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

PubMed

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

2012-02-28

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

ReaDDy - A Software for Particle-Based Reaction-Diffusion Dynamics in Crowded Cellular Environments

PubMed Central

Schöneberg, Johannes; Noé, Frank

2013-01-01

We introduce the software package ReaDDy for simulation of detailed spatiotemporal mechanisms of dynamical processes in the cell, based on reaction-diffusion dynamics with particle resolution. In contrast to other particle-based reaction kinetics programs, ReaDDy supports particle interaction potentials. This permits effects such as space exclusion, molecular crowding and aggregation to be modeled. The biomolecules simulated can be represented as a sphere, or as a more complex geometry such as a domain structure or polymer chain. ReaDDy bridges the gap between small-scale but highly detailed molecular dynamics or Brownian dynamics simulations and large-scale but little-detailed reaction kinetics simulations. ReaDDy has a modular design that enables the exchange of the computing core by efficient platform-specific implementations or dynamical models that are different from Brownian dynamics. PMID:24040218

Quantifying time-varying cellular secretions with local linear models.

PubMed

Byers, Jeff M; Christodoulides, Joseph A; Delehanty, James B; Raghu, Deepa; Raphael, Marc P

2017-07-01

Extracellular protein concentrations and gradients initiate a wide range of cellular responses, such as cell motility, growth, proliferation and death. Understanding inter-cellular communication requires spatio-temporal knowledge of these secreted factors and their causal relationship with cell phenotype. Techniques which can detect cellular secretions in real time are becoming more common but generalizable data analysis methodologies which can quantify concentration from these measurements are still lacking. Here we introduce a probabilistic approach in which local-linear models and the law of mass action are applied to obtain time-varying secreted concentrations from affinity-based biosensor data. We first highlight the general features of this approach using simulated data which contains both static and time-varying concentration profiles. Next we apply the technique to determine concentration of secreted antibodies from 9E10 hybridoma cells as detected using nanoplasmonic biosensors. A broad range of time-dependent concentrations was observed: from steady-state secretions of 230 pM near the cell surface to large transients which reached as high as 56 nM over several minutes and then dissipated.

Bypass transition and spot nucleation in boundary layers

NASA Astrophysics Data System (ADS)

Kreilos, Tobias; Khapko, Taras; Schlatter, Philipp; Duguet, Yohann; Henningson, Dan S.; Eckhardt, Bruno

2016-08-01

The spatiotemporal aspects of the transition to turbulence are considered in the case of a boundary-layer flow developing above a flat plate exposed to free-stream turbulence. Combining results on the receptivity to free-stream turbulence with the nonlinear concept of a transition threshold, a physically motivated model suggests a spatial distribution of spot nucleation events. To describe the evolution of turbulent spots a probabilistic cellular automaton is introduced, with all parameters directly obtained from numerical simulations of the boundary layer. The nucleation rates are then combined with the cellular automaton model, yielding excellent quantitative agreement with the statistical characteristics for different free-stream turbulence levels. We thus show how the recent theoretical progress on transitional wall-bounded flows can be extended to the much wider class of spatially developing boundary-layer flows.

Cellular processing of gold nanoparticles: CE-ICP-MS evidence for the speciation changes in human cytosol.

PubMed

Legat, Joanna; Matczuk, Magdalena; Timerbaev, Andrei R; Jarosz, Maciej

2018-01-01

The cellular uptake of gold nanoparticles (AuNPs) may (or may not) affect their speciation, but information on the chemical forms in which the particles exist in the cell remains obscure. An analytical method based on the use of capillary electrophoresis hyphenated with inductively coupled plasma mass spectrometry (ICP-MS) has been proposed to shed light on the intracellular processing of AuNPs. It was observed that when being introduced into normal cytosol, the conjugates of 10-50 nm AuNPs with albumin evolved in human serum stayed intact. On the contrary, under simulated cancer cytosol conditions, the nanoconjugates underwent decomposition, the rate of which and the resulting metal speciation patterns were strongly influenced by particle size. The new peaks that appeared in ICP-MS electropherograms could be ascribed to nanosized species, as upon ultracentrifugation, they quantitatively precipitated whereas the supernatant showed only trace Au signals. Our present study is the first step to unravel a mystery of the cellular chemistry for metal-based nanomedicines.

A membrane computing simulator of trans-hierarchical antibiotic resistance evolution dynamics in nested ecological compartments (ARES).

PubMed

Campos, Marcelino; Llorens, Carlos; Sempere, José M; Futami, Ricardo; Rodriguez, Irene; Carrasco, Purificación; Capilla, Rafael; Latorre, Amparo; Coque, Teresa M; Moya, Andres; Baquero, Fernando

2015-08-05

Antibiotic resistance is a major biomedical problem upon which public health systems demand solutions to construe the dynamics and epidemiological risk of resistant bacteria in anthropogenically-altered environments. The implementation of computable models with reciprocity within and between levels of biological organization (i.e. essential nesting) is central for studying antibiotic resistances. Antibiotic resistance is not just the result of antibiotic-driven selection but more properly the consequence of a complex hierarchy of processes shaping the ecology and evolution of the distinct subcellular, cellular and supra-cellular vehicles involved in the dissemination of resistance genes. Such a complex background motivated us to explore the P-system standards of membrane computing an innovative natural computing formalism that abstracts the notion of movement across membranes to simulate antibiotic resistance evolution processes across nested levels of micro- and macro-environmental organization in a given ecosystem. In this article, we introduce ARES (Antibiotic Resistance Evolution Simulator) a software device that simulates P-system model scenarios with five types of nested computing membranes oriented to emulate a hierarchy of eco-biological compartments, i.e. a) peripheral ecosystem; b) local environment; c) reservoir of supplies; d) animal host; and e) host's associated bacterial organisms (microbiome). Computational objects emulating molecular entities such as plasmids, antibiotic resistance genes, antimicrobials, and/or other substances can be introduced into this framework and may interact and evolve together with the membranes, according to a set of pre-established rules and specifications. ARES has been implemented as an online server and offers additional tools for storage and model editing and downstream analysis. The stochastic nature of the P-system model implemented in ARES explicitly links within and between host dynamics into a simulation, with feedback reciprocity among the different units of selection influenced by antibiotic exposure at various ecological levels. ARES offers the possibility of modeling predictive multilevel scenarios of antibiotic resistance evolution that can be interrogated, edited and re-simulated if necessary, with different parameters, until a correct model description of the process in the real world is convincingly approached. ARES can be accessed at http://gydb.org/ares.

cellGPU: Massively parallel simulations of dynamic vertex models

NASA Astrophysics Data System (ADS)

Sussman, Daniel M.

2017-10-01

Vertex models represent confluent tissue by polygonal or polyhedral tilings of space, with the individual cells interacting via force laws that depend on both the geometry of the cells and the topology of the tessellation. This dependence on the connectivity of the cellular network introduces several complications to performing molecular-dynamics-like simulations of vertex models, and in particular makes parallelizing the simulations difficult. cellGPU addresses this difficulty and lays the foundation for massively parallelized, GPU-based simulations of these models. This article discusses its implementation for a pair of two-dimensional models, and compares the typical performance that can be expected between running cellGPU entirely on the CPU versus its performance when running on a range of commercial and server-grade graphics cards. By implementing the calculation of topological changes and forces on cells in a highly parallelizable fashion, cellGPU enables researchers to simulate time- and length-scales previously inaccessible via existing single-threaded CPU implementations. Program Files doi:http://dx.doi.org/10.17632/6j2cj29t3r.1 Licensing provisions: MIT Programming language: CUDA/C++ Nature of problem: Simulations of off-lattice "vertex models" of cells, in which the interaction forces depend on both the geometry and the topology of the cellular aggregate. Solution method: Highly parallelized GPU-accelerated dynamical simulations in which the force calculations and the topological features can be handled on either the CPU or GPU. Additional comments: The code is hosted at https://gitlab.com/dmsussman/cellGPU, with documentation additionally maintained at http://dmsussman.gitlab.io/cellGPUdocumentation

Self-organisation in Cellular Automata with Coalescent Particles: Qualitative and Quantitative Approaches

NASA Astrophysics Data System (ADS)

Hellouin de Menibus, Benjamin; Sablik, Mathieu

2017-06-01

This article introduces new tools to study self-organisation in a family of simple cellular automata which contain some particle-like objects with good collision properties (coalescence) in their time evolution. We draw an initial configuration at random according to some initial shift-ergodic measure, and use the limit measure to describe the asymptotic behaviour of the automata. We first take a qualitative approach, i.e. we obtain information on the limit measure(s). We prove that only particles moving in one particular direction can persist asymptotically. This provides some previously unknown information on the limit measures of various deterministic and probabilistic cellular automata: 3 and 4-cyclic cellular automata [introduced by Fisch (J Theor Probab 3(2):311-338, 1990; Phys D 45(1-3):19-25, 1990)], one-sided captive cellular automata [introduced by Theyssier (Captive Cellular Automata, 2004)], the majority-traffic cellular automaton, a self stabilisation process towards a discrete line [introduced by Regnault and Rémila (in: Mathematical Foundations of Computer Science 2015—40th International Symposium, MFCS 2015, Milan, Italy, Proceedings, Part I, 2015)]. In a second time we restrict our study to a subclass, the gliders cellular automata. For this class we show quantitative results, consisting in the asymptotic law of some parameters: the entry times [generalising K ůrka et al. (in: Proceedings of AUTOMATA, 2011)], the density of particles and the rate of convergence to the limit measure.

Meta-heuristic algorithms as tools for hydrological science

NASA Astrophysics Data System (ADS)

Yoo, Do Guen; Kim, Joong Hoon

2014-12-01

In this paper, meta-heuristic optimization techniques are introduced and their applications to water resources engineering, particularly in hydrological science are introduced. In recent years, meta-heuristic optimization techniques have been introduced that can overcome the problems inherent in iterative simulations. These methods are able to find good solutions and require limited computation time and memory use without requiring complex derivatives. Simulation-based meta-heuristic methods such as Genetic algorithms (GAs) and Harmony Search (HS) have powerful searching abilities, which can occasionally overcome the several drawbacks of traditional mathematical methods. For example, HS algorithms can be conceptualized from a musical performance process and used to achieve better harmony; such optimization algorithms seek a near global optimum determined by the value of an objective function, providing a more robust determination of musical performance than can be achieved through typical aesthetic estimation. In this paper, meta-heuristic algorithms and their applications (focus on GAs and HS) in hydrological science are discussed by subject, including a review of existing literature in the field. Then, recent trends in optimization are presented and a relatively new technique such as Smallest Small World Cellular Harmony Search (SSWCHS) is briefly introduced, with a summary of promising results obtained in previous studies. As a result, previous studies have demonstrated that meta-heuristic algorithms are effective tools for the development of hydrological models and the management of water resources.

Introducing nuclei scatterer patterns into histology based intravascular ultrasound simulation framework

NASA Astrophysics Data System (ADS)

Kraft, Silvan; Karamalis, Athanasios; Sheet, Debdoot; Drecoll, Enken; Rummeny, Ernst J.; Navab, Nassir; Noël, Peter B.; Katouzian, Amin

2013-03-01

Medical ultrasonic grayscale images are formed from acoustic waves following their interactions with distributed scatterers within tissues media. For accurate simulation of acoustic wave propagation, a reliable model describing unknown parameters associated with tissues scatterers such as distribution, size and acoustic properties is essential. In this work, we introduce a novel approach defining ultrasonic scatterers by incorporating a distribution of cellular nuclei patterns in biological tissues to simulate ultrasonic response of atherosclerotic tissues in intravascular ultrasound (IVUS). For this reason, a virtual phantom is generated through manual labeling of different tissue types (fibrotic, lipidic and calcified) on histology sections. Acoustic properties of each tissue type are defined by assuming that the ultrasound signal is primarily backscattered by the nuclei of the organic cells within the intima and media of the vessel wall. This resulting virtual phantom is subsequently used to simulate ultrasonic wave propagation through the tissue medium computed using finite difference estimation. Subsequently B-mode images for a specific histological section are processed from the simulated radiofrequency (RF) data and compared with the original IVUS of the same tissue section. Real IVUS RF signals for these histological sections were obtained using a single-element mechanically rotating 40MHz transducer. Evaluation is performed by trained reviewers subjectively assessing both simulated and real B-mode IVUS images. Our simulation platform provides a high image quality with a very promising correlation to the original IVUS images. This will facilitate to better understand progression of such a chronic disease from micro-level and its integration into cardiovascular disease-specific models.

a Discrete Mathematical Model to Simulate Malware Spreading

NASA Astrophysics Data System (ADS)

Del Rey, A. Martin; Sánchez, G. Rodriguez

2012-10-01

With the advent and worldwide development of Internet, the study and control of malware spreading has become very important. In this sense, some mathematical models to simulate malware propagation have been proposed in the scientific literature, and usually they are based on differential equations exploiting the similarities with mathematical epidemiology. The great majority of these models study the behavior of a particular type of malware called computer worms; indeed, to the best of our knowledge, no model has been proposed to simulate the spreading of a computer virus (the traditional type of malware which differs from computer worms in several aspects). In this sense, the purpose of this work is to introduce a new mathematical model not based on continuous mathematics tools but on discrete ones, to analyze and study the epidemic behavior of computer virus. Specifically, cellular automata are used in order to design such model.

PetriScape - A plugin for discrete Petri net simulations in Cytoscape.

PubMed

Almeida, Diogo; Azevedo, Vasco; Silva, Artur; Baumbach, Jan

2016-06-04

Systems biology plays a central role for biological network analysis in the post-genomic era. Cytoscape is the standard bioinformatics tool offering the community an extensible platform for computational analysis of the emerging cellular network together with experimental omics data sets. However, only few apps/plugins/tools are available for simulating network dynamics in Cytoscape 3. Many approaches of varying complexity exist but none of them have been integrated into Cytoscape as app/plugin yet. Here, we introduce PetriScape, the first Petri net simulator for Cytoscape. Although discrete Petri nets are quite simplistic models, they are capable of modeling global network properties and simulating their behaviour. In addition, they are easily understood and well visualizable. PetriScape comes with the following main functionalities: (1) import of biological networks in SBML format, (2) conversion into a Petri net, (3) visualization as Petri net, and (4) simulation and visualization of the token flow in Cytoscape. PetriScape is the first Cytoscape plugin for Petri nets. It allows a straightforward Petri net model creation, simulation and visualization with Cytoscape, providing clues about the activity of key components in biological networks.

PetriScape - A plugin for discrete Petri net simulations in Cytoscape.

PubMed

Almeida, Diogo; Azevedo, Vasco; Silva, Artur; Baumbach, Jan

2016-03-01

Systems biology plays a central role for biological network analysis in the post-genomic era. Cytoscape is the standard bioinformatics tool offering the community an extensible platform for computational analysis of the emerging cellular network together with experimental omics data sets. However, only few apps/plugins/tools are available for simulating network dynamics in Cytoscape 3. Many approaches of varying complexity exist but none of them have been integrated into Cytoscape as app/plugin yet. Here, we introduce PetriScape, the first Petri net simulator for Cytoscape. Although discrete Petri nets are quite simplistic models, they are capable of modeling global network properties and simulating their behaviour. In addition, they are easily understood and well visualizable. PetriScape comes with the following main functionalities: (1) import of biological networks in SBML format, (2) conversion into a Petri net, (3) visualization as Petri net, and (4) simulation and visualization of the token flow in Cytoscape. PetriScape is the first Cytoscape plugin for Petri nets. It allows a straightforward Petri net model creation, simulation and visualization with Cytoscape, providing clues about the activity of key components in biological networks.

Smart Bandwidth Assignation in an Underlay Cellular Network for Internet of Vehicles.

PubMed

de la Iglesia, Idoia; Hernandez-Jayo, Unai; Osaba, Eneko; Carballedo, Roberto

2017-09-27

The evolution of the IoT (Internet of Things) paradigm applied to new scenarios as VANETs (Vehicular Ad Hoc Networks) has gained momentum in recent years. Both academia and industry have triggered advanced studies in the IoV (Internet of Vehicles), which is understood as an ecosystem where different types of users (vehicles, elements of the infrastructure, pedestrians) are connected. How to efficiently share the available radio resources among the different types of eligible users is one of the important issues to be addressed. This paper briefly analyzes various concepts presented hitherto in the literature and it proposes an enhanced algorithm for ensuring a robust co-existence of the aforementioned system users. Therefore, this paper introduces an underlay RRM (Radio Resource Management) methodology which is capable of (1) improving cellular spectral efficiency while making a minimal impact on cellular communications and (2) ensuring the different QoS (Quality of Service) requirements of ITS (Intelligent Transportation Systems) applications. Simulation results, where we compare the proposed algorithm to the other two RRM, show the promising spectral efficiency performance of the proposed RRM methodology.

Smart Bandwidth Assignation in an Underlay Cellular Network for Internet of Vehicles

PubMed Central

de la Iglesia, Idoia; Hernandez-Jayo, Unai

2017-01-01

The evolution of the IoT (Internet of Things) paradigm applied to new scenarios as VANETs (Vehicular Ad Hoc Networks) has gained momentum in recent years. Both academia and industry have triggered advanced studies in the IoV (Internet of Vehicles), which is understood as an ecosystem where different types of users (vehicles, elements of the infrastructure, pedestrians) are connected. How to efficiently share the available radio resources among the different types of eligible users is one of the important issues to be addressed. This paper briefly analyzes various concepts presented hitherto in the literature and it proposes an enhanced algorithm for ensuring a robust co-existence of the aforementioned system users. Therefore, this paper introduces an underlay RRM (Radio Resource Management) methodology which is capable of (1) improving cellular spectral efficiency while making a minimal impact on cellular communications and (2) ensuring the different QoS (Quality of Service) requirements of ITS (Intelligent Transportation Systems) applications. Simulation results, where we compare the proposed algorithm to the other two RRM, show the promising spectral efficiency performance of the proposed RRM methodology. PMID:28953256

Characteristics of traffic flow at a non-signalized intersection in the framework of game theory

NASA Astrophysics Data System (ADS)

Fan, Hongqiang; Jia, Bin; Tian, Junfang; Yun, Lifen

2014-12-01

At a non-signalized intersection, some vehicles violate the traffic rules to pass the intersection as soon as possible. These behaviors may cause many traffic conflicts even traffic accidents. In this paper, a simulation model is proposed to research the effects of these behaviors at a non-signalized intersection. Vehicle’s movement is simulated by the cellular automaton (CA) model. The game theory is introduced for simulating the intersection dynamics. Two types of driver participate the game process: cooperator (C) and defector (D). The cooperator obey the traffic rules, but the defector does not. A transition process may occur when the cooperator is waiting before the intersection. The critical value of waiting time follows the Weibull distribution. One transition regime is found in the phase diagram. The simulation results illustrate the applicability of the proposed model and reveal a number of interesting insights into the intersection management, including that the existence of defectors is benefit for the capacity of intersection, but also reduce the safety of intersection.

Novel method to dynamically load cells in 3D-hydrogels culture for blast injury studies

NASA Astrophysics Data System (ADS)

Sory, David R.; Areias, Anabela C.; Overby, Darryl R.; Proud, William G.

2017-01-01

For at least a century explosive devices have been one of the most important causes of injuries in military conflicts as well as in terrorist attacks. Although significant experimental and modelling efforts have been focussed on blast injuries at the organ or tissue level, few studies have investigated the mechanisms of blast injuries at the cellular level. This paper introduces an in vitro method compatible with living cells to examine the effects of high stress and short-duration pulses relevant to blast loadings and blunt trauma. The experimental phase involves high strain-rate axial compression of cylindrical specimens within an hermetically sealed chamber made of biocompatible polymer. Numerical simulations were performed in order to verify the experimental loading conditions and to characterize the loading path within the sample. A proof of concept is presented so as to establish a new window to address fundamental questions regarding blast injury at the cellular level.

Equiaxed and columnar dendrite growth simulation in Al-7Si- Mg ternary alloys using cellular automaton method

NASA Astrophysics Data System (ADS)

Chen, Rui; Xu, Qingyan; Liu, Baicheng

2015-06-01

In this paper, a modified cellular automaton (MCA) model allowing for the prediction of dendrite growth of Al-Si-Mg ternary alloys in two and three dimensions is presented. The growth kinetic of S/L interface is calculated based on the solute equilibrium approach. In order to describe the dendrite growth with arbitrarily crystallographic orientations, this model introduces a modified decentered octahedron algorithm for neighborhood tracking to eliminate the effect of mesh dependency on dendrite growth. The thermody namic and kinetic data needed for dendrite growth is obtained through coupling with Pandat software package in combination with thermodynamic/kinetic/equilibrium phase diagram calculation databases. The effect of interactions between various alloying elements on solute diffusion coefficient is considered in the model. This model has first been used to simulate Al-7Si (weight percent) binary dendrite growth followed by a validation using theoretical predictions. For ternary alloy, Al-7Si-0.5Mg dendrite simulation has been carried out and the effects of solute interactions on diffusion matrix as well as the differences of Si and Mg in solute distribution have been analyzed. For actual application, this model has been applied to simulate the equiaxed dendrite growth with various crystallographic orientations of Al-7Si-0.36Mg ternary alloy, and the predicted secondary dendrite arm spacing (SDAS) shows a reasonable agreement with the experimental ones. Furthermore, the columnar dendrite growth in directional solidification has also been simulated and the predicted primary dendrite arm spacing (PDAS) is in good agreement with experiments. The simulated results effectively demonstrate the abilities of the model in prediction of dendritic microstructure of Al-Si-Mg ternary alloy.

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

PubMed

Soleimani, Hamid; Drakakis, Emmanuel M

2017-06-01

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

BioJazz: in silico evolution of cellular networks with unbounded complexity using rule-based modeling.

PubMed

Feng, Song; Ollivier, Julien F; Swain, Peter S; Soyer, Orkun S

2015-10-30

Systems biologists aim to decipher the structure and dynamics of signaling and regulatory networks underpinning cellular responses; synthetic biologists can use this insight to alter existing networks or engineer de novo ones. Both tasks will benefit from an understanding of which structural and dynamic features of networks can emerge from evolutionary processes, through which intermediary steps these arise, and whether they embody general design principles. As natural evolution at the level of network dynamics is difficult to study, in silico evolution of network models can provide important insights. However, current tools used for in silico evolution of network dynamics are limited to ad hoc computer simulations and models. Here we introduce BioJazz, an extendable, user-friendly tool for simulating the evolution of dynamic biochemical networks. Unlike previous tools for in silico evolution, BioJazz allows for the evolution of cellular networks with unbounded complexity by combining rule-based modeling with an encoding of networks that is akin to a genome. We show that BioJazz can be used to implement biologically realistic selective pressures and allows exploration of the space of network architectures and dynamics that implement prescribed physiological functions. BioJazz is provided as an open-source tool to facilitate its further development and use. Source code and user manuals are available at: http://oss-lab.github.io/biojazz and http://osslab.lifesci.warwick.ac.uk/BioJazz.aspx. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

ChainMail based neural dynamics modeling of soft tissue deformation for surgical simulation.

PubMed

Zhang, Jinao; Zhong, Yongmin; Smith, Julian; Gu, Chengfan

2017-07-20

Realistic and real-time modeling and simulation of soft tissue deformation is a fundamental research issue in the field of surgical simulation. In this paper, a novel cellular neural network approach is presented for modeling and simulation of soft tissue deformation by combining neural dynamics of cellular neural network with ChainMail mechanism. The proposed method formulates the problem of elastic deformation into cellular neural network activities to avoid the complex computation of elasticity. The local position adjustments of ChainMail are incorporated into the cellular neural network as the local connectivity of cells, through which the dynamic behaviors of soft tissue deformation are transformed into the neural dynamics of cellular neural network. Experiments demonstrate that the proposed neural network approach is capable of modeling the soft tissues' nonlinear deformation and typical mechanical behaviors. The proposed method not only improves ChainMail's linear deformation with the nonlinear characteristics of neural dynamics but also enables the cellular neural network to follow the principle of continuum mechanics to simulate soft tissue deformation.

Hybrid lattice gas simulations of flow through porous media

NASA Astrophysics Data System (ADS)

Becklehimer, Jeffrey Lynn

1997-10-01

This study introduces a suite of models designed to investigate transport phenomena in simulated porous media such as rigid or quenched sediment and clay-like deformable environments. This is achieved by using a variety of techniques that are borrowed from the field of statistical physics. These techniques include percolation, lattice gas, and cellular automata. A percolation-based model is used to study a porous medium by using rods and chains of various shapes and sizes to model the porous media formed by sediments. This is further extended to model clay-like deformable media by interacting heavy sediment particles. An interacting lattice gas computer simulation model based on the Metropolis algorithm is used to study the transport properties of fluid particles and permeability of a porous sediment. Finally, a hybrid lattice gas model is introduced by combining the Metropolis Monte Carlo method with a direct simulation which involves the collision rules as in cellular automata. This model is then used to study shock propagation in a fluid filled porous medium. This study is then extended to study shock propagation through in a fluid filled elastic porous medium. Several interesting and new results were obtained. These results show that for rigid chain percolation the percolation threshold shows a dependence on the chain length of pc~ Lc-1/2 and the jamming coverage decreases with the chain length as Lc- 1/3. For the random SAW-like chains the percolation threshold decays with the chain length as Lc- 0.01 and the jamming coverage as Lc-1/3. The fluid flow model shows that permeability depends nonmonotonically on the concentration of the fluid. For some fluids at a fixed porosity, the permeability increases on increasing the bias until a certain value Bc above which it decreases. Also, it was found that a shock propagates in a drift-like fashion when in a rigid porous medium when the porosity is high; low porosity damps out the shock front very quickly. For a shock propagating in a clay-like porous medium an unusually super-fast power-law behavior is observed for the RMS displacements of the fluid and clay particles.

Automated Quantification of Hematopoietic Cell – Stromal Cell Interactions in Histological Images of Undecalcified Bone

PubMed Central

Zehentmeier, Sandra; Cseresnyes, Zoltan; Escribano Navarro, Juan; Niesner, Raluca A.; Hauser, Anja E.

2015-01-01

Confocal microscopy is the method of choice for the analysis of localization of multiple cell types within complex tissues such as the bone marrow. However, the analysis and quantification of cellular localization is difficult, as in many cases it relies on manual counting, thus bearing the risk of introducing a rater-dependent bias and reducing interrater reliability. Moreover, it is often difficult to judge whether the co-localization between two cells results from random positioning, especially when cell types differ strongly in the frequency of their occurrence. Here, a method for unbiased quantification of cellular co-localization in the bone marrow is introduced. The protocol describes the sample preparation used to obtain histological sections of whole murine long bones including the bone marrow, as well as the staining protocol and the acquisition of high-resolution images. An analysis workflow spanning from the recognition of hematopoietic and non-hematopoietic cell types in 2-dimensional (2D) bone marrow images to the quantification of the direct contacts between those cells is presented. This also includes a neighborhood analysis, to obtain information about the cellular microenvironment surrounding a certain cell type. In order to evaluate whether co-localization of two cell types is the mere result of random cell positioning or reflects preferential associations between the cells, a simulation tool which is suitable for testing this hypothesis in the case of hematopoietic as well as stromal cells, is used. This approach is not limited to the bone marrow, and can be extended to other tissues to permit reproducible, quantitative analysis of histological data. PMID:25938636

The salt marsh vegetation spread dynamics simulation and prediction based on conditions optimized CA

NASA Astrophysics Data System (ADS)

Guan, Yujuan; Zhang, Liquan

2006-10-01

The biodiversity conservation and management of the salt marsh vegetation relies on processing their spatial information. Nowadays, more attentions are focused on their classification surveying and describing qualitatively dynamics based on RS images interpreted, rather than on simulating and predicting their dynamics quantitatively, which is of greater importance for managing and planning the salt marsh vegetation. In this paper, our notion is to make a dynamic model on large-scale and to provide a virtual laboratory in which researchers can run it according requirements. Firstly, the characteristic of the cellular automata was analyzed and a conclusion indicated that it was necessary for a CA model to be extended geographically under varying conditions of space-time circumstance in order to make results matched the facts accurately. Based on the conventional cellular automata model, the author introduced several new conditions to optimize it for simulating the vegetation objectively, such as elevation, growth speed, invading ability, variation and inheriting and so on. Hence the CA cells and remote sensing image pixels, cell neighbors and pixel neighbors, cell rules and nature of the plants were unified respectively. Taking JiuDuanSha as the test site, where holds mainly Phragmites australis (P.australis) community, Scirpus mariqueter (S.mariqueter) community and Spartina alterniflora (S.alterniflora) community. The paper explored the process of making simulation and predictions about these salt marsh vegetable changing with the conditions optimized CA (COCA) model, and examined the links among data, statistical models, and ecological predictions. This study exploited the potential of applying Conditioned Optimized CA model technique to solve this problem.

All-atom molecular dynamics of virus capsids as drug targets

DOE PAGES

Perilla, Juan R.; Hadden, Jodi A.; Goh, Boon Chong; ...

2016-04-29

Virus capsids are protein shells that package the viral genome. Although their morphology and biological functions can vary markedly, capsids often play critical roles in regulating viral infection pathways. A detailed knowledge of virus capsids, including their dynamic structure, interactions with cellular factors, and the specific roles that they play in the replication cycle, is imperative for the development of antiviral therapeutics. The following Perspective introduces an emerging area of computational biology that focuses on the dynamics of virus capsids and capsid–protein assemblies, with particular emphasis on the effects of small-molecule drug binding on capsid structure, stability, and allosteric pathways.more » When performed at chemical detail, molecular dynamics simulations can reveal subtle changes in virus capsids induced by drug molecules a fraction of their size. Finally, the current challenges of performing all-atom capsid–drug simulations are discussed, along with an outlook on the applicability of virus capsid simulations to reveal novel drug targets.« less

Simulation of Channel Segregation During Directional Solidification of In—75 wt pct Ga. Qualitative Comparison with In Situ Observations

NASA Astrophysics Data System (ADS)

Saad, Ali; Gandin, Charles-André; Bellet, Michel; Shevchenko, Natalia; Eckert, Sven

2015-11-01

Freckles are common defects in industrial casting. They result from thermosolutal convection due to buoyancy forces generated from density variations in the liquid. The present paper proposes a numerical analysis for the formation of channel segregation using the three-dimensional (3D) cellular automaton (CA)—finite element (FE) model. The model integrates kinetics laws for the nucleation and growth of a microstructure with the solution of the conservation equations for the casting, while introducing an intermediate modeling scale for a direct representation of the envelope of the dendritic grains. Directional solidification of a cuboid cell is studied. Its geometry, the alloy chosen as well as the process parameters are inspired from experimental observations recently reported in the literature. Snapshots of the convective pattern, the solute distribution, and the morphology of the growth front are qualitatively compared. Similitudes are found when considering the coupled 3D CAFE simulations. Limitations of the model to reach direct simulation of the experiments are discussed.

All-atom molecular dynamics of virus capsids as drug targets

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

Perilla, Juan R.; Hadden, Jodi A.; Goh, Boon Chong

Virus capsids are protein shells that package the viral genome. Although their morphology and biological functions can vary markedly, capsids often play critical roles in regulating viral infection pathways. A detailed knowledge of virus capsids, including their dynamic structure, interactions with cellular factors, and the specific roles that they play in the replication cycle, is imperative for the development of antiviral therapeutics. The following Perspective introduces an emerging area of computational biology that focuses on the dynamics of virus capsids and capsid–protein assemblies, with particular emphasis on the effects of small-molecule drug binding on capsid structure, stability, and allosteric pathways.more » When performed at chemical detail, molecular dynamics simulations can reveal subtle changes in virus capsids induced by drug molecules a fraction of their size. Finally, the current challenges of performing all-atom capsid–drug simulations are discussed, along with an outlook on the applicability of virus capsid simulations to reveal novel drug targets.« less

A Content-Addressable Memory structure using quantum cells in nanotechnology with energy dissipation analysis

NASA Astrophysics Data System (ADS)

Sadoghifar, Ali; Heikalabad, Saeed Rasouli

2018-05-01

Quantum-dot cellular automata is one of the recent new technologies at the nanoscale that can be a suitable replacement for CMOS technology. The circuits constructed in QCA technology have desirable features such as low power consumption, high speed and small size. These features can be more distinct in memory structures. In this paper, we design a new structure for content addressable memory cell in QCA. For this purpose, first, a unique gate is introduced for mask operation in QCA and then this gate is used to improve the performance of CAM. These structures are evaluated with QCADesigner simulator.

Hybrid stochastic simulations of intracellular reaction-diffusion systems.

PubMed

Kalantzis, Georgios

2009-06-01

With the observation that stochasticity is important in biological systems, chemical kinetics have begun to receive wider interest. While the use of Monte Carlo discrete event simulations most accurately capture the variability of molecular species, they become computationally costly for complex reaction-diffusion systems with large populations of molecules. On the other hand, continuous time models are computationally efficient but they fail to capture any variability in the molecular species. In this study a hybrid stochastic approach is introduced for simulating reaction-diffusion systems. We developed an adaptive partitioning strategy in which processes with high frequency are simulated with deterministic rate-based equations, and those with low frequency using the exact stochastic algorithm of Gillespie. Therefore the stochastic behavior of cellular pathways is preserved while being able to apply it to large populations of molecules. We describe our method and demonstrate its accuracy and efficiency compared with the Gillespie algorithm for two different systems. First, a model of intracellular viral kinetics with two steady states and second, a compartmental model of the postsynaptic spine head for studying the dynamics of Ca+2 and NMDA receptors.

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

PubMed

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

2010-05-01

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

Effect of psychological tension on pedestrian counter flow via an extended cost potential field cellular automaton model

NASA Astrophysics Data System (ADS)

Li, Xingli; Guo, Fang; Kuang, Hua; Zhou, Huaguo

2017-12-01

Psychology tells us that the different level of tension may lead to different behavior variation for individuals. In this paper, an extended cost potential field cellular automaton is proposed to simulate pedestrian counter flow under an emergency by considering behavior variation of pedestrian induced by psychological tension. A quantitative formula is introduced to describe behavioral changes caused by psychological tension, which also leads to the increasing cost of discomfort. The numerical simulations are performed under the periodic boundary condition and show that the presented model can capture some essential features of pedestrian counter flow, such as lane formation and segregation phenomenon for normal condition. Furthermore, an interesting feature is found that when pedestrians are in an extremely nervous state, a stable lane formation will be broken by a disordered mixture flow. The psychological nervousness under an emergency is not always negative to moving efficiency and a moderate level of tension will delay the occurrence of jamming phase. In addition, a larger asymmetrical ratio of left walkers to right walkers will improve the critical density related to the jamming phase and retard the occurrence of completely jammed phase. These findings will be helpful in pedestrian control and management under an emergency.

Cooperative Game-Based Energy Efficiency Management over Ultra-Dense Wireless Cellular Networks

PubMed Central

Li, Ming; Chen, Pengpeng; Gao, Shouwan

2016-01-01

Ultra-dense wireless cellular networks have been envisioned as a promising technique for handling the explosive increase of wireless traffic volume. With the extensive deployment of small cells in wireless cellular networks, the network spectral efficiency (SE) is improved with the use of limited frequency. However, the mutual inter-tier and intra-tier interference between or among small cells and macro cells becomes serious. On the other hand, more chances for potential cooperation among different cells are introduced. Energy efficiency (EE) has become one of the most important problems for future wireless networks. This paper proposes a cooperative bargaining game-based method for comprehensive EE management in an ultra-dense wireless cellular network, which highlights the complicated interference influence on energy-saving challenges and the power-coordination process among small cells and macro cells. Especially, a unified EE utility with the consideration of the interference mitigation is proposed to jointly address the SE, the deployment efficiency (DE), and the EE. In particular, closed-form power-coordination solutions for the optimal EE are derived to show the convergence property of the algorithm. Moreover, a simplified algorithm is presented to reduce the complexity of the signaling overhead, which is significant for ultra-dense small cells. Finally, numerical simulations are provided to illustrate the efficiency of the proposed cooperative bargaining game-based and simplified schemes. PMID:27649170

Cooperative Game-Based Energy Efficiency Management over Ultra-Dense Wireless Cellular Networks.

PubMed

Li, Ming; Chen, Pengpeng; Gao, Shouwan

2016-09-13

Ultra-dense wireless cellular networks have been envisioned as a promising technique for handling the explosive increase of wireless traffic volume. With the extensive deployment of small cells in wireless cellular networks, the network spectral efficiency (SE) is improved with the use of limited frequency. However, the mutual inter-tier and intra-tier interference between or among small cells and macro cells becomes serious. On the other hand, more chances for potential cooperation among different cells are introduced. Energy efficiency (EE) has become one of the most important problems for future wireless networks. This paper proposes a cooperative bargaining game-based method for comprehensive EE management in an ultra-dense wireless cellular network, which highlights the complicated interference influence on energy-saving challenges and the power-coordination process among small cells and macro cells. Especially, a unified EE utility with the consideration of the interference mitigation is proposed to jointly address the SE, the deployment efficiency (DE), and the EE. In particular, closed-form power-coordination solutions for the optimal EE are derived to show the convergence property of the algorithm. Moreover, a simplified algorithm is presented to reduce the complexity of the signaling overhead, which is significant for ultra-dense small cells. Finally, numerical simulations are provided to illustrate the efficiency of the proposed cooperative bargaining game-based and simplified schemes.

Cellular traction force recovery: An optimal filtering approach in two-dimensional Fourier space.

PubMed

Huang, Jianyong; Qin, Lei; Peng, Xiaoling; Zhu, Tao; Xiong, Chunyang; Zhang, Youyi; Fang, Jing

2009-08-21

Quantitative estimation of cellular traction has significant physiological and clinical implications. As an inverse problem, traction force recovery is essentially susceptible to noise in the measured displacement data. For traditional procedure of Fourier transform traction cytometry (FTTC), noise amplification is accompanied in the force reconstruction and small tractions cannot be recovered from the displacement field with low signal-noise ratio (SNR). To improve the FTTC process, we develop an optimal filtering scheme to suppress the noise in the force reconstruction procedure. In the framework of the Wiener filtering theory, four filtering parameters are introduced in two-dimensional Fourier space and their analytical expressions are derived in terms of the minimum-mean-squared-error (MMSE) optimization criterion. The optimal filtering approach is validated with simulations and experimental data associated with the adhesion of single cardiac myocyte to elastic substrate. The results indicate that the proposed method can highly enhance SNR of the recovered forces to reveal tiny tractions in cell-substrate interaction.

Computer simulation of a cellular automata model for the immune response in a retrovirus system

NASA Astrophysics Data System (ADS)

Pandey, R. B.

1989-02-01

Immune response in a retrovirus system is modeled by a network of three binary cell elements to take into account some of the main functional features of T4 cells, T8 cells, and viruses. Two different intercell interactions are introduced, one of which leads to three fixed points while the other yields bistable fixed points oscillating between a healthy state and a sick state in a mean field treatment. Evolution of these cells is studied for quenched and annealed random interactions on a simple cubic lattice with a nearest neighbor interaction using inhomogenous cellular automata. Populations of T4 cells and viral cells oscillate together with damping (with constant amplitude) for annealed (quenched) interaction on increasing the value of mixing probability B from zero to a characteristic value B ca ( B cq). For higher B, the average number of T4 cells increases while that of the viral infected cells decreases monotonically on increasing B, suggesting a phase transition at B ca ( B cq).

Petri net-based method for the analysis of the dynamics of signal propagation in signaling pathways.

PubMed

Hardy, Simon; Robillard, Pierre N

2008-01-15

Cellular signaling networks are dynamic systems that propagate and process information, and, ultimately, cause phenotypical responses. Understanding the circuitry of the information flow in cells is one of the keys to understanding complex cellular processes. The development of computational quantitative models is a promising avenue for attaining this goal. Not only does the analysis of the simulation data based on the concentration variations of biological compounds yields information about systemic state changes, but it is also very helpful for obtaining information about the dynamics of signal propagation. This article introduces a new method for analyzing the dynamics of signal propagation in signaling pathways using Petri net theory. The method is demonstrated with the Ca(2+)/calmodulin-dependent protein kinase II (CaMKII) regulation network. The results constitute temporal information about signal propagation in the network, a simplified graphical representation of the network and of the signal propagation dynamics and a characterization of some signaling routes as regulation motifs.

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

PubMed Central

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

2008-01-01

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

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

PubMed

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

2008-08-15

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

X-ray micro-modulated luminescence tomography (XMLT)

PubMed Central

Cong, Wenxiang; Liu, Fenglin; Wang, Chao; Wang, Ge

2014-01-01

Imaging depth of optical microscopy has been fundamentally limited to millimeter or sub-millimeter due to strong scattering of light in a biological sample. X-ray microscopy can resolve spatial details of few microns deep inside a sample but contrast resolution is inadequate to depict heterogeneous features at cellular or sub-cellular levels. To enhance and enrich biological contrast at large imaging depth, various nanoparticles are introduced and become essential to basic research and molecular medicine. Nanoparticles can be functionalized as imaging probes, similar to fluorescent and bioluminescent proteins. LiGa5O8:Cr3+ nanoparticles were recently synthesized to facilitate luminescence energy storage with x-ray pre-excitation and subsequently stimulated luminescence emission by visible/near-infrared (NIR) light. In this paper, we propose an x-ray micro-modulated luminescence tomography (XMLT, or MLT to be more general) approach to quantify a nanophosphor distribution in a thick biological sample with high resolution. Our numerical simulation studies demonstrate the feasibility of the proposed approach. PMID:24663898

Stochastic cellular automata model for stock market dynamics

NASA Astrophysics Data System (ADS)

Bartolozzi, M.; Thomas, A. W.

2004-04-01

In the present work we introduce a stochastic cellular automata model in order to simulate the dynamics of the stock market. A direct percolation method is used to create a hierarchy of clusters of active traders on a two-dimensional grid. Active traders are characterized by the decision to buy, σi (t)=+1 , or sell, σi (t)=-1 , a stock at a certain discrete time step. The remaining cells are inactive, σi (t)=0 . The trading dynamics is then determined by the stochastic interaction between traders belonging to the same cluster. Extreme, intermittent events, such as crashes or bubbles, are triggered by a phase transition in the state of the bigger clusters present on the grid, where almost all the active traders come to share the same spin orientation. Most of the stylized aspects of the financial market time series, including multifractal proprieties, are reproduced by the model. A direct comparison is made with the daily closures of the S&P500 index.

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

NASA Astrophysics Data System (ADS)

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.

Multi-Cellular Logistics of Collective Cell Migration

PubMed Central

Yamao, Masataka; Naoki, Honda; Ishii, Shin

2011-01-01

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

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

NASA Astrophysics Data System (ADS)

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.

BUDEM: an urban growth simulation model using CA for Beijing metropolitan area

NASA Astrophysics Data System (ADS)

Long, Ying; Shen, Zhenjiang; Du, Liqun; Mao, Qizhi; Gao, Zhanping

2008-10-01

It is in great need of identifying the future urban form of Beijing, which faces challenges of rapid growth in urban development projects implemented in Beijing. We develop Beijing Urban Developing Model (BUDEM in short) to support urban planning and corresponding policies evaluation. BUDEM is the spatio-temporal dynamic model for simulating urban growth in Beijing metropolitan area, using cellular automata (CA) and Multi-agent system (MAS) approaches. In this phase, the computer simulation using CA in Beijing metropolitan area is conducted, which attempts to provide a premise of urban activities including different kinds of urban development projects for industrial plants, shopping facilities, houses. In the paper, concept model of BUDEM is introduced, which is established basing on prevalent urban growth theories. The method integrating logistic regression and MonoLoop is used to retrieve weights in the transition rule by MCE. After model sensibility analysis, we apply BUDEM into three aspects of urban planning practices: (1) Identifying urban growth mechanism in various historical phases since 1986; (2) Identifying urban growth policies needed to implement desired urban form (BEIJING2020), namely planned urban form; (3) Simulating urban growth scenarios of 2049 (BEIJING2049) basing on the urban form and parameter set of BEIJING2020.

Discrete stochastic simulation methods for chemically reacting systems.

PubMed

Cao, Yang; Samuels, David C

2009-01-01

Discrete stochastic chemical kinetics describe the time evolution of a chemically reacting system by taking into account the fact that, in reality, chemical species are present with integer populations and exhibit some degree of randomness in their dynamical behavior. In recent years, with the development of new techniques to study biochemistry dynamics in a single cell, there are increasing studies using this approach to chemical kinetics in cellular systems, where the small copy number of some reactant species in the cell may lead to deviations from the predictions of the deterministic differential equations of classical chemical kinetics. This chapter reviews the fundamental theory related to stochastic chemical kinetics and several simulation methods based on that theory. We focus on nonstiff biochemical systems and the two most important discrete stochastic simulation methods: Gillespie's stochastic simulation algorithm (SSA) and the tau-leaping method. Different implementation strategies of these two methods are discussed. Then we recommend a relatively simple and efficient strategy that combines the strengths of the two methods: the hybrid SSA/tau-leaping method. The implementation details of the hybrid strategy are given here and a related software package is introduced. Finally, the hybrid method is applied to simple biochemical systems as a demonstration of its application.

[Evaluation of Cellular Effects Caused by Lunar Regolith Simulant Including Fine Particles].

PubMed

Horie, Masanori; Miki, Takeo; Honma, Yoshiyuki; Aoki, Shigeru; Morimoto, Yasuo

2015-06-01

The National Aeronautics and Space Administration has announced a plan to establish a manned colony on the surface of the moon, and our country, Japan, has declared its participation. The surface of the moon is covered with soil called lunar regolith, which includes fine particles. It is possible that humans will inhale lunar regolith if it is brought into the spaceship. Therefore, an evaluation of the pulmonary effects caused by lunar regolith is important for exploration of the moon. In the present study, we examine the cellular effects of lunar regolith simulant, whose components are similar to those of lunar regolith. We focused on the chemical component and particle size in particular. The regolith simulant was fractionated to < 10 μm, < 25 μm and 10-25 μm by gravitational sedimentation in suspensions. We also examined the cellular effects of fine regolith simulant whose primary particle size is 5.10 μm. These regolith simulants were applied to human lung carcinoma A549 cells at concentrations of 0.1 and 1.0 mg/ml. Cytotoxicity, oxidative stress and immune response were examined after 24 h exposure. Cell membrane damage, mitochondrial dysfunction and induction of Interleukin-8 (IL-8) were observed at the concentration of 1.0 mg/ml. The cellular effects of the regolith simulant at the concentration of 0.1 mg/ml were small, as compared with crystalline silica as a positive control. Secretion of IL-1β and tumor necrosis factor-α (TNF-α) was observed at the concentration of 1.0 mg/ml, but induction of gene expression was not observed at 24 h after exposure. Induction of cellular oxidative stress was small. Although the cellular effects tended to be stronger in the < 10 μm particles, there was no remarkable difference. These results suggest that the chemical components and particle size have little relationship to the cellular effects of lunar regolith simulant such as cell membrane damage, induction of oxidative stress and proinflammatory effect.

Computer simulation of a cellular automata model for the immune response in a retrovirus system

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

Pandey, R.B.

1989-02-01

Immune response in a retrovirus system is modeled by a network of three binary cell elements to take into account some of the main functional features of T4 cells, T8 cells, and viruses. Two different intercell interactions are introduced, one of which leads to three fixed points while the other yields bistable fixed points oscillating between a healthy state and a sick state in a mean field treatment. Evolution of these cells is studied for quenched and annealed random interactions on a simple cubic lattice with a nearest neighbor interaction using inhomogenous cellular automata. Populations of T4 cells and viralmore » cells oscillate together with damping (with constant amplitude) for annealed (quenched) interaction on increasing the value of mixing probability B from zero to a characteristic value B/sub ca/ (B/sub cq/). For higher B, the average number of T4 cells increases while that of the viral infected cells decreases monotonically on increasing B, suggesting a phase transition at B/sub ca/ (B/sub cq/).« less

An extended cost potential field cellular automata model considering behavior variation of pedestrian flow

NASA Astrophysics Data System (ADS)

Guo, Fang; Li, Xingli; Kuang, Hua; Bai, Yang; Zhou, Huaguo

2016-11-01

The original cost potential field cellular automata describing normal pedestrian evacuation is extended to study more general evacuation scenarios. Based on the cost potential field function, through considering the psychological characteristics of crowd under emergencies, the quantitative formula of behavior variation is introduced to reflect behavioral changes caused by psychology tension. The numerical simulations are performed to investigate the effects of the magnitude of behavior variation, the different pedestrian proportions with different behavior variation and other factors on the evacuation efficiency and process in a room. The spatiotemporal dynamic characteristic during the evacuation process is also discussed. The results show that compared with the normal evacuation, the behavior variation under an emergency does not necessarily lead to the decrease of the evacuation efficiency. At low density, the increase of the behavior variation can improve the evacuation efficiency, while at high density, the evacuation efficiency drops significantly with the increasing amplitude of the behavior variation. In addition, the larger proportion of pedestrian affected by the behavior variation will prolong the evacuation time.

Quantum cloning by cellular automata

NASA Astrophysics Data System (ADS)

D'Ariano, G. M.; Macchiavello, C.; Rossi, M.

2013-03-01

We introduce a quantum cellular automaton that achieves approximate phase-covariant cloning of qubits. The automaton is optimized for 1→2N economical cloning. The use of the automaton for cloning allows us to exploit different foliations for improving the performance with given resources.

Cellular Automata Simulation for Wealth Distribution

NASA Astrophysics Data System (ADS)

Lo, Shih-Ching

2009-08-01

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

Study on bi-directional pedestrian movement using ant algorithms

NASA Astrophysics Data System (ADS)

Sibel, Gokce; Ozhan, Kayacan

2016-01-01

A cellular automata model is proposed to simulate bi-directional pedestrian flow. Pedestrian movement is investigated by using ant algorithms. Ants communicate with each other by dropping a chemical, called a pheromone, on the substrate while crawling forward. Similarly, it is considered that oppositely moving pedestrians drop ‘visual pheromones’ on their way and the visual pheromones might cause attractive or repulsive interactions. This pheromenon is introduced into modelling the pedestrians’ walking preference. In this way, the decision-making process of pedestrians will be based on ‘the instinct of following’. At some densities, the relationships of velocity-density and flux-density are analyzed for different evaporation rates of visual pheromones. Lane formation and phase transition are observed for certain evaporation rates of visual pheromones.

Molecular ping-pong Game of Life on a two-dimensional DNA origami array.

PubMed

Jonoska, N; Seeman, N C

2015-07-28

We propose a design for programmed molecular interactions that continuously change molecular arrangements in a predesigned manner. We introduce a model where environmental control through laser illumination allows platform attachment/detachment oscillations between two floating molecular species. The platform is a two-dimensional DNA origami array of tiles decorated with strands that provide both, the floating molecular tiles to attach and to pass communicating signals to neighbouring array tiles. In particular, we show how algorithmic molecular interactions can control cyclic molecular arrangements by exhibiting a system that can simulate the dynamics similar to two-dimensional cellular automata on a DNA origami array platform. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Atomistic to continuum modeling of solidification microstructures

DOE PAGES

Karma, Alain; Tourret, Damien

2015-09-26

We summarize recent advances in modeling of solidification microstructures using computational methods that bridge atomistic to continuum scales. We first discuss progress in atomistic modeling of equilibrium and non-equilibrium solid–liquid interface properties influencing microstructure formation, as well as interface coalescence phenomena influencing the late stages of solidification. The latter is relevant in the context of hot tearing reviewed in the article by M. Rappaz in this issue. We then discuss progress to model microstructures on a continuum scale using phase-field methods. We focus on selected examples in which modeling of 3D cellular and dendritic microstructures has been directly linked tomore » experimental observations. Finally, we discuss a recently introduced coarse-grained dendritic needle network approach to simulate the formation of well-developed dendritic microstructures. The approach reliably bridges the well-separated scales traditionally simulated by phase-field and grain structure models, hence opening new avenues for quantitative modeling of complex intra- and inter-grain dynamical interactions on a grain scale.« less

Bamgineer: Introduction of simulated allele-specific copy number variants into exome and targeted sequence data sets.

PubMed

Samadian, Soroush; Bruce, Jeff P; Pugh, Trevor J

2018-03-01

Somatic copy number variations (CNVs) play a crucial role in development of many human cancers. The broad availability of next-generation sequencing data has enabled the development of algorithms to computationally infer CNV profiles from a variety of data types including exome and targeted sequence data; currently the most prevalent types of cancer genomics data. However, systemic evaluation and comparison of these tools remains challenging due to a lack of ground truth reference sets. To address this need, we have developed Bamgineer, a tool written in Python to introduce user-defined haplotype-phased allele-specific copy number events into an existing Binary Alignment Mapping (BAM) file, with a focus on targeted and exome sequencing experiments. As input, this tool requires a read alignment file (BAM format), lists of non-overlapping genome coordinates for introduction of gains and losses (bed file), and an optional file defining known haplotypes (vcf format). To improve runtime performance, Bamgineer introduces the desired CNVs in parallel using queuing and parallel processing on a local machine or on a high-performance computing cluster. As proof-of-principle, we applied Bamgineer to a single high-coverage (mean: 220X) exome sequence file from a blood sample to simulate copy number profiles of 3 exemplar tumors from each of 10 tumor types at 5 tumor cellularity levels (20-100%, 150 BAM files in total). To demonstrate feasibility beyond exome data, we introduced read alignments to a targeted 5-gene cell-free DNA sequencing library to simulate EGFR amplifications at frequencies consistent with circulating tumor DNA (10, 1, 0.1 and 0.01%) while retaining the multimodal insert size distribution of the original data. We expect Bamgineer to be of use for development and systematic benchmarking of CNV calling algorithms by users using locally-generated data for a variety of applications. The source code is freely available at http://github.com/pughlab/bamgineer.

Reproducing the Photospheric Magnetic Field Evolution during the Rise of Cycle 24 with Flux Transport by Supergranules

NASA Technical Reports Server (NTRS)

Hathaway, David; Upton, Lisa

2012-01-01

We simulate the transport of magnetic flux in the Sun s photosphere by an evolving pattern of cellular horizontal flows (supergranules). Characteristics of the simulated flow pattern can match observed characteristics including the velocity power spectrum, cell lifetimes, and cell motions in longitude and latitude. Simulations using an average, and north-south symmetric, meridional motion of the cellular pattern produce polar magnetic fields that are too weak in the North and too strong in the South. Simulations using cellular patterns with meridional motions that evolve with the observed changes in strength and north-south asymmetry will be analyzed to see if they reproduce the polar field evolution observed during the rise of Cycle 24.

Reproducing the Photospheric Magnetic Field Evolution During the Rise of Cycle 24 with Flux Transport by Supergranules

NASA Technical Reports Server (NTRS)

Hathaway, David H.; Upton, Lisa

2012-01-01

We simulate the transport of magnetic flux in the Sun s photosphere by an evolving pattern of cellular horizontal flows (supergranules). Characteristics of the simulated flow pattern match observed characteristics including the velocity power spectrum, cell lifetimes, and cell pattern motion in longitude and latitude. Simulations using an average, and north-south symmetric, meridional motion of the cellular pattern produce polar magnetic fields that are too weak in the North and too strong in the South. Simulations using cellular patterns with meridional motions that evolve with the observed changes in strength and north-south asymmetry will be analyzed to see if they reproduce the polar field evolution observed during the rise of Cycle 24.

An efficient Cellular Potts Model algorithm that forbids cell fragmentation

NASA Astrophysics Data System (ADS)

Durand, Marc; Guesnet, Etienne

2016-11-01

The Cellular Potts Model (CPM) is a lattice based modeling technique which is widely used for simulating cellular patterns such as foams or biological tissues. Despite its realism and generality, the standard Monte Carlo algorithm used in the scientific literature to evolve this model preserves connectivity of cells on a limited range of simulation temperature only. We present a new algorithm in which cell fragmentation is forbidden for all simulation temperatures. This allows to significantly enhance realism of the simulated patterns. It also increases the computational efficiency compared with the standard CPM algorithm even at same simulation temperature, thanks to the time spared in not doing unrealistic moves. Moreover, our algorithm restores the detailed balance equation, ensuring that the long-term stage is independent of the chosen acceptance rate and chosen path in the temperature space.

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

PubMed Central

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

2004-01-01

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

Introducing Bond-Line Organic Structures in High School Biology: An Activity that Incorporates Pleasant-Smelling Molecules

ERIC Educational Resources Information Center

Rios, Andro C.; French, Gerald

2011-01-01

Chemical education occurs in settings other than just the chemistry classroom. High school biology courses are frequently where students are introduced to organic molecules and their importance to cellular chemistry. However, structural representations are often intimidating because students have not been introduced to the language. As part of a…

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

PubMed

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.

A new concept for medical imaging centered on cellular phone technology.

PubMed

Granot, Yair; Ivorra, Antoni; Rubinsky, Boris

2008-04-30

According to World Health Organization reports, some three quarters of the world population does not have access to medical imaging. In addition, in developing countries over 50% of medical equipment that is available is not being used because it is too sophisticated or in disrepair or because the health personnel are not trained to use it. The goal of this study is to introduce and demonstrate the feasibility of a new concept in medical imaging that is centered on cellular phone technology and which may provide a solution to medical imaging in underserved areas. The new system replaces the conventional stand-alone medical imaging device with a new medical imaging system made of two independent components connected through cellular phone technology. The independent units are: a) a data acquisition device (DAD) at a remote patient site that is simple, with limited controls and no image display capability and b) an advanced image reconstruction and hardware control multiserver unit at a central site. The cellular phone technology transmits unprocessed raw data from the patient site DAD and receives and displays the processed image from the central site. (This is different from conventional telemedicine where the image reconstruction and control is at the patient site and telecommunication is used to transmit processed images from the patient site). The primary goal of this study is to demonstrate that the cellular phone technology can function in the proposed mode. The feasibility of the concept is demonstrated using a new frequency division multiplexing electrical impedance tomography system, which we have developed for dynamic medical imaging, as the medical imaging modality. The system is used to image through a cellular phone a simulation of breast cancer tumors in a medical imaging diagnostic mode and to image minimally invasive tissue ablation with irreversible electroporation in a medical imaging interventional mode.

Boolean linear differential operators on elementary cellular automata

NASA Astrophysics Data System (ADS)

Martín Del Rey, Ángel

2014-12-01

In this paper, the notion of boolean linear differential operator (BLDO) on elementary cellular automata (ECA) is introduced and some of their more important properties are studied. Special attention is paid to those differential operators whose coefficients are the ECA with rule numbers 90 and 150.

Simulation of interdiffusion and voids growth based on cellular automata

NASA Astrophysics Data System (ADS)

Zhang, Fan; Zhang, Boyan; Zhang, Nan; Du, Haishun; Zhang, Xinhong

2017-02-01

In the interdiffusion of two solid-state materials, if the diffusion coefficients of the two materials are not the same, the interface of the two materials will shift to the material with the lower diffusion coefficient. This effect is known as the Kirkendall effect. The Kirkendall effect leads to Kirkendall porosity. The pores act as sinks for vacancies and become voids. In this paper, the movement of the Kirkendall plane at interdiffusion is simulated based on cellular automata. The number of vacancies, the critical radius of voids nucleation and the nucleation rate are analysed. The vacancies diffusion, vacancies aggregation and voids growth are also simulated based on cellular automata.

An epidemiological modeling and data integration framework.

PubMed

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

2010-01-01

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

Cellular interface morphologies in directional solidification. II - The effect of grain boundaries

NASA Technical Reports Server (NTRS)

Ungar, Lyle H.; Brown, Robert A.

1984-01-01

A singular perturbation analysis valid for small grain-boundary slopes is used with the one-sided model for solidification to show that grain boundaries introduce imperfections into the symmetry of the developing cellular interfaces which rupture the junction between the family of planar shapes and the bifurcating cellular families. Undulating interfaces are shown to develop first near grain boundaries, and to evolve with decreasing temperature gradient either by a smooth transition from the almost planar family or by a sudden jump to moderate-amplitude cellular forms, depending on the growth rate.

Mosquito population dynamics from cellular automata-based simulation

NASA Astrophysics Data System (ADS)

Syafarina, Inna; Sadikin, Rifki; Nuraini, Nuning

2016-02-01

In this paper we present an innovative model for simulating mosquito-vector population dynamics. The simulation consist of two stages: demography and dispersal dynamics. For demography simulation, we follow the existing model for modeling a mosquito life cycles. Moreover, we use cellular automata-based model for simulating dispersal of the vector. In simulation, each individual vector is able to move to other grid based on a random walk. Our model is also capable to represent immunity factor for each grid. We simulate the model to evaluate its correctness. Based on the simulations, we can conclude that our model is correct. However, our model need to be improved to find a realistic parameters to match real data.

Spiking network simulation code for petascale computers.

PubMed

Kunkel, Susanne; Schmidt, Maximilian; Eppler, Jochen M; Plesser, Hans E; Masumoto, Gen; Igarashi, Jun; Ishii, Shin; Fukai, Tomoki; Morrison, Abigail; Diesmann, Markus; Helias, Moritz

2014-01-01

Brain-scale networks exhibit a breathtaking heterogeneity in the dynamical properties and parameters of their constituents. At cellular resolution, the entities of theory are neurons and synapses and over the past decade researchers have learned to manage the heterogeneity of neurons and synapses with efficient data structures. Already early parallel simulation codes stored synapses in a distributed fashion such that a synapse solely consumes memory on the compute node harboring the target neuron. As petaflop computers with some 100,000 nodes become increasingly available for neuroscience, new challenges arise for neuronal network simulation software: Each neuron contacts on the order of 10,000 other neurons and thus has targets only on a fraction of all compute nodes; furthermore, for any given source neuron, at most a single synapse is typically created on any compute node. From the viewpoint of an individual compute node, the heterogeneity in the synaptic target lists thus collapses along two dimensions: the dimension of the types of synapses and the dimension of the number of synapses of a given type. Here we present a data structure taking advantage of this double collapse using metaprogramming techniques. After introducing the relevant scaling scenario for brain-scale simulations, we quantitatively discuss the performance on two supercomputers. We show that the novel architecture scales to the largest petascale supercomputers available today.

Spiking network simulation code for petascale computers

PubMed Central

Kunkel, Susanne; Schmidt, Maximilian; Eppler, Jochen M.; Plesser, Hans E.; Masumoto, Gen; Igarashi, Jun; Ishii, Shin; Fukai, Tomoki; Morrison, Abigail; Diesmann, Markus; Helias, Moritz

2014-01-01

Brain-scale networks exhibit a breathtaking heterogeneity in the dynamical properties and parameters of their constituents. At cellular resolution, the entities of theory are neurons and synapses and over the past decade researchers have learned to manage the heterogeneity of neurons and synapses with efficient data structures. Already early parallel simulation codes stored synapses in a distributed fashion such that a synapse solely consumes memory on the compute node harboring the target neuron. As petaflop computers with some 100,000 nodes become increasingly available for neuroscience, new challenges arise for neuronal network simulation software: Each neuron contacts on the order of 10,000 other neurons and thus has targets only on a fraction of all compute nodes; furthermore, for any given source neuron, at most a single synapse is typically created on any compute node. From the viewpoint of an individual compute node, the heterogeneity in the synaptic target lists thus collapses along two dimensions: the dimension of the types of synapses and the dimension of the number of synapses of a given type. Here we present a data structure taking advantage of this double collapse using metaprogramming techniques. After introducing the relevant scaling scenario for brain-scale simulations, we quantitatively discuss the performance on two supercomputers. We show that the novel architecture scales to the largest petascale supercomputers available today. PMID:25346682

Prevalence and multiplicity of cutaneous beta papilloma viruses in plucked hairs depend on cellular DNA input.

PubMed

Weissenborn, S J; Neale, R; de Koning, M N C; Waterboer, T; Abeni, D; Bouwes Bavinck, J N; Wieland, U; Pfister, H J

2009-11-01

In view of the low loads of beta human papillomaviruses in skin samples, amounts of cellular DNA used in qualitative PCR may become limiting for virus detection and introduce variations in prevalence and multiplicity. This issue was explored within the context of a multicentre study and increasing prevalence and multiplicity was found with increasing input amounts of cellular DNA extracted from hair bulbs. To improve the quality and comparability between different epidemiologic studies ideally equal amounts of cellular DNA should be employed. When cellular DNA input varies this should be clearly taken into account in assessing viral prevalence and multiplicity.

COMMUNICATION: Resonant activation in polymer translocation: new insights into the escape dynamics of molecules driven by an oscillating field

NASA Astrophysics Data System (ADS)

Pizzolato, N.; Fiasconaro, A.; Persano Adorno, D.; Spagnolo, B.

2010-09-01

The translocation of molecules across cellular membranes or through synthetic nanopores is strongly affected by thermal fluctuations. In this work we study how the dynamics of a polymer in a noisy environment changes when the translocation process is driven by an oscillating electric field. An improved version of the Rouse model for a flexible polymer has been adopted to mimic the molecular dynamics, by taking into account the harmonic interactions between adjacent monomers and the excluded-volume effect by introducing a Lennard-Jones potential between all beads. A bending recoil torque has also been included in our model. The polymer dynamics is simulated in a two-dimensional domain by numerically solving the Langevin equations of motion. Thermal fluctuations are taken into account by introducing a Gaussian uncorrelated noise. The mean first translocation time of the polymer centre of inertia shows a minimum as a function of the frequency of the oscillating forcing field. This finding represents the first evidence of the resonant activation behaviour in the dynamics of polymer translocation.

The Use of Microgravity Simulators for Space Research

NASA Technical Reports Server (NTRS)

Zhang, Ye; Richards, Stephanie E.; Richards, Jeffrey T.; Levine, Howard G.

2016-01-01

The spaceflight environment is known to influence biological processes ranging from stimulation of cellular metabolism to possible impacts on cellular damage repair, suppression of immune functions, and bone loss in astronauts. Microgravity is one of the most significant stress factors experienced by living organisms during spaceflight, and therefore, understanding cellular responses to altered gravity at the physiological and molecular level is critical for expanding our knowledge of life in space. Since opportunities to conduct experiments in space are scarce, various microgravity simulators and analogues have been widely used in space biology ground studies. Even though simulated microgravity conditions have produced some, but not all of the biological effects observed in the true microgravity environment, they provide test beds that are effective, affordable, and readily available to facilitate microgravity research. Kennedy Space Center (KSC) provides ground microgravity simulator support to offer a variety of microgravity simulators and platforms for Space Biology investigators. Assistance will be provided by both KSC and external experts in molecular biology, microgravity simulation, and engineering. Comparisons between the physical differences in microgravity simulators, examples of experiments using the simulators, and scientific questions regarding the use of microgravity simulators will be discussed.

The Use of Microgravity Simulators for Space Research

NASA Technical Reports Server (NTRS)

Zhang, Ye; Richards, Stephanie E.; Wade, Randall I.; Richards, Jeffrey T.; Fritsche, Ralph F.; Levine, Howard G.

2016-01-01

The spaceflight environment is known to influence biological processes ranging from stimulation of cellular metabolism to possible impacts on cellular damage repair, suppression of immune functions, and bone loss in astronauts. Microgravity is one of the most significant stress factors experienced by living organisms during spaceflight, and therefore, understanding cellular responses to altered gravity at the physiological and molecular level is critical for expanding our knowledge of life in space. Since opportunities to conduct experiments in space are scarce, various microgravity simulators and analogues have been widely used in space biology ground studies. Even though simulated microgravity conditions have produced some, but not all of the biological effects observed in the true microgravity environment, they provide test beds that are effective, affordable, and readily available to facilitate microgravity research. A Micro-g Simulator Center is being developed at Kennedy Space Center (KSC) to offer a variety of microgravity simulators and platforms for Space Biology investigators. Assistance will be provided by both KSC and external experts in molecular biology, microgravity simulation, and engineering. Comparisons between the physical differences in microgravity simulators, examples of experiments using the simulators, and scientific questions regarding the use of microgravity simulators will be discussed.

Formalizing Knowledge in Multi-Scale Agent-Based Simulations

PubMed Central

Somogyi, Endre; Sluka, James P.; Glazier, James A.

2017-01-01

Multi-scale, agent-based simulations of cellular and tissue biology are increasingly common. These simulations combine and integrate a range of components from different domains. Simulations continuously create, destroy and reorganize constituent elements causing their interactions to dynamically change. For example, the multi-cellular tissue development process coordinates molecular, cellular and tissue scale objects with biochemical, biomechanical, spatial and behavioral processes to form a dynamic network. Different domain specific languages can describe these components in isolation, but cannot describe their interactions. No current programming language is designed to represent in human readable and reusable form the domain specific knowledge contained in these components and interactions. We present a new hybrid programming language paradigm that naturally expresses the complex multi-scale objects and dynamic interactions in a unified way and allows domain knowledge to be captured, searched, formalized, extracted and reused. PMID:29338063

Formalizing Knowledge in Multi-Scale Agent-Based Simulations.

PubMed

Somogyi, Endre; Sluka, James P; Glazier, James A

2016-10-01

Multi-scale, agent-based simulations of cellular and tissue biology are increasingly common. These simulations combine and integrate a range of components from different domains. Simulations continuously create, destroy and reorganize constituent elements causing their interactions to dynamically change. For example, the multi-cellular tissue development process coordinates molecular, cellular and tissue scale objects with biochemical, biomechanical, spatial and behavioral processes to form a dynamic network. Different domain specific languages can describe these components in isolation, but cannot describe their interactions. No current programming language is designed to represent in human readable and reusable form the domain specific knowledge contained in these components and interactions. We present a new hybrid programming language paradigm that naturally expresses the complex multi-scale objects and dynamic interactions in a unified way and allows domain knowledge to be captured, searched, formalized, extracted and reused.

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

NASA Astrophysics Data System (ADS)

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

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

A comparative cellular and molecular biology of longevity database.

PubMed

Stuart, Jeffrey A; Liang, Ping; Luo, Xuemei; Page, Melissa M; Gallagher, Emily J; Christoff, Casey A; Robb, Ellen L

2013-10-01

Discovering key cellular and molecular traits that promote longevity is a major goal of aging and longevity research. One experimental strategy is to determine which traits have been selected during the evolution of longevity in naturally long-lived animal species. This comparative approach has been applied to lifespan research for nearly four decades, yielding hundreds of datasets describing aspects of cell and molecular biology hypothesized to relate to animal longevity. Here, we introduce a Comparative Cellular and Molecular Biology of Longevity Database, available at ( http://genomics.brocku.ca/ccmbl/ ), as a compendium of comparative cell and molecular data presented in the context of longevity. This open access database will facilitate the meta-analysis of amalgamated datasets using standardized maximum lifespan (MLSP) data (from AnAge). The first edition contains over 800 data records describing experimental measurements of cellular stress resistance, reactive oxygen species metabolism, membrane composition, protein homeostasis, and genome homeostasis as they relate to vertebrate species MLSP. The purpose of this review is to introduce the database and briefly demonstrate its use in the meta-analysis of combined datasets.

The effect of feedback on attitudes toward cellular phone use while driving: a comparison between novice and experienced drivers.

PubMed

Wang, Ying; Zhang, Wei; Reimer, Bryan; Lavallière, Martin; Lesch, Mary F; Horrey, William J; Wu, Su

2010-10-01

To assess and compare the effectiveness of a simulation-based approach to change drivers' attitudes toward cellular phone use while driving for younger novice and older experienced drivers. Thirty young novice drivers were tested on a driving simulator in this study. Their performance in dealing with driving tasks was measured for a single task and dual tasks (driving while using a cellular phone) and compared to 30 older experienced drivers tested previously in another study. Half of the younger drivers received video-based feedback regarding their performance in the two conditions, with an emphasis on the contribution of dual-tasking to degraded performance. The other half did not receive any performance feedback. Drivers' perceptions and attitudes toward cellular phone use while driving were investigated by a questionnaire before, immediately after, and again one month following the simulation-based testing for both groups of drivers (feedback; no feedback). All drivers (including the novice and experienced) reported willingness to engage in driving and talking on a cellular phone in some situations. The simulated driving test showed that a secondary cellular phone task significantly degraded driving performance for both the novice and the experienced drivers. The feedback treatment group (both the novice and the experienced) showed significant attitude change toward cellular phone use while driving (toward being less favorable), whereas the control group had no attitude change. At the one-month follow-up, the benefit of feedback was sustained more so in the experienced driver group than the novice driver group, although both groups still benefited relative to the control conditions. Simulation-based feedback training is promising for short-term education in novice drivers but may be more effective in the long-term for drivers with higher levels of experience. Drivers with more experience appear to have a greater, more sustained benefit from the training than novices. Additional research is needed to better tailor this education method toward novice drivers. Simulation-based participative education approach through feedback needs to be better tailored toward novice drivers.

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

PubMed

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

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

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

PubMed

Kumar, Rakesh; Maurya, Ranjana; Saran, Shweta

2018-02-23

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

Enhanced Handoff Scheme for Downlink-Uplink Asymmetric Channels in Cellular Systems

PubMed Central

2013-01-01

In the latest cellular networks, data services like SNS and UCC can create asymmetric packet generation rates over the downlink and uplink channels. This asymmetry can lead to a downlink-uplink asymmetric channel condition being experienced by cell edge users. This paper proposes a handoff scheme to cope effectively with downlink-uplink asymmetric channels. The proposed handoff scheme exploits the uplink channel quality as well as the downlink channel quality to determine the appropriate timing and direction of handoff. We first introduce downlink and uplink channel models that consider the intercell interference, to verify the downlink-uplink channel asymmetry. Based on these results, we propose an enhanced handoff scheme that exploits both the uplink and downlink channel qualities to reduce the handoff-call dropping probability and the service interruption time. The simulation results show that the proposed handoff scheme reduces the handoff-call dropping probability about 30% and increases the satisfaction of the service interruption time requirement about 7% under high-offered load, compared to conventional mobile-assisted handoff. Especially, the proposed handoff scheme is more efficient when the uplink QoS requirement is much stricter than the downlink QoS requirement or uplink channel quality is worse than downlink channel quality. PMID:24501576

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

Kuruganti, Phani Teja

The smart grid is a combined process of revitalizing the traditional power grid applications and introducing new applications to improve the efficiency of power generation, transmission and distribution. This can be achieved by leveraging advanced communication and networking technologies. Therefore the selection of the appropriate communication technology for different smart grid applications has been debated a lot in the recent past. After comparing different possible technologies, a recent research study has arrived at a conclusion that the 3G cellular technology is the right choice for distribution side smart grid applications like smart metering, advanced distribution automation and demand response managementmore » system. In this paper, we argue that the current 3G/4G cellular technologies are not an appropriate choice for smart grid distribution applications and propose a Hybrid Spread Spectrum (HSS) based Advanced Metering Infrastructure (AMI) as one of the alternatives to 3G/4G technologies. We present a preliminary PHY and MAC layer design of a HSS based AMI network and evaluate their performance using matlab and NS2 simulations. Also, we propose a time hierarchical scheme that can significantly reduce the volume of random access traffic generated during blackouts and the delay in power outage reporting.« less

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

PubMed

Diaz, N; Tischer, I

2016-05-13

Cellular automata model identification is an important way of building simplified simulation models. In this study, we describe a generic architectural framework to ease the development process of new metaheuristic-based algorithms for cellular automata model identification in protein-folding trajectories. Our framework was developed by a methodology based on design patterns that allow an improved experience for new algorithms development. The usefulness of the proposed framework is demonstrated by the implementation of four algorithms, able to obtain extremely precise cellular automata models of the protein-folding process with a protein contact map representation. Dynamic rules obtained by the proposed approach are discussed, and future use for the new tool is outlined.

New insights into chromatin folding and dynamics from multi-scale modeling

NASA Astrophysics Data System (ADS)

Olson, Wilma

The dynamic organization of chromatin plays an essential role in the regulation of gene expression and in other fundamental cellular processes. The underlying physical basis of these activities lies in the sequential positioning, chemical composition, and intermolecular interactions of the nucleosomes-the familiar assemblies of roughly 150 DNA base pairs and eight histone proteins-found on chromatin fibers. We have developed a mesoscale model of short nucleosomal arrays and a computational framework that make it possible to incorporate detailed structural features of DNA and histones in simulations of short chromatin constructs with 3-25 evenly spaced nucleosomes. The correspondence between the predicted and observed effects of nucleosome composition, spacing, and numbers on long-range communication between regulatory proteins bound to the ends of designed nucleosome arrays lends credence to the model and to the molecular insights gleaned from the simulated structures. We have extracted effective nucleosome-nucleosome potentials from the mesoscale simulations and introduced the potentials in a larger scale computational treatment of regularly repeating chromatin fibers. Our results reveal a remarkable influence of nucleosome spacing on chromatin flexibility. Small changes in the length of the DNA fragments linking successive nucleosomes introduce marked changes in the local interactions of the nucleosomes and in the spatial configurations of the fiber as a whole. The changes in nucleosome positioning influence the statistical properties of longer chromatin constructs with 100-10,000 nucleosomes. We are investigating the extent to which the `local' interactions of regularly spaced nucleosomes contribute to the corresponding interactions in chains with mixed spacings as a step toward the treatment of fibers with nucleosomes positioned at the sites mapped at base-pair resolution on genomic sequences. Support of the work by USPHS R01 GM 34809 is gratefully acknowledged.

The Development of Design Tools for Fault Tolerant Quantum Dot Cellular Automata Based Logic

NASA Technical Reports Server (NTRS)

Armstrong, Curtis D.; Humphreys, William M.

2003-01-01

We are developing software to explore the fault tolerance of quantum dot cellular automata gate architectures in the presence of manufacturing variations and device defects. The Topology Optimization Methodology using Applied Statistics (TOMAS) framework extends the capabilities of the A Quantum Interconnected Network Array Simulator (AQUINAS) by adding front-end and back-end software and creating an environment that integrates all of these components. The front-end tools establish all simulation parameters, configure the simulation system, automate the Monte Carlo generation of simulation files, and execute the simulation of these files. The back-end tools perform automated data parsing, statistical analysis and report generation.

Heavy vehicle driver workload assessment. Task 7B, in-cab text message system and cellular phone use by heavy vehicle drivers in a part-task driving simulator

DOT National Transportation Integrated Search

This report contains the results of a simulator study conducted to serve as a supplement to a National Highway Traffic Safety Administration (NHTSA) heavy vehicle driver workload field study. Its purpose was the evaluation of effects of cellular phon...

A High-Performance Cellular Automaton Model of Tumor Growth with Dynamically Growing Domains

PubMed Central

Poleszczuk, Jan; Enderling, Heiko

2014-01-01

Tumor growth from a single transformed cancer cell up to a clinically apparent mass spans many spatial and temporal orders of magnitude. Implementation of cellular automata simulations of such tumor growth can be straightforward but computing performance often counterbalances simplicity. Computationally convenient simulation times can be achieved by choosing appropriate data structures, memory and cell handling as well as domain setup. We propose a cellular automaton model of tumor growth with a domain that expands dynamically as the tumor population increases. We discuss memory access, data structures and implementation techniques that yield high-performance multi-scale Monte Carlo simulations of tumor growth. We discuss tumor properties that favor the proposed high-performance design and present simulation results of the tumor growth model. We estimate to which parameters the model is the most sensitive, and show that tumor volume depends on a number of parameters in a non-monotonic manner. PMID:25346862

Altered cellular kinetics in growth plate according to alterations in weight bearing.

PubMed

Park, Hoon; Kong, Sun Young; Kim, Hyun Woo; Yang, Ick Hwan

2012-05-01

To examine the effects of change in weight bearing on the growth plate metabolism, a simulated animal model of weightlessness was introduced and the chondrocytes' cellular kinetics was evaluated. Unloading condition on the hind-limb of Sprague-Dawley rats was created by fixing a tail and lifting the hind-limb. Six rats aged 6 weeks old were assigned to each group of unloading, reloading, and control groups of unloading or reloading. Unloading was maintained for three weeks, and then reloading was applied for another one week thereafter. Histomorphometry for the assessment of vertical length of the growth plate, 5-bromo-2'-deoxyuridin immunohistochemistry for cellular kinetics, and biotin nick end labeling transferase-mediated deoxyuridine triphosphate-biotin nick end labeling (TUNEL) assay for chondrocytes apoptosis in the growth plate were performed. The vertical length of the growth plate and the proliferative potential of chondrocytes were decreased in the unloading group compared to those of control groups. Inter-group differences were more significant in the proliferative and hypertrophic zones. Reloading increased the length of growth plate and proliferative potential of chondrocytes. However, apoptotic changes in the growth plate were not affected by the alterations of weight bearing. Alterations in the weight bearing induced changes in the chondrocytic proliferative potential of the growth plate, however, had no effects on the apoptosis. This may explain why non-weight bearing in various clinical situations hampers normal longitudinal bone growth. Further studies on the factors for reversibility of chondrocytic proliferation upon variable mechanical stresses are needed.

Modeling of the static recrystallization for 7055 aluminum alloy by cellular automaton

NASA Astrophysics Data System (ADS)

Zhang, Tao; Lu, Shi-hong; Zhang, Jia-bin; Li, Zheng-fang; Chen, Peng; Gong, Hai; Wu, Yun-xin

2017-09-01

In order to simulate the flow behavior and microstructure evolution during the pass interval period of the multi-pass deformation process, models of static recovery (SR) and static recrystallization (SRX) by the cellular automaton (CA) method for the 7055 aluminum alloy were established. Double-pass hot compression tests were conducted to acquire flow stress and microstructure variation during the pass interval period. With the basis of the material constants obtained from the compression tests, models of the SR, incubation period, nucleation rate and grain growth were fitted by least square method. A model of the grain topology and a statistical computation of the CA results were also introduced. The effects of the pass interval time, temperature, strain, strain rate and initial grain size on the microstructure variation for the SRX of the 7055 aluminum alloy were studied. The results show that a long pass interval time, large strain, high temperature and large strain rate are beneficial for finer grains during the pass interval period. The stable size of the static recrystallized grain is not concerned with the initial grain size, but mainly depends on the strain rate and temperature. The SRX plays a vital role in grain refinement, while the SR has no effect on the variation of microstructure morphology. Using flow stress and microstructure comparisons of the simulated and experimental CA results, the established CA models can accurately predict the flow stress and microstructure evolution during the pass interval period, and provide guidance for the selection of optimized parameters for the multi-pass deformation process.

A Metascalable Computing Framework for Large Spatiotemporal-Scale Atomistic Simulations

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

Nomura, K; Seymour, R; Wang, W

2009-02-17

A metascalable (or 'design once, scale on new architectures') parallel computing framework has been developed for large spatiotemporal-scale atomistic simulations of materials based on spatiotemporal data locality principles, which is expected to scale on emerging multipetaflops architectures. The framework consists of: (1) an embedded divide-and-conquer (EDC) algorithmic framework based on spatial locality to design linear-scaling algorithms for high complexity problems; (2) a space-time-ensemble parallel (STEP) approach based on temporal locality to predict long-time dynamics, while introducing multiple parallelization axes; and (3) a tunable hierarchical cellular decomposition (HCD) parallelization framework to map these O(N) algorithms onto a multicore cluster based onmore » hybrid implementation combining message passing and critical section-free multithreading. The EDC-STEP-HCD framework exposes maximal concurrency and data locality, thereby achieving: (1) inter-node parallel efficiency well over 0.95 for 218 billion-atom molecular-dynamics and 1.68 trillion electronic-degrees-of-freedom quantum-mechanical simulations on 212,992 IBM BlueGene/L processors (superscalability); (2) high intra-node, multithreading parallel efficiency (nanoscalability); and (3) nearly perfect time/ensemble parallel efficiency (eon-scalability). The spatiotemporal scale covered by MD simulation on a sustained petaflops computer per day (i.e. petaflops {center_dot} day of computing) is estimated as NT = 2.14 (e.g. N = 2.14 million atoms for T = 1 microseconds).« less

The Art of Interpreting Epigenetic Activity | Center for Cancer Research

Cancer.gov

Even though all the cells of the human body share a common genomic blueprint, epigenetic activity such as DNA methylation, introduces molecular diversity that results in functionally and biologically different cellular constituents. In cancers, this ability of epigenetic activity to introduce molecular diversity is emerging as a powerful classifier of biological aggressiveness.

Dynamic Simulation of 1D Cellular Automata in the Active aTAM.

PubMed

Jonoska, Nataša; Karpenko, Daria; Seki, Shinnosuke

2015-07-01

The Active aTAM is a tile based model for self-assembly where tiles are able to transfer signals and change identities according to the signals received. We extend Active aTAM to include deactivation signals and thereby allow detachment of tiles. We show that the model allows a dynamic simulation of cellular automata with assemblies that do not record the entire computational history but only the current updates of the states, and thus provide a way for (a) algorithmic dynamical structural changes in the assembly and (b) reusable space in self-assembly. The simulation is such that at a given location the sequence of tiles that attach and detach corresponds precisely to the sequence of states the synchronous cellular automaton generates at that location.

Dynamic Simulation of 1D Cellular Automata in the Active aTAM

PubMed Central

Jonoska, Nataša; Karpenko, Daria; Seki, Shinnosuke

2016-01-01

The Active aTAM is a tile based model for self-assembly where tiles are able to transfer signals and change identities according to the signals received. We extend Active aTAM to include deactivation signals and thereby allow detachment of tiles. We show that the model allows a dynamic simulation of cellular automata with assemblies that do not record the entire computational history but only the current updates of the states, and thus provide a way for (a) algorithmic dynamical structural changes in the assembly and (b) reusable space in self-assembly. The simulation is such that at a given location the sequence of tiles that attach and detach corresponds precisely to the sequence of states the synchronous cellular automaton generates at that location. PMID:27789918

Adrenergic Receptor Stimulation Prevents Radiation-Induced DNA Strand Breaks, Apoptosis and Gene Expression in Simulated Microgravity

NASA Technical Reports Server (NTRS)

Moreno-Villanueva, Maria; Krieger, Stephanie; Feiveson, Alan; Kovach, Annie Marie; Buerkle, Alexander; Wu, Honglu

2017-01-01

Under Earth gravity conditions cellular damage can be counteracted by activation of the physiological defense mechanisms or through medical interventions. The mode of action of both, physiological response and medical interventions can be affected by microgravity leading to failure in repairing the damage. There are many studies reporting the effects of microgravity and/or radiation on cellular functions. However, little is known about the synergistic effects on cellular response to radiation when other endogenous cellular stress-response pathways are previously activated. Here, we investigated whether previous stimulation of the adrenergic receptor, which modulates immune response, affects radiation-induced apoptosis in immune cells under simulated microgravity conditions. Peripheral blood mononuclear cells (PBMCs) were stimulated with isoproterenol (a sympathomimetic drug) and exposed to 0.8 or 2Gy gamma-radiation in simulated microgravity versus Earth gravity. Expression of genes involved in adrenergic receptor pathways, DNA repair and apoptosis as well as the number of apoptotic cells and DNA strand breaks were determined. Our results showed that, under simulated microgravity conditions, previous treatment with isoproterenol prevented radiation-induced i) gene down regulation, ii) DNA strand breaks formation and iii) apoptosis induction. Interestedly, we found a radiation-induced increase of adrenergic receptor gene expression, which was also abolished in simulated microgravity. Understanding the mechanisms of isoproterenol-mediated radioprotection in simulated microgravity can help to develop countermeasures for space-associated health risks as well as radio-sensitizers for cancer therapy.

Predicting mining activity with parallel genetic algorithms

USGS Publications Warehouse

Talaie, S.; Leigh, R.; Louis, S.J.; Raines, G.L.; Beyer, H.G.; O'Reilly, U.M.; Banzhaf, Arnold D.; Blum, W.; Bonabeau, C.; Cantu-Paz, E.W.; ,; ,

2005-01-01

We explore several different techniques in our quest to improve the overall model performance of a genetic algorithm calibrated probabilistic cellular automata. We use the Kappa statistic to measure correlation between ground truth data and data predicted by the model. Within the genetic algorithm, we introduce a new evaluation function sensitive to spatial correctness and we explore the idea of evolving different rule parameters for different subregions of the land. We reduce the time required to run a simulation from 6 hours to 10 minutes by parallelizing the code and employing a 10-node cluster. Our empirical results suggest that using the spatially sensitive evaluation function does indeed improve the performance of the model and our preliminary results also show that evolving different rule parameters for different regions tends to improve overall model performance. Copyright 2005 ACM.

WE-DE-202-02: Are Track Structure Simulations Truly Needed for Radiobiology at the Cellular and Tissue Levels?

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

Stewart, R.

Radiation therapy for the treatment of cancer has been established as a highly precise and effective way to eradicate a localized region of diseased tissue. To achieve further significant gains in the therapeutic ratio, we need to move towards biologically optimized treatment planning. To achieve this goal, we need to understand how the radiation-type dependent patterns of induced energy depositions within the cell (physics) connect via molecular, cellular and tissue reactions to treatment outcome such as tumor control and undesirable effects on normal tissue. Several computational biology approaches have been developed connecting physics to biology. Monte Carlo simulations are themore » most accurate method to calculate physical dose distributions at the nanometer scale, however simulations at the DNA scale are slow and repair processes are generally not simulated. Alternative models that rely on the random formation of individual DNA lesions within one or two turns of the DNA have been shown to reproduce the clusters of DNA lesions, including single strand breaks (SSBs), double strand breaks (DSBs) without the need for detailed track structure simulations. Efficient computational simulations of initial DNA damage induction facilitate computational modeling of DNA repair and other molecular and cellular processes. Mechanistic, multiscale models provide a useful conceptual framework to test biological hypotheses and help connect fundamental information about track structure and dosimetry at the sub-cellular level to dose-response effects on larger scales. In this symposium we will learn about the current state of the art of computational approaches estimating radiation damage at the cellular and sub-cellular scale. How can understanding the physics interactions at the DNA level be used to predict biological outcome? We will discuss if and how such calculations are relevant to advance our understanding of radiation damage and its repair, or, if the underlying biological processes are too complex for a mechanistic approach. Can computer simulations be used to guide future biological research? We will debate the feasibility of explaining biology from a physicists’ perspective. Learning Objectives: Understand the potential applications and limitations of computational methods for dose-response modeling at the molecular, cellular and tissue levels Learn about mechanism of action underlying the induction, repair and biological processing of damage to DNA and other constituents Understand how effects and processes at one biological scale impact on biological processes and outcomes on other scales J. Schuemann, NCI/NIH grantsS. McMahon, Funding: European Commission FP7 (grant EC FP7 MC-IOF-623630)« less

Simulation of root forms using cellular automata model

NASA Astrophysics Data System (ADS)

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

2016-02-01

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.

A hybrid parallel framework for the cellular Potts model simulations

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

Jiang, Yi; He, Kejing; Dong, Shoubin

2009-01-01

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

An agent-based method for simulating porous fluid-saturated structures with indistinguishable components

NASA Astrophysics Data System (ADS)

Kashani, Jamal; Pettet, Graeme John; Gu, YuanTong; Zhang, Lihai; Oloyede, Adekunle

2017-10-01

Single-phase porous materials contain multiple components that intermingle up to the ultramicroscopic level. Although the structures of the porous materials have been simulated with agent-based methods, the results of the available methods continue to provide patterns of distinguishable solid and fluid agents which do not represent materials with indistinguishable phases. This paper introduces a new agent (hybrid agent) and category of rules (intra-agent rule) that can be used to create emergent structures that would more accurately represent single-phase structures and materials. The novel hybrid agent carries the characteristics of system's elements and it is capable of changing within itself, while also responding to its neighbours as they also change. As an example, the hybrid agent under one-dimensional cellular automata formalism in a two-dimensional domain is used to generate patterns that demonstrate the striking morphological and characteristic similarities with the porous saturated single-phase structures where each agent of the ;structure; carries semi-permeability property and consists of both fluid and solid in space and at all times. We conclude that the ability of the hybrid agent to change locally provides an enhanced protocol to simulate complex porous structures such as biological tissues which could facilitate models for agent-based techniques and numerical methods.

Spermine Condenses DNA, but Not RNA Duplexes

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

Katz, Andrea M.; Tolokh, Igor S.; Pabit, Suzette A.

Interactions between the polyamine spermine and nucleic acids drive important cellular processes. Spermine condenses DNA, and some RNAs such as poly(rA):poly(rU). A large fraction of the spermine present in cells is bound to RNA, but apparently does not condense it. Here, we study the effect of spermine binding to short duplex RNA and DNA and compare our findings with predictions of molecular dynamics simulations. When small numbers of spermine are introduced, RNA with a designed sequence, containing a mixture of 14 GC pairs and 11 AU pairs, resists condensation relative to DNA of an equivalent sequence or to 25 basemore » pair poly(rA):poly(rU) RNA. Comparison of wide-angle x-ray scattering profiles with simulation suggests that spermine is sequestered deep within the major groove of mixed sequence RNA, preventing condensation by limiting opportunities to bridge to other molecules as well as stabilizing the RNA by locking it into a particular conformation. In contrast, for DNA, simulations suggest that spermine binds external to the duplex, offering opportunities for intermolecular interaction. The goal of this study is to explain how RNA can remain soluble, and available for interaction with other molecules in the cell, despite the presence of spermine at concentrations high enough to precipitate DNA.« less

ML-Space: Hybrid Spatial Gillespie and Particle Simulation of Multi-Level Rule-Based Models in Cell Biology.

PubMed

Bittig, Arne T; Uhrmacher, Adelinde M

2017-01-01

Spatio-temporal dynamics of cellular processes can be simulated at different levels of detail, from (deterministic) partial differential equations via the spatial Stochastic Simulation algorithm to tracking Brownian trajectories of individual particles. We present a spatial simulation approach for multi-level rule-based models, which includes dynamically hierarchically nested cellular compartments and entities. Our approach ML-Space combines discrete compartmental dynamics, stochastic spatial approaches in discrete space, and particles moving in continuous space. The rule-based specification language of ML-Space supports concise and compact descriptions of models and to adapt the spatial resolution of models easily.

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

NASA Astrophysics Data System (ADS)

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

2014-09-01

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

[Simulation of urban ecological security pattern based on cellular automata: a case of Dongguan City, Guangdong Province of South China].

PubMed

Yang, Qing-Sheng; Qiao, Ji-Gang; Ai, Bin

2013-09-01

Taking the Dongguan City with rapid urbanization as a case, and selecting landscape ecological security level as evaluation criterion, the urbanization cellular number of 1 km x 1 km ecological security cells was obtained, and imbedded into the transition rules of cellular automata (CA) as the restraint term to control urban development, establish ecological security urban CA, and simulate ecological security urban development pattern. The results showed the integrated landscape ecological security index of the City decreased from 0.497 in 1998 to 0.395 in 2005, indicating that the ecological security at landscape scale was decreased. The CA-simulated integrated ecological security index of the City in 2005 was increased from the measured 0.395 to 0.479, showing that the simulated urban landscape ecological pressure from human became lesser, ecological security became better, and integrated landscape ecological security became higher. CA could be used as an effective tool in researching urban ecological security.

Liposome encapsulation of chelating agents

DOEpatents

Rahman, Yueh Erh

1976-01-13

A method for transferring a chelating agent across a cellular membrane by encapsulating the charged chelating agent within liposomes and carrying the liposome-encapsulated chelating agent to the cellular membrane where the liposomes containing the chelating agent will be taken up by the cells, thereby transferring the chelating agent across the cellular membrane. A chelating agent can be introduced into the interior of a cell of a living organism wherein the liposomes will be decomposed, releasing the chelating agent to the interior of the cell. The released chelating agent will complex intracellularly deposited toxic heavy metals, permitting the more soluble metal complex to transfer across the cellular membrane from the cell and subsequently be removed from the living organism.

Combinatorial approaches to evaluate nanodiamond uptake and induced cellular fate

NASA Astrophysics Data System (ADS)

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

PubMed Central

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

Quantifying white matter tract diffusion parameters in the presence of increased extra-fiber cellularity and vasogenic edema

PubMed Central

Chiang, Chia-Wen; Wang, Yong; Sun, Peng; Lin, Tsen-Hsuan; Trinkaus, Kathryn; Cross, Anne H.; Song, Sheng-Kwei

2014-01-01

The effect of extra-fiber structural and pathological components confounding diffusion tensor imaging (DTI) computation was quantitatively investigated using data generated by both Monte-Carlo simulations and tissue phantoms. Increased extent of vasogenic edema, by addition of various amount of gel to fixed normal mouse trigeminal nerves or by increasing non-restricted isotropic diffusion tensor components in Monte-Carlo simulations, significantly decreased fractional anisotropy (FA), increased radial diffusivity, while less significantly increased axial diffusivity derived by DTI. Increased cellularity, mimicked by graded increase of the restricted isotropic diffusion tensor component in Monte-Carlo simulations, significantly decreased FA and axial diffusivity with limited impact on radial diffusivity derived by DTI. The MC simulation and tissue phantom data were also analyzed by the recently developed diffusion basis spectrum imaging (DBSI) to simultaneously distinguish and quantify the axon/myelin integrity and extra-fiber diffusion components. Results showed that increased cellularity or vasogenic edema did not affect the DBSI-derived fiber FA, axial or radial diffusivity. Importantly, the extent of extra-fiber cellularity and edema estimated by DBSI correlated with experimentally added gel and Monte-Carlo simulations. We also examined the feasibility of applying 25-direction diffusion encoding scheme for DBSI analysis on coherent white matter tracts. Results from both phantom experiments and simulations suggested that the 25-direction diffusion scheme provided comparable DBSI estimation of both fiber diffusion parameters and extra-fiber cellularity/edema extent as those by 99-direction scheme. An in vivo 25-direction DBSI analysis was performed on experimental autoimmune encephalomyelitis (EAE, an animal model of human multiple sclerosis) optic nerve as an example to examine the validity of derived DBSI parameters with post-imaging immunohistochemistry verification. Results support that in vivo DBSI using 25-direction diffusion scheme correctly reflect the underlying axonal injury, demyelination, and inflammation of optic nerves in EAE mice. PMID:25017446

Analytical Simulations of Energy-Absorbing Impact Spheres for a Mars Sample Return Earth Entry Vehicle

NASA Technical Reports Server (NTRS)

Billings, Marcus Dwight; Fasanella, Edwin L. (Technical Monitor)

2002-01-01

Nonlinear dynamic finite element simulations were performed to aid in the design of an energy-absorbing impact sphere for a passive Earth Entry Vehicle (EEV) that is a possible architecture for the Mars Sample Return (MSR) mission. The MSR EEV concept uses an entry capsule and energy-absorbing impact sphere designed to contain and limit the acceleration of collected samples during Earth impact without a parachute. The spherical shaped impact sphere is composed of solid hexagonal and pentagonal foam-filled cells with hybrid composite, graphite-epoxy/Kevlar cell walls. Collected Martian samples will fit inside a smaller spherical sample container at the center of the EEV's cellular structure. Comparisons were made of analytical results obtained using MSC.Dytran with test results obtained from impact tests performed at NASA Langley Research Center for impact velocities from 30 to 40 m/s. Acceleration, velocity, and deformation results compared well with the test results. The correlated finite element model was then used for simulations of various off-nominal impact scenarios. Off-nominal simulations at an impact velocity of 40 m/s included a rotated cellular structure impact onto a flat surface, a cellular structure impact onto an angled surface, and a cellular structure impact onto the corner of a step.

Computer Modeling of the Earliest Cellular Structures and Functions

NASA Technical Reports Server (NTRS)

Pohorille, Andrew; Chipot, Christophe; Schweighofer, Karl

2000-01-01

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

Non Linear Programming (NLP) Formulation for Quantitative Modeling of Protein Signal Transduction Pathways

PubMed Central

Morris, Melody K.; Saez-Rodriguez, Julio; Lauffenburger, Douglas A.; Alexopoulos, Leonidas G.

2012-01-01

Modeling of signal transduction pathways plays a major role in understanding cells' function and predicting cellular response. Mathematical formalisms based on a logic formalism are relatively simple but can describe how signals propagate from one protein to the next and have led to the construction of models that simulate the cells response to environmental or other perturbations. Constrained fuzzy logic was recently introduced to train models to cell specific data to result in quantitative pathway models of the specific cellular behavior. There are two major issues in this pathway optimization: i) excessive CPU time requirements and ii) loosely constrained optimization problem due to lack of data with respect to large signaling pathways. Herein, we address both issues: the former by reformulating the pathway optimization as a regular nonlinear optimization problem; and the latter by enhanced algorithms to pre/post-process the signaling network to remove parts that cannot be identified given the experimental conditions. As a case study, we tackle the construction of cell type specific pathways in normal and transformed hepatocytes using medium and large-scale functional phosphoproteomic datasets. The proposed Non Linear Programming (NLP) formulation allows for fast optimization of signaling topologies by combining the versatile nature of logic modeling with state of the art optimization algorithms. PMID:23226239

Immersed Boundary Models for Quantifying Flow-Induced Mechanical Stimuli on Stem Cells Seeded on 3D Scaffolds in Perfusion Bioreactors.

PubMed

Guyot, Yann; Smeets, Bart; Odenthal, Tim; Subramani, Ramesh; Luyten, Frank P; Ramon, Herman; Papantoniou, Ioannis; Geris, Liesbet

2016-09-01

Perfusion bioreactors regulate flow conditions in order to provide cells with oxygen, nutrients and flow-associated mechanical stimuli. Locally, these flow conditions can vary depending on the scaffold geometry, cellular confluency and amount of extra cellular matrix deposition. In this study, a novel application of the immersed boundary method was introduced in order to represent a detailed deformable cell attached to a 3D scaffold inside a perfusion bioreactor and exposed to microscopic flow. The immersed boundary model permits the prediction of mechanical effects of the local flow conditions on the cell. Incorporating stiffness values measured with atomic force microscopy and micro-flow boundary conditions obtained from computational fluid dynamics simulations on the entire scaffold, we compared cell deformation, cortical tension, normal and shear pressure between different cell shapes and locations. We observed a large effect of the precise cell location on the local shear stress and we predicted flow-induced cortical tensions in the order of 5 pN/μm, at the lower end of the range reported in literature. The proposed method provides an interesting tool to study perfusion bioreactors processes down to the level of the individual cell's micro-environment, which can further aid in the achievement of robust bioprocess control for regenerative medicine applications.

Periodic, Quasi-periodic and Chaotic Dynamics in Simple Gene Elements with Time Delays

PubMed Central

Suzuki, Yoko; Lu, Mingyang; Ben-Jacob, Eshel; Onuchic, José N.

2016-01-01

Regulatory gene circuit motifs play crucial roles in performing and maintaining vital cellular functions. Frequently, theoretical studies of gene circuits focus on steady-state behaviors and do not include time delays. In this study, the inclusion of time delays is shown to entirely change the time-dependent dynamics for even the simplest possible circuits with one and two gene elements with self and cross regulations. These elements can give rise to rich behaviors including periodic, quasi-periodic, weak chaotic, strong chaotic and intermittent dynamics. We introduce a special power-spectrum-based method to characterize and discriminate these dynamical modes quantitatively. Our simulation results suggest that, while a single negative feedback loop of either one- or two-gene element can only have periodic dynamics, the elements with two positive/negative feedback loops are the minimalist elements to have chaotic dynamics. These elements typically have one negative feedback loop that generates oscillations, and another unit that allows frequent switches among multiple steady states or between oscillatory and non-oscillatory dynamics. Possible dynamical features of several simple one- and two-gene elements are presented in details. Discussion is presented for possible roles of the chaotic behavior in the robustness of cellular functions and diseases, for example, in the context of cancer. PMID:26876008

Non Linear Programming (NLP) formulation for quantitative modeling of protein signal transduction pathways.

PubMed

Mitsos, Alexander; Melas, Ioannis N; Morris, Melody K; Saez-Rodriguez, Julio; Lauffenburger, Douglas A; Alexopoulos, Leonidas G

2012-01-01

Modeling of signal transduction pathways plays a major role in understanding cells' function and predicting cellular response. Mathematical formalisms based on a logic formalism are relatively simple but can describe how signals propagate from one protein to the next and have led to the construction of models that simulate the cells response to environmental or other perturbations. Constrained fuzzy logic was recently introduced to train models to cell specific data to result in quantitative pathway models of the specific cellular behavior. There are two major issues in this pathway optimization: i) excessive CPU time requirements and ii) loosely constrained optimization problem due to lack of data with respect to large signaling pathways. Herein, we address both issues: the former by reformulating the pathway optimization as a regular nonlinear optimization problem; and the latter by enhanced algorithms to pre/post-process the signaling network to remove parts that cannot be identified given the experimental conditions. As a case study, we tackle the construction of cell type specific pathways in normal and transformed hepatocytes using medium and large-scale functional phosphoproteomic datasets. The proposed Non Linear Programming (NLP) formulation allows for fast optimization of signaling topologies by combining the versatile nature of logic modeling with state of the art optimization algorithms.

Periodic, Quasi-periodic and Chaotic Dynamics in Simple Gene Elements with Time Delays

NASA Astrophysics Data System (ADS)

Suzuki, Yoko; Lu, Mingyang; Ben-Jacob, Eshel; Onuchic, José N.

2016-02-01

Regulatory gene circuit motifs play crucial roles in performing and maintaining vital cellular functions. Frequently, theoretical studies of gene circuits focus on steady-state behaviors and do not include time delays. In this study, the inclusion of time delays is shown to entirely change the time-dependent dynamics for even the simplest possible circuits with one and two gene elements with self and cross regulations. These elements can give rise to rich behaviors including periodic, quasi-periodic, weak chaotic, strong chaotic and intermittent dynamics. We introduce a special power-spectrum-based method to characterize and discriminate these dynamical modes quantitatively. Our simulation results suggest that, while a single negative feedback loop of either one- or two-gene element can only have periodic dynamics, the elements with two positive/negative feedback loops are the minimalist elements to have chaotic dynamics. These elements typically have one negative feedback loop that generates oscillations, and another unit that allows frequent switches among multiple steady states or between oscillatory and non-oscillatory dynamics. Possible dynamical features of several simple one- and two-gene elements are presented in details. Discussion is presented for possible roles of the chaotic behavior in the robustness of cellular functions and diseases, for example, in the context of cancer.

Meaningful interpretation of subdiffusive measurements in living cells (crowded environment) by fluorescence fluctuation microscopy.

PubMed

Baumann, Gerd; Place, Robert F; Földes-Papp, Zeno

2010-08-01

In living cell or its nucleus, the motions of molecules are complicated due to the large crowding and expected heterogeneity of the intracellular environment. Randomness in cellular systems can be either spatial (anomalous) or temporal (heterogeneous). In order to separate both processes, we introduce anomalous random walks on fractals that represented crowded environments. We report the use of numerical simulation and experimental data of single-molecule detection by fluorescence fluctuation microscopy for detecting resolution limits of different mobile fractions in crowded environment of living cells. We simulate the time scale behavior of diffusion times tau(D)(tau) for one component, e.g. the fast mobile fraction, and a second component, e.g. the slow mobile fraction. The less the anomalous exponent alpha the higher the geometric crowding of the underlying structure of motion that is quantified by the ratio of the Hausdorff dimension and the walk exponent d(f)/d(w) and specific for the type of crowding generator used. The simulated diffusion time decreases for smaller values of alpha # 1 but increases for a larger time scale tau at a given value of alpha # 1. The effect of translational anomalous motion is substantially greater if alpha differs much from 1. An alpha value close to 1 contributes little to the time dependence of subdiffusive motions. Thus, quantitative determination of molecular weights from measured diffusion times and apparent diffusion coefficients, respectively, in temporal auto- and crosscorrelation analyses and from time-dependent fluorescence imaging data are difficult to interpret and biased in crowded environments of living cells and their cellular compartments; anomalous dynamics on different time scales tau must be coupled with the quantitative analysis of how experimental parameters change with predictions from simulated subdiffusive dynamics of molecular motions and mechanistic models. We first demonstrate that the crowding exponent alpha also determines the resolution of differences in diffusion times between two components in addition to photophysical parameters well-known for normal motion in dilute solution. The resolution limit between two different kinds of single molecule species is also analyzed under translational anomalous motion with broken ergodicity. We apply our theoretical predictions of diffusion times and lower limits for the time resolution of two components to fluorescence images in human prostate cancer cells transfected with GFP-Ago2 and GFP-Ago1. In order to mimic heterogeneous behavior in crowded environments of living cells, we need to introduce so-called continuous time random walks (CTRW). CTRWs were originally performed on regular lattice. This purely stochastic molecule behavior leads to subdiffusive motion with broken ergodicity in our simulations. For the first time, we are able to quantitatively differentiate between anomalous motion without broken ergodicity and anomalous motion with broken ergodicity in time-dependent fluorescence microscopy data sets of living cells. Since the experimental conditions to measure a selfsame molecule over an extended period of time, at which biology is taken place, in living cells or even in dilute solution are very restrictive, we need to perform the time average over a subpopulation of different single molecules of the same kind. For time averages over subpopulations of single molecules, the temporal auto- and crosscorrelation functions are first found. Knowing the crowding parameter alpha for the cell type and cellular compartment type, respectively, the heterogeneous parameter gamma can be obtained from the measurements in the presence of the interacting reaction partner, e.g. ligand, with the same alpha value. The product alpha x gamma = gamma is not a simple fitting parameter in the temporal auto- and two-color crosscorrelation functions because it is related to the proper physical models of anomalous (spatial) and heterogeneous (temporal) randomness in cellular systems.We have already derived an analytical solution gamma for in the special case of gamma = 3/2. In the case of two-color crosscorrelation or/and two-color fluorescence imaging (co-localization experiments), the second component is also a two-color species gr, for example a different molecular complex with an additional ligand. Here, we first show that plausible biological mechanisms from FCS/ FCCS and fluorescence imaging in living cells are highly questionable without proper quantitative physical models of subdiffusive motion and temporal randomness. At best, such quantitative FCS/ FCCS and fluorescence imaging data are difficult to interpret under crowding and heterogeneous conditions. It is challenging to translate proper physical models of anomalous (spatial) and heterogeneous (temporal) randomness in living cells and their cellular compartments like the nucleus into biological models of the cell biological process under study testable by single-molecule approaches. Otherwise, quantitative FCS/FCCS and fluorescence imaging measurements in living cells are not well described and cannot be interpreted in a meaningful way.

Cellular image segmentation using n-agent cooperative game theory

NASA Astrophysics Data System (ADS)

Dimock, Ian B.; Wan, Justin W. L.

2016-03-01

Image segmentation is an important problem in computer vision and has significant applications in the segmentation of cellular images. Many different imaging techniques exist and produce a variety of image properties which pose difficulties to image segmentation routines. Bright-field images are particularly challenging because of the non-uniform shape of the cells, the low contrast between cells and background, and imaging artifacts such as halos and broken edges. Classical segmentation techniques often produce poor results on these challenging images. Previous attempts at bright-field imaging are often limited in scope to the images that they segment. In this paper, we introduce a new algorithm for automatically segmenting cellular images. The algorithm incorporates two game theoretic models which allow each pixel to act as an independent agent with the goal of selecting their best labelling strategy. In the non-cooperative model, the pixels choose strategies greedily based only on local information. In the cooperative model, the pixels can form coalitions, which select labelling strategies that benefit the entire group. Combining these two models produces a method which allows the pixels to balance both local and global information when selecting their label. With the addition of k-means and active contour techniques for initialization and post-processing purposes, we achieve a robust segmentation routine. The algorithm is applied to several cell image datasets including bright-field images, fluorescent images and simulated images. Experiments show that the algorithm produces good segmentation results across the variety of datasets which differ in cell density, cell shape, contrast, and noise levels.

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

NASA Astrophysics Data System (ADS)

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

2015-11-01

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

A new simulation system of traffic flow based on cellular automata principle

NASA Astrophysics Data System (ADS)

Shan, Junru

2017-05-01

Traffic flow is a complex system of multi-behavior so it is difficult to give a specific mathematical equation to express it. With the rapid development of computer technology, it is an important method to study the complex traffic behavior by simulating the interaction mechanism between vehicles and reproduce complex traffic behavior. Using the preset of multiple operating rules, cellular automata is a kind of power system which has discrete time and space. It can be a good simulation of the real traffic process and a good way to solve the traffic problems.

21st Century Intrusions into Learning. A Legal Memorandum: Quarterly Law Topics for School Leaders, Summer 2005

ERIC Educational Resources Information Center

Pickett, A. Dean; Thomas, Christopher

2005-01-01

Thirty to forty years ago educators had at most the challenge of tape recorders and players and transistor radios to confront as electronic distractions in the classroom. Then pagers were introduced and became associated with drug trafficking and gang activity. Not long after, the first cellular phones were introduced and, when they became…

Nonsynchronous updating in the multiverse of cellular automata

NASA Astrophysics Data System (ADS)

Reia, Sandro M.; Kinouchi, Osame

2015-04-01

In this paper we study updating effects on cellular automata rule space. We consider a subset of 6144 order-3 automata from the space of 262144 bidimensional outer-totalistic rules. We compare synchronous to asynchronous and sequential updatings. Focusing on two automata, we discuss how update changes destroy typical structures of these rules. Besides, we show that the first-order phase transition in the multiverse of synchronous cellular automata, revealed with the use of a recently introduced control parameter, seems to be robust not only to changes in update schema but also to different initial densities.

Nonsynchronous updating in the multiverse of cellular automata.

PubMed

Reia, Sandro M; Kinouchi, Osame

2015-04-01

In this paper we study updating effects on cellular automata rule space. We consider a subset of 6144 order-3 automata from the space of 262144 bidimensional outer-totalistic rules. We compare synchronous to asynchronous and sequential updatings. Focusing on two automata, we discuss how update changes destroy typical structures of these rules. Besides, we show that the first-order phase transition in the multiverse of synchronous cellular automata, revealed with the use of a recently introduced control parameter, seems to be robust not only to changes in update schema but also to different initial densities.

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

NASA Technical Reports Server (NTRS)

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

2013-01-01

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

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

NASA Technical Reports Server (NTRS)

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

1980-01-01

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

Driven to distraction: dual-Task studies of simulated driving and conversing on a cellular telephone.

PubMed

Strayer, D L; Johnston, W A

2001-11-01

Dual-task studies assessed the effects of cellular-phone conversations on performance of a simulated driving task. Performance was not disrupted by listening to radio broadcasts or listening to a book on tape. Nor was it disrupted by a continuous shadowing task using a handheld phone, ruling out, in this case, dual-task interpretations associated with holding the phone, listening, or speaking, However significant interference was observed in a word-generation variant of the shadowing task, and this deficit increased with the difficulty of driving. Moreover unconstrained conversations using either a handheld or a hands-free cell phone resulted in a twofold increase in the failure to detect simulated traffic signals and slower reactions to those signals that were detected. We suggest that cellular-phone use disrupts performance by diverting attention to an engaging cognitive context other than the one immediately associated with driving.

Rugged and breathable forms of stretchable electronics with adherent composite substrates for transcutaneous monitoring.

PubMed

Jang, Kyung-In; Han, Sang Youn; Xu, Sheng; Mathewson, Kyle E; Zhang, Yihui; Jeong, Jae-Woong; Kim, Gwang-Tae; Webb, R Chad; Lee, Jung Woo; Dawidczyk, Thomas J; Kim, Rak Hwan; Song, Young Min; Yeo, Woon-Hong; Kim, Stanley; Cheng, Huanyu; Rhee, Sang Il; Chung, Jeahoon; Kim, Byunggik; Chung, Ha Uk; Lee, Dongjun; Yang, Yiyuan; Cho, Moongee; Gaspar, John G; Carbonari, Ronald; Fabiani, Monica; Gratton, Gabriele; Huang, Yonggang; Rogers, John A

2014-09-03

Research in stretchable electronics involves fundamental scientific topics relevant to applications with importance in human healthcare. Despite significant progress in active components, routes to mechanically robust construction are lacking. Here, we introduce materials and composite designs for thin, breathable, soft electronics that can adhere strongly to the skin, with the ability to be applied and removed hundreds of times without damaging the devices or the skin, even in regions with substantial topography and coverage of hair. The approach combines thin, ultralow modulus, cellular silicone materials with elastic, strain-limiting fabrics, to yield a compliant but rugged platform for stretchable electronics. Theoretical and experimental studies highlight the mechanics of adhesion and elastic deformation. Demonstrations include cutaneous optical, electrical and radio frequency sensors for measuring hydration state, electrophysiological activity, pulse and cerebral oximetry. Multipoint monitoring of a subject in an advanced driving simulator provides a practical example.

Influence of the Investor's Behavior on the Complexity of the Stock Market

NASA Astrophysics Data System (ADS)

Atman, A. P. F.; Gonçalves, Bruna Amin

2012-04-01

One of the pillars of the finance theory is the efficient-market hypothesis, which is used to analyze the stock market. However, in recent years, this hypothesis has been questioned by a number of studies showing evidence of unusual behaviors in the returns of financial assets ("anomalies") caused by behavioral aspects of the economic agents. Therefore, it is time to initiate a debate about the efficient-market hypothesis and the "behavioral finances." We here introduce a cellular automaton model to study the stock market complexity, considering different behaviors of the economical agents. From the analysis of the stationary standard of investment observed in the simulations and the Hurst exponents obtained for the term series of stock index, we draw conclusions concerning the complexity of the model compared to real markets. We also investigate which conditions of the investors are able to influence the efficient market hypothesis statements.

Knowledge environments representing molecular entities for the virtual physiological human.

PubMed

Hofmann-Apitius, Martin; Fluck, Juliane; Furlong, Laura; Fornes, Oriol; Kolárik, Corinna; Hanser, Susanne; Boeker, Martin; Schulz, Stefan; Sanz, Ferran; Klinger, Roman; Mevissen, Theo; Gattermayer, Tobias; Oliva, Baldo; Friedrich, Christoph M

2008-09-13

In essence, the virtual physiological human (VPH) is a multiscale representation of human physiology spanning from the molecular level via cellular processes and multicellular organization of tissues to complex organ function. The different scales of the VPH deal with different entities, relationships and processes, and in consequence the models used to describe and simulate biological functions vary significantly. Here, we describe methods and strategies to generate knowledge environments representing molecular entities that can be used for modelling the molecular scale of the VPH. Our strategy to generate knowledge environments representing molecular entities is based on the combination of information extraction from scientific text and the integration of information from biomolecular databases. We introduce @neuLink, a first prototype of an automatically generated, disease-specific knowledge environment combining biomolecular, chemical, genetic and medical information. Finally, we provide a perspective for the future implementation and use of knowledge environments representing molecular entities for the VPH.

Two-lane traffic-flow model with an exact steady-state solution.

PubMed

Kanai, Masahiro

2010-12-01

We propose a stochastic cellular-automaton model for two-lane traffic flow based on the misanthrope process in one dimension. The misanthrope process is a stochastic process allowing for an exact steady-state solution; hence, we have an exact flow-density diagram for two-lane traffic. In addition, we introduce two parameters that indicate, respectively, driver's driving-lane preference and passing-lane priority. Due to the additional parameters, the model shows a deviation of the density ratio for driving-lane use and a biased lane efficiency in flow. Then, a mean-field approach explicitly describes the asymmetric flow by the hop rates, the driving-lane preference, and the passing-lane priority. Meanwhile, the simulation results are in good agreement with an observational data, and we thus estimate these parameters. We conclude that the proposed model successfully produces two-lane traffic flow particularly with the driving-lane preference and the passing-lane priority.

Rugged and breathable forms of stretchable electronics with adherent composite substrates for transcutaneous monitoring

NASA Astrophysics Data System (ADS)

Jang, Kyung-In; Han, Sang Youn; Xu, Sheng; Mathewson, Kyle E.; Zhang, Yihui; Jeong, Jae-Woong; Kim, Gwang-Tae; Webb, R. Chad; Lee, Jung Woo; Dawidczyk, Thomas J.; Kim, Rak Hwan; Song, Young Min; Yeo, Woon-Hong; Kim, Stanley; Cheng, Huanyu; Rhee, Sang Il; Chung, Jeahoon; Kim, Byunggik; Chung, Ha Uk; Lee, Dongjun; Yang, Yiyuan; Cho, Moongee; Gaspar, John G.; Carbonari, Ronald; Fabiani, Monica; Gratton, Gabriele; Huang, Yonggang; Rogers, John A.

2014-09-01

Research in stretchable electronics involves fundamental scientific topics relevant to applications with importance in human healthcare. Despite significant progress in active components, routes to mechanically robust construction are lacking. Here, we introduce materials and composite designs for thin, breathable, soft electronics that can adhere strongly to the skin, with the ability to be applied and removed hundreds of times without damaging the devices or the skin, even in regions with substantial topography and coverage of hair. The approach combines thin, ultralow modulus, cellular silicone materials with elastic, strain-limiting fabrics, to yield a compliant but rugged platform for stretchable electronics. Theoretical and experimental studies highlight the mechanics of adhesion and elastic deformation. Demonstrations include cutaneous optical, electrical and radio frequency sensors for measuring hydration state, electrophysiological activity, pulse and cerebral oximetry. Multipoint monitoring of a subject in an advanced driving simulator provides a practical example.

Non-invasive imaging using reporter genes altering cellular water permeability

NASA Astrophysics Data System (ADS)

Mukherjee, Arnab; Wu, Di; Davis, Hunter C.; Shapiro, Mikhail G.

2016-12-01

Non-invasive imaging of gene expression in live, optically opaque animals is important for multiple applications, including monitoring of genetic circuits and tracking of cell-based therapeutics. Magnetic resonance imaging (MRI) could enable such monitoring with high spatiotemporal resolution. However, existing MRI reporter genes based on metalloproteins or chemical exchange probes are limited by their reliance on metals or relatively low sensitivity. Here we introduce a new class of MRI reporters based on the human water channel aquaporin 1. We show that aquaporin overexpression produces contrast in diffusion-weighted MRI by increasing tissue water diffusivity without affecting viability. Low aquaporin levels or mixed populations comprising as few as 10% aquaporin-expressing cells are sufficient to produce MRI contrast. We characterize this new contrast mechanism through experiments and simulations, and demonstrate its utility in vivo by imaging gene expression in tumours. Our results establish an alternative class of sensitive, metal-free reporter genes for non-invasive imaging.

Navigation studies based on the ubiquitous positioning technologies

NASA Astrophysics Data System (ADS)

Ye, Lei; Mi, Weijie; Wang, Defeng

2007-11-01

This paper summarized the nowadays positioning technologies, such as absolute positioning methods and relative positioning methods, indoor positioning and outdoor positioning, active positioning and passive positioning. Global Navigation Satellite System (GNSS) technologies were introduced as the omnipresent out-door positioning technologies, including GPS, GLONASS, Galileo and BD-1/2. After analysis of the shortcomings of GNSS, indoor positioning technologies were discussed and compared, including A-GPS, Cellular network, Infrared, Electromagnetism, Computer Vision Cognition, Embedded Pressure Sensor, Ultrasonic, RFID (Radio Frequency IDentification), Bluetooth, WLAN etc.. Then the concept and characteristics of Ubiquitous Positioning was proposed. After the ubiquitous positioning technologies contrast and selection followed by system engineering methodology, a navigation system model based on Incorporate Indoor-Outdoor Positioning Solution was proposed. And this model was simulated in the Galileo Demonstration for World Expo Shanghai project. In the conclusion, the prospects of ubiquitous positioning based navigation were shown, especially to satisfy the public location information acquiring requirement.

Simulation of root forms using cellular automata model

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

Winarno, Nanang, E-mail: nanang-winarno@upi.edu; Prima, Eka Cahya; Afifah, Ratih Mega Ayu

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 usedmore » 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.« less

A cellular automata model for population expansion of Spartina alterniflora at Jiuduansha Shoals, Shanghai, China

NASA Astrophysics Data System (ADS)

Huang, Hua-mei; Zhang, Li-quan; Guan, Yu-juan; Wang, Dong-hui

2008-03-01

Biological invasion has received considerable attention recently because of increasing impacts on local ecosystems. Expansion of Spartina alterniflora, a non-native species, on the intertidal mudflats of Jiuduansha Shoals at the Yangtze River Estuary is a prime example of a spatially-structured invasion in a relatively simple habitat, for which strategic control efforts can be modeled and applied. Here, we developed a Cellular Automata (CA) model, in conjunction with Remote Sensing and Geographical Information Systems, to simulate the expanding process of S. alterniflora for a period of 8 years after being introduced to the new shoals, and to study the interactions between spatial pattern and ecosystem processes for the saltmarsh vegetation. The results showed that the CA model could simulate the population dynamics of S. alterniflora and Phragmites australis on the Jiuduansha Shoals successfully. The results strongly support the hypothesis of space pre-emption as well as range expansion with simple advancing wave fronts for these two species. In the Yangtze River Estuary, the native species P. australis shares the same niche with the exotic species S. alterniflora. However, the range expansion rate of P. australis was much slower than that of S. alterniflora. With the accretion of the Jiuduansha Shoals due to the large quantity of sediments deposited by the Yangtze River, a rapid range expansion of S. alterniflora is predicted to last for a long period into future. This study indicated the potential for this approach to provide valuable insights into population and community ecology of invasive species, which could be very important for wetland biodiversity conservation and resource management in the Yangtze River Estuary and other such impacted areas.

BioASF: a framework for automatically generating executable pathway models specified in BioPAX.

PubMed

Haydarlou, Reza; Jacobsen, Annika; Bonzanni, Nicola; Feenstra, K Anton; Abeln, Sanne; Heringa, Jaap

2016-06-15

Biological pathways play a key role in most cellular functions. To better understand these functions, diverse computational and cell biology researchers use biological pathway data for various analysis and modeling purposes. For specifying these biological pathways, a community of researchers has defined BioPAX and provided various tools for creating, validating and visualizing BioPAX models. However, a generic software framework for simulating BioPAX models is missing. Here, we attempt to fill this gap by introducing a generic simulation framework for BioPAX. The framework explicitly separates the execution model from the model structure as provided by BioPAX, with the advantage that the modelling process becomes more reproducible and intrinsically more modular; this ensures natural biological constraints are satisfied upon execution. The framework is based on the principles of discrete event systems and multi-agent systems, and is capable of automatically generating a hierarchical multi-agent system for a given BioPAX model. To demonstrate the applicability of the framework, we simulated two types of biological network models: a gene regulatory network modeling the haematopoietic stem cell regulators and a signal transduction network modeling the Wnt/β-catenin signaling pathway. We observed that the results of the simulations performed using our framework were entirely consistent with the simulation results reported by the researchers who developed the original models in a proprietary language. The framework, implemented in Java, is open source and its source code, documentation and tutorial are available at http://www.ibi.vu.nl/programs/BioASF CONTACT: j.heringa@vu.nl. © The Author 2016. Published by Oxford University Press.

Fast and accurate automated cell boundary determination for fluorescence microscopy

NASA Astrophysics Data System (ADS)

Arce, Stephen Hugo; Wu, Pei-Hsun; Tseng, Yiider

2013-07-01

Detailed measurement of cell phenotype information from digital fluorescence images has the potential to greatly advance biomedicine in various disciplines such as patient diagnostics or drug screening. Yet, the complexity of cell conformations presents a major barrier preventing effective determination of cell boundaries, and introduces measurement error that propagates throughout subsequent assessment of cellular parameters and statistical analysis. State-of-the-art image segmentation techniques that require user-interaction, prolonged computation time and specialized training cannot adequately provide the support for high content platforms, which often sacrifice resolution to foster the speedy collection of massive amounts of cellular data. This work introduces a strategy that allows us to rapidly obtain accurate cell boundaries from digital fluorescent images in an automated format. Hence, this new method has broad applicability to promote biotechnology.

WE-DE-202-01: Connecting Nanoscale Physics to Initial DNA Damage Through Track Structure Simulations

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

Schuemann, J.

Radiation therapy for the treatment of cancer has been established as a highly precise and effective way to eradicate a localized region of diseased tissue. To achieve further significant gains in the therapeutic ratio, we need to move towards biologically optimized treatment planning. To achieve this goal, we need to understand how the radiation-type dependent patterns of induced energy depositions within the cell (physics) connect via molecular, cellular and tissue reactions to treatment outcome such as tumor control and undesirable effects on normal tissue. Several computational biology approaches have been developed connecting physics to biology. Monte Carlo simulations are themore » most accurate method to calculate physical dose distributions at the nanometer scale, however simulations at the DNA scale are slow and repair processes are generally not simulated. Alternative models that rely on the random formation of individual DNA lesions within one or two turns of the DNA have been shown to reproduce the clusters of DNA lesions, including single strand breaks (SSBs), double strand breaks (DSBs) without the need for detailed track structure simulations. Efficient computational simulations of initial DNA damage induction facilitate computational modeling of DNA repair and other molecular and cellular processes. Mechanistic, multiscale models provide a useful conceptual framework to test biological hypotheses and help connect fundamental information about track structure and dosimetry at the sub-cellular level to dose-response effects on larger scales. In this symposium we will learn about the current state of the art of computational approaches estimating radiation damage at the cellular and sub-cellular scale. How can understanding the physics interactions at the DNA level be used to predict biological outcome? We will discuss if and how such calculations are relevant to advance our understanding of radiation damage and its repair, or, if the underlying biological processes are too complex for a mechanistic approach. Can computer simulations be used to guide future biological research? We will debate the feasibility of explaining biology from a physicists’ perspective. Learning Objectives: Understand the potential applications and limitations of computational methods for dose-response modeling at the molecular, cellular and tissue levels Learn about mechanism of action underlying the induction, repair and biological processing of damage to DNA and other constituents Understand how effects and processes at one biological scale impact on biological processes and outcomes on other scales J. Schuemann, NCI/NIH grantsS. McMahon, Funding: European Commission FP7 (grant EC FP7 MC-IOF-623630)« less

Mathematical modeling of the dynamic storage of iron in ferritin

PubMed Central

2010-01-01

Background Iron is essential for the maintenance of basic cellular processes. In the regulation of its cellular levels, ferritin acts as the main intracellular iron storage protein. In this work we present a mathematical model for the dynamics of iron storage in ferritin during the process of intestinal iron absorption. A set of differential equations were established considering kinetic expressions for the main reactions and mass balances for ferritin, iron and a discrete population of ferritin species defined by their respective iron content. Results Simulation results showing the evolution of ferritin iron content following a pulse of iron were compared with experimental data for ferritin iron distribution obtained with purified ferritin incubated in vitro with different iron levels. Distinctive features observed experimentally were successfully captured by the model, namely the distribution pattern of iron into ferritin protein nanocages with different iron content and the role of ferritin as a controller of the cytosolic labile iron pool (cLIP). Ferritin stabilizes the cLIP for a wide range of total intracellular iron concentrations, but the model predicts an exponential increment of the cLIP at an iron content > 2,500 Fe/ferritin protein cage, when the storage capacity of ferritin is exceeded. Conclusions The results presented support the role of ferritin as an iron buffer in a cellular system. Moreover, the model predicts desirable characteristics for a buffer protein such as effective removal of excess iron, which keeps intracellular cLIP levels approximately constant even when large perturbations are introduced, and a freely available source of iron under iron starvation. In addition, the simulated dynamics of the iron removal process are extremely fast, with ferritin acting as a first defense against dangerous iron fluctuations and providing the time required by the cell to activate slower transcriptional regulation mechanisms and adapt to iron stress conditions. In summary, the model captures the complexity of the iron-ferritin equilibrium, and can be used for further theoretical exploration of the role of ferritin in the regulation of intracellular labile iron levels and, in particular, as a relevant regulator of transepithelial iron transport during the process of intestinal iron absorption. PMID:21047430

Mathematical modeling of the dynamic storage of iron in ferritin.

PubMed

Salgado, J Cristian; Olivera-Nappa, Alvaro; Gerdtzen, Ziomara P; Tapia, Victoria; Theil, Elizabeth C; Conca, Carlos; Nuñez, Marco T

2010-11-03

Iron is essential for the maintenance of basic cellular processes. In the regulation of its cellular levels, ferritin acts as the main intracellular iron storage protein. In this work we present a mathematical model for the dynamics of iron storage in ferritin during the process of intestinal iron absorption. A set of differential equations were established considering kinetic expressions for the main reactions and mass balances for ferritin, iron and a discrete population of ferritin species defined by their respective iron content. Simulation results showing the evolution of ferritin iron content following a pulse of iron were compared with experimental data for ferritin iron distribution obtained with purified ferritin incubated in vitro with different iron levels. Distinctive features observed experimentally were successfully captured by the model, namely the distribution pattern of iron into ferritin protein nanocages with different iron content and the role of ferritin as a controller of the cytosolic labile iron pool (cLIP). Ferritin stabilizes the cLIP for a wide range of total intracellular iron concentrations, but the model predicts an exponential increment of the cLIP at an iron content > 2,500 Fe/ferritin protein cage, when the storage capacity of ferritin is exceeded. The results presented support the role of ferritin as an iron buffer in a cellular system. Moreover, the model predicts desirable characteristics for a buffer protein such as effective removal of excess iron, which keeps intracellular cLIP levels approximately constant even when large perturbations are introduced, and a freely available source of iron under iron starvation. In addition, the simulated dynamics of the iron removal process are extremely fast, with ferritin acting as a first defense against dangerous iron fluctuations and providing the time required by the cell to activate slower transcriptional regulation mechanisms and adapt to iron stress conditions. In summary, the model captures the complexity of the iron-ferritin equilibrium, and can be used for further theoretical exploration of the role of ferritin in the regulation of intracellular labile iron levels and, in particular, as a relevant regulator of transepithelial iron transport during the process of intestinal iron absorption.

Why should biochemistry students be introduced to molecular dynamics simulations--and how can we introduce them?

PubMed

Elmore, Donald E

2016-01-01

Molecular dynamics (MD) simulations play an increasingly important role in many aspects of biochemical research but are often not part of the biochemistry curricula at the undergraduate level. This article discusses the pedagogical value of exposing students to MD simulations and provides information to help instructors consider what software and hardware resources are necessary to successfully introduce these simulations into their courses. In addition, a brief review of the MD-based activities in this issue and other sources are provided. © 2016 The International Union of Biochemistry and Molecular Biology.

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

PubMed

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.

Inference of neuronal network spike dynamics and topology from calcium imaging data

PubMed Central

Lütcke, Henry; Gerhard, Felipe; Zenke, Friedemann; Gerstner, Wulfram; Helmchen, Fritjof

2013-01-01

Two-photon calcium imaging enables functional analysis of neuronal circuits by inferring action potential (AP) occurrence (“spike trains”) from cellular fluorescence signals. It remains unclear how experimental parameters such as signal-to-noise ratio (SNR) and acquisition rate affect spike inference and whether additional information about network structure can be extracted. Here we present a simulation framework for quantitatively assessing how well spike dynamics and network topology can be inferred from noisy calcium imaging data. For simulated AP-evoked calcium transients in neocortical pyramidal cells, we analyzed the quality of spike inference as a function of SNR and data acquisition rate using a recently introduced peeling algorithm. Given experimentally attainable values of SNR and acquisition rate, neural spike trains could be reconstructed accurately and with up to millisecond precision. We then applied statistical neuronal network models to explore how remaining uncertainties in spike inference affect estimates of network connectivity and topological features of network organization. We define the experimental conditions suitable for inferring whether the network has a scale-free structure and determine how well hub neurons can be identified. Our findings provide a benchmark for future calcium imaging studies that aim to reliably infer neuronal network properties. PMID:24399936

A triple-mode hexa-standard reconfigurable TI cross-coupled ΣΔ modulator

NASA Astrophysics Data System (ADS)

Prakash A. V, Jos; Jose, Babita R.; Mathew, Jimson; Jose, Bijoy A.

2017-07-01

Hardware reconfigurability is an attractive solution for modern multi-standard wireless systems. This paper analyses the performance and implementation of an efficient triple-mode hexa-standard reconfigurable sigma-delta (∑Δ) modulator designed for six different wireless communication standards. Enhanced noise-shaping characteristics and increased digitisation rate, obtained by time-interleaved cross-coupling of ∑Δ paths, have been utilised for the modulator design. Power/hardware efficiency and the capability to acclimate the requirements of wide hexa-standard specifications are achieved by introducing an advanced noise-shaping structure, the dual-extended architecture. Simulation results of the proposed architecture using Hspice shows that the proposed modulator obtains a peak signal-to-noise ratio of 83.4/80.2/67.8/61.5/60.8/51.03 dB for hexa-standards, i.e. GSM/Bluetooth/GPS/WCDMA/WLAN/WiMAX standards with significantly less hardware and low operating frequency. The proposed architecture is implemented in 45 nm CMOS process using a 1 V supply and 0.7 V input range with a power consumption of 1.93 mW. Both architectural- and transistor-level simulation results prove the effectiveness and feasibility of this architecture to accomplish multi-standard cellular communication characteristics.

PyClone: statistical inference of clonal population structure in cancer.

PubMed

Roth, Andrew; Khattra, Jaswinder; Yap, Damian; Wan, Adrian; Laks, Emma; Biele, Justina; Ha, Gavin; Aparicio, Samuel; Bouchard-Côté, Alexandre; Shah, Sohrab P

2014-04-01

We introduce PyClone, a statistical model for inference of clonal population structures in cancers. PyClone is a Bayesian clustering method for grouping sets of deeply sequenced somatic mutations into putative clonal clusters while estimating their cellular prevalences and accounting for allelic imbalances introduced by segmental copy-number changes and normal-cell contamination. Single-cell sequencing validation demonstrates PyClone's accuracy.

A class of cellular automata modeling winnerless competition

NASA Astrophysics Data System (ADS)

Afraimovich, V.; Ordaz, F. C.; Urías, J.

2002-06-01

Neural units introduced by Rabinovich et al. ("Sensory coding with dynamically competitive networks," UCSD and CIT, February 1999) motivate a class of cellular automata (CA) where spatio-temporal encoding is feasible. The spatio-temporal information capacity of a CA is estimated by the information capacity of the attractor set, which happens to be finitely specified. Two-dimensional CA are studied in detail. An example is given for which the attractor is not a subshift.

New cellular automaton model for magnetohydrodynamics

NASA Technical Reports Server (NTRS)

Chen, Hudong; Matthaeus, William H.

1987-01-01

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

Dynamic Finite Element Predictions for Mars Sample Return Cellular Impact Test #4

NASA Technical Reports Server (NTRS)

Fasanella, Edwin L.; Billings, Marcus D.

2001-01-01

The nonlinear finite element program MSC.Dytran was used to predict the impact pulse for (he drop test of an energy absorbing cellular structure. This pre-test simulation was performed to aid in the design of an energy absorbing concept for a highly reliable passive Earth Entry Vehicle (EEV) that will directly impact the Earth without a parachute. In addition, a goal of the simulation was to bound the acceleration pulse produced and delivered to the simulated space cargo container. EEV's are designed to return materials from asteroids, comets, or planets for laboratory analysis on Earth. The EEV concept uses an energy absorbing cellular structure designed to contain and limit the acceleration of space exploration samples during Earth impact. The spherical shaped cellular structure is composed of solid hexagonal and pentagonal foam-filled cells with hybrid graphite-epoxy/Kevlar cell walls. Space samples fit inside a smaller sphere at the enter of the EEV's cellular structure. The material models and failure criteria were varied to determine their effect on the resulting acceleration pulse. Pre-test analytical predictions using MSC.Dytran were compared with the test results obtained from impact test #4 using bungee accelerator located at the NASA Langley Research Center Impact Dynamics Research Facility. The material model used to represent the foam and the proper failure criteria for the cell walls were critical in predicting the impact loads of the cellular structure. It was determined that a FOAMI model for the foam and a 20% failure strain criteria for the cell walls gave an accurate prediction of the acceleration pulse for drop test #4.

Introducing Simulation via the Theory of Records

ERIC Educational Resources Information Center

Johnson, Arvid C.

2011-01-01

While spreadsheet simulation can be a useful method by which to help students to understand some of the more advanced concepts in an introductory statistics course, introducing the simulation methodology at the same time as these concepts can result in student cognitive overload. This article describes a spreadsheet model that has been…

CERENA: ChEmical REaction Network Analyzer--A Toolbox for the Simulation and Analysis of Stochastic Chemical Kinetics.

PubMed

Kazeroonian, Atefeh; Fröhlich, Fabian; Raue, Andreas; Theis, Fabian J; Hasenauer, Jan

2016-01-01

Gene expression, signal transduction and many other cellular processes are subject to stochastic fluctuations. The analysis of these stochastic chemical kinetics is important for understanding cell-to-cell variability and its functional implications, but it is also challenging. A multitude of exact and approximate descriptions of stochastic chemical kinetics have been developed, however, tools to automatically generate the descriptions and compare their accuracy and computational efficiency are missing. In this manuscript we introduced CERENA, a toolbox for the analysis of stochastic chemical kinetics using Approximations of the Chemical Master Equation solution statistics. CERENA implements stochastic simulation algorithms and the finite state projection for microscopic descriptions of processes, the system size expansion and moment equations for meso- and macroscopic descriptions, as well as the novel conditional moment equations for a hybrid description. This unique collection of descriptions in a single toolbox facilitates the selection of appropriate modeling approaches. Unlike other software packages, the implementation of CERENA is completely general and allows, e.g., for time-dependent propensities and non-mass action kinetics. By providing SBML import, symbolic model generation and simulation using MEX-files, CERENA is user-friendly and computationally efficient. The availability of forward and adjoint sensitivity analyses allows for further studies such as parameter estimation and uncertainty analysis. The MATLAB code implementing CERENA is freely available from http://cerenadevelopers.github.io/CERENA/.

CERENA: ChEmical REaction Network Analyzer—A Toolbox for the Simulation and Analysis of Stochastic Chemical Kinetics

PubMed Central

Kazeroonian, Atefeh; Fröhlich, Fabian; Raue, Andreas; Theis, Fabian J.; Hasenauer, Jan

2016-01-01

Gene expression, signal transduction and many other cellular processes are subject to stochastic fluctuations. The analysis of these stochastic chemical kinetics is important for understanding cell-to-cell variability and its functional implications, but it is also challenging. A multitude of exact and approximate descriptions of stochastic chemical kinetics have been developed, however, tools to automatically generate the descriptions and compare their accuracy and computational efficiency are missing. In this manuscript we introduced CERENA, a toolbox for the analysis of stochastic chemical kinetics using Approximations of the Chemical Master Equation solution statistics. CERENA implements stochastic simulation algorithms and the finite state projection for microscopic descriptions of processes, the system size expansion and moment equations for meso- and macroscopic descriptions, as well as the novel conditional moment equations for a hybrid description. This unique collection of descriptions in a single toolbox facilitates the selection of appropriate modeling approaches. Unlike other software packages, the implementation of CERENA is completely general and allows, e.g., for time-dependent propensities and non-mass action kinetics. By providing SBML import, symbolic model generation and simulation using MEX-files, CERENA is user-friendly and computationally efficient. The availability of forward and adjoint sensitivity analyses allows for further studies such as parameter estimation and uncertainty analysis. The MATLAB code implementing CERENA is freely available from http://cerenadevelopers.github.io/CERENA/. PMID:26807911

Coupling biomechanics to a cellular level model: an approach to patient-specific image driven multi-scale and multi-physics tumor simulation.

PubMed

May, Christian P; Kolokotroni, Eleni; Stamatakos, Georgios S; Büchler, Philippe

2011-10-01

Modeling of tumor growth has been performed according to various approaches addressing different biocomplexity levels and spatiotemporal scales. Mathematical treatments range from partial differential equation based diffusion models to rule-based cellular level simulators, aiming at both improving our quantitative understanding of the underlying biological processes and, in the mid- and long term, constructing reliable multi-scale predictive platforms to support patient-individualized treatment planning and optimization. The aim of this paper is to establish a multi-scale and multi-physics approach to tumor modeling taking into account both the cellular and the macroscopic mechanical level. Therefore, an already developed biomodel of clinical tumor growth and response to treatment is self-consistently coupled with a biomechanical model. Results are presented for the free growth case of the imageable component of an initially point-like glioblastoma multiforme tumor. The composite model leads to significant tumor shape corrections that are achieved through the utilization of environmental pressure information and the application of biomechanical principles. Using the ratio of smallest to largest moment of inertia of the tumor material to quantify the effect of our coupled approach, we have found a tumor shape correction of 20% by coupling biomechanics to the cellular simulator as compared to a cellular simulation without preferred growth directions. We conclude that the integration of the two models provides additional morphological insight into realistic tumor growth behavior. Therefore, it might be used for the development of an advanced oncosimulator focusing on tumor types for which morphology plays an important role in surgical and/or radio-therapeutic treatment planning. Copyright © 2011 Elsevier Ltd. All rights reserved.

Absorbed Power Minimization in Cellular Users with Circular Antenna Arrays

NASA Astrophysics Data System (ADS)

Christofilakis, Vasilis; Votis, Constantinos; Tatsis, Giorgos; Raptis, Vasilis; Kostarakis, Panos

2010-01-01

Nowadays electromagnetic pollution of non ionizing radiation generated by cellular phones concerns millions of people. In this paper the use of circular antenna array as a means of minimizing the absorbed power by cellular phone users is introduced. In particular, the different characteristics of radiation patterns produced by a helical conventional antenna used in mobile phones operating at 900 MHz and those produced by a circular antenna array, hypothetically used in the same mobile phones, are in detail examined. Furthermore, the percentage of decrement of the power absorbed in the head as a function of direction of arrival is estimated for the circular antenna array.

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

PubMed

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

2013-08-01

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

A Cellular Automaton Framework for Infectious Disease Spread Simulation

PubMed Central

Pfeifer, Bernhard; Kugler, Karl; Tejada, Maria M; Baumgartner, Christian; Seger, Michael; Osl, Melanie; Netzer, Michael; Handler, Michael; Dander, Andreas; Wurz, Manfred; Graber, Armin; Tilg, Bernhard

2008-01-01

In this paper, a cellular automaton framework for processing the spatiotemporal spread of infectious diseases is presented. The developed environment simulates and visualizes how infectious diseases might spread, and hence provides a powerful instrument for health care organizations to generate disease prevention and contingency plans. In this study, the outbreak of an avian flu like virus was modeled in the state of Tyrol, and various scenarios such as quarantine, effect of different medications on viral spread and changes of social behavior were simulated. The proposed framework is implemented using the programming language Java. The set up of the simulation environment requires specification of the disease parameters and the geographical information using a population density colored map, enriched with demographic data. The results of the numerical simulations and the analysis of the computed parameters will be used to get a deeper understanding of how the disease spreading mechanisms work, and how to protect the population from contracting the disease. Strategies for optimization of medical treatment and vaccination regimens will also be investigated using our cellular automaton framework. In this study, six different scenarios were simulated. It showed that geographical barriers may help to slow down the spread of an infectious disease, however, when an aggressive and deadly communicable disease spreads, only quarantine and controlled medical treatment are able to stop the outbreak, if at all. PMID:19415136

Morphology of uranium electrodeposits on cathode in electrorefining process: A phase-field simulation

NASA Astrophysics Data System (ADS)

Shibuta, Yasushi; Sato, Takumi; Suzuki, Toshio; Ohta, Hirokazu; Kurata, Masaki

2013-05-01

Morphology of uranium electrodeposits on cathode with respect to applied voltage, zirconium concentration in the molten salt and the size of primary deposit during pyroprocessing is systematically investigated by the phase-field simulation. It is found that there is a threshold zirconium concentration in the molten salt demarcating planar and cellular/needle-like electrodeposits, which agrees with experimental results. In addition, the effect of size of primary deposits on the morphology of electrodeposits is examined. It is then confirmed that cellular/needle-like electrodeposits are formed from large primary deposits at all applied voltages considered, whereas both the planar and cellular/needle-like electrodeposits are formed from the primary deposits of 10 μm and less.

Erythroid cell growth and differentiation in vitro in the simulated microgravity environment of the NASA rotating wall vessel bioreactor

NASA Technical Reports Server (NTRS)

Sytkowski, A. J.; Davis, K. L.

2001-01-01

Prolonged exposure of humans and experimental animals to the altered gravitational conditions of space flight has adverse effects on the lymphoid and erythroid hematopoietic systems. Although some information is available regarding the cellular and molecular changes in lymphocytes exposed to microgravity, little is known about the erythroid cellular changes that may underlie the reduction in erythropoiesis and resultant anemia. We now report a reduction in erythroid growth and a profound inhibition of erythropoietin (Epo)-induced differentiation in a ground-based simulated microgravity model system. Rauscher murine erythroleukemia cells were grown either in tissue culture vessels at 1 x g or in the simulated microgravity environment of the NASA-designed rotating wall vessel (RWV) bioreactor. Logarithmic growth was observed under both conditions; however, the doubling time in simulated microgravity was only one-half of that seen at 1 x g. No difference in apoptosis was detected. Induction with Epo at the initiation of the culture resulted in differentiation of approximately 25% of the cells at 1 x g, consistent with our previous observations. In contrast, induction with Epo at the initiation of simulated microgravity resulted in only one-half of this degree of differentiation. Significantly, the growth of cells in simulated microgravity for 24 h prior to Epo induction inhibited the differentiation almost completely. The results suggest that the NASA RWV bioreactor may serve as a suitable ground-based microgravity simulator to model the cellular and molecular changes in erythroid cells observed in true microgravity.

Towards mechanism-based simulation of impact damage using exascale computing

NASA Astrophysics Data System (ADS)

Shterenlikht, Anton; Margetts, Lee; McDonald, Samuel; Bourne, Neil K.

2017-01-01

Over the past 60 years, the finite element method has been very successful in modelling deformation in engineering structures. However the method requires the definition of constitutive models that represent the response of the material to applied loads. There are two issues. Firstly, the models are often difficult to define. Secondly, there is often no physical connection between the models and the mechanisms that accommodate deformation. In this paper, we present a potentially disruptive two-level strategy which couples the finite element method at the macroscale with cellular automata at the mesoscale. The cellular automata are used to simulate mechanisms, such as crack propagation. The stress-strain relationship emerges as a continuum mechanics scale interpretation of changes at the micro- and meso-scales. Iterative two-way updating between the cellular automata and finite elements drives the simulation forward as the material undergoes progressive damage at high strain rates. The strategy is particularly attractive on large-scale computing platforms as both methods scale well on tens of thousands of CPUs.

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

Simulating Quantitative Cellular Responses Using Asynchronous Threshold Boolean Network Ensembles

EPA Science Inventory

With increasing knowledge about the potential mechanisms underlying cellular functions, it is becoming feasible to predict the response of biological systems to genetic and environmental perturbations. Due to the lack of homogeneity in living tissues it is difficult to estimate t...

Photosynthesis and Respiration in a Jar.

ERIC Educational Resources Information Center

Buttner, Joseph K.

2000-01-01

Describes an activity that reduces the biosphere to a water-filled jar to simulate the relationship between cellular respiration, photosynthesis, and energy. Allows students in high school biology and related courses to explore quantitatively cellular respiration and photosynthesis in almost any laboratory setting. (ASK)

Applications of formal simulation languages in the control and monitoring subsystems of Space Station Freedom

NASA Technical Reports Server (NTRS)

Lacovara, R. C.

1990-01-01

The notions, benefits, and drawbacks of numeric simulation are introduced. Two formal simulation languages, Simpscript and Modsim are introduced. The capabilities of each are discussed briefly, and then the two programs are compared. The use of simulation in the process of design engineering for the Control and Monitoring System (CMS) for Space Station Freedom is discussed. The application of the formal simulation language to the CMS design is presented, and recommendations are made as to their use.

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

PubMed Central

Somogyi, Endre; Glazier, James A.

2017-01-01

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

Myokit: A simple interface to cardiac cellular electrophysiology.

PubMed

Clerx, Michael; Collins, Pieter; de Lange, Enno; Volders, Paul G A

2016-01-01

Myokit is a new powerful and versatile software tool for modeling and simulation of cardiac cellular electrophysiology. Myokit consists of an easy-to-read modeling language, a graphical user interface, single and multi-cell simulation engines and a library of advanced analysis tools accessible through a Python interface. Models can be loaded from Myokit's native file format or imported from CellML. Model export is provided to C, MATLAB, CellML, CUDA and OpenCL. Patch-clamp data can be imported and used to estimate model parameters. In this paper, we review existing tools to simulate the cardiac cellular action potential to find that current tools do not cater specifically to model development and that there is a gap between easy-to-use but limited software and powerful tools that require strong programming skills from their users. We then describe Myokit's capabilities, focusing on its model description language, simulation engines and import/export facilities in detail. Using three examples, we show how Myokit can be used for clinically relevant investigations, multi-model testing and parameter estimation in Markov models, all with minimal programming effort from the user. This way, Myokit bridges a gap between performance, versatility and user-friendliness. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

PubMed

Somogyi, Endre; Glazier, James A

2017-04-01

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

Crowding in Cellular Environments at an Atomistic Level from Computer Simulations

PubMed Central

2017-01-01

The effects of crowding in biological environments on biomolecular structure, dynamics, and function remain not well understood. Computer simulations of atomistic models of concentrated peptide and protein systems at different levels of complexity are beginning to provide new insights. Crowding, weak interactions with other macromolecules and metabolites, and altered solvent properties within cellular environments appear to remodel the energy landscape of peptides and proteins in significant ways including the possibility of native state destabilization. Crowding is also seen to affect dynamic properties, both conformational dynamics and diffusional properties of macromolecules. Recent simulations that address these questions are reviewed here and discussed in the context of relevant experiments. PMID:28666087

WE-DE-202-00: Connecting Radiation Physics with Computational Biology

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

NONE

Radiation therapy for the treatment of cancer has been established as a highly precise and effective way to eradicate a localized region of diseased tissue. To achieve further significant gains in the therapeutic ratio, we need to move towards biologically optimized treatment planning. To achieve this goal, we need to understand how the radiation-type dependent patterns of induced energy depositions within the cell (physics) connect via molecular, cellular and tissue reactions to treatment outcome such as tumor control and undesirable effects on normal tissue. Several computational biology approaches have been developed connecting physics to biology. Monte Carlo simulations are themore » most accurate method to calculate physical dose distributions at the nanometer scale, however simulations at the DNA scale are slow and repair processes are generally not simulated. Alternative models that rely on the random formation of individual DNA lesions within one or two turns of the DNA have been shown to reproduce the clusters of DNA lesions, including single strand breaks (SSBs), double strand breaks (DSBs) without the need for detailed track structure simulations. Efficient computational simulations of initial DNA damage induction facilitate computational modeling of DNA repair and other molecular and cellular processes. Mechanistic, multiscale models provide a useful conceptual framework to test biological hypotheses and help connect fundamental information about track structure and dosimetry at the sub-cellular level to dose-response effects on larger scales. In this symposium we will learn about the current state of the art of computational approaches estimating radiation damage at the cellular and sub-cellular scale. How can understanding the physics interactions at the DNA level be used to predict biological outcome? We will discuss if and how such calculations are relevant to advance our understanding of radiation damage and its repair, or, if the underlying biological processes are too complex for a mechanistic approach. Can computer simulations be used to guide future biological research? We will debate the feasibility of explaining biology from a physicists’ perspective. Learning Objectives: Understand the potential applications and limitations of computational methods for dose-response modeling at the molecular, cellular and tissue levels Learn about mechanism of action underlying the induction, repair and biological processing of damage to DNA and other constituents Understand how effects and processes at one biological scale impact on biological processes and outcomes on other scales J. Schuemann, NCI/NIH grantsS. McMahon, Funding: European Commission FP7 (grant EC FP7 MC-IOF-623630)« less

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

McMahon, S.

Radiation therapy for the treatment of cancer has been established as a highly precise and effective way to eradicate a localized region of diseased tissue. To achieve further significant gains in the therapeutic ratio, we need to move towards biologically optimized treatment planning. To achieve this goal, we need to understand how the radiation-type dependent patterns of induced energy depositions within the cell (physics) connect via molecular, cellular and tissue reactions to treatment outcome such as tumor control and undesirable effects on normal tissue. Several computational biology approaches have been developed connecting physics to biology. Monte Carlo simulations are themore » most accurate method to calculate physical dose distributions at the nanometer scale, however simulations at the DNA scale are slow and repair processes are generally not simulated. Alternative models that rely on the random formation of individual DNA lesions within one or two turns of the DNA have been shown to reproduce the clusters of DNA lesions, including single strand breaks (SSBs), double strand breaks (DSBs) without the need for detailed track structure simulations. Efficient computational simulations of initial DNA damage induction facilitate computational modeling of DNA repair and other molecular and cellular processes. Mechanistic, multiscale models provide a useful conceptual framework to test biological hypotheses and help connect fundamental information about track structure and dosimetry at the sub-cellular level to dose-response effects on larger scales. In this symposium we will learn about the current state of the art of computational approaches estimating radiation damage at the cellular and sub-cellular scale. How can understanding the physics interactions at the DNA level be used to predict biological outcome? We will discuss if and how such calculations are relevant to advance our understanding of radiation damage and its repair, or, if the underlying biological processes are too complex for a mechanistic approach. Can computer simulations be used to guide future biological research? We will debate the feasibility of explaining biology from a physicists’ perspective. Learning Objectives: Understand the potential applications and limitations of computational methods for dose-response modeling at the molecular, cellular and tissue levels Learn about mechanism of action underlying the induction, repair and biological processing of damage to DNA and other constituents Understand how effects and processes at one biological scale impact on biological processes and outcomes on other scales J. Schuemann, NCI/NIH grantsS. McMahon, Funding: European Commission FP7 (grant EC FP7 MC-IOF-623630)« less

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

PubMed Central

Kaul, Himanshu; Cui, Zhanfeng; Ventikos, Yiannis

2013-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Support for Simulation-Based Learning; The Effects of Model Progression and Assignments on Learning about Oscillatory Motion.

ERIC Educational Resources Information Center

Swaak, Janine; And Others

In this study, learners worked with a simulation of harmonic oscillation. Two supportive measures were introduced: model progression and assignments. In model progression, the model underlying the simulation is not offered in its full complexity from the start, but variables are gradually introduced. Assignments are small exercises that help the…

Introducing Molecular Life Science Students to Model Building Using Computer Simulations

ERIC Educational Resources Information Center

Aegerter-Wilmsen, Tinri; Kettenis, Dik; Sessink, Olivier; Hartog, Rob; Bisseling, Ton; Janssen, Fred

2006-01-01

Computer simulations can facilitate the building of models of natural phenomena in research, such as in the molecular life sciences. In order to introduce molecular life science students to the use of computer simulations for model building, a digital case was developed in which students build a model of a pattern formation process in…

3D simulation of friction stir welding based on movable cellular automaton method

NASA Astrophysics Data System (ADS)

Eremina, Galina M.

2017-12-01

The paper is devoted to a 3D computer simulation of the peculiarities of material flow taking place in friction stir welding (FSW). The simulation was performed by the movable cellular automaton (MCA) method, which is a representative of particle methods in mechanics. Commonly, the flow of material in FSW is simulated based on computational fluid mechanics, assuming the material as continuum and ignoring its structure. The MCA method considers a material as an ensemble of bonded particles. The rupture of interparticle bonds and the formation of new bonds enable simulations of crack nucleation and healing as well as mas mixing and microwelding. The simulation results showed that using pins of simple shape (cylinder, cone, and pyramid) without a shoulder results in small displacements of plasticized material in workpiece thickness directions. Nevertheless, the optimal ratio of longitudinal velocity to rotational speed makes it possible to transport the welded material around the pin several times and to produce a joint of good quality.

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

PubMed Central

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

2014-01-01

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. PMID:24664988

Self-organization and stability of magnetosome chains—A simulation study

PubMed Central

Faivre, Damien; Klumpp, Stefan

2018-01-01

Magnetotactic bacteria orient in magnetic fields with the help of their magnetosome chain, a linear structure of membrane enclosed magnetic nanoparticles (magnetosomes) anchored to a cytoskeletal filament. Here, we use simulations to study the assembly and the stability of magnetosome chains. We introduce a computational model describing the attachment of the magnetosomes to the filament and their magnetic interactions. We show that the filamentous backbone is crucial for the robust assembly of the magnetic particles into a linear chain, which in turn is key for the functionality of the chain in cellular orientation and magnetically directed swimming. In addition, we simulate the response to an external magnetic field that is rotated away from the axis of the filament, an experimental method used to probe the mechanical stability of the chain. The competition between alignment along the filament and alignment with the external fields leads to the rupture of a chain if the applied field exceeeds a threshold value. These observations are in agreement with previous experiments at the population level. Beyond that, our simulations provide a detailed picture of chain rupture at the single cell level, which is found to happen through two abrupt events, which both depend on the field strength and orientation. The re-formation of the chain structure after such rupture is found to be strongly sped up in the presence of a magnetic field parallel to the filament, an observation that may also be of interest for the design of self-healing materials. Our simulations underline the dynamic nature of the magnetosome chain. More generally, they show the rich complexity of self-assembly in systems with competing driving forces for alignment. PMID:29315342

The Neurona at Home project: Simulating a large-scale cellular automata brain in a distributed computing environment

NASA Astrophysics Data System (ADS)

Acedo, L.; Villanueva-Oller, J.; Moraño, J. A.; Villanueva, R.-J.

2013-01-01

The Berkeley Open Infrastructure for Network Computing (BOINC) has become the standard open source solution for grid computing in the Internet. Volunteers use their computers to complete an small part of the task assigned by a dedicated server. We have developed a BOINC project called Neurona@Home whose objective is to simulate a cellular automata random network with, at least, one million neurons. We consider a cellular automata version of the integrate-and-fire model in which excitatory and inhibitory nodes can activate or deactivate neighbor nodes according to a set of probabilistic rules. Our aim is to determine the phase diagram of the model and its behaviour and to compare it with the electroencephalographic signals measured in real brains.

A cellular automata model of Ebola virus dynamics

NASA Astrophysics Data System (ADS)

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.

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

PubMed

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

2018-05-15

Nonsense mutations promote premature translational termination, introducing stop codons within the coding region of mRNAs and causing inherited diseases, including thalassemia. For instance, in β 0 39 thalassemia the CAG (glutamine) codon is mutated to the UAG stop codon, leading to premature translation termination and to mRNA destabilization through the well described NMD (nonsense-mediated mRNA decay). In order to develop an approach facilitating translation and, therefore, protection from NMD, ribosomal read-through molecules, such as aminoglycoside antibiotics, have been tested on mRNAs carrying premature stop codons. These findings have introduced new hopes for the development of a pharmacological approach to the β 0 39 thalassemia therapy. While several strategies, designed to enhance translational read-through, have been reported to inhibit NMD efficiency concomitantly, experimental tools for systematic analysis of mammalian NMD inhibition by translational read-through are lacking. We developed a human cellular model of the β 0 39 thalassemia mutation with UPF-1 suppressed and showing a partial NMD suppression. This novel cellular model could be used for the screening of molecules exhibiting preferential read-through activity allowing a great rescue of the mutated transcripts.

Experimental design for dynamics identification of cellular processes.

PubMed

Dinh, Vu; Rundell, Ann E; Buzzard, Gregery T

2014-03-01

We address the problem of using nonlinear models to design experiments to characterize the dynamics of cellular processes by using the approach of the Maximally Informative Next Experiment (MINE), which was introduced in W. Dong et al. (PLoS ONE 3(8):e3105, 2008) and independently in M.M. Donahue et al. (IET Syst. Biol. 4:249-262, 2010). In this approach, existing data is used to define a probability distribution on the parameters; the next measurement point is the one that yields the largest model output variance with this distribution. Building upon this approach, we introduce the Expected Dynamics Estimator (EDE), which is the expected value using this distribution of the output as a function of time. We prove the consistency of this estimator (uniform convergence to true dynamics) even when the chosen experiments cluster in a finite set of points. We extend this proof of consistency to various practical assumptions on noisy data and moderate levels of model mismatch. Through the derivation and proof, we develop a relaxed version of MINE that is more computationally tractable and robust than the original formulation. The results are illustrated with numerical examples on two nonlinear ordinary differential equation models of biomolecular and cellular processes.

Cellular Signaling Networks Function as Generalized Wiener-Kolmogorov Filters to Suppress Noise

NASA Astrophysics Data System (ADS)

Hinczewski, Michael; Thirumalai, D.

2014-10-01

Cellular signaling involves the transmission of environmental information through cascades of stochastic biochemical reactions, inevitably introducing noise that compromises signal fidelity. Each stage of the cascade often takes the form of a kinase-phosphatase push-pull network, a basic unit of signaling pathways whose malfunction is linked with a host of cancers. We show that this ubiquitous enzymatic network motif effectively behaves as a Wiener-Kolmogorov optimal noise filter. Using concepts from umbral calculus, we generalize the linear Wiener-Kolmogorov theory, originally introduced in the context of communication and control engineering, to take nonlinear signal transduction and discrete molecule populations into account. This allows us to derive rigorous constraints for efficient noise reduction in this biochemical system. Our mathematical formalism yields bounds on filter performance in cases important to cellular function—such as ultrasensitive response to stimuli. We highlight features of the system relevant for optimizing filter efficiency, encoded in a single, measurable, dimensionless parameter. Our theory, which describes noise control in a large class of signal transduction networks, is also useful both for the design of synthetic biochemical signaling pathways and the manipulation of pathways through experimental probes such as oscillatory input.

Ultralife's polymer electrolyte rechargeable lithium-ion batteries for use in the mobile electronics industry

NASA Astrophysics Data System (ADS)

Cuellar, Edward A.; Manna, Michael E.; Wise, Ralph D.; Gavrilov, Alexei B.; Bastian, Matthew J.; Brey, Rufus M.; DeMatteis, Jeffrey

Ultralife Polymer™ brand batteries for cellular phones as made by Nokia Mobile Phones Incorporated were introduced in July 2000. Characteristics of the UBC443483 cell and UB750N battery are described and related to the power and battery requirements of these cellular phones and chargers. Current, power, and pulse capability are presented as functions of temperature, depth of discharge, and storage at the cell level. Safety protection devices and chargers are discussed at the battery pack level, as well as performance in cellular phones under various wireless communication protocols. Performance is competitive with liquid lithium-ion systems while offering opportunity for non-traditional form factors.

A nonstandard finite difference scheme for a basic model of cellular immune response to viral infection

NASA Astrophysics Data System (ADS)

Korpusik, Adam

2017-02-01

We present a nonstandard finite difference scheme for a basic model of cellular immune response to viral infection. The main advantage of this approach is that it preserves the essential qualitative features of the original continuous model (non-negativity and boundedness of the solution, equilibria and their stability conditions), while being easy to implement. All of the qualitative features are preserved independently of the chosen step-size. Numerical simulations of our approach and comparison with other conventional simulation methods are presented.

Cellular automaton simulation examining progenitor hierarchy structure effects on mammary ductal carcinoma in situ.

PubMed

Bankhead, Armand; Magnuson, Nancy S; Heckendorn, Robert B

2007-06-07

A computer simulation is used to model ductal carcinoma in situ, a form of non-invasive breast cancer. The simulation uses known histological morphology, cell types, and stochastic cell proliferation to evolve tumorous growth within a duct. The ductal simulation is based on a hybrid cellular automaton design using genetic rules to determine each cell's behavior. The genetic rules are a mutable abstraction that demonstrate genetic heterogeneity in a population. Our goal was to examine the role (if any) that recently discovered mammary stem cell hierarchies play in genetic heterogeneity, DCIS initiation and aggressiveness. Results show that simpler progenitor hierarchies result in greater genetic heterogeneity and evolve DCIS significantly faster. However, the more complex progenitor hierarchy structure was able to sustain the rapid reproduction of a cancer cell population for longer periods of time.

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

PubMed

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.

Optimizing Cellular Networks Enabled with Renewal Energy via Strategic Learning.

PubMed

Sohn, Insoo; Liu, Huaping; Ansari, Nirwan

2015-01-01

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

Current status of robotic simulators in acquisition of robotic surgical skills.

PubMed

Kumar, Anup; Smith, Roger; Patel, Vipul R

2015-03-01

This article provides an overview of the current status of simulator systems in robotic surgery training curriculum, focusing on available simulators for training, their comparison, new technologies introduced in simulation focusing on concepts of training along with existing challenges and future perspectives of simulator training in robotic surgery. The different virtual reality simulators available in the market like dVSS, dVT, RoSS, ProMIS and SEP have shown face, content and construct validity in robotic skills training for novices outside the operating room. Recently, augmented reality simulators like HoST, Maestro AR and RobotiX Mentor have been introduced in robotic training providing a more realistic operating environment, emphasizing more on procedure-specific robotic training . Further, the Xperience Team Trainer, which provides training to console surgeon and bed-side assistant simultaneously, has been recently introduced to emphasize the importance of teamwork and proper coordination. Simulator training holds an important place in current robotic training curriculum of future robotic surgeons. There is a need for more procedure-specific augmented reality simulator training, utilizing advancements in computing and graphical capabilities for new innovations in simulator technology. Further studies are required to establish its cost-benefit ratio along with concurrent and predictive validity.

Computational membrane biophysics: From ion channel interactions with drugs to cellular function.

PubMed

Miranda, Williams E; Ngo, Van A; Perissinotti, Laura L; Noskov, Sergei Yu

2017-11-01

The rapid development of experimental and computational techniques has changed fundamentally our understanding of cellular-membrane transport. The advent of powerful computers and refined force-fields for proteins, ions, and lipids has expanded the applicability of Molecular Dynamics (MD) simulations. A myriad of cellular responses is modulated through the binding of endogenous and exogenous ligands (e.g. neurotransmitters and drugs, respectively) to ion channels. Deciphering the thermodynamics and kinetics of the ligand binding processes to these membrane proteins is at the heart of modern drug development. The ever-increasing computational power has already provided insightful data on the thermodynamics and kinetics of drug-target interactions, free energies of solvation, and partitioning into lipid bilayers for drugs. This review aims to provide a brief summary about modeling approaches to map out crucial binding pathways with intermediate conformations and free-energy surfaces for drug-ion channel binding mechanisms that are responsible for multiple effects on cellular functions. We will discuss post-processing analysis of simulation-generated data, which are then transformed to kinetic models to better understand the molecular underpinning of the experimental observables under the influence of drugs or mutations in ion channels. This review highlights crucial mathematical frameworks and perspectives on bridging different well-established computational techniques to connect the dynamics and timescales from all-atom MD and free energy simulations of ion channels to the physiology of action potentials in cellular models. This article is part of a Special Issue entitled: Biophysics in Canada, edited by Lewis Kay, John Baenziger, Albert Berghuis and Peter Tieleman. Copyright © 2017 Elsevier B.V. All rights reserved.

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

NASA Astrophysics Data System (ADS)

Rajagopalan, Ramesh; Hoffman, Mitchell

2016-09-01

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

1D-3D hybrid modeling-from multi-compartment models to full resolution models in space and time.

PubMed

Grein, Stephan; Stepniewski, Martin; Reiter, Sebastian; Knodel, Markus M; Queisser, Gillian

2014-01-01

Investigation of cellular and network dynamics in the brain by means of modeling and simulation has evolved into a highly interdisciplinary field, that uses sophisticated modeling and simulation approaches to understand distinct areas of brain function. Depending on the underlying complexity, these models vary in their level of detail, in order to cope with the attached computational cost. Hence for large network simulations, single neurons are typically reduced to time-dependent signal processors, dismissing the spatial aspect of each cell. For single cell or networks with relatively small numbers of neurons, general purpose simulators allow for space and time-dependent simulations of electrical signal processing, based on the cable equation theory. An emerging field in Computational Neuroscience encompasses a new level of detail by incorporating the full three-dimensional morphology of cells and organelles into three-dimensional, space and time-dependent, simulations. While every approach has its advantages and limitations, such as computational cost, integrated and methods-spanning simulation approaches, depending on the network size could establish new ways to investigate the brain. In this paper we present a hybrid simulation approach, that makes use of reduced 1D-models using e.g., the NEURON simulator-which couples to fully resolved models for simulating cellular and sub-cellular dynamics, including the detailed three-dimensional morphology of neurons and organelles. In order to couple 1D- and 3D-simulations, we present a geometry-, membrane potential- and intracellular concentration mapping framework, with which graph- based morphologies, e.g., in the swc- or hoc-format, are mapped to full surface and volume representations of the neuron and computational data from 1D-simulations can be used as boundary conditions for full 3D simulations and vice versa. Thus, established models and data, based on general purpose 1D-simulators, can be directly coupled to the emerging field of fully resolved, highly detailed 3D-modeling approaches. We present the developed general framework for 1D/3D hybrid modeling and apply it to investigate electrically active neurons and their intracellular spatio-temporal calcium dynamics.

Design of Improved Arithmetic Logic Unit in Quantum-Dot Cellular Automata

NASA Astrophysics Data System (ADS)

Heikalabad, Saeed Rasouli; Gadim, Mahya Rahimpour

2018-06-01

The quantum-dot cellular automata (QCA) can be replaced to overcome the limitation of CMOS technology. An arithmetic logic unit (ALU) is a basic structure of any computer devices. In this paper, design of improved single-bit arithmetic logic unit in quantum dot cellular automata is presented. The proposed structure for ALU has AND, OR, XOR and ADD operations. A unique 2:1 multiplexer, an ultra-efficient two-input XOR and a low complexity full adder are used in the proposed structure. Also, an extended design of this structure is provided for two-bit ALU in this paper. The proposed structure of ALU is simulated by QCADesigner and simulation result is evaluated. Evaluation results show that the proposed design has best performance in terms of area, complexity and delay compared to the previous designs.

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

NASA Astrophysics Data System (ADS)

Gouvêa, Maury Meirelles, Jr.

2017-03-01

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

Design of Improved Arithmetic Logic Unit in Quantum-Dot Cellular Automata

NASA Astrophysics Data System (ADS)

Heikalabad, Saeed Rasouli; Gadim, Mahya Rahimpour

2018-03-01

The quantum-dot cellular automata (QCA) can be replaced to overcome the limitation of CMOS technology. An arithmetic logic unit (ALU) is a basic structure of any computer devices. In this paper, design of improved single-bit arithmetic logic unit in quantum dot cellular automata is presented. The proposed structure for ALU has AND, OR, XOR and ADD operations. A unique 2:1 multiplexer, an ultra-efficient two-input XOR and a low complexity full adder are used in the proposed structure. Also, an extended design of this structure is provided for two-bit ALU in this paper. The proposed structure of ALU is simulated by QCADesigner and simulation result is evaluated. Evaluation results show that the proposed design has best performance in terms of area, complexity and delay compared to the previous designs.

Dengue fever spreading based on probabilistic cellular automata with two lattices

NASA Astrophysics Data System (ADS)

Pereira, F. M. M.; Schimit, P. H. T.

2018-06-01

Modeling and simulation of mosquito-borne diseases have gained attention due to a growing incidence in tropical countries in the past few years. Here, we study the dengue spreading in a population modeled by cellular automata, where there are two lattices to model the human-mosquitointeraction: one lattice for human individuals, and one lattice for mosquitoes in order to enable different dynamics in populations. The disease considered is the dengue fever with one, two or three different serotypes coexisting in population. Although many regions exhibit the incidence of only one serotype, here we set a complete framework to also study the occurrence of two and three serotypes at the same time in a population. Furthermore, the flexibility of the model allows its use to other mosquito-borne diseases, like chikungunya, yellow fever and malaria. An approximation of the cellular automata is proposed in terms of ordinary differential equations; the spreading of mosquitoes is studied and the influence of some model parameters are analyzed with numerical simulations. Finally, a method to combat dengue spreading is simulated based on a reduction of mosquito birth and mosquito bites in population.

Optimizing radiotherapy protocols using computer automata to model tumour cell death as a function of oxygen diffusion processes.

PubMed

Paul-Gilloteaux, Perrine; Potiron, Vincent; Delpon, Grégory; Supiot, Stéphane; Chiavassa, Sophie; Paris, François; Costes, Sylvain V

2017-05-23

The concept of hypofractionation is gaining momentum in radiation oncology centres, enabled by recent advances in radiotherapy apparatus. The gain of efficacy of this innovative treatment must be defined. We present a computer model based on translational murine data for in silico testing and optimization of various radiotherapy protocols with respect to tumour resistance and the microenvironment heterogeneity. This model combines automata approaches with image processing algorithms to simulate the cellular response of tumours exposed to ionizing radiation, modelling the alteration of oxygen permeabilization in blood vessels against repeated doses, and introducing mitotic catastrophe (as opposed to arbitrary delayed cell-death) as a means of modelling radiation-induced cell death. Published data describing cell death in vitro as well as tumour oxygenation in vivo are used to inform parameters. Our model is validated by comparing simulations to in vivo data obtained from the radiation treatment of mice transplanted with human prostate tumours. We then predict the efficacy of untested hypofractionation protocols, hypothesizing that tumour control can be optimized by adjusting daily radiation dosage as a function of the degree of hypoxia in the tumour environment. Further biological refinement of this tool will permit the rapid development of more sophisticated strategies for radiotherapy.

A signaling visualization toolkit to support rational design of combination therapies and biomarker discovery: SiViT.

PubMed

Bown, James L; Shovman, Mark; Robertson, Paul; Boiko, Andrei; Goltsov, Alexey; Mullen, Peter; Harrison, David J

2017-05-02

Targeted cancer therapy aims to disrupt aberrant cellular signalling pathways. Biomarkers are surrogates of pathway state, but there is limited success in translating candidate biomarkers to clinical practice due to the intrinsic complexity of pathway networks. Systems biology approaches afford better understanding of complex, dynamical interactions in signalling pathways targeted by anticancer drugs. However, adoption of dynamical modelling by clinicians and biologists is impeded by model inaccessibility. Drawing on computer games technology, we present a novel visualization toolkit, SiViT, that converts systems biology models of cancer cell signalling into interactive simulations that can be used without specialist computational expertise. SiViT allows clinicians and biologists to directly introduce for example loss of function mutations and specific inhibitors. SiViT animates the effects of these introductions on pathway dynamics, suggesting further experiments and assessing candidate biomarker effectiveness. In a systems biology model of Her2 signalling we experimentally validated predictions using SiViT, revealing the dynamics of biomarkers of drug resistance and highlighting the role of pathway crosstalk. No model is ever complete: the iteration of real data and simulation facilitates continued evolution of more accurate, useful models. SiViT will make accessible libraries of models to support preclinical research, combinatorial strategy design and biomarker discovery.

A Numerical Study of Scalable Cardiac Electro-Mechanical Solvers on HPC Architectures

PubMed Central

Colli Franzone, Piero; Pavarino, Luca F.; Scacchi, Simone

2018-01-01

We introduce and study some scalable domain decomposition preconditioners for cardiac electro-mechanical 3D simulations on parallel HPC (High Performance Computing) architectures. The electro-mechanical model of the cardiac tissue is composed of four coupled sub-models: (1) the static finite elasticity equations for the transversely isotropic deformation of the cardiac tissue; (2) the active tension model describing the dynamics of the intracellular calcium, cross-bridge binding and myofilament tension; (3) the anisotropic Bidomain model describing the evolution of the intra- and extra-cellular potentials in the deforming cardiac tissue; and (4) the ionic membrane model describing the dynamics of ionic currents, gating variables, ionic concentrations and stretch-activated channels. This strongly coupled electro-mechanical model is discretized in time with a splitting semi-implicit technique and in space with isoparametric finite elements. The resulting scalable parallel solver is based on Multilevel Additive Schwarz preconditioners for the solution of the Bidomain system and on BDDC preconditioned Newton-Krylov solvers for the non-linear finite elasticity system. The results of several 3D parallel simulations show the scalability of both linear and non-linear solvers and their application to the study of both physiological excitation-contraction cardiac dynamics and re-entrant waves in the presence of different mechano-electrical feedbacks. PMID:29674971

Stochastic dynamics and mechanosensitivity of myosin II minifilaments

NASA Astrophysics Data System (ADS)

Albert, Philipp J.; Erdmann, Thorsten; Schwarz, Ulrich S.

2014-09-01

Tissue cells are in a state of permanent mechanical tension that is maintained mainly by myosin II minifilaments, which are bipolar assemblies of tens of myosin II molecular motors contracting actin networks and bundles. Here we introduce a stochastic model for myosin II minifilaments as two small myosin II motor ensembles engaging in a stochastic tug-of-war. Each of the two ensembles is described by the parallel cluster model that allows us to use exact stochastic simulations and at the same time to keep important molecular details of the myosin II cross-bridge cycle. Our simulation and analytical results reveal a strong dependence of myosin II minifilament dynamics on environmental stiffness that is reminiscent of the cellular response to substrate stiffness. For small stiffness, minifilaments form transient crosslinks exerting short spikes of force with negligible mean. For large stiffness, minifilaments form near permanent crosslinks exerting a mean force which hardly depends on environmental elasticity. This functional switch arises because dissociation after the power stroke is suppressed by force (catch bonding) and because ensembles can no longer perform the power stroke at large forces. Symmetric myosin II minifilaments perform a random walk with an effective diffusion constant which decreases with increasing ensemble size, as demonstrated for rigid substrates with an analytical treatment.

Wise retained in the endoplasmic reticulum inhibits Wnt signaling by reducing cell surface LRP6.

PubMed

Guidato, Sonia; Itasaki, Nobue

2007-10-15

The Wnt signaling pathway is tightly regulated by extracellular and intracellular modulators. Wise was isolated as a secreted protein capable of interacting with the Wnt co-receptor LRP6. Studies in Xenopus embryos revealed that Wise either enhances or inhibits the Wnt pathway depending on the cellular context. Here we show that the cellular localization of Wise has distinct effects on the Wnt pathway readout. While secreted Wise either synergizes or inhibits the Wnt signals depending on the partner ligand, ER-retained Wise consistently blocks the Wnt pathway. ER-retained Wise reduces LRP6 on the cell surface, making cells less susceptible to the Wnt signal. This study provides a cellular mechanism for the action of Wise and introduces the modulation of cellular susceptibility to Wnt signals as a novel mechanism of the regulation of the Wnt pathway.

Hierarchical Targeting Strategy for Enhanced Tumor Tissue Accumulation/Retention and Cellular Internalization.

PubMed

Wang, Sheng; Huang, Peng; Chen, Xiaoyuan

2016-09-01

Targeted delivery of therapeutic agents is an important way to improve the therapeutic index and reduce side effects. To design nanoparticles for targeted delivery, both enhanced tumor tissue accumulation/retention and enhanced cellular internalization should be considered simultaneously. So far, there have been very few nanoparticles with immutable structures that can achieve this goal efficiently. Hierarchical targeting, a novel targeting strategy based on stimuli responsiveness, shows good potential to enhance both tumor tissue accumulation/retention and cellular internalization. Here, the recent design and development of hierarchical targeting nanoplatforms, based on changeable particle sizes, switchable surface charges and activatable surface ligands, will be introduced. In general, the targeting moieties in these nanoplatforms are not activated during blood circulation for efficient tumor tissue accumulation, but re-activated by certain internal or external stimuli in the tumor microenvironment for enhanced cellular internalization. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

PubMed

Nakajima, Kohei; Haruna, Taichi

2011-09-01

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

Control of fluxes in metabolic networks

PubMed Central

Basler, Georg; Nikoloski, Zoran; Larhlimi, Abdelhalim; Barabási, Albert-László; Liu, Yang-Yu

2016-01-01

Understanding the control of large-scale metabolic networks is central to biology and medicine. However, existing approaches either require specifying a cellular objective or can only be used for small networks. We introduce new coupling types describing the relations between reaction activities, and develop an efficient computational framework, which does not require any cellular objective for systematic studies of large-scale metabolism. We identify the driver reactions facilitating control of 23 metabolic networks from all kingdoms of life. We find that unicellular organisms require a smaller degree of control than multicellular organisms. Driver reactions are under complex cellular regulation in Escherichia coli, indicating their preeminent role in facilitating cellular control. In human cancer cells, driver reactions play pivotal roles in malignancy and represent potential therapeutic targets. The developed framework helps us gain insights into regulatory principles of diseases and facilitates design of engineering strategies at the interface of gene regulation, signaling, and metabolism. PMID:27197218

Progress in Mathematical Modeling of Gastrointestinal Slow Wave Abnormalities

PubMed Central

Du, Peng; Calder, Stefan; Angeli, Timothy R.; Sathar, Shameer; Paskaranandavadivel, Niranchan; O'Grady, Gregory; Cheng, Leo K.

2018-01-01

Gastrointestinal (GI) motility is regulated in part by electrophysiological events called slow waves, which are generated by the interstitial cells of Cajal (ICC). Slow waves propagate by a process of “entrainment,” which occurs over a decreasing gradient of intrinsic frequencies in the antegrade direction across much of the GI tract. Abnormal initiation and conduction of slow waves have been demonstrated in, and linked to, a number of GI motility disorders. A range of mathematical models have been developed to study abnormal slow waves and applied to propose novel methods for non-invasive detection and therapy. This review provides a general outline of GI slow wave abnormalities and their recent classification using multi-electrode (high-resolution) mapping methods, with a particular emphasis on the spatial patterns of these abnormal activities. The recently-developed mathematical models are introduced in order of their biophysical scale from cellular to whole-organ levels. The modeling techniques, main findings from the simulations, and potential future directions arising from notable studies are discussed. PMID:29379448

Capturing microscopic features of bone remodeling into a macroscopic model based on biological rationales of bone adaptation.

PubMed

Kim, Young Kwan; Kameo, Yoshitaka; Tanaka, Sakae; Adachi, Taiji

2017-10-01

To understand Wolff's law, bone adaptation by remodeling at the cellular and tissue levels has been discussed extensively through experimental and simulation studies. For the clinical application of a bone remodeling simulation, it is significant to establish a macroscopic model that incorporates clarified microscopic mechanisms. In this study, we proposed novel macroscopic models based on the microscopic mechanism of osteocytic mechanosensing, in which the flow of fluid in the lacuno-canalicular porosity generated by fluid pressure gradients plays an important role, and theoretically evaluated the proposed models, taking biological rationales of bone adaptation into account. The proposed models were categorized into two groups according to whether the remodeling equilibrium state was defined globally or locally, i.e., the global or local uniformity models. Each remodeling stimulus in the proposed models was quantitatively evaluated through image-based finite element analyses of a swine cancellous bone, according to two introduced criteria associated with the trabecular volume and orientation at remodeling equilibrium based on biological rationales. The evaluation suggested that nonuniformity of the mean stress gradient in the local uniformity model, one of the proposed stimuli, has high validity. Furthermore, the adaptive potential of each stimulus was discussed based on spatial distribution of a remodeling stimulus on the trabecular surface. The theoretical consideration of a remodeling stimulus based on biological rationales of bone adaptation would contribute to the establishment of a clinically applicable and reliable simulation model of bone remodeling.

Simulation of Changes in Diffusion Related to Different Pathologies at Cellular Level After Traumatic Brain Injury

PubMed Central

Lin, Mu; He, Hongjian; Schifitto, Giovanni; Zhong, Jianhui

2016-01-01

Purpose The goal of the current study was to investigate tissue pathology at the cellular level in traumatic brain injury (TBI) as revealed by Monte Carlo simulation of diffusion tensor imaging (DTI)-derived parameters and elucidate the possible sources of conflicting findings of DTI abnormalities as reported in the TBI literature. Methods A model with three compartments separated by permeable membranes was employed to represent the diffusion environment of water molecules in brain white matter. The dynamic diffusion process was simulated with a Monte Carlo method using adjustable parameters of intra-axonal diffusivity, axon separation, glial cell volume fraction, and myelin sheath permeability. The effects of tissue pathology on DTI parameters were investigated by adjusting the parameters of the model corresponding to different stages of brain injury. Results The results suggest that the model is appropriate and the DTI-derived parameters simulate the predominant cellular pathology after TBI. Our results further indicate that when edema is not prevalent, axial and radial diffusivity have better sensitivity to axonal injury and demyelination than other DTI parameters. Conclusion DTI is a promising biomarker to detect and stage tissue injury after TBI. The observed inconsistencies among previous studies are likely due to scanning at different stages of tissue injury after TBI. PMID:26256558

Introducing Teamwork Challenges in Simulation Using Game Cards.

PubMed

Chang, Todd P; Kwan, Karen Y; Liberman, Danica; Song, Eric; Dao, Eugene H; Chung, Dayun; Morton, Inge; Festekjian, Ara

2015-08-01

Poor teamwork and communication during resuscitations are linked to patient safety problems and poorer outcomes. We present a novel simulation-based educational intervention using game cards to introduce challenges in teamwork. This intervention uses sets of game cards that designate roles, limitations, or communication challenges designed to introduce common communication or teamwork problems. Game cards are designed to be applicable for any simulation-based scenario and are independent from patient physiology. In our example, participants were pediatric emergency medicine fellows undergoing simulation training for orientation. We describe the use of card sets in different scenarios with increasing teamwork challenge and difficulty. Both postscenario and summative debriefings were facilitated to allow participants to reflect on their performance and discover ways to apply their strategies to real resuscitations. In this article, we present our experience with the novel use of game cards to modify simulation scenarios to improve communication and teamwork skills.

1D-3D hybrid modeling—from multi-compartment models to full resolution models in space and time

PubMed Central

Grein, Stephan; Stepniewski, Martin; Reiter, Sebastian; Knodel, Markus M.; Queisser, Gillian

2014-01-01

Investigation of cellular and network dynamics in the brain by means of modeling and simulation has evolved into a highly interdisciplinary field, that uses sophisticated modeling and simulation approaches to understand distinct areas of brain function. Depending on the underlying complexity, these models vary in their level of detail, in order to cope with the attached computational cost. Hence for large network simulations, single neurons are typically reduced to time-dependent signal processors, dismissing the spatial aspect of each cell. For single cell or networks with relatively small numbers of neurons, general purpose simulators allow for space and time-dependent simulations of electrical signal processing, based on the cable equation theory. An emerging field in Computational Neuroscience encompasses a new level of detail by incorporating the full three-dimensional morphology of cells and organelles into three-dimensional, space and time-dependent, simulations. While every approach has its advantages and limitations, such as computational cost, integrated and methods-spanning simulation approaches, depending on the network size could establish new ways to investigate the brain. In this paper we present a hybrid simulation approach, that makes use of reduced 1D-models using e.g., the NEURON simulator—which couples to fully resolved models for simulating cellular and sub-cellular dynamics, including the detailed three-dimensional morphology of neurons and organelles. In order to couple 1D- and 3D-simulations, we present a geometry-, membrane potential- and intracellular concentration mapping framework, with which graph- based morphologies, e.g., in the swc- or hoc-format, are mapped to full surface and volume representations of the neuron and computational data from 1D-simulations can be used as boundary conditions for full 3D simulations and vice versa. Thus, established models and data, based on general purpose 1D-simulators, can be directly coupled to the emerging field of fully resolved, highly detailed 3D-modeling approaches. We present the developed general framework for 1D/3D hybrid modeling and apply it to investigate electrically active neurons and their intracellular spatio-temporal calcium dynamics. PMID:25120463

Oncogenes in retroviruses and cells

NASA Astrophysics Data System (ADS)

Kurth, Reinhard

1983-09-01

Oncogenes are genes that cause cancer. Retroviruses contain oncogenes and cause cancer in animals and, perhaps, in man. The viruses have appropriated their oncogenes from normal cellular DNA by genetic recombination. Correspondingly, uninfected vertebrate cells contain a family of evolutionary conserved cellular oncogenes. Retrovirus infection, introducing additional viral oncogenes into the cells, as well as carcinogen-mediated activation of cellular oncogenes may both lead to increased synthesis of oncogene encoded transforming proteins which convert normal cells to tumor cells. Unique retroviruses of human origin have recently been identified. They may, on occasion, directly cause tumors in man. However, the general significance of retroviruses may better be illustrated by their remarkable genetic composition which allows them to promote tumor growth by a variety of genetic mechanisms.

Intelligent call admission control for multi-class services in mobile cellular networks

NASA Astrophysics Data System (ADS)

Ma, Yufeng; Hu, Xiulin; Zhang, Yunyu

2005-11-01

Scarcity of the spectrum resource and mobility of users make quality of service (QoS) provision a critical issue in mobile cellular networks. This paper presents a fuzzy call admission control scheme to meet the requirement of the QoS. A performance measure is formed as a weighted linear function of new call and handoff call blocking probabilities of each service class. Simulation compares the proposed fuzzy scheme with complete sharing and guard channel policies. Simulation results show that fuzzy scheme has a better robust performance in terms of average blocking criterion.

Simulating pedestrian flow by an improved two-process cellular automaton model

NASA Astrophysics Data System (ADS)

Jin, Cheng-Jie; Wang, Wei; Jiang, Rui; Dong, Li-Yun

In this paper, we study the pedestrian flow with an Improved Two-Process (ITP) cellular automaton model, which is originally proposed by Blue and Adler. Simulations of pedestrian counterflow have been conducted, under both periodic and open boundary conditions. The lane formation phenomenon has been reproduced without using the place exchange rule. We also present and discuss the flow-density and velocity-density relationships of both uni-directional flow and counterflow. By the comparison with the Blue-Adler model, we find the ITP model has higher values of maximum flow, critical density and completely jammed density under different conditions.

Strange non-chaotic attractors in a state controlled-cellular neural network-based quasiperiodically forced MLC circuit

NASA Astrophysics Data System (ADS)

Ezhilarasu, P. Megavarna; Inbavalli, M.; Murali, K.; Thamilmaran, K.

2018-07-01

In this paper, we report the dynamical transitions to strange non-chaotic attractors in a quasiperiodically forced state controlled-cellular neural network (SC-CNN)-based MLC circuit via two different mechanisms, namely the Heagy-Hammel route and the gradual fractalisation route. These transitions were observed through numerical simulations and hardware experiments and confirmed using statistical tools, such as maximal Lyapunov exponent spectrum and its variance and singular continuous spectral analysis. We find that there is a remarkable agreement of the results from both numerical simulations as well as from hardware experiments.

Micro-simulation of vehicle conflicts involving right-turn vehicles at signalized intersections based on cellular automata.

PubMed

Chai, C; Wong, Y D

2014-02-01

At intersection, vehicles coming from different directions conflict with each other. Improper geometric design and signal settings at signalized intersection will increase occurrence of conflicts between road users and results in a reduction of the safety level. This study established a cellular automata (CA) model to simulate vehicular interactions involving right-turn vehicles (as similar to left-turn vehicles in US). Through various simulation scenarios for four case cross-intersections, the relationships between conflict occurrences involving right-turn vehicles with traffic volume and right-turn movement control strategies are analyzed. Impacts of traffic volume, permissive right-turn compared to red-amber-green (RAG) arrow, shared straight-through and right-turn lane as well as signal setting are estimated from simulation results. The simulation model is found to be able to provide reasonable assessment of conflicts through comparison of existed simulation approach and observed accidents. Through the proposed approach, prediction models for occurrences and severity of vehicle conflicts can be developed for various geometric layouts and traffic control strategies. Copyright © 2013 Elsevier Ltd. All rights reserved.

Statistical Emulator for Expensive Classification Simulators

NASA Technical Reports Server (NTRS)

Ross, Jerret; Samareh, Jamshid A.

2016-01-01

Expensive simulators prevent any kind of meaningful analysis to be performed on the phenomena they model. To get around this problem the concept of using a statistical emulator as a surrogate representation of the simulator was introduced in the 1980's. Presently, simulators have become more and more complex and as a result running a single example on these simulators is very expensive and can take days to weeks or even months. Many new techniques have been introduced, termed criteria, which sequentially select the next best (most informative to the emulator) point that should be run on the simulator. These criteria methods allow for the creation of an emulator with only a small number of simulator runs. We follow and extend this framework to expensive classification simulators.

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

PubMed

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.

Reprogramming One-Carbon Metabolic Pathways To Decouple l-Serine Catabolism from Cell Growth in Corynebacterium glutamicum.

PubMed

Zhang, Yun; Shang, Xiuling; Lai, Shujuan; Zhang, Yu; Hu, Qitiao; Chai, Xin; Wang, Bo; Liu, Shuwen; Wen, Tingyi

2018-02-16

l-Serine, the principal one-carbon source for DNA biosynthesis, is difficult for microorganisms to accumulate due to the coupling of l-serine catabolism and microbial growth. Here, we reprogrammed the one-carbon unit metabolic pathways in Corynebacterium glutamicum to decouple l-serine catabolism from cell growth. In silico model-based simulation showed a negative influence on glyA-encoding serine hydroxymethyltransferase flux with l-serine productivity. Attenuation of glyA transcription resulted in increased l-serine accumulation, and a decrease in purine pools, poor growth and longer cell shapes. The gcvTHP-encoded glycine cleavage (Gcv) system from Escherichia coli was introduced into C. glutamicum, allowing glycine-derived 13 CH 2 to be assimilated into intracellular purine synthesis, which resulted in an increased amount of one-carbon units. Gcv introduction not only restored cell viability and morphology but also increased l-serine accumulation. Moreover, comparative proteomic analysis indicated that abundance changes of the enzymes involved in one-carbon unit cycles might be responsible for maintaining one-carbon unit homeostasis. Reprogramming of the one-carbon metabolic pathways allowed cells to reach a comparable growth rate to accumulate 13.21 g/L l-serine by fed-batch fermentation in minimal medium. This novel strategy provides new insights into the regulation of cellular properties and essential metabolite accumulation by introducing an extrinsic pathway.

Engineering a pH responsive pore forming protein.

PubMed

Kisovec, Matic; Rezelj, Saša; Knap, Primož; Cajnko, Miša Mojca; Caserman, Simon; Flašker, Ajda; Žnidaršič, Nada; Repič, Matej; Mavri, Janez; Ruan, Yi; Scheuring, Simon; Podobnik, Marjetka; Anderluh, Gregor

2017-02-08

Listeriolysin O (LLO) is a cytolysin capable of forming pores in cholesterol-rich lipid membranes of host cells. It is conveniently suited for engineering a pH-governed responsiveness, due to a pH sensor identified in its structure that was shown before to affect its stability. Here we introduced a new level of control of its hemolytic activity by making a variant with hemolytic activity that was pH-dependent. Based on detailed structural analysis coupled with molecular dynamics and mutational analysis, we found that the bulky side chain of Tyr406 allosterically affects the pH sensor. Molecular dynamics simulation further suggested which other amino acid residues may also allosterically influence the pH-sensor. LLO was engineered to the point where it can, in a pH-regulated manner, perforate artificial and cellular membranes. The single mutant Tyr406Ala bound to membranes and oligomerized similarly to the wild-type LLO, however, the final membrane insertion step was pH-affected by the introduced mutation. We show that the mutant toxin can be activated at the surface of artificial membranes or living cells by a single wash with slightly acidic pH buffer. Y406A mutant has a high potential in development of novel nanobiotechnological applications such as controlled release of substances or as a sensor of environmental pH.

Engineering a pH responsive pore forming protein

NASA Astrophysics Data System (ADS)

Kisovec, Matic; Rezelj, Saša; Knap, Primož; Cajnko, Miša Mojca; Caserman, Simon; Flašker, Ajda; Žnidaršič, Nada; Repič, Matej; Mavri, Janez; Ruan, Yi; Scheuring, Simon; Podobnik, Marjetka; Anderluh, Gregor

2017-02-01

Listeriolysin O (LLO) is a cytolysin capable of forming pores in cholesterol-rich lipid membranes of host cells. It is conveniently suited for engineering a pH-governed responsiveness, due to a pH sensor identified in its structure that was shown before to affect its stability. Here we introduced a new level of control of its hemolytic activity by making a variant with hemolytic activity that was pH-dependent. Based on detailed structural analysis coupled with molecular dynamics and mutational analysis, we found that the bulky side chain of Tyr406 allosterically affects the pH sensor. Molecular dynamics simulation further suggested which other amino acid residues may also allosterically influence the pH-sensor. LLO was engineered to the point where it can, in a pH-regulated manner, perforate artificial and cellular membranes. The single mutant Tyr406Ala bound to membranes and oligomerized similarly to the wild-type LLO, however, the final membrane insertion step was pH-affected by the introduced mutation. We show that the mutant toxin can be activated at the surface of artificial membranes or living cells by a single wash with slightly acidic pH buffer. Y406A mutant has a high potential in development of novel nanobiotechnological applications such as controlled release of substances or as a sensor of environmental pH.

Methods of introducing nucleic acids into cellular DNA

DOEpatents

Lajoie, Marc J.; Gregg, Christopher J.; Mosberg, Joshua A.; Church, George M.

2017-06-27

A method of introducing a nucleic acid sequence into a cell is provided where the cell has impaired or inhibited or disrupted DnaG primase activity or impaired or inhibited or disrupted DnaB helicase activity, or larger or increased gaps or distance between Okazaki fragments or lowered or reduced frequency of Okazaki fragment initiation, or the cell has increased single stranded DNA (ssDNA) on the lagging strand of the replication fork including transforming the cell through recombination with a nucleic acid oligomer.

Reliable Cellular Automata with Self-Organization

NASA Astrophysics Data System (ADS)

Gács, Peter

2001-04-01

In a probabilistic cellular automaton in which all local transitions have positive probability, the problem of keeping a bit of information indefinitely is nontrivial, even in an infinite automaton. Still, there is a solution in 2 dimensions, and this solution can be used to construct a simple 3-dimensional discrete-time universal fault-tolerant cellular automaton. This technique does not help much to solve the following problems: remembering a bit of information in 1 dimension; computing in dimensions lower than 3; computing in any dimension with non-synchronized transitions. Our more complex technique organizes the cells in blocks that perform a reliable simulation of a second (generalized) cellular automaton. The cells of the latter automaton are also organized in blocks, simulating even more reliably a third automaton, etc. Since all this (a possibly infinite hierarchy) is organized in "software," it must be under repair all the time from damage caused by errors. A large part of the problem is essentially self-stabilization recovering from a mess of arbitrary size and content. The present paper constructs an asynchronous one-dimensional fault-tolerant cellular automaton, with the further feature of "self-organization." The latter means that unless a large amount of input information must be given, the initial configuration can be chosen homogeneous.

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

PubMed Central

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

2013-01-01

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

Experimental identification of a comb-shaped chaotic region in multiple parameter spaces simulated by the Hindmarsh—Rose neuron model

NASA Astrophysics Data System (ADS)

Jia, Bing

2014-03-01

A comb-shaped chaotic region has been simulated in multiple two-dimensional parameter spaces using the Hindmarsh—Rose (HR) neuron model in many recent studies, which can interpret almost all of the previously simulated bifurcation processes with chaos in neural firing patterns. In the present paper, a comb-shaped chaotic region in a two-dimensional parameter space was reproduced, which presented different processes of period-adding bifurcations with chaos with changing one parameter and fixed the other parameter at different levels. In the biological experiments, different period-adding bifurcation scenarios with chaos by decreasing the extra-cellular calcium concentration were observed from some neural pacemakers at different levels of extra-cellular 4-aminopyridine concentration and from other pacemakers at different levels of extra-cellular caesium concentration. By using the nonlinear time series analysis method, the deterministic dynamics of the experimental chaotic firings were investigated. The period-adding bifurcations with chaos observed in the experiments resembled those simulated in the comb-shaped chaotic region using the HR model. The experimental results show that period-adding bifurcations with chaos are preserved in different two-dimensional parameter spaces, which provides evidence of the existence of the comb-shaped chaotic region and a demonstration of the simulation results in different two-dimensional parameter spaces in the HR neuron model. The results also present relationships between different firing patterns in two-dimensional parameter spaces.

Cellular automaton model of crowd evacuation inspired by slime mould

NASA Astrophysics Data System (ADS)

Kalogeiton, V. S.; Papadopoulos, D. P.; Georgilas, I. P.; Sirakoulis, G. Ch.; Adamatzky, A. I.

2015-04-01

In all the living organisms, the self-preservation behaviour is almost universal. Even the most simple of living organisms, like slime mould, is typically under intense selective pressure to evolve a response to ensure their evolution and safety in the best possible way. On the other hand, evacuation of a place can be easily characterized as one of the most stressful situations for the individuals taking part on it. Taking inspiration from the slime mould behaviour, we are introducing a computational bio-inspired model crowd evacuation model. Cellular Automata (CA) were selected as a fully parallel advanced computation tool able to mimic the Physarum's behaviour. In particular, the proposed CA model takes into account while mimicking the Physarum foraging process, the food diffusion, the organism's growth, the creation of tubes for each organism, the selection of optimum tube for each human in correspondence to the crowd evacuation under study and finally, the movement of all humans at each time step towards near exit. To test the model's efficiency and robustness, several simulation scenarios were proposed both in virtual and real-life indoor environments (namely, the first floor of office building B of the Department of Electrical and Computer Engineering of Democritus University of Thrace). The proposed model is further evaluated in a purely quantitative way by comparing the simulation results with the corresponding ones from the bibliography taken by real data. The examined fundamental diagrams of velocity-density and flow-density are found in full agreement with many of the already published corresponding results proving the adequacy, the fitness and the resulting dynamics of the model. Finally, several real Physarum experiments were conducted in an archetype of the aforementioned real-life environment proving at last that the proposed model succeeded in reproducing sufficiently the Physarum's recorded behaviour derived from observation of the aforementioned biological laboratory experiments.

Adsorption of charged protein residues on an inorganic nanosheet: Computer simulation of LDH interaction with ion channel

NASA Astrophysics Data System (ADS)

Tsukanov, Alexey A.; Psakhie, Sergey G.

2016-08-01

Quasi-two-dimensional and hybrid nanomaterials based on layered double hydroxides (LDH), cationic clays, layered oxyhydroxides and hydroxides of metals possess large specific surface area and strong electrostatic properties with permanent or pH-dependent electric charge. Such nanomaterials may impact cellular electrostatics, changing the ion balance, pH and membrane potential. Selective ion adsorption/exchange may alter the transmembrane electrochemical gradient, disrupting potential-dependent cellular processes. Cellular proteins as a rule have charged residues which can be effectively adsorbed on the surface of layered hydroxide based nanomaterials. The aim of this study is to attempt to shed some light on the possibility and mechanisms of protein "adhesion" an LDH nanosheet and to propose a new direction in anticancer medicine, based on physical impact and strong electrostatics. An unbiased molecular dynamics simulation was performed and the combined process free energy estimation (COPFEE) approach was used.

Are There Roles for Brain Cell Senescence in Aging and Neurodegenerative Disorders?

PubMed Central

Tan, Florence C. C.; Hutchison, Emmette R.; Eitan, Erez; Mattson, Mark P.

2014-01-01

The term cellular senescence was introduced more than five decades ago to describe the state of growth arrest observed in aging cells. Since this initial discovery, the phenotypes associated with cellular senescence have expanded beyond growth arrest to include alterations in cellular metabolism, secreted cytokines, epigenetic regulation and protein expression. Recently, senescence has been shown to play an important role in vivo not only in relation to aging, but also during embryonic development. Thus, cellular senescence serves different purposes and comprises a wide range of distinct phenotypes across multiple cell types. Whether all cell types, including post-mitotic neurons, are capable of entering into a senescent state remains unclear. In this review we examine recent data that suggest that cellular senescence plays a role in brain aging and, notably, may not be limited to glia but also neurons. We suggest that there is a high level of similarity between some of the pathological changes that occur in the brain in Alzheimer’s and Parkinson’s diseases and those phenotypes observed in cellular senescence, leading us to propose that neurons and glia can exhibit hallmarks of senescence previously documented in peripheral tissues. PMID:25305051

Are there roles for brain cell senescence in aging and neurodegenerative disorders?

PubMed

Tan, Florence C C; Hutchison, Emmette R; Eitan, Erez; Mattson, Mark P

2014-12-01

The term cellular senescence was introduced more than five decades ago to describe the state of growth arrest observed in aging cells. Since this initial discovery, the phenotypes associated with cellular senescence have expanded beyond growth arrest to include alterations in cellular metabolism, secreted cytokines, epigenetic regulation and protein expression. Recently, senescence has been shown to play an important role in vivo not only in relation to aging, but also during embryonic development. Thus, cellular senescence serves different purposes and comprises a wide range of distinct phenotypes across multiple cell types. Whether all cell types, including post-mitotic neurons, are capable of entering into a senescent state remains unclear. In this review we examine recent data that suggest that cellular senescence plays a role in brain aging and, notably, may not be limited to glia but also neurons. We suggest that there is a high level of similarity between some of the pathological changes that occur in the brain in Alzheimer's and Parkinson's diseases and those phenotypes observed in cellular senescence, leading us to propose that neurons and glia can exhibit hallmarks of senescence previously documented in peripheral tissues.

Emergence of tissue mechanics from cellular processes: shaping a fly wing

NASA Astrophysics Data System (ADS)

Merkel, Matthias; Etournay, Raphael; Popovic, Marko; Nandi, Amitabha; Brandl, Holger; Salbreux, Guillaume; Eaton, Suzanne; Jülicher, Frank

Nowadays, biologistsare able to image biological tissueswith up to 10,000 cells in vivowhere the behavior of each individual cell can be followed in detail.However, how precisely large-scale tissue deformation and stresses emerge from cellular behavior remains elusive. Here, we study this question in the developing wing of the fruit fly. To this end, we first establish a geometrical framework that exactly decomposes tissue deformation into contributions by different kinds of cellular processes. These processes comprise cell shape changes, cell neighbor exchanges, cell divisions, and cell extrusions. As the key idea, we introduce a tiling of the cellular network into triangles. This approach also reveals that tissue deformation can also be created by correlated cellular motion. Based on quantifications using these concepts, we developed a novel continuum mechanical model for the fly wing. In particular, our model includes active anisotropic stresses and a delay in the response of cell rearrangements to material stresses. A different approach to study the emergence of tissue mechanics from cellular behavior are cell-based models. We characterize the properties of a cell-based model for 3D tissues that is a hybrid between single particle models and the so-called vertex models.

Virtual tissues in toxicology.

PubMed

Shah, Imran; Wambaugh, John

2010-02-01

New approaches are vital for efficiently evaluating human health risk of thousands of chemicals in commerce. In vitro models offer a high-throughput approach for assaying chemical-induced molecular and cellular changes; however, bridging these perturbations to in vivo effects across chemicals, dose, time, and species remains challenging. Technological advances in multiresolution imaging and multiscale simulation are making it feasible to reconstruct tissues in silico. In toxicology, these "virtual" tissues (VT) aim to predict histopathological outcomes from alterations of cellular phenotypes that are controlled by chemical-induced perturbations in molecular pathways. The behaviors of thousands of heterogeneous cells in tissues are simulated discretely using agent-based modeling (ABM), in which computational "agents" mimic cell interactions and cellular responses to the microenvironment. The behavior of agents is constrained by physical laws and biological rules derived from experimental evidence. VT extend compartmental physiologic models to simulate both acute insults as well as the chronic effects of low-dose exposure. Furthermore, agent behavior can encode the logic of signaling and genetic regulatory networks to evaluate the role of different pathways in chemical-induced injury. To extrapolate toxicity across species, chemicals, and doses, VT require four main components: (a) organization of prior knowledge on physiologic events to define the mechanistic rules for agent behavior, (b) knowledge on key chemical-induced molecular effects, including activation of stress sensors and changes in molecular pathways that alter the cellular phenotype, (c) multiresolution quantitative and qualitative analysis of histologic data to characterize and measure chemical-, dose-, and time-dependent physiologic events, and (d) multiscale, spatiotemporal simulation frameworks to effectively calibrate and evaluate VT using experimental data. This investigation presents the motivation, implementation, and application of VT with examples from hepatotoxicity and carcinogenesis.

Automated and Adaptable Quantification of Cellular Alignment from Microscopic Images for Tissue Engineering Applications

PubMed Central

Xu, Feng; Beyazoglu, Turker; Hefner, Evan; Gurkan, Umut Atakan

2011-01-01

Cellular alignment plays a critical role in functional, physical, and biological characteristics of many tissue types, such as muscle, tendon, nerve, and cornea. Current efforts toward regeneration of these tissues include replicating the cellular microenvironment by developing biomaterials that facilitate cellular alignment. To assess the functional effectiveness of the engineered microenvironments, one essential criterion is quantification of cellular alignment. Therefore, there is a need for rapid, accurate, and adaptable methodologies to quantify cellular alignment for tissue engineering applications. To address this need, we developed an automated method, binarization-based extraction of alignment score (BEAS), to determine cell orientation distribution in a wide variety of microscopic images. This method combines a sequenced application of median and band-pass filters, locally adaptive thresholding approaches and image processing techniques. Cellular alignment score is obtained by applying a robust scoring algorithm to the orientation distribution. We validated the BEAS method by comparing the results with the existing approaches reported in literature (i.e., manual, radial fast Fourier transform-radial sum, and gradient based approaches). Validation results indicated that the BEAS method resulted in statistically comparable alignment scores with the manual method (coefficient of determination R2=0.92). Therefore, the BEAS method introduced in this study could enable accurate, convenient, and adaptable evaluation of engineered tissue constructs and biomaterials in terms of cellular alignment and organization. PMID:21370940

Microsandwich cellular solids

NASA Technical Reports Server (NTRS)

Balakrishna Bhat, T.; O'Donnell, Tim; Wang, Taylor G.

1989-01-01

This article introduces a new concept of microsandwiching in which the cell wall itself is a sandwich structure and is substantially stiffer. Some experimental results are presented to show the efficacy of this approach. A method for optimizing the design of honeycomb microsandwich is also briefly outlined.

Natural isotope correction of MS/MS measurements for metabolomics and (13)C fluxomics.

PubMed

Niedenführ, Sebastian; ten Pierick, Angela; van Dam, Patricia T N; Suarez-Mendez, Camilo A; Nöh, Katharina; Wahl, S Aljoscha

2016-05-01

Fluxomics and metabolomics are crucial tools for metabolic engineering and biomedical analysis to determine the in vivo cellular state. Especially, the application of (13)C isotopes allows comprehensive insights into the functional operation of cellular metabolism. Compared to single MS, tandem mass spectrometry (MS/MS) provides more detailed and accurate measurements of the metabolite enrichment patterns (tandem mass isotopomers), increasing the accuracy of metabolite concentration measurements and metabolic flux estimation. MS-type data from isotope labeling experiments is biased by naturally occurring stable isotopes (C, H, N, O, etc.). In particular, GC-MS(/MS) requires derivatization for the usually non-volatile intracellular metabolites introducing additional natural isotopes leading to measurements that do not directly represent the carbon labeling distribution. To make full use of LC- and GC-MS/MS mass isotopomer measurements, the influence of natural isotopes has to be eliminated (corrected). Our correction approach is analyzed for the two most common applications; (13)C fluxomics and isotope dilution mass spectrometry (IDMS) based metabolomics. Natural isotopes can have an impact on the calculated flux distribution which strongly depends on the substrate labeling and the actual flux distribution. Second, we show that in IDMS based metabolomics natural isotopes lead to underestimated concentrations that can and should be corrected with a nonlinear calibration. Our simulations indicate that the correction for natural abundance in isotope based fluxomics and quantitative metabolomics is essential for correct data interpretation. © 2015 Wiley Periodicals, Inc.

Reciprocal Control of the Circadian Clock and Cellular Redox State - a Critical Appraisal.

PubMed

Putker, Marrit; O'Neill, John Stuart

2016-01-01

Redox signalling comprises the biology of molecular signal transduction mediated by reactive oxygen (or nitrogen) species. By specific and reversible oxidation of redox-sensitive cysteines, many biological processes sense and respond to signals from the intracellular redox environment. Redox signals are therefore important regulators of cellular homeostasis. Recently, it has become apparent that the cellular redox state oscillates in vivo and in vitro, with a period of about one day (circadian). Circadian time-keeping allows cells and organisms to adapt their biology to resonate with the 24-hour cycle of day/night. The importance of this innate biological time-keeping is illustrated by the association of clock disruption with the early onset of several diseases (e.g. type II diabetes, stroke and several forms of cancer). Circadian regulation of cellular redox balance suggests potentially two distinct roles for redox signalling in relation to the cellular clock: one where it is regulated by the clock, and one where it regulates the clock. Here, we introduce the concepts of redox signalling and cellular timekeeping, and then critically appraise the evidence for the reciprocal regulation between cellular redox state and the circadian clock. We conclude there is a substantial body of evidence supporting circadian regulation of cellular redox state, but that it would be premature to conclude that the converse is also true. We therefore propose some approaches that might yield more insight into redox control of cellular timekeeping.

Reciprocal Control of the Circadian Clock and Cellular Redox State - a Critical Appraisal

PubMed Central

Putker, Marrit; O’Neill, John Stuart

2016-01-01

Redox signalling comprises the biology of molecular signal transduction mediated by reactive oxygen (or nitrogen) species. By specific and reversible oxidation of redox-sensitive cysteines, many biological processes sense and respond to signals from the intracellular redox environment. Redox signals are therefore important regulators of cellular homeostasis. Recently, it has become apparent that the cellular redox state oscillates in vivo and in vitro, with a period of about one day (circadian). Circadian time-keeping allows cells and organisms to adapt their biology to resonate with the 24-hour cycle of day/night. The importance of this innate biological time-keeping is illustrated by the association of clock disruption with the early onset of several diseases (e.g. type II diabetes, stroke and several forms of cancer). Circadian regulation of cellular redox balance suggests potentially two distinct roles for redox signalling in relation to the cellular clock: one where it is regulated by the clock, and one where it regulates the clock. Here, we introduce the concepts of redox signalling and cellular timekeeping, and then critically appraise the evidence for the reciprocal regulation between cellular redox state and the circadian clock. We conclude there is a substantial body of evidence supporting circadian regulation of cellular redox state, but that it would be premature to conclude that the converse is also true. We therefore propose some approaches that might yield more insight into redox control of cellular timekeeping. PMID:26810072

Liquid Crystal Spatial Light Modulators for Simulating Zonal Multifocal Lenses.

PubMed

Li, Yiyu; Bradley, Arthur; Xu, Renfeng; Kollbaum, Pete S

2017-09-01

To maximize efficiency of the normally lengthy and costly multizone lens design and testing process, it is advantageous to evaluate the potential efficacy of a design as thoroughly as possible prior to lens fabrication and on-eye testing. The current work describes an ex vivo approach of optical design testing. The aim of this study was to describe a system capable of examining the optical characteristics of multizone bifocal and multifocal optics by subaperture stitching using liquid crystal technologies. A liquid crystal spatial light modulator (SLM) was incorporated in each of two channels to generate complementary subapertures by amplitude modulation. Additional trial lenses and phase plates were placed in pupil conjugate planes of either channel to integrate the desired bifocal and multifocal optics once the two optical paths were recombined. A high-resolution Shack-Hartmann aberrometer was integrated to measure the optics of the dual-channel system. Power and wavefront error maps as well as point spread functions were measured and computed for each of three multizone multifocal designs. High transmission modulation was achieved by introducing half-wavelength optical path differences to create two- and five-zone bifocal apertures. Dual-channel stitching revealed classic annular rings in the point spread functions generated from two-zone designs when the outer annular optic was defocused. However, low efficiency of the SLM prevented us from simultaneously measuring the eye + simulator aberrations, and the higher-order diffraction patterns generated by the cellular structure of the liquid crystal arrays limited the visual field to ±0.45 degrees. The system successfully simulated bifocal and multifocal simultaneous lenses allowing for future evaluation of both objective and subjective evaluation of complex optical designs. However, low efficiency and diffraction phenomena of the SLM limit the utility of this technology for simulating multizone and multifocal optics.

From Stochastic Foam to Designed Structure: Balancing Cost and Performance of Cellular Metals

PubMed Central

Lehmhus, Dirk; Vesenjak, Matej

2017-01-01

Over the past two decades, a large number of metallic foams have been developed. In recent years research on this multi-functional material class has further intensified. However, despite their unique properties only a limited number of large-scale applications have emerged. One important reason for this sluggish uptake is their high cost. Many cellular metals require expensive raw materials, complex manufacturing procedures, or a combination thereof. Some attempts have been made to decrease costs by introducing novel foams based on cheaper components and new manufacturing procedures. However, this has often yielded materials with unreliable properties that inhibit utilization of their full potential. The resulting balance between cost and performance of cellular metals is probed in this editorial, which attempts to consider cost not in absolute figures, but in relation to performance. To approach such a distinction, an alternative classification of cellular metals is suggested which centers on structural aspects and the effort of realizing them. The range thus covered extends from fully stochastic foams to cellular structures designed-to-purpose. PMID:28786935

Multifunctional Cellular Materials Based on 2D Nanomaterials: Prospects and Challenges.

PubMed

Qiu, Ling; He, Zijun; Li, Dan

2018-01-01

Recent advances in emerging 2D nanomaterial-based cellular materials (2D-CMs) open up new opportunities for the development of next generation cellular solids with exceptional properties. Herein, an overview of the current research status of 2D-CMs is provided and their future opportunities are highlighted. First, the unique features of 2D nanomaterials are introduced to illustrate why these nanoscale building blocks are promising for the development of novel cellular materials and what the new features of 2D nanoscale building blocks can offer when compared to their 0D and 1D counterparts. An in-depth discussion on the structure-property relationships of 2D-CMs is then provided, and the remarkable functions that can be achieved by engineering their cellular architecture are highlighted. Additionally, the use of 2D-CMs to tackle key challenges in different practical applications is demonstrated. In conclusion, a personal perspective on the challenges and future research directions of 2D-CMs is given. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A cellular automaton model of wildfire propagation and extinction

Treesearch

Keith C. Clarke; James A. Brass; Phillip J. Riggan

1994-01-01

We propose a new model to predict the spatial and temporal behavior of wildfires. Fire spread and intensity were simulated using a cellular automaton model. Monte Carlo techniques were used to provide fire risk probabilities for areas where fuel loadings and topography are known. The model assumes predetermined or measurable environmental variables such as wind...

A Comparison of Three Approaches to Model Human Behavior

NASA Astrophysics Data System (ADS)

Palmius, Joel; Persson-Slumpi, Thomas

2010-11-01

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

Lipid-converter, a framework for lipid manipulations in molecular dynamics simulations

PubMed Central

Larsson, Per; Kasson, Peter M.

2014-01-01

Construction of lipid membrane and membrane protein systems for molecular dynamics simulations can be a challenging process. In addition, there are few available tools to extend existing studies by repeating simulations using other force fields and lipid compositions. To facilitate this, we introduce lipidconverter, a modular Python framework for exchanging force fields and lipid composition in coordinate files obtained from simulations. Force fields and lipids are specified by simple text files, making it easy to introduce support for additional force fields and lipids. The converter produces simulation input files that can be used for structural relaxation of the new membranes. PMID:25081234

Modeling and Simulation of Hydropower Station Diversion System's characteristic line method by introducing water head to flow feedback

NASA Astrophysics Data System (ADS)

Guangwen, Xu; Xi, Li; Ze, Yao

2018-06-01

To solve the damping problem of water hammer wave in the modeling method of water diversion system of hydropower station, this paper introduces the feedback regulation technology from head to flow, that is: A fixed water head is taken out for flow feedback, and the following conclusions are obtained through modeling and simulation. Adjusting the feedback coefficient F of the water head to the flow rate can change the damping characteristic of the system, which can simulate the attenuation process of the water shock wave in the true water diversion pipeline. Even if a small feedback coefficient is introduced, the damping effect of the system is very obvious, but it has little effect on the amplitude of the first water shock wave after the transition process. Therefore, it is feasible and reasonable to introduce water head to flow rate feedback coefficient F in hydraulic turbine diversion system.

The extracellular matrix: Structure, composition, age-related differences, tools for analysis and applications for tissue engineering.

PubMed

Kular, Jaspreet K; Basu, Shouvik; Sharma, Ram I

2014-01-01

The extracellular matrix is a structural support network made up of diverse proteins, sugars and other components. It influences a wide number of cellular processes including migration, wound healing and differentiation, all of which is of particular interest to researchers in the field of tissue engineering. Understanding the composition and structure of the extracellular matrix will aid in exploring the ways the extracellular matrix can be utilised in tissue engineering applications especially as a scaffold. This review summarises the current knowledge of the composition, structure and functions of the extracellular matrix and introduces the effect of ageing on extracellular matrix remodelling and its contribution to cellular functions. Additionally, the current analytical technologies to study the extracellular matrix and extracellular matrix-related cellular processes are also reviewed.

Administrative and research policies required to bring cellular therapies from the research laboratory to the patient's bedside.

PubMed

Yim, Robyn

2005-10-01

The research process is a balance between the inherent risks of new discoveries and the risks of research participant safety. Conflicts of interest, inherent to the research process, as well as those introduced by emerging cellular therapies, have the potential to compromise safety. The relationship of trust between the researcher and the clinical trial participant facilitates objective decision making, in the best interest of both parties. In the setup of each clinical trial, investigators incorporate ethical, political, legal, financial, and regulatory considerations as protocols are established. Responsibility to abide by these decisions ensures a systematic process and safeguards participants in this process. The integrity of the research process is strengthened by identifying potential conflicting issues with the guiding principles established in the protocols, which may threaten the objectivity of involved parties and jeopardize safety of the participants. The rapid pace and changing paradigms of new discoveries in cellular therapies exaggerate existing conflicts and introduce new ones. Ethical issues raised by emerging cellular therapies include the division of opinions regarding the use of embryonic and fetal tissue to develop stem cell lines for research, the individual versus professional conscience of a researcher, overselling of outcomes as a result of the researcher's desire to be the first to discover a cellular therapy, and therapeutic misconception resulting from a participant's desire for a miracle cure. The basic ethical issue of whether stem cells should be utilized as a cellular therapy raises heated debates because some believe that it is not acceptable to use fetal material as a source of research material for future cures and others feel equally as strong that inaction is unethical because it results in needless suffering and death owing to the absence of this research. Political issues include the divergent position statements of presidential administrations on cellular therapy, variations in individual state laws, and states becoming involved in research funding, such as California's Proposition 71. Legal concerns include expanding private litigation with diversity of lawsuits, expanding lists of defendants, and the use of class-action lawsuits in research cases. Ownership issues also arise in terms of intellectual property, patents, and ownership of stem cells collected from minors, as in umbilical cord blood donations. Situations that challenge the regulatory processes established to ensure participant safety include differences in reporting requirements for private- and public-funded research and the lack of adequate funding and resources to implement and support the institutional review board (IRB) process. Financial considerations influence the development of clinical protocols, because funding is often limited. Financial incentives, personal investment in companies funding research activities, and fundraising pressures may present potential conflicts. In addition, the increasing role of emerging biotechnology start-up companies and pharmaceutical companies in clinical research introduces additional financial considerations. Administrative policies are needed to address these possible conflicts and ensure research participant safety as cellular therapies progress from the research laboratories to the patient's bedside. Administrative policies to ensure minimum standards of quality for emerging products before human clinical trials, policies to enforce consistent reporting requirements for private and public cellular research, policies to minimize financial conflicts of interest, policies to strengthen implementation of the existing IRB process and to structure into the process a consistent, systematic review of these identified conflicts, and policies to limit private litigation will help to preserve the objectivity of the review process and ultimately increase participant safety.

Parallel Implementation of Triangular Cellular Automata for Computing Two-Dimensional Elastodynamic Response on Arbitrary Domains

NASA Astrophysics Data System (ADS)

Leamy, Michael J.; Springer, Adam C.

In this research we report parallel implementation of a Cellular Automata-based simulation tool for computing elastodynamic response on complex, two-dimensional domains. Elastodynamic simulation using Cellular Automata (CA) has recently been presented as an alternative, inherently object-oriented technique for accurately and efficiently computing linear and nonlinear wave propagation in arbitrarily-shaped geometries. The local, autonomous nature of the method should lead to straight-forward and efficient parallelization. We address this notion on symmetric multiprocessor (SMP) hardware using a Java-based object-oriented CA code implementing triangular state machines (i.e., automata) and the MPI bindings written in Java (MPJ Express). We use MPJ Express to reconfigure our existing CA code to distribute a domain's automata to cores present on a dual quad-core shared-memory system (eight total processors). We note that this message passing parallelization strategy is directly applicable to computer clustered computing, which will be the focus of follow-on research. Results on the shared memory platform indicate nearly-ideal, linear speed-up. We conclude that the CA-based elastodynamic simulator is easily configured to run in parallel, and yields excellent speed-up on SMP hardware.

Dirac Cellular Automaton from Split-step Quantum Walk

PubMed Central

Mallick, Arindam; Chandrashekar, C. M.

2016-01-01

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

Effects of pH and aggregation in the human prion conversion into scrapie form: a study using molecular dynamics with excited normal modes.

PubMed

Lima, Angelica Nakagawa; de Oliveira, Ronaldo Junio; Braz, Antônio Sérgio Kimus; de Souza Costa, Maurício Garcia; Perahia, David; Scott, Luis Paulo Barbour

2018-03-15

There are two different prion conformations: (1) the cellular natural (PrP C ) and (2) the scrapie (PrP Sc ), an infectious form that tends to aggregate under specific conditions. PrP C and PrP Sc are widely different regarding secondary and tertiary structures. PrP Sc contains more and longer β-strands compared to PrP C . The lack of solved PrP Sc structures precludes a proper understanding of the mechanisms related to the transition between cellular and scrapie forms, as well as the aggregation process. In order to investigate the conformational transition between PrP C and PrP Sc , we applied MDeNM (molecular dynamics with excited normal modes), an enhanced sampling simulation technique that has been recently developed to probe large structural changes. These simulations yielded new structural rearrangements of the cellular prion that would have been difficult to obtain with standard MD simulations. We observed an increase in β-sheet formation under low pH (≤ 4) and upon oligomerization, whose relevance was discussed on the basis of the energy landscape theory for protein folding. The characterization of intermediate structures corresponding to transition states allowed us to propose a conversion model from the cellular to the scrapie prion, which possibly ignites the fibril formation. This model can assist the design of new drugs to prevent neurological disorders related to the prion aggregation mechanism.

Epidermal Homeostasis and Radiation Responses in a Multiscale Tissue Modeling Framework

NASA Technical Reports Server (NTRS)

Hu, Shaowen; Cucinotta, Francis A.

2013-01-01

The surface of skin is lined with several thin layers of epithelial cells that are maintained throughout life time by a small population of stem cells. High dose radiation exposures could injure and deplete the underlying proliferative cells and induce cutaneous radiation syndrome. In this work we propose a multiscale computational model for skin epidermal dynamics that links phenomena occurring at the subcellular, cellular, and tissue levels of organization, to simulate the experimental data of the radiation response of swine epidermis, which is closely similar to human epidermis. Incorporating experimentally measured histological and cell kinetic parameters, we obtain results of population kinetics and proliferation indexes comparable to observations in unirradiated and acutely irradiated swine experiments. At the sub-cellular level, several recently published Wnt signaling controlled cell-cycle models are applied and the roles of key components and parameters are analyzed. Based on our simulation results, we demonstrate that a moderate increase of proliferation rate for the survival proliferative cells is sufficient to fully repopulate the area denuded by high dose radiation, as long as the integrity of underlying basement membrane is maintained. Our work highlights the importance of considering proliferation kinetics as well as the spatial organization of tissues when conducting in vivo investigations of radiation responses. This integrated model allow us to test the validity of several basic biological rules at the cellular level and sub-cellular mechanisms by qualitatively comparing simulation results with published research, and enhance our understanding of the pathophysiological effects of ionizing radiation on skin.

Hybrid deterministic/stochastic simulation of complex biochemical systems.

PubMed

Lecca, Paola; Bagagiolo, Fabio; Scarpa, Marina

2017-11-21

In a biological cell, cellular functions and the genetic regulatory apparatus are implemented and controlled by complex networks of chemical reactions involving genes, proteins, and enzymes. Accurate computational models are indispensable means for understanding the mechanisms behind the evolution of a complex system, not always explored with wet lab experiments. To serve their purpose, computational models, however, should be able to describe and simulate the complexity of a biological system in many of its aspects. Moreover, it should be implemented by efficient algorithms requiring the shortest possible execution time, to avoid enlarging excessively the time elapsing between data analysis and any subsequent experiment. Besides the features of their topological structure, the complexity of biological networks also refers to their dynamics, that is often non-linear and stiff. The stiffness is due to the presence of molecular species whose abundance fluctuates by many orders of magnitude. A fully stochastic simulation of a stiff system is computationally time-expensive. On the other hand, continuous models are less costly, but they fail to capture the stochastic behaviour of small populations of molecular species. We introduce a new efficient hybrid stochastic-deterministic computational model and the software tool MoBioS (MOlecular Biology Simulator) implementing it. The mathematical model of MoBioS uses continuous differential equations to describe the deterministic reactions and a Gillespie-like algorithm to describe the stochastic ones. Unlike the majority of current hybrid methods, the MoBioS algorithm divides the reactions' set into fast reactions, moderate reactions, and slow reactions and implements a hysteresis switching between the stochastic model and the deterministic model. Fast reactions are approximated as continuous-deterministic processes and modelled by deterministic rate equations. Moderate reactions are those whose reaction waiting time is greater than the fast reaction waiting time but smaller than the slow reaction waiting time. A moderate reaction is approximated as a stochastic (deterministic) process if it was classified as a stochastic (deterministic) process at the time at which it crosses the threshold of low (high) waiting time. A Gillespie First Reaction Method is implemented to select and execute the slow reactions. The performances of MoBios were tested on a typical example of hybrid dynamics: that is the DNA transcription regulation. The simulated dynamic profile of the reagents' abundance and the estimate of the error introduced by the fully deterministic approach were used to evaluate the consistency of the computational model and that of the software tool.

Membrane Sculpting by F-BAR Domains Studied by Molecular Dynamics Simulations

PubMed Central

Yu, Hang; Schulten, Klaus

2013-01-01

Interplay between cellular membranes and their peripheral proteins drives many processes in eukaryotic cells. Proteins of the Bin/Amphiphysin/Rvs (BAR) domain family, in particular, play a role in cellular morphogenesis, for example curving planar membranes into tubular membranes. However, it is still unclear how F-BAR domain proteins act on membranes. Electron microscopy revealed that, in vitro, F-BAR proteins form regular lattices on cylindrically deformed membrane surfaces. Using all-atom and coarse-grained (CG) molecular dynamics simulations, we show that such lattices, indeed, induce tubes of observed radii. A 250 ns all-atom simulation reveals that F-BAR domain curves membranes via the so-called scaffolding mechanism. Plasticity of the F-BAR domain permits conformational change in response to membrane interaction, via partial unwinding of the domains 3-helix bundle structure. A CG simulation covering more than 350 µs provides a dynamic picture of membrane tubulation by lattices of F-BAR domains. A series of CG simulations identified the optimal lattice type for membrane sculpting, which matches closely the lattices seen through cryo-electron microscopy. PMID:23382665

Simulating Hepatic Lesions as Virtual Cellular Systems

EPA Science Inventory

The US EPA Virtual Liver (v-Liver) project is aimed at reducing the uncertainty in estimating the risk of toxic outcomes in humans by simulating the dose-dependent effects of environmental chemicals in silico. The v-Liver embodies an emerging field of research in computational ti...

Atrial Model Development and Prototype Simulations: CRADA Final Report on Tasks 3 and 4

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

O'Hara, T.; Zhang, X.; Villongco, C.

2016-10-28

The goal of this CRADA was to develop essential tools needed to simulate human atrial electrophysiology in 3-dimensions using an anatomical image-based anatomy and physiologically detailed human cellular model. The atria were modeled as anisotropic, representing the preferentially longitudinal electrical coupling between myocytes. Across the entire anatomy, cellular electrophysiology was heterogeneous, with left and right atrial myocytes defined differently. Left and right cell types for the “control” case of sinus rhythm (SR) was compared with remodeled electrophysiology and calcium cycling characteristics of chronic atrial fibrillation (cAF). The effects of Isoproterenol (ISO), a beta-adrenergic agonist that represents the functional consequences ofmore » PKA phosphorylation of various ion channels and transporters, was also simulated in SR and cAF to represent atrial activity under physical or emotional stress. Results and findings from Tasks 3 & 4 are described. Tasks 3 and 4 are, respectively: Input parameters prepared for a Cardioid simulation; Report including recommendations for additional scenario development and post-processing analytic strategy.« less

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

PubMed

Zhang, Fan; Liu, Runsheng; Zheng, Jie

2016-12-23

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

Effect of simulated microgravity and shear stress on microcin B17 production by Escherichia coli and on its excretion into the medium

NASA Technical Reports Server (NTRS)

Fang, A.; Pierson, D. L.; Koenig, D. W.; Mishra, S. K.; Demain, A. L.

1997-01-01

Production of the antibacterial polypeptide microcin B17 (MccB17) by Escherichia coli ZK650 was inhibited by simulated microgravity. The site of MccB17 accumulation was found to be different, depending on whether the organism was grown in shaking flasks or in rotating bioreactors designed to establish a simulated microgravity environment. In flasks, the accumulation was cellular, but in the reactors, virtually all the microcin was found in the medium. The change from a cellular site to an extracellular one was apparently not a function of gravity, since extracellular production occurred in these bioreactors, irrespective of whether they were operated in the simulated microgravity or normal gravity mode. More probably, excretion is due to the much lower degree of shear stress in the bioreactors. Addition of even a single glass bead to the 50-ml medium volume in the bioreactor created enough shear to change the site of MccB17 accumulation from the medium to the cells.

Ca-Pri a Cellular Automata Phenomenological Research Investigation: Simulation Results

NASA Astrophysics Data System (ADS)

Iannone, G.; Troisi, A.

2013-05-01

Following the introduction of a phenomenological cellular automata (CA) model capable to reproduce city growth and urban sprawl, we develop a toy model simulation considering a realistic framework. The main characteristic of our approach is an evolution algorithm based on inhabitants preferences. The control of grown cells is obtained by means of suitable functions which depend on the initial condition of the simulation. New born urban settlements are achieved by means of a logistic evolution of the urban pattern while urban sprawl is controlled by means of the population evolution function. In order to compare model results with a realistic urban framework we have considered, as the area of study, the island of Capri (Italy) in the Mediterranean Sea. Two different phases of the urban evolution on the island have been taken into account: a new born initial growth as induced by geographic suitability and the simulation of urban spread after 1943 induced by the population evolution after this date.

Impact of simulated microgravity on the normal developmental time line of an animal-bacteria symbiosis

PubMed Central

Foster, Jamie S.; Khodadad, Christina L. M.; Ahrendt, Steven R.; Parrish, Mirina L.

2013-01-01

The microgravity environment during space flight imposes numerous adverse effects on animal and microbial physiology. It is unclear, however, how microgravity impacts those cellular interactions between mutualistic microbes and their hosts. Here, we used the symbiosis between the host squid Euprymna scolopes and its luminescent bacterium Vibrio fischeri as a model system. We examined the impact of simulated microgravity on the timeline of bacteria-induced development in the host light organ, the site of the symbiosis. To simulate the microgravity environment, host squid and symbiosis-competent bacteria were incubated together in high-aspect ratio rotating wall vessel bioreactors and examined throughout the early stages of the bacteria-induced morphogenesis. The host innate immune response was suppressed under simulated microgravity; however, there was an acceleration of bacteria-induced apoptosis and regression in the host tissues. These results suggest that the space flight environment may alter the cellular interactions between animal hosts and their natural healthy microbiome. PMID:23439280

A new coarse-grained model for E. coli cytoplasm: accurate calculation of the diffusion coefficient of proteins and observation of anomalous diffusion.

PubMed

Hasnain, Sabeeha; McClendon, Christopher L; Hsu, Monica T; Jacobson, Matthew P; Bandyopadhyay, Pradipta

2014-01-01

A new coarse-grained model of the E. coli cytoplasm is developed by describing the proteins of the cytoplasm as flexible units consisting of one or more spheres that follow Brownian dynamics (BD), with hydrodynamic interactions (HI) accounted for by a mean-field approach. Extensive BD simulations were performed to calculate the diffusion coefficients of three different proteins in the cellular environment. The results are in close agreement with experimental or previously simulated values, where available. Control simulations without HI showed that use of HI is essential to obtain accurate diffusion coefficients. Anomalous diffusion inside the crowded cellular medium was investigated with Fractional Brownian motion analysis, and found to be present in this model. By running a series of control simulations in which various forces were removed systematically, it was found that repulsive interactions (volume exclusion) are the main cause for anomalous diffusion, with a secondary contribution from HI.

Fire training in a virtual-reality environment

NASA Astrophysics Data System (ADS)

Freund, Eckhard; Rossmann, Jurgen; Bucken, Arno

2005-03-01

Although fire is very common in our daily environment - as a source of energy at home or as a tool in industry - most people cannot estimate the danger of a conflagration. Therefore it is important to train people in combating fire. Beneath training with propane simulators or real fires and real extinguishers, fire training can be performed in virtual reality, which means a pollution-free and fast way of training. In this paper we describe how to enhance a virtual-reality environment with a real-time fire simulation and visualisation in order to establish a realistic emergency-training system. The presented approach supports extinguishing of the virtual fire including recordable performance data as needed in teletraining environments. We will show how to get realistic impressions of fire using advanced particle-simulation and how to use the advantages of particles to trigger states in a modified cellular automata used for the simulation of fire-behaviour. Using particle systems that interact with cellular automata it is possible to simulate a developing, spreading fire and its reaction on different extinguishing agents like water, CO2 or oxygen. The methods proposed in this paper have been implemented and successfully tested on Cosimir, a commercial robot-and VR-simulation-system.

Wavefront cellular learning automata.

PubMed

Moradabadi, Behnaz; Meybodi, Mohammad Reza

2018-02-01

This paper proposes a new cellular learning automaton, called a wavefront cellular learning automaton (WCLA). The proposed WCLA has a set of learning automata mapped to a connected structure and uses this structure to propagate the state changes of the learning automata over the structure using waves. In the WCLA, after one learning automaton chooses its action, if this chosen action is different from the previous action, it can send a wave to its neighbors and activate them. Each neighbor receiving the wave is activated and must choose a new action. This structure for the WCLA is necessary in many dynamic areas such as social networks, computer networks, grid computing, and web mining. In this paper, we introduce the WCLA framework as an optimization tool with diffusion capability, study its behavior over time using ordinary differential equation solutions, and present its accuracy using expediency analysis. To show the superiority of the proposed WCLA, we compare the proposed method with some other types of cellular learning automata using two benchmark problems.

Designed Transcriptional Regulation in Mammalian Cells Based on TALE- and CRISPR/dCas9.

PubMed

Lebar, Tina; Jerala, Roman

2018-01-01

Transcriptional regulation lies at the center of many cellular processes and is the result of cellular response to different external and internal signals. Control of transcription of selected genes enables an unprecedented access to shape the cellular response. While orthogonal transcription factors from bacteria, yeast, plants, or other cells have been used to introduce new cellular logic into mammalian cells, the discovery of designable modular DNA binding domains, such as Transcription Activator-Like Effectors (TALEs) and the CRISPR system, enable targeting of almost any selected DNA sequence. Fusion or conditional association of DNA targeting domain with transcriptional effector domains enables controlled regulation of almost any endogenous or ectopic gene. Moreover, the designed regulators can be linked into genetic circuits to implement complex responses, such as different types of Boolean functions and switches. In this chapter, we describe the protocols for achieving efficient transcriptional regulation with TALE- and CRISPR-based designed transcription factors in mammalian cells.

Wavefront cellular learning automata

NASA Astrophysics Data System (ADS)

Moradabadi, Behnaz; Meybodi, Mohammad Reza

2018-02-01

This paper proposes a new cellular learning automaton, called a wavefront cellular learning automaton (WCLA). The proposed WCLA has a set of learning automata mapped to a connected structure and uses this structure to propagate the state changes of the learning automata over the structure using waves. In the WCLA, after one learning automaton chooses its action, if this chosen action is different from the previous action, it can send a wave to its neighbors and activate them. Each neighbor receiving the wave is activated and must choose a new action. This structure for the WCLA is necessary in many dynamic areas such as social networks, computer networks, grid computing, and web mining. In this paper, we introduce the WCLA framework as an optimization tool with diffusion capability, study its behavior over time using ordinary differential equation solutions, and present its accuracy using expediency analysis. To show the superiority of the proposed WCLA, we compare the proposed method with some other types of cellular learning automata using two benchmark problems.

Control of fluxes in metabolic networks.

PubMed

Basler, Georg; Nikoloski, Zoran; Larhlimi, Abdelhalim; Barabási, Albert-László; Liu, Yang-Yu

2016-07-01

Understanding the control of large-scale metabolic networks is central to biology and medicine. However, existing approaches either require specifying a cellular objective or can only be used for small networks. We introduce new coupling types describing the relations between reaction activities, and develop an efficient computational framework, which does not require any cellular objective for systematic studies of large-scale metabolism. We identify the driver reactions facilitating control of 23 metabolic networks from all kingdoms of life. We find that unicellular organisms require a smaller degree of control than multicellular organisms. Driver reactions are under complex cellular regulation in Escherichia coli, indicating their preeminent role in facilitating cellular control. In human cancer cells, driver reactions play pivotal roles in malignancy and represent potential therapeutic targets. The developed framework helps us gain insights into regulatory principles of diseases and facilitates design of engineering strategies at the interface of gene regulation, signaling, and metabolism. © 2016 Basler et al.; Published by Cold Spring Harbor Laboratory Press.

Designer amphiphilic proteins as building blocks for the intracellular formation of organelle-like compartments

NASA Astrophysics Data System (ADS)

Huber, Matthias C.; Schreiber, Andreas; von Olshausen, Philipp; Varga, Balázs R.; Kretz, Oliver; Joch, Barbara; Barnert, Sabine; Schubert, Rolf; Eimer, Stefan; Kele, Péter; Schiller, Stefan M.

2015-01-01

Nanoscale biological materials formed by the assembly of defined block-domain proteins control the formation of cellular compartments such as organelles. Here, we introduce an approach to intentionally ‘program’ the de novo synthesis and self-assembly of genetically encoded amphiphilic proteins to form cellular compartments, or organelles, in Escherichia coli. These proteins serve as building blocks for the formation of artificial compartments in vivo in a similar way to lipid-based organelles. We investigated the formation of these organelles using epifluorescence microscopy, total internal reflection fluorescence microscopy and transmission electron microscopy. The in vivo modification of these protein-based de novo organelles, by means of site-specific incorporation of unnatural amino acids, allows the introduction of artificial chemical functionalities. Co-localization of membrane proteins results in the formation of functionalized artificial organelles combining artificial and natural cellular function. Adding these protein structures to the cellular machinery may have consequences in nanobiotechnology, synthetic biology and materials science, including the constitution of artificial cells and bio-based metamaterials.

3D visualization of subcellular structures of Schizosaccharomyces pombe by hard X-ray tomography.

PubMed

Yang, Y; Li, W; Liu, G; Zhang, X; Chen, J; Wu, W; Guan, Y; Xiong, Y; Tian, Y; Wu, Z

2010-10-01

Cellular structures of the fission yeast, Schizosaccharomyces pombe, were examined by using hard X-ray tomography. Since cells are nearly transparent to hard X-rays, Zernike phase contrast and heavy metal staining were introduced to improve image contrast. Through using such methods, images taken at 8 keV displayed sufficient contrast for observing cellular structures. The cell wall, the intracellular organelles and the entire structural organization of the whole cells were visualized in three-dimensional at a resolution better than 100 nm. Comparison between phase contrast and absorption contrast was also made, indicating the obvious advantage of phase contrast for cellular imaging at this energy. Our results demonstrate that hard X-ray tomography with Zernike phase contrast is suitable for cellular imaging. Its unique abilities make it have potential to become a useful tool for revealing structural information from cells, especially thick eukaryotic cells. © 2010 The Authors Journal compilation © 2010 The Royal Microscopical Society.

Exact results of 1D traffic cellular automata: The low-density behavior of the Fukui-Ishibashi model

NASA Astrophysics Data System (ADS)

Salcido, Alejandro; Hernández-Zapata, Ernesto; Carreón-Sierra, Susana

2018-03-01

The maximum entropy states of the cellular automata models for traffic flow in a single-lane with no anticipation are presented and discussed. The exact analytical solutions for the low-density behavior of the stochastic Fukui-Ishibashi traffic model were obtained and compared with computer simulations of the model. An excellent agreement was found.

A stochastic cellular automata model of tautomer equilibria

NASA Astrophysics Data System (ADS)

Bowers, Gregory A.; Seybold, Paul G.

2018-03-01

Many chemical substances, including drugs and biomolecules, exist in solution not as a single species, but as a collection of tautomers and related species. Importantly, each of these species is an independent compoundwith its own specific biochemical and physicochemical properties. The species interconvert in a dynamic and often complicated manner, making modelling the overall species composition difficult. Agent-based cellular automata models are uniquely suited to meet this challenge, allowing the equilibria to be simulated using simple rulesand at the same time capturing the inherent stochasticity of the natural phenomenon. In the present example a stochastic cellular automata model is employed to simulate the tautomer equilibria of 9-anthrone and 9-anthrol in the presence of their common anion. The observed KE of the 9-anthrone ⇌ 9-anthrol tautomerisation along with the measured tautomer pKa values were used to model the equilibria at pH values 4, 7 and 10. At pH 4 and 7, the anthrone comprises >99% of the total species population, while at pH 10the anthrone and the anion each represent just under half of the total population. The advantages of the cellular automata approach over the customary coupled differential equation approach are discussed.

Assessment of statistical education in Indonesia: Preliminary results and initiation to simulation-based inference

NASA Astrophysics Data System (ADS)

Saputra, K. V. I.; Cahyadi, L.; Sembiring, U. A.

2018-01-01

Start in this paper, we assess our traditional elementary statistics education and also we introduce elementary statistics with simulation-based inference. To assess our statistical class, we adapt the well-known CAOS (Comprehensive Assessment of Outcomes in Statistics) test that serves as an external measure to assess the student’s basic statistical literacy. This test generally represents as an accepted measure of statistical literacy. We also introduce a new teaching method on elementary statistics class. Different from the traditional elementary statistics course, we will introduce a simulation-based inference method to conduct hypothesis testing. From the literature, it has shown that this new teaching method works very well in increasing student’s understanding of statistics.

Promoting advanced traveler information systems among cellular and land-line phone users : SmarTraveler experience in Boston

DOT National Transportation Integrated Search

1997-01-01

In 1993 the SmarTraveler advanced traveler information system (ATIS) was introduced to travelers in the greater Boston area as part of an operational test jointly funded by FHWA and the Massachusetts Executive Office of Transportation and Constructio...

LIVING RESOURCES AND THEIR HABITATS ARE THE FOCUS OF THE GULF ECOLOGY DIVISION'S MISSION

EPA Science Inventory

This brief article introduces ERF Newsletter readers to the Gulf Ecology Division. Future articles will showcase our estuarine and near-coastal research efforts in areas such as biochemical and cellular toxicology, temporal and spatial scaling of ecological data, reproductive and...

Brownian dynamics simulations of sequence-dependent duplex denaturation in dynamically superhelical DNA

NASA Astrophysics Data System (ADS)

Mielke, Steven P.; Grønbech-Jensen, Niels; Krishnan, V. V.; Fink, William H.; Benham, Craig J.

2005-09-01

The topological state of DNA in vivo is dynamically regulated by a number of processes that involve interactions with bound proteins. In one such process, the tracking of RNA polymerase along the double helix during transcription, restriction of rotational motion of the polymerase and associated structures, generates waves of overtwist downstream and undertwist upstream from the site of transcription. The resulting superhelical stress is often sufficient to drive double-stranded DNA into a denatured state at locations such as promoters and origins of replication, where sequence-specific duplex opening is a prerequisite for biological function. In this way, transcription and other events that actively supercoil the DNA provide a mechanism for dynamically coupling genetic activity with regulatory and other cellular processes. Although computer modeling has provided insight into the equilibrium dynamics of DNA supercoiling, to date no model has appeared for simulating sequence-dependent DNA strand separation under the nonequilibrium conditions imposed by the dynamic introduction of torsional stress. Here, we introduce such a model and present results from an initial set of computer simulations in which the sequences of dynamically superhelical, 147 base pair DNA circles were systematically altered in order to probe the accuracy with which the model can predict location, extent, and time of stress-induced duplex denaturation. The results agree both with well-tested statistical mechanical calculations and with available experimental information. Additionally, we find that sites susceptible to denaturation show a propensity for localizing to supercoil apices, suggesting that base sequence determines locations of strand separation not only through the energetics of interstrand interactions, but also by influencing the geometry of supercoiling.

Jimena: efficient computing and system state identification for genetic regulatory networks.

PubMed

Karl, Stefan; Dandekar, Thomas

2013-10-11

Boolean networks capture switching behavior of many naturally occurring regulatory networks. For semi-quantitative modeling, interpolation between ON and OFF states is necessary. The high degree polynomial interpolation of Boolean genetic regulatory networks (GRNs) in cellular processes such as apoptosis or proliferation allows for the modeling of a wider range of node interactions than continuous activator-inhibitor models, but suffers from scaling problems for networks which contain nodes with more than ~10 inputs. Many GRNs from literature or new gene expression experiments exceed those limitations and a new approach was developed. (i) As a part of our new GRN simulation framework Jimena we introduce and setup Boolean-tree-based data structures; (ii) corresponding algorithms greatly expedite the calculation of the polynomial interpolation in almost all cases, thereby expanding the range of networks which can be simulated by this model in reasonable time. (iii) Stable states for discrete models are efficiently counted and identified using binary decision diagrams. As application example, we show how system states can now be sampled efficiently in small up to large scale hormone disease networks (Arabidopsis thaliana development and immunity, pathogen Pseudomonas syringae and modulation by cytokinins and plant hormones). Jimena simulates currently available GRNs about 10-100 times faster than the previous implementation of the polynomial interpolation model and even greater gains are achieved for large scale-free networks. This speed-up also facilitates a much more thorough sampling of continuous state spaces which may lead to the identification of new stable states. Mutants of large networks can be constructed and analyzed very quickly enabling new insights into network robustness and behavior.

Brownian dynamics simulations of sequence-dependent duplex denaturation in dynamically superhelical DNA.

PubMed

Mielke, Steven P; Grønbech-Jensen, Niels; Krishnan, V V; Fink, William H; Benham, Craig J

2005-09-22

The topological state of DNA in vivo is dynamically regulated by a number of processes that involve interactions with bound proteins. In one such process, the tracking of RNA polymerase along the double helix during transcription, restriction of rotational motion of the polymerase and associated structures, generates waves of overtwist downstream and undertwist upstream from the site of transcription. The resulting superhelical stress is often sufficient to drive double-stranded DNA into a denatured state at locations such as promoters and origins of replication, where sequence-specific duplex opening is a prerequisite for biological function. In this way, transcription and other events that actively supercoil the DNA provide a mechanism for dynamically coupling genetic activity with regulatory and other cellular processes. Although computer modeling has provided insight into the equilibrium dynamics of DNA supercoiling, to date no model has appeared for simulating sequence-dependent DNA strand separation under the nonequilibrium conditions imposed by the dynamic introduction of torsional stress. Here, we introduce such a model and present results from an initial set of computer simulations in which the sequences of dynamically superhelical, 147 base pair DNA circles were systematically altered in order to probe the accuracy with which the model can predict location, extent, and time of stress-induced duplex denaturation. The results agree both with well-tested statistical mechanical calculations and with available experimental information. Additionally, we find that sites susceptible to denaturation show a propensity for localizing to supercoil apices, suggesting that base sequence determines locations of strand separation not only through the energetics of interstrand interactions, but also by influencing the geometry of supercoiling.

Effects of Gravity, Microgravity or Microgravity Simulation on Early Mammalian Development.

PubMed

Ruden, Douglas M; Bolnick, Alan; Awonuga, Awoniyi; Abdulhasan, Mohammed; Perez, Gloria; Puscheck, Elizabeth E; Rappolee, Daniel A

2018-06-11

Plant and animal life forms evolved mechanisms for sensing and responding to gravity on Earth where homeostatic needs require responses. The lack of gravity, such as in the International Space Station (ISS), causes acute, intra-generational changes in the quality of life. These include maintaining calcium levels in bone, maintaining muscle tone, and disturbances in the vestibular apparatus in the ears. These problems decrease work efficiency and quality of life of humans not only during microgravity exposures but also after return to higher gravity on Earth or destinations such as Mars or the Moon. It has been hypothesized that lack of gravity during mammalian development may cause prenatal, postnatal and transgenerational effects that conflict with the environment, especially if the developing organism and its progeny are returned, or introduced de novo, into the varied gravity environments mentioned above. Although chicken and frog pregastrulation development, and plant root development, have profound effects due to orientation of cues by gravity-sensing mechanisms and responses, mammalian development is not typically characterized as gravity-sensing. Although no effects of microgravity simulation (MGS) on mouse fertilization were observed in two reports, negative effects of MGS on early mammalian development after fertilization and before gastrulation are presented in four reports that vary with the modality of MGS. This review will analyze the positive and negative mammalian early developmental outcomes, and enzymatic and epigenetic mechanisms known to mediate developmental responses to simulated microgravity on Earth and microgravity during spaceflight experiments. We will update experimental techniques that have already been developed or need to be developed for zero gravity molecular, cellular, and developmental biology experiments.

The Virtual Liver Project: Simulating Tissue Injury Through Molecular and Cellular Processes

EPA Science Inventory

Efficiently and humanely testing the safety of thousands of environmental chemicals is a challenge. The US EPA Virtual Liver Project (v-Liver™) is aimed at simulating the effects of environmental chemicals computationally in order to estimate the risk of toxic outcomes in humans...

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

NASA Astrophysics Data System (ADS)

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

2012-01-01

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

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

NASA Astrophysics Data System (ADS)

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 cellular solids and make substantial contributions to the theoretical advance of impact dynamics.

Virtual Habitat -a dynamic simulation of closed life support systems -human model status

NASA Astrophysics Data System (ADS)

Markus Czupalla, M. Sc.; Zhukov, Anton; Hwang, Su-Au; Schnaitmann, Jonas

In order to optimize Life Support Systems on a system level, stability questions must be in-vestigated. To do so the exploration group of the Technical University of Munich (TUM) is developing the "Virtual Habitat" (V-HAB) dynamic LSS simulation software. V-HAB shall provide the possibility to conduct dynamic simulations of entire mission scenarios for any given LSS configuration. The Virtual Habitat simulation tool consists of four main modules: • Closed Environment Module (CEM) -monitoring of compounds in a closed environment • Crew Module (CM) -dynamic human simulation • P/C Systems Module (PCSM) -dynamic P/C subsystems • Plant Module (PM) -dynamic plant simulation The core module of the simulation is the dynamic and environment sensitive human module. Introduced in its basic version in 2008, the human module has been significantly updated since, increasing its capabilities and maturity significantly. In this paper three newly added human model subsystems (thermal regulation, digestion and schedule controller) are introduced touching also on the human stress subsystem which is cur-rently under development. Upon the introduction of these new subsystems, the integration of these into the overall V-HAB human model is discussed, highlighting the impact on the most important I/F. The overall human model capabilities shall further be summarized and presented based on meaningful test cases. In addition to the presentation of the results, the correlation strategy for the Virtual Habitat human model shall be introduced assessing the models current confidence level and giving an outlook on the future correlation strategy. Last but not least, the remaining V-HAB mod-ules shall be introduced shortly showing how the human model is integrated into the overall simulation.

Topological bifurcations in a model society of reasonable contrarians

NASA Astrophysics Data System (ADS)

Bagnoli, Franco; Rechtman, Raúl

2013-12-01

People are often divided into conformists and contrarians, the former tending to align to the majority opinion in their neighborhood and the latter tending to disagree with that majority. In practice, however, the contrarian tendency is rarely followed when there is an overwhelming majority with a given opinion, which denotes a social norm. Such reasonable contrarian behavior is often considered a mark of independent thought and can be a useful strategy in financial markets. We present the opinion dynamics of a society of reasonable contrarian agents. The model is a cellular automaton of Ising type, with antiferromagnetic pair interactions modeling contrarianism and plaquette terms modeling social norms. We introduce the entropy of the collective variable as a way of comparing deterministic (mean-field) and probabilistic (simulations) bifurcation diagrams. In the mean-field approximation the model exhibits bifurcations and a chaotic phase, interpreted as coherent oscillations of the whole society. However, in a one-dimensional spatial arrangement one observes incoherent oscillations and a constant average. In simulations on Watts-Strogatz networks with a small-world effect the mean-field behavior is recovered, with a bifurcation diagram that resembles the mean-field one but where the rewiring probability is used as the control parameter. Similar bifurcation diagrams are found for scale-free networks, and we are able to compute an effective connectivity for such networks.

Topological bifurcations in a model society of reasonable contrarians.

PubMed

Bagnoli, Franco; Rechtman, Raúl

2013-12-01

People are often divided into conformists and contrarians, the former tending to align to the majority opinion in their neighborhood and the latter tending to disagree with that majority. In practice, however, the contrarian tendency is rarely followed when there is an overwhelming majority with a given opinion, which denotes a social norm. Such reasonable contrarian behavior is often considered a mark of independent thought and can be a useful strategy in financial markets. We present the opinion dynamics of a society of reasonable contrarian agents. The model is a cellular automaton of Ising type, with antiferromagnetic pair interactions modeling contrarianism and plaquette terms modeling social norms. We introduce the entropy of the collective variable as a way of comparing deterministic (mean-field) and probabilistic (simulations) bifurcation diagrams. In the mean-field approximation the model exhibits bifurcations and a chaotic phase, interpreted as coherent oscillations of the whole society. However, in a one-dimensional spatial arrangement one observes incoherent oscillations and a constant average. In simulations on Watts-Strogatz networks with a small-world effect the mean-field behavior is recovered, with a bifurcation diagram that resembles the mean-field one but where the rewiring probability is used as the control parameter. Similar bifurcation diagrams are found for scale-free networks, and we are able to compute an effective connectivity for such networks.

Identification of Circular RNAs from the Parental Genes Involved in Multiple Aspects of Cellular Metabolism in Barley

PubMed Central

Darbani, Behrooz; Noeparvar, Shahin; Borg, Søren

2016-01-01

RNA circularization made by head-to-tail back-splicing events is involved in the regulation of gene expression from transcriptional to post-translational levels. By exploiting RNA-Seq data and down-stream analysis, we shed light on the importance of circular RNAs in plants. The results introduce circular RNAs as novel interactors in the regulation of gene expression in plants and imply the comprehensiveness of this regulatory pathway by identifying circular RNAs for a diverse set of genes. These genes are involved in several aspects of cellular metabolism as hormonal signaling, intracellular protein sorting, carbohydrate metabolism and cell-wall biogenesis, respiration, amino acid biosynthesis, transcription and translation, and protein ubiquitination. Additionally, these parental loci of circular RNAs, from both nuclear and mitochondrial genomes, encode for different transcript classes including protein coding transcripts, microRNA, rRNA, and long non-coding/microprotein coding RNAs. The results shed light on the mitochondrial exonic circular RNAs and imply the importance of circular RNAs for regulation of mitochondrial genes. Importantly, we introduce circular RNAs in barley and elucidate their cellular-level alterations across tissues and in response to micronutrients iron and zinc. In further support of circular RNAs' functional roles in plants, we report several cases where fluctuations of circRNAs do not correlate with the levels of their parental-loci encoded linear transcripts. PMID:27375638

In silico characterization of cell-cell interactions using a cellular automata model of cell culture.

PubMed

Kihara, Takanori; Kashitani, Kosuke; Miyake, Jun

2017-07-14

Cell proliferation is a key characteristic of eukaryotic cells. During cell proliferation, cells interact with each other. In this study, we developed a cellular automata model to estimate cell-cell interactions using experimentally obtained images of cultured cells. We used four types of cells; HeLa cells, human osteosarcoma (HOS) cells, rat mesenchymal stem cells (MSCs), and rat smooth muscle A7r5 cells. These cells were cultured and stained daily. The obtained cell images were binarized and clipped into squares containing about 10 4 cells. These cells showed characteristic cell proliferation patterns. The growth curves of these cells were generated from the cell proliferation images and we determined the doubling time of these cells from the growth curves. We developed a simple cellular automata system with an easily accessible graphical user interface. This system has five variable parameters, namely, initial cell number, doubling time, motility, cell-cell adhesion, and cell-cell contact inhibition (of proliferation). Within these parameters, we obtained initial cell numbers and doubling times experimentally. We set the motility at a constant value because the effect of the parameter for our simulation was restricted. Therefore, we simulated cell proliferation behavior with cell-cell adhesion and cell-cell contact inhibition as variables. By comparing growth curves and proliferation cell images, we succeeded in determining the cell-cell interaction properties of each cell. Simulated HeLa and HOS cells exhibited low cell-cell adhesion and weak cell-cell contact inhibition. Simulated MSCs exhibited high cell-cell adhesion and positive cell-cell contact inhibition. Simulated A7r5 cells exhibited low cell-cell adhesion and strong cell-cell contact inhibition. These simulated results correlated with the experimental growth curves and proliferation images. Our simulation approach is an easy method for evaluating the cell-cell interaction properties of cells.

High Severity Wildfire Effect On Rainfall Infiltration And Runoff: A Cellular Automata Based Simulation

NASA Astrophysics Data System (ADS)

Vergara-Blanco, J. E.; Leboeuf-Pasquier, J.; Benavides-Solorio, J. D. D.

2017-12-01

A simulation software that reproduces rainfall infiltration and runoff for a storm event in a particular forest area is presented. A cellular automaton is utilized to represent space and time. On the time scale, the simulation is composed by a sequence of discrete time steps. On the space scale, the simulation is composed of forest surface cells. The software takes into consideration rain intensity and length, individual forest cell soil absorption capacity evolution, and surface angle of inclination. The software is developed with the C++ programming language. The simulation is executed on a 100 ha area within La Primavera Forest in Jalisco, Mexico. Real soil texture for unburned terrain and high severity wildfire affected terrain is employed to recreate the specific infiltration profile. Historical rainfall data of a 92 minute event is used. The Horton infiltration equation is utilized for infiltration capacity calculation. A Digital Elevation Model (DEM) is employed to reproduce the surface topography. The DEM is displayed with a 3D mesh graph where individual surface cells can be observed. The plot colouring renders water content development at the cell level throughout the storm event. The simulation shows that the cumulative infiltration and runoff which take place at the surface cell level depend on the specific storm intensity, fluctuation and length, overall terrain topography, cell slope, and soil texture. Rainfall cumulative infiltration for unburned and high severity wildfire terrain are compared: unburned terrain exhibits a significantly higher amount of rainfall infiltration.It is concluded that a cellular automaton can be utilized with a C++ program to reproduce rainfall infiltration and runoff under diverse soil texture, topographic and rainfall conditions in a forest setting. This simulation is geared for an optimization program to pinpoint the locations of a series of forest land remediation efforts to support reforestation or to minimize runoff.

Texturing Silicon Nanowires for Highly Localized Optical Modulation of Cellular Dynamics.

PubMed

Fang, Yin; Jiang, Yuanwen; Acaron Ledesma, Hector; Yi, Jaeseok; Gao, Xiang; Weiss, Dara E; Shi, Fengyuan; Tian, Bozhi

2018-06-18

Engineered silicon-based materials can display photoelectric and photothermal responses under light illumination, which may lead to further innovations at the silicon-biology interfaces. Silicon nanowires have small radial dimensions, promising as highly localized cellular modulators, however the single crystalline form typically has limited photothermal efficacy due to the poor light absorption and fast heat dissipation. In this work, we report strategies to improve the photothermal response from silicon nanowires by introducing nanoscale textures on the surface and in the bulk. We next demonstrate high-resolution extracellular modulation of calcium dynamics in a number of mammalian cells including glial cells, neurons, and cancer cells. The new materials may be broadly used in probing and modulating electrical and chemical signals at the subcellular length scale, which is currently a challenge in the field of electrophysiology or cellular engineering.

An authenticated image encryption scheme based on chaotic maps and memory cellular automata

NASA Astrophysics Data System (ADS)

Bakhshandeh, Atieh; Eslami, Ziba

2013-06-01

This paper introduces a new image encryption scheme based on chaotic maps, cellular automata and permutation-diffusion architecture. In the permutation phase, a piecewise linear chaotic map is utilized to confuse the plain-image and in the diffusion phase, we employ the Logistic map as well as a reversible memory cellular automata to obtain an efficient and secure cryptosystem. The proposed method admits advantages such as highly secure diffusion mechanism, computational efficiency and ease of implementation. A novel property of the proposed scheme is its authentication ability which can detect whether the image is tampered during the transmission or not. This is particularly important in applications where image data or part of it contains highly sensitive information. Results of various analyses manifest high security of this new method and its capability for practical image encryption.

Theory of Epithelial Cell Shape Transitions Induced by Mechanoactive Chemical Gradients.

PubMed

Dasbiswas, Kinjal; Hannezo, Edouard; Gov, Nir S

2018-02-27

Cell shape is determined by a balance of intrinsic properties of the cell as well as its mechanochemical environment. Inhomogeneous shape changes underlie many morphogenetic events and involve spatial gradients in active cellular forces induced by complex chemical signaling. Here, we introduce a mechanochemical model based on the notion that cell shape changes may be induced by external diffusible biomolecules that influence cellular contractility (or equivalently, adhesions) in a concentration-dependent manner-and whose spatial profile in turn is affected by cell shape. We map out theoretically the possible interplay between chemical concentration and cellular structure. Besides providing a direct route to spatial gradients in cell shape profiles in tissues, we show that the dependence on cell shape helps create robust mechanochemical gradients. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Computationally efficient simulation of electrical activity at cell membranes interacting with self-generated and externally imposed electric fields

NASA Astrophysics Data System (ADS)

Agudelo-Toro, Andres; Neef, Andreas

2013-04-01

Objective. We present a computational method that implements a reduced set of Maxwell's equations to allow simulation of cells under realistic conditions: sub-micron cell morphology, a conductive non-homogeneous space and various ion channel properties and distributions. Approach. While a reduced set of Maxwell's equations can be used to couple membrane currents to extra- and intracellular potentials, this approach is rarely taken, most likely because adequate computational tools are missing. By using these equations, and introducing an implicit solver, numerical stability is attained even with large time steps. The time steps are limited only by the time development of the membrane potentials. Main results. This method allows simulation times of tens of minutes instead of weeks, even for complex problems. The extracellular fields are accurately represented, including secondary fields, which originate at inhomogeneities of the extracellular space and can reach several millivolts. We present a set of instructive examples that show how this method can be used to obtain reference solutions for problems, which might not be accurately captured by the traditional approaches. This includes the simulation of realistic magnitudes of extracellular action potential signals in restricted extracellular space. Significance. The electric activity of neurons creates extracellular potentials. Recent findings show that these endogenous fields act back onto the neurons, contributing to the synchronization of population activity. The influence of endogenous fields is also relevant for understanding therapeutic approaches such as transcranial direct current, transcranial magnetic and deep brain stimulation. The mutual interaction between fields and membrane currents is not captured by today's concepts of cellular electrophysiology, including the commonly used activation function, as those concepts are based on isolated membranes in an infinite, isopotential extracellular space. The presented tool makes simulations with detailed morphology and implicit interactions of currents and fields available to the electrophysiology community.

Metchnikoff's Munchies

ERIC Educational Resources Information Center

Cluett, Edward; Gould, Jessica

2006-01-01

This article describes an inquiry-based activity for high school students in which they determine the pH of the digestive compartment in "Paramecia" using different pH indicators. This lab activity introduces students to the challenges of research on the cellular level and illustrates one of the primary methods that scientists use to measure the…

Teaching Cell Anatomy with a Fabric Model

ERIC Educational Resources Information Center

Kluka, Michelle

2005-01-01

Middle schoolers are often first introduced to detailed cellular anatomy through one-dimensional drawings in basic life science books, fill-in-the blank handouts accompanied by notes from the teacher, or desktop hard-plastic commercial models that resemble giant lollipops. One of the most important, yet difficult, life science concepts for…

Sequences for Student Investigation

ERIC Educational Resources Information Center

Barton, Jeffrey; Feil, David; Lartigue, David; Mullins, Bernadette

2004-01-01

We describe two classes of sequences that give rise to accessible problems for undergraduate research. These problems may be understood with virtually no prerequisites and are well suited for computer-aided investigation. The first sequence is a variation of one introduced by Stephen Wolfram in connection with his study of cellular automata. The…

Simulating Space Radiation-Induced Breast Tumor Incidence Using Automata.

PubMed

Heuskin, A C; Osseiran, A I; Tang, J; Costes, S V

2016-07-01

Estimating cancer risk from space radiation has been an ongoing challenge for decades primarily because most of the reported epidemiological data on radiation-induced risks are derived from studies of atomic bomb survivors who were exposed to an acute dose of gamma rays instead of chronic high-LET cosmic radiation. In this study, we introduce a formalism using cellular automata to model the long-term effects of ionizing radiation in human breast for different radiation qualities. We first validated and tuned parameters for an automata-based two-stage clonal expansion model simulating the age dependence of spontaneous breast cancer incidence in an unexposed U.S. We then tested the impact of radiation perturbation in the model by modifying parameters to reflect both targeted and nontargeted radiation effects. Targeted effects (TE) reflect the immediate impact of radiation on a cell's DNA with classic end points being gene mutations and cell death. They are well known and are directly derived from experimental data. In contrast, nontargeted effects (NTE) are persistent and affect both damaged and undamaged cells, are nonlinear with dose and are not well characterized in the literature. In this study, we introduced TE in our model and compared predictions against epidemiologic data of the atomic bomb survivor cohort. TE alone are not sufficient for inducing enough cancer. NTE independent of dose and lasting ∼100 days postirradiation need to be added to accurately predict dose dependence of breast cancer induced by gamma rays. Finally, by integrating experimental relative biological effectiveness (RBE) for TE and keeping NTE (i.e., radiation-induced genomic instability) constant with dose and LET, the model predicts that RBE for breast cancer induced by cosmic radiation would be maximum at 220 keV/μm. This approach lays the groundwork for further investigation into the impact of chronic low-dose exposure, inter-individual variation and more complex space radiation scenarios.

Allosteric dynamics of SAMHD1 studied by molecular dynamics simulations

NASA Astrophysics Data System (ADS)

Patra, K. K.; Bhattacharya, A.; Bhattacharya, S.

2016-10-01

SAMHD1 is a human cellular enzyme that blocks HIV-1 infection in myeloid cells and non-cycling CD4+T cells. The enzyme is an allosterically regulated triphosphohydrolase that modulates the level of cellular dNTP. The virus restriction is attributed to the lowering of the pool of dNTP in the cell to a point where reverse-transcription is impaired. Mutations in SAMHD1 are also implicated in Aicardi-Goutieres syndrome. A mechanistic understanding of the allosteric activation of the enzyme is still elusive. We have performed molecular dynamics simulations to examine the allosteric site dynamics of the protein and to examine the connection between the stability of the tetrameric complex and the Allosite occupancy.

A cellular automata model of SARS epidemic spreading

NASA Astrophysics Data System (ADS)

Xu, Tian; Zhang, Peipei; Su, Beibei; Jiang, Yumai; He, Da-Ren

2004-03-01

We suggest a cellular automata model for a simulation on the process of SARS spreading in Beijing. Suppose a number of people are located in a two-dimensional lattice, in which a certain portion belongs to immune and others belong to acceptive. In every time step each of the acceptive people may become ill with a certain probability if one of his 8 neighbors is a SARS patient. At same time all the people have another possibility to change their positions. Each patient will recover or die after different number of days. A recovered patient becomes immune. The numerical simulation by this model leads to the results, which are in a good agreement with the practical statistical data.

Opinion evolution based on cellular automata rules in small world networks

NASA Astrophysics Data System (ADS)

Shi, Xiao-Ming; Shi, Lun; Zhang, Jie-Fang

2010-03-01

In this paper, we apply cellular automata rules, which can be given by a truth table, to human memory. We design each memory as a tracking survey mode that keeps the most recent three opinions. Each cellular automata rule, as a personal mechanism, gives the final ruling in one time period based on the data stored in one's memory. The key focus of the paper is to research the evolution of people's attitudes to the same question. Based on a great deal of empirical observations from computer simulations, all the rules can be classified into 20 groups. We highlight the fact that the phenomenon shown by some rules belonging to the same group will be altered within several steps by other rules in different groups. It is truly amazing that, compared with the last hundreds of presidential voting in America, the eras of important events in America's history coincide with the simulation results obtained by our model.

Impact Test and Simulation of Energy Absorbing Concepts for Earth Entry Vehicles

NASA Technical Reports Server (NTRS)

Billings, Marcus D.; Fasanella, Edwin L.; Kellas, Sotiris

2001-01-01

Nonlinear dynamic finite element simulations have been performed to aid in the design of an energy absorbing concept for a highly reliable passive Earth Entry Vehicle (EEV) that will directly impact the Earth without a parachute. EEV's are designed to return materials from asteroids, comets, or planets for laboratory analysis on Earth. The EEV concept uses an energy absorbing cellular structure designed to contain and limit the acceleration of space exploration samples during Earth impact. The spherical shaped cellular structure is composed of solid hexagonal and pentagonal foam-filled cells with hybrid graphite- epoxy/Kevlar cell walls. Space samples fit inside a smaller sphere at the center of the EEV's cellular structure. Comparisons of analytical predictions using MSC,Dytran with test results obtained from impact tests performed at NASA Langley Research Center were made for three impact velocities ranging from 32 to 40 m/s. Acceleration and deformation results compared well with the test results. These finite element models will be useful for parametric studies of off-nominal impact conditions.

FlashPhotol: Using a Flash Photolysis Apparatus Simulator to Introduce Students to the Kinetics of Transient Species and Fast Reactions

ERIC Educational Resources Information Center

Bigger, Stephen W.

2016-01-01

FlashPhotol is an educational software package that introduces students to the kinetics of transient species and fast reactions. This is achieved by means of a computer-simulated flash photolysis apparatus that comprises all major functional elements and that students can use to perform various experiments. The experimental interface presents a…

Numerical simulation of deformation and fracture of space protective shell structures from concrete and fiber concrete under pulse loading

NASA Astrophysics Data System (ADS)

Radchenko, P. A.; Batuev, S. P.; Radchenko, A. V.; Plevkov, V. S.

2015-11-01

This paper presents results of numerical simulation of interaction between aircraft Boeing 747-400 and protective shell of nuclear power plant. The shell is presented as complex multilayered cellular structure comprising layers of concrete and fiber concrete bonded with steel trusses. Numerical simulation was held three-dimensionally using the author's algorithm and software taking into account algorithms for building grids of complex geometric objects and parallel computations. The dynamics of stress-strain state and fracture of structure were studied. Destruction is described using two-stage model that allows taking into account anisotropy of elastic and strength properties of concrete and fiber concrete. It is shown that wave processes initiate destruction of shell cellular structure—cells start to destruct in unloading wave, originating after output of compression wave to the free surfaces of cells.

A Divide-and-Conquer/Cellular-Decomposition Framework for Million-to-Billion Atom Simulations of Chemical Reactions

DTIC Science & Technology

2007-01-01

as a function of the particle velocity that drives the shock [7]. The MD and experimen- tal data agree very well. Furthermore, the simulation shows...topological anomalies in multimillion - node chemical bond networks in materials [48]. At the Col- laboratory for Advanced Computing and Simulations ...to-billion atom simulations of chemical reactions Aiichiro Nakano a,*, Rajiv K. Kalia a, Ken-ichi Nomura a, Ashish Sharma a, Priya Vashishta a, Fuyuki

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

PubMed

Sulis, William H

2016-04-01

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

v-Liver: Simulating Hepatic Tissue Lesions as Virtual Cellular Systems

EPA Science Inventory

The US EPA Virtual Liver (v-Liver) project is aimed at reducing the uncertainty in estimating the risk of toxic outcomes in humans by simulating the dose-dependent effects of environmental chemicals in silico. The v-Liver embodies an emerging field of research in computational ti...

Energy dissipation dataset for reversible logic gates in quantum dot-cellular automata.

PubMed

Bahar, Ali Newaz; Rahman, Mohammad Maksudur; Nahid, Nur Mohammad; Hassan, Md Kamrul

2017-02-01

This paper presents an energy dissipation dataset of different reversible logic gates in quantum-dot cellular automata. The proposed circuits have been designed and verified using QCADesigner simulator. Besides, the energy dissipation has been calculated under three different tunneling energy level at temperature T =2 K. For estimating the energy dissipation of proposed gates; QCAPro tool has been employed.

WE-EF-BRA-02: A Monte Carlo Study of Macroscopic and Microscopic Dose Descriptors for Kilovoltage Cellular Dosimetry

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

Oliver, P; Thomson, R

2015-06-15

Purpose: To investigate how doses to cellular (microscopic) targets depend on cell morphology, and how cellular doses relate to doses to bulk tissues and water for 20 to 370 keV photon sources using Monte Carlo (MC) simulations. Methods: Simulation geometries involve cell clusters, single cells, and single nuclear cavities embedded in various healthy and cancerous bulk tissue phantoms. A variety of nucleus and cytoplasm elemental compositions are investigated. Cell and nucleus radii range from 5 to 10 microns and 2 to 9 microns, respectively. Doses to water and bulk tissue cavities are compared to nucleus and cytoplasm doses. Results: Variationsmore » in cell dose with simulation geometry are most pronounced for lower energy sources. Nuclear doses are sensitive to the surrounding geometry: the nuclear dose in a multicell model differs from the dose to a cavity of nuclear medium in an otherwise homogeneous bulk tissue phantom by more than 7% at 20 keV. Nuclear doses vary with cell size by up to 20% at 20 keV, with 10% differences persisting up to 90 keV. Bulk tissue and water cavity doses differ from cellular doses by up to 16%. MC results are compared to cavity theory predictions; large and small cavity theories qualitatively predict nuclear doses for energies below and above 50 keV, respectively. Burlin’s (1969) intermediate cavity theory best predicts MC results with an average discrepancy of 4%. Conclusion: Cellular doses vary as a function of source energy, subcellular compartment size, elemental composition, and tissue morphology. Neither water nor bulk tissue is an appropriate surrogate for subcellular targets in radiation dosimetry. The influence of microscopic inhomogeneities in the surrounding environment on the nuclear dose and the importance of the nucleus as a target for radiation-induced cell death emphasizes the potential importance of cellular dosimetry for understanding radiation effects. Funded by the Natural Sciences and Engineering Research Council of Canada (NSERC), the Canada Research Chairs Program (CRC), and the Ontario Ministry of Training, Colleges and Universities.« less

Oscillatory cellular patterns in three-dimensional directional solidification

NASA Astrophysics Data System (ADS)

Tourret, D.; Debierre, J.-M.; Song, Y.; Mota, F. L.; Bergeon, N.; Guérin, R.; Trivedi, R.; Billia, B.; Karma, A.

2015-10-01

We present a phase-field study of oscillatory breathing modes observed during the solidification of three-dimensional cellular arrays in microgravity. Directional solidification experiments conducted onboard the International Space Station have allowed us to observe spatially extended homogeneous arrays of cells and dendrites while minimizing the amount of gravity-induced convection in the liquid. In situ observations of transparent alloys have revealed the existence, over a narrow range of control parameters, of oscillations in cellular arrays with a period ranging from about 25 to 125 min. Cellular patterns are spatially disordered, and the oscillations of individual cells are spatiotemporally uncorrelated at long distance. However, in regions displaying short-range spatial ordering, groups of cells can synchronize into oscillatory breathing modes. Quantitative phase-field simulations show that the oscillatory behavior of cells in this regime is linked to a stability limit of the spacing in hexagonal cellular array structures. For relatively high cellular front undercooling (i.e., low growth velocity or high thermal gradient), a gap appears in the otherwise continuous range of stable array spacings. Close to this gap, a sustained oscillatory regime appears with a period that compares quantitatively well with experiment. For control parameters where this gap exists, oscillations typically occur for spacings at the edge of the gap. However, after a change of growth conditions, oscillations can also occur for nearby values of control parameters where this gap just closes and a continuous range of spacings exists. In addition, sustained oscillations at to the opening of this stable gap exhibit a slow periodic modulation of the phase-shift among cells with a slower period of several hours. While long-range coherence of breathing modes can be achieved in simulations for a perfect spatial arrangement of cells as initial condition, global disorder is observed in both three-dimensional experiments and simulations from realistic noisy initial conditions. In the latter case, erratic tip-splitting events promoted by large-amplitude oscillations contribute to maintaining the long-range array disorder, unlike in thin-sample experiments where long-range coherence of oscillations is experimentally observable.

Simulation Based Optimization of Complex Monolithic Composite Structures Using Cellular Core Technology

NASA Astrophysics Data System (ADS)

Hickmott, Curtis W.

Cellular core tooling is a new technology which has the capability to manufacture complex integrated monolithic composite structures. This novel tooling method utilizes thermoplastic cellular cores as inner tooling. The semi-rigid nature of the cellular cores makes them convenient for lay-up, and under autoclave temperature and pressure they soften and expand providing uniform compaction on all surfaces including internal features such as ribs and spar tubes. This process has the capability of developing fully optimized aerospace structures by reducing or eliminating assembly using fasteners or bonded joints. The technology is studied in the context of evaluating its capabilities, advantages, and limitations in developing high quality structures. The complex nature of these parts has led to development of a model using the Finite Element Analysis (FEA) software Abaqus and the plug-in COMPRO Common Component Architecture (CCA) provided by Convergent Manufacturing Technologies. This model utilizes a "virtual autoclave" technique to simulate temperature profiles, resin flow paths, and ultimately deformation from residual stress. A model has been developed simulating the temperature profile during curing of composite parts made with the cellular core technology. While modeling of composites has been performed in the past, this project will look to take this existing knowledge and apply it to this new manufacturing method capable of building more complex parts and develop a model designed specifically for building large, complex components with a high degree of accuracy. The model development has been carried out in conjunction with experimental validation. A double box beam structure was chosen for analysis to determine the effects of the technology on internal ribs and joints. Double box beams were manufactured and sectioned into T-joints for characterization. Mechanical behavior of T-joints was performed using the T-joint pull-off test and compared to traditional tooling methods. Components made with the cellular core tooling method showed an improved strength at the joints. It is expected that this knowledge will help optimize the processing of complex, integrated structures and benefit applications in aerospace where lighter, structurally efficient components would be advantageous.

Oscillatory cellular patterns in three-dimensional directional solidification

DOE PAGES

Tourret, D.; Debierre, J. -M.; Song, Y.; ...

2015-09-11

We present a phase-field study of oscillatory breathing modes observed during the solidification of three-dimensional cellular arrays in micro-gravity. Directional solidification experiments conducted onboard the International Space Station have allowed for the first time to observe spatially extended homogeneous arrays of cells and dendrites while minimizing the amount of gravity-induced convection in the liquid. In situ observations of transparent alloys have revealed the existence, over a narrow range of control parameters, of oscillations in cellular arrays with a period ranging from about 25 to 125 minutes. Cellular patterns are spatially disordered, and the oscillations of individual cells are spatiotemporally uncorrelatedmore » at long distance. However, in regions displaying short-range spatial ordering, groups of cells can synchronize into oscillatory breathing modes. Quantitative phase-field simulations show that the oscillatory behavior of cells in this regime is linked to a stability limit of the spacing in hexagonal cellular array structures. For relatively high cellular front undercooling (\\ie low growth velocity or high thermal gradient), a gap appears in the otherwise continuous range of stable array spacings. Close to this gap, a sustained oscillatory regime appears with a period that compares quantitatively well with experiment. For control parameters where this gap exist, oscillations typically occur for spacings at the edge of the gap. However, after a change of growth conditions, oscillations can also occur for nearby values of control parameters where this gap just closes and a continuous range of spacings exists. In addition, sustained oscillations at to the opening of this stable gap exhibit a slow periodic modulation of the phase-shift among cells with a slower period of several hours. While long-range coherence of breathing modes can be achieved in simulations for a perfect spatial arrangement of cells as initial condition, global disorder is observed in both three-dimensional experiments and simulations from realistic noisy initial conditions. The, erratic tip splitting events promoted by large amplitude oscillations contribute to maintaining the long-range array disorder, unlike in thin sample experiments where long-range coherence of oscillations is experimentally observable.« less

Oscillatory cellular patterns in three-dimensional directional solidification

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

Tourret, D.; Debierre, J. -M.; Song, Y.

We present a phase-field study of oscillatory breathing modes observed during the solidification of three-dimensional cellular arrays in micro-gravity. Directional solidification experiments conducted onboard the International Space Station have allowed for the first time to observe spatially extended homogeneous arrays of cells and dendrites while minimizing the amount of gravity-induced convection in the liquid. In situ observations of transparent alloys have revealed the existence, over a narrow range of control parameters, of oscillations in cellular arrays with a period ranging from about 25 to 125 minutes. Cellular patterns are spatially disordered, and the oscillations of individual cells are spatiotemporally uncorrelatedmore » at long distance. However, in regions displaying short-range spatial ordering, groups of cells can synchronize into oscillatory breathing modes. Quantitative phase-field simulations show that the oscillatory behavior of cells in this regime is linked to a stability limit of the spacing in hexagonal cellular array structures. For relatively high cellular front undercooling (\\ie low growth velocity or high thermal gradient), a gap appears in the otherwise continuous range of stable array spacings. Close to this gap, a sustained oscillatory regime appears with a period that compares quantitatively well with experiment. For control parameters where this gap exist, oscillations typically occur for spacings at the edge of the gap. However, after a change of growth conditions, oscillations can also occur for nearby values of control parameters where this gap just closes and a continuous range of spacings exists. In addition, sustained oscillations at to the opening of this stable gap exhibit a slow periodic modulation of the phase-shift among cells with a slower period of several hours. While long-range coherence of breathing modes can be achieved in simulations for a perfect spatial arrangement of cells as initial condition, global disorder is observed in both three-dimensional experiments and simulations from realistic noisy initial conditions. The, erratic tip splitting events promoted by large amplitude oscillations contribute to maintaining the long-range array disorder, unlike in thin sample experiments where long-range coherence of oscillations is experimentally observable.« less

Appropriate Arrangement of Nori Aquafarming Grounds in the Ariake Sea on the Basis of Convective Dispersion Simulation Model

NASA Astrophysics Data System (ADS)

Tabata, Toshinori; Hiramatsu, Kazuaki; Harada, Masayoshi; Shiraishi, Hideto; Shuto, Toshio

This study investigated appropriate arrangement of nori aquafarming grounds from the view point of nori growth in the Ariake Sea coastal waters. Databases of the sea-bed topography and nori aquafarming grounds were constructed using GIS. Then the tidal currents and salinity in the Ariake Sea were simulated using a two-dimensional depth-integrated model, which was developed by integrating the three-dimensional continuity, momentum, and diffusion equations. The wetting and drying scheme was also introduced to account for the appearance and disappearance of tidal flats. The velocities and directions of the simulated tidal currents, salinity, and tidal land appearance were in good agreement with observed data. Five scenarios considered by the Fukuoka Prefectural Government were introduced in the simulation model to identify the most appropriate arrangement. An experimental formula for nitrogen assimilation kinetics in the nori body was introduced to evaluate the simulation results for the five scenarios. The scenarios with a reduced density of aquafarming grounds had increased nori growth, suggesting that the arrangement of the aquafarming grounds affected the nori growth. The simulation results were used to identify the most appropriate arrangement of aquafarming grounds.

Reserch on Urban Spatial Expansion Model Based on Multi-Object Gray Decision-Making and Ca: a Case Study of Pidu District, Chengdu City

NASA Astrophysics Data System (ADS)

Liu, Z.; Li, Y.

2018-04-01

This paper from the perspective of the Neighbor cellular space, Proposed a new urban space expansion model based on a new multi-objective gray decision and CA. The model solved the traditional cellular automata conversion rules is difficult to meet the needs of the inner space-time analysis of urban changes and to overcome the problem of uncertainty in the combination of urban drivers and urban cellular automata. At the same time, the study takes Pidu District as a research area and carries out urban spatial simulation prediction and analysis, and draws the following conclusions: (1) The design idea of the urban spatial expansion model proposed in this paper is that the urban driving factor and the neighborhood function are tightly coupled by the multi-objective grey decision method based on geographical conditions. The simulation results show that the simulation error of urban spatial expansion is less than 5.27 %. The Kappa coefficient is 0.84. It shows that the model can better capture the inner transformation mechanism of the city. (2) We made a simulation prediction for Pidu District of Chengdu by discussing Pidu District of Chengdu as a system instance.In this way, we analyzed the urban growth tendency of this area.presenting a contiguous increasing mode, which is called "urban intensive development". This expansion mode accorded with sustainable development theory and the ecological urbanization design theory.

Genome Scale Modeling in Systems Biology: Algorithms and Resources

PubMed Central

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

2014-01-01

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

Melt-processed polymeric cellular dosage forms for immediate drug release.

PubMed

Blaesi, Aron H; Saka, Nannaji

2015-12-28

The present immediate-release solid dosage forms, such as the oral tablets and capsules, comprise granular matrices. While effective in releasing the drug rapidly, they are fraught with difficulties inherent in processing particulate matter. By contrast, liquid-based processes would be far more predictable; but the standard cast microstructures are unsuited for immediate-release because they resist fluid percolation and penetration. In this article, we introduce cellular dosage forms that can be readily prepared from polymeric melts by incorporating the nucleation, growth, and coalescence of microscopic gas bubbles in a molding process. We show that the cell topology and formulation of such cellular structures can be engineered to reduce the length-scale of the mass-transfer step, which determines the time of drug release, from as large as the dosage form itself to as small as the thickness of the cell wall. This allows the cellular dosage forms to achieve drug release rates over an order of magnitude faster compared with those of cast matrices, spanning the entire spectrum of immediate-release and beyond. The melt-processed polymeric cellular dosage forms enable predictive design of immediate-release solid dosage forms by tailoring microstructures, and could be manufactured efficiently in a single step.

Systems biology of cellular membranes: a convergence with biophysics.

PubMed

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

2017-09-01

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

In silico biology of bone modelling and remodelling: adaptation.

PubMed

Gerhard, Friederike A; Webster, Duncan J; van Lenthe, G Harry; Müller, Ralph

2009-05-28

Modelling and remodelling are the processes by which bone adapts its shape and internal structure to external influences. However, the cellular mechanisms triggering osteoclastic resorption and osteoblastic formation are still unknown. In order to investigate current biological theories, in silico models can be applied. In the past, most of these models were based on the continuum assumption, but some questions related to bone adaptation can be addressed better by models incorporating the trabecular microstructure. In this paper, existing simulation models are reviewed and one of the microstructural models is extended to test the hypothesis that bone adaptation can be simulated without particular knowledge of the local strain distribution in the bone. Validation using an experimental murine loading model showed that this is possible. Furthermore, the experimental model revealed that bone formation cannot be attributed only to an increase in trabecular thickness but also to structural reorganization including the growth of new trabeculae. How these new trabeculae arise is still an unresolved issue and might be better addressed by incorporating other levels of hierarchy, especially the cellular level. The cellular level sheds light on the activity and interplay between the different cell types, leading to the effective change in the whole bone. For this reason, hierarchical multi-scale simulations might help in the future to better understand the biomathematical laws behind bone adaptation.

Numerical and experimental validation for the thermal transmittance of windows with cellular shades

DOE PAGES

Hart, Robert

2018-02-21

Some highly energy efficient window attachment products are available today, but more rapid market adoption would be facilitated by fair performance metrics. It is important to have validated simulation tools to provide a basis for this analysis. This paper outlines a review and validation of the ISO 15099 center-of-glass zero-solar-load heat transfer correlations for windows with cellular shades. Thermal transmittance was measured experimentally, simulated using computational fluid dynamics (CFD) analysis, and simulated utilizing correlations from ISO 15099 as implemented in Berkeley Lab WINDOW and THERM software. CFD analysis showed ISO 15099 underestimates heat flux of rectangular cavities by up tomore » 60% when aspect ratio (AR) = 1 and overestimates heat flux up to 20% when AR = 0.5. CFD analysis also showed that wave-type surfaces of cellular shades have less than 2% impact on heat flux through the cavities and less than 5% for natural convection of room-side surface. WINDOW was shown to accurately represent heat flux of the measured configurations to a mean relative error of 0.5% and standard deviation of 3.8%. Finally, several shade parameters showed significant influence on correlation accuracy, including distance between shade and glass, inconsistency in cell stretch, size of perimeter gaps, and the mounting hardware.« less

Numerical and experimental validation for the thermal transmittance of windows with cellular shades

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

Hart, Robert

Some highly energy efficient window attachment products are available today, but more rapid market adoption would be facilitated by fair performance metrics. It is important to have validated simulation tools to provide a basis for this analysis. This paper outlines a review and validation of the ISO 15099 center-of-glass zero-solar-load heat transfer correlations for windows with cellular shades. Thermal transmittance was measured experimentally, simulated using computational fluid dynamics (CFD) analysis, and simulated utilizing correlations from ISO 15099 as implemented in Berkeley Lab WINDOW and THERM software. CFD analysis showed ISO 15099 underestimates heat flux of rectangular cavities by up tomore » 60% when aspect ratio (AR) = 1 and overestimates heat flux up to 20% when AR = 0.5. CFD analysis also showed that wave-type surfaces of cellular shades have less than 2% impact on heat flux through the cavities and less than 5% for natural convection of room-side surface. WINDOW was shown to accurately represent heat flux of the measured configurations to a mean relative error of 0.5% and standard deviation of 3.8%. Finally, several shade parameters showed significant influence on correlation accuracy, including distance between shade and glass, inconsistency in cell stretch, size of perimeter gaps, and the mounting hardware.« less

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

NASA Astrophysics Data System (ADS)

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

2014-07-01

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

MATLAB Simulation of Gradient-Based Neural Network for Online Matrix Inversion

NASA Astrophysics Data System (ADS)

Zhang, Yunong; Chen, Ke; Ma, Weimu; Li, Xiao-Dong

This paper investigates the simulation of a gradient-based recurrent neural network for online solution of the matrix-inverse problem. Several important techniques are employed as follows to simulate such a neural system. 1) Kronecker product of matrices is introduced to transform a matrix-differential-equation (MDE) to a vector-differential-equation (VDE); i.e., finally, a standard ordinary-differential-equation (ODE) is obtained. 2) MATLAB routine "ode45" is introduced to solve the transformed initial-value ODE problem. 3) In addition to various implementation errors, different kinds of activation functions are simulated to show the characteristics of such a neural network. Simulation results substantiate the theoretical analysis and efficacy of the gradient-based neural network for online constant matrix inversion.

Asymmetric cellular memory in bacteria exposed to antibiotics.

PubMed

Mathis, Roland; Ackermann, Martin

2017-03-09

The ability to form a cellular memory and use it for cellular decision-making could help bacteria to cope with recurrent stress conditions. We analyzed whether bacteria would form a cellular memory specifically if past events are predictive of future conditions. We worked with the asymmetrically dividing bacterium Caulobacter crescentus where past events are expected to only be informative for one of the two cells emerging from division, the sessile cell that remains in the same microenvironment and does not migrate. Time-resolved analysis of individual cells revealed that past exposure to low levels of antibiotics increases tolerance to future exposure for the sessile but not for the motile cell. Using computer simulations, we found that such an asymmetry in cellular memory could be an evolutionary response to situations where the two cells emerging from division will experience different future conditions. Our results raise the question whether bacteria can evolve the ability to form and use cellular memory conditionally in situations where it is beneficial.

Magnetic field effects on the energy deposition spectra of MV photon radiation.

PubMed

Kirkby, C; Stanescu, T; Fallone, B G

2009-01-21

Several groups worldwide have proposed various concepts for improving megavoltage (MV) radiotherapy that involve irradiating patients in the presence of a magnetic field-either for image guidance in the case of hybrid radiotherapy-MRI machines or for purposes of introducing tighter control over dose distributions. The presence of a magnetic field alters the trajectory of charged particles between interactions with the medium and thus has the potential to alter energy deposition patterns within a sub-cellular target volume. In this work, we use the MC radiation transport code PENELOPE with appropriate algorithms invoked to incorporate magnetic field deflections to investigate electron energy fluence in the presence of a uniform magnetic field and the energy deposition spectra within a 10 microm water sphere as a function of magnetic field strength. The simulations suggest only very minor changes to the electron fluence even for extremely strong magnetic fields. Further, calculations of the dose-averaged lineal energy indicate that a magnetic field strength of at least 70 T is required before beam quality will change by more than 2%.

Universality in the Self Organized Critical behavior of a cellular model of superconducting vortex dynamics

NASA Astrophysics Data System (ADS)

Sun, Yudong; Vadakkan, Tegy; Bassler, Kevin

2007-03-01

We study the universality and robustness of variants of the simple model of superconducting vortex dynamics first introduced by Bassler and Paczuski in Phys. Rev. Lett. 81, 3761 (1998). The model is a coarse-grained model that captures the essential features of the plastic vortex motion. It accounts for the repulsive interaction between vortices, the pining of vortices at quenched disordered locations in the material, and the over-damped dynamics of the vortices that leads to tearing of the flux line lattice. We report the results of extensive simulations of the critical ``Bean state" dynamics of the model. We find a phase diagram containing four distinct phases of dynamical behavior, including two phases with distinct Self Organized Critical (SOC) behavior. Exponents describing the avalanche scaling behavior in the two SOC phases are determined using finite-size scaling. The exponents are found to be robust within each phase and for different variants of the model. The difference of the scaling behavior in the two phases is also observed in the morphology of the avalanches.

Probabilistic representation of gene regulatory networks.

PubMed

Mao, Linyong; Resat, Haluk

2004-09-22

Recent experiments have established unambiguously that biological systems can have significant cell-to-cell variations in gene expression levels even in isogenic populations. Computational approaches to studying gene expression in cellular systems should capture such biological variations for a more realistic representation. In this paper, we present a new fully probabilistic approach to the modeling of gene regulatory networks that allows for fluctuations in the gene expression levels. The new algorithm uses a very simple representation for the genes, and accounts for the repression or induction of the genes and for the biological variations among isogenic populations simultaneously. Because of its simplicity, introduced algorithm is a very promising approach to model large-scale gene regulatory networks. We have tested the new algorithm on the synthetic gene network library bioengineered recently. The good agreement between the computed and the experimental results for this library of networks, and additional tests, demonstrate that the new algorithm is robust and very successful in explaining the experimental data. The simulation software is available upon request. Supplementary material will be made available on the OUP server.

Critical edge between frozen extinction and chaotic life

NASA Astrophysics Data System (ADS)

Monetti, Roberto A.; Albano, Ezequiel V.

1995-12-01

The cellular automata ``game of life'' (GL) proposed by J. Conway simulates the dynamic evolution of a society of living organisms. It has been extensively studied in order to understand the emergence of complexity and diversity from a set of local rules. More recently, the capability of GL to self-oranize into a critical state has opened an interesting debate. In this work we adopt a different approach: by introducing stochastic rules in the GL it is found that ``life'' exhibits a very rich critical behavior. Discontinuous (first-order) irreversible phase transitions (IPT's) between an extinct phase and a steady state supporting life are found. A precise location of the critical edge is achieved by means of an epidemic analysis, which also allows us to determine dynamic critical exponents. Furthermore, by means of a damage spreading study we conclude that the living phase is chaotic. The edge of the frozen-chaotic transition coincides with that of the IPT's life extinction. Close to the edge, fractal spreading of the damage is observed; however, deep inside the living phase such spreading becomes homogeneous. (c) 1995 The American Physical Society

Virtual reality training for endoscopic surgery: voluntary or obligatory?

PubMed

van Dongen, K W; van der Wal, W A; Rinkes, I H M Borel; Schijven, M P; Broeders, I A M J

2008-03-01

Virtual reality (VR) simulators have been developed to train basic endoscopic surgical skills outside of the operating room. An important issue is how to create optimal conditions for integration of these types of simulators into the surgical training curriculum. The willingness of surgical residents to train these skills on a voluntary basis was surveyed. Twenty-one surgical residents were given unrestricted access to a VR simulator for a period of four months. After this period, a competitive element was introduced to enhance individual training time spent on the simulator. The overall end-scores for individual residents were announced periodically to the full surgical department, and the winner was awarded a prize. In the first four months of study, only two of the 21 residents (10%) trained on the simulator, for a total time span of 163 minutes. After introducing the competitive element the number of trainees increased to seven residents (33%). The amount of training time spent on the simulator increased to 738 minutes. Free unlimited access to a VR simulator for training basic endoscopic skills, without any form of obligation or assessment, did not motivate surgical residents to use the simulator. Introducing a competitive element for enhancing training time had only a marginal effect. The acquisition of expensive devices to train basic psychomotor skills for endoscopic surgery is probably only effective when it is an integrated and mandatory part of the surgical curriculum.

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

PubMed Central

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

2011-01-01

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

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

PubMed Central

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

2010-01-01

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

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

PubMed

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.

Some theoretical issues on computer simulations

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

Barrett, C.L.; Reidys, C.M.

1998-02-01

The subject of this paper is the development of mathematical foundations for a theory of simulation. Sequentially updated cellular automata (sCA) over arbitrary graphs are employed as a paradigmatic framework. In the development of the theory, the authors focus on the properties of causal dependencies among local mappings in a simulation. The main object of and study is the mapping between a graph representing the dependencies among entities of a simulation and a representing the equivalence classes of systems obtained by all possible updates.

Simulated microgravity induces an inflammatory response in the common carotid artery of rats.

PubMed

Liu, Huan; Wang, Zhong-Chao; Yue, Yuan; Yu, Jin-Wen; Cai, Yue; Bai, Yun-Gang; Zhang, Hai-Jun; Bao, Jun-Xiang; Ren, Xin-Ling; Xie, Man-Jiang; Ma, Jin

2014-08-01

Post-spaceflight orthostatic intolerance is one of the most important adverse effects after exposure to space microgravity, and there are still no effective countermeasures. It has been considered that arterial remodeling may play an important role in the occurrence of post-spaceflight orthostatic intolerance, but the cellular mechanisms remain unknown. In this study, we investigated whether an inflammatory response exists in the common carotid artery of rats exposed to simulated microgravity. For this, Sprague-Dawley rats were subjected to 4 weeks of hindlimb unweighting to simulate microgravity. The expression levels of the adhesion molecules E-selectin and vascular cell adhesion molecule-1 (VCAM-1), and the cytokine monocyte chemoattractant protein-1 (MCP-1) in the common carotid artery of simulated microgravity rats were evaluated by immunohistochemical staining, quantitative RT-PCR, and Western blot analyses. The recruitment of monocytes in the common carotid artery of rats exposed to simulated microgravity was investigated by en face immunofluorescence staining and monocyte binding assays. Our results provided convincing evidence that there is an inflammatory response in the common carotid artery of rats exposed to simulated microgravity. Our work suggests that the inflammatory response may be a novel cellular mechanism that is responsible for the arterial remodeling that occurs during exposure to microgravity.

Effect of Dendritic Polymer Architecture on Biological Behaviors of Self-Assembled Nanocarriers

NASA Astrophysics Data System (ADS)

Hsu, Hao-Jui

Polymeric self-assembled nanocarriers represent one of the most versatile platforms for drug delivery. Through tailoring the physiochemical properties of amphiphilic block copolymers, self-assembled nanocarriers with great thermodynamic stability and desired biological properties could be achieved. The PEGylated dendron-based copolymers (PDCs) are one of the novel amphiphilic copolymers that have attracted a great deal of scientific interest due to their unique dendritic structure and properties. While the dendritic polymer architecture of PDC has been shown to enhance the thermodynamic stability of the self-assembling PDCs, dendron micelles, the effect of this polymer architecture on the biological properties of dendron micelles has not yet been studied. Therefore, this dissertation research is focused on understanding the role of dendritic polymer structure on moderating the biological properties of various self-assembled nanocarriers. To systematically investigate this, three studies have been designed and performed. First, we studied whether the dendritic structure of PDC allows dendron micelles to behave non-specific cellular interactions in a similar way that dendrimers would do. Second, cell-specific interactions of dendron micelles mediated by conjugated ligands were investigated. Third, we investigated the influence of dendritic PEG outer shell on micelle-serum protein interactions and its subsequent implication. Our results revealed that both non-specific and specific cellular interactions of dendron micelles were controllable through modulation of the PEG corona length. While the non-specific charge-dependent cellular interactions of dendron micelles were tunable through controlling the length of PEG corona, the use of long PEG tether was found to enhance the ligand-mediated cellular interactions of dendron micelles. With the ligand tethers, a 27-fold enhancement in ligand-mediated cellular interactions can be achieved, compared to non-targeted dendron micelles. Furthermore, we demonstrate that the dense PEG outer shell introduced by its dendritic structure reduced non-specific micelle-serum protein interactions and suppressed the subsequent micelle disintegration or premature drug release, which was not the case for linear block copolymer (LBC)-based micelles. Molecular dynamic (MD) simulation results also supported that dendron micelles exhibited a weaker interaction with serum albumin compared to LBC-based micelles. In the presence of serum proteins, the half-life of dendron micelles was 2-fold longer than that of LBC-based micelles, which could be attributed to their low serum protein interactions. In conclusion, our results provide fundamental understanding on the role of PEG corona and the effect of polymeric architecture on biological properties of polymer micelles, all indicating that dendron micelles have great potential as a novel drug delivery platform.

Engineering of Surface Functionality onto Polystyrene Microcarriers for the Attachment and Growth of Human Endothelial Cells

NASA Astrophysics Data System (ADS)

Xiong, Gordon M.; Foord, John S.; Griffiths, Jon-Paul; Parker, Emily M.; Moloney, Mark G.; Choong, Cleo

2014-08-01

This work reports the effects of introducing diverse chemical functionalities onto the surface of polystyrene microcarrier beads on their ability to function as injectable cell carriers. Cellular adhesion and proliferation, as well as cellular outgrowths from microcarrier surfaces, using human umbilical vein endothelial cells (HUVECs), were examined in detail. It was observed that initial cell adhesion appeared to be most significantly decreased by hydrophobicity, whilst cell proliferation appeared to be improved in most chemical functional groups over unmodified polystyrene. Overall, our study highlights the importance of surface chemistry in directing the growth and function of human endothelial cells.

Diazo Groups Endure Metabolism and Enable Chemoselectivity in Cellulo

PubMed Central

2015-01-01

We introduce a stabilized diazo group as a reporter for chemical biology. ManDiaz, which is a diazo derivative of N-acetylmannosamine, is found to endure cellular metabolism and label the surface of a mammalian cell. There its diazo group can undergo a 1,3-dipolar cycloaddition with a strained alkyne, providing a signal comparable to that from the azido congener, ManNAz. The chemoselectivity of diazo and alkynyl groups enables dual labeling of cells that is not possible with azido and alkynyl groups. Thus, the diazo group, which is approximately half the size of an azido group, provides unique opportunities for orthogonal labeling of cellular components. PMID:25658416

Diazo groups endure metabolism and enable chemoselectivity in cellulo.

PubMed

Andersen, Kristen A; Aronoff, Matthew R; McGrath, Nicholas A; Raines, Ronald T

2015-02-25

We introduce a stabilized diazo group as a reporter for chemical biology. ManDiaz, which is a diazo derivative of N-acetylmannosamine, is found to endure cellular metabolism and label the surface of a mammalian cell. There its diazo group can undergo a 1,3-dipolar cycloaddition with a strained alkyne, providing a signal comparable to that from the azido congener, ManNAz. The chemoselectivity of diazo and alkynyl groups enables dual labeling of cells that is not possible with azido and alkynyl groups. Thus, the diazo group, which is approximately half the size of an azido group, provides unique opportunities for orthogonal labeling of cellular components.

Cellular Biotechnology Operations Support System Fluid Dynamics Investigation

NASA Technical Reports Server (NTRS)

2003-01-01

Aboard the International Space Station (ISS), the Tissue Culture Medium (TCM) is the bioreactor vessel in which cell cultures are grown. With its two syringe ports, it is much like a bag used to administer intravenous fluid, except it allows gas exchange needed for life. The TCM contains cell culture medium, and when frozen cells are flown to the ISS, they are thawed and introduced to the TCM through the syringe ports. In the Cellular Biotechnology Operations Support System-Fluid Dynamics Investigation (CBOSS-FDI) experiment, several mixing procedures are being assessed to determine which method achieves the most uniform mixing of growing cells and culture medium.

Introducing Computer Simulation into the High School: An Applied Mathematics Curriculum.

ERIC Educational Resources Information Center

Roberts, Nancy

1981-01-01

A programing language called DYNAMO, developed especially for writing simulation models, is promoted. Details of six, self-teaching curriculum packages recently developed for simulation-oriented instruction are provided. (MP)

Modeling integrated cellular machinery using hybrid Petri-Boolean networks.

PubMed

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

2013-01-01

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

Coarse-grained Brownian ratchet model of membrane protrusion on cellular scale.

PubMed

Inoue, Yasuhiro; Adachi, Taiji

2011-07-01

Membrane protrusion is a mechanochemical process of active membrane deformation driven by actin polymerization. Previously, Brownian ratchet (BR) was modeled on the basis of the underlying molecular mechanism. However, because the BR requires a priori load that cannot be determined without information of the cell shape, it cannot be effective in studies in which resultant shapes are to be solved. Other cellular-scale models describing the protrusion have also been suggested for modeling a whole cell; however, these models were not developed on the basis of coarse-grained physics representing the underlying molecular mechanism. Therefore, to express the membrane protrusion on the cellular scale, we propose a novel mathematical model, the coarse-grained BR (CBR), which is derived on the basis of nonequilibrium thermodynamics theory. The CBR can reproduce the BR within the limit of the quasistatic process of membrane protrusion and can estimate the protrusion velocity consistently with an effective elastic constant that represents the state of the energy of the membrane. Finally, to demonstrate the applicability of the CBR, we attempt to perform a cellular-scale simulation of migrating keratocyte in which the proposed CBR is used for the membrane protrusion model on the cellular scale. The results show that the experimentally observed shapes of the leading edge are well reproduced by the simulation. In addition, The trend of dependences of the protrusion velocity on the curvature of the leading edge, the temperature, and the substrate stiffness also agreed with the other experimental results. Thus, the CBR can be considered an appropriate cellular-scale model to express the membrane protrusion on the basis of its underlying molecular mechanism.

Modeling Integrated Cellular Machinery Using Hybrid Petri-Boolean Networks

PubMed Central

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

2013-01-01

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

Stochastic Nature in Cellular Processes

NASA Astrophysics Data System (ADS)

Liu, Bo; Liu, Sheng-Jun; Wang, Qi; Yan, Shi-Wei; Geng, Yi-Zhao; Sakata, Fumihiko; Gao, Xing-Fa

2011-11-01

The importance of stochasticity in cellular processes is increasingly recognized in both theoretical and experimental studies. General features of stochasticity in gene regulation and expression are briefly reviewed in this article, which include the main experimental phenomena, classification, quantization and regulation of noises. The correlation and transmission of noise in cascade networks are analyzed further and the stochastic simulation methods that can capture effects of intrinsic and extrinsic noise are described.

Manufacturing and Characterization of 18Ni Marage 300 Lattice Components by Selective Laser Melting.

PubMed

Contuzzi, Nicola; Campanelli, Sabina L; Casavola, Caterina; Lamberti, Luciano

2013-08-13

The spreading use of cellular structures brings the need to speed up manufacturing processes without deteriorating mechanical properties. By using Selective Laser Melting (SLM) to produce cellular structures, the designer has total freedom in defining part geometry and manufacturing is simplified. The paper investigates the suitability of Selective Laser Melting for manufacturing steel cellular lattice structures with characteristic dimensions in the micrometer range. Alternative lattice topologies including reinforcing bars in the vertical direction also are considered. The selected lattice structure topology is shown to be superior over other lattice structure designs considered in literature. Compression tests are carried out in order to evaluate mechanical strength of lattice strut specimens made via SLM. Compressive behavior of samples also is simulated by finite element analysis and numerical results are compared with experimental data in order to assess the constitutive behavior of the lattice structure designs considered in this study. Experimental data show that it is possible to build samples of relative density in the 0.2456-0.4367 range. Compressive strength changes almost linearly with respect to relative density, which in turns depends linearly on the number of vertical reinforces. Specific strength increases with cell and strut edge size. Numerical simulations confirm the plastic nature of the instability phenomena that leads the cellular structures to collapse under compression loading.

Molecular dynamics simulations of heterogeneous cell membranes in response to uniaxial membrane stretches at high loading rates.

PubMed

Zhang, Lili; Zhang, Zesheng; Jasa, John; Li, Dongli; Cleveland, Robin O; Negahban, Mehrdad; Jérusalem, Antoine

2017-08-16

The chemobiomechanical signatures of diseased cells are often distinctively different from that of healthy cells. This mainly arises from cellular structural/compositional alterations induced by disease development or therapeutic molecules. Therapeutic shock waves have the potential to mechanically destroy diseased cells and/or increase cell membrane permeability for drug delivery. However, the biomolecular mechanisms by which shock waves interact with diseased and healthy cellular components remain largely unknown. By integrating atomistic simulations with a novel multiscale numerical framework, this work provides new biomolecular mechanistic perspectives through which many mechanosensitive cellular processes could be quantitatively characterised. Here we examine the biomechanical responses of the chosen representative membrane complexes under rapid mechanical loadings pertinent to therapeutic shock wave conditions. We find that their rupture characteristics do not exhibit significant sensitivity to the applied strain rates. Furthermore, we show that the embedded rigid inclusions markedly facilitate stretch-induced membrane disruptions while mechanically stiffening the associated complexes under the applied membrane stretches. Our results suggest that the presence of rigid molecules in cellular membranes could serve as "mechanical catalysts" to promote the mechanical destructions of the associated complexes, which, in concert with other biochemical/medical considerations, should provide beneficial information for future biomechanical-mediated therapeutics.

Integration of logistic regression, Markov chain and cellular automata models to simulate urban expansion

NASA Astrophysics Data System (ADS)

Jokar Arsanjani, Jamal; Helbich, Marco; Kainz, Wolfgang; Darvishi Boloorani, Ali

2013-04-01

This research analyses the suburban expansion in the metropolitan area of Tehran, Iran. A hybrid model consisting of logistic regression model, Markov chain (MC), and cellular automata (CA) was designed to improve the performance of the standard logistic regression model. Environmental and socio-economic variables dealing with urban sprawl were operationalised to create a probability surface of spatiotemporal states of built-up land use for the years 2006, 2016, and 2026. For validation, the model was evaluated by means of relative operating characteristic values for different sets of variables. The approach was calibrated for 2006 by cross comparing of actual and simulated land use maps. The achieved outcomes represent a match of 89% between simulated and actual maps of 2006, which was satisfactory to approve the calibration process. Thereafter, the calibrated hybrid approach was implemented for forthcoming years. Finally, future land use maps for 2016 and 2026 were predicted by means of this hybrid approach. The simulated maps illustrate a new wave of suburban development in the vicinity of Tehran at the western border of the metropolis during the next decades.

Safety evaluation of driver cognitive failures and driving errors on right-turn filtering movement at signalized road intersections based on Fuzzy Cellular Automata (FCA) model.

PubMed

Chai, Chen; Wong, Yiik Diew; Wang, Xuesong

2017-07-01

This paper proposes a simulation-based approach to estimate safety impact of driver cognitive failures and driving errors. Fuzzy Logic, which involves linguistic terms and uncertainty, is incorporated with Cellular Automata model to simulate decision-making process of right-turn filtering movement at signalized intersections. Simulation experiments are conducted to estimate the relationships between cognitive failures and driving errors with safety performance. Simulation results show Different types of cognitive failures are found to have varied relationship with driving errors and safety performance. For right-turn filtering movement, cognitive failures are more likely to result in driving errors with denser conflicting traffic stream. Moreover, different driving errors are found to have different safety impacts. The study serves to provide a novel approach to linguistically assess cognitions and replicate decision-making procedures of the individual driver. Compare to crash analysis, the proposed FCA model allows quantitative estimation of particular cognitive failures, and the impact of cognitions on driving errors and safety performance. Copyright © 2017 Elsevier Ltd. All rights reserved.

Evaluation of the dispersion effect in through movement bicycles at signalized intersection via cellular automata simulation

NASA Astrophysics Data System (ADS)

Jiang, Hang; Ma, Yongjian; Jiang, Lin; Chen, Guozhou; Wang, Dongwei

2018-05-01

At signalized intersection areas, bicycle traffic presents a dispersion feature which may influence the movements of vehicles during peak period. The primary objective of this study is to simulate the dispersion effect in through-movement bicycle traffic at intersection areas and evaluate its influence on through-movement traffic. A cellular automata (CA) model is developed and validated to simulate the operations of through-movement bicycle traffic departing from two types of intersection approaches. Simulation results show that bicycles benefit from the dispersion effect when they depart from the approach with an exclusive right-turn vehicle lane. But when bicycles travel from the approach with a shared right-turn and through vehicle lane, the dispersion effect will result in friction interference and block interference on through-movement vehicles. Bicycle interferences reduce the vehicle speed and increase the delay of through-movement vehicles. The policy implications in regard to the dispersion effect from two types of approaches are discussed to improve the performance of through-movement traffic operations at signalized intersections.

Simulation of the M13 life cycle II: Investigation of the control mechanisms of M13 infection and establishment of the carrier state.

PubMed

Smeal, Steven W; Schmitt, Margaret A; Pereira, Ronnie Rodrigues; Prasad, Ashok; Fisk, John D

2017-01-01

Bacteriophage M13 is a true parasite of bacteria, able to co-opt the infected cell and control the production of progeny across many cellular generations. Here, our genetically-structured simulation of M13 is applied to quantitatively dissect the interplay between the host cellular environment and the controlling interactions governing the phage life cycle during the initial establishment of infection and across multiple cell generations. Multiple simulations suggest that phage-encoded feedback interactions constrain the utilization of host DNA polymerase, RNA polymerase and ribosomes. The simulation reveals the importance of p5 translational attenuation in controlling the production of phage double-stranded DNA and suggests an underappreciated role for p5 translational self-attenuation in resource allocation. The control elements active in a single generation are sufficient to reproduce the experimentally-observed multigenerational curing of the phage infection. Understanding the subtleties of regulation will be important for maximally exploiting M13 particles as scaffolds for nanoscale devices. Copyright © 2016 Elsevier Inc. All rights reserved.

Rethinking iron regulation and assessment in iron deficiency, the anemia of chronic disease, and obesity: introducing Hepcidin

USDA-ARS?s Scientific Manuscript database

Adequate iron availability is essential to human development and overall health. Iron is a key component of oxygen-carrying proteins; a vital player in cellular metabolism, and essential to cell growth and differentiation. Tight regulation of iron at the systemic and cytosolic level is necessary bec...

Beyond the Central Dogma: Bringing Epigenetics into the Classroom

ERIC Educational Resources Information Center

Drits-Esser, Dina; Malone, Molly; Barber, Nicola C.; Stark, Louisa A.

2014-01-01

Epigenetics is the study of how external factors and internal cellular signals can lead to changes in the packaging and processing of DNA sequences, thereby altering the expression of genes and traits. Exploring the epigenome introduces students to environmental influences on our genes and the complexities of gene expression. A supplemental…

Mathematics, Thermodynamics, and Modeling to Address Ten Common Misconceptions about Protein Structure, Folding, and Stability

ERIC Educational Resources Information Center

Robic, Srebrenka

2010-01-01

To fully understand the roles proteins play in cellular processes, students need to grasp complex ideas about protein structure, folding, and stability. Our current understanding of these topics is based on mathematical models and experimental data. However, protein structure, folding, and stability are often introduced as descriptive, qualitative…

Cellular replication limits in the Luria-Delbrück mutation model

NASA Astrophysics Data System (ADS)

Rodriguez-Brenes, Ignacio A.; Wodarz, Dominik; Komarova, Natalia L.

2016-08-01

Originally developed to elucidate the mechanisms of natural selection in bacteria, the Luria-Delbrück model assumed that cells are intrinsically capable of dividing an unlimited number of times. This assumption however, is not true for human somatic cells which undergo replicative senescence. Replicative senescence is thought to act as a mechanism to protect against cancer and the escape from it is a rate-limiting step in cancer progression. Here we introduce a Luria-Delbrück model that explicitly takes into account cellular replication limits in the wild type cell population and models the emergence of mutants that escape replicative senescence. We present results on the mean, variance, distribution, and asymptotic behavior of the mutant population in terms of three classical formulations of the problem. More broadly the paper introduces the concept of incorporating replicative limits as part of the Luria-Delbrück mutational framework. Guidelines to extend the theory to include other types of mutations and possible applications to the modeling of telomere crisis and fluctuation analysis are also discussed.

Computational design of a red fluorophore ligase for site-specific protein labeling in living cells

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

Liu, Daniel S.; Nivon, Lucas G.; Richter, Florian

In this study, chemical fluorophores offer tremendous size and photophysical advantages over fluorescent proteins but are much more challenging to target to specific cellular proteins. Here, we used Rosetta-based computation to design a fluorophore ligase that accepts the red dye resorufin, starting from Escherichia coli lipoic acid ligase. X-ray crystallography showed that the design closely matched the experimental structure. Resorufin ligase catalyzed the site-specific and covalent attachment of resorufin to various cellular proteins genetically fused to a 13-aa recognition peptide in multiple mammalian cell lines and in primary cultured neurons. We used resorufin ligase to perform superresolution imaging of themore » intermediate filament protein vimentin by stimulated emission depletion and electron microscopies. This work illustrates the power of Rosetta for major redesign of enzyme specificity and introduces a tool for minimally invasive, highly specific imaging of cellular proteins by both conventional and superresolution microscopies.« less

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

PubMed

Denker, Elsa; Jiang, Di

2012-05-01

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

Exploiting the biomolecular corona: pre-coating of nanoparticles enables controlled cellular interactions.

PubMed

Simon, Johanna; Müller, Laura K; Kokkinopoulou, Maria; Lieberwirth, Ingo; Morsbach, Svenja; Landfester, Katharina; Mailänder, Volker

2018-06-14

Formation of the biomolecular corona ultimately determines the successful application of nanoparticles in vivo. Adsorption of biomolecules such as proteins is an inevitable process that takes place instantaneously upon contact with physiological fluid (e.g. blood). Therefore, strategies are needed to control this process in order to improve the properties of the nanoparticles and to allow targeted drug delivery. Here, we show that the design of the protein corona by a pre-formed protein corona with tailored properties enables targeted cellular interactions. Nanoparticles were pre-coated with immunoglobulin depleted plasma to create and design a protein corona that reduces cellular uptake by immune cells. It was proven that a pre-formed protein corona remains stable even after nanoparticles were re-introduced to plasma. This opens up the great potential to exploit protein corona formation, which will significantly influence the development of novel nanomaterials.

Computational design of a red fluorophore ligase for site-specific protein labeling in living cells

DOE PAGES

Liu, Daniel S.; Nivon, Lucas G.; Richter, Florian; ...

2014-10-13

In this study, chemical fluorophores offer tremendous size and photophysical advantages over fluorescent proteins but are much more challenging to target to specific cellular proteins. Here, we used Rosetta-based computation to design a fluorophore ligase that accepts the red dye resorufin, starting from Escherichia coli lipoic acid ligase. X-ray crystallography showed that the design closely matched the experimental structure. Resorufin ligase catalyzed the site-specific and covalent attachment of resorufin to various cellular proteins genetically fused to a 13-aa recognition peptide in multiple mammalian cell lines and in primary cultured neurons. We used resorufin ligase to perform superresolution imaging of themore » intermediate filament protein vimentin by stimulated emission depletion and electron microscopies. This work illustrates the power of Rosetta for major redesign of enzyme specificity and introduces a tool for minimally invasive, highly specific imaging of cellular proteins by both conventional and superresolution microscopies.« less

Surface chemistry governs cellular tropism of nanoparticles in the brain

NASA Astrophysics Data System (ADS)

Song, Eric; Gaudin, Alice; King, Amanda R.; Seo, Young-Eun; Suh, Hee-Won; Deng, Yang; Cui, Jiajia; Tietjen, Gregory T.; Huttner, Anita; Saltzman, W. Mark

2017-05-01

Nanoparticles are of long-standing interest for the treatment of neurological diseases such as glioblastoma. Most past work focused on methods to introduce nanoparticles into the brain, suggesting that reaching the brain interstitium will be sufficient to ensure therapeutic efficacy. However, optimized nanoparticle design for drug delivery to the central nervous system is limited by our understanding of their cellular deposition in the brain. Here, we investigated the cellular fate of poly(lactic acid) nanoparticles presenting different surface chemistries, after administration by convection-enhanced delivery. We demonstrate that nanoparticles with `stealth' properties mostly avoid internalization by all cell types, but internalization can be enhanced by functionalization with bio-adhesive end-groups. We also show that association rates measured in cultured cells predict the extent of internalization of nanoparticles in cell populations. Finally, evaluating therapeutic efficacy in an orthotopic model of glioblastoma highlights the need to balance significant uptake without inducing adverse toxicity.

A Genetic Approach to Promoter Recognition during Trans Induction of Viral Gene Expression

NASA Astrophysics Data System (ADS)

Coen, Donald M.; Weinheimer, Steven P.; McKnight, Steven L.

1986-10-01

Viral infection of mammalian cells entails the regulated induction of viral gene expression. The induction of many viral genes, including the herpes simplex virus gene encoding thymidine kinase (tk), depends on viral regulatory proteins that act in trans. Because recognition of the tk promoter by cellular transcription factors is well understood, its trans induction by viral regulatory proteins may serve as a useful model for the regulation of eukaryotic gene expression. A comprehensive set of mutations was therefore introduced into the chromosome of herpes simplex virus at the tk promoter to directly analyze the effects of promoter mutations on tk transcription. The promoter domains required for efficient tk expression under conditions of trans induction corresponded to those important for recognition by cellular transcription factors. Thus, trans induction of tk expression may be catalyzed initially by the interaction of viral regulatory proteins with cellular transcription factors.

[Translational/regulatory science researches of NIHS for regenerative medicine and cellular therapy products].

PubMed

Sato, Yoji

2014-01-01

In 2013, the Japanese Diet passed the Regenerative Medicine Promotion Act and the revisions to the Pharmaceutical Affairs Act, which was also renamed as the Therapeutic Products Act (TPA). One of the aims of the new/revised Acts is to promote the development and translation of and access to regenerative/cellular therapies. In the TPA, a product derived from processing cells is categorized as a subgroup of "regenerative medicine, cellular therapy and gene therapy products" (RCGPs), products distinct from pharmaceuticals and medical devices, allowing RCGPs to obtain a conditional and time- limited marketing authorization much earlier than that under the conventional system. To foster not only RCGPs, but also innovative pharmaceuticals and medical devices, the Ministry of Health, Labour and Welfare recently launched Translational Research Program for Innovative Pharmaceuticals, Medical Devices and RCGPs. This mini-review introduces contributions of the National Institute of Health Sciences (NIHS) to research projects on RCGPs in the Program.

Color moiré simulations in contact-type 3-D displays.

PubMed

Lee, B-R; Son, J-Y; Chernyshov, O O; Lee, H; Jeong, I-K

2015-06-01

A new method of color moiré fringe simulation in the contact-type 3-D displays is introduced. The method allows simulating color moirés appearing in the displays, which cannot be approximated by conventional cosine approximation of a line grating. The color moirés are mainly introduced by the line width of the boundary lines between the elemental optics in and plate thickness of viewing zone forming optics. This is because the lines are hiding some parts of pixels under the viewing zone forming optics, and the plate thickness induces a virtual contraction of the pixels. The simulated color moiré fringes are closely matched with those appearing at the displays.

Cellular telephone interference with medical equipment.

PubMed

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

2005-10-01

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

Using mixed reality, force feedback and tactile augmentation to improve the realism of medical simulation.

PubMed

Fisher, J Brian; Porter, Susan M

2002-01-01

This paper describes an application of a display approach which uses chromakey techniques to composite real and computer-generated images allowing a user to see his hands and medical instruments collocated with the display of virtual objects during a medical training simulation. Haptic feedback is provided through the use of a PHANTOM force feedback device in addition to tactile augmentation, which allows the user to touch virtual objects by introducing corresponding real objects in the workspace. A simplified catheter introducer insertion simulation was developed to demonstrate the capabilities of this approach.

Testing flight software on the ground: Introducing the hardware-in-the-loop simulation method to the Alpha Magnetic Spectrometer on the International Space Station

NASA Astrophysics Data System (ADS)

Sun, Wenhao; Cai, Xudong; Meng, Qiao

2016-04-01

Complex automatic protection functions are being added to the onboard software of the Alpha Magnetic Spectrometer. A hardware-in-the-loop simulation method has been introduced to overcome the difficulties of ground testing that are brought by hardware and environmental limitations. We invented a time-saving approach by reusing the flight data as the data source of the simulation system instead of mathematical models. This is easy to implement and it works efficiently. This paper presents the system framework, implementation details and some application examples.

Field validation of a free-agent cellular automata model of fire spread with fire–atmosphere coupling

Treesearch

Gary Achtemeier

2012-01-01

A cellular automata fire model represents ‘elements’ of fire by autonomous agents. A few simple algebraic expressions substituted for complex physical and meteorological processes and solved iteratively yield simulations for ‘super-diffusive’ fire spread and coupled surface-layer (2-m) fire–atmosphere processes. Pressure anomalies, which are integrals of the thermal...

RESTSIM: A Simulation Model That Highlights Decision Making under Conditions of Uncertainty.

ERIC Educational Resources Information Center

Zinkhan, George M.; Taylor, James R.

1983-01-01

Describes RESTSIM, an interactive computer simulation program for graduate and upper-level undergraduate management, marketing, and retailing courses, which introduces naive users to simulation as a decision support technique, and provides a vehicle for studying various statistical procedures for evaluating simulation output. (MBR)

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

PubMed Central

Lu, Luyao; Xia, Ling; Zhu, Xiuwei

2012-01-01

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

Reduced native state stability in crowded cellular environment due to protein-protein interactions.

PubMed

Harada, Ryuhei; Tochio, Naoya; Kigawa, Takanori; Sugita, Yuji; Feig, Michael

2013-03-06

The effect of cellular crowding environments on protein structure and stability is a key issue in molecular and cellular biology. The classical view of crowding emphasizes the volume exclusion effect that generally favors compact, native states. Here, results from molecular dynamics simulations and NMR experiments show that protein crowders may destabilize native states via protein-protein interactions. In the model system considered here, mixtures of villin head piece and protein G at high concentrations, villin structures become increasingly destabilized upon increasing crowder concentrations. The denatured states observed in the simulation involve partial unfolding as well as more subtle conformational shifts. The unfolded states remain overall compact and only partially overlap with unfolded ensembles at high temperature and in the presence of urea. NMR measurements on the same systems confirm structural changes upon crowding based on changes of chemical shifts relative to dilute conditions. An analysis of protein-protein interactions and energetic aspects suggests the importance of enthalpic and solvation contributions to the crowding free energies that challenge an entropic-centered view of crowding effects.

Digital Cellular Solid Pressure Vessels: A Novel Approach for Human Habitation in Space

NASA Technical Reports Server (NTRS)

Cellucci, Daniel; Jenett, Benjamin; Cheung, Kenneth C.

2017-01-01

It is widely assumed that human exploration beyond Earth's orbit will require vehicles capable of providing long duration habitats that simulate an Earth-like environment - consistent artificial gravity, breathable atmosphere, and sufficient living space- while requiring the minimum possible launch mass. This paper examines how the qualities of digital cellular solids - high-performance, repairability, reconfigurability, tunable mechanical response - allow the accomplishment of long-duration habitat objectives at a fraction of the mass required for traditional structural technologies. To illustrate the impact digital cellular solids could make as a replacement to conventional habitat subsystems, we compare recent proposed deep space habitat structural systems with a digital cellular solids pressure vessel design that consists of a carbon fiber reinforced polymer (CFRP) digital cellular solid cylindrical framework that is lined with an ultra-high molecular weight polyethylene (UHMWPE) skin. We use the analytical treatment of a linear specific modulus scaling cellular solid to find the minimum mass pressure vessel for a structure and find that, for equivalent habitable volume and appropriate safety factors, the use of digital cellular solids provides clear methods for producing structures that are not only repairable and reconfigurable, but also higher performance than their conventionally manufactured counterparts.

Design Optimization of Irregular Cellular Structure for Additive Manufacturing

NASA Astrophysics Data System (ADS)

Song, Guo-Hua; Jing, Shi-Kai; Zhao, Fang-Lei; Wang, Ye-Dong; Xing, Hao; Zhou, Jing-Tao

2017-09-01

Irregularcellular structurehas great potential to be considered in light-weight design field. However, the research on optimizing irregular cellular structures has not yet been reporteddue to the difficulties in their modeling technology. Based on the variable density topology optimization theory, an efficient method for optimizing the topology of irregular cellular structures fabricated through additive manufacturing processes is proposed. The proposed method utilizes tangent circles to automatically generate the main outline of irregular cellular structure. The topological layoutof each cellstructure is optimized using the relative density informationobtained from the proposed modified SIMP method. A mapping relationship between cell structure and relative densityelement is builtto determine the diameter of each cell structure. The results show that the irregular cellular structure can be optimized with the proposed method. The results of simulation and experimental test are similar for irregular cellular structure, which indicate that the maximum deformation value obtained using the modified Solid Isotropic Microstructures with Penalization (SIMP) approach is lower 5.4×10-5 mm than that using the SIMP approach under the same under the same external load. The proposed research provides the instruction to design the other irregular cellular structure.

Multiscale design and multiobjective optimization of orthopedic hip implants with functionally graded cellular material.

PubMed

Arabnejad Khanoki, Sajad; Pasini, Damiano

2012-03-01

Revision surgeries of total hip arthroplasty are often caused by a deficient structural compatibility of the implant. Two main culprits, among others, are bone-implant interface instability and bone resorption. To address these issues, in this paper we propose a novel type of implant, which, in contrast to current hip replacement implants made of either a fully solid or a foam material, consists of a lattice microstructure with nonhomogeneous distribution of material properties. A methodology based on multiscale mechanics and design optimization is introduced to synthesize a graded cellular implant that can minimize concurrently bone resorption and implant interface failure. The procedure is applied to the design of a 2D left implanted femur with optimized gradients of relative density. To assess the manufacturability of the graded cellular microstructure, a proof-of-concept is fabricated by using rapid prototyping. The results from the analysis are used to compare the optimized cellular implant with a fully dense titanium implant and a homogeneous foam implant with a relative density of 50%. The bone resorption and the maximum value of interface stress of the cellular implant are found to be over 70% and 50% less than the titanium implant while being 53% and 65% less than the foam implant.

Effect of solid distribution on elastic properties of open-cell cellular solids using numerical and experimental methods.

PubMed

Zargarian, A; Esfahanian, M; Kadkhodapour, J; Ziaei-Rad, S

2014-09-01

Effect of solid distribution between edges and vertices of three-dimensional cellular solid with an open-cell structure was investigated both numerically and experimentally. Finite element analysis (FEA) with continuum elements and appropriate periodic boundary condition was employed to calculate the elastic properties of cellular solids using tetrakaidecahedral (Kelvin) unit cell. Relative densities between 0.01 and 0.1 and various values of solid fractions were considered. In order to validate the numerical model, three scaffolds with the relative density of 0.08, but different amounts of solid in vertices, were fabricated via 3-D printing technique. Good agreement was observed between numerical simulation and experimental results. Results of numerical simulation showed that, at low relative densities (<0.03), Young׳s modulus increased by shifting materials away from edges to vertices at first and then decreased after reaching a critical point. However, for the high values of relative density, Young׳s modulus increased monotonically. Mechanisms of such a behavior were discussed in detail. Results also indicated that Poisson׳s ratio decreased by increasing relative density and solid fraction in vertices. By fitting a curve to the data obtained from the numerical simulation and considering the relative density and solid fraction in vertices, empirical relations were derived for Young׳s modulus and Poisson׳s ratio. Copyright © 2014 Elsevier Ltd. All rights reserved.

Numerical and experimental validation of a particle Galerkin method for metal grinding simulation

NASA Astrophysics Data System (ADS)

Wu, C. T.; Bui, Tinh Quoc; Wu, Youcai; Luo, Tzui-Liang; Wang, Morris; Liao, Chien-Chih; Chen, Pei-Yin; Lai, Yu-Sheng

2018-03-01

In this paper, a numerical approach with an experimental validation is introduced for modelling high-speed metal grinding processes in 6061-T6 aluminum alloys. The derivation of the present numerical method starts with an establishment of a stabilized particle Galerkin approximation. A non-residual penalty term from strain smoothing is introduced as a means of stabilizing the particle Galerkin method. Additionally, second-order strain gradients are introduced to the penalized functional for the regularization of damage-induced strain localization problem. To handle the severe deformation in metal grinding simulation, an adaptive anisotropic Lagrangian kernel is employed. Finally, the formulation incorporates a bond-based failure criterion to bypass the prospective spurious damage growth issues in material failure and cutting debris simulation. A three-dimensional metal grinding problem is analyzed and compared with the experimental results to demonstrate the effectiveness and accuracy of the proposed numerical approach.

Interaction and Impact Studies for Distributed Energy Resource, Transactive Energy, and Electric Grid, using High Performance Computing ?based Modeling and Simulation

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

Kelley, B. M.

The electric utility industry is undergoing significant transformations in its operation model, including a greater emphasis on automation, monitoring technologies, and distributed energy resource management systems (DERMS). With these changes and new technologies, while driving greater efficiencies and reliability, these new models may introduce new vectors of cyber attack. The appropriate cybersecurity controls to address and mitigate these newly introduced attack vectors and potential vulnerabilities are still widely unknown and performance of the control is difficult to vet. This proposal argues that modeling and simulation (M&S) is a necessary tool to address and better understand these problems introduced by emergingmore » technologies for the grid. M&S will provide electric utilities a platform to model its transmission and distribution systems and run various simulations against the model to better understand the operational impact and performance of cybersecurity controls.« less

Cells, Agents, and Support Vectors in Interaction - Modeling Urban Sprawl based on Machine Learning and Artificial Intelligence Techniques in a Post-Industrial Region

NASA Astrophysics Data System (ADS)

Rienow, A.; Menz, G.

2015-12-01

Since the beginning of the millennium, artificial intelligence techniques as cellular automata (CA) and multi-agent systems (MAS) have been incorporated into land-system simulations to address the complex challenges of transitions in urban areas as open, dynamic systems. The study presents a hybrid modeling approach for modeling the two antagonistic processes of urban sprawl and urban decline at once. The simulation power of support vector machines (SVM), cellular automata (CA) and multi-agent systems (MAS) are integrated into one modeling framework and applied to the largest agglomeration of Central Europe: the Ruhr. A modified version of SLEUTH (short for Slope, Land-use, Exclusion, Urban, Transport, and Hillshade) functions as the CA component. SLEUTH makes use of historic urban land-use data sets and growth coefficients for the purpose of modeling physical urban expansion. The machine learning algorithm of SVM is applied in order to enhance SLEUTH. Thus, the stochastic variability of the CA is reduced and information about the human and ecological forces driving the local suitability of urban sprawl is incorporated. Subsequently, the supported CA is coupled with the MAS ReHoSh (Residential Mobility and the Housing Market of Shrinking City Systems). The MAS models population patterns, housing prices, and housing demand in shrinking regions based on interactions between household and city agents. Semi-explicit urban weights are introduced as a possibility of modeling from and to the pixel simultaneously. Three scenarios of changing housing preferences reveal the urban development of the region in terms of quantity and location. They reflect the dissemination of sustainable thinking among stakeholders versus the steady dream of owning a house in sub- and exurban areas. Additionally, the outcomes are transferred into a digital petri dish reflecting a synthetic environment with perfect conditions of growth. Hence, the generic growth elements affecting the future face of post-industrial cities are revealed. Finally, the advantages and limitations of linking pixels and people by combining AI and machine learning techniques in a multi-scale geosimulation approach are to be discussed.

Dynamic Finite Element Predictions for Mars Sample Return Cellular Impact Test #4

NASA Technical Reports Server (NTRS)

Fasanella, Edwin L.; Billings, Marcus D.

2001-01-01

The nonlinear, transient dynamic finite element code, MSC.Dytran, was used to simulate an impact test of an energy absorbing Earth Entry Vehicle (EEV) that will impact without a parachute. EEVOs are designed to return materials from asteroids, comets, or planets for laboratory analysis on Earth. The EEV concept uses an energy absorbing cellular structure designed to contain and limit the acceleration of space exploration samples during Earth impact. The spherical shaped cellular structure is composed of solid hexagonal and pentagonal foam-filled cells with hybrid graphite-epoxy/Kevlar cell walls. Space samples fit inside a smaller sphere at the center of the EEVOs cellular structure. Pre-test analytical predictions were compared with the test results from a bungee accelerator. The model used to represent the foam and the proper failure criteria for the cell walls were critical in predicting the impact loads of the cellular structure. It was determined that a FOAM1 model for the foam and a 20% failure strain criteria for the cell walls gave an accurate prediction of the acceleration pulse for cellular impact.

Stochastic simulations of fatty-acid proto-cell models

NASA Astrophysics Data System (ADS)

Mavelli, F.; Ruiz-Mirazo, K.

2007-06-01

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

Computer modeling describes gravity-related adaptation in cell cultures.

PubMed

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

2009-12-16

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

Calibrating cellular automaton models for pedestrians walking through corners

NASA Astrophysics Data System (ADS)

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.

Simulation of land use change in the three gorges reservoir area based on CART-CA

NASA Astrophysics Data System (ADS)

Yuan, Min

2018-05-01

This study proposes a new method to simulate spatiotemporal complex multiple land uses by using classification and regression tree algorithm (CART) based CA model. In this model, we use classification and regression tree algorithm to calculate land class conversion probability, and combine neighborhood factor, random factor to extract cellular transformation rules. The overall Kappa coefficient is 0.8014 and the overall accuracy is 0.8821 in the land dynamic simulation results of the three gorges reservoir area from 2000 to 2010, and the simulation results are satisfactory.

Simulations of Living Cell Origins Using a Cellular Automata Model

NASA Astrophysics Data System (ADS)

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.

Simulations of living cell origins using a cellular automata model.

PubMed

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.

Cellular Automata Generalized To An Inferential System

NASA Astrophysics Data System (ADS)

Blower, David J.

2007-11-01

Stephen Wolfram popularized elementary one-dimensional cellular automata in his book, A New Kind of Science. Among many remarkable things, he proved that one of these cellular automata was a Universal Turing Machine. Such cellular automata can be interpreted in a different way by viewing them within the context of the formal manipulation rules from probability theory. Bayes's Theorem is the most famous of such formal rules. As a prelude, we recapitulate Jaynes's presentation of how probability theory generalizes classical logic using modus ponens as the canonical example. We emphasize the important conceptual standing of Boolean Algebra for the formal rules of probability manipulation and give an alternative demonstration augmenting and complementing Jaynes's derivation. We show the complementary roles played in arguments of this kind by Bayes's Theorem and joint probability tables. A good explanation for all of this is afforded by the expansion of any particular logic function via the disjunctive normal form (DNF). The DNF expansion is a useful heuristic emphasized in this exposition because such expansions point out where relevant 0s should be placed in the joint probability tables for logic functions involving any number of variables. It then becomes a straightforward exercise to rely on Boolean Algebra, Bayes's Theorem, and joint probability tables in extrapolating to Wolfram's cellular automata. Cellular automata are seen as purely deductive systems, just like classical logic, which probability theory is then able to generalize. Thus, any uncertainties which we might like to introduce into the discussion about cellular automata are handled with ease via the familiar inferential path. Most importantly, the difficult problem of predicting what cellular automata will do in the far future is treated like any inferential prediction problem.

Analysis of high-throughput screening reveals the effect of surface topographies on cellular morphology.

PubMed

Hulsman, Marc; Hulshof, Frits; Unadkat, Hemant; Papenburg, Bernke J; Stamatialis, Dimitrios F; Truckenmüller, Roman; van Blitterswijk, Clemens; de Boer, Jan; Reinders, Marcel J T

2015-03-01

Surface topographies of materials considerably impact cellular behavior as they have been shown to affect cell growth, provide cell guidance, and even induce cell differentiation. Consequently, for successful application in tissue engineering, the contact interface of biomaterials needs to be optimized to induce the required cell behavior. However, a rational design of biomaterial surfaces is severely hampered because knowledge is lacking on the underlying biological mechanisms. Therefore, we previously developed a high-throughput screening device (TopoChip) that measures cell responses to large libraries of parameterized topographical material surfaces. Here, we introduce a computational analysis of high-throughput materiome data to capture the relationship between the surface topographies of materials and cellular morphology. We apply robust statistical techniques to find surface topographies that best promote a certain specified cellular response. By augmenting surface screening with data-driven modeling, we determine which properties of the surface topographies influence the morphological properties of the cells. With this information, we build models that predict the cellular response to surface topographies that have not yet been measured. We analyze cellular morphology on 2176 surfaces, and find that the surface topography significantly affects various cellular properties, including the roundness and size of the nucleus, as well as the perimeter and orientation of the cells. Our learned models capture and accurately predict these relationships and reveal a spectrum of topographies that induce various levels of cellular morphologies. Taken together, this novel approach of high-throughput screening of materials and subsequent analysis opens up possibilities for a rational design of biomaterial surfaces. Copyright © 2015 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

The Development and Comparison of Molecular Dynamics Simulation and Monte Carlo Simulation

NASA Astrophysics Data System (ADS)

Chen, Jundong

2018-03-01

Molecular dynamics is an integrated technology that combines physics, mathematics and chemistry. Molecular dynamics method is a computer simulation experimental method, which is a powerful tool for studying condensed matter system. This technique not only can get the trajectory of the atom, but can also observe the microscopic details of the atomic motion. By studying the numerical integration algorithm in molecular dynamics simulation, we can not only analyze the microstructure, the motion of particles and the image of macroscopic relationship between them and the material, but can also study the relationship between the interaction and the macroscopic properties more conveniently. The Monte Carlo Simulation, similar to the molecular dynamics, is a tool for studying the micro-molecular and particle nature. In this paper, the theoretical background of computer numerical simulation is introduced, and the specific methods of numerical integration are summarized, including Verlet method, Leap-frog method and Velocity Verlet method. At the same time, the method and principle of Monte Carlo Simulation are introduced. Finally, similarities and differences of Monte Carlo Simulation and the molecular dynamics simulation are discussed.

Basic guidelines to introduce electric circuit simulation software in a general physics course

NASA Astrophysics Data System (ADS)

Moya, A. A.

2018-05-01

The introduction of electric circuit simulation software for undergraduate students in a general physics course is proposed in order to contribute to the constructive learning of electric circuit theory. This work focuses on the lab exercises based on dc, transient and ac analysis in electric circuits found in introductory physics courses, and shows how students can use the simulation software to do simple activities associated with a lab exercise itself and with related topics. By introducing electric circuit simulation programs in a general physics course as a brief activitiy complementing lab exercise, students develop basic skills in using simulation software, improve their knowledge on the topology of electric circuits and perceive that the technology contributes to their learning, all without reducing the time spent on the actual content of the course.

Stochastic simulation of human pulmonary blood flow and transit time frequency distribution based on anatomic and elasticity data.

PubMed

Huang, Wei; Shi, Jun; Yen, R T

2012-12-01

The objective of our study was to develop a computing program for computing the transit time frequency distributions of red blood cell in human pulmonary circulation, based on our anatomic and elasticity data of blood vessels in human lung. A stochastic simulation model was introduced to simulate blood flow in human pulmonary circulation. In the stochastic simulation model, the connectivity data of pulmonary blood vessels in human lung was converted into a probability matrix. Based on this model, the transit time of red blood cell in human pulmonary circulation and the output blood pressure were studied. Additionally, the stochastic simulation model can be used to predict the changes of blood flow in human pulmonary circulation with the advantage of the lower computing cost and the higher flexibility. In conclusion, a stochastic simulation approach was introduced to simulate the blood flow in the hierarchical structure of a pulmonary circulation system, and to calculate the transit time distributions and the blood pressure outputs.

Cellular structure of lean hydrogen flames in microgravity

NASA Technical Reports Server (NTRS)

Patnaik, G.; Kailasanath, K.

1990-01-01

Detailed, time-dependent, two-dimensional numerical simulations of premixed laminar flames have been used to study the initiation and subsequent development of cellular structures in lean hydrogen-air flames. The model includes detailed hydrogen-oxygen combustion with 24 elementary reactions of eight reactive species and a nitrogen diluent, molecular diffusion of all species, thermal conduction, viscosity, and convection. This model has been used to study the nonlinear evolution of cellular flame structure and shows that cell splitting, as observed in experiments, can be predicted numerically for sufficiently reactive mixtures. The structures that evolved also resembled the cellular structures observed in experiments. The present study shows that the 'cell-split limit' postulated from experimental observations is an intrinsic property of the mixture and that external factors such as heat losses are not necessary to cause this limit.

Numerical simulation of dendrite growth in nickel-based superalloy and validated by in-situ observation using high temperature confocal laser scanning microscopy

NASA Astrophysics Data System (ADS)

Yan, Xuewei; Xu, Qingyan; Liu, Baicheng

2017-12-01

Dendritic structures are the predominant microstructural constituents of nickel-based superalloys, an understanding of the dendrite growth is required in order to obtain the desirable microstructure and improve the performance of castings. For this reason, numerical simulation method and an in-situ observation technology by employing high temperature confocal laser scanning microscopy (HT-CLSM) were used to investigate dendrite growth during solidification process. A combined cellular automaton-finite difference (CA-FD) model allowing for the prediction of dendrite growth of binary alloys was developed. The algorithm of cells capture was modified, and a deterministic cellular automaton (DCA) model was proposed to describe neighborhood tracking. The dendrite and detail morphology, especially hundreds of dendrites distribution at a large scale and three-dimensional (3-D) polycrystalline growth, were successfully simulated based on this model. The dendritic morphologies of samples before and after HT-CLSM were both observed by optical microscope (OM) and scanning electron microscope (SEM). The experimental observations presented a reasonable agreement with the simulation results. It was also found that primary or secondary dendrite arm spacing, and segregation pattern were significantly influenced by dendrite growth. Furthermore, the directional solidification (DS) dendritic evolution behavior and detail morphology were also simulated based on the proposed model, and the simulation results also agree well with experimental results.

Simulating muscular thin films using thermal contraction capabilities in finite element analysis tools.

PubMed

Webster, Victoria A; Nieto, Santiago G; Grosberg, Anna; Akkus, Ozan; Chiel, Hillel J; Quinn, Roger D

2016-10-01

In this study, new techniques for approximating the contractile properties of cells in biohybrid devices using Finite Element Analysis (FEA) have been investigated. Many current techniques for modeling biohybrid devices use individual cell forces to simulate the cellular contraction. However, such techniques result in long simulation runtimes. In this study we investigated the effect of the use of thermal contraction on simulation runtime. The thermal contraction model was significantly faster than models using individual cell forces, making it beneficial for rapidly designing or optimizing devices. Three techniques, Stoney׳s Approximation, a Modified Stoney׳s Approximation, and a Thermostat Model, were explored for calibrating thermal expansion/contraction parameters (TECPs) needed to simulate cellular contraction using thermal contraction. The TECP values were calibrated by using published data on the deflections of muscular thin films (MTFs). Using these techniques, TECP values that suitably approximate experimental deflections can be determined by using experimental data obtained from cardiomyocyte MTFs. Furthermore, a sensitivity analysis was performed in order to investigate the contribution of individual variables, such as elastic modulus and layer thickness, to the final calibrated TECP for each calibration technique. Additionally, the TECP values are applicable to other types of biohybrid devices. Two non-MTF models were simulated based on devices reported in the existing literature. Copyright © 2016 Elsevier Ltd. All rights reserved.

Depth-resolved cellular microrheology using HiLo microscopy.

PubMed

Michaelson, Jarett; Choi, Heejin; So, Peter; Huang, Hayden

2012-06-01

It is increasingly important to measure cell mechanical properties in three-dimensional environments. Particle tracking microrheology (PTM) can measure cellular viscoelastic properties; however, out-of-plane data can introduce artifacts into these measurements. We developed a technique that employs HiLo microscopy to reduce out-of-plane contributions. This method eliminated signals from 90% of probes 0.5 μm or further from the focal plane, while retaining all in-plane probes. We used this technique to characterize live-cell bilayers and found that there were significant, frequency-dependent changes to the extracted cell moduli when compared to conventional analysis. Our results indicate that removal of out-of-plane information is vital for accurate assessments of cell mechanical properties.

Low Reactive Level Laser Therapy for Mesenchymal Stromal Cells Therapies

PubMed Central

Kushibiki, Toshihiro; Hirasawa, Takeshi; Okawa, Shinpei; Ishihara, Miya

2015-01-01

Low reactive level laser therapy (LLLT) is mainly focused on the activation of intracellular or extracellular chromophore and the initiation of cellular signaling by using low power lasers. Over the past forty years, it was realized that the laser therapy had the potential to improve wound healing and reduce pain and inflammation. In recent years, the term LLLT has become widely recognized in the field of regenerative medicine. In this review, we will describe the mechanisms of action of LLLT at a cellular level and introduce the application to mesenchymal stem cells and mesenchymal stromal cells (MSCs) therapies. Finally, our recent research results that LLLT enhanced the MSCs differentiation to osteoblast will also be described. PMID:26273309

A novel computational method to simulate non-enzymatic self-replication. [Abstract only

NASA Technical Reports Server (NTRS)

Navarro-Gonzalez, Rafael; Reggia, James A.; Wu, Jayoung; Chou, Hui-Hsien

1994-01-01

Non-enzymatic, template-directed synthesis of oligonucleotides has been extensively studied in the laboratory as a model to understand the kind of chemical processes that might have contributed to the origin of life on Earth. Several oligonucleotides have been shown to catalyze the synthesis of their complements from activated mononucleotides; however, a restricted number of them have been found to self-replicate. Recently we developed an efficient modified cellular automata method that supports the study of self-replicating oligonucleotides. With this method the oligonucleotide molecules are represented as active cells imbedded in a two-dimensional array of inactive cells symbolizing the environment. Random movements and probability-governed chemical reactions occurring in a cellular space can effectively simulate the experimental behavior observed in self-directed replication of oligonucleotides.

APRON: A Cellular Processor Array Simulation and Hardware Design Tool

NASA Astrophysics Data System (ADS)

Barr, David R. W.; Dudek, Piotr

2009-12-01

We present a software environment for the efficient simulation of cellular processor arrays (CPAs). This software (APRON) is used to explore algorithms that are designed for massively parallel fine-grained processor arrays, topographic multilayer neural networks, vision chips with SIMD processor arrays, and related architectures. The software uses a highly optimised core combined with a flexible compiler to provide the user with tools for the design of new processor array hardware architectures and the emulation of existing devices. We present performance benchmarks for the software processor array implemented on standard commodity microprocessors. APRON can be configured to use additional processing hardware if necessary and can be used as a complete graphical user interface and development environment for new or existing CPA systems, allowing more users to develop algorithms for CPA systems.

Numerical Simulation of Thawing Process of Biological Tissue

NASA Astrophysics Data System (ADS)

Momose, Noboru; Tada, Yukio; Hayashi, Yujiro

Heat transfer and simplified physicochemical model for thawing of the frozen biological cell element consisting of cell and extracellular region was proposed. The melting of intra-and extra-cellular ice, the water transport through cell membrane and other microscale behavior during thawing process were discussed as a function of temperature. Recovery of the cell volume and change of osmotic pressure difference during thawing were clarified theortically in connection with heating velocity, initial cell volume and membrane permeability. Extending this model, the thawing of cellular tissue consisted of numerous cell elements was also simulated. There was a position where osmotic pressure difference became maximum during thawing. Summarizing these results, the thawing damage due to osmotic stress was discussed in relation with the heating operation and the size effect of tissue.

Microstructure-based hyperelastic models for closed-cell solids

PubMed Central

Wyatt, Hayley

2017-01-01

For cellular bodies involving large elastic deformations, mesoscopic continuum models that take into account the interplay between the geometry and the microstructural responses of the constituents are developed, analysed and compared with finite-element simulations of cellular structures with different architecture. For these models, constitutive restrictions for the physical plausibility of the material responses are established, and global descriptors such as nonlinear elastic and shear moduli and Poisson’s ratio are obtained from the material characteristics of the constituents. Numerical results show that these models capture well the mechanical responses of finite-element simulations for three-dimensional periodic structures of neo-Hookean material with closed cells under large tension. In particular, the mesoscopic models predict the macroscopic stiffening of the structure when the stiffness of the cell-core increases. PMID:28484340

Microstructure-based hyperelastic models for closed-cell solids.

PubMed

Mihai, L Angela; Wyatt, Hayley; Goriely, Alain

2017-04-01

For cellular bodies involving large elastic deformations, mesoscopic continuum models that take into account the interplay between the geometry and the microstructural responses of the constituents are developed, analysed and compared with finite-element simulations of cellular structures with different architecture. For these models, constitutive restrictions for the physical plausibility of the material responses are established, and global descriptors such as nonlinear elastic and shear moduli and Poisson's ratio are obtained from the material characteristics of the constituents. Numerical results show that these models capture well the mechanical responses of finite-element simulations for three-dimensional periodic structures of neo-Hookean material with closed cells under large tension. In particular, the mesoscopic models predict the macroscopic stiffening of the structure when the stiffness of the cell-core increases.

Microstructure-based hyperelastic models for closed-cell solids

NASA Astrophysics Data System (ADS)

Mihai, L. Angela; Wyatt, Hayley; Goriely, Alain

2017-04-01

For cellular bodies involving large elastic deformations, mesoscopic continuum models that take into account the interplay between the geometry and the microstructural responses of the constituents are developed, analysed and compared with finite-element simulations of cellular structures with different architecture. For these models, constitutive restrictions for the physical plausibility of the material responses are established, and global descriptors such as nonlinear elastic and shear moduli and Poisson's ratio are obtained from the material characteristics of the constituents. Numerical results show that these models capture well the mechanical responses of finite-element simulations for three-dimensional periodic structures of neo-Hookean material with closed cells under large tension. In particular, the mesoscopic models predict the macroscopic stiffening of the structure when the stiffness of the cell-core increases.

Simulation analysis of an integrated model for dynamic cellular manufacturing system

NASA Astrophysics Data System (ADS)

Hao, Chunfeng; Luan, Shichao; Kong, Jili

2017-05-01

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

A hybrid multiscale Monte Carlo algorithm (HyMSMC) to cope with disparity in time scales and species populations in intracellular networks.

PubMed

Samant, Asawari; Ogunnaike, Babatunde A; Vlachos, Dionisios G

2007-05-24

The fundamental role that intrinsic stochasticity plays in cellular functions has been shown via numerous computational and experimental studies. In the face of such evidence, it is important that intracellular networks are simulated with stochastic algorithms that can capture molecular fluctuations. However, separation of time scales and disparity in species population, two common features of intracellular networks, make stochastic simulation of such networks computationally prohibitive. While recent work has addressed each of these challenges separately, a generic algorithm that can simultaneously tackle disparity in time scales and population scales in stochastic systems is currently lacking. In this paper, we propose the hybrid, multiscale Monte Carlo (HyMSMC) method that fills in this void. The proposed HyMSMC method blends stochastic singular perturbation concepts, to deal with potential stiffness, with a hybrid of exact and coarse-grained stochastic algorithms, to cope with separation in population sizes. In addition, we introduce the computational singular perturbation (CSP) method as a means of systematically partitioning fast and slow networks and computing relaxation times for convergence. We also propose a new criteria of convergence of fast networks to stochastic low-dimensional manifolds, which further accelerates the algorithm. We use several prototype and biological examples, including a gene expression model displaying bistability, to demonstrate the efficiency, accuracy and applicability of the HyMSMC method. Bistable models serve as stringent tests for the success of multiscale MC methods and illustrate limitations of some literature methods.

Dynamic route guidance strategy in a two-route pedestrian-vehicle mixed traffic flow system

NASA Astrophysics Data System (ADS)

Liu, Mianfang; Xiong, Shengwu; Li, Bixiang

2016-05-01

With the rapid development of transportation, traffic questions have become the major issue for social, economic and environmental aspects. Especially, during serious emergencies, it is very important to alleviate road traffic congestion and improve the efficiency of evacuation to reduce casualties, and addressing these problems has been a major task for the agencies responsible in recent decades. Advanced road guidance strategies have been developed for homogeneous traffic flows, or to reduce traffic congestion and enhance the road capacity in a symmetric two-route scenario. However, feedback strategies have rarely been considered for pedestrian-vehicle mixed traffic flows with variable velocities and sizes in an asymmetric multi-route traffic system, which is a common phenomenon in many developing countries. In this study, we propose a weighted road occupancy feedback strategy (WROFS) for pedestrian-vehicle mixed traffic flows, which considers the system equilibrium to ease traffic congestion. In order to more realistic simulating the behavior of mixed traffic objects, the paper adopted a refined and dynamic cellular automaton model (RDPV_CA model) as the update mechanism for pedestrian-vehicle mixed traffic flow. Moreover, a bounded rational threshold control was introduced into the feedback strategy to avoid some negative effect of delayed information and reduce. Based on comparisons with the two previously proposed strategies, the simulation results obtained in a pedestrian-vehicle traffic flow scenario demonstrated that the proposed strategy with a bounded rational threshold was more effective and system equilibrium, system stability were reached.

Discriminating cellular heterogeneity using microwell-based RNA cytometry

PubMed Central

Dimov, Ivan K.; Lu, Rong; Lee, Eric P.; Seita, Jun; Sahoo, Debashis; Park, Seung-min; Weissman, Irving L.; Lee, Luke P.

2014-01-01

Discriminating cellular heterogeneity is important for understanding cellular physiology. However, it is limited by the technical difficulties of single-cell measurements. Here, we develop a two-stage system to determine cellular heterogeneity. In the first stage, we perform multiplex single-cell RNA-cytometry in a microwell array containing over 60,000 reaction chambers. In the second stage, we use the RNA-cytometry data to determine cellular heterogeneity by providing a heterogeneity likelihood score. Moreover, we use Monte-Carlo simulation and RNA-cytometry data to calculate the minimum number of cells required for detecting heterogeneity. We applied this system to characterize the RNA distributions of aging related genes in a highly purified mouse hematopoietic stem cell population. We identified genes that reveal novel heterogeneity of these cells. We also show that changes in expression of genes such as Birc6 during aging can be attributed to the shift of relative portions of cells in the high-expressing subgroup versus low-expressing subgroup. PMID:24667995

Urban Ecological Security Simulation and Prediction Using an Improved Cellular Automata (CA) Approach-A Case Study for the City of Wuhan in China.

PubMed

Gao, Yuan; Zhang, Chuanrong; He, Qingsong; Liu, Yaolin

2017-06-15

Ecological security is an important research topic, especially urban ecological security. As highly populated eco-systems, cities always have more fragile ecological environments. However, most of the research on urban ecological security in literature has focused on evaluating current or past status of the ecological environment. Very little literature has carried out simulation or prediction of future ecological security. In addition, there is even less literature exploring the urban ecological environment at a fine scale. To fill-in the literature gap, in this study we simulated and predicted urban ecological security at a fine scale (district level) using an improved Cellular Automata (CA) approach. First we used the pressure-state-response (PSR) method based on grid-scale data to evaluate urban ecological security. Then, based on the evaluation results, we imported the geographically weighted regression (GWR) concept into the CA model to simulate and predict urban ecological security. We applied the improved CA approach in a case study-simulating and predicting urban ecological security for the city of Wuhan in Central China. By comparing the simulated ecological security values from 2010 using the improved CA model to the actual ecological security values of 2010, we got a relatively high value of the kappa coefficient, which indicates that this CA model can simulate or predict well future development of ecological security in Wuhan. Based on the prediction results for 2020, we made some policy recommendations for each district in Wuhan.

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

NASA Astrophysics Data System (ADS)

Czechowski, Zbigniew; Budek, Agnieszka; Białecki, Mariusz

2017-10-01

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

Manufacturing and Characterization of 18Ni Marage 300 Lattice Components by Selective Laser Melting

PubMed Central

Contuzzi, Nicola; Campanelli, Sabina L.; Casavola, Caterina; Lamberti, Luciano

2013-01-01

The spreading use of cellular structures brings the need to speed up manufacturing processes without deteriorating mechanical properties. By using Selective Laser Melting (SLM) to produce cellular structures, the designer has total freedom in defining part geometry and manufacturing is simplified. The paper investigates the suitability of Selective Laser Melting for manufacturing steel cellular lattice structures with characteristic dimensions in the micrometer range. Alternative lattice topologies including reinforcing bars in the vertical direction also are considered. The selected lattice structure topology is shown to be superior over other lattice structure designs considered in literature. Compression tests are carried out in order to evaluate mechanical strength of lattice strut specimens made via SLM. Compressive behavior of samples also is simulated by finite element analysis and numerical results are compared with experimental data in order to assess the constitutive behavior of the lattice structure designs considered in this study. Experimental data show that it is possible to build samples of relative density in the 0.2456–0.4367 range. Compressive strength changes almost linearly with respect to relative density, which in turns depends linearly on the number of vertical reinforces. Specific strength increases with cell and strut edge size. Numerical simulations confirm the plastic nature of the instability phenomena that leads the cellular structures to collapse under compression loading. PMID:28811445

A cellular automata approach for modeling surface water runoff

NASA Astrophysics Data System (ADS)

Jozefik, Zoltan; Nanu Frechen, Tobias; Hinz, Christoph; Schmidt, Heiko

2015-04-01

This abstract reports the development and application of a two-dimensional cellular automata based model, which couples the dynamics of overland flow, infiltration processes and surface evolution through sediment transport. The natural hill slopes are represented by their topographic elevation and spatially varying soil properties infiltration rates and surface roughness coefficients. This model allows modeling of Hortonian overland flow and infiltration during complex rainfall events. An advantage of the cellular automata approach over the kinematic wave equations is that wet/dry interfaces that often appear with rainfall overland flows can be accurately captured and are not a source of numerical instabilities. An adaptive explicit time stepping scheme allows for rainfall events to be adequately resolved in time, while large time steps are taken during dry periods to provide for simulation run time efficiency. The time step is constrained by the CFL condition and mass conservation considerations. The spatial discretization is shown to be first-order accurate. For validation purposes, hydrographs for non-infiltrating and infiltrating plates are compared to the kinematic wave analytic solutions and data taken from literature [1,2]. Results show that our cellular automata model quantitatively accurately reproduces hydrograph patterns. However, recent works have showed that even through the hydrograph is satisfyingly reproduced, the flow field within the plot might be inaccurate [3]. For a more stringent validation, we compare steady state velocity, water flux, and water depth fields to rainfall simulation experiments conducted in Thies, Senegal [3]. Comparisons show that our model is able to accurately capture these flow properties. Currently, a sediment transport and deposition module is being implemented and tested. [1] M. Rousseau, O. Cerdan, O. Delestre, F. Dupros, F. James, S. Cordier. Overland flow modeling with the Shallow Water Equation using a well balanced numerical scheme: Adding efficiency or sum more complexity?. 2012. [2] Fritz R. Fiedler, J. A. Ramirez. A numerical method for simulating discontinuous shallow flow over an infiltrating surface. In. J. Numer. Mech. Fluids 200: 32: 219-240. [3] C. Mügler, O. Planchon, J. Patin, S. Weill, N. Silvera, P. Richard, E. Mouche. Comparison of Roughness models to simulate overland flow and tracer transport experiments under simulated rainfall at plot scale. Journal of Hydrology. 402 (2011) 25-40.

Integrating simulation training into the nursing curriculum.

PubMed

Wilford, Amanda; Doyle, Thomas J

The use of simulation is gaining momentum in nurse education across the UK. The Nursing and Midwifery Council is currently investigating the use of simulation in pre-registration nursing. This article gives a brief history of simulation, discusses competence issues and why simulation is best placed to teach nurses in today's health service. An innovative approach to implementing simulation into the nursing curriculum is introduced.

Psychosocial vital signs: using simulation to introduce a new concept.

PubMed

Spade, Charlotte M

2008-01-01

Psychosocial vital signs (PVS) is a tool used for defining and measuring essential psychosocial variables of health. Because nurse-patient interaction is basic to PVS, simulation is the methodology used for introducing this new concept to students. When learning PVS as a fundamental nursing skill, students' thinking is informed and guided toward a holistic view of their patients. The author discusses components of PVS and the curriculum used for teaching students how to use PVS.

Uncapped mRNA introduced into tobacco protoplasts can be imported into the nucleus and is trapped by leptomycin B.

PubMed

Stuger, Rogier; Forreiter, Christoph

2004-08-01

The mechanism of nuclear export of RNAs in yeast and animal cells is rapidly being uncovered, but RNA export in plants has received little attention. We introduced capped and uncapped fluorescent mRNAs into tobacco (Nicotiana plumbaginifolia) protoplasts and studied their cellular localization. Following insertion, capped transcripts were found in the cytoplasm, while uncapped messengers transiently appeared in the nucleus in about one-quarter to one-third of the cells. These mRNAs were trapped by the nuclear export-inhibiting drug leptomycin B, pointing to an export mechanism in plants similar to Rev-NES-mediated RNP export in other organisms.

A Study on Cognitive Radio Coexisting with Cellular Systems

NASA Astrophysics Data System (ADS)

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

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

Performance Comparison of Orthogonal and Quasi-orthogonal Codes in Quasi-Synchronous Cellular CDMA Communication

NASA Astrophysics Data System (ADS)

Jos, Sujit; Kumar, Preetam; Chakrabarti, Saswat

Orthogonal and quasi-orthogonal codes are integral part of any DS-CDMA based cellular systems. Orthogonal codes are ideal for use in perfectly synchronous scenario like downlink cellular communication. Quasi-orthogonal codes are preferred over orthogonal codes in the uplink communication where perfect synchronization cannot be achieved. In this paper, we attempt to compare orthogonal and quasi-orthogonal codes in presence of timing synchronization error. This will give insight into the synchronization demands in DS-CDMA systems employing the two classes of sequences. The synchronization error considered is smaller than chip duration. Monte-Carlo simulations have been carried out to verify the analytical and numerical results.

Modeling 2D and 3D diffusion.

PubMed

Saxton, Michael J

2007-01-01

Modeling obstructed diffusion is essential to the understanding of diffusion-mediated processes in the crowded cellular environment. Simple Monte Carlo techniques for modeling obstructed random walks are explained and related to Brownian dynamics and more complicated Monte Carlo methods. Random number generation is reviewed in the context of random walk simulations. Programming techniques and event-driven algorithms are discussed as ways to speed simulations.

Impact of Resolution on Simulation of Closed Mesoscale Cellular Convection Identified by Dynamically Guided Watershed Segmentation

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

Martini, Matus N.; Gustafson, William I.; Yang, Qing

2014-11-18

Organized mesoscale cellular convection (MCC) is a common feature of marine stratocumulus that forms in response to a balance between mesoscale dynamics and smaller scale processes such as cloud radiative cooling and microphysics. We use the Weather Research and Forecasting model with chemistry (WRF-Chem) and fully coupled cloud-aerosol interactions to simulate marine low clouds during the VOCALS-REx campaign over the southeast Pacific. A suite of experiments with 3- and 9-km grid spacing indicates resolution-dependent behavior. The simulations with finer grid spacing have smaller liquid water paths and cloud fractions, while cloud tops are higher. The observed diurnal cycle is reasonablymore » well simulated. To isolate organized MCC characteristics we develop a new automated method, which uses a variation of the watershed segmentation technique that combines the detection of cloud boundaries with a test for coincident vertical velocity characteristics. This ensures that the detected cloud fields are dynamically consistent for closed MCC, the most common MCC type over the VOCALS-REx region. We demonstrate that the 3-km simulation is able to reproduce the scaling between horizontal cell size and boundary layer height seen in satellite observations. However, the 9-km simulation is unable to resolve smaller circulations corresponding to shallower boundary layers, instead producing invariant MCC horizontal scale for all simulated boundary layers depths. The results imply that climate models with grid spacing of roughly 3 km or smaller may be needed to properly simulate the MCC structure in the marine stratocumulus regions.« less

Numerical simulation of biofilm growth in flow channels using a cellular automaton approach coupled with a macro flow computation.

PubMed

Yamamoto, Takehiro; Ueda, Shuya

2013-01-01

Biofilm is a slime-like complex aggregate of microorganisms and their products, extracellular polymer substances, that grows on a solid surface. The growth phenomenon of biofilm is relevant to the corrosion and clogging of water pipes, the chemical processes in a bioreactor, and bioremediation. In these phenomena, the behavior of the biofilm under flow has an important role. Therefore, controlling the biofilm behavior in each process is important. To provide a computational tool for analyzing biofilm growth, the present study proposes a computational model for the simulation of biofilm growth in flows. This model accounts for the growth, decay, detachment and adhesion of biofilms. The proposed model couples the computation of the surrounding fluid flow, using the finite volume method, with the simulation of biofilm growth, using the cellular automaton approach, a relatively low-computational-cost method. Furthermore, a stochastic approach for considering the adhesion process is proposed. Numerical simulations for the biofilm growth on a planar wall and that in an L-shaped rectangular channel were carried out. A variety of biofilm structures were observed depending on the strength of the flow. Moreover, the importance of the detachment and adhesion processes was confirmed.

Simulation of Atrial Fibrosis Using Coupled Myocyte-Fibroblast Cellular and Human Atrial Models

PubMed Central

Gao, Yuan

2017-01-01

Atrial fibrosis is characterized by expansion of extracellular matrix and increase in the number of fibroblasts which has been associated with the development and maintenance of atrial arrhythmias. However, the mechanisms how the fibrosis contributes to atrial arrhythmia remain incompletely understood. In this study, we used a proposed fibroblast model coupled with the human atrial myocyte to investigate the effects of fibrosis on atrial excitability and repolarization at both cellular and macroscopic levels. The 12-lead electrocardiogram (ECG) was also simulated to explore the index of clinical diagnosis for fibrosis. The simulation results showed that the fibrosis can modify action potential morphology of human atrial myocyte, slow down wave propagation, and have rate adaptation, thus causing the atrial electrical heterogeneity. The fibrosis alone was sufficient to cause arrhythmia, induce reentry wave, and result in low amplitude and wide P waves at normal heart rate and significant prolonged and inverse P waves at high heart rate. All these symptoms aggravated when the level of fibrosis increased. Our simulations demonstrated that fibrosis is the substrate of atrial arrhythmia and thereby may be a potential target in the treatment of atrial arrhythmias. PMID:29441121

Direct numerical simulation of cellular-scale blood flow in microvascular networks

NASA Astrophysics Data System (ADS)

Balogh, Peter; Bagchi, Prosenjit

2017-11-01

A direct numerical simulation method is developed to study cellular-scale blood flow in physiologically realistic microvascular networks that are constructed in silico following published in vivo images and data, and are comprised of bifurcating, merging, and winding vessels. The model resolves large deformation of individual red blood cells (RBC) flowing in such complex networks. The vascular walls and deformable interfaces of the RBCs are modeled using the immersed-boundary methods. Time-averaged hemodynamic quantities obtained from the simulations agree quite well with published in vivo data. Our simulations reveal that in several vessels the flow rates and pressure drops could be negatively correlated. The flow resistance and hematocrit are also found to be negatively correlated in some vessels. These observations suggest a deviation from the classical Poiseuille's law in such vessels. The cells are observed to frequently jam at vascular bifurcations resulting in reductions in hematocrit and flow rate in the daughter and mother vessels. We find that RBC jamming results in several orders of magnitude increase in hemodynamic resistance, and thus provides an additional mechanism of increased in vivo blood viscosity as compared to that determined in vitro. Funded by NSF CBET 1604308.

The Simultaneous Production Model; A Model for the Construction, Testing, Implementation and Revision of Educational Computer Simulation Environments.

ERIC Educational Resources Information Center

Zillesen, Pieter G. van Schaick

This paper introduces a hardware and software independent model for producing educational computer simulation environments. The model, which is based on the results of 32 studies of educational computer simulations program production, implies that educational computer simulation environments are specified, constructed, tested, implemented, and…

Computer Simulation of a Hardwood Processing Plant

Treesearch

D. Earl Kline; Philip A. Araman

1990-01-01

The overall purpose of this paper is to introduce computer simulation as a decision support tool that can be used to provide managers with timely information. A simulation/animation modeling procedure is demonstrated for wood products manufacuring systems. Simulation modeling techniques are used to assist in identifying and solving problems. Animation is used for...

Simulation As a Tool in Education Research and Development. A Technical Paper. EdTalk.

ERIC Educational Resources Information Center

Hood, Paul

This document introduces simulation as a field of endeavor that has great potential for education research, development, and training. Simulation allows education developers to explore, develop, and test new educational programs and practices before communities, educators, and students are asked to participate in them. Simulation technologies…

Snowplow simulator training evaluation : potential fuel & drivetrain maintenance cost reduction

DOT National Transportation Integrated Search

2007-12-01

The Arizona Department of Transportation (ADOT) introduced simulator-based training in 2004, when maintenance crews in five rural districts received a third-party snowplow safety topics course on the L-3 TransSim VS III simulator. In 2005, a simulato...

Modeling Land Use/Cover Changes in an African Rural Landscape

NASA Astrophysics Data System (ADS)

Kamusoko, C.; Aniya, M.

2006-12-01

Land use/cover changes are analyzed in the Bindura district of Zimbabwe, Africa through the integration of data from a time series of Landsat imagery (1973, 1989 and 2000), a household survey and GIS coverages. We employed a hybrid supervised/unsupervised classification approach to generate land use/cover maps from which landscape metrics were calculated. Population and other household variables were derived from a sample of surveyed villages, while road accessibility and slope were obtained from topographic maps and digital elevation model, respectively. Markov-cellular automata modeling approach that incorporates Markov chain analysis, cellular automata and multi-criteria evaluation (MCE) / multi-objective allocation (MOLA) procedures was used to simulate land use/cover changes. A GIS-based MCE technique computed transition potential maps, whereas transition areas were derived from the 1973-2000 land use/cover maps using the Markov chain analysis. A 5 x 5 cellular automata filter was used to develop a spatially explicit contiguity- weighting factor to change the cells based on its previous state and those of its neighbors, while MOLA resolved land use/cover class allocation conflicts. The kappa index of agreement was used for model validation. Observed trends in land use/cover changes indicate that deforestation and the encroachment of cultivation in woodland areas is a continuous trend in the study area. This suggests that economic activities driven by agricultural expansion were the main causes of landscape fragmentation, leading to landscape degradation. Rigorous calibration of transition potential maps done by a MCE algorithm and Markovian transition probabilities produced accurate inputs for the simulation of land use/cover changes. Overall standard kappa index of agreement ranged from 0.73 to 0.83, which is sufficient for simulating land use/cover changes in the study area. Land use/cover simulations under the 1989 and 2000 scenario indicated further landscape degradation in the rural areas of the Bindura district. Keywords: Zimbabwe, land use/cover changes, landscape fragmentation, GIS, land use/cover change modeling, multi-criteria evaluation/multi-objective allocation procedures, Markov-cellular automata

Simulation of Escherichia coli Dynamics in Biofilms and Submerged Colonies with an Individual-Based Model Including Metabolic Network Information.

PubMed

Tack, Ignace L M M; Nimmegeers, Philippe; Akkermans, Simen; Hashem, Ihab; Van Impe, Jan F M

2017-01-01

Clustered microbial communities are omnipresent in the food industry, e.g., as colonies of microbial pathogens in/on food media or as biofilms on food processing surfaces. These clustered communities are often characterized by metabolic differentiation among their constituting cells as a result of heterogeneous environmental conditions in the cellular surroundings. This paper focuses on the role of metabolic differentiation due to oxygen gradients in the development of Escherichia coli cell communities, whereby low local oxygen concentrations lead to cellular secretion of weak acid products. For this reason, a metabolic model has been developed for the facultative anaerobe E. coli covering the range of aerobic, microaerobic, and anaerobic environmental conditions. This metabolic model is expressed as a multiparametric programming problem, in which the influence of low extracellular pH values and the presence of undissociated acid cell products in the environment has been taken into account. Furthermore, the developed metabolic model is incorporated in MICRODIMS, an in-house developed individual-based modeling framework to simulate microbial colony and biofilm dynamics. Two case studies have been elaborated using the MICRODIMS simulator: (i) biofilm growth on a substratum surface and (ii) submerged colony growth in a semi-solid mixed food product. In the first case study, the acidification of the biofilm environment and the emergence of typical biofilm morphologies have been observed, such as the mushroom-shaped structure of mature biofilms and the formation of cellular chains at the exterior surface of the biofilm. The simulations show that these morphological phenomena are respectively dependent on the initial affinity of pioneer cells for the substratum surface and the cell detachment process at the outer surface of the biofilm. In the second case study, a no-growth zone emerges in the colony center due to a local decline of the environmental pH. As a result, cellular growth in the submerged colony is limited to the colony periphery, implying a linear increase of the colony radius over time. MICRODIMS has been successfully used to reproduce complex dynamics of clustered microbial communities.

Multiscale simulation of molecular processes in cellular environments.

PubMed

Chiricotto, Mara; Sterpone, Fabio; Derreumaux, Philippe; Melchionna, Simone

2016-11-13

We describe the recent advances in studying biological systems via multiscale simulations. Our scheme is based on a coarse-grained representation of the macromolecules and a mesoscopic description of the solvent. The dual technique handles particles, the aqueous solvent and their mutual exchange of forces resulting in a stable and accurate methodology allowing biosystems of unprecedented size to be simulated.This article is part of the themed issue 'Multiscale modelling at the physics-chemistry-biology interface'. © 2016 The Author(s).

Effect of simulated microgravity on oxidation-sensitive gene expression in PC12 cells

NASA Astrophysics Data System (ADS)

Kwon, Ohwon; Sartor, Maureen; Tomlinson, Craig R.; Millard, Ronald W.; Olah, Mark E.; Sankovic, John M.; Banerjee, Rupak K.

2006-01-01

Oxygen utilization by and oxygen dependence of cellular processes may be different in biological systems that are exposed to microgravity (micro-g). A baseline in which cellular changes in oxygen sensitive molecular processes occur during micro-g conditions would be important to pursue this question. The objective of this research is to analyze oxidation-sensitive gene expression in a model cell line [rat pheochromocytoma (PC12)] under simulated micro-g conditions. The PC12 cell line is well characterized in its response to oxygen, and is widely recognized as a sensitive model for studying the responses of oxygen-sensitive molecular and cellular processes. This study uses the rotating wall vessel bioreactor (RWV) designed at NASA to simulate micro-g. Gene expression in PC12 cells in response to micro-g was analyzed by DNA microarray technology. The microarray analysis of PC12 cells cultured for 4 days under simulated micro-g under standardized oxygen environment conditions revealed more than 100 genes whose expression levels were changed at least twofold (up-regulation of 65 genes and down-regulation of 39 genes) compared with those from cells in the unit gravity (unit-g) control. This study observed that genes involved in the oxidoreductase activity category were most significantly differentially expressed under micro-g conditions. Also, known oxidation-sensitive transcription factors such as hypoxia-inducible factor-2α, c-myc, and the peroxisome proliferator-activated receptor-γ were changed significantly. Our initial results from the gene expression microarray studies may provide a context in which to evaluate the effect of varying oxygen environments on the background of differential gene regulation of biological processes under variable gravity conditions.

Effect of simulated microgravity on oxidation-sensitive gene expression in PC12 cells

PubMed Central

Kwon, Ohwon; Sartor, Maureen; Tomlinson, Craig R.; Millard, Ronald W.; Olah, Mark E.; Sankovic, John M.; Banerjee, Rupak K.

2008-01-01

Oxygen utilization by and oxygen dependence of cellular processes may be different in biological systems that are exposed to microgravity (micro-g). A baseline in which cellular changes in oxygen sensitive molecular processes occur during micro-g conditions would be important to pursue this question. The objective of this research is to analyze oxidation-sensitive gene expression in a model cell line [rat pheochromocytoma (PC12)] under simulated micro-g conditions. The PC12 cell line is well characterized in its response to oxygen, and is widely recognized as a sensitive model for studying the responses of oxygen-sensitive molecular and cellular processes. This study uses the rotating wall vessel bioreactor (RWV) designed at NASA to simulate micro-g. Gene expression in PC12 cells in response to micro-g was analyzed by DNA microarray technology. The microarray analysis of PC12 cells cultured for 4 days under simulated micro-g under standardized oxygen environment conditions revealed more than 100 genes whose expression levels were changed at least twofold (up-regulation of 65 genes and down-regulation of 39 genes) compared with those from cells in the unit gravity (unit-g) control. This study observed that genes involved in the oxidoreductase activity category were most significantly differentially expressed under micro-g conditions. Also, known oxidation-sensitive transcription factors such as hypoxia-inducible factor-2α, c-myc, and the peroxisome proliferator-activated receptor-γ were changed significantly. Our initial results from the gene expression microarray studies may provide a context in which to evaluate the effect of varying oxygen environments on the background of differential gene regulation of biological processes under variable gravity conditions. PMID:19081771

Direct Numerical Simulation of Cellular-Scale Blood Flow in 3D Microvascular Networks.

PubMed

Balogh, Peter; Bagchi, Prosenjit

2017-12-19

We present, to our knowledge, the first direct numerical simulation of 3D cellular-scale blood flow in physiologically realistic microvascular networks. The vascular networks are designed following in vivo images and data, and are comprised of bifurcating, merging, and winding vessels. Our model resolves the large deformation and dynamics of each individual red blood cell flowing through the networks with high fidelity, while simultaneously retaining the highly complex geometric details of the vascular architecture. To our knowledge, our simulations predict several novel and unexpected phenomena. We show that heterogeneity in hemodynamic quantities, which is a hallmark of microvascular blood flow, appears both in space and time, and that the temporal heterogeneity is more severe than its spatial counterpart. The cells are observed to frequently jam at vascular bifurcations resulting in reductions in hematocrit and flow rate in the daughter and mother vessels. We find that red blood cell jamming at vascular bifurcations results in several orders-of-magnitude increase in hemodynamic resistance, and thus provides an additional mechanism of increased in vivo blood viscosity as compared to that determined in vitro. A striking result from our simulations is negative pressure-flow correlations observed in several vessels, implying a significant deviation from Poiseuille's law. Furthermore, negative correlations between vascular resistance and hematocrit are observed in various vessels, also defying a major principle of particulate suspension flow. To our knowledge, these novel findings are absent in blood flow in straight tubes, and they underscore the importance of considering realistic physiological geometry and resolved cellular interactions in modeling microvascular hemodynamics. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Predicting the impact of lava flows at Mount Etna by an innovative method based on Cellular Automata: Applications regarding land-use and civil defence planning

NASA Astrophysics Data System (ADS)

Crisci, G. M.; Avolio, M. V.; D'Ambrosio, D.; di Gregorio, S.; Lupiano, G. V.; Rongo, R.; Spataro, W.; Benhcke, B.; Neri, M.

2009-04-01

Forecasting the time, character and impact of future eruptions is difficult at volcanoes with complex eruptive behaviour, such as Mount Etna, where eruptions occur from the summit and on the flanks, affecting areas distant from each other. Modern efforts for hazard evaluation and contingency planning in volcanic areas draw heavily on hazard maps and numerical simulations. The computational model here applied belongs to the SCIARA family of lava flow simulation models. In the specific case this is the SCIARA-fv release, which is considered to give the most accurate and efficient performance, given the extent (567 km2) of the study area and the great number of simulations to be carried out. The model is based on the Cellular Automata computational paradigm and, specifically, on the Macroscopic Cellular Automata approach for the modelling of spatially extended dynamic systems2. This work addresses the problem of compiling high-detailed susceptibility maps with an elaborate approach in the numerical simulation of Etnean lava flows, based on the results of 39,300 simulations of flows erupted from a grid of 393 hypothetical vents in the eastern sector of Etna. This sector was chosen because it is densely populated and frequently affected by flank eruptions. Besides the definition of general susceptibility maps, the availability of a large number of lava flows of different eruption types, magnitudes and locations simulated for this study allows the instantaneous extraction of various scenarios on demand. For instance, in a Civil Defence oriented application, it is possible to identify all source areas of lava flows capable of affecting a given area of interest, such as a town or a major infrastructure. Indeed, this application is rapidly accomplished by querying the simulation database, by selecting the lava flows that affect the area of interest and by circumscribing their sources. Eventually, a specific category of simulation is dedicated to the assessment of protective measures, such as earth barriers, for mitigating lava invasion susceptibility in given areas. For the case if the town of Nicolosi, results show that the barrier would be necessary to effectively protect the town centre. The methodology here described can therefore represent a substantial advance in the field of lava flows impact prediction and can also have immediate, far-reaching implications both in land-use and civil defence planning.

A framework for WRF to WRF-IBM grid nesting to enable multiscale simulations

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

Wiersema, David John; Lundquist, Katherine A.; Chow, Fotini Katapodes

With advances in computational power, mesoscale models, such as the Weather Research and Forecasting (WRF) model, are often pushed to higher resolutions. As the model’s horizontal resolution is refined, the maximum resolved terrain slope will increase. Because WRF uses a terrain-following coordinate, this increase in resolved terrain slopes introduces additional grid skewness. At high resolutions and over complex terrain, this grid skewness can introduce large numerical errors that require methods, such as the immersed boundary method, to keep the model accurate and stable. Our implementation of the immersed boundary method in the WRF model, WRF-IBM, has proven effective at microscalemore » simulations over complex terrain. WRF-IBM uses a non-conforming grid that extends beneath the model’s terrain. Boundary conditions at the immersed boundary, the terrain, are enforced by introducing a body force term to the governing equations at points directly beneath the immersed boundary. Nesting between a WRF parent grid and a WRF-IBM child grid requires a new framework for initialization and forcing of the child WRF-IBM grid. This framework will enable concurrent multi-scale simulations within the WRF model, improving the accuracy of high-resolution simulations and enabling simulations across a wide range of scales.« less

Modeling the Potential Spread of the Recently Identified Non-Native Panther Grouper (Chromileptes altivelis) in the Atlantic Using a Cellular Automaton Approach

PubMed Central

Johnston, Matthew W.; Purkis, Sam J.

2013-01-01

The Indo-pacific panther grouper (Chromileptes altiveli) is a predatory fish species and popular imported aquarium fish in the United States which has been recently documented residing in western Atlantic waters. To date, the most successful marine invasive species in the Atlantic is the lionfish (Pterois volitans/miles), which, as for the panther grouper, is assumed to have been introduced to the wild through aquarium releases. However, unlike lionfish, the panther grouper is not yet thought to have an established breeding population in the Atlantic. Using a proven modeling technique developed to track the lionfish invasion, presented is the first known estimation of the potential spread of panther grouper in the Atlantic. The employed cellular automaton-based computer model examines the life history of the subject species including fecundity, mortality, and reproductive potential and combines this with habitat preferences and physical oceanic parameters to forecast the distribution and periodicity of spread of this potential new invasive species. Simulations were examined for origination points within one degree of capture locations of panther grouper from the United States Geological Survey Nonindigenous Aquatic Species Database to eliminate introduction location bias, and two detailed case studies were scrutinized. The model indicates three primary locations where settlement is likely given the inputs and limits of the model; Jupiter Florida/Vero Beach, the Cape Hatteras Tropical Limit/Myrtle Beach South Carolina, and Florida Keys/Ten Thousand Islands locations. Of these locations, Jupiter Florida/Vero Beach has the highest settlement rate in the model and is indicated as the area in which the panther grouper is most likely to become established. This insight is valuable if attempts are to be made to halt this potential marine invasive species. PMID:24009726

Modeling the potential spread of the recently identified non-native panther grouper (Chromileptes altivelis) in the Atlantic using a cellular automaton approach.

PubMed

Johnston, Matthew W; Purkis, Sam J

2013-01-01

The Indo-pacific panther grouper (Chromileptes altiveli) is a predatory fish species and popular imported aquarium fish in the United States which has been recently documented residing in western Atlantic waters. To date, the most successful marine invasive species in the Atlantic is the lionfish (Pterois volitans/miles), which, as for the panther grouper, is assumed to have been introduced to the wild through aquarium releases. However, unlike lionfish, the panther grouper is not yet thought to have an established breeding population in the Atlantic. Using a proven modeling technique developed to track the lionfish invasion, presented is the first known estimation of the potential spread of panther grouper in the Atlantic. The employed cellular automaton-based computer model examines the life history of the subject species including fecundity, mortality, and reproductive potential and combines this with habitat preferences and physical oceanic parameters to forecast the distribution and periodicity of spread of this potential new invasive species. Simulations were examined for origination points within one degree of capture locations of panther grouper from the United States Geological Survey Nonindigenous Aquatic Species Database to eliminate introduction location bias, and two detailed case studies were scrutinized. The model indicates three primary locations where settlement is likely given the inputs and limits of the model; Jupiter Florida/Vero Beach, the Cape Hatteras Tropical Limit/Myrtle Beach South Carolina, and Florida Keys/Ten Thousand Islands locations. Of these locations, Jupiter Florida/Vero Beach has the highest settlement rate in the model and is indicated as the area in which the panther grouper is most likely to become established. This insight is valuable if attempts are to be made to halt this potential marine invasive species.

Mathematical modeling and computational prediction of cancer drug resistance.

PubMed

Sun, Xiaoqiang; Hu, Bin

2017-06-23

Diverse forms of resistance to anticancer drugs can lead to the failure of chemotherapy. Drug resistance is one of the most intractable issues for successfully treating cancer in current clinical practice. Effective clinical approaches that could counter drug resistance by restoring the sensitivity of tumors to the targeted agents are urgently needed. As numerous experimental results on resistance mechanisms have been obtained and a mass of high-throughput data has been accumulated, mathematical modeling and computational predictions using systematic and quantitative approaches have become increasingly important, as they can potentially provide deeper insights into resistance mechanisms, generate novel hypotheses or suggest promising treatment strategies for future testing. In this review, we first briefly summarize the current progress of experimentally revealed resistance mechanisms of targeted therapy, including genetic mechanisms, epigenetic mechanisms, posttranslational mechanisms, cellular mechanisms, microenvironmental mechanisms and pharmacokinetic mechanisms. Subsequently, we list several currently available databases and Web-based tools related to drug sensitivity and resistance. Then, we focus primarily on introducing some state-of-the-art computational methods used in drug resistance studies, including mechanism-based mathematical modeling approaches (e.g. molecular dynamics simulation, kinetic model of molecular networks, ordinary differential equation model of cellular dynamics, stochastic model, partial differential equation model, agent-based model, pharmacokinetic-pharmacodynamic model, etc.) and data-driven prediction methods (e.g. omics data-based conventional screening approach for node biomarkers, static network approach for edge biomarkers and module biomarkers, dynamic network approach for dynamic network biomarkers and dynamic module network biomarkers, etc.). Finally, we discuss several further questions and future directions for the use of computational methods for studying drug resistance, including inferring drug-induced signaling networks, multiscale modeling, drug combinations and precision medicine. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

The usability of WeChat as a mobile and interactive medium in student-centered medical teaching.

PubMed

Wang, Juan; Gao, Furong; Li, Jiao; Zhang, Jieping; Li, Siguang; Xu, Guo-Tong; Xu, Lei; Chen, Jianjun; Lu, Lixia

2017-09-01

Biochemistry and cellular biology courses for medical students at Tongji University include the assessment that provides students with feedback to enhance their learning, which is a type of formative assessment. However, frequent instant feedback and guidance for students is often absent or inconsistently included in the teaching process. WeChat, the most popular Chinese social media, was introduced in biochemistry and cellular biology course. A WeChat official account (OA) was set up as an instant interactive platform. Over a period of two semesters, OA sent 73 push notifications. The components included course notices, preclass thought questions, after-class study materials, answer questions and feedback, simulation exercises, teacher-student interaction, and research progress relevant to the course. WeChat OA served as an active-learning teaching tool, provided more frequent feedback and guidance to students, and facilitated better student-centered communication in the teaching process. Using the WeChat OA in medical teaching emphasized interactive, interoperable, effective, engaging, adaptable, and more participatory teaching styles. As a new platform, WeChat OA was free, Internet-reliant, and easily managed. Using this new medium as a communication tool accelerated further advancement of instant feedback and improvement in teaching activities. Notifications and interactive feedback via the mobile social medium WeChat OA anytime and anywhere facilitated a student-centered teaching mode. Use of WeChat OA significantly increased the proportion of students interactively participating and resulted in a high degree of student satisfaction. © 2017 by The International Union of Biochemistry and Molecular Biology, 45(5):421-425, 2017. © 2017 The International Union of Biochemistry and Molecular Biology.

Simulating complex intracellular processes using object-oriented computational modelling.

PubMed

Johnson, Colin G; Goldman, Jacki P; Gullick, William J

2004-11-01

The aim of this paper is to give an overview of computer modelling and simulation in cellular biology, in particular as applied to complex biochemical processes within the cell. This is illustrated by the use of the techniques of object-oriented modelling, where the computer is used to construct abstractions of objects in the domain being modelled, and these objects then interact within the computer to simulate the system and allow emergent properties to be observed. The paper also discusses the role of computer simulation in understanding complexity in biological systems, and the kinds of information which can be obtained about biology via simulation.

Computational study of noise in a large signal transduction network.

PubMed

Intosalmi, Jukka; Manninen, Tiina; Ruohonen, Keijo; Linne, Marja-Leena

2011-06-21

Biochemical systems are inherently noisy due to the discrete reaction events that occur in a random manner. Although noise is often perceived as a disturbing factor, the system might actually benefit from it. In order to understand the role of noise better, its quality must be studied in a quantitative manner. Computational analysis and modeling play an essential role in this demanding endeavor. We implemented a large nonlinear signal transduction network combining protein kinase C, mitogen-activated protein kinase, phospholipase A2, and β isoform of phospholipase C networks. We simulated the network in 300 different cellular volumes using the exact Gillespie stochastic simulation algorithm and analyzed the results in both the time and frequency domain. In order to perform simulations in a reasonable time, we used modern parallel computing techniques. The analysis revealed that time and frequency domain characteristics depend on the system volume. The simulation results also indicated that there are several kinds of noise processes in the network, all of them representing different kinds of low-frequency fluctuations. In the simulations, the power of noise decreased on all frequencies when the system volume was increased. We concluded that basic frequency domain techniques can be applied to the analysis of simulation results produced by the Gillespie stochastic simulation algorithm. This approach is suited not only to the study of fluctuations but also to the study of pure noise processes. Noise seems to have an important role in biochemical systems and its properties can be numerically studied by simulating the reacting system in different cellular volumes. Parallel computing techniques make it possible to run massive simulations in hundreds of volumes and, as a result, accurate statistics can be obtained from computational studies. © 2011 Intosalmi et al; licensee BioMed Central Ltd.

FAST TRACK COMMUNICATION Solving the ultradiscrete KdV equation

NASA Astrophysics Data System (ADS)

Willox, Ralph; Nakata, Yoichi; Satsuma, Junkichi; Ramani, Alfred; Grammaticos, Basile

2010-12-01

We show that a generalized cellular automaton, exhibiting solitonic interactions, can be explicitly solved by means of techniques first introduced in the context of the scattering problem for the KdV equation. We apply this method to calculate the phase-shifts caused by interactions between the solitonic and non-solitonic parts into which arbitrary initial states separate in time.

Multicellular regulation of entropy, spatial order, and information

NASA Astrophysics Data System (ADS)

Youk, Hyun

Many multicellular systems such as tissues and microbial biofilms consist of cells that secrete and sense signalling molecules. Understanding how collective behaviours of secrete-and-sense cells is an important challenge. We combined experimental and theoretical approaches to understand multicellular coordination of gene expression and spatial pattern formation among secrete-and-sense cells. We engineered secrete-and-sense yeast cells to show that cells can collectively and permanently remember a past event by reminding each other with their secreted signalling molecule. If one cell ``forgets'' then another cell can remind it. Cell-cell communication ensures a long-term (permanent) memory by overcoming common limitations of intracellular memory. We also established a new theoretical framework inspired by statistical mechanics to understand how fields of secrete-and-sense cells form spatial patterns. We introduce new metrics - cellular entropy, cellular Hamiltonian, and spatial order index - for dynamics of cellular automata that form spatial patterns. Our theory predicts how fast any spatial patterns form, how ordered they are, and establishes cellular Hamiltonian that, like energy for non-living systems, monotonically decreases towards a minimum over time. ERC Starting Grant (MultiCellSysBio), NWO VIDI, NWO NanoFront.

Engineering microbial phenotypes through rewiring of genetic networks

PubMed Central

Rodrigues, Rui T.L.; Lee, Sangjin; Haines, Matthew

2017-01-01

Abstract The ability to program cellular behaviour is a major goal of synthetic biology, with applications in health, agriculture and chemicals production. Despite efforts to build ‘orthogonal’ systems, interactions between engineered genetic circuits and the endogenous regulatory network of a host cell can have a significant impact on desired functionality. We have developed a strategy to rewire the endogenous cellular regulatory network of yeast to enhance compatibility with synthetic protein and metabolite production. We found that introducing novel connections in the cellular regulatory network enabled us to increase the production of heterologous proteins and metabolites. This strategy is demonstrated in yeast strains that show significantly enhanced heterologous protein expression and higher titers of terpenoid production. Specifically, we found that the addition of transcriptional regulation between free radical induced signalling and nitrogen regulation provided robust improvement of protein production. Assessment of rewired networks revealed the importance of key topological features such as high betweenness centrality. The generation of rewired transcriptional networks, selection for specific phenotypes, and analysis of resulting library members is a powerful tool for engineering cellular behavior and may enable improved integration of heterologous protein and metabolite pathways. PMID:28369627

Mathematics, thermodynamics, and modeling to address ten common misconceptions about protein structure, folding, and stability.

PubMed

Robic, Srebrenka

2010-01-01

To fully understand the roles proteins play in cellular processes, students need to grasp complex ideas about protein structure, folding, and stability. Our current understanding of these topics is based on mathematical models and experimental data. However, protein structure, folding, and stability are often introduced as descriptive, qualitative phenomena in undergraduate classes. In the process of learning about these topics, students often form incorrect ideas. For example, by learning about protein folding in the context of protein synthesis, students may come to an incorrect conclusion that once synthesized on the ribosome, a protein spends its entire cellular life time in its fully folded native confirmation. This is clearly not true; proteins are dynamic structures that undergo both local fluctuations and global unfolding events. To prevent and address such misconceptions, basic concepts of protein science can be introduced in the context of simple mathematical models and hands-on explorations of publicly available data sets. Ten common misconceptions about proteins are presented, along with suggestions for using equations, models, sequence, structure, and thermodynamic data to help students gain a deeper understanding of basic concepts relating to protein structure, folding, and stability.

Estimating cellular parameters through optimization procedures: elementary principles and applications.

PubMed

Kimura, Akatsuki; Celani, Antonio; Nagao, Hiromichi; Stasevich, Timothy; Nakamura, Kazuyuki

2015-01-01

Construction of quantitative models is a primary goal of quantitative biology, which aims to understand cellular and organismal phenomena in a quantitative manner. In this article, we introduce optimization procedures to search for parameters in a quantitative model that can reproduce experimental data. The aim of optimization is to minimize the sum of squared errors (SSE) in a prediction or to maximize likelihood. A (local) maximum of likelihood or (local) minimum of the SSE can efficiently be identified using gradient approaches. Addition of a stochastic process enables us to identify the global maximum/minimum without becoming trapped in local maxima/minima. Sampling approaches take advantage of increasing computational power to test numerous sets of parameters in order to determine the optimum set. By combining Bayesian inference with gradient or sampling approaches, we can estimate both the optimum parameters and the form of the likelihood function related to the parameters. Finally, we introduce four examples of research that utilize parameter optimization to obtain biological insights from quantified data: transcriptional regulation, bacterial chemotaxis, morphogenesis, and cell cycle regulation. With practical knowledge of parameter optimization, cell and developmental biologists can develop realistic models that reproduce their observations and thus, obtain mechanistic insights into phenomena of interest.

Microcanonical model for interface formation

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

Rucklidge, A.; Zaleski, S.

1988-04-01

We describe a new cellular automaton model which allows us to simulate separation of phases. The model is an extension of existing cellular automata for the Ising model, such as Q2R. It conserves particle number and presents the qualitative features of spinodal decomposition. The dynamics is deterministic and does not require random number generators. The spins exchange energy with small local reservoirs or demons. The rate of relaxation to equilibrium is investigated, and the results are compared to the Lifshitz-Slyozov theory.

A quantum relativistic battle of the sexes cellular automaton

NASA Astrophysics Data System (ADS)

Alonso-Sanz, Ramón; Situ, Haozhen

2017-02-01

The effect of variable entangling on the dynamics of a spatial quantum relativistic formulation of the iterated battle of the sexes game is studied in this work. The game is played in the cellular automata manner, i.e., with local and synchronous interaction. The game is assessed in fair and unfair contests. Despite the full range of quantum parameters initially accessible, they promptly converge into fairly stable configurations, that often show rich spatial structures in simulations with no negligible entanglement.

Traffic dynamics of an on-ramp system with a cellular automaton model

NASA Astrophysics Data System (ADS)

Li, Xin-Gang; Gao, Zi-You; Jia, Bin; Jiang, Rui

2010-06-01

This paper uses the cellular automaton model to study the dynamics of traffic flow around an on-ramp with an acceleration lane. It adopts a parameter, which can reflect different lane-changing behaviour, to represent the diversity of driving behaviour. The refined cellular automaton model is used to describe the lower acceleration rate of a vehicle. The phase diagram and the capacity of the on-ramp system are investigated. The simulation results show that in the single cell model, the capacity of the on-ramp system will stay at the highest flow of a one lane system when the driver is moderate and careful; it will be reduced when the driver is aggressive. In the refined cellular automaton model, the capacity is always reduced even when the driver is careful. It proposes that the capacity drop of the on-ramp system is caused by aggressive lane-changing behaviour and lower acceleration rate.

Laboratory testing of a building envelope segment based on cellular concrete

NASA Astrophysics Data System (ADS)

Fořt, Jan; Pavlík, Zbyšek; Černý, Robert

2016-07-01

Hygrothermal performance of a building envelope based on cellular concrete blocks is studied in the paper. Simultaneously, the strain fields induced by the heat and moisture changes are monitored. The studied wall is exposed to the climatic load corresponding to the winter climatic conditions of the moderate year for Prague. The winter climatic exposure is chosen in order to simulate the critical conditions of the building structure from the point of view of material performance and temperature and humidity loading. The evaluation of hygrothermal performance of a researched wall is done on the basis of relative humidity and temperature profiles measured along the cross section of the cellular concrete blocks. Strain gauges are fixed on the wall surface in expected orientation of the blocks expansion. The obtained results show a good hygrothermal function of the analyzed cellular concrete wall and its insignificant strain.

Molecular Dynamics Simulations of Simple Liquids

ERIC Educational Resources Information Center

Speer, Owner F.; Wengerter, Brian C.; Taylor, Ramona S.

2004-01-01

An experiment, in which students were given the opportunity to perform molecular dynamics simulations on a series of molecular liquids using the Amber suite of programs, is presented. They were introduced to both physical theories underlying classical mechanics simulations and to the atom-atom pair distribution function.

Event-based simulation of networks with pulse delayed coupling

NASA Astrophysics Data System (ADS)

Klinshov, Vladimir; Nekorkin, Vladimir

2017-10-01

Pulse-mediated interactions are common in networks of different nature. Here we develop a general framework for simulation of networks with pulse delayed coupling. We introduce the discrete map governing the dynamics of such networks and describe the computation algorithm for its numerical simulation.

Discrete dynamic modeling of cellular signaling networks.

PubMed

Albert, Réka; Wang, Rui-Sheng

2009-01-01

Understanding signal transduction in cellular systems is a central issue in systems biology. Numerous experiments from different laboratories generate an abundance of individual components and causal interactions mediating environmental and developmental signals. However, for many signal transduction systems there is insufficient information on the overall structure and the molecular mechanisms involved in the signaling network. Moreover, lack of kinetic and temporal information makes it difficult to construct quantitative models of signal transduction pathways. Discrete dynamic modeling, combined with network analysis, provides an effective way to integrate fragmentary knowledge of regulatory interactions into a predictive mathematical model which is able to describe the time evolution of the system without the requirement for kinetic parameters. This chapter introduces the fundamental concepts of discrete dynamic modeling, particularly focusing on Boolean dynamic models. We describe this method step-by-step in the context of cellular signaling networks. Several variants of Boolean dynamic models including threshold Boolean networks and piecewise linear systems are also covered, followed by two examples of successful application of discrete dynamic modeling in cell biology.

Atrial fibrillation in the elderly: the potential contribution of reactive oxygen species

PubMed Central

Schillinger, Kurt J.; Patel, Vickas V.

2012-01-01

Atrial fibrillation (AF) is the most commonly encountered cardiac arrhythmia, and is a significant source of healthcare expenditures throughout the world. It is an arrhythmia with a very clearly defined predisposition for individuals of advanced age, and this fact has led to intense study of the mechanistic links between aging and AF. By promoting oxidative damage to multiple subcellular and cellular structures, reactive oxygen species (ROS) have been shown to induce the intra- and extra-cellular changes necessary to promote the pathogenesis of AF. In addition, the generation and accumulation of ROS have been intimately linked to the cellular processes which underlie aging. This review begins with an overview of AF pathophysiology, and introduces the critical structures which, when damaged, predispose an otherwise healthy atrium to AF. The available evidence that ROS can lead to damage of these critical structures is then reviewed. Finally, the evidence linking the process of aging to the pathogenesis of AF is discussed. PMID:23341843

Profile of new green fluorescent protein transgenic Jinhua pigs as an imaging source

NASA Astrophysics Data System (ADS)

Kawarasaki, Tatsuo; Uchiyama, Kazuhiko; Hirao, Atsushi; Azuma, Sadahiro; Otake, Masayoshi; Shibata, Masatoshi; Tsuchiya, Seiko; Enosawa, Shin; Takeuchi, Koichi; Konno, Kenjiro; Hakamata, Yoji; Yoshino, Hiroyuki; Wakai, Takuya; Ookawara, Shigeo; Tanaka, Hozumi; Kobayashi, Eiji; Murakami, Takashi

2009-09-01

Animal imaging sources have become an indispensable material for biological sciences. Specifically, gene-encoded biological probes serve as stable and high-performance tools to visualize cellular fate in living animals. We use a somatic cell cloning technique to create new green fluorescent protein (GFP)-expressing Jinhua pigs with a miniature body size, and characterized the expression profile in various tissues/organs and ex vivo culture conditions. The born GFP-transgenic pig demonstrate an organ/tissue-dependent expression pattern. Strong GFP expression is observed in the skeletal muscle, pancreas, heart, and kidney. Regarding cellular levels, bone-marrow-derived mesenchymal stromal cells, hepatocytes, and islet cells of the pancreas also show sufficient expression with the unique pattern. Moreover, the cloned pigs demonstrate normal growth and fertility, and the introduced GFP gene is stably transmitted to pigs in subsequent generations. The new GFP-expressing Jinhua pigs may be used as new cellular/tissue light resources for biological imaging in preclinical research fields such as tissue engineering, experimental regenerative medicine, and transplantation.

Development of nano-fabrication technique utilizing self-organizational behavior of point defects induced by ion irradiation

NASA Astrophysics Data System (ADS)

Nitta, Noriko; Taniwaki, Masafumi

2006-04-01

The present authors proposed a novel nano-fabrication technique that is able to arrange the fine cells orderly, based on their finding in GaSb implanted at a low temperature. In this article, first the experimental results that anomalous cellular structure was formed in GaSb by ion implantation is introduced and the self-organizational formation mechanism of the structure is described. Next a nano-fabrication technique that utilizes focused ion beam is described. This technique consists of two procedures, i.e. the formation process of the voids array and the development of the initial array to ordered cellular structure. Finally, the nano-fabrication is actually performed by this technique and their results are reported. Fabrication succeeded in structures where the dot (cell) interval was 100 nm or larger. The minimum ion dose for initial voids which develops to the ordered cellular structure is evaluated. It is also shown that the substrate temperature during implantation is an essential parameter for this technique.

Reverse engineering of gene regulatory networks.

PubMed

Cho, K H; Choo, S M; Jung, S H; Kim, J R; Choi, H S; Kim, J

2007-05-01

Systems biology is a multi-disciplinary approach to the study of the interactions of various cellular mechanisms and cellular components. Owing to the development of new technologies that simultaneously measure the expression of genetic information, systems biological studies involving gene interactions are increasingly prominent. In this regard, reconstructing gene regulatory networks (GRNs) forms the basis for the dynamical analysis of gene interactions and related effects on cellular control pathways. Various approaches of inferring GRNs from gene expression profiles and biological information, including machine learning approaches, have been reviewed, with a brief introduction of DNA microarray experiments as typical tools for measuring levels of messenger ribonucleic acid (mRNA) expression. In particular, the inference methods are classified according to the required input information, and the main idea of each method is elucidated by comparing its advantages and disadvantages with respect to the other methods. In addition, recent developments in this field are introduced and discussions on the challenges and opportunities for future research are provided.

Study of fracture and stress-induced morphological instabilities in polymeric materials

NASA Astrophysics Data System (ADS)

Sabouri-Ghomi, Mohsen

We study the phenomena of fracture in polymers at the molecular and continuum level. At a molecular level, we study the failure of polymer/polymer interfaces. Our main focus is on a specific mode of failure known as chain pull-out fracture, which is common to weak adhesive junctions, and polymer blends and mixtures. In the case of the interface between incompatible polymers, reinforcement is achieved by adding a block copolymer to the interface. We introduce a microscopic model based on Brownian dynamics to investigate the effect of the polymerization index N, of the block connector chain, on fracture toughness of such reinforced polymeric junctions. We consider the mushroom regime, where connector chains are grafted with low surface density, for the case of large pulling velocity. We find that for short chains the interface fracture toughness depends linearly on the polymerization index N of the connector chains, while for longer chains the dependence becomes N 3/2. We propose a scaling argument, based on the geometry of the initial configuration, that accounts for both short and long chains and the crossover between them. At the continuum level, we study the pattern selection mechanism of finger-like crack growth phenomena in gradient driven growth problems in general, and the structure of stress-induced morphological instabilities in crazing of polymer glasses in particular. We simulate solidification in a narrow channel through the use of a phase-field model with an adaptive grid. By tuning a dimensionless parameter, the Peclet number, we show a continuous crossover from a free dendrite at high Peclet numbers to anisotropic viscous fingering at low Peclet numbers. At low Peclet numbers we find good agreement between our results, theoretical predictions, and experiment, providing the first quantitative test of solvability theory for anisotropic viscous fingers. For high undercoolings, we find new phenomena, a solid forger which satisfies stability and thermodynamic criterion. We further provide an analytical form for the shape of these fingers, based on local models of solidification, which fits our numerical results from simulation. Later we study the growth of crazes in polymer glasses by deriving the equations of motion of plastic flow at the craze tip, and the steady-state velocity profile of this flow. By developing a phenomenological model, we solve the full time-dependent equations of motion of this highly non-linear phenomena. Our simulation produces the steady-state cellular pattern observed in experiments. We further show that polymer glasses with lower yield stress produce cellular patterns with sharper tips and more cells, indicating instabilities with smaller wavelengths.

Feasibility of 3D printed air slab diode caps for small field dosimetry.

PubMed

Perrett, Benjamin; Charles, Paul; Markwell, Tim; Kairn, Tanya; Crowe, Scott

2017-09-01

Commercial diode detectors used for small field dosimetry introduce a field-size-dependent over-response relative to an ideal, water-equivalent dosimeter due to high density components in the body of the detector. An air gap above the detector introduces a field-size-dependent under-response, and can be used to offset the field-size-dependent detector over-response. Other groups have reported experimental validation of caps containing air gaps for use with several types of diodes in small fields. This paper examines two designs for 3D printed diode air caps for the stereotactic field diode (SFD)-a cap containing a sealed air cavity, and a cap with an air cavity at the face of the SFD. Monte Carlo simulations of both designs were performed to determine dimensions for an air cavity to introduce the desired dosimetric correction. Various parameter changes were also simulated to estimate the dosimetric uncertainties introduced by 3D printing. Cap layer dimensions, cap density changes due to 3D printing, and unwanted air gaps were considered. For the sealed design the optimal air gap size for water-equivalent cap material was 0.6 mm, which increased to 1.0 mm when acrylonitrile butadiene styrene in the cap was simulated. The unsealed design had less variation, a 0.4 mm air gap is optimal in both situations. Unwanted air pockets in the bore of the cap and density changes introduced by the 3D printing process can potentially introduce significant dosimetric effects. These effects may be limited by using fine print resolutions and minimising the volume of cap material.

Contemporary evolution during invasion: evidence for differentiation, natural selection, and local adaptation.

PubMed

Colautti, Robert I; Lau, Jennifer A

2015-05-01

Biological invasions are 'natural' experiments that can improve our understanding of contemporary evolution. We evaluate evidence for population differentiation, natural selection and adaptive evolution of invading plants and animals at two nested spatial scales: (i) among introduced populations (ii) between native and introduced genotypes. Evolution during invasion is frequently inferred, but rarely confirmed as adaptive. In common garden studies, quantitative trait differentiation is only marginally lower (~3.5%) among introduced relative to native populations, despite genetic bottlenecks and shorter timescales (i.e. millennia vs. decades). However, differentiation between genotypes from the native vs. introduced range is less clear and confounded by nonrandom geographic sampling; simulations suggest this causes a high false-positive discovery rate (>50%) in geographically structured populations. Selection differentials (¦s¦) are stronger in introduced than in native species, although selection gradients (¦β¦) are not, consistent with introduced species experiencing weaker genetic constraints. This could facilitate rapid adaptation, but evidence is limited. For example, rapid phenotypic evolution often manifests as geographical clines, but simulations demonstrate that nonadaptive trait clines can evolve frequently during colonization (~two-thirds of simulations). Additionally, QST-FST studies may often misrepresent the strength and form of natural selection acting during invasion. Instead, classic approaches in evolutionary ecology (e.g. selection analysis, reciprocal transplant, artificial selection) are necessary to determine the frequency of adaptive evolution during invasion and its influence on establishment, spread and impact of invasive species. These studies are rare but crucial for managing biological invasions in the context of global change. © 2015 John Wiley & Sons Ltd.

Modeling of fracture of protective concrete structures under impact loads

NASA Astrophysics Data System (ADS)

Radchenko, P. A.; Batuev, S. P.; Radchenko, A. V.; Plevkov, V. S.

2015-10-01

This paper presents results of numerical simulation of interaction between a Boeing 747-400 aircraft and the protective shell of a nuclear power plant. The shell is presented as a complex multilayered cellular structure consisting of layers of concrete and fiber concrete bonded with steel trusses. Numerical simulation was performed three-dimensionally using the original algorithm and software taking into account algorithms for building grids of complex geometric objects and parallel computations. Dynamics of the stress-strain state and fracture of the structure were studied. Destruction is described using a two-stage model that allows taking into account anisotropy of elastic and strength properties of concrete and fiber concrete. It is shown that wave processes initiate destruction of the cellular shell structure; cells start to destruct in an unloading wave originating after the compression wave arrival at free cell surfaces.

The evolution of void-filled cosmological structures

NASA Technical Reports Server (NTRS)

Regos, Eniko; Geller, Margaret J.

1991-01-01

1D, 2D, and 3D simulations are used here to investigate the salient features in the evolution of void-filled cosmological structures in universes with arbitrary values of Omega. It is found that the growth of a void as a function of time decreases significantly at the time corresponding to Omega = 0.5. In models constructed in 2D and 3D, suitable initial conditions lead to cellular structure with faceted voids similar to those observed in redshift surveys. Matter compressed to planes flows more rapidly toward condensations at the intersections than would be expected for spherical infall. The peculiar streaming velocities for void diameters of 5000 km/s should be observable. The simulations provide a more physical basis and dynamics for the bubbly and Voronois tesselation models used to derive statistical properties of cellular large-scale structure.

Induction of vascular endothelial phenotype and cellular proliferation from human cord blood stem cells cultured in simulated microgravity

NASA Astrophysics Data System (ADS)

Chiu, Brian; Z-M Wan, Jim; Abley, Doris; Akabutu, John

2005-05-01

Recent studies have demonstrated that stem cells derived from adult hematopoietic tissues are capable of trans-differentiation into non-hematopoietic cells, and that the culture in microgravity ( μg) may modulate the proliferation and differentiation. We investigated the application of μg to human umbilical cord blood stem cells (CBSC) in the induction of vascular endothelial phenotype expression and cellular proliferation. CD34+ mononuclear cells were isolated from waste human umbilical cord blood samples and cultured in simulated μg for 14 days. The cells were seeded in rotary wall vessels (RWV) with or without microcarrier beads (MCB) and vascular endothelial growth factor was added during culture. Controls consisted of culture in 1 G. The cell cultures in RWV were examined by inverted microscopy. Cell counts, endothelial cell and leukocyte markers performed by flow-cytometry and FACS scan were assayed at days 1, 4, 7 and at the termination of the experiments. Culture in RWV revealed significantly increased cellular proliferation with three-dimensional (3D) tissue-like aggregates. At day 4, CD34+ cells cultured in RWV bioreactor without MCB developed vascular tubular assemblies and exhibited endothelial phenotypic markers. These data suggest that CD34+ human umbilical cord blood progenitors are capable of trans-differentiation into vascular endothelial cell phenotype and assemble into 3D tissue structures. Culture of CBSC in simulated μg may be potentially beneficial in the fields of stem cell biology and somatic cell therapy.

A Simulation of Coevolution Using Playing Cards

ERIC Educational Resources Information Center

Tatina, Robert

2007-01-01

In this article, the author describes a simulation of a coevolutionary "arms race" and introduce a way of teaching it that lets students use the theory of natural selection to explain the outcomes of the simulation. The simulation uses the numerical cards from an UNO[R] playing card deck to represent the speeds of individuals in populations of…

Morphing hybrid honeycomb (MOHYCOMB) with in situ Poisson’s ratio modulation

NASA Astrophysics Data System (ADS)

Heath, Callum J. C.; Neville, Robin M.; Scarpa, Fabrizio; Bond, Ian P.; Potter, Kevin D.

2016-08-01

Electrostatic adhesion can be used as a means of reversible attachment. Through application of high voltage (~2 kV) across closely spaced parallel plate electrodes, significant shear stresses (11 kPa) can be generated. The highest levels of electrostatic holding force can be achieved through close contact of connection surfaces; this is facilitated by flexible electrodes which can conform to reduce air gaps. Cellular structures are comprised of thin walled elements, making them ideal host structures for electrostatic adhesive elements. The reversible adhesion provides control of the internal connectivity of the cellular structure, and determines the effective cell geometry. This would offer variable stiffness and control of the effective Poisson’s ratio of the global cellular array. Using copper-polyimide thin film laminates and PVDF thin film dielectrics, double lap shear electrostatic adhesive elements have been introduced to a cellular geometry. By activating different groups of reversible adhesive interfaces, the cellular array can assume four different cell configurations. A maximum stiffness modulation of 450% between the ‘All off’ and ‘All on’ cell morphologies has been demonstrated. This structure is also capable of in situ effective Poisson’s ratio variations, with the ability to switch between values of -0.45 and 0.54. Such a structure offers the potential for tuneable vibration absorption (due to its variable stiffness properties), or as a smart honeycomb with controllable curvature and is termed morphing hybrid honeycomb.

Label-free high-throughput imaging flow cytometry

NASA Astrophysics Data System (ADS)

Mahjoubfar, A.; Chen, C.; Niazi, K. R.; Rabizadeh, S.; Jalali, B.

2014-03-01

Flow cytometry is an optical method for studying cells based on their individual physical and chemical characteristics. It is widely used in clinical diagnosis, medical research, and biotechnology for analysis of blood cells and other cells in suspension. Conventional flow cytometers aim a laser beam at a stream of cells and measure the elastic scattering of light at forward and side angles. They also perform single-point measurements of fluorescent emissions from labeled cells. However, many reagents used in cell labeling reduce cellular viability or change the behavior of the target cells through the activation of undesired cellular processes or inhibition of normal cellular activity. Therefore, labeled cells are not completely representative of their unaltered form nor are they fully reliable for downstream studies. To remove the requirement of cell labeling in flow cytometry, while still meeting the classification sensitivity and specificity goals, measurement of additional biophysical parameters is essential. Here, we introduce an interferometric imaging flow cytometer based on the world's fastest continuous-time camera. Our system simultaneously measures cellular size, scattering, and protein concentration as supplementary biophysical parameters for label-free cell classification. It exploits the wide bandwidth of ultrafast laser pulses to perform blur-free quantitative phase and intensity imaging at flow speeds as high as 10 meters per second and achieves nanometer-scale optical path length resolution for precise measurements of cellular protein concentration.

Desipramine induces disorder in cholesterol-rich membranes: implications for viral trafficking

NASA Astrophysics Data System (ADS)

Pakkanen, Kirsi; Salonen, Emppu; Mäkelä, Anna R.; Oker-Blom, Christian; Vattulainen, Ilpo; Vuento, Matti

2009-12-01

In this study, the effect of desipramine (DMI) on phospholipid bilayers and parvoviral entry was elucidated. In atomistic molecular dynamics simulations, DMI was found to introduce disorder in cholesterol-rich phospholipid bilayers. This was manifested by a decrease in the deuterium order parameter SCD as well as an increase in the membrane area. Disordering of the membrane suggested DMI to destabilize cholesterol-rich membrane domains (rafts) in cellular conditions. To relate the raft disrupting ability of DMI with novel biological relevance, we studied the intracellular effect of DMI using canine parvovirus (CPV), a virus known to interact with endosomal membranes and sphingomyelin, as an intracellular probe. DMI was found to cause retention of the virus in intracellular vesicular structures leading to the inhibition of viral proliferation. This implies that DMI has a deleterious effect on the viral traffic. As recycling endosomes and the internal vesicles of multivesicular bodies are known to contain raft components, the effect of desipramine beyond the plasma membrane step could be caused by raft disruption leading to impaired endosomal function and possibly have direct influence on the penetration of the virus through an endosomal membrane.

Double quick, double click reversible peptide "stapling".

PubMed

Grison, Claire M; Burslem, George M; Miles, Jennifer A; Pilsl, Ludwig K A; Yeo, David J; Imani, Zeynab; Warriner, Stuart L; Webb, Michael E; Wilson, Andrew J

2017-07-01

The development of constrained peptides for inhibition of protein-protein interactions is an emerging strategy in chemical biology and drug discovery. This manuscript introduces a versatile, rapid and reversible approach to constrain peptides in a bioactive helical conformation using BID and RNase S peptides as models. Dibromomaleimide is used to constrain BID and RNase S peptide sequence variants bearing cysteine (Cys) or homocysteine ( h Cys) amino acids spaced at i and i + 4 positions by double substitution. The constraint can be readily removed by displacement of the maleimide using excess thiol. This new constraining methodology results in enhanced α-helical conformation (BID and RNase S peptide) as demonstrated by circular dichroism and molecular dynamics simulations, resistance to proteolysis (BID) as demonstrated by trypsin proteolysis experiments and retained or enhanced potency of inhibition for Bcl-2 family protein-protein interactions (BID), or greater capability to restore the hydrolytic activity of the RNAse S protein (RNase S peptide). Finally, use of a dibromomaleimide functionalized with an alkyne permits further divergent functionalization through alkyne-azide cycloaddition chemistry on the constrained peptide with fluorescein, oligoethylene glycol or biotin groups to facilitate biophysical and cellular analyses. Hence this methodology may extend the scope and accessibility of peptide stapling.

Increased dimensionality of cell-cell communication can decrease the precision of gradient sensing

NASA Astrophysics Data System (ADS)

Smith, Tyler; Levchenko, Andre; Nemenman, Ilya; Mugler, Andrew

Gradient sensing is a biological computation that involves comparison of concentrations measured in at least two different locations. As such, the pre- cision of gradient sensing is limited by the intrinsic stochasticity in the com- munication that brings such distributed information to the same location. We have recently analyzed such limitations experimentally and theoretically in multicellular gradient sensing in mammary epithelial cell organoids. For 1d chains of collectively sensing cells, the communication noise puts a se- vere constraint on how the accuracy of gradient sensing increases with the number of cells in the sensor. A question remains as to whether the effect of the noise can be mitigated by the extra spatial averaging allowed in sensing by 2d and 3d cellular organoids. Here we show using computer simulations that, counterintuitively, such spatial averaging decreases gradient sensitiv- ity (while it increases concentration sensitivity). We explain the findings analytically and propose that a recently introduced Regional Excitation - Global Inhibition model of gradient sensing can overcome this limitation and use 2d or 3d spatial averaging to improve the sensing accuracy. Supported by NSF Grant PHY/1410978 and James S. McDonnell Foundation Grant # 220020321.

A novel micro-emulsion and micelle assembling method to prepare DEC205 monoclonal antibody coupled cationic nanoliposomes for simulating exosomes to target dendritic cells.

PubMed

Li, Kexin; Chang, Shasha; Wang, Zhongyan; Zhao, Xiuli; Chen, Dawei

2015-08-01

Cationic biomimetic exosomes were prepared using a novel micro-emulsion and micelle assembling method by introducing DEC205 monoclonal antibody as specific ligand to target dendritic cells (DCs). The Box-Behnken experimental design was applied for optimization of nanoliposomes (NLip) and DEC205 monoclonal antibody was then conjugated on the surface of NLip (DEC205-NLip). NLip and DEC205-NLip respectively had an average size of 62.7 ± 6.33 nm and 81.64 ± 4.25 nm, zeta potential of +30.5 ± 2.3 mV and +19.8 ± 1.8 mV and encapsulation efficiency of 91.02 ± 3.1% and 93.10 ± 2.2%. In addition, the toxicity studies confirmed DEC205 monoclonal antibody could significantly reduce the cytotoxicity of the cationic lipid against DCs. And the cellular uptake experiment evaluated the significant targeting effect of the DEC205 monoclonal antibody on DC cells. In conclusion, the novel method presented here to prepare biomimetic exosomes was an efficient approach to develop antigen carriers for specific DCs targeting. Copyright © 2015 Elsevier B.V. All rights reserved.

Multi-Scale Spatio-Temporal Modeling: Lifelines of Microorganisms in Bioreactors and Tracking Molecules in Cells

NASA Astrophysics Data System (ADS)

Lapin, Alexei; Klann, Michael; Reuss, Matthias

Agent-based models are rigorous tools for simulating the interactions of individual entities, such as organisms or molecules within cells and assessing their effects on the dynamic behavior of the system as a whole. In context with bioprocess and biosystems engineering there are several interesting and important applications. This contribution aims at introducing this strategy with the aid of two examples characterized by striking distinctions in the scale of the individual entities and the mode of their interactions. In the first example a structured-segregated model is applied to travel along the lifelines of single cells in the environment of a three-dimensional turbulent field of a stirred bioreactor. The modeling approach is based on an Euler-Lagrange formulation of the system. The strategy permits one to account for the heterogeneity present in real reactors in both the fluid and cellular phases, respectively. The individual response of the cells to local variations in the extracellular concentrations is pictured by a dynamically structured model of the key reactions of the central metabolism. The approach permits analysis of the lifelines of individual cells in space and time.

Agent-based modeling: Methods and techniques for simulating human systems

PubMed Central

Bonabeau, Eric

2002-01-01

Agent-based modeling is a powerful simulation modeling technique that has seen a number of applications in the last few years, including applications to real-world business problems. After the basic principles of agent-based simulation are briefly introduced, its four areas of application are discussed by using real-world applications: flow simulation, organizational simulation, market simulation, and diffusion simulation. For each category, one or several business applications are described and analyzed. PMID:12011407

Computer Simulation of the Population Growth (Schizosaccharomyces Pombe) Experiment.

ERIC Educational Resources Information Center

Daley, Michael; Hillier, Douglas

1981-01-01

Describes a computer program (available from authors) developed to simulate "Growth of a Population (Yeast) Experiment." Students actively revise the counting techniques with realistically simulated haemocytometer or eye-piece grid and are reminded of the necessary dilution technique. Program can be modified to introduce such variables…

Virtual reality simulator for vitreoretinal surgery using integrated OCT data.

PubMed

Kozak, Igor; Banerjee, Pat; Luo, Jia; Luciano, Cristian

2014-01-01

Operative practice using surgical simulators has become a part of training in many surgical specialties, including ophthalmology. We introduce a virtual reality retina surgery simulator capable of integrating optical coherence tomography (OCT) scans from real patients for practicing vitreoretinal surgery using different pathologic scenarios.

UNICOR: a species connectivity and corridor network simulator

Treesearch

E. L. Landguth; B. K. Hand; J. Glassy; S. A. Cushman; M. A. Sawaya

2012-01-01

We introduce UNIversal CORridor network simulator (UNICOR), a species connectivity and corridor identifi cation tool. UNICOR applies Dijkstra's shortest path algorithm to individual-based simulations. Outputs can be used to designate movement corridors, identify isolated populations, and prioritize conservation plans to promote species persistence. The key...

Microscopic Car Modeling for Intelligent Traffic and Scenario Generation in the UCF Driving Simulator : Year 2

DOT National Transportation Integrated Search

2000-01-01

A multi-year project was initiated to introduce autonomous vehicles in the University of Central Florida (UCF) Driving Simulator for real-time interaction with the simulator vehicle. This report describes the progress during the second year. In the f...

A Simulation of Counter-Cyclical Intervention: Some Practical Lessons

ERIC Educational Resources Information Center

Grawe, Nathan D.; Watts, Michael, Ed.

2007-01-01

The author introduces a simulation of counter-cyclical interventions that highlights important issues surrounding the practice of government intervention. The simulation provides experiential insight as to why economists have long debated the degree of persistence exhibited by disequilibrating shocks and connects this debate to discussions about…

A model for the kinetics of a solar-pumped long path laser experiment

NASA Technical Reports Server (NTRS)

Stock, L. V.; Wilson, J. W.; Deyoung, R. J.

1986-01-01

A kinetic model for a solar-simulator pumped iodine laser system is developed and compared to an experiment in which the solar simulator output is dispersed over a large active volume (150 cu cm) with low simulator light intensity (approx. 200 solar constants). A trace foreign gas which quenches the upper level is introduced into the model. Furthermore, a constant representing optical absorption of the stimulated emission is introduced, in addition to a constant representing the scattering at each of the mirrors, via the optical cavity time constant. The non-uniform heating of the gas is treated as well as the pressure change as a function of time within the cavity. With these new phenomena introduced into the kinetic model, a best reasonable fit to the experimental data is found by adjusting the reaction rate coefficients within the range of known uncertainty by numerical methods giving a new bound within this range of uncertainty. The experimental parameters modeled are the lasing time, laser pulse energy, and time to laser threshold.

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

PubMed

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.

Multi-agent simulation of the von Thunen model formation mechanism

NASA Astrophysics Data System (ADS)

Tao, Haiyan; Li, Xia; Chen, Xiaoxiang; Deng, Chengbin

2008-10-01

This research tries to explain the internal driving forces of circular structure formation in urban geography via the simulation of interaction between individual behavior and market. On the premise of single city center, unchanged scale merit and complete competition, enterprise migration theory as well, an R-D algorithm, that has agents searched the best behavior rules in some given locations, is introduced with agent-based modeling technique. The experiment conducts a simulation on Swarm platform, whose result reflects and replays the formation process of Von Thünen circular structure. Introducing and considering some heterogeneous factors, such as traffic roads, the research verifies several landuse models and discusses the self-adjustment function of price mechanism.

H2LIFT: global navigation simulation ship tracking and WMD detection in the maritime domain

NASA Astrophysics Data System (ADS)

Wyffels, Kevin

2007-04-01

This paper presents initial results for a tracking simulation of multiple maritime vehicles for use in a data fusion program detecting Weapons of Mass Destruction (WMD). This simulation supports a fusion algorithm (H2LIFT) for collecting and analyzing data providing a heuristic analysis tool for detecting weapons of mass destruction in the maritime domain. Tools required to develop a navigational simulation fitting a set of project objectives are introduced for integration into the H2LIFT algorithm. Emphasis is placed on the specific requirements of the H2LIFT project, however the basic equations, algorithms, and methodologies can be used as tools in a variety of scenario simulations. Discussion will be focused on track modeling (e.g. position tracking of ships), navigational techniques, WMD detection, and simulation of these models using Matlab and Simulink. Initial results provide absolute ship position data for a given multi-ship maritime scenario with random generation of a given ship containing a WMD. Required coordinate systems, conversions between coordinate systems, Earth modeling techniques, and navigational conventions and techniques are introduced for development of the simulations.

Injectable, cellular-scale optoelectronics with applications for wireless optogenetics.

PubMed

Kim, Tae-il; McCall, Jordan G; Jung, Yei Hwan; Huang, Xian; Siuda, Edward R; Li, Yuhang; Song, Jizhou; Song, Young Min; Pao, Hsuan An; Kim, Rak-Hwan; Lu, Chaofeng; Lee, Sung Dan; Song, Il-Sun; Shin, Gunchul; Al-Hasani, Ream; Kim, Stanley; Tan, Meng Peun; Huang, Yonggang; Omenetto, Fiorenzo G; Rogers, John A; Bruchas, Michael R

2013-04-12

Successful integration of advanced semiconductor devices with biological systems will accelerate basic scientific discoveries and their translation into clinical technologies. In neuroscience generally, and in optogenetics in particular, the ability to insert light sources, detectors, sensors, and other components into precise locations of the deep brain yields versatile and important capabilities. Here, we introduce an injectable class of cellular-scale optoelectronics that offers such features, with examples of unmatched operational modes in optogenetics, including completely wireless and programmed complex behavioral control over freely moving animals. The ability of these ultrathin, mechanically compliant, biocompatible devices to afford minimally invasive operation in the soft tissues of the mammalian brain foreshadow applications in other organ systems, with potential for broad utility in biomedical science and engineering.

New Tools and New Biology: Recent Miniaturized Systems for Molecular and Cellular Biology

PubMed Central

Hamon, Morgan; Hong, Jong Wook

2013-01-01

Recent advances in applied physics and chemistry have led to the development of novel microfluidic systems. Microfluidic systems allow minute amounts of reagents to be processed using μm-scale channels and offer several advantages over conventional analytical devices for use in biological sciences: faster, more accurate and more reproducible analytical performance, reduced cell and reagent consumption, portability, and integration of functional components in a single chip. In this review, we introduce how microfluidics has been applied to biological sciences. We first present an overview of the fabrication of microfluidic systems and describe the distinct technologies available for biological research. We then present examples of microsystems used in biological sciences, focusing on applications in molecular and cellular biology. PMID:24305843

Requirements for a mobile communications satellite system. Volume 2: Technical report

NASA Technical Reports Server (NTRS)

Horstein, M.

1983-01-01

Three types of satellite aided mobile communications are considered for users in areas not served by (terrestrial) cellular radio systems. In system 1, mobile units are provided a direct satellite link to a gateway station, which serves as the interface to the terrestrial toll network. In system 2, a terrestrial radio link similar to those in cellular systems connects the mobile unit to a translator station; each translator relays the traffic from mobile units in its vicinity, via satellite, to the regional gateway. It is not feasible for system 2 to provide obiquitous coverage. Therefore, system 3 is introduced, in which the small percentage of users not within range of a translator are provided a direct satellite link as in system 1.

Inhibiting host-pathogen interactions using membrane-based nanostructures.

PubMed

Bricarello, Daniel A; Patel, Mira A; Parikh, Atul N

2012-06-01

Virulent strains of bacteria and viruses recognize host cells by their plasma membrane receptors and often exploit the native translocation machinery to invade the cell. A promising therapeutic concept for early interruption of pathogen infection is to subvert this pathogenic trickery using exogenously introduced decoys that present high-affinity mimics of cellular receptors. This review highlights emerging applications of molecularly engineered lipid-bilayer-based nanostructures, namely (i) functionalized liposomes, (ii) supported colloidal bilayers or protocells and (iii) reconstituted lipoproteins, which display functional cellular receptors in optimized conformational and aggregative states. These decoys outcompete host cell receptors by preferentially binding to and neutralizing virulence factors of both bacteria and viruses, thereby promising a new approach to antipathogenic therapy. Copyright © 2012 Elsevier Ltd. All rights reserved.

Active dynamics of tissue shear flow

NASA Astrophysics Data System (ADS)

Popović, Marko; Nandi, Amitabha; Merkel, Matthias; Etournay, Raphaël; Eaton, Suzanne; Jülicher, Frank; Salbreux, Guillaume

2017-03-01

We present a hydrodynamic theory to describe shear flows in developing epithelial tissues. We introduce hydrodynamic fields corresponding to state properties of constituent cells as well as a contribution to overall tissue shear flow due to rearrangements in cell network topology. We then construct a generic linear constitutive equation for the shear rate due to topological rearrangements and we investigate a novel rheological behaviour resulting from memory effects in the tissue. We identify two distinct active cellular processes: generation of active stress in the tissue, and actively driven topological rearrangements. We find that these two active processes can produce distinct cellular and tissue shape changes, depending on boundary conditions applied on the tissue. Our findings have consequences for the understanding of tissue morphogenesis during development.

Depth-resolved cellular microrheology using HiLo microscopy

PubMed Central

Michaelson, Jarett; Choi, Heejin; So, Peter; Huang, Hayden

2012-01-01

It is increasingly important to measure cell mechanical properties in three-dimensional environments. Particle tracking microrheology (PTM) can measure cellular viscoelastic properties; however, out-of-plane data can introduce artifacts into these measurements. We developed a technique that employs HiLo microscopy to reduce out-of-plane contributions. This method eliminated signals from 90% of probes 0.5 μm or further from the focal plane, while retaining all in-plane probes. We used this technique to characterize live-cell bilayers and found that there were significant, frequency-dependent changes to the extracted cell moduli when compared to conventional analysis. Our results indicate that removal of out-of-plane information is vital for accurate assessments of cell mechanical properties. PMID:22741071

Evaluating a Novel Cellular Automata-Based Distributed Power Management Approach for Mobile Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Adabi, Sepideh; Adabi, Sahar; Rezaee, Ali

According to the traditional definition of Wireless Sensor Networks (WSNs), static sensors have limited the feasibility of WSNs in some kind of approaches, so the mobility was introduced in WSN. Mobile nodes in a WSN come equipped with battery and from the point of deployment, this battery reserve becomes a valuable resource since it cannot be replenished. Hence, maximizing the network lifetime by minimizing the energy is an important challenge in Mobile WSN. Energy conservation can be accomplished by different approaches. In this paper, we presented an energy conservation solution based on Cellular Automata. The main objective of this solution is based on dynamically adjusting the transmission range and switching between operational states of the sensor nodes.

Field-driven mesoscale phase transition in polarized colloids in microgravity

NASA Astrophysics Data System (ADS)

Khusid, Boris; Elele, Ezinwa

2014-11-01

An unexpected phase transition in a polarized suspension was reported by Kumar, Khusid, Acrivos, PRL 95, 258301, 2005 and Agarwal, Yethiraj, PRL 102, 198301, 2009. Following the field application, particles aggregated head-to-tail into chains that bridged the interelectrode gap and then formed a cellular pattern, in which large-scale particle-free voids were enclosed by particle-rich thin walls. Surprisingly, the size of particle-free domains scales linearly with the gap thickness but is insensitive to the particle size and the field strength and frequency. Cellular structures were not observed in simulations of equilibrium in a polarized suspension (Richardi, Weis, J. Chem. Phys. 135, 124502, 2011; Almudallal, Saika-Voivod, PRE 84, 011402, 2011). Nonequilibrium simulations (Park, Saintillan, PRE 83, 041409, 2011) showed cellular-like structures but at a particle concentration much higher than in experiments. A requirement for precise matching of densities between particles and a fluid to avoid gravity effects limits terrestrial experiments to negatively polarized particles. We will present data on positively polarized non-buoyancy-matched particles and the development of experiments in the International Space Station needed to evaluate gravity contribution. Supported by NASA's Physical Science Research Program, NNX13AQ53G.

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

NASA Astrophysics Data System (ADS)

Hua, Wei; Liu, Jun

2006-04-01

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

Plate-impact loading of cellular structures formed by selective laser melting

NASA Astrophysics Data System (ADS)

Winter, R. E.; Cotton, M.; Harris, E. J.; Maw, J. R.; Chapman, D. J.; Eakins, D. E.; McShane, G.

2014-03-01

Porous materials are of great interest because of improved energy absorption over their solid counterparts. Their properties, however, have been difficult to optimize. Additive manufacturing has emerged as a potential technique to closely define the structure and properties of porous components, i.e. density, strut width and pore size; however, the behaviour of these materials at very high impact energies remains largely unexplored. We describe an initial study of the dynamic compression response of lattice materials fabricated through additive manufacturing. Lattices consisting of an array of intersecting stainless steel rods were fabricated into discs using selective laser melting. The resulting discs were impacted against solid stainless steel targets at velocities ranging from 300 to 700 m s-1 using a gas gun. Continuum CTH simulations were performed to identify key features in the measured wave profiles, while 3D simulations, in which the individual cells were modelled, revealed details of microscale deformation during collapse of the lattice structure. The validated computer models have been used to provide an understanding of the deformation processes in the cellular samples. The study supports the optimization of cellular structures for application as energy absorbers.

Mutual information and the fidelity of response of gene regulatory models

NASA Astrophysics Data System (ADS)

Tabbaa, Omar P.; Jayaprakash, C.

2014-08-01

We investigate cellular response to extracellular signals by using information theory techniques motivated by recent experiments. We present results for the steady state of the following gene regulatory models found in both prokaryotic and eukaryotic cells: a linear transcription-translation model and a positive or negative auto-regulatory model. We calculate both the information capacity and the mutual information exactly for simple models and approximately for the full model. We find that (1) small changes in mutual information can lead to potentially important changes in cellular response and (2) there are diminishing returns in the fidelity of response as the mutual information increases. We calculate the information capacity using Gillespie simulations of a model for the TNF-α-NF-κ B network and find good agreement with the measured value for an experimental realization of this network. Our results provide a quantitative understanding of the differences in cellular response when comparing experimentally measured mutual information values of different gene regulatory models. Our calculations demonstrate that Gillespie simulations can be used to compute the mutual information of more complex gene regulatory models, providing a potentially useful tool in synthetic biology.

Coverage Extension and Balancing the Transmitted Power of the Moving Relay Node at LTE-A Cellular Network

PubMed Central

Aldhaibani, Jaafar A.; Yahya, Abid; Ahmad, R. Badlishah

2014-01-01

The poor capacity at cell boundaries is not enough to meet the growing demand and stringent design which required high capacity and throughput irrespective of user's location in the cellular network. In this paper, we propose new schemes for an optimum fixed relay node (RN) placement in LTE-A cellular network to enhance throughput and coverage extension at cell edge region. The proposed approach mitigates interferences between all nodes and ensures optimum utilization with the optimization of transmitted power. Moreover, we proposed a new algorithm to balance the transmitted power of moving relay node (MR) over cell size and providing required SNR and throughput at the users inside vehicle along with reducing the transmitted power consumption by MR. The numerical analysis along with the simulation results indicates that an improvement in capacity for users is 40% increment at downlink transmission from cell capacity. Furthermore, the results revealed that there is saving nearly 75% from transmitted power in MR after using proposed balancing algorithm. ATDI simulator was used to verify the numerical results, which deals with real digital cartographic and standard formats for terrain. PMID:24672378

Coverage extension and balancing the transmitted power of the moving relay node at LTE-A cellular network.

PubMed

Aldhaibani, Jaafar A; Yahya, Abid; Ahmad, R Badlishah

2014-01-01

The poor capacity at cell boundaries is not enough to meet the growing demand and stringent design which required high capacity and throughput irrespective of user's location in the cellular network. In this paper, we propose new schemes for an optimum fixed relay node (RN) placement in LTE-A cellular network to enhance throughput and coverage extension at cell edge region. The proposed approach mitigates interferences between all nodes and ensures optimum utilization with the optimization of transmitted power. Moreover, we proposed a new algorithm to balance the transmitted power of moving relay node (MR) over cell size and providing required SNR and throughput at the users inside vehicle along with reducing the transmitted power consumption by MR. The numerical analysis along with the simulation results indicates that an improvement in capacity for users is 40% increment at downlink transmission from cell capacity. Furthermore, the results revealed that there is saving nearly 75% from transmitted power in MR after using proposed balancing algorithm. ATDI simulator was used to verify the numerical results, which deals with real digital cartographic and standard formats for terrain.

Fractals: To Know, to Do, to Simulate.

ERIC Educational Resources Information Center

Talanquer, Vicente; Irazoque, Glinda

1993-01-01

Discusses the development of fractal theory and suggests fractal aggregates as an attractive alternative for introducing fractal concepts. Describes methods for producing metallic fractals and a computer simulation for drawing fractals. (MVL)

Octree-based, GPU implementation of a continuous cellular automaton for the simulation of complex, evolving surfaces

NASA Astrophysics Data System (ADS)

Ferrando, N.; Gosálvez, M. A.; Cerdá, J.; Gadea, R.; Sato, K.

2011-03-01

Presently, dynamic surface-based models are required to contain increasingly larger numbers of points and to propagate them over longer time periods. For large numbers of surface points, the octree data structure can be used as a balance between low memory occupation and relatively rapid access to the stored data. For evolution rules that depend on neighborhood states, extended simulation periods can be obtained by using simplified atomistic propagation models, such as the Cellular Automata (CA). This method, however, has an intrinsic parallel updating nature and the corresponding simulations are highly inefficient when performed on classical Central Processing Units (CPUs), which are designed for the sequential execution of tasks. In this paper, a series of guidelines is presented for the efficient adaptation of octree-based, CA simulations of complex, evolving surfaces into massively parallel computing hardware. A Graphics Processing Unit (GPU) is used as a cost-efficient example of the parallel architectures. For the actual simulations, we consider the surface propagation during anisotropic wet chemical etching of silicon as a computationally challenging process with a wide-spread use in microengineering applications. A continuous CA model that is intrinsically parallel in nature is used for the time evolution. Our study strongly indicates that parallel computations of dynamically evolving surfaces simulated using CA methods are significantly benefited by the incorporation of octrees as support data structures, substantially decreasing the overall computational time and memory usage.

Numerical simulation on the adaptation of forms in trabecular bone to mechanical disuse and basic multi-cellular unit activation threshold at menopause

NASA Astrophysics Data System (ADS)

Gong, He; Fan, Yubo; Zhang, Ming

2008-04-01

The objective of this paper is to identify the effects of mechanical disuse and basic multi-cellular unit (BMU) activation threshold on the form of trabecular bone during menopause. A bone adaptation model with mechanical- biological factors at BMU level was integrated with finite element analysis to simulate the changes of trabecular bone structure during menopause. Mechanical disuse and changes in the BMU activation threshold were applied to the model for the period from 4 years before to 4 years after menopause. The changes in bone volume fraction, trabecular thickness and fractal dimension of the trabecular structures were used to quantify the changes of trabecular bone in three different cases associated with mechanical disuse and BMU activation threshold. It was found that the changes in the simulated bone volume fraction were highly correlated and consistent with clinical data, and that the trabecular thickness reduced significantly during menopause and was highly linearly correlated with the bone volume fraction, and that the change trend of fractal dimension of the simulated trabecular structure was in correspondence with clinical observations. The numerical simulation in this paper may help to better understand the relationship between the bone morphology and the mechanical, as well as biological environment; and can provide a quantitative computational model and methodology for the numerical simulation of the bone structural morphological changes caused by the mechanical environment, and/or the biological environment.

WESTPA: An interoperable, highly scalable software package for weighted ensemble simulation and analysis

PubMed Central

Zwier, Matthew C.; Adelman, Joshua L.; Kaus, Joseph W.; Pratt, Adam J.; Wong, Kim F.; Rego, Nicholas B.; Suárez, Ernesto; Lettieri, Steven; Wang, David W.; Grabe, Michael; Zuckerman, Daniel M.; Chong, Lillian T.

2015-01-01

The weighted ensemble (WE) path sampling approach orchestrates an ensemble of parallel calculations with intermittent communication to enhance the sampling of rare events, such as molecular associations or conformational changes in proteins or peptides. Trajectories are replicated and pruned in a way that focuses computational effort on under-explored regions of configuration space while maintaining rigorous kinetics. To enable the simulation of rare events at any scale (e.g. atomistic, cellular), we have developed an open-source, interoperable, and highly scalable software package for the execution and analysis of WE simulations: WESTPA (The Weighted Ensemble Simulation Toolkit with Parallelization and Analysis). WESTPA scales to thousands of CPU cores and includes a suite of analysis tools that have been implemented in a massively parallel fashion. The software has been designed to interface conveniently with any dynamics engine and has already been used with a variety of molecular dynamics (e.g. GROMACS, NAMD, OpenMM, AMBER) and cell-modeling packages (e.g. BioNetGen, MCell). WESTPA has been in production use for over a year, and its utility has been demonstrated for a broad set of problems, ranging from atomically detailed host-guest associations to non-spatial chemical kinetics of cellular signaling networks. The following describes the design and features of WESTPA, including the facilities it provides for running WE simulations, storing and analyzing WE simulation data, as well as examples of input and output. PMID:26392815

Urban Ecological Security Simulation and Prediction Using an Improved Cellular Automata (CA) Approach—A Case Study for the City of Wuhan in China

PubMed Central

Gao, Yuan; Zhang, Chuanrong; He, Qingsong; Liu, Yaolin

2017-01-01

Ecological security is an important research topic, especially urban ecological security. As highly populated eco-systems, cities always have more fragile ecological environments. However, most of the research on urban ecological security in literature has focused on evaluating current or past status of the ecological environment. Very little literature has carried out simulation or prediction of future ecological security. In addition, there is even less literature exploring the urban ecological environment at a fine scale. To fill-in the literature gap, in this study we simulated and predicted urban ecological security at a fine scale (district level) using an improved Cellular Automata (CA) approach. First we used the pressure-state-response (PSR) method based on grid-scale data to evaluate urban ecological security. Then, based on the evaluation results, we imported the geographically weighted regression (GWR) concept into the CA model to simulate and predict urban ecological security. We applied the improved CA approach in a case study—simulating and predicting urban ecological security for the city of Wuhan in Central China. By comparing the simulated ecological security values from 2010 using the improved CA model to the actual ecological security values of 2010, we got a relatively high value of the kappa coefficient, which indicates that this CA model can simulate or predict well future development of ecological security in Wuhan. Based on the prediction results for 2020, we made some policy recommendations for each district in Wuhan. PMID:28617348

Biomechanical simulation of thorax deformation using finite element approach.

PubMed

Zhang, Guangzhi; Chen, Xian; Ohgi, Junji; Miura, Toshiro; Nakamoto, Akira; Matsumura, Chikanori; Sugiura, Seiryo; Hisada, Toshiaki

2016-02-06

The biomechanical simulation of the human respiratory system is expected to be a useful tool for the diagnosis and treatment of respiratory diseases. Because the deformation of the thorax significantly influences airflow in the lungs, we focused on simulating the thorax deformation by introducing contraction of the intercostal muscles and diaphragm, which are the main muscles responsible for the thorax deformation during breathing. We constructed a finite element model of the thorax, including the rib cage, intercostal muscles, and diaphragm. To reproduce the muscle contractions, we introduced the Hill-type transversely isotropic hyperelastic continuum skeletal muscle model, which allows the intercostal muscles and diaphragm to contract along the direction of the fibres with clinically measurable muscle activation and active force-length relationship. The anatomical fibre orientations of the intercostal muscles and diaphragm were introduced. Thorax deformation consists of movements of the ribs and diaphragm. By activating muscles, we were able to reproduce the pump-handle and bucket-handle motions for the ribs and the clinically observed motion for the diaphragm. In order to confirm the effectiveness of this approach, we simulated the thorax deformation during normal quiet breathing and compared the results with four-dimensional computed tomography (4D-CT) images for verification. Thorax deformation can be simulated by modelling the respiratory muscles according to continuum mechanics and by introducing muscle contractions. The reproduction of representative motions of the ribs and diaphragm and the comparison of the thorax deformations during normal quiet breathing with 4D-CT images demonstrated the effectiveness of the proposed approach. This work may provide a platform for establishing a computational mechanics model of the human respiratory system.

Using exploratory regression to identify optimal driving factors for cellular automaton modeling of land use change.

PubMed

Feng, Yongjiu; Tong, Xiaohua

2017-09-22

Defining transition rules is an important issue in cellular automaton (CA)-based land use modeling because these models incorporate highly correlated driving factors. Multicollinearity among correlated driving factors may produce negative effects that must be eliminated from the modeling. Using exploratory regression under pre-defined criteria, we identified all possible combinations of factors from the candidate factors affecting land use change. Three combinations that incorporate five driving factors meeting pre-defined criteria were assessed. With the selected combinations of factors, three logistic regression-based CA models were built to simulate dynamic land use change in Shanghai, China, from 2000 to 2015. For comparative purposes, a CA model with all candidate factors was also applied to simulate the land use change. Simulations using three CA models with multicollinearity eliminated performed better (with accuracy improvements about 3.6%) than the model incorporating all candidate factors. Our results showed that not all candidate factors are necessary for accurate CA modeling and the simulations were not sensitive to changes in statistically non-significant driving factors. We conclude that exploratory regression is an effective method to search for the optimal combinations of driving factors, leading to better land use change models that are devoid of multicollinearity. We suggest identification of dominant factors and elimination of multicollinearity before building land change models, making it possible to simulate more realistic outcomes.