better than the only available viral IRES prediction server, VIPS. The IRESPred server is freely available at http://bioinfo.net.in/IRESPred/. PMID:27264539

Cellular automata with voting rule

International Nuclear Information System (INIS)

Makowiec, D.

1996-01-01

The chosen local interaction - the voting (majority) rule applied to the square lattice is known to cause the non ergodic cellular automata behaviour. Presented computer simulation results verify two cases of non ergodicity. The first one is implicated by the noise introduced to the local interactions and the second one follows properties of the initial lattice configuration selected at random. For the simplified voting rule - non symmetric voting, the critical behaviour has been explained rigorously. (author)

The Structure of an Infectious Human Polyomavirus and Its Interactions with Cellular Receptors.

Science.gov (United States)

Hurdiss, Daniel L; Frank, Martin; Snowden, Joseph S; Macdonald, Andrew; Ranson, Neil A

2018-04-21

BK polyomavirus (BKV) causes polyomavirus-associated nephropathy and hemorrhagic cystitis in immunosuppressed patients. These are diseases for which we currently have limited treatment options, but potential therapies could include pre-transplant vaccination with a multivalent BKV vaccine or therapeutics which inhibit capsid assembly or block attachment and entry into target cells. A useful tool in such efforts would be a high-resolution structure of the infectious BKV virion and how this interacts with its full repertoire of cellular receptors. We present the 3.4-Å cryoelectron microscopy structure of native, infectious BKV in complex with the receptor fragment of GT1b ganglioside. We also present structural evidence that BKV can utilize glycosaminoglycans as attachment receptors. This work highlights features that underpin capsid stability and provides a platform for rational design and development of urgently needed pharmacological interventions for BKV-associated diseases. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Ocean acidification affects competition for space: projections of community structure using cellular automata.

Science.gov (United States)

McCoy, Sophie J; Allesina, Stefano; Pfister, Catherine A

2016-03-16

Historical ecological datasets from a coastal marine community of crustose coralline algae (CCA) enabled the documentation of ecological changes in this community over 30 years in the Northeast Pacific. Data on competitive interactions obtained from field surveys showed concordance between the 1980s and 2013, yet also revealed a reduction in how strongly species interact. Here, we extend these empirical findings with a cellular automaton model to forecast ecological dynamics. Our model suggests the emergence of a new dominant competitor in a global change scenario, with a reduced role of herbivory pressure, or trophic control, in regulating competition among CCA. Ocean acidification, due to its energetic demands, may now instead play this role in mediating competitive interactions and thereby promote species diversity within this guild. © 2016 The Author(s).

Elastomeric Cellular Structure Enhanced by Compressible Liquid Filler

Science.gov (United States)

Sun, Yueting; Xu, Xiaoqing; Xu, Chengliang; Qiao, Yu; Li, Yibing

2016-05-01

Elastomeric cellular structures provide a promising solution for energy absorption. Their flexible and resilient nature is particularly relevant to protection of human bodies. Herein we develop an elastomeric cellular structure filled with nanoporous material functionalized (NMF) liquid. Due to the nanoscale infiltration in NMF liquid and its interaction with cell walls, the cellular structure has a much enhanced mechanical performance, in terms of loading capacity and energy absorption density. Moreover, it is validated that the structure is highly compressible and self-restoring. Its hyper-viscoelastic characteristics are elucidated.

Magnetohydrodynamics cellular automata

International Nuclear Information System (INIS)

Hatori, Tadatsugu.

1990-02-01

There has been a renewal of interest in cellular automata, partly because they give an architecture for a special purpose computer with parallel processing optimized to solve a particular problem. The lattice gas cellular automata are briefly surveyed, which are recently developed to solve partial differential equations such as hydrodynamics or magnetohydrodynamics. A new model is given in the present paper to implement the magnetic Lorentz force in a more deterministic and local procedure than the previous one. (author)

Magnetohydrodynamic cellular automata

Energy Technology Data Exchange (ETDEWEB)

Hatori, Tadatsugu [National Inst. for Fusion Science, Nagoya (Japan)

1990-03-01

There has been a renewal of interest in cellular automata, partly because they give an architecture for a special purpose computer with parallel processing optimized to solve a particular problem. The lattice gas cellular automata are briefly surveyed, which are recently developed to solve partial differential equations such as hydrodynamics or magnetohydrodynamics. A new model is given in the present paper to implement the magnetic Lorentz force in a more deterministic and local procedure than the previous one. (author).

Magnetohydrodynamic cellular automata

International Nuclear Information System (INIS)

Hatori, Tadatsugu

1990-01-01

There has been a renewal of interest in cellular automata, partly because they give an architecture for a special purpose computer with parallel processing optimized to solve a particular problem. The lattice gas cellular automata are briefly surveyed, which are recently developed to solve partial differential equations such as hydrodynamics or magnetohydrodynamics. A new model is given in the present paper to implement the magnetic Lorentz force in a more deterministic and local procedure than the previous one. (author)

Atomistic simulations of anionic Au-144(SR)(60) nanoparticles interacting with asymmetric model lipid membranes

DEFF Research Database (Denmark)

Heikkila, E.; Martinez-Seara, H.; Gurtovenko, A. A.

2014-01-01

whose lipid composition and transmembrane distribution are to a large extent consistent with real plasma membranes of eukaryotic cells. To this end, we use a model system which comprises two cellular compartments, extracellular and cytosolic, divided by two asymmetric lipid bilayers. The simulations...... clearly show that AuNP- attaches to the extracellular membrane surface within a few tens of nanoseconds, while it avoids contact with the membrane on the cytosolic side. This behavior stems from several factors. In essence, when the nanoparticle interacts with lipids in the extracellular compartment...

Localized Modeling of Biochemical and Flow Interactions during Cancer Cell Adhesion.

Directory of Open Access Journals (Sweden)

Julie Behr

Full Text Available This work focuses on one component of a larger research effort to develop a simulation tool to model populations of flowing cells. Specifically, in this study a local model of the biochemical interactions between circulating melanoma tumor cells (TC and substrate adherent polymorphonuclear neutrophils (PMN is developed. This model provides realistic three-dimensional distributions of bond formation and attendant attraction and repulsion forces that are consistent with the time dependent Computational Fluid Dynamics (CFD framework of the full system model which accounts local pressure, shear and repulsion forces. The resulting full dynamics model enables exploration of TC adhesion to adherent PMNs, which is a known participating mechanism in melanoma cell metastasis. The model defines the adhesion molecules present on the TC and PMN cell surfaces, and calculates their interactions as the melanoma cell flows past the PMN. Biochemical rates of reactions between individual molecules are determined based on their local properties. The melanoma cell in the model expresses ICAM-1 molecules on its surface, and the PMN expresses the β-2 integrins LFA-1 and Mac-1. In this work the PMN is fixed to the substrate and is assumed fully rigid and of a prescribed shear-rate dependent shape obtained from micro-PIV experiments. The melanoma cell is transported with full six-degrees-of-freedom dynamics. Adhesion models, which represent the ability of molecules to bond and adhere the cells to each other, and repulsion models, which represent the various physical mechanisms of cellular repulsion, are incorporated with the CFD solver. All models are general enough to allow for future extensions, including arbitrary adhesion molecule types, and the ability to redefine the values of parameters to represent various cell types. The model presented in this study will be part of a clinical tool for development of personalized medical treatment programs.

Localized Modeling of Biochemical and Flow Interactions during Cancer Cell Adhesion.

Science.gov (United States)

Behr, Julie; Gaskin, Byron; Fu, Changliang; Dong, Cheng; Kunz, Robert

2015-01-01

This work focuses on one component of a larger research effort to develop a simulation tool to model populations of flowing cells. Specifically, in this study a local model of the biochemical interactions between circulating melanoma tumor cells (TC) and substrate adherent polymorphonuclear neutrophils (PMN) is developed. This model provides realistic three-dimensional distributions of bond formation and attendant attraction and repulsion forces that are consistent with the time dependent Computational Fluid Dynamics (CFD) framework of the full system model which accounts local pressure, shear and repulsion forces. The resulting full dynamics model enables exploration of TC adhesion to adherent PMNs, which is a known participating mechanism in melanoma cell metastasis. The model defines the adhesion molecules present on the TC and PMN cell surfaces, and calculates their interactions as the melanoma cell flows past the PMN. Biochemical rates of reactions between individual molecules are determined based on their local properties. The melanoma cell in the model expresses ICAM-1 molecules on its surface, and the PMN expresses the β-2 integrins LFA-1 and Mac-1. In this work the PMN is fixed to the substrate and is assumed fully rigid and of a prescribed shear-rate dependent shape obtained from micro-PIV experiments. The melanoma cell is transported with full six-degrees-of-freedom dynamics. Adhesion models, which represent the ability of molecules to bond and adhere the cells to each other, and repulsion models, which represent the various physical mechanisms of cellular repulsion, are incorporated with the CFD solver. All models are general enough to allow for future extensions, including arbitrary adhesion molecule types, and the ability to redefine the values of parameters to represent various cell types. The model presented in this study will be part of a clinical tool for development of personalized medical treatment programs.

Numerical Simulation of Interactions between Corrosion Pits on Stainless Steel under Loading Conditions

International Nuclear Information System (INIS)

Wang, Haitao; Han, En-Hou

2017-01-01

The interactions between corrosion pits on stainless steel under loading conditions are studied by using a cellular automata model coupled with finite element method at a mesoscopic scale. The cellular automata model focuses on a metal/film/electrolyte system, including anodic dissolution, passivation, diffusion of hydrogen ions and salt film hydrolysis. The Chopard block algorithm is used to improve the diffusion simulation efficiency. The finite element method is used to calculate the stress concentration on the pit surface during pit growth, and the effect of local stress and strain on anodic current is obtained by using the Gutman model, which is used as the boundary conditions of the cellular automata model. The transient current characteristics of the interactions between corrosion pits under different simulation factors including the breakdown of the passive film at the pit mouth and the diffusion of hydrogen ions are analyzed. The analysis of the pit stability product shows that the simulation results are close to the experimental conclusions.

Numerical Simulation of Interactions between Corrosion Pits on Stainless Steel under Loading Conditions

Energy Technology Data Exchange (ETDEWEB)

Wang, Haitao; Han, En-Hou [Chinese Academy of Sciences, Shenyang (China)

2017-04-15

The interactions between corrosion pits on stainless steel under loading conditions are studied by using a cellular automata model coupled with finite element method at a mesoscopic scale. The cellular automata model focuses on a metal/film/electrolyte system, including anodic dissolution, passivation, diffusion of hydrogen ions and salt film hydrolysis. The Chopard block algorithm is used to improve the diffusion simulation efficiency. The finite element method is used to calculate the stress concentration on the pit surface during pit growth, and the effect of local stress and strain on anodic current is obtained by using the Gutman model, which is used as the boundary conditions of the cellular automata model. The transient current characteristics of the interactions between corrosion pits under different simulation factors including the breakdown of the passive film at the pit mouth and the diffusion of hydrogen ions are analyzed. The analysis of the pit stability product shows that the simulation results are close to the experimental conclusions.

Optimization of spectral printer modeling based on a modified cellular Yule-Nielsen spectral Neugebauer model.

Science.gov (United States)

Liu, Qiang; Wan, Xiaoxia; Xie, Dehong

2014-06-01

The study presented here optimizes several steps in the spectral printer modeling workflow based on a cellular Yule-Nielsen spectral Neugebauer (CYNSN) model. First, a printer subdividing method was developed that reduces the number of sub-models while maintaining the maximum device gamut. Second, the forward spectral prediction accuracy of the CYNSN model for each subspace of the printer was improved using back propagation artificial neural network (BPANN) estimated n values. Third, a sequential gamut judging method, which clearly reduced the complexity of the optimal sub-model and cell searching process during printer backward modeling, was proposed. After that, we further modified the use of the modeling color metric and comprehensively improved the spectral and perceptual accuracy of the spectral printer model. The experimental results show that the proposed optimization approaches provide obvious improvements in aspects of the modeling accuracy or efficiency for each of the corresponding steps, and an overall improvement of the optimized spectral printer modeling workflow was also demonstrated.

Nested cellular automata

International Nuclear Information System (INIS)

Quasthoff, U.

1985-07-01

Cellular automata by definition consist of a finite or infinite number of cells, say of unit length, with each cell having the same transition function. These cells are usually considered as the smallest elements and so the space filled with these cells becomes discrete. Nevertheless, large pictures created by such cellular automata look very fractal. So we try to replace each cell by a couple of smaller cells, which have the same transition functions as the large ones. There are automata where this replacement does not destroy the macroscopic structure. In these cases this nesting process can be iterated. The paper contains large classes of automata with the above properties. In the case of one dimensional automata with two states and next neighbour interaction and a nesting function of the same type a complete classification is given. (author)

Cellular interactions via conditioned media induce in vivo nephron generation from tubular epithelial cells or mesenchymal stem cells

International Nuclear Information System (INIS)

Machiguchi, Toshihiko; Nakamura, Tatsuo

2013-01-01

Highlights: •We have attempted in vivo nephron generation using conditioned media. •Vascular and tubular cells do cross-talks on cell proliferation and tubular changes. •Tubular cells suppress these changes in mesenchymal stem cells. •Tubular cells differentiate mesenchymal stem cells into tubular cells. •Nephrons can be created from implanted tubular cells or mesenchymal stem cells. -- Abstract: There are some successful reports of kidney generation by utilizing the natural course of kidney development, namely, the use of an artificially treated metanephros, blastocyst or ureteric bud. Under a novel concept of cellular interactions via conditioned media (CMs), we have attempted in vivo nephron generation from tubular epithelial cells (TECs) or mesenchymal stem cells (MSCs). Here we used 10× CMs of vascular endothelial cells (VECs) and TECs, which is the first to introduce a CM into the field of organ regeneration. We first present stimulative cross-talks induced by these CMs between VECs and TECs on cell proliferation and morphological changes. In MSCs, TEC-CM suppressed these changes, however, induced cytokeratin expression, indicating the differentiation of MSCs into TECs. As a result, glomerular and tubular structures were created following the implantation of TECs or MSCs with both CMs. Our findings suggest that the cellular interactions via CMs might induce in vivo nephron generation from TECs or MSCs. As a promoting factor, CMs could also be applied to the regeneration of other organs and tissues

A cellular automata model for traffic flow based on kinetics theory, vehicles capabilities and driver reactions

Science.gov (United States)

Guzmán, H. A.; Lárraga, M. E.; Alvarez-Icaza, L.; Carvajal, J.

2018-02-01

In this paper, a reliable cellular automata model oriented to faithfully reproduce deceleration and acceleration according to realistic reactions of drivers, when vehicles with different deceleration capabilities are considered is presented. The model focuses on describing complex traffic phenomena by coding in its rules the basic mechanisms of drivers behavior, vehicles capabilities and kinetics, while preserving simplicity. In particular, vehiclés kinetics is based on uniform accelerated motion, rather than in impulsive accelerated motion as in most existing CA models. Thus, the proposed model calculates in an analytic way three safe preserving distances to determine the best action a follower vehicle can take under a worst case scenario. Besides, the prediction analysis guarantees that under the proper assumptions, collision between vehicles may not happen at any future time. Simulations results indicate that all interactions of heterogeneous vehicles (i.e., car-truck, truck-car, car-car and truck-truck) are properly reproduced by the model. In addition, the model overcomes one of the major limitations of CA models for traffic modeling: the inability to perform smooth approach to slower or stopped vehicles. Moreover, the model is also capable of reproducing most empirical findings including the backward speed of the downstream front of the traffic jam, and different congested traffic patterns induced by a system with open boundary conditions with an on-ramp. Like most CA models, integer values are used to make the model run faster, which makes the proposed model suitable for real time traffic simulation of large networks.

Analysis of Protein-Membrane Interactions

DEFF Research Database (Denmark)

Kemmer, Gerdi Christine

Cellular membranes are complex structures, consisting of hundreds of different lipids and proteins. These membranes act as barriers between distinct environments, constituting hot spots for many essential functions of the cell, including signaling, energy conversion, and transport. These functions....... Discovered interactions were then probed on the level of the membrane using liposome-based assays. In the second part, a transmembrane protein was investigated. Assays to probe activity of the plasma membrane ATPase (Arabidopsis thaliana H+ -ATPase isoform 2 (AHA2)) in single liposomes using both giant...... are implemented by soluble proteins reversibly binding to, as well as by integral membrane proteins embedded in, cellular membranes. The activity and interaction of these proteins is furthermore modulated by the lipids of the membrane. Here, liposomes were used as model membrane systems to investigate...

On stochastic geometry modeling of cellular uplink transmission with truncated channel inversion power control

KAUST Repository

Elsawy, Hesham; Hossain, Ekram

2014-01-01

Using stochastic geometry, we develop a tractable uplink modeling paradigm for outage probability and spectral efficiency in both single and multi-tier cellular wireless networks. The analysis accounts for per user equipment (UE) power control

Modeling the properties of closed-cell cellular materials from tomography images using finite shell elements

International Nuclear Information System (INIS)

Caty, O.; Maire, E.; Youssef, S.; Bouchet, R.

2008-01-01

Closed-cell cellular materials exhibit several interesting properties. These properties are, however, very difficult to simulate and understand from the knowledge of the cellular microstructure. This problem is mostly due to the highly complex organization of the cells and to their very fine walls. X-ray tomography can produce three-dimensional (3-D) images of the structure, enabling one to visualize locally the damage of the cell walls that would result in the structure collapsing. These data could be used for meshing with continuum elements of the structure for finite element (FE) calculations. But when the density is very low, the walls are fine and the meshes based on continuum elements are not suitable to represent accurately the structure while preserving the representativeness of the model in terms of cell size. This paper presents a shell FE model obtained from tomographic 3-D images that allows bigger volumes of low-density closed-cell cellular materials to be calculated. The model is enriched by direct thickness measurement on the tomographic images. The values measured are ascribed to the shell elements. To validate and use the model, a structure composed of stainless steel hollow spheres is firstly compressed and scanned to observe local deformations. The tomographic data are also meshed with shells for a FE calculation. The convergence of the model is checked and its performance is compared with a continuum model. The global behavior is compared with the measures of the compression test. At the local scale, the model allows the local stress and strain field to be calculated. The calculated deformed shape is compared with the deformed tomographic images

Symmetry structure in discrete models of biochemical systems: natural subsystems and the weak control hierarchy in a new model of computation driven by interactions.

Science.gov (United States)

Nehaniv, Chrystopher L; Rhodes, John; Egri-Nagy, Attila; Dini, Paolo; Morris, Eric Rothstein; Horváth, Gábor; Karimi, Fariba; Schreckling, Daniel; Schilstra, Maria J

2015-07-28

Interaction computing is inspired by the observation that cell metabolic/regulatory systems construct order dynamically, through constrained interactions between their components and based on a wide range of possible inputs and environmental conditions. The goals of this work are to (i) identify and understand mathematically the natural subsystems and hierarchical relations in natural systems enabling this and (ii) use the resulting insights to define a new model of computation based on interactions that is useful for both biology and computation. The dynamical characteristics of the cellular pathways studied in systems biology relate, mathematically, to the computational characteristics of automata derived from them, and their internal symmetry structures to computational power. Finite discrete automata models of biological systems such as the lac operon, the Krebs cycle and p53-mdm2 genetic regulation constructed from systems biology models have canonically associated algebraic structures (their transformation semigroups). These contain permutation groups (local substructures exhibiting symmetry) that correspond to 'pools of reversibility'. These natural subsystems are related to one another in a hierarchical manner by the notion of 'weak control'. We present natural subsystems arising from several biological examples and their weak control hierarchies in detail. Finite simple non-Abelian groups are found in biological examples and can be harnessed to realize finitary universal computation. This allows ensembles of cells to achieve any desired finitary computational transformation, depending on external inputs, via suitably constrained interactions. Based on this, interaction machines that grow and change their structure recursively are introduced and applied, providing a natural model of computation driven by interactions.

Estimating cellular network performance during hurricanes

International Nuclear Information System (INIS)

Booker, Graham; Torres, Jacob; Guikema, Seth; Sprintson, Alex; Brumbelow, Kelly

2010-01-01

Cellular networks serve a critical role during and immediately after a hurricane, allowing citizens to contact emergency services when land-line communication is lost and serving as a backup communication channel for emergency responders. However, due to their ubiquitous deployment and limited design for extreme loading events, basic network elements, such as cellular towers and antennas are prone to failures during adverse weather conditions such as hurricanes. Accordingly, a systematic and computationally feasible approach is required for assessing and improving the reliability of cellular networks during hurricanes. In this paper we develop a new multi-disciplinary approach to efficiently and accurately assess cellular network reliability during hurricanes. We show how the performance of a cellular network during and immediately after future hurricanes can be estimated based on a combination of hurricane wind field models, structural reliability analysis, Monte Carlo simulation, and cellular network models and simulation tools. We then demonstrate the use of this approach for assessing the improvement in system reliability that can be achieved with discrete topological changes in the system. Our results suggest that adding redundancy, particularly through a mesh topology or through the addition of an optical fiber ring around the perimeter of the system can be an effective way to significantly increase the reliability of some cellular systems during hurricanes.

The interaction between radiation and complexes of cis-Pt(II) and Rh(II): studies at the molecular and cellular level

International Nuclear Information System (INIS)

Chibber, R.

1985-01-01

As a first step in gaining an understanding of the relative cellular effects of the transition metal/nitroimidazole complexes the authors have examined the effect of radiation given to cells in the presence of metal complexes not containing a nitroimidazole ligand. The compounds used in the cellular work are a series of Rh(II) carboxylates, cisplatin and JM8 (CBDCA, cis-diammine-1, 1-cyclobutane dicarboxylate platinum (II)). In radiation chemical experiments, Rh(II) acetate and cisplatin were chosen to represent model systems. Results from these radiation chemical and cellular experiments then allow interpretation of the changes in biological response caused by these agents, which are discussed in terms of the mechanism(s) thought to be operative in radiosensitization. (author)

Developing a theoretical predictive model for cellular response to combined actions of low radiation and hyperthermia

International Nuclear Information System (INIS)

Jin Kyu Kim; Petin, V.G.; Mishra, K.P.

2007-01-01

Complete text of publication follows. Background: Organisms in their living environment are not exposed to merely a single stress agent. Several factors such as radiation and heat may simultaneously exert their stressful effect to the organisms. The combined exposure to two stressors can result in an enhanced effect that would be expected from the addition of the separate exposures to individual agents. Objective: This study has been undertaken to develop a theoretical model for assessment of combined effects of low dose radiation and mild heat for predictive cellular response assay. Rationale: Present study was motivated from the belief that synergism may occur in terms of lethal lesions arising from the interaction of non-lethal sub-lesions induced by individual agents. The sub-lesions induced by each agent may be negligible or undetectable. But, there exists a possibility of some cross talk between sublesions produced by radiation and heat. These processes may reflect the real mechanisms for inflicting the lethal damage by otherwise ignorable or undetectable insults to exposed organisms. Results: A theoretically developed mathematical model of the synergy was formulated which was tested for validation on the experimental data. The model predictions fairly closely corresponded with several experimental results. .The significance of synergistic effects for radiation biology has been demonstrated. A number of common peculiarities of synergistic interactions were found to play their roles. A unified biophysical concept for synergistic interaction has been suggested. Conclusions: For a constant dose rate, synergistic interaction between radiation and hyperthermia especially at low intensity is realized only within a certain range of temperature, independently of the target object analyzed. For temperatures below the range, the synergistic effect was not observed and cell killing was mainly determined by the damage induced by ionizing radiation. On the contrary, the

An improved cellular automaton method to model multispecies biofilms.

Science.gov (United States)

Tang, Youneng; Valocchi, Albert J

2013-10-01

Biomass-spreading rules used in previous cellular automaton methods to simulate multispecies biofilm introduced extensive mixing between different biomass species or resulted in spatially discontinuous biomass concentration and distribution; this caused results based on the cellular automaton methods to deviate from experimental results and those from the more computationally intensive continuous method. To overcome the problems, we propose new biomass-spreading rules in this work: Excess biomass spreads by pushing a line of grid cells that are on the shortest path from the source grid cell to the destination grid cell, and the fractions of different biomass species in the grid cells on the path change due to the spreading. To evaluate the new rules, three two-dimensional simulation examples are used to compare the biomass distribution computed using the continuous method and three cellular automaton methods, one based on the new rules and the other two based on rules presented in two previous studies. The relationship between the biomass species is syntrophic in one example and competitive in the other two examples. Simulation results generated using the cellular automaton method based on the new rules agree much better with the continuous method than do results using the other two cellular automaton methods. The new biomass-spreading rules are no more complex to implement than the existing rules. Copyright © 2013 Elsevier Ltd. All rights reserved.

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

Science.gov (United States)

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.

Modeling multimodal human-computer interaction

NARCIS (Netherlands)

Obrenovic, Z.; Starcevic, D.

2004-01-01

Incorporating the well-known Unified Modeling Language into a generic modeling framework makes research on multimodal human-computer interaction accessible to a wide range off software engineers. Multimodal interaction is part of everyday human discourse: We speak, move, gesture, and shift our gaze

Semantic models for adaptive interactive systems

CERN Document Server

Hussein, Tim; Lukosch, Stephan; Ziegler, Jürgen; Calvary, Gaëlle

2013-01-01

Providing insights into methodologies for designing adaptive systems based on semantic data, and introducing semantic models that can be used for building interactive systems, this book showcases many of the applications made possible by the use of semantic models.Ontologies may enhance the functional coverage of an interactive system as well as its visualization and interaction capabilities in various ways. Semantic models can also contribute to bridging gaps; for example, between user models, context-aware interfaces, and model-driven UI generation. There is considerable potential for using

Three-factor models versus time series models: quantifying time-dependencies of interactions between stimuli in cell biology and psychobiology for short longitudinal data.

Science.gov (United States)

Frank, Till D; Kiyatkin, Anatoly; Cheong, Alex; Kholodenko, Boris N

2017-06-01

Signal integration determines cell fate on the cellular level, affects cognitive processes and affective responses on the behavioural level, and is likely to be involved in psychoneurobiological processes underlying mood disorders. Interactions between stimuli may subjected to time effects. Time-dependencies of interactions between stimuli typically lead to complex cell responses and complex responses on the behavioural level. We show that both three-factor models and time series models can be used to uncover such time-dependencies. However, we argue that for short longitudinal data the three factor modelling approach is more suitable. In order to illustrate both approaches, we re-analysed previously published short longitudinal data sets. We found that in human embryonic kidney 293 cells cells the interaction effect in the regulation of extracellular signal-regulated kinase (ERK) 1 signalling activation by insulin and epidermal growth factor is subjected to a time effect and dramatically decays at peak values of ERK activation. In contrast, we found that the interaction effect induced by hypoxia and tumour necrosis factor-alpha for the transcriptional activity of the human cyclo-oxygenase-2 promoter in HEK293 cells is time invariant at least in the first 12-h time window after stimulation. Furthermore, we applied the three-factor model to previously reported animal studies. In these studies, memory storage was found to be subjected to an interaction effect of the beta-adrenoceptor agonist clenbuterol and certain antagonists acting on the alpha-1-adrenoceptor / glucocorticoid-receptor system. Our model-based analysis suggests that only if the antagonist drug is administer in a critical time window, then the interaction effect is relevant. © The authors 2016. Published by Oxford University Press on behalf of the Institute of Mathematics and its Applications. All rights reserved.

Irradiations of human melanoma cells by 14 MeV neutrons; survival curves interpretation; physical simulation of neutrons interactions in the cellular medium

International Nuclear Information System (INIS)

Bodez, Veronique

2000-01-01

14 MeV neutrons are used to irradiate human melanoma cells in order to study survival curves at low dose and low dose rate. We have simulated with the MCNP code, transport of neutrons through the experimental setup to evaluate the contamination of the primary beam by gamma and electrons, for the feasibility of our experiments. We have shown a rapid decrease of the survival curve in the first cGy followed by a plateau for doses up to 30 cGy; after we observed an exponential decrease. This results are observed for the first time, for neutrons at low dose rate (5 cGy/h). In parallel with this experimental point, we have developed a simulation code which permitted the study of neutrons interactions with the cellular medium for individual cells defined as in our experimental conditions. We show that most of the energy is deposited by protons from neutron interactions with external medium, and by heavy ions for interactions into the cell. On the other hand the code gives a good order of magnitude of the dose rate, compared to the experimental values given by silicon diodes. The first results show that we can, using a theory based on induced repair of cells, give an interpretation of the observed experimental plateau. We can give an estimation of the radial distribution of dose for the tracks of charged ions, we show the possibility of calculate interaction cross sections with cellular organelles. Such a work gives interesting perspectives for the future in radiobiology, radiotherapy or radioprotection. (author) [fr

MIiSR: Molecular Interactions in Super-Resolution Imaging Enables the Analysis of Protein Interactions, Dynamics and Formation of Multi-protein Structures.

Directory of Open Access Journals (Sweden)

Fabiana A Caetano

2015-12-01

Full Text Available Our current understanding of the molecular mechanisms which regulate cellular processes such as vesicular trafficking has been enabled by conventional biochemical and microscopy techniques. However, these methods often obscure the heterogeneity of the cellular environment, thus precluding a quantitative assessment of the molecular interactions regulating these processes. Herein, we present Molecular Interactions in Super Resolution (MIiSR software which provides quantitative analysis tools for use with super-resolution images. MIiSR combines multiple tools for analyzing intermolecular interactions, molecular clustering and image segmentation. These tools enable quantification, in the native environment of the cell, of molecular interactions and the formation of higher-order molecular complexes. The capabilities and limitations of these analytical tools are demonstrated using both modeled data and examples derived from the vesicular trafficking system, thereby providing an established and validated experimental workflow capable of quantitatively assessing molecular interactions and molecular complex formation within the heterogeneous environment of the cell.

Statistical mechanics of cellular automata

International Nuclear Information System (INIS)

Wolfram, S.

1983-01-01

Cellular automata are used as simple mathematical models to investigate self-organization in statistical mechanics. A detailed analysis is given of ''elementary'' cellular automata consisting of a sequence of sites with values 0 or 1 on a line, with each site evolving deterministically in discrete time steps according to p definite rules involving the values of its nearest neighbors. With simple initial configurations, the cellular automata either tend to homogeneous states, or generate self-similar patterns with fractal dimensions approx. =1.59 or approx. =1.69. With ''random'' initial configurations, the irreversible character of the cellular automaton evolution leads to several self-organization phenomena. Statistical properties of the structures generated are found to lie in two universality classes, independent of the details of the initial state or the cellular automaton rules. More complicated cellular automata are briefly considered, and connections with dynamical systems theory and the formal theory of computation are discussed

Morphological analysis of the cellular interactions between the eugregarine Gregarina garnhami (Apicomplexa) and the epithelium of its host, the desert locust Schistocerca gregaria

Czech Academy of Sciences Publication Activity Database

Valigurová, A.; Koudela, Břetislav

2008-01-01

Roč. 44, č. 3 (2008), s. 197-207 ISSN 0932-4739 R&D Projects: GA ČR GD524/03/H133 Institutional research plan: CEZ:AV0Z60220518 Keywords : Gragarina garnhami * Schistocerca gregaria * epimerite * detachment of trophozoite * cellular interactions Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 1.000, year: 2008

Revealing the sequence and resulting cellular morphology of receptor-ligand interactions during Plasmodium falciparum invasion of erythrocytes.

Directory of Open Access Journals (Sweden)

Greta E Weiss

2015-02-01

Full Text Available During blood stage Plasmodium falciparum infection, merozoites invade uninfected erythrocytes via a complex, multistep process involving a series of distinct receptor-ligand binding events. Understanding each element in this process increases the potential to block the parasite's life cycle via drugs or vaccines. To investigate specific receptor-ligand interactions, they were systematically blocked using a combination of genetic deletion, enzymatic receptor cleavage and inhibition of binding via antibodies, peptides and small molecules, and the resulting temporal changes in invasion and morphological effects on erythrocytes were filmed using live cell imaging. Analysis of the videos have shown receptor-ligand interactions occur in the following sequence with the following cellular morphologies; 1 an early heparin-blockable interaction which weakly deforms the erythrocyte, 2 EBA and PfRh ligands which strongly deform the erythrocyte, a process dependant on the merozoite's actin-myosin motor, 3 a PfRh5-basigin binding step which results in a pore or opening between parasite and host through which it appears small molecules and possibly invasion components can flow and 4 an AMA1-RON2 interaction that mediates tight junction formation, which acts as an anchor point for internalization. In addition to enhancing general knowledge of apicomplexan biology, this work provides a rational basis to combine sequentially acting merozoite vaccine candidates in a single multi-receptor-blocking vaccine.

Interaction Modeling at PROS Research Center

OpenAIRE

Panach , José ,; Aquino , Nathalie; PASTOR , Oscar

2011-01-01

Part 1: Long and Short Papers; International audience; This paper describes how the PROS Research Center deals with interaction in the context of a model-driven approach for the development of information systems. Interaction is specified in a conceptual model together with the structure and behavior of the system. Major achievements and current research challenges of PROS in the field of interaction modeling are presented.

Cellular Automata Simulation for Wealth Distribution

Science.gov (United States)

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.

Probabilistic cellular automata.

Science.gov (United States)

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.

Cellular modelling of secondary radial growth in conifer trees: application to Pinus radiata (D. Don).

Science.gov (United States)

Forest, Loïc; Demongeot, Jacques; Demongeota, Jacques

2006-05-01

The radial growth of conifer trees proceeds from the dynamics of a merismatic tissue called vascular cambium or cambium. Cambium is a thin layer of active proliferating cells. The purpose of this paper was to model the main characteristics of cambial activity and its consecutive radial growth. Cell growth is under the control of the auxin hormone indole-3-acetic. The model is composed of a discrete part, which accounts for cellular proliferation, and a continuous part involving the transport of auxin. Cambium is modeled in a two-dimensional cross-section by a cellular automaton that describes the set of all its constitutive cells. Proliferation is defined as growth and division of cambial cells under neighbouring constraints, which can eliminate some cells from the cambium. The cell-growth rate is determined from auxin concentration, calculated with the continuous model. We studied the integration of each elementary cambial cell activity into the global coherent movement of macroscopic morphogenesis. Cases of normal and abnormal growth of Pinus radiata (D. Don) are modelled. Abnormal growth includes deformed trees where gravity influences auxin transport, producing heterogeneous radial growth. Cross-sectional microscopic views are also provided to validate the model's hypothesis and results.

Vector-Interaction-Enhanced Bag Model

Science.gov (United States)

Cierniak, Mateusz; Klähn, Thomas; Fischer, Tobias; Bastian, Niels-Uwe

2018-02-01

A commonly applied quark matter model in astrophysics is the thermodynamic bag model (tdBAG). The original MIT bag model approximates the effect of quark confinement, but does not explicitly account for the breaking of chiral symmetry, an important property of Quantum Chromodynamics (QCD). It further ignores vector repulsion. The vector-interaction-enhanced bag model (vBag) improves the tdBAG approach by accounting for both dynamical chiral symmetry breaking and repulsive vector interactions. The latter is of particular importance to studies of dense matter in beta-equilibriumto explain the two solar mass maximum mass constraint for neutron stars. The model is motivated by analyses of QCD based Dyson-Schwinger equations (DSE), assuming a simple quark-quark contact interaction. Here, we focus on the study of hybrid neutron star properties resulting from the application of vBag and will discuss possible extensions.

A material optimization model to approximate energy bounds for cellular materials under multiload conditions

DEFF Research Database (Denmark)

Guedes, J.M.; Rodrigues, H.C.; Bendsøe, Martin P.

2003-01-01

This paper describes a computational model, based on inverse homogenization and topology design, for approximating energy bounds for two-phase composites under multiple load cases. The approach allows for the identification of possible single-scale cellular materials that give rise to the optimal...

Idealized Mesoscale Model Simulations of Open Cellular Convection Over the Sea

DEFF Research Database (Denmark)

Vincent, Claire Louise; Hahmann, Andrea N.; Kelly, Mark C.

2012-01-01

The atmospheric conditions during an observed case of open cellular convection over the North Sea were simulated using the Weather Research and Forecasting (WRF) numerical model. Wind, temperature and water vapour mixing ratio profiles from the WRF simulation were used to initialize an idealized...... version of the model, which excluded the effects of topography, surface inhomogeneities and large-scale weather forcing. Cells with an average diameter of 17.4 km developed. Simulations both with and without a capping inversion were made, and the cell-scale kinetic energy budget was calculated for each...... case. By considering all sources of explicit diffusion in the model, the budgets were balanced. In comparison with previous work based on observational studies, the use of three-dimensional, gridded model data afforded the possibility of calculating all terms in the budgets, which showed...

An examination of adaptive cellular protective mechanisms using a multi-stage carcinogenesis model

International Nuclear Information System (INIS)

Schollnberger, H.; Stewart, R. D.; Mitchel, R. E. J.; Hofmann, W.

2004-01-01

A multi-stage cancer model that describes the putative rate-limiting steps in carcinogenesis was developed and used to investigate the potential impact on lung cancer incidence of the hormesis mechanisms suggested by Feinendegen and Pollycove. In this deterministic cancer model, radiation and endogenous processes damage the DNA of target cells in the lung. Some fraction of the misrepaired our unrepaired DNA damage induces genomic instability and, ultimately, leads to the accumulation of malignant cells. The model accounts for cell birth and death processes. Ita also includes a rate of malignant transformation and a lag period for tumour formation. Cellular defence mechanisms are incorporated into the model by postulating dose and dose rate dependent radical scavenging. The accuracy of DNA damage repair also depends on dose and dose rate. Sensitivity studies were conducted to identify critical model inputs and to help define the shapes of the cumulative lung cancer incidence curves that may arise when dose and dose rate dependent cellular defence mechanisms are incorporated into a multi-stage cancer model. For lung cancer, both linear no-threshold (LNT) and non-LNT shaped responses can be obtained. The reported studied clearly show that it is critical to know whether or not and to what extent multiply damaged DNA sites are formed by endogenous processes. Model inputs that give rise to U-shaped responses are consistent with an effective cumulative lung cancer incidence threshold that may be as high as 300 mGy (4 mGy per year for 75 years). (Author) 11 refs

Compound C prevents Hypoxia-Inducible Factor-1α protein stabilization by regulating the cellular oxygen availability via interaction with Mitochondrial Complex I

Directory of Open Access Journals (Sweden)

Hagen Thilo

2011-04-01

Full Text Available Abstract The transcription factor Hypoxia-Inducible Factor-1α is a master regulator of the cellular response to low oxygen concentration. Compound C, an inhibitor of AMP-activated kinase, has been reported to inhibit hypoxia dependent Hypoxia-Inducible Factor-1α activation via a mechanism that is independent of AMP-activated kinase but dependent on its interaction with the mitochondrial electron transport chain. The objective of this study is to characterize the interaction of Compound C with the mitochondrial electron transport chain and to determine the mechanism through which the drug influences the stability of the Hypoxia-Inducible Factor-1α protein. We found that Compound C functions as an inhibitor of complex I of the mitochondrial electron transport chain as demonstrated by its effect on mitochondrial respiration. It also prevents hypoxia-induced Hypoxia-Inducible Factor-1α stabilization in a dose dependent manner. In addition, Compound C does not have significant effects on reactive oxygen species production from complex I via both forward and reverse electron flux. This study provides evidence that similar to other mitochondrial electron transport chain inhibitors, Compound C regulates Hypoxia-Inducible Factor-1α stability by controlling the cellular oxygen concentration.

Epstein–Barr virus glycoprotein gM can interact with the cellular protein p32 and knockdown of p32 impairs virus

International Nuclear Information System (INIS)

Changotra, Harish; Turk, Susan M.; Artigues, Antonio; Thakur, Nagendra; Gore, Mindy; Muggeridge, Martin I.; Hutt-Fletcher, Lindsey M.

2016-01-01

The Epstein–Barr virus glycoprotein complex gMgN has been implicated in assembly and release of fully enveloped virus, although the precise role that it plays has not been elucidated. We report here that the long predicted cytoplasmic tail of gM is not required for complex formation and that it interacts with the cellular protein p32, which has been reported to be involved in nuclear egress of human cytomegalovirus and herpes simplex virus. Although redistribution of p32 and colocalization with gM was not observed in virus infected cells, knockdown of p32 expression by siRNA or lentivirus-delivered shRNA recapitulated the phenotype of a virus lacking expression of gNgM. A proportion of virus released from cells sedimented with characteristics of virus lacking an intact envelope and there was an increase in virus trapped in nuclear condensed chromatin. The observations suggest the possibility that p32 may also be involved in nuclear egress of Epstein–Barr virus. - Highlights: • The predicted cytoplasmic tail of gM is not required to complex with gN. • Cellular p32 can interact with the predicted cytoplasmic tail of EBV gM. • Knockdown of p32 recapitulates the phenotype of virus lacking the gNgM complex.

Epstein–Barr virus glycoprotein gM can interact with the cellular protein p32 and knockdown of p32 impairs virus

Energy Technology Data Exchange (ETDEWEB)

Changotra, Harish; Turk, Susan M. [Department of Microbiology and Immunology, Center for Molecular and Tumor Virology and Feist-Weiller Cancer Center, Louisiana State University Health Sciences Center, Shreveport, LA (United States); Artigues, Antonio [Department of Biochemistry, University of Kansas Medical Center, Kansas City, KS (United States); Thakur, Nagendra; Gore, Mindy; Muggeridge, Martin I. [Department of Microbiology and Immunology, Center for Molecular and Tumor Virology and Feist-Weiller Cancer Center, Louisiana State University Health Sciences Center, Shreveport, LA (United States); Hutt-Fletcher, Lindsey M., E-mail: lhuttf@lsuhsc.edu [Department of Microbiology and Immunology, Center for Molecular and Tumor Virology and Feist-Weiller Cancer Center, Louisiana State University Health Sciences Center, Shreveport, LA (United States)

2016-02-15

The Epstein–Barr virus glycoprotein complex gMgN has been implicated in assembly and release of fully enveloped virus, although the precise role that it plays has not been elucidated. We report here that the long predicted cytoplasmic tail of gM is not required for complex formation and that it interacts with the cellular protein p32, which has been reported to be involved in nuclear egress of human cytomegalovirus and herpes simplex virus. Although redistribution of p32 and colocalization with gM was not observed in virus infected cells, knockdown of p32 expression by siRNA or lentivirus-delivered shRNA recapitulated the phenotype of a virus lacking expression of gNgM. A proportion of virus released from cells sedimented with characteristics of virus lacking an intact envelope and there was an increase in virus trapped in nuclear condensed chromatin. The observations suggest the possibility that p32 may also be involved in nuclear egress of Epstein–Barr virus. - Highlights: • The predicted cytoplasmic tail of gM is not required to complex with gN. • Cellular p32 can interact with the predicted cytoplasmic tail of EBV gM. • Knockdown of p32 recapitulates the phenotype of virus lacking the gNgM complex.

An Interactive Tool for Animating Biology, and Its Use in Spatial and Temporal Modeling of a Cancerous Tumor and Its Microenvironment.

Directory of Open Access Journals (Sweden)

Naamah Bloch

Full Text Available The ability to visualize the ongoing events of a computational model of biology is critical, both in order to see the dynamics of the biological system in action and to enable interaction with the model from which one can observe the resulting behavior. To this end, we have built a new interactive animation tool, SimuLife, for visualizing reactive models of cellular biology. SimuLife is web-based, and is freely accessible at http://simulife.weizmann.ac.il/. We have used SimuLife to animate a model that describes the development of a cancerous tumor, based on the individual components of the system and its environment. This has helped in understanding the dynamics of the tumor and its surrounding blood vessels, and in verifying the behavior, fine-tuning the model accordingly, and learning in which way different factors affect the tumor.

On Modeling Large-Scale Multi-Agent Systems with Parallel, Sequential and Genuinely Asynchronous Cellular Automata

International Nuclear Information System (INIS)

Tosic, P.T.

2011-01-01

We study certain types of Cellular Automata (CA) viewed as an abstraction of large-scale Multi-Agent Systems (MAS). We argue that the classical CA model needs to be modified in several important respects, in order to become a relevant and sufficiently general model for the large-scale MAS, and so that thus generalized model can capture many important MAS properties at the level of agent ensembles and their long-term collective behavior patterns. We specifically focus on the issue of inter-agent communication in CA, and propose sequential cellular automata (SCA) as the first step, and genuinely Asynchronous Cellular Automata (ACA) as the ultimate deterministic CA-based abstract models for large-scale MAS made of simple reactive agents. We first formulate deterministic and nondeterministic versions of sequential CA, and then summarize some interesting configuration space properties (i.e., possible behaviors) of a restricted class of sequential CA. In particular, we compare and contrast those properties of sequential CA with the corresponding properties of the classical (that is, parallel and perfectly synchronous) CA with the same restricted class of update rules. We analytically demonstrate failure of the studied sequential CA models to simulate all possible behaviors of perfectly synchronous parallel CA, even for a very restricted class of non-linear totalistic node update rules. The lesson learned is that the interleaving semantics of concurrency, when applied to sequential CA, is not refined enough to adequately capture the perfect synchrony of parallel CA updates. Last but not least, we outline what would be an appropriate CA-like abstraction for large-scale distributed computing insofar as the inter-agent communication model is concerned, and in that context we propose genuinely asynchronous CA. (author)

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

Science.gov (United States)

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).

A Computational Model of Cellular Engraftment on Lung Scaffolds.

Science.gov (United States)

Pothen, Joshua J; Rajendran, Vignesh; Wagner, Darcy; Weiss, Daniel J; Smith, Bradford J; Ma, Baoshun; Bates, Jason H T

2016-01-01

The possibility that stem cells might be used to regenerate tissue is now being investigated for a variety of organs, but these investigations are still essentially exploratory and have few predictive tools available to guide experimentation. We propose, in this study, that the field of lung tissue regeneration might be better served by predictive tools that treat stem cells as agents that obey certain rules of behavior governed by both their phenotype and their environment. Sufficient knowledge of these rules of behavior would then, in principle, allow lung tissue development to be simulated computationally. Toward this end, we developed a simple agent-based computational model to simulate geographic patterns of cells seeded onto a lung scaffold. Comparison of the simulated patterns to those observed experimentally supports the hypothesis that mesenchymal stem cells proliferate preferentially toward the scaffold boundary, whereas alveolar epithelial cells do not. This demonstrates that a computational model of this type has the potential to assist in the discovery of rules of cellular behavior.

Targeting Virus-host Interactions of HIV Replication.

Science.gov (United States)

Weydert, Caroline; De Rijck, Jan; Christ, Frauke; Debyser, Zeger

2016-01-01

Cellular proteins that are hijacked by HIV in order to complete its replication cycle, form attractive new targets for antiretroviral therapy. In particular, the protein-protein interactions between these cellular proteins (cofactors) and viral proteins are of great interest to develop new therapies. Research efforts have led to the validation of different cofactors and some successes in therapeutic applications. Maraviroc, the first cofactor inhibitor approved for human medicinal use, provided a proof of concept. Furthermore, compounds developed as Integrase-LEDGF/p75 interaction inhibitors (LEDGINs) have advanced to early clinical trials. Other compounds targeting cofactors and cofactor-viral protein interactions are currently under development. Likewise, interactions between cellular restriction factors and their counteracting HIV protein might serve as interesting targets in order to impair HIV replication. In this respect, compounds targeting the Vif-APOBEC3G interaction have been described. In this review, we focus on compounds targeting the Integrase- LEDGF/p75 interaction, the Tat-P-TEFb interaction and the Vif-APOBEC3G interaction. Additionally we give an overview of currently discovered compounds presumably targeting cellular cofactor-HIV protein interactions.

Super-Resolution Microscopy: Shedding Light on the Cellular Plasma Membrane.

Science.gov (United States)

Stone, Matthew B; Shelby, Sarah A; Veatch, Sarah L

2017-06-14

Lipids and the membranes they form are fundamental building blocks of cellular life, and their geometry and chemical properties distinguish membranes from other cellular environments. Collective processes occurring within membranes strongly impact cellular behavior and biochemistry, and understanding these processes presents unique challenges due to the often complex and myriad interactions between membrane components. Super-resolution microscopy offers a significant gain in resolution over traditional optical microscopy, enabling the localization of individual molecules even in densely labeled samples and in cellular and tissue environments. These microscopy techniques have been used to examine the organization and dynamics of plasma membrane components, providing insight into the fundamental interactions that determine membrane functions. Here, we broadly introduce the structure and organization of the mammalian plasma membrane and review recent applications of super-resolution microscopy to the study of membranes. We then highlight some inherent challenges faced when using super-resolution microscopy to study membranes, and we discuss recent technical advancements that promise further improvements to super-resolution microscopy and its application to the plasma membrane.

Investigation of phase diagrams for cylindrical Ising nanotube using cellular automata

Science.gov (United States)

Astaraki, M.; Ghaemi, M.; Afzali, K.

2018-05-01

Recent developments in the field of applied nanoscience and nanotechnology have heightened the need for categorizing various characteristics of nanostructures. In this regard, this paper establishes a novel method to investigate magnetic properties (phase diagram and spontaneous magnetization) of a cylindrical Ising nanotube. Using a two-layer Ising model and the core-shell concept, the interactions within nanotube has been modelled. In the model, both ferromagnetic and antiferromagnetic cases have been considered. Furthermore, the effect of nanotube's length on the critical temperature is investigated. The model has been simulated using cellular automata approach and phase diagrams were constructed for different values of inter- and intra-layer couplings. For the antiferromagnetic case, the possibility of existence of compensation point is observed.

Modeling and Experimental Study of Soft Error Propagation Based on Cellular Automaton

OpenAIRE

He, Wei; Wang, Yueke; Xing, Kefei; Yang, Jianwei

2016-01-01

Aiming to estimate SEE soft error performance of complex electronic systems, a soft error propagation model based on cellular automaton is proposed and an estimation methodology based on circuit partitioning and error propagation is presented. Simulations indicate that different fault grade jamming and different coupling factors between cells are the main parameters influencing the vulnerability of the system. Accelerated radiation experiments have been developed to determine the main paramet...

Cellular Automaton Modeling of Dendritic Growth Using a Multi-grid Method

International Nuclear Information System (INIS)

Natsume, Y; Ohsasa, K

2015-01-01

A two-dimensional cellular automaton model with a multi-grid method was developed to simulate dendritic growth. In the present model, we used a triple-grid system for temperature, solute concentration and solid fraction fields as a new approach of the multi-grid method. In order to evaluate the validity of the present model, we carried out simulations of single dendritic growth, secondary dendrite arm growth, multi-columnar dendritic growth and multi-equiaxed dendritic growth. From the results of the grid dependency from the simulation of single dendritic growth, we confirmed that the larger grid can be used in the simulation and that the computational time can be reduced dramatically. In the simulation of secondary dendrite arm growth, the results from the present model were in good agreement with the experimental data and the simulated results from a phase-field model. Thus, the present model can quantitatively simulate dendritic growth. From the simulated results of multi-columnar and multi-equiaxed dendrites, we confirmed that the present model can perform simulations under practical solidification conditions. (paper)

A new stochastic cellular automaton model on traffic flow and its jamming phase transition

International Nuclear Information System (INIS)

Sakai, Satoshi; Nishinari, Katsuhiro; Iida, Shinji

2006-01-01

A general stochastic traffic cellular automaton (CA) model, which includes the slow-to-start effect and driver's perspective, is proposed in this paper. It is shown that this model includes well-known traffic CA models such as the Nagel-Schreckenberg model, the quick-start model and the slow-to-start model as specific cases. Fundamental diagrams of this new model clearly show metastable states around the critical density even when the stochastic effect is present. We also obtain analytic expressions of the phase transition curve in phase diagrams by using approximate flow-density relations at boundaries. These phase transition curves are in excellent agreement with numerical results

Drosophila: An Emergent Model for Delineating Interactions between the Circadian Clock and Drugs of Abuse

Directory of Open Access Journals (Sweden)

Aliza K. De Nobrega

2017-01-01

Full Text Available Endogenous circadian oscillators orchestrate rhythms at the cellular, physiological, and behavioral levels across species to coordinate activity, for example, sleep/wake cycles, metabolism, and learning and memory, with predictable environmental cycles. The 21st century has seen a dramatic rise in the incidence of circadian and sleep disorders with globalization, technological advances, and the use of personal electronics. The circadian clock modulates alcohol- and drug-induced behaviors with circadian misalignment contributing to increased substance use and abuse. Invertebrate models, such as Drosophila melanogaster, have proven invaluable for the identification of genetic and molecular mechanisms underlying highly conserved processes including the circadian clock, drug tolerance, and reward systems. In this review, we highlight the contributions of Drosophila as a model system for understanding the bidirectional interactions between the circadian system and the drugs of abuse, alcohol and cocaine, and illustrate the highly conserved nature of these interactions between Drosophila and mammalian systems. Research in Drosophila provides mechanistic insights into the corresponding behaviors in higher organisms and can be used as a guide for targeted inquiries in mammals.

Using Interaction Scenarios to Model Information Systems

DEFF Research Database (Denmark)

Bækgaard, Lars; Bøgh Andersen, Peter

The purpose of this paper is to define and discuss a set of interaction primitives that can be used to model the dynamics of socio-technical activity systems, including information systems, in a way that emphasizes structural aspects of the interaction that occurs in such systems. The primitives...... a number of case studies that indicate that interaction primitives can be useful modeling tools for supplementing conventional flow-oriented modeling of business processes....... are based on a unifying, conceptual definition of the disparate interaction types - a robust model of the types. The primitives can be combined and may thus represent mediated interaction. We present a set of visualizations that can be used to define multiple related interactions and we present and discuss...

Oxidative Damage and Cellular Defense Mechanisms in Sea Urchin Models of Aging

Science.gov (United States)

Du, Colin; Anderson, Arielle; Lortie, Mae; Parsons, Rachel; Bodnar, Andrea

2013-01-01

The free radical or oxidative stress theory of aging proposes that the accumulation of oxidative cellular damage is a major contributor to the aging process and a key determinant of species longevity. This study investigates the oxidative stress theory in a novel model for aging research, the sea urchin. Sea urchins present a unique model for the study of aging due to the existence of species with tremendously different natural life spans including some species with extraordinary longevity and negligible senescence. Cellular oxidative damage, antioxidant capacity and proteasome enzyme activities were measured in the tissues of three sea urchin species: short-lived Lytechinus variegatus, long-lived Strongylocentrotus franciscanus and Strongylocentrotus purpuratus which has an intermediate lifespan. Levels of protein carbonyls and 4-hydroxynonenal (HNE) measured in tissues (muscle, nerve, esophagus, gonad, coelomocytes, ampullae) and 8-hydroxy-2’-deoxyguanosine (8-OHdG) measured in cell-free coelomic fluid showed no general increase with age. The fluorescent age-pigment lipofuscin measured in muscle, nerve and esophagus, increased with age however it appeared to be predominantly extracellular. Antioxidant mechanisms (total antioxidant capacity, superoxide dismutase) and proteasome enzyme activities were maintained with age. In some instances, levels of oxidative damage were lower and antioxidant activity higher in cells or tissues of the long-lived species compared to the short-lived species, however further studies are required to determine the relationship between oxidative damage and longevity in these animals. Consistent with the predictions of the oxidative stress theory of aging, the results suggest that negligible senescence is accompanied by a lack of accumulation of cellular oxidative damage with age and maintenance of antioxidant capacity and proteasome enzyme activities may be important mechanisms to mitigate damage. PMID:23707327

Cellular automaton model of mass transport with chemical reactions

International Nuclear Information System (INIS)

Karapiperis, T.; Blankleider, B.

1993-10-01

The transport and chemical reactions of solutes are modelled as a cellular automaton in which molecules of different species perform a random walk on a regular lattice and react according to a local probabilistic rule. The model describes advection and diffusion in a simple way, and as no restriction is placed on the number of particles at a lattice site, it is also able to describe a wide variety of chemical reactions. Assuming molecular chaos and a smooth density function, we obtain the standard reaction-transport equations in the continuum limit. Simulations on one-and two-dimensional lattices show that the discrete model can be used to approximate the solutions of the continuum equations. We discuss discrepancies which arise from correlations between molecules and how these discrepancies disappear as the continuum limit is approached. Of particular interest are simulations displaying long-time behaviour which depends on long-wavelength statistical fluctuations not accounted for by the standard equations. The model is applied to the reactions a + b ↔ c and a + b → c with homogeneous and inhomogeneous initial conditions as well as to systems subject to autocatalytic reactions and displaying spontaneous formation of spatial concentration patterns. (author) 9 figs., 34 refs

Mathematical Modeling of Tuberculosis Bacillary Counts and Cellular Populations in the Organs of Infected Mice

Science.gov (United States)

Bru, Antonio; Cardona, Pere-Joan

2010-01-01

Background Mycobacterium tuberculosis is a particularly aggressive microorganism and the host's defense is based on the induction of cellular immunity, in which the creation of a granulomatous structure has an important role. Methodology We present here a new 2D cellular automata model based on the concept of a multifunctional process that includes key factors such as the chemokine attraction of the cells; the role of innate immunity triggered by natural killers; the presence of neutrophils; apoptosis and necrosis of infected macrophages; the removal of dead cells by macrophages, which induces the production of foamy macrophages (FMs); the life cycle of the bacilli as a determinant for the evolution of infected macrophages; and the immune response. Results The results obtained after the inclusion of two degrees of tolerance to the inflammatory response triggered by the infection shows that the model can cover a wide spectrum, ranging from highly-tolerant (i.e. mice) to poorly-tolerant hosts (i.e. mini-pigs or humans). Conclusions This model suggest that stopping bacillary growth at the onset of the infection might be difficult and the important role played by FMs in bacillary drainage in poorly-tolerant hosts together with apoptosis and innate lymphocytes. It also shows the poor ability of the cellular immunity to control the infection, provides a clear protective character to the granuloma, due its ability to attract a sufficient number of cells, and explains why an already infected host can be constantly reinfected. PMID:20886087

In silico modeling of human α2C-adrenoreceptor interaction with filamin-2.

Directory of Open Access Journals (Sweden)

Marcin Pawlowski

Full Text Available Vascular smooth muscle α2C-adrenoceptors (α2C-ARs mediate vasoconstriction of small blood vessels, especially arterioles. Studies of endogenous receptors in human arteriolar smooth muscle cells (referred to as microVSM and transiently transfected receptors in heterologous HEK293 cells show that the α2C-ARs are perinuclear receptors that translocate to the cell surface under cellular stress and elicit a biological response. Recent studies in microVSM unraveled a crucial role of Rap1A-Rho-ROCK-F-actin pathways in receptor translocation, and identified protein-protein interaction of α2C-ARs with the actin binding protein filamin-2 as an essential step in the process. To better understand the molecular nature and specificity of this interaction, in this study, we constructed comparative models of human α2C-AR and human filamin-2 proteins. Finally, we performed in silico protein-protein docking to provide a structural platform for the investigation of human α2C-AR and filamin-2 interactions. We found that electrostatic interactions seem to play a key role in this complex formation which manifests in interactions between the C-terminal arginines of α2C-ARs (particularly R454 and R456 and negatively charged residues from filamin-2 region between residues 1979 and 2206. Phylogenetic and sequence analysis showed that these interactions have evolved in warm-blooded animals.

Identification of novel putative-binding proteins for cellular prion protein and a specific interaction with the STIP1 homology and U-Box-containing protein 1

Science.gov (United States)

Gimenez, Ana Paula Lappas; Richter, Larissa Morato Luciani; Atherino, Mariana Campos; Beirão, Breno Castello Branco; Fávaro, Celso; Costa, Michele Dietrich Moura; Zanata, Silvio Marques; Malnic, Bettina; Mercadante, Adriana Frohlich

2015-01-01

ABSTRACT Prion diseases involve the conversion of the endogenous cellular prion protein, PrPC, into a misfolded infectious isoform, PrPSc. Several functions have been attributed to PrPC, and its role has also been investigated in the olfactory system. PrPC is expressed in both the olfactory bulb (OB) and olfactory epithelium (OE) and the nasal cavity is an important route of transmission of diseases caused by prions. Moreover, Prnp−/− mice showed impaired behavior in olfactory tests. Given the high PrPC expression in OE and its putative role in olfaction, we screened a mouse OE cDNA library to identify novel PrPC-binding partners. Ten different putative PrPC ligands were identified, which were involved in functions such as cellular proliferation and apoptosis, cytoskeleton and vesicle transport, ubiquitination of proteins, stress response, and other physiological processes. In vitro binding assays confirmed the interaction of PrPC with STIP1 homology and U-Box containing protein 1 (Stub1) and are reported here for the first time. Stub1 is a co-chaperone with ubiquitin E3-ligase activity, which is associated with neurodegenerative diseases characterized by protein misfolding and aggregation. Physiological and pathological implications of PrPC-Stub1 interaction are under investigation. The PrPC-binding proteins identified here are not exclusive to the OE, suggesting that these interactions may occur in other tissues and play general biological roles. These data corroborate the proposal that PrPC is part of a multiprotein complex that modulates several cellular functions and provide a platform for further studies on the physiological and pathological roles of prion protein. PMID:26237451

Developing multi-cellular tumor spheroid model (MCTS) in the chitosan/collagen/alginate (CCA) fibrous scaffold for anticancer drug screening

Energy Technology Data Exchange (ETDEWEB)

Wang, Jian-Zheng, E-mail: wppzheng@126.com [Laboratory of Biomedical Material Engineering, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 457 Zhongshan Road, Dalian 116023 (China); Affiliated General Hospital, Tianguan Group Co., Ltd, Nanyang 473000 (China); Testing Center of Henan Tianguan Group Co., Ltd, Nanyang 473000 (China); Zhu, Yu-Xia [Laboratory of Biomedical Material Engineering, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 457 Zhongshan Road, Dalian 116023 (China); Affiliated General Hospital, Tianguan Group Co., Ltd, Nanyang 473000 (China); Testing Center of Henan Tianguan Group Co., Ltd, Nanyang 473000 (China); Ma, Hui-Chao; Chen, Si-Nan; Chao, Ji-Ye; Ruan, Wen-Ding; Wang, Duo; Du, Feng-guang [Affiliated General Hospital, Tianguan Group Co., Ltd, Nanyang 473000 (China); Testing Center of Henan Tianguan Group Co., Ltd, Nanyang 473000 (China); Meng, Yue-Zhong [State Key Laboratory of Optoelectronic Materials and Technologies, Sun Yat-sen University, Guangzhou 510275 (China)

2016-05-01

In this work, a 3D MCTS-CCA system was constructed by culturing multi-cellular tumor spheroid (MCTS) in the chitosan/collagen/alginate (CCA) fibrous scaffold for anticancer drug screening. The CCA scaffolds were fabricated by spray-spinning. The interactions between the components of the spray-spun fibers were evidenced by methods of Coomassie Blue stain, X-ray diffraction (XRD) and Fourier transform-infrared spectroscopy (FTIR). Co-culture indicated that MCF-7 cells showed a spatial growth pattern of multi-cellular tumor spheroid (MCTS) in the CCA fibrous scaffold with increased proliferation rate and drug-resistance to MMC, ADM and 5-Aza comparing with the 2D culture cells. Significant increases of total viable cells were found in 3D MCTS groups after drug administration by method of apoptotic analysis. Glucose–lactate analysis indicated that the metabolism of MCTS in CCA scaffold was closer to the tumor issue in vivo than the monolayer cells. In addition, MCTS showed the characteristic of epithelial mesenchymal transition (EMT) which is subverted by carcinoma cells to facilitate metastatic spread. These results demonstrated that MCTS in CCA scaffold possessed a more conservative phenotype of tumor than monolayer cells, and anticancer drug screening in 3D MCTS-CCA system might be superior to the 2D culture system. - Highlights: • Chitosan/collagen/alginate (CCA) scaffolds were fabricated by spray-spinning. • MCF-7 cells presented a multi-cellular tumor spheroid model (MCTS) in CCA scaffold. • MCTS in CCA possessed a more conservative phenotype of tumor than monolayer cells. • Anticancer drug screening in MCTS-CCA system is superior to 2D culture system.

Developing multi-cellular tumor spheroid model (MCTS) in the chitosan/collagen/alginate (CCA) fibrous scaffold for anticancer drug screening

International Nuclear Information System (INIS)

Wang, Jian-Zheng; Zhu, Yu-Xia; Ma, Hui-Chao; Chen, Si-Nan; Chao, Ji-Ye; Ruan, Wen-Ding; Wang, Duo; Du, Feng-guang; Meng, Yue-Zhong

2016-01-01

In this work, a 3D MCTS-CCA system was constructed by culturing multi-cellular tumor spheroid (MCTS) in the chitosan/collagen/alginate (CCA) fibrous scaffold for anticancer drug screening. The CCA scaffolds were fabricated by spray-spinning. The interactions between the components of the spray-spun fibers were evidenced by methods of Coomassie Blue stain, X-ray diffraction (XRD) and Fourier transform-infrared spectroscopy (FTIR). Co-culture indicated that MCF-7 cells showed a spatial growth pattern of multi-cellular tumor spheroid (MCTS) in the CCA fibrous scaffold with increased proliferation rate and drug-resistance to MMC, ADM and 5-Aza comparing with the 2D culture cells. Significant increases of total viable cells were found in 3D MCTS groups after drug administration by method of apoptotic analysis. Glucose–lactate analysis indicated that the metabolism of MCTS in CCA scaffold was closer to the tumor issue in vivo than the monolayer cells. In addition, MCTS showed the characteristic of epithelial mesenchymal transition (EMT) which is subverted by carcinoma cells to facilitate metastatic spread. These results demonstrated that MCTS in CCA scaffold possessed a more conservative phenotype of tumor than monolayer cells, and anticancer drug screening in 3D MCTS-CCA system might be superior to the 2D culture system. - Highlights: • Chitosan/collagen/alginate (CCA) scaffolds were fabricated by spray-spinning. • MCF-7 cells presented a multi-cellular tumor spheroid model (MCTS) in CCA scaffold. • MCTS in CCA possessed a more conservative phenotype of tumor than monolayer cells. • Anticancer drug screening in MCTS-CCA system is superior to 2D culture system.

Modelling Interactions between Land Use, Climate, and Hydrology along with Stakeholders’ Negotiation for Water Resources Management

Directory of Open Access Journals (Sweden)

Babak Farjad

2017-11-01

Full Text Available This paper describes the main functionalities of an integrated framework to model the interactions between land use, climate, and hydrology along with stakeholders’ negotiation. Its novelty lies in the combination of individual-based and spatially distributed models within the Socio-Hydrology paradigm to capture the complexity and uncertainty inherent to these systems. It encompasses a land-use/land-cover cellular automata model, an agent-based model used for automated stakeholders’ negotiation, and the hydrological MIKE SHE/MIKE 11 model, which are linked and can be accessed through a web-based interface. It enables users to run simulations to explore a wide range of scenarios related to land development and water resource management while considering the reciprocal influence of human and natural systems. This framework was developed with the involvement of key stakeholders from the initial design stage to the final demonstration and validation.

Strength analysis and modeling of cellular lattice structures manufactured using selective laser melting for tooling applications

DEFF Research Database (Denmark)

Mahshid, Rasoul; Hansen, Hans Nørgaard; Loft Højbjerre, Klaus

2016-01-01

Additive manufacturing is rapidly developing and gaining popularity for direct metal fabrication systems like selective laser melting (SLM). The technology has shown significant improvement for high-quality fabrication of lightweight design-efficient structures such as conformal cooling channels...... in injection molding tools and lattice structures. This research examines the effect of cellular lattice structures on the strength of workpieces additively manufactured from ultra high-strength steel powder. Two commercial SLM machines are used to fabricate cellular samples based on four architectures— solid......, hollow, lattice structure and rotated lattice structure. Compression test is applied to the specimens while they are deformed. The analytical approach includes finite element (FE), geometrical and mathematical models for prediction of collapse strength. The results from the the models are verified...

Role of toll-like receptors 3, 4 and 7 in cellular uptake and response to titanium dioxide nanoparticles

Directory of Open Access Journals (Sweden)

Peng Chen, Koki Kanehira and Akiyoshi Taniguchi

2013-01-01

Full Text Available Innate immune response is believed to be among the earliest provisional cellular responses, and mediates the interactions between microbes and cells. Toll-like receptors (TLRs are critical to these interactions. We hypothesize that TLRs also play an important role in interactions between nanoparticles (NPs and cells, although little information has been reported concerning such an interaction. In this study, we investigated the role of TLR3, TLR4 and TLR7 in cellular uptake of titanium dioxide NP (TiO2 NP agglomerates and the resulting inflammatory responses to these NPs. Our data indicate that TLR4 is involved in the uptake of TiO2 NPs and promotes the associated inflammatory responses. The data also suggest that TLR3, which has a subcellular location distinct from that of TLR4, inhibits the denaturation of cellular protein caused by TiO2 NPs. In contrast, the unique cellular localization of TLR7 has middle-ground functional roles in cellular response after TiO2 NP exposure. These findings are important for understanding the molecular interaction mechanisms between NPs and cells.

Interconnectivity of human cellular metabolism and disease prevalence

International Nuclear Information System (INIS)

Lee, Deok-Sun

2010-01-01

Fluctuations of metabolic reaction fluxes may cause abnormal concentrations of toxic or essential metabolites, possibly leading to metabolic diseases. The mutual binding of enzymatic proteins and ones involving common metabolites enforces distinct coupled reactions, by which local perturbations may spread through the cellular network. Such network effects at the molecular interaction level in human cellular metabolism can reappear in the patterns of disease occurrence. Here we construct the enzyme-reaction network and the metabolite-reaction network, capturing the flux coupling of metabolic reactions caused by the interacting enzymes and the shared metabolites, respectively. Diseases potentially caused by the failure of individual metabolic reactions can be identified by using the known disease–gene association, which allows us to derive the probability of an inactivated reaction causing diseases from the disease records at the population level. We find that the greater the number of proteins that catalyze a reaction, the higher the mean prevalence of its associated diseases. Moreover, the number of connected reactions and the mean size of the avalanches in the networks constructed are also shown to be positively correlated with the disease prevalence. These findings illuminate the impact of the cellular network topology on disease development, suggesting that the global organization of the molecular interaction network should be understood to assist in disease diagnosis, treatment, and drug discovery

Interconnectivity of human cellular metabolism and disease prevalence

Science.gov (United States)

Lee, Deok-Sun

2010-12-01

Fluctuations of metabolic reaction fluxes may cause abnormal concentrations of toxic or essential metabolites, possibly leading to metabolic diseases. The mutual binding of enzymatic proteins and ones involving common metabolites enforces distinct coupled reactions, by which local perturbations may spread through the cellular network. Such network effects at the molecular interaction level in human cellular metabolism can reappear in the patterns of disease occurrence. Here we construct the enzyme-reaction network and the metabolite-reaction network, capturing the flux coupling of metabolic reactions caused by the interacting enzymes and the shared metabolites, respectively. Diseases potentially caused by the failure of individual metabolic reactions can be identified by using the known disease-gene association, which allows us to derive the probability of an inactivated reaction causing diseases from the disease records at the population level. We find that the greater the number of proteins that catalyze a reaction, the higher the mean prevalence of its associated diseases. Moreover, the number of connected reactions and the mean size of the avalanches in the networks constructed are also shown to be positively correlated with the disease prevalence. These findings illuminate the impact of the cellular network topology on disease development, suggesting that the global organization of the molecular interaction network should be understood to assist in disease diagnosis, treatment, and drug discovery.

Reconstruction and validation of RefRec: a global model for the yeast molecular interaction network.

Directory of Open Access Journals (Sweden)

Tommi Aho

2010-05-01

Full Text Available Molecular interaction networks establish all cell biological processes. The networks are under intensive research that is facilitated by new high-throughput measurement techniques for the detection, quantification, and characterization of molecules and their physical interactions. For the common model organism yeast Saccharomyces cerevisiae, public databases store a significant part of the accumulated information and, on the way to better understanding of the cellular processes, there is a need to integrate this information into a consistent reconstruction of the molecular interaction network. This work presents and validates RefRec, the most comprehensive molecular interaction network reconstruction currently available for yeast. The reconstruction integrates protein synthesis pathways, a metabolic network, and a protein-protein interaction network from major biological databases. The core of the reconstruction is based on a reference object approach in which genes, transcripts, and proteins are identified using their primary sequences. This enables their unambiguous identification and non-redundant integration. The obtained total number of different molecular species and their connecting interactions is approximately 67,000. In order to demonstrate the capacity of RefRec for functional predictions, it was used for simulating the gene knockout damage propagation in the molecular interaction network in approximately 590,000 experimentally validated mutant strains. Based on the simulation results, a statistical classifier was subsequently able to correctly predict the viability of most of the strains. The results also showed that the usage of different types of molecular species in the reconstruction is important for accurate phenotype prediction. In general, the findings demonstrate the benefits of global reconstructions of molecular interaction networks. With all the molecular species and their physical interactions explicitly modeled, our

Interactive differential equations modeling program

International Nuclear Information System (INIS)

Rust, B.W.; Mankin, J.B.

1976-01-01

Due to the recent emphasis on mathematical modeling, many ecologists are using mathematics and computers more than ever, and engineers, mathematicians and physical scientists are now included in ecological projects. However, the individual ecologist, with intuitive knowledge of the system, still requires the means to critically examine and adjust system models. An interactive program was developed with the primary goal of allowing an ecologist with minimal experience in either mathematics or computers to develop a system model. It has also been used successfully by systems ecologists, engineers, and mathematicians. This program was written in FORTRAN for the DEC PDP-10, a remote terminal system at Oak Ridge National Laboratory. However, with relatively minor modifications, it can be implemented on any remote terminal system with a FORTRAN IV compiler, or equivalent. This program may be used to simulate any phenomenon which can be described as a system of ordinary differential equations. The program allows the user to interactively change system parameters and/or initial conditions, to interactively select a set of variables to be plotted, and to model discontinuities in the state variables and/or their derivatives. One of the most useful features to the non-computer specialist is the ability to interactively address the system parameters by name and to interactively adjust their values between simulations. These and other features are described in greater detail

Cellular interactions of a water-soluble supramolecular polymer complex of carbon nanotubes with human epithelial colorectal adenocarcinoma cells.

Science.gov (United States)

Lee, Yeonju; Geckeler, Kurt E

2012-08-01

Water-soluble, PAX-loaded carbon nanotubes are fabricated by employing a synthetic polyampholyte, PDM. To investigate the suitability of the polyampholyte and the nanotubes as drug carriers, different cellular interactions such as the human epithelial Caco-2 cells viability, their effect on the cell growth, and the change in the transepithelial electrical resistance in Caco-2 cells are studied. The resulting complex is found to exhibit an effective anti-cancer effect against colon cancer cells and an increased the reduction of the electrical resistance in the Caco-2 cells when compared to the precursor PAX. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Long-range interactions and parallel scalability in molecular simulations

NARCIS (Netherlands)

Patra, M.; Hyvönen, M.T.; Falck, E.; Sabouri-Ghomi, M.; Vattulainen, I.; Karttunen, M.E.J.

2007-01-01

Typical biomolecular systems such as cellular membranes, DNA, and protein complexes are highly charged. Thus, efficient and accurate treatment of electrostatic interactions is of great importance in computational modeling of such systems. We have employed the GROMACS simulation package to perform

Origami interleaved tube cellular materials

International Nuclear Information System (INIS)

Cheung, Kenneth C; Tachi, Tomohiro; Calisch, Sam; Miura, Koryo

2014-01-01

A novel origami cellular material based on a deployable cellular origami structure is described. The structure is bi-directionally flat-foldable in two orthogonal (x and y) directions and is relatively stiff in the third orthogonal (z) direction. While such mechanical orthotropicity is well known in cellular materials with extruded two dimensional geometry, the interleaved tube geometry presented here consists of two orthogonal axes of interleaved tubes with high interfacial surface area and relative volume that changes with fold-state. In addition, the foldability still allows for fabrication by a flat lamination process, similar to methods used for conventional expanded two dimensional cellular materials. This article presents the geometric characteristics of the structure together with corresponding kinematic and mechanical modeling, explaining the orthotropic elastic behavior of the structure with classical dimensional scaling analysis. (paper)

Origami interleaved tube cellular materials

Science.gov (United States)

Cheung, Kenneth C.; Tachi, Tomohiro; Calisch, Sam; Miura, Koryo

2014-09-01

A novel origami cellular material based on a deployable cellular origami structure is described. The structure is bi-directionally flat-foldable in two orthogonal (x and y) directions and is relatively stiff in the third orthogonal (z) direction. While such mechanical orthotropicity is well known in cellular materials with extruded two dimensional geometry, the interleaved tube geometry presented here consists of two orthogonal axes of interleaved tubes with high interfacial surface area and relative volume that changes with fold-state. In addition, the foldability still allows for fabrication by a flat lamination process, similar to methods used for conventional expanded two dimensional cellular materials. This article presents the geometric characteristics of the structure together with corresponding kinematic and mechanical modeling, explaining the orthotropic elastic behavior of the structure with classical dimensional scaling analysis.

An analytical model for interactive failures

International Nuclear Information System (INIS)

Sun Yong; Ma Lin; Mathew, Joseph; Zhang Sheng

2006-01-01

In some systems, failures of certain components can interact with each other, and accelerate the failure rates of these components. These failures are defined as interactive failure. Interactive failure is a prevalent cause of failure associated with complex systems, particularly in mechanical systems. The failure risk of an asset will be underestimated if the interactive effect is ignored. When failure risk is assessed, interactive failures of an asset need to be considered. However, the literature is silent on previous research work in this field. This paper introduces the concepts of interactive failure, develops an analytical model to analyse this type of failure quantitatively, and verifies the model using case studies and experiments

Repair and mutagenesis in procaryotes as cellular responses to ambiental agents

International Nuclear Information System (INIS)

Gomes, R.A.

1982-01-01

The correct and incorrect mechanisms of DNA repair are discussed, as well as the cellular responses induced by the DNA lesions; the reductone mollecular effects; the cellular interactions among irradiated populations of microorganisms and the utilization of microbial assays for the detection of oncogenic activities of chemicals. (M.A.) [pt

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

Science.gov (United States)

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

Spatial Evolutionary Games of Interaction among Generic Cancer Cells

DEFF Research Database (Denmark)

Bach, Lars Arve; Sumpter, David J.T.; Alsner, Jan

2003-01-01

Evolutionary game models of cellular interactions have shown that heterogeneity in the cellular genotypic composition is maintained through evolution to stable coexistence of growth-promoting and non-promoting cell types. We generalise these mean-field models and relax the assumption of perfect...... mixing of cells by instead implementing an individual-based model that includes the stochastic and spatial effects likely to occur in tumours. The scope for coexistence of genotypic strategies changed with the inclusion of explicit space and stochasticity. The spatial models show some interesting...... deviations from their mean-field counterparts, for example the possibility of altruistic (paracrine) cell strategies to thrive. Such effects can however, be highly sensitive to model implementation and the more realistic models with semi-synchronous and stochastic updating do not show evolution of altruism...

Porous models for wave-seabed interactions

Energy Technology Data Exchange (ETDEWEB)

Jeng, Dong-Sheng [Shanghai Jiaotong Univ., SH (China)

2013-02-01

Detailed discussion about the phenomenon of wave-seabed interactions. Novel models for wave-induced seabed response. Intensive theoretical derivations for wave-seabed interactions. Practical examples for engineering applications. ''Porous Models for Wave-seabed Interactions'' discusses the Phenomenon of wave-seabed interactions, which is a vital issue for coastal and geotechnical engineers involved in the design of foundations for marine structures such as pipelines, breakwaters, platforms, etc. The most important sections of this book will be the fully detailed theoretical models of wave-seabed interaction problem, which are particularly useful for postgraduate students and junior researchers entering the discipline of marine geotechnics and offshore engineering. This book also converts the research outcomes of theoretical studies to engineering applications that will provide front-line engineers with practical and effective tools in the assessment of seabed instability in engineering design.

Genetic variation in the cellular response of Daphnia magna (Crustacea: Cladocera) to its bacterial parasite.

Science.gov (United States)

Auld, Stuart K J R; Scholefield, Jennifer A; Little, Tom J

2010-11-07

Linking measures of immune function with infection, and ultimately, host and parasite fitness is a major goal in the field of ecological immunology. In this study, we tested for the presence and timing of a cellular immune response in the crustacean Daphnia magna following exposure to its sterilizing endoparasite Pasteuria ramosa. We found that D. magna possesses two cell types circulating in the haemolymph: a spherical one, which we call a granulocyte and an irregular-shaped amoeboid cell first described by Metchnikoff over 125 years ago. Daphnia magna mounts a strong cellular response (of the amoeboid cells) just a few hours after parasite exposure. We further tested for, and found, considerable genetic variation for the magnitude of this cellular response. These data fostered a heuristic model of resistance in this naturally coevolving host-parasite interaction. Specifically, the strongest cellular responses were found in the most susceptible hosts, indicating resistance is not always borne from a response that destroys invading parasites, but rather stems from mechanisms that prevent their initial entry. Thus, D. magna may have a two-stage defence--a genetically determined barrier to parasite establishment and a cellular response once establishment has begun.

Cell physiology based pharmacodynamic modeling of antimicrobial drug combinations

OpenAIRE

Hethey, Christoph Philipp

2017-01-01

Mathematical models of bacterial growth have been successfully applied to study the relationship between antibiotic drug exposure and the antibacterial effect. Since these models typically lack a representation of cellular processes and cell physiology, the mechanistic integration of drug action is not possible on the cellular level. The cellular mechanisms of drug action, however, are particularly relevant for the prediction, analysis and understanding of interactions between antibiotics. In...

Searching for cellular partners of hantaviral nonstructural protein NSs: Y2H screening of mouse cDNA library and analysis of cellular interactome.

Science.gov (United States)

Rönnberg, Tuomas; Jääskeläinen, Kirsi; Blot, Guillaume; Parviainen, Ville; Vaheri, Antti; Renkonen, Risto; Bouloy, Michele; Plyusnin, Alexander

2012-01-01

Hantaviruses (Bunyaviridae) are negative-strand RNA viruses with a tripartite genome. The small (S) segment encodes the nucleocapsid protein and, in some hantaviruses, also the nonstructural protein (NSs). The aim of this study was to find potential cellular partners for the hantaviral NSs protein. Toward this aim, yeast two-hybrid (Y2H) screening of mouse cDNA library was performed followed by a search for potential NSs protein counterparts via analyzing a cellular interactome. The resulting interaction network was shown to form logical, clustered structures. Furthermore, several potential binding partners for the NSs protein, for instance ACBD3, were identified and, to prove the principle, interaction between NSs and ACBD3 proteins was demonstrated biochemically.

The joy of interactive modeling

Science.gov (United States)

Donchyts, Gennadii; Baart, Fedor; van Dam, Arthur; Jagers, Bert

2013-04-01

The conventional way of working with hydrodynamical models usually consists of the following steps: 1) define a schematization (e.g., in a graphical user interface, or by editing input files) 2) run model from start to end 3) visualize results 4) repeat any of the previous steps. This cycle commonly takes up from hours to several days. What if we can make this happen instantly? As most of the research done using numerical models is in fact qualitative and exploratory (Oreskes et al., 1994), why not use these models as such? How can we adapt models so that we can edit model input, run and visualize results at the same time? More and more, interactive models become available as online apps, mainly for demonstration and educational purposes. These models often simplify the physics behind flows and run on simplified model geometries, particularly when compared with state-of-the-art scientific simulation packages. Here we show how the aforementioned conventional standalone models ("static, run once") can be transformed into interactive models. The basic concepts behind turning existing (conventional) model engines into interactive engines are the following. The engine does not run the model from start to end, but is always available in memory, and can be fed by new boundary conditions, or state changes at any time. The model can be run continuously, per step, or up to a specified time. The Hollywood principle dictates how the model engine is instructed from 'outside', instead of the model engine taking all necessary actions on its own initiative. The underlying techniques that facilitate these concepts are introspection of the computation engine, which exposes its state variables, and control functions, e.g. for time stepping, via a standardized interface, such as BMI (Peckam et. al., 2012). In this work we have used a shallow water flow model engine D-Flow Flexible Mesh. The model was converted from executable to a library, and coupled to the graphical modelling

Integration of statistical modeling and high-content microscopy to systematically investigate cell-substrate interactions.

Science.gov (United States)

Chen, Wen Li Kelly; Likhitpanichkul, Morakot; Ho, Anthony; Simmons, Craig A

2010-03-01

Cell-substrate interactions are multifaceted, involving the integration of various physical and biochemical signals. The interactions among these microenvironmental factors cannot be facilely elucidated and quantified by conventional experimentation, and necessitate multifactorial strategies. Here we describe an approach that integrates statistical design and analysis of experiments with automated microscopy to systematically investigate the combinatorial effects of substrate-derived stimuli (substrate stiffness and matrix protein concentration) on mesenchymal stem cell (MSC) spreading, proliferation and osteogenic differentiation. C3H10T1/2 cells were grown on type I collagen- or fibronectin-coated polyacrylamide hydrogels with tunable mechanical properties. Experimental conditions, which were defined according to central composite design, consisted of specific permutations of substrate stiffness (3-144 kPa) and adhesion protein concentration (7-520 microg/mL). Spreading area, BrdU incorporation and Runx2 nuclear translocation were quantified using high-content microscopy and modeled as mathematical functions of substrate stiffness and protein concentration. The resulting response surfaces revealed distinct patterns of protein-specific, substrate stiffness-dependent modulation of MSC proliferation and differentiation, demonstrating the advantage of statistical modeling in the detection and description of higher-order cellular responses. In a broader context, this approach can be adapted to study other types of cell-material interactions and can facilitate the efficient screening and optimization of substrate properties for applications involving cell-material interfaces. Copyright 2009 Elsevier Ltd. All rights reserved.

Advanced spatial metrics analysis in cellular automata land use and cover change modeling

International Nuclear Information System (INIS)

Zamyatin, Alexander; Cabral, Pedro

2011-01-01

This paper proposes an approach for a more effective definition of cellular automata transition rules for landscape change modeling using an advanced spatial metrics analysis. This approach considers a four-stage methodology based on: (i) the search for the appropriate spatial metrics with minimal correlations; (ii) the selection of the appropriate neighborhood size; (iii) the selection of the appropriate technique for spatial metrics application; and (iv) the analysis of the contribution level of each spatial metric for joint use. The case study uses an initial set of 7 spatial metrics of which 4 are selected for modeling. Results show a better model performance when compared to modeling without any spatial metrics or with the initial set of 7 metrics.

Structure of fast ion energy depositions in water. Application to the Monte Carlo study of cellular inactivation

International Nuclear Information System (INIS)

Champion, Ch.

1999-01-01

In order to understand the physical processes involved in the heavy ion irradiation of biological samples, a Monte Carlo simulation code and a random inventory code for interaction clusters in volumes comparable to those of sensible biological sites like nucleosomes (few nm 3 ) have been developed. It is now well known that macroscopic parameters like the dose rate or the stopping power are not suitable to explain the cellular inactivation induced by heavy ions irradiation. The aim of this work is the development of a mechanistic model based on the identification of primary processes susceptible to be of major importance on the biological aspect. The code developed simulates the creation and transport in water of all secondary particles produced by the impact of heavy ions. Once all energy depositions generated, an algorithm of random inventory of interaction clusters has been built in order to evaluate the type of critical energy deposition which presents a correlation with the experimental data of cellular inactivation. For light ions, like particles, this cluster model has permitted to reproduce the variations of the experimental number of lethal lesions observed, in particular the decay of biological efficiency. However, for heavy ions, these parameters do not allow to reproduce the experimental data of cellular inactivation. Therefore, the concept of ionization clusters described in terms of critical deposition in critical volumes is not sufficient. (J.S.)

Algorithm for cellular reprogramming.

Science.gov (United States)

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.

Interactions of donor sources and media influence the histo-morphological quality of full-thickness skin models.

Science.gov (United States)

Lange, Julia; Weil, Frederik; Riegler, Christoph; Groeber, Florian; Rebhan, Silke; Kurdyn, Szymon; Alb, Miriam; Kneitz, Hermann; Gelbrich, Götz; Walles, Heike; Mielke, Stephan

2016-10-01

Human artificial skin models are increasingly employed as non-animal test platforms for research and medical purposes. However, the overall histopathological quality of such models may vary significantly. Therefore, the effects of manufacturing protocols and donor sources on the quality of skin models built-up from fibroblasts and keratinocytes derived from juvenile foreskins is studied. Histo-morphological parameters such as epidermal thickness, number of epidermal cell layers, dermal thickness, dermo-epidermal adhesion and absence of cellular nuclei in the corneal layer are obtained and scored accordingly. In total, 144 full-thickness skin models derived from 16 different donors, built-up in triplicates using three different culture conditions were successfully generated. In univariate analysis both media and donor age affected the quality of skin models significantly. Both parameters remained statistically significant in multivariate analyses. Performing general linear model analyses we could show that individual medium-donor-interactions influence the quality. These observations suggest that the optimal choice of media may differ from donor to donor and coincides with findings where significant inter-individual variations of growth rates in keratinocytes and fibroblasts have been described. Thus, the consideration of individual medium-donor-interactions may improve the overall quality of human organ models thereby forming a reproducible test platform for sophisticated clinical research. Copyright © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

Science.gov (United States)

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.

Characteristics of Middle School Students Learning Actions in Outdoor Mathematical Activities with the Cellular Phone

Science.gov (United States)

Daher, Wajeeh; Baya'a, Nimer

2012-01-01

Learning in the cellular phone environment enables utilizing the multiple functions of the cellular phone, such as mobility, availability, interactivity, verbal and voice communication, taking pictures or recording audio and video, measuring time and transferring information. These functions together with mathematics-designated cellular phone…

Stochastic hyperfine interactions modeling library

Science.gov (United States)

Zacate, Matthew O.; Evenson, William E.

2011-04-01

The stochastic hyperfine interactions modeling library (SHIML) provides a set of routines to assist in the development and application of stochastic models of hyperfine interactions. The library provides routines written in the C programming language that (1) read a text description of a model for fluctuating hyperfine fields, (2) set up the Blume matrix, upon which the evolution operator of the system depends, and (3) find the eigenvalues and eigenvectors of the Blume matrix so that theoretical spectra of experimental techniques that measure hyperfine interactions can be calculated. The optimized vector and matrix operations of the BLAS and LAPACK libraries are utilized; however, there was a need to develop supplementary code to find an orthonormal set of (left and right) eigenvectors of complex, non-Hermitian matrices. In addition, example code is provided to illustrate the use of SHIML to generate perturbed angular correlation spectra for the special case of polycrystalline samples when anisotropy terms of higher order than A can be neglected. Program summaryProgram title: SHIML Catalogue identifier: AEIF_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEIF_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU GPL 3 No. of lines in distributed program, including test data, etc.: 8224 No. of bytes in distributed program, including test data, etc.: 312 348 Distribution format: tar.gz Programming language: C Computer: Any Operating system: LINUX, OS X RAM: Varies Classification: 7.4 External routines: TAPP [1], BLAS [2], a C-interface to BLAS [3], and LAPACK [4] Nature of problem: In condensed matter systems, hyperfine methods such as nuclear magnetic resonance (NMR), Mössbauer effect (ME), muon spin rotation (μSR), and perturbed angular correlation spectroscopy (PAC) measure electronic and magnetic structure within Angstroms of nuclear probes through the hyperfine interaction. When

The similia principle: results obtained in a cellular model system.

Science.gov (United States)

Wiegant, Fred; Van Wijk, Roeland

2010-01-01

This paper describes the results of a research program focused on the beneficial effect of low dose stress conditions that were applied according to the similia principle to cells previously disturbed by more severe stress conditions. In first instance, we discuss criteria for research on the similia principle at the cellular level. Then, the homologous ('isopathic') approach is reviewed, in which the initial (high dose) stress used to disturb cellular physiology and the subsequent (low dose) stress are identical. Beneficial effects of low dose stress are described in terms of increased cellular survival capacity and at the molecular level as an increase in the synthesis of heat shock proteins (hsps). Both phenomena reflect a stimulation of the endogenous cellular self-recovery capacity. Low dose stress conditions applied in a homologous approach stimulate the synthesis of hsps and enhance survival in comparison with stressed cells that were incubated in the absence of low dose stress conditions. Thirdly, the specificity of the low dose stress condition is described where the initial (high dose) stress is different in nature from the subsequently applied (low dose) stress; the heterologous or 'heteropathic' approach. The results support the similia principle at the cellular level and add to understanding of how low dose stress conditions influence the regulatory processes underlying self-recovery. In addition, the phenomenon of 'symptom aggravation' which is also observed at the cellular level, is discussed in the context of self-recovery. Finally, the difference in efficiency between the homologous and the heterologous approach is discussed; a perspective is indicated for further research; and the relationship between studies on the similia principle and the recently introduced concept of 'postconditioning hormesis' is emphasized. Copyright 2009 The Faculty of Homeopathy. Published by Elsevier Ltd. All rights reserved.

TNF-α inhibits trophoblast integration into endothelial cellular networks.

Science.gov (United States)

Xu, B; Nakhla, S; Makris, A; Hennessy, A

2011-03-01

Preeclampsia has been linked to shallow trophoblast invasion and failure of uterine spiral artery transformation. Interaction between trophoblast cells and maternal uterine endothelium is critically important for this remodelling. The aim of our study was to investigate the effect of TNF-α on the interactions of trophoblast-derived JEG-3 cells into capillary-like cellular networks. We have employed an in vitro trophoblast-endothelial cell co-culture model to quantify trophoblast integration into endothelial cellular networks and to investigate the effects of TNF-α. Controlled co-cultures were also treated with anti-TNF-α antibody (5 μg/ml) to specifically block the effect of TNF-α. The invasion was evaluated by performing quantitative PCR (Q-PCR) to analyse gene expression of matrix metalloproteinases-2 (MMP-2), MMP-9, tissue inhibitor of matrix metalloproteinase (TIMP)-1, integrins (α(1)β(1) and α(6)β(4)), plasminogen activator inhibitor (PAI)-1, E-cadherin and VE-cadherin. JEG-3 cell integration into endothelial networks was significantly inhibited by exogenous TNF-α. The inhibition was observed in the range of 0.2-5 ng/ml, to a maximum 56% inhibition at the highest concentration. This inhibition was reversed by anti-TNF-α antibody. Q-PCR analysis showed that mRNA expression of integrins α(1)β(1) and MMP-2 was significantly decreased. VE-cadherin mRNA expression was significantly up-regulated (32-80%, p integration into maternal endothelial cellular networks, and this process involves the inhibition of MMP-2 and a failure of integrins switch from α(6)β(4) to α(1)β(1.) These molecular correlations reflect the changes identified in human preeclampsia. Copyright © 2011 Elsevier Ltd. All rights reserved.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Surface Dynamic Process Simulation with the Use of Cellular Automata

International Nuclear Information System (INIS)

Adamska-Szatko, M.; Bala, J.

2010-01-01

Cellular automata are known for many applications, especially for physical and biological simulations. Universal cellular automata can be used for modelling complex natural phenomena. The paper presents simulation of surface dynamic process. Simulation uses 2-dimensional cellular automata algorithm. Modelling and visualisation were created by in-house developed software with standard OpenGL graphic library. (authors)

A Computational Model of Cellular Engraftment on Lung Scaffolds

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Joshua J. Pothen

2016-10-01

Full Text Available The possibility that stem cells might be used to regenerate tissue is now being investigated for a variety of organs, but these investigations are still essentially exploratory and have few predictive tools available to guide experimentation. We propose, in this study, that the field of lung tissue regeneration might be better served by predictive tools that treat stem cells as agents that obey certain rules of behavior governed by both their phenotype and their environment. Sufficient knowledge of these rules of behavior would then, in principle, allow lung tissue development to be simulated computationally. Toward this end, we developed a simple agent-based computational model to simulate geographic patterns of cells seeded onto a lung scaffold. Comparison of the simulated patterns to those observed experimentally supports the hypothesis that mesenchymal stem cells proliferate preferentially toward the scaffold boundary, whereas alveolar epithelial cells do not. This demonstrates that a computational model of this type has the potential to assist in the discovery of rules of cellular behavior

Drug-model membrane interactions

International Nuclear Information System (INIS)

Deniz, Usha K.

1994-01-01

In the present day world, drugs play a very important role in medicine and it is necessary to understand their mode of action at the molecular level, in order to optimise their use. Studies of drug-biomembrane interactions are essential for gaining such as understanding. However, it would be prohibitively difficult to carry out such studies, since biomembranes are highly complex systems. Hence, model membranes (made up of these lipids which are important components of biomembranes) of varying degrees of complexity are used to investigate drug-membrane interactions. Bio- as well as model-membranes undergo a chain melting transition when heated, the chains being in a disordered state above the transition point, T CM . This transition is of physiological importance since biomembranes select their components such that T CM is less than the ambient temperature but not very much so, so that membrane flexibility is ensured and porosity, avoided. The influence of drugs on the transition gives valuable clues about various parameters such as the location of the drug in the membrane. Deep insights into drug-membrane interactions are obtained by observing the effect of drugs on membrane structure and the mobilities of the various groups in lipids, near T CM . Investigation of such changes have been carried out with several drugs, using techniques such as DSC, XRD and NMR. The results indicate that the drug-membrane interaction not only depends on the nature of drug and lipids but also on the form of the model membrane - stacked bilayer or vesicles. The light that these results shed on the nature of drug-membrane interactions is discussed. (author). 13 refs., 13 figs., 1 tab

Cellular automata model for human articular chondrocytes migration, proliferation and cell death: An in vitro validation.

Science.gov (United States)

Vaca-González, J J; Gutiérrez, M L; Guevara, J M; Garzón-Alvarado, D A

2017-01-01

Articular cartilage is characterized by low cell density of only one cell type, chondrocytes, and has limited self-healing properties. When articular cartilage is affected by traumatic injuries, a therapeutic strategy such as autologous chondrocyte implantation is usually proposed for its treatment. This approach requires in vitro chondrocyte expansion to yield high cell number for cell transplantation. To improve the efficiency of this procedure, it is necessary to assess cell dynamics such as migration, proliferation and cell death during culture. Computational models such as cellular automata can be used to simulate cell dynamics in order to enhance the result of cell culture procedures. This methodology has been implemented for several cell types; however, an experimental validation is required for each one. For this reason, in this research a cellular automata model, based on random-walk theory, was devised in order to predict articular chondrocyte behavior in monolayer culture during cell expansion. Results demonstrated that the cellular automata model corresponded to cell dynamics and computed-accurate quantitative results. Moreover, it was possible to observe that cell dynamics depend on weighted probabilities derived from experimental data and cell behavior varies according to the cell culture period. Thus, depending on whether cells were just seeded or proliferated exponentially, culture time probabilities differed in percentages in the CA model. Furthermore, in the experimental assessment a decreased chondrocyte proliferation was observed along with increased passage number. This approach is expected to having other uses as in enhancing articular cartilage therapies based on tissue engineering and regenerative medicine.

Building mathematics cellular phone learning communities

Directory of Open Access Journals (Sweden)

Wajeeh M. Daher

2011-04-01

Full Text Available Researchers emphasize the importance of maintaining learning communities and environments. This article describes the building and nourishment of a learning community, one comprised of middle school students who learned mathematics out-of-class using the cellular phone. The building of the learning community was led by three third year pre-service teachers majoring in mathematics and computers. The pre-service teachers selected thirty 8th grade students to learn mathematics with the cellular phone and be part of a learning community experimenting with this learning. To analyze the building and development stages of the cellular phone learning community, two models of community building stages were used; first the team development model developed by Tuckman (1965, second the life cycle model of a virtual learning community developed by Garber (2004. The research findings indicate that a learning community which is centered on a new technology has five 'life' phases of development: Pre-birth, birth, formation, performing, and maturity. Further, the research finding indicate that the norms that were encouraged by the preservice teachers who initiated the cellular phone learning community resulted in a community which developed, nourished and matured to be similar to a community of experienced applied mathematicians who use mathematical formulae to study everyday phenomena.

A Modified Cellular Automaton Approach for Mixed Bicycle Traffic Flow Modeling

Directory of Open Access Journals (Sweden)

Xiaonian Shan

2015-01-01

Full Text Available Several previous studies have used the Cellular Automaton (CA for the modeling of bicycle traffic flow. However, previous CA models have several limitations, resulting in differences between the simulated and the observed traffic flow features. The primary objective of this study is to propose a modified CA model for simulating the characteristics of mixed bicycle traffic flow. Field data were collected on physically separated bicycle path in Shanghai, China, and were used to calibrate the CA model using the genetic algorithm. Traffic flow features between simulations of several CA models and field observations were compared. The results showed that our modified CA model produced more accurate simulation for the fundamental diagram and the passing events in mixed bicycle traffic flow. Based on our model, the bicycle traffic flow features, including the fundamental diagram, the number of passing events, and the number of lane changes, were analyzed. We also analyzed the traffic flow features with different traffic densities, traffic components on different travel lanes. Results of the study can provide important information for understanding and simulating the operations of mixed bicycle traffic flow.

STRING 8--a global view on proteins and their functional interactions in 630 organisms

DEFF Research Database (Denmark)

Jensen, Lars Juhl; Kuhn, Michael; Stark, Manuel

2008-01-01

Functional partnerships between proteins are at the core of complex cellular phenotypes, and the networks formed by interacting proteins provide researchers with crucial scaffolds for modeling, data reduction and annotation. STRING is a database and web resource dedicated to protein-protein inter......Functional partnerships between proteins are at the core of complex cellular phenotypes, and the networks formed by interacting proteins provide researchers with crucial scaffolds for modeling, data reduction and annotation. STRING is a database and web resource dedicated to protein......-protein interactions, including both physical and functional interactions. It weights and integrates information from numerous sources, including experimental repositories, computational prediction methods and public text collections, thus acting as a meta-database that maps all interaction evidence onto a common set...... of genomes and proteins. The most important new developments in STRING 8 over previous releases include a URL-based programming interface, which can be used to query STRING from other resources, improved interaction prediction via genomic neighborhood in prokaryotes, and the inclusion of protein structures...

Cellular Model of Atherogenesis Based on Pluripotent Vascular Wall Pericytes.

Science.gov (United States)

Ivanova, Ekaterina A; Orekhov, Alexander N

2016-01-01

Pericytes are pluripotent cells that can be found in the vascular wall of both microvessels and large arteries and veins. They have distinct morphology with long branching processes and form numerous contacts with each other and with endothelial cells, organizing the vascular wall cells into a three-dimensional network. Accumulating evidence demonstrates that pericytes may play a key role in the pathogenesis of vascular disorders, including atherosclerosis. Macrovascular pericytes are able to accumulate lipids and contribute to growth and vascularization of the atherosclerotic plaque. Moreover, they participate in the local inflammatory process and thrombosis, which can lead to fatal consequences. At the same time, pericytes can represent a useful model for studying the atherosclerotic process and for the development of novel therapeutic approaches. In particular, they are suitable for testing various substances' potential for decreasing lipid accumulation induced by the incubation of cells with atherogenic low-density lipoprotein. In this review we will discuss the application of cellular models for studying atherosclerosis and provide several examples of successful application of these models to drug research.

Embryonic stem cells as an ectodermal cellular model of human p63-related dysplasia syndromes.

NARCIS (Netherlands)

Rostagno, P.; Wolchinsky, Z.; Vigano, A.M.; Shivtiel, S.; Zhou, Huiqing; Bokhoven, J.H.L.M. van; Ferone, G.; Missero, C.; Mantovani, R.; Aberdam, D.; Virolle, T.

2010-01-01

Heterozygous mutations in the TP63 transcription factor underlie the molecular basis of several similar autosomal dominant ectodermal dysplasia (ED) syndromes. Here we provide a novel cellular model derived from embryonic stem (ES) cells that recapitulates in vitro the main steps of embryonic skin

3D hierarchical computational model of wood as a cellular material with fibril reinforced, heterogeneous multiple layers

DEFF Research Database (Denmark)

Qing, Hai; Mishnaevsky, Leon

2009-01-01

A 3D hierarchical computational model of deformation and stiffness of wood, which takes into account the structures of wood at several scale levels (cellularity, multilayered nature of cell walls, composite-like structures of the wall layers) is developed. At the mesoscale, the softwood cell...... cellular model. With the use of the developed hierarchical model, the influence of the microstructure, including microfibril angles (MFAs, which characterizes the orientation of the cellulose fibrils with respect to the cell axis), the thickness of the cell wall, the shape of the cell cross...... is presented as a 3D hexagon-shape-tube with multilayered walls. The layers in the softwood cell are considered as considered as composite reinforced by microfibrils (celluloses). The elastic properties of the layers are determined with Halpin–Tsai equations, and introduced into mesoscale finite element...

On Elementary and Algebraic Cellular Automata

Science.gov (United States)

Gulak, Yuriy

In this paper we study elementary cellular automata from an algebraic viewpoint. The goal is to relate the emergent complex behavior observed in such systems with the properties of corresponding algebraic structures. We introduce algebraic cellular automata as a natural generalization of elementary ones and discuss their applications as generic models of complex systems.

Physical Property Control on the Cellular Uptake Pathway and Spatial Distribution of Nanoparticles in Cells.

Science.gov (United States)

Ahn, Sungsook; Seo, Eunseok; Kim, Ki Hean; Lee, Sang Joon

2015-06-01

Nanoparticles have been developed in broad biomedical research in terms of effective cellular interactions to treat and visualize diseased cells. Considering the charge and polar functional groups of proteins that are embedded in cellular membranes, charged nanoparticles have been strategically developed to enhance electrostatic cellular interactions. In this study, we show that cellular uptake efficiency, pathway, and spatial distribution of gold nanoparticles in a cell are significantly modulated based on the surface condition of gold nanoparticles and human cancer cells that were tuned by controlling the pH of the medium and by introducing an electron beam. Cellular uptake efficiency is increased when electrostatic attraction is induced between the cells and the gold nanoparticles. Cell surface modification changes the cellular uptake pathways of the gold nanoparticles and concentrates the gold nanoparticles at the membrane region. Surface modification of the gold nanoparticles also contributes to deep penetration and homogeneous spatial distributions in a cell.

From equilibrium spin models to probabilistic cellular automata

International Nuclear Information System (INIS)

Georges, A.; Le Doussal, P.

1989-01-01

The general equivalence between D-dimensional probabilistic cellular automata (PCA) and (D + 1)-dimensional equilibrium spin models satisfying a disorder condition is first described in a pedagogical way and then used to analyze the phase diagrams, the critical behavior, and the universality classes of some automato. Diagrammatic representations of time-dependent correlation functions PCA are introduced. Two important classes of PCA are singled out for which these correlation functions simplify: (1) Quasi-Hamiltonian automata, which have a current-carrying steady state, and for which some correlation functions are those of a D-dimensional static model PCA satisfying the detailed balance condition appear as a particular case of these rules for which the current vanishes. (2) Linear (and more generally affine) PCA for which the diagrammatics reduces to a random walk problem closely related to (D + 1)-dimensional directed SAWs: both problems display a critical behavior with mean-field exponents in any dimension. The correlation length and effective velocity of propagation of excitations can be calculated for affine PCA, as is shown on an explicit D = 1 example. The authors conclude with some remarks on nonlinear PCA, for which the diagrammatics is related to reaction-diffusion processes, and which belong in some cases to the universality class of Reggeon field theory

Graphene nanoplatelets spontaneously translocate into the cytosol and physically interact with cellular organelles in the fish cell line PLHC-1

Energy Technology Data Exchange (ETDEWEB)

Lammel, Tobias; Navas, José M., E-mail: jmnavas@inia.es

2014-05-01

Highlights: • We assessed the cytotoxicity and uptake of graphene nanomaterials in PLHC-1 cells. • GO and CXYG nanoplatelets caused physical injury of the plasma membrane. • GO and CXYG accumulated in the cytosol and interacted with cellular organelles. • PLHC-1 cells exposed to GO/CXYG demonstrated high ROS levels but low cytotoxicity. • ROS formation was related with GO/CXYG-induced structural damage of mitochondria. - Abstract: Graphene and graphene derivatives constitute a novel class of carbon-based nanomaterials being increasingly produced and used in technical and consumer applications. Release of graphene nanoplatelets during the life cycle of these applications may result in human and environmental exposure calling for assessment of their potential to cause harm to humans and wildlife. This study aimed to assess the toxicity of graphene oxide (GO) and carboxyl graphene (CXYG) nanoplatelets to non-mammalian species using the fish cell line PLHC-1 as in vitro model. The cytotoxicity of GO and CXYG was assessed using different assays measuring alterations in plasma membrane integrity, metabolic activity, and lysosomal and mitochondrial function. The induction of oxidative stress was assessed by measuring intracellular reactive oxygen species (ROS) levels. Interaction with the plasma membrane and internalization of nanoplatelets were investigated by electron microscopy. Graphene nanoplatelets spontaneously penetrated through the plasma membrane and accumulated in the cytosol, where they further interacted with mitochondrial and nuclear membranes. PLHC-1 cells demonstrated significantly reduced mitochondrial membrane potential (MMP) and increased ROS levels at 16 μg/ml GO and CXYG (72 h), but barely any decrease in cell viability. The observation of intracellular graphene accumulations not enclosed by membranes suggests that GO and CXYG internalization in fish hepatoma cells occurs through an endocytosis-independent mechanism.

Interaction between cellular retinoic acid-binding protein II and histone hypoacetylation in renal cell carcinoma

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Viroj Wiwanitkit

2008-04-01

Full Text Available Renal cell carcinoma is a rare but serious malignancy. Since a reduction in the level of retinoic acid receptor beta 2 (RARbeta2 expression in cancer cells due in part to histone hypoacetylation which is controlled by histone deacetylase (HD, the study on the interaction between cellular retinoic acid-binding proteins II (CRABP II, which is proposed to have its potential influence on retinoic acid (RA response, and HD can be useful. Comparing to CARBP II and HD, the CARBP II-HD poses the same function and biological process as HD. This can confirm that HD has a significant suppressive effect on the expression of CARBP II. Therefore, reduction in the level of RARbeta2 expression in cancer cells can be expected and this can lead to failure in treatment of renal cell carcinoma with RA. The author hereby purpose that additional HD inhibitor should be added into the regiment of RA to increase the effectiveness of treatment.

A radiation measurement study on cellular phone

International Nuclear Information System (INIS)

Mohd Yusof Mohd Ali; Rozaimah Abd Rahim; Roha Tukimin; Khairol Nizam Mohamed; Mohd Amirul Nizam Mohamad Thari; Ahmad Fadzli Ahmad Sanusi

2007-01-01

This paper will explain the radiation level produced by various selected cellular phone from various models and brands available in the market. The result obtained from this study will also recommend whether a cellular phone is safe for public usage or it might cause any effect on public health. Finally, a database of radiation measurement level produced by selected various cellular phone will also be developed and exhibited in this paper. (Author)

HSV-I and the cellular DNA damage response.

Science.gov (United States)

Smith, Samantha; Weller, Sandra K

2015-04-01

Peter Wildy first observed genetic recombination between strains of HSV in 1955. At the time, knowledge of DNA repair mechanisms was limited, and it has only been in the last decade that particular DNA damage response (DDR) pathways have been examined in the context of viral infections. One of the first reports addressing the interaction between a cellular DDR protein and HSV-1 was the observation by Lees-Miller et al . that DNA-dependent protein kinase catalytic subunit levels were depleted in an ICP0-dependent manner during Herpes simplex virus 1 infection. Since then, there have been numerous reports describing the interactions between HSV infection and cellular DDR pathways. Due to space limitations, this review will focus predominantly on the most recent observations regarding how HSV navigates a potentially hostile environment to replicate its genome.

Role of cellular adhesions in tissue dynamics spectroscopy

Science.gov (United States)

Merrill, Daniel A.; An, Ran; Turek, John; Nolte, David

2014-02-01

Cellular adhesions play a critical role in cell behavior, and modified expression of cellular adhesion compounds has been linked to various cancers. We tested the role of cellular adhesions in drug response by studying three cellular culture models: three-dimensional tumor spheroids with well-developed cellular adhesions and extracellular matrix (ECM), dense three-dimensional cell pellets with moderate numbers of adhesions, and dilute three-dimensional cell suspensions in agarose having few adhesions. Our technique for measuring the drug response for the spheroids and cell pellets was biodynamic imaging (BDI), and for the suspensions was quasi-elastic light scattering (QELS). We tested several cytoskeletal chemotherapeutic drugs (nocodazole, cytochalasin-D, paclitaxel, and colchicine) on three cancer cell lines chosen from human colorectal adenocarcinoma (HT-29), human pancreatic carcinoma (MIA PaCa-2), and rat osteosarcoma (UMR-106) to exhibit differences in adhesion strength. Comparing tumor spheroid behavior to that of cell suspensions showed shifts in the spectral motion of the cancer tissues that match predictions based on different degrees of cell-cell contacts. The HT-29 cell line, which has the strongest adhesions in the spheroid model, exhibits anomalous behavior in some cases. These results highlight the importance of using three-dimensional tissue models in drug screening with cellular adhesions being a contributory factor in phenotypic differences between the drug responses of tissue and cells.

A federation of simulations based on cellular automata in cyber-physical systems

Directory of Open Access Journals (Sweden)

Hoang Van Tran

2016-02-01

Full Text Available In cyber-physical system (CPS, cooperation between a variety of computational and physical elements usually poses difficulties to current modelling and simulation tools. Although much research has proposed to address those challenges, most solutions do not completely cover uncertain interactions in CPS. In this paper, we present a new approach to federate simulations for CPS. A federation is a combination of, and coordination between simulations upon a standard of communication. In addition, a mixed simulation is defined as several parallel simulations federated in a common time progress. Such simulations run on the models of physical systems, which are built based on cellular automata theory. The experimental results are performed on a federation of three simulations of forest fire spread, river pollution diffusion and wireless sensor network. The obtained results can be utilized to observe and predict the behaviours of physical systems in their interactions.

Cellular Prion Protein and Caveolin-1 Interaction in a Neuronal Cell Line Precedes Fyn/Erk 1/2 Signal Transduction

Directory of Open Access Journals (Sweden)

Mattia Toni

2006-01-01

Full Text Available It has been reported that cellular prion protein (PrPc is enriched in caveolae or caveolae-like domains with caveolin-1 (Cav-1 participating to signal transduction events by Fyn kinase recruitment. By using the Glutathione-S-transferase (GST-fusion proteins assay, we observed that PrPc strongly interacts in vitro with Cav-1. Thus, we ascertained the PrPc caveolar localization in a hypothalamic neuronal cell line (GN11, by confocal microscopy analysis, flotation on density gradient, and coimmunoprecipitation experiments. Following the anti-PrPc antibody-mediated stimulation of live GN11 cells, we observed that PrPc clustered on plasma membrane domains rich in Cav-1 in which Fyn kinase converged to be activated. After these events, a signaling cascade through p42/44 MAP kinase (Erk 1/2 was triggered, suggesting that following translocations from rafts to caveolae or caveolae-like domains PrPc could interact with Cav-1 and induce signal transduction events.

Error performance analysis in downlink cellular networks with interference management

KAUST Repository

Afify, Laila H.; Elsawy, Hesham; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim

2015-01-01

Modeling aggregate network interference in cellular networks has recently gained immense attention both in academia and industry. While stochastic geometry based models have succeeded to account for the cellular network geometry, they mostly

Cellular Automata Modelling of Photo-Induced Oxidation Processes in Molecularly Doped Polymers

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David M. Goldie

2016-11-01

Full Text Available The possibility of employing cellular automata (CA to model photo-induced oxidation processes in molecularly doped polymers is explored. It is demonstrated that the oxidation dynamics generated using CA models exhibit stretched-exponential behavior. This dynamical characteristic is in general agreement with an alternative analysis conducted using standard rate equations provided the molecular doping levels are sufficiently low to prohibit the presence of safe-sites which are impenetrable to dissolved oxygen. The CA models therefore offer the advantage of exploring the effect of dopant agglomeration which is difficult to assess from standard rate equation solutions. The influence of UV-induced bleaching or darkening upon the resulting oxidation dynamics may also be easily incorporated into the CA models and these optical effects are investigated for various photo-oxidation product scenarios. Output from the CA models is evaluated for experimental photo-oxidation data obtained from a series of hydrazone-doped polymers.

The modeling of predator-prey interactions

OpenAIRE

Muhammad Shakil; H. A. Wahab; Muhammad Naeem, et al.

2015-01-01

In this paper, we aim to study the interactions between the territorial animals like foxes and the rabbits. The territories for the foxes are considered to be the simple cells. The interactions between predator and its prey are represented by the chemical reactions which obey the mass action law. In this sense, we apply the mass action law for predator prey models and the quasi chemical approach is applied for the interactions between the predator and its prey to develop the modeled equations...

Towards a rigorous network of protein-protein interactions of the model sulfate reducer Desulfovibrio vulgaris Hildenborough.

Directory of Open Access Journals (Sweden)

Swapnil R Chhabra

Full Text Available Protein-protein interactions offer an insight into cellular processes beyond what may be obtained by the quantitative functional genomics tools of proteomics and transcriptomics. The aforementioned tools have been extensively applied to study Escherichia coli and other aerobes and more recently to study the stress response behavior of Desulfovibrio vulgaris Hildenborough, a model obligate anaerobe and sulfate reducer and the subject of this study. Here we carried out affinity purification followed by mass spectrometry to reconstruct an interaction network among 12 chromosomally encoded bait and 90 prey proteins based on 134 bait-prey interactions identified to be of high confidence. Protein-protein interaction data are often plagued by the lack of adequate controls and replication analyses necessary to assess confidence in the results, including identification of potential false positives. We addressed these issues through the use of biological replication, exponentially modified protein abundance indices, results from an experimental negative control, and a statistical test to assign confidence to each putative interacting pair applicable to small interaction data studies. We discuss the biological significance of metabolic features of D. vulgaris revealed by these protein-protein interaction data and the observed protein modifications. These include the distinct role of the putative carbon monoxide-induced hydrogenase, unique electron transfer routes associated with different oxidoreductases, and the possible role of methylation in regulating sulfate reduction.

Mobility-Aware Modeling and Analysis of Dense Cellular Networks With $C$ -Plane/ $U$ -Plane Split Architecture

KAUST Repository

Ibrahim, Hazem

2016-09-19

The unrelenting increase in the population of mobile users and their traffic demands drive cellular network operators to densify their network infrastructure. Network densification shrinks the footprint of base stations (BSs) and reduces the number of users associated with each BS, leading to an improved spatial frequency reuse and spectral efficiency, and thus, higher network capacity. However, the densification gain comes at the expense of higher handover rates and network control overhead. Hence, user’s mobility can diminish or even nullifies the foreseen densification gain. In this context, splitting the control plane ( C -plane) and user plane ( U -plane) is proposed as a potential solution to harvest densification gain with reduced cost in terms of handover rate and network control overhead. In this paper, we use stochastic geometry to develop a tractable mobility-aware model for a two-tier downlink cellular network with ultra-dense small cells and C -plane/ U -plane split architecture. The developed model is then used to quantify the effect of mobility on the foreseen densification gain with and without C -plane/ U -plane split. To this end, we shed light on the handover problem in dense cellular environments, show scenarios where the network fails to support certain mobility profiles, and obtain network design insights.

Using a Cellular Automata-Markov Model to Reconstruct Spatial Land-Use Patterns in Zhenlai County, Northeast China

Directory of Open Access Journals (Sweden)

Yuanyuan Yang

2015-05-01

Full Text Available Decadal to centennial land use and land cover change has been consistently singled out as a key element and an important driver of global environmental change, playing an essential role in balancing energy use. Understanding long-term human-environment interactions requires historical reconstruction of past land use and land cover changes. Most of the existing historical reconstructions have insufficient spatial and thematic detail and do not consider various land change types. In this context, this paper explored the possibility of using a cellular automata-Markov model in 90 m × 90 m spatial resolution to reconstruct historical land use in the 1930s in Zhenlai County, China. Then the three-map comparison methodology was employed to assess the predictive accuracy of the transition modeling. The model could produce backward projections by analyzing land use changes in recent decades, assuming that the present land use pattern is dynamically dependent on the historical one. The reconstruction results indicated that in the 1930s most of the study area was occupied by grasslands, followed by wetlands and arable land, while other land categories occupied relatively small areas. Analysis of the three-map comparison illustrated that the major differences among the three maps have less to do with the simulation model and more to do with the inconsistencies among the land categories during the study period. Different information provided by topographic maps and remote sensing images must be recognized.

Micropatterned co-culture of hepatocyte spheroids layered on non-parenchymal cells to understand heterotypic cellular interactions

International Nuclear Information System (INIS)

Otsuka, Hidenori; Sasaki, Kohei; Okimura, Saya; Nagamura, Masako; Nakasone, Yuichi

2013-01-01

Microfabrication and micropatterning techniques in tissue engineering offer great potential for creating and controlling cellular microenvironments including cell–matrix interactions, soluble stimuli and cell–cell interactions. Here, we present a novel approach to generate layered patterning of hepatocyte spheroids on micropatterned non-parenchymal feeder cells using microfabricated poly(ethylene glycol) (PEG) hydrogels. Micropatterned PEG-hydrogel-treated substrates with two-dimensional arrays of gelatin circular domains (ϕ = 100 μm) were prepared by photolithographic method. Only on the critical structure of PEG hydrogel with perfect protein rejection, hepatocytes were co-cultured with non-parenchymal cells to be led to enhanced hepatocyte functions. Then, we investigated the mechanism of the functional enhancement in co-culture with respect to the contributions of soluble factors and direct cell–cell interactions. In particular, to elucidate the influence of soluble factors on hepatocyte function, hepatocyte spheroids underlaid with fibroblasts (NIH/3T3 mouse fibroblasts) or endothelial cells (BAECs: bovine aortic endothelial cells) were compared with physically separated co-culture of hepatocyte monospheroids with NIH3T3 or BAEC using trans-well culture systems. Our results suggested that direct heterotypic cell-to-cell contact and soluble factors, both of these between hepatocytes and fibroblasts, significantly enhanced hepatocyte functions. In contrast, direct heterotypic cell-to-cell contact between hepatocytes and endothelial cells only contributed to enhance hepatocyte functions. This patterning technique can be a useful experimental tool for applications in basic science, drug screening and tissue engineering, as well as in the design of artificial liver devices. (paper)

Molecular and cellular neurocardiology: development, and cellular and molecular adaptations to heart disease

Science.gov (United States)

Anderson, Mark E.; Birren, Susan J.; Fukuda, Keiichi; Herring, Neil; Hoover, Donald B.; Kanazawa, Hideaki; Paterson, David J.; Ripplinger, Crystal M.

2016-01-01

Abstract The nervous system and cardiovascular system develop in concert and are functionally interconnected in both health and disease. This white paper focuses on the cellular and molecular mechanisms that underlie neural–cardiac interactions during development, during normal physiological function in the mature system, and during pathological remodelling in cardiovascular disease. The content on each subject was contributed by experts, and we hope that this will provide a useful resource for newcomers to neurocardiology as well as aficionados. PMID:27060296

Marginal and Interaction Effects in Ordered Response Models

OpenAIRE

Debdulal Mallick

2009-01-01

In discrete choice models the marginal effect of a variable of interest that is interacted with another variable differs from the marginal effect of a variable that is not interacted with any variable. The magnitude of the interaction effect is also not equal to the marginal effect of the interaction term. I present consistent estimators of both marginal and interaction effects in ordered response models. This procedure is general and can easily be extended to other discrete choice models. I ...

Modelling sediment dynamics due to hillslope-river interactions : incorporating fluvial behaviour in landscape evolution model LAPSUS

NARCIS (Netherlands)

Baartman, Jantiene E. M.; van Gorp, Wouter; Temme, Arnaud J. A. M.; Schoorl, Jeroen M.

Landscape evolution models (LEMs) simulate the three-dimensional development of landscapes over time. Different LEMs have different foci, e.g. erosional behaviour, river dynamics, the fluvial domain, hillslopes or a combination. LEM LAPSUS is a relatively simple cellular model operating on

Dynamic PET scanning and compartmental model analysis to determine cellular level radiotracer distribution in vivo

International Nuclear Information System (INIS)

Smith, G.T.; Hubner, K.F.; Goodman, M.M.; Stubbs, J.B.

1992-01-01

Positron emission tomography (PET) has been used to measure tissue radiotracer concentration in vivo. Radiochemical distribution can be determined with compartmental model analysis. A two compartment model describes the kinetics of N-13 ammonia ( 13 NH 3 ) in the myocardium. The model consists of a vascular space, Q 1 and a space for 13 NH 3 bound within the tissue, Q 2 . Differential equations for the model can be written: X(t) = AX(t) + BU( t), Y(t)= CX(t)+ DU(t) (1) where X(t) is a column vector [Q 1 (t); Q 2 (t)], U(t) is the arterial input activity measured from the left ventricular blood pool, and Y(t) is the measured tissue activity using PET. Matrices A, B, C, and D are dependent on physiological parameters describing the kinetics of 13 NH 3 in the myocardium. Estimated parameter matrices in Equation 1 have been validated in dog experiments by measuring myocardial perfusion with dynamic PET scanning and intravenous injection of 13 NH 3 . Tracer concentrations for each compartment can be calculated by direct integration of Equation 1. If the cellular level distribution of each compartment is known, the concentration of tracer within the intracellular and extracellular space can be determined. Applications of this type of modeling include parameter estimation for measurement of physiological processes, organ level dosimetry, and determination of cellular radiotracer distribution

Deep Predictive Models in Interactive Music

OpenAIRE

Martin, Charles P.; Ellefsen, Kai Olav; Torresen, Jim

2018-01-01

Automatic music generation is a compelling task where much recent progress has been made with deep learning models. In this paper, we ask how these models can be integrated into interactive music systems; how can they encourage or enhance the music making of human users? Musical performance requires prediction to operate instruments, and perform in groups. We argue that predictive models could help interactive systems to understand their temporal context, and ensemble behaviour. Deep learning...

The Monash University Interactive Simple Climate Model

Science.gov (United States)

Dommenget, D.

2013-12-01

The Monash university interactive simple climate model is a web-based interface that allows students and the general public to explore the physical simulation of the climate system with a real global climate model. It is based on the Globally Resolved Energy Balance (GREB) model, which is a climate model published by Dommenget and Floeter [2011] in the international peer review science journal Climate Dynamics. The model simulates most of the main physical processes in the climate system in a very simplistic way and therefore allows very fast and simple climate model simulations on a normal PC computer. Despite its simplicity the model simulates the climate response to external forcings, such as doubling of the CO2 concentrations very realistically (similar to state of the art climate models). The Monash simple climate model web-interface allows you to study the results of more than a 2000 different model experiments in an interactive way and it allows you to study a number of tutorials on the interactions of physical processes in the climate system and solve some puzzles. By switching OFF/ON physical processes you can deconstruct the climate and learn how all the different processes interact to generate the observed climate and how the processes interact to generate the IPCC predicted climate change for anthropogenic CO2 increase. The presentation will illustrate how this web-base tool works and what are the possibilities in teaching students with this tool are.

Relativistic direct interaction and hadron models

International Nuclear Information System (INIS)

Biswas, T.

1984-01-01

Direct interaction theories at a nonrelativistic level have been used successfully in several areas earlier (e.g. nuclear physics). But for hadron spectroscopy relativistic effects are important and hence the need for a relativistic direct interaction theory arises. It is the goal of this thesis to suggest such a theory which has the simplicity and the flexibility required for phenomenological model building. In general the introduction of relativity in a direct interaction theory is shown to be non-trivial. A first attempt leads to only an approximate form for allowed interactions. Even this is far too complex for phenomenological applicability. To simplify the model an extra spacelike particle called the vertex is introduced in any set of physical (timelike) particles. The vertex model is successfully used to fit and to predict experimental data on hadron spectra, γ and psi states fit very well with an interaction function inspired by QCD. Light mesons also fit reasonably well. Better forms of hyperfine interaction functions would be needed to improve the fitting of light mesons. The unexpectedly low pi meson mass is partially explained. Baryon ground states are fitted with unprecedented accuracy with very few adjustable parameters. For baryon excited states it is shown that better QCD motivated interaction functions are needed for a fit. Predictions for bb states in e + e - experiments are made to assist current experiments

Evaluation of the Cytotoxicity and Genotoxicity of Flavonolignans in Different Cellular Models

Directory of Open Access Journals (Sweden)

Michal Bijak

2017-12-01

Full Text Available Flavonolignans are the main components of silymarin, which represents 1.5–3% of the dry fruit weight of Milk thistle (Silybum marianum L. Gaernt.. In ancient Greece and Romania, physicians and herbalists used the Silybum marianum to treat a range of liver diseases. Besides their hepatoprotective action, silymarin flavonolignans have many other healthy properties, such as anti-platelet and anti-inflammatory actions. The aim of this study was to evaluate the toxic effect of flavonolignans on blood platelets, peripheral blood mononuclear cells (PBMCs and human lung cancer cell line—A549—using different molecular techniques. We established that three major flavonolignans: silybin, silychristin and silydianin, in concentrations of up to 100 µM, have neither a cytotoxic nor genotoxic effect on blood platelets, PMBCs and A549. We also saw that silybin and silychristin have a protective effect on cellular mitochondria, observed as a reduction of spontaneous mitochondrial DNA (mtDNA damage in A549, measured as mtDNA copies, and mtDNA lesions in ND1 and ND5 genes. Additionally, we observed that flavonolignans increase the blood platelets’ mitochondrial membrane potential and reduce the generation of reactive oxygen species in blood platelets. Our current findings show for the first time that the three major flavonolignans, silybin, silychristin and silydianin, do not have any cytotoxicity and genotoxicity in various cellular models, and that they actually protect cellular mitochondria. This proves that the antiplatelet and anti-inflammatory effect of these compounds is part of our molecular health mechanisms.

Multiscale modeling of porous ceramics using movable cellular automaton method

Science.gov (United States)

Smolin, Alexey Yu.; Smolin, Igor Yu.; Smolina, Irina Yu.

2017-10-01

The paper presents a multiscale model for porous ceramics based on movable cellular automaton method, which is a particle method in novel computational mechanics of solid. The initial scale of the proposed approach corresponds to the characteristic size of the smallest pores in the ceramics. At this scale, we model uniaxial compression of several representative samples with an explicit account of pores of the same size but with the unique position in space. As a result, we get the average values of Young's modulus and strength, as well as the parameters of the Weibull distribution of these properties at the current scale level. These data allow us to describe the material behavior at the next scale level were only the larger pores are considered explicitly, while the influence of small pores is included via effective properties determined earliar. If the pore size distribution function of the material has N maxima we need to perform computations for N-1 levels in order to get the properties step by step from the lowest scale up to the macroscale. The proposed approach was applied to modeling zirconia ceramics with bimodal pore size distribution. The obtained results show correct behavior of the model sample at the macroscale.

Model Checking Feature Interactions

DEFF Research Database (Denmark)

Le Guilly, Thibaut; Olsen, Petur; Pedersen, Thomas

2015-01-01

This paper presents an offline approach to analyzing feature interactions in embedded systems. The approach consists of a systematic process to gather the necessary information about system components and their models. The model is first specified in terms of predicates, before being refined to t...... to timed automata. The consistency of the model is verified at different development stages, and the correct linkage between the predicates and their semantic model is checked. The approach is illustrated on a use case from home automation....

Glider-based computing in reaction-diffusion hexagonal cellular automata

International Nuclear Information System (INIS)

Adamatzky, Andrew; Wuensche, Andrew; De Lacy Costello, Benjamin

2006-01-01

A three-state hexagonal cellular automaton, discovered in [Wuensche A. Glider dynamics in 3-value hexagonal cellular automata: the beehive rule. Int J Unconvention Comput, in press], presents a conceptual discrete model of a reaction-diffusion system with inhibitor and activator reagents. The automaton model of reaction-diffusion exhibits mobile localized patterns (gliders) in its space-time dynamics. We show how to implement the basic computational operations with these mobile localizations, and thus demonstrate collision-based logical universality of the hexagonal reaction-diffusion cellular automaton

Computational Modeling of Proteins based on Cellular Automata: A Method of HP Folding Approximation.

Science.gov (United States)

Madain, Alia; Abu Dalhoum, Abdel Latif; Sleit, Azzam

2018-06-01

The design of a protein folding approximation algorithm is not straightforward even when a simplified model is used. The folding problem is a combinatorial problem, where approximation and heuristic algorithms are usually used to find near optimal folds of proteins primary structures. Approximation algorithms provide guarantees on the distance to the optimal solution. The folding approximation approach proposed here depends on two-dimensional cellular automata to fold proteins presented in a well-studied simplified model called the hydrophobic-hydrophilic model. Cellular automata are discrete computational models that rely on local rules to produce some overall global behavior. One-third and one-fourth approximation algorithms choose a subset of the hydrophobic amino acids to form H-H contacts. Those algorithms start with finding a point to fold the protein sequence into two sides where one side ignores H's at even positions and the other side ignores H's at odd positions. In addition, blocks or groups of amino acids fold the same way according to a predefined normal form. We intend to improve approximation algorithms by considering all hydrophobic amino acids and folding based on the local neighborhood instead of using normal forms. The CA does not assume a fixed folding point. The proposed approach guarantees one half approximation minus the H-H endpoints. This lower bound guaranteed applies to short sequences only. This is proved as the core and the folds of the protein will have two identical sides for all short sequences.

A mathematical model in cellular manufacturing system considering subcontracting approach under constraints

Directory of Open Access Journals (Sweden)

Kamran Forghani

2012-10-01

Full Text Available In this paper, a new mathematical model in cellular manufacturing systems (CMSs has been presented. In order to increase the performance of manufacturing system, the production quantity of parts has been considered as a decision variable, i.e. each part can be produced and outsourced, simultaneously. This extension would be minimized the unused capacity of machines. The exceptional elements (EEs are taken into account and would be totally outsourced to the external supplier in order to remove intercellular material handling cost. The problem has been formulated as a mixed-integer programming to minimize the sum of manufacturing variable costs under budget, machines capacity and demand constraints. Also, to evaluate advantages of the model, several illustrative numerical examples have been provided to compare the performance of the proposed model with the available classical approaches in the literature.

Cellular dynamics of bovine aortic smooth muscle cells measured using MEMS force sensors

Science.gov (United States)

Tsukagoshi, Takuya; Nguyen, Thanh-Vinh; Hirayama Shoji, Kayoko; Takahashi, Hidetoshi; Matsumoto, Kiyoshi; Shimoyama, Isao

2018-04-01

Adhesive cells perceive the mechanical properties of the substrates to which they adhere, adjusting their cellular mechanical forces according to their biological characteristics. This mechanical interaction subsequently affects the growth, locomotion, and differentiation of the cell. However, little is known about the detailed mechanism that underlies this interaction between adherent cells and substrates because dynamically measuring mechanical phenomena is difficult. Here, we utilize microelectromechamical systems force sensors that can measure cellular traction forces with high temporal resolution (~2.5 µs) over long periods (~3 h). We found that the cellular dynamics reflected physical phenomena with time scales from milliseconds to hours, which contradicts the idea that cellular motion is slow. A single focal adhesion (FA) generates an average force of 7 nN, which disappears in ms via the action of trypsin-ethylenediaminetetraacetic acid. The force-changing rate obtained from our measurements suggests that the time required for an FA to decompose was nearly proportional to the force acting on the FA.

Cellular and Molecular Anesthesia: from Bench to Bedside

Directory of Open Access Journals (Sweden)

Ali Dabbagh

2015-12-01

Full Text Available Cellular and Molecular Anesthesia: from Bench to BedsideIn the current practice of anesthesia, each day, anesthesiologists deal with a great work: they use the cellular mechanisms of drug molecules to induce their desired effects for induction and maintenance of anesthesia to achieve appropriate tolerance of surgery and its pain, modulation of stress response, sedation needed for performing a variety of procedures, emergency anesthesia care, acute and chronic pain management or other everyday jobs of anesthesiologists during perioperative period.As a matter of fact, molecular anesthesia has been cited for more than 6 decades though in avery limited scale. In 1956, the molecular mechanisms of morphine and pethidine are described (1. Pauling in 1961 published an article in Science describing a molecular theorey for general anesthesia (2.In its report “the World in 2025”, Thomson Reuters has predicted clinical medicine would be the most active research front; while molecular biology has the 9th rank (3. But are we still practicing in clinic the same as today?In fact, the future trend of anesthesia is highly dependent on finding the novel cellular and molecular mechanisms and the possible interactions of the newly discovered molecules and inreraction mechanisms with organ systems. Today, we emphasize on the role of pharmacologists, physiologists, immunologists, anatomists, embryologists, geneticians, cellular medicine specialists, physicists and other basic science specialists; some very interesting examples are published in this volume of the Journal (4-7.However, changes that have well started now would “revolutionize” our daily practice during the next decade in such a way that it will change the basis of medicine: presumably we will have a new model medicine known as “personalized medicine” or “precision medicine”. In this approach, the content of each patient’s genes accompanied with his/her cellular and molecular analysis is

A model of tumor architecture and spatial interactions with tumor microenvironment in breast carcinoma

Science.gov (United States)

Ben Cheikh, Bassem; Bor-Angelier, Catherine; Racoceanu, Daniel

2017-03-01

Breast carcinomas are cancers that arise from the epithelial cells of the breast, which are the cells that line the lobules and the lactiferous ducts. Breast carcinoma is the most common type of breast cancer and can be divided into different subtypes based on architectural features and growth patterns, recognized during a histopathological examination. Tumor microenvironment (TME) is the cellular environment in which tumor cells develop. Being composed of various cell types having different biological roles, TME is recognized as playing an important role in the progression of the disease. The architectural heterogeneity in breast carcinomas and the spatial interactions with TME are, to date, not well understood. Developing a spatial model of tumor architecture and spatial interactions with TME can advance our understanding of tumor heterogeneity. Furthermore, generating histological synthetic datasets can contribute to validating, and comparing analytical methods that are used in digital pathology. In this work, we propose a modeling method that applies to different breast carcinoma subtypes and TME spatial distributions based on mathematical morphology. The model is based on a few morphological parameters that give access to a large spectrum of breast tumor architectures and are able to differentiate in-situ ductal carcinomas (DCIS) and histological subtypes of invasive carcinomas such as ductal (IDC) and lobular carcinoma (ILC). In addition, a part of the parameters of the model controls the spatial distribution of TME relative to the tumor. The validation of the model has been performed by comparing morphological features between real and simulated images.

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