A simple electric circuit model for proton exchange membrane fuel cells

NASA Astrophysics Data System (ADS)

Lazarou, Stavros; Pyrgioti, Eleftheria; Alexandridis, Antonio T.

A simple and novel dynamic circuit model for a proton exchange membrane (PEM) fuel cell suitable for the analysis and design of power systems is presented. The model takes into account phenomena like activation polarization, ohmic polarization, and mass transport effect present in a PEM fuel cell. The proposed circuit model includes three resistors to approach adequately these phenomena; however, since for the PEM dynamic performance connection or disconnection of an additional load is of crucial importance, the proposed model uses two saturable inductors accompanied by an ideal transformer to simulate the double layer charging effect during load step changes. To evaluate the effectiveness of the proposed model its dynamic performance under load step changes is simulated. Experimental results coming from a commercial PEM fuel cell module that uses hydrogen from a pressurized cylinder at the anode and atmospheric oxygen at the cathode, clearly verify the simulation results.

An operating principle of the turtle utricle to detect wide dynamic range.

PubMed

Nam, Jong-Hoon

2018-03-01

The utricle encodes both static information such as head orientation, and dynamic information such as vibrations. It is not well understood how the utricle can encode both static and dynamic information for a wide dynamic range (from <0.05 to >2 times the gravitational acceleration; from DC to > 1000 Hz vibrations). Using computational models of the hair cells in the turtle utricle, this study presents an explanation on how the turtle utricle encodes stimulations over such a wide dynamic range. Two hair bundles were modeled using the finite element method-one representing the striolar hair cell (Cell S), and the other representing the medial extrastriolar hair cell (Cell E). A mechano-transduction (MET) channel model was incorporated to compute MET current (i MET ) due to hair bundle deflection. A macro-mechanical model of the utricle was used to compute otoconial motions from head accelerations (a Head ). According to known anatomical data, Cell E has a long kinocilium that is embedded into the stiff otoconial layer. Unlike Cell E, the hair bundle of Cell S falls short of the otoconial layer. Considering such difference in the mechanical connectivity between the hair cell bundle and the otoconial layer, three cases were simulated: Cell E displacement-clamped, Cell S viscously-coupled, and Cell S displacement-clamped. Head accelerations at different amplitude levels and different frequencies were simulated for the three cases. When a realistic head motion was simulated, Cell E was responsive to head orientation, while the viscously-coupled Cell S was responsive to fast head motion imitating the feeding strike of a turtle. Copyright © 2017 Elsevier B.V. All rights reserved.

Information flow and protein dynamics: the interplay between nuclear magnetic resonance spectroscopy and molecular dynamics simulations

PubMed Central

Pastor, Nina; Amero, Carlos

2015-01-01

Proteins participate in information pathways in cells, both as links in the chain of signals, and as the ultimate effectors. Upon ligand binding, proteins undergo conformation and motion changes, which can be sensed by the following link in the chain of information. Nuclear magnetic resonance (NMR) spectroscopy and molecular dynamics (MD) simulations represent powerful tools for examining the time-dependent function of biological molecules. The recent advances in NMR and the availability of faster computers have opened the door to more detailed analyses of structure, dynamics, and interactions. Here we briefly describe the recent applications that allow NMR spectroscopy and MD simulations to offer unique insight into the basic motions that underlie information transfer within and between cells. PMID:25999971

GPU-accelerated Red Blood Cells Simulations with Transport Dissipative Particle Dynamics.

PubMed

Blumers, Ansel L; Tang, Yu-Hang; Li, Zhen; Li, Xuejin; Karniadakis, George E

2017-08-01

Mesoscopic numerical simulations provide a unique approach for the quantification of the chemical influences on red blood cell functionalities. The transport Dissipative Particles Dynamics (tDPD) method can lead to such effective multiscale simulations due to its ability to simultaneously capture mesoscopic advection, diffusion, and reaction. In this paper, we present a GPU-accelerated red blood cell simulation package based on a tDPD adaptation of our red blood cell model, which can correctly recover the cell membrane viscosity, elasticity, bending stiffness, and cross-membrane chemical transport. The package essentially processes all computational workloads in parallel by GPU, and it incorporates multi-stream scheduling and non-blocking MPI communications to improve inter-node scalability. Our code is validated for accuracy and compared against the CPU counterpart for speed. Strong scaling and weak scaling are also presented to characterizes scalability. We observe a speedup of 10.1 on one GPU over all 16 cores within a single node, and a weak scaling efficiency of 91% across 256 nodes. The program enables quick-turnaround and high-throughput numerical simulations for investigating chemical-driven red blood cell phenomena and disorders.

HIV dynamics linked to memory CD4+ T cell homeostasis.

PubMed

Murray, John M; Zaunders, John; Emery, Sean; Cooper, David A; Hey-Nguyen, William J; Koelsch, Kersten K; Kelleher, Anthony D

2017-01-01

The dynamics of latent HIV is linked to infection and clearance of resting memory CD4+ T cells. Infection also resides within activated, non-dividing memory cells and can be impacted by antigen-driven and homeostatic proliferation despite suppressive antiretroviral therapy (ART). We investigated whether plasma viral level (pVL) and HIV DNA dynamics could be explained by HIV's impact on memory CD4+ T cell homeostasis. Median total, 2-LTR and integrated HIV DNA levels per μL of peripheral blood, for 8 primary (PHI) and 8 chronic HIV infected (CHI) individuals enrolled on a raltegravir (RAL) based regimen, exhibited greatest changes over the 1st year of ART. Dynamics slowed over the following 2 years so that total HIV DNA levels were equivalent to reported values for individuals after 10 years of ART. The mathematical model reproduced the multiphasic dynamics of pVL, and levels of total, 2-LTR and integrated HIV DNA in both PHI and CHI over 3 years of ART. Under these simulations, residual viremia originated from reactivated latently infected cells where most of these cells arose from clonal expansion within the resting phenotype. Since virion production from clonally expanded cells will not be affected by antiretroviral drugs, simulations of ART intensification had little impact on pVL. HIV DNA decay over the first year of ART followed the loss of activated memory cells (120 day half-life) while the 5.9 year half-life of total HIV DNA after this point mirrored the slower decay of resting memory cells. Simulations had difficulty reproducing the fast early HIV DNA dynamics, including 2-LTR levels peaking at week 12, and the later slow loss of total and 2-LTR HIV DNA, suggesting some ongoing infection. In summary, our modelling indicates that much of the dynamical behavior of HIV can be explained by its impact on memory CD4+ T cell homeostasis.

Three-dimensional simulation of pseudopod-driven swimming of amoeboid cells

NASA Astrophysics Data System (ADS)

Campbell, Eric; Bagchi, Prosenjit

2016-11-01

Pseudopod-driven locomotion is common in eukaryotic cells, such as amoeba, neutrophils, and cancer cells. Pseudopods are protrusions of the cell body that grow, bifurcate, and retract. Due to the dynamic nature of pseudopods, the shape of a motile cell constantly changes. The actin-myosin protein dynamics is a likely mechanism for pseudopod growth. Existing theoretical models often focus on the acto-myosin dynamics, and not the whole cell shape dynamics. Here we present a full 3D simulation of pseudopod-driven motility by coupling a surface-bound reaction-diffusion (RD) model for the acto-myosin dynamics, a continuum model for the cell membrane deformation, and flow of the cytoplasmic and extracellular fluids. The whole cell is represented as a viscous fluid surrounded by a membrane. A finite-element method is used to solve the membrane deformation, and the RD model on the deforming membrane, while a finite-difference/spectral method is used to solve the flow fields inside and outside the cell. The fluid flow and cell deformation are coupled by the immersed-boundary method. The model predicts pseudopod growth, bifurcation, and retraction as observed for a swimming amoeba. The work provides insights on the role of membrane stiffness and cytoplasmic viscosity on amoeboid swimming. Funded by NSF CBET 1438255.

Peptide crystal simulations reveal hidden dynamics

PubMed Central

Janowski, Pawel A.; Cerutti, David S.; Holton, James; Case, David A.

2013-01-01

Molecular dynamics simulations of biomolecular crystals at atomic resolution have the potential to recover information on dynamics and heterogeneity hidden in the X-ray diffraction data. We present here 9.6 microseconds of dynamics in a small helical peptide crystal with 36 independent copies of the unit cell. The average simulation structure agrees with experiment to within 0.28 Å backbone and 0.42 Å all-atom rmsd; a model refined against the average simulation density agrees with the experimental structure to within 0.20 Å backbone and 0.33 Å all-atom rmsd. The R-factor between the experimental structure factors and those derived from this unrestrained simulation is 23% to 1.0 Å resolution. The B-factors for most heavy atoms agree well with experiment (Pearson correlation of 0.90), but B-factors obtained by refinement against the average simulation density underestimate the coordinate fluctuations in the underlying simulation where the simulation samples alternate conformations. A dynamic flow of water molecules through channels within the crystal lattice is observed, yet the average water density is in remarkable agreement with experiment. A minor population of unit cells is characterized by reduced water content, 310 helical propensity and a gauche(−) side-chain rotamer for one of the valine residues. Careful examination of the experimental data suggests that transitions of the helices are a simulation artifact, although there is indeed evidence for alternate valine conformers and variable water content. This study highlights the potential for crystal simulations to detect dynamics and heterogeneity in experimental diffraction data, as well as to validate computational chemistry methods. PMID:23631449

Actin cable distribution and dynamics arising from cross-linking, motor pulling, and filament turnover

PubMed Central

Tang, Haosu; Laporte, Damien; Vavylonis, Dimitrios

2014-01-01

The growth of fission yeast relies on the polymerization of actin filaments nucleated by formin For3p, which localizes at tip cortical sites. These actin filaments bundle to form actin cables that span the cell and guide the movement of vesicles toward the cell tips. A big challenge is to develop a quantitative understanding of these cellular actin structures. We used computer simulations to study the spatial and dynamical properties of actin cables. We simulated individual actin filaments as semiflexible polymers in three dimensions composed of beads connected with springs. Polymerization out of For3p cortical sites, bundling by cross-linkers, pulling by type V myosin, and severing by cofilin are simulated as growth, cross-linking, pulling, and turnover of the semiflexible polymers. With the foregoing mechanisms, the model generates actin cable structures and dynamics similar to those observed in live-cell experiments. Our simulations reproduce the particular actin cable structures in myoVΔ cells and predict the effect of increased myosin V pulling. Increasing cross-linking parameters generates thicker actin cables. It also leads to antiparallel and parallel phases with straight or curved cables, consistent with observations of cells overexpressing α-actinin. Finally, the model predicts that clustering of formins at cell tips promotes actin cable formation. PMID:25103242

Computer simulation of the processes of inactivation of bacterial cells by dynamic low-coherent speckles

NASA Astrophysics Data System (ADS)

Ulianova, Onega V.; Ulyanov, Sergey S.; Sazanova, Elena V.; Zhihong, Zhang; Sibo, Zhou; Luo, Qingming; Zudina, Irina; Bednov, Andrey

2006-05-01

Biochemical, biophysical and optical aspects of interaction of low-coherent light with bacterial cells have been discussed. Influence of low-coherent speckles on the colonies grows is investigated. It has been demonstrated that effects of light on the inhibition of cells (Francisella Tularensis) are connected with speckle dynamics. The regimes of illumination of cell suspension with purpose of devitalization of hazard bacteria, caused very dangerous infections, such as tularemia, are found. Mathematical model of interaction of low-coherent laser radiation with bacteria suspension has been proposed. Computer simulations of the processes of laser-cells interaction have been carried out.

A hybrid computational model to explore the topological characteristics of epithelial tissues.

PubMed

González-Valverde, Ismael; García-Aznar, José Manuel

2017-11-01

Epithelial tissues show a particular topology where cells resemble a polygon-like shape, but some biological processes can alter this tissue topology. During cell proliferation, mitotic cell dilation deforms the tissue and modifies the tissue topology. Additionally, cells are reorganized in the epithelial layer and these rearrangements also alter the polygon distribution. We present here a computer-based hybrid framework focused on the simulation of epithelial layer dynamics that combines discrete and continuum numerical models. In this framework, we consider topological and mechanical aspects of the epithelial tissue. Individual cells in the tissue are simulated by an off-lattice agent-based model, which keeps the information of each cell. In addition, we model the cell-cell interaction forces and the cell cycle. Otherwise, we simulate the passive mechanical behaviour of the cell monolayer using a material that approximates the mechanical properties of the cell. This continuum approach is solved by the finite element method, which uses a dynamic mesh generated by the triangulation of cell polygons. Forces generated by cell-cell interaction in the agent-based model are also applied on the finite element mesh. Cell movement in the agent-based model is driven by the displacements obtained from the deformed finite element mesh of the continuum mechanical approach. We successfully compare the results of our simulations with some experiments about the topology of proliferating epithelial tissues in Drosophila. Our framework is able to model the emergent behaviour of the cell monolayer that is due to local cell-cell interactions, which have a direct influence on the dynamics of the epithelial tissue. Copyright © 2017 John Wiley & Sons, Ltd.

Evaluation Program for Secondary Spacecraft Cells: Initial Evaluation Tests of General Electric Company 6.0 Ampere Hour Nickel Cadmium Spacecraft Cells for the Dynamic Explorer Satellite Program

NASA Technical Reports Server (NTRS)

Harkness, J. D.

1980-01-01

Evaluation tests of 10 nickel cadmium cells are described. Although pressures were greater than what normally was exhibited by General Electric cells in the past, it is recommended that these cells be placed on life test simulating the predicted Dynamic Explorer flight profiles.

A Computational Approach for Modeling Neutron Scattering Data from Lipid Bilayers

DOE PAGES

Carrillo, Jan-Michael Y.; Katsaras, John; Sumpter, Bobby G.; ...

2017-01-12

Biological cell membranes are responsible for a range of structural and dynamical phenomena crucial to a cell's well-being and its associated functions. Due to the complexity of cell membranes, lipid bilayer systems are often used as biomimetic models. These systems have led to signficant insights into vital membrane phenomena such as domain formation, passive permeation and protein insertion. Experimental observations of membrane structure and dynamics are, however, limited in resolution, both spatially and temporally. Importantly, computer simulations are starting to play a more prominent role in interpreting experimental results, enabling a molecular under- standing of lipid membranes. Particularly, the synergymore » between scattering experiments and simulations offers opportunities for new discoveries in membrane physics, as the length and time scales probed by molecular dynamics (MD) simulations parallel those of experiments. We also describe a coarse-grained MD simulation approach that mimics neutron scattering data from large unilamellar lipid vesicles over a range of bilayer rigidity. Specfically, we simulate vesicle form factors and membrane thickness fluctuations determined from small angle neutron scattering (SANS) and neutron spin echo (NSE) experiments, respectively. Our simulations accurately reproduce trends from experiments and lay the groundwork for investigations of more complex membrane systems.« less

Degradation modeling of high temperature proton exchange membrane fuel cells using dual time scale simulation

NASA Astrophysics Data System (ADS)

Pohl, E.; Maximini, M.; Bauschulte, A.; vom Schloß, J.; Hermanns, R. T. E.

2015-02-01

HT-PEM fuel cells suffer from performance losses due to degradation effects. Therefore, the durability of HT-PEM is currently an important factor of research and development. In this paper a novel approach is presented for an integrated short term and long term simulation of HT-PEM accelerated lifetime testing. The physical phenomena of short term and long term effects are commonly modeled separately due to the different time scales. However, in accelerated lifetime testing, long term degradation effects have a crucial impact on the short term dynamics. Our approach addresses this problem by applying a novel method for dual time scale simulation. A transient system simulation is performed for an open voltage cycle test on a HT-PEM fuel cell for a physical time of 35 days. The analysis describes the system dynamics by numerical electrochemical impedance spectroscopy. Furthermore, a performance assessment is performed in order to demonstrate the efficiency of the approach. The presented approach reduces the simulation time by approximately 73% compared to conventional simulation approach without losing too much accuracy. The approach promises a comprehensive perspective considering short term dynamic behavior and long term degradation effects.

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

Dynamic and rheological properties of soft biological cell suspensions

PubMed Central

Yazdani, Alireza; Li, Xuejin

2016-01-01

Quantifying dynamic and rheological properties of suspensions of soft biological particles such as vesicles, capsules, and red blood cells (RBCs) is fundamentally important in computational biology and biomedical engineering. In this review, recent studies on dynamic and rheological behavior of soft biological cell suspensions by computer simulations are presented, considering both unbounded and confined shear flow. Furthermore, the hemodynamic and hemorheological characteristics of RBCs in diseases such as malaria and sickle cell anemia are highlighted. PMID:27540271

Relation Between the Cell Volume and the Cell Cycle Dynamics in Mammalian cell

NASA Astrophysics Data System (ADS)

Magno, A. C. G.; Oliveira, I. L.; Hauck, J. V. S.

2016-08-01

The main goal of this work is to add and analyze an equation that represents the volume in a dynamical model of the mammalian cell cycle proposed by Gérard and Goldbeter (2011) [1]. The cell division occurs when the cyclinB/Cdkl complex is totally degraded (Tyson and Novak, 2011)[2] and it reaches a minimum value. At this point, the cell is divided into two newborn daughter cells and each one will contain the half of the cytoplasmic content of the mother cell. The equations of our base model are only valid if the cell volume, where the reactions occur, is constant. Whether the cell volume is not constant, that is, the rate of change of its volume with respect to time is explicitly taken into account in the mathematical model, then the equations of the original model are no longer valid. Therefore, every equations were modified from the mass conservation principle for considering a volume that changes with time. Through this approach, the cell volume affects all model variables. Two different dynamic simulation methods were accomplished: deterministic and stochastic. In the stochastic simulation, the volume affects every model's parameters which have molar unit, whereas in the deterministic one, it is incorporated into the differential equations. In deterministic simulation, the biochemical species may be in concentration units, while in stochastic simulation such species must be converted to number of molecules which are directly proportional to the cell volume. In an effort to understand the influence of the new equation a stability analysis was performed. This elucidates how the growth factor impacts the stability of the model's limit cycles. In conclusion, a more precise model, in comparison to the base model, was created for the cell cycle as it now takes into consideration the cell volume variation

The effect of crystallinity on cell growth in semi-crystalline microcellular foams by solid-state process: modeling and numerical simulation

NASA Astrophysics Data System (ADS)

Rezvanpanah, Elham; Ghaffarian Anbaran, S. Reza

2017-11-01

This study establishes a model and simulation scheme to describe the effect of crystallinity as one of the most effective parameters on cell growth phenomena in a solid batch foaming process. The governing model of cell growth dynamics, based on the well-known ‘Cell model’, is attained in details. To include the effect of crystallinity in the model, the properties of the polymer/gas mixtures (i.e. solubility, diffusivity, surface tension and viscosity) are estimated by modifying relations to consider the effect of crystallinity. A finite element-finite difference (FEFD) method is employed to solve the highly nonlinear and coupled equations of cell growth dynamics. The proposed simulation is able to evaluate all properties of the system at the given process condition and uses them to calculate the cell size, pressure and gas concentration gradient with time. A high-density polyethylene/nitrogen (HDPE/N2) system is used herein as a case study. Comparing the simulation results with the others works and experimental results verify the accuracy of the simulation scheme. The cell growth is a complicated combination of several phenomena. This study attempted to reach a better understanding of cell growth trend, driving and retarding forces and the effect of crystallinity on them.

Accelerating molecular dynamic simulation on the cell processor and Playstation 3.

PubMed

Luttmann, Edgar; Ensign, Daniel L; Vaidyanathan, Vishal; Houston, Mike; Rimon, Noam; Øland, Jeppe; Jayachandran, Guha; Friedrichs, Mark; Pande, Vijay S

2009-01-30

Implementation of molecular dynamics (MD) calculations on novel architectures will vastly increase its power to calculate the physical properties of complex systems. Herein, we detail algorithmic advances developed to accelerate MD simulations on the Cell processor, a commodity processor found in PlayStation 3 (PS3). In particular, we discuss issues regarding memory access versus computation and the types of calculations which are best suited for streaming processors such as the Cell, focusing on implicit solvation models. We conclude with a comparison of improved performance on the PS3's Cell processor over more traditional processors. (c) 2008 Wiley Periodicals, Inc.

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

Using computer simulations to determine the limitations of dynamic clamp stimuli applied at the soma in mimicking distributed conductance sources.

PubMed

Lin, Risa J; Jaeger, Dieter

2011-05-01

In previous studies we used the technique of dynamic clamp to study how temporal modulation of inhibitory and excitatory inputs control the frequency and precise timing of spikes in neurons of the deep cerebellar nuclei (DCN). Although this technique is now widely used, it is limited to interpreting conductance inputs as being location independent; i.e., all inputs that are biologically distributed across the dendritic tree are applied to the soma. We used computer simulations of a morphologically realistic model of DCN neurons to compare the effects of purely somatic vs. distributed dendritic inputs in this cell type. We applied the same conductance stimuli used in our published experiments to the model. To simulate variability in neuronal responses to repeated stimuli, we added a somatic white current noise to reproduce subthreshold fluctuations in the membrane potential. We were able to replicate our dynamic clamp results with respect to spike rates and spike precision for different patterns of background synaptic activity. We found only minor differences in the spike pattern generation between focal or distributed input in this cell type even when strong inhibitory or excitatory bursts were applied. However, the location dependence of dynamic clamp stimuli is likely to be different for each cell type examined, and the simulation approach developed in the present study will allow a careful assessment of location dependence in all cell types.

Internal protein motions in molecular-dynamics simulations of Bragg and diffuse X-ray scattering.

PubMed

Wall, Michael E

2018-03-01

Molecular-dynamics (MD) simulations of Bragg and diffuse X-ray scattering provide a means of obtaining experimentally validated models of protein conformational ensembles. This paper shows that compared with a single periodic unit-cell model, the accuracy of simulating diffuse scattering is increased when the crystal is modeled as a periodic supercell consisting of a 2 × 2 × 2 layout of eight unit cells. The MD simulations capture the general dependence of correlations on the separation of atoms. There is substantial agreement between the simulated Bragg reflections and the crystal structure; there are local deviations, however, indicating both the limitation of using a single structure to model disordered regions of the protein and local deviations of the average structure away from the crystal structure. Although it was anticipated that a simulation of longer duration might be required to achieve maximal agreement of the diffuse scattering calculation with the data using the supercell model, only a microsecond is required, the same as for the unit cell. Rigid protein motions only account for a minority fraction of the variation in atom positions from the simulation. The results indicate that protein crystal dynamics may be dominated by internal motions rather than packing interactions, and that MD simulations can be combined with Bragg and diffuse X-ray scattering to model the protein conformational ensemble.

Internal protein motions in molecular-dynamics simulations of Bragg and diffuse X-ray scattering

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

Wall, Michael E.

Molecular-dynamics (MD) simulations of Bragg and diffuse X-ray scattering provide a means of obtaining experimentally validated models of protein conformational ensembles. This paper shows that compared with a single periodic unit-cell model, the accuracy of simulating diffuse scattering is increased when the crystal is modeled as a periodic supercell consisting of a 2 × 2 × 2 layout of eight unit cells. The MD simulations capture the general dependence of correlations on the separation of atoms. There is substantial agreement between the simulated Bragg reflections and the crystal structure; there are local deviations, however, indicating both the limitation of using a single structuremore » to model disordered regions of the protein and local deviations of the average structure away from the crystal structure. Although it was anticipated that a simulation of longer duration might be required to achieve maximal agreement of the diffuse scattering calculation with the data using the supercell model, only a microsecond is required, the same as for the unit cell. Rigid protein motions only account for a minority fraction of the variation in atom positions from the simulation. The results indicate that protein crystal dynamics may be dominated by internal motions rather than packing interactions, and that MD simulations can be combined with Bragg and diffuse X-ray scattering to model the protein conformational ensemble.« less

Internal protein motions in molecular-dynamics simulations of Bragg and diffuse X-ray scattering

DOE PAGES

Wall, Michael E.

2018-01-25

Molecular-dynamics (MD) simulations of Bragg and diffuse X-ray scattering provide a means of obtaining experimentally validated models of protein conformational ensembles. This paper shows that compared with a single periodic unit-cell model, the accuracy of simulating diffuse scattering is increased when the crystal is modeled as a periodic supercell consisting of a 2 × 2 × 2 layout of eight unit cells. The MD simulations capture the general dependence of correlations on the separation of atoms. There is substantial agreement between the simulated Bragg reflections and the crystal structure; there are local deviations, however, indicating both the limitation of using a single structuremore » to model disordered regions of the protein and local deviations of the average structure away from the crystal structure. Although it was anticipated that a simulation of longer duration might be required to achieve maximal agreement of the diffuse scattering calculation with the data using the supercell model, only a microsecond is required, the same as for the unit cell. Rigid protein motions only account for a minority fraction of the variation in atom positions from the simulation. The results indicate that protein crystal dynamics may be dominated by internal motions rather than packing interactions, and that MD simulations can be combined with Bragg and diffuse X-ray scattering to model the protein conformational ensemble.« less

Modeling and Simulation With Operational Databases to Enable Dynamic Situation Assessment & Prediction

DTIC Science & Technology

2010-11-01

subsections discuss the design of the simulations. 3.12.1 Lanchester5D Simulation A Lanchester simulation was developed to conduct performance...benchmarks using the WarpIV Kernel and HyperWarpSpeed. The Lanchester simulation contains a user-definable number of grid cells in which blue and red...forces engage in battle using Lanchester equations. Having a user-definable number of grid cells enables the simulation to be stressed with high entity

Modeling universal dynamics of cell spreading on elastic substrates.

PubMed

Fan, Houfu; Li, Shaofan

2015-11-01

A three-dimensional (3D) multiscale moving contact line model is combined with a soft matter cell model to study the universal dynamics of cell spreading over elastic substrates. We have studied both the early stage and the late stage cell spreading by taking into account the actin tension effect. In this work, the cell is modeled as an active nematic droplet, and the substrate is modeled as a St. Venant Kirchhoff elastic medium. A complete 3D simulation of cell spreading has been carried out. The simulation results show that the spreading area versus spreading time at different stages obeys specific power laws, which is in good agreement with experimental data and theoretical prediction reported in the literature. Moreover, the simulation results show that the substrate elasticity may affect force dipole distribution inside the cell. The advantage of this approach is that it combines the hydrodynamics of actin retrograde flow with moving contact line model so that it can naturally include actin tension effect resulting from actin polymerization and actomyosin contraction, and thus it might be capable of simulating complex cellular scale phenomenon, such as cell spreading or even crawling.

Analysis of l-glutamic acid fermentation by using a dynamic metabolic simulation model of Escherichia coli

PubMed Central

2013-01-01

Background Understanding the process of amino acid fermentation as a comprehensive system is a challenging task. Previously, we developed a literature-based dynamic simulation model, which included transcriptional regulation, transcription, translation, and enzymatic reactions related to glycolysis, the pentose phosphate pathway, the tricarboxylic acid (TCA) cycle, and the anaplerotic pathway of Escherichia coli. During simulation, cell growth was defined such as to reproduce the experimental cell growth profile of fed-batch cultivation in jar fermenters. However, to confirm the biological appropriateness of our model, sensitivity analysis and experimental validation were required. Results We constructed an l-glutamic acid fermentation simulation model by removing sucAB, a gene encoding α-ketoglutarate dehydrogenase. We then performed systematic sensitivity analysis for l-glutamic acid production; the results of this process corresponded with previous experimental data regarding l-glutamic acid fermentation. Furthermore, it allowed us to predicted the possibility that accumulation of 3-phosphoglycerate in the cell would regulate the carbon flux into the TCA cycle and lead to an increase in the yield of l-glutamic acid via fermentation. We validated this hypothesis through a fermentation experiment involving a model l-glutamic acid-production strain, E. coli MG1655 ΔsucA in which the phosphoglycerate kinase gene had been amplified to cause accumulation of 3-phosphoglycerate. The observed increase in l-glutamic acid production verified the biologically meaningful predictive power of our dynamic metabolic simulation model. Conclusions In this study, dynamic simulation using a literature-based model was shown to be useful for elucidating the precise mechanisms involved in fermentation processes inside the cell. Further exhaustive sensitivity analysis will facilitate identification of novel factors involved in the metabolic regulation of amino acid fermentation. PMID:24053676

Analysis of L-glutamic acid fermentation by using a dynamic metabolic simulation model of Escherichia coli.

PubMed

Nishio, Yousuke; Ogishima, Soichi; Ichikawa, Masao; Yamada, Yohei; Usuda, Yoshihiro; Masuda, Tadashi; Tanaka, Hiroshi

2013-09-22

Understanding the process of amino acid fermentation as a comprehensive system is a challenging task. Previously, we developed a literature-based dynamic simulation model, which included transcriptional regulation, transcription, translation, and enzymatic reactions related to glycolysis, the pentose phosphate pathway, the tricarboxylic acid (TCA) cycle, and the anaplerotic pathway of Escherichia coli. During simulation, cell growth was defined such as to reproduce the experimental cell growth profile of fed-batch cultivation in jar fermenters. However, to confirm the biological appropriateness of our model, sensitivity analysis and experimental validation were required. We constructed an L-glutamic acid fermentation simulation model by removing sucAB, a gene encoding α-ketoglutarate dehydrogenase. We then performed systematic sensitivity analysis for L-glutamic acid production; the results of this process corresponded with previous experimental data regarding L-glutamic acid fermentation. Furthermore, it allowed us to predicted the possibility that accumulation of 3-phosphoglycerate in the cell would regulate the carbon flux into the TCA cycle and lead to an increase in the yield of L-glutamic acid via fermentation. We validated this hypothesis through a fermentation experiment involving a model L-glutamic acid-production strain, E. coli MG1655 ΔsucA in which the phosphoglycerate kinase gene had been amplified to cause accumulation of 3-phosphoglycerate. The observed increase in L-glutamic acid production verified the biologically meaningful predictive power of our dynamic metabolic simulation model. In this study, dynamic simulation using a literature-based model was shown to be useful for elucidating the precise mechanisms involved in fermentation processes inside the cell. Further exhaustive sensitivity analysis will facilitate identification of novel factors involved in the metabolic regulation of amino acid fermentation.

A Linked-Cell Domain Decomposition Method for Molecular Dynamics Simulation on a Scalable Multiprocessor

DOE PAGES

Yang, L. H.; Brooks III, E. D.; Belak, J.

1992-01-01

A molecular dynamics algorithm for performing large-scale simulations using the Parallel C Preprocessor (PCP) programming paradigm on the BBN TC2000, a massively parallel computer, is discussed. The algorithm uses a linked-cell data structure to obtain the near neighbors of each atom as time evoles. Each processor is assigned to a geometric domain containing many subcells and the storage for that domain is private to the processor. Within this scheme, the interdomain (i.e., interprocessor) communication is minimized.

Molecular dynamics simulations of membrane proteins and their interactions: from nanoscale to mesoscale.

PubMed

Chavent, Matthieu; Duncan, Anna L; Sansom, Mark Sp

2016-10-01

Molecular dynamics simulations provide a computational tool to probe membrane proteins and systems at length scales ranging from nanometers to close to a micrometer, and on microsecond timescales. All atom and coarse-grained simulations may be used to explore in detail the interactions of membrane proteins and specific lipids, yielding predictions of lipid binding sites in good agreement with available structural data. Building on the success of protein-lipid interaction simulations, larger scale simulations reveal crowding and clustering of proteins, resulting in slow and anomalous diffusional dynamics, within realistic models of cell membranes. Current methods allow near atomic resolution simulations of small membrane organelles, and of enveloped viruses to be performed, revealing key aspects of their structure and functionally important dynamics. Copyright © 2016 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Development of Novel PEM Membrane and Multiphase CD Modeling of PEM Fuel Cell

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

K. J. Berry; Susanta Das

2009-12-30

To understand heat and water management phenomena better within an operational proton exchange membrane fuel cell's (PEMFC) conditions, a three-dimensional, two-phase computational fluid dynamic (CFD) flow model has been developed and simulated for a complete PEMFC. Both liquid and gas phases are considered in the model by taking into account the gas flow, diffusion, charge transfer, change of phase, electro-osmosis, and electrochemical reactions to understand the overall dynamic behaviors of species within an operating PEMFC. The CFD model is solved numerically under different parametric conditions in terms of water management issues in order to improve cell performance. The results obtainedmore » from the CFD two-phase flow model simulations show improvement in cell performance as well as water management under PEMFCs operational conditions as compared to the results of a single phase flow model available in the literature. The quantitative information obtained from the two-phase model simulation results helped to develop a CFD control algorithm for low temperature PEM fuel cell stacks which opens up a route in designing improvement of PEMFC for better operational efficiency and performance. To understand heat and water management phenomena better within an operational proton exchange membrane fuel cell's (PEMFC) conditions, a three-dimensional, two-phase computational fluid dynamic (CFD) flow model has been developed and simulated for a complete PEMFC. Both liquid and gas phases are considered in the model by taking into account the gas flow, diffusion, charge transfer, change of phase, electro-osmosis, and electrochemical reactions to understand the overall dynamic behaviors of species within an operating PEMFC. The CFD model is solved numerically under different parametric conditions in terms of water management issues in order to improve cell performance. The results obtained from the CFD two-phase flow model simulations show improvement in cell performance as well as water management under PEMFCs operational conditions as compared to the results of a single phase flow model available in the literature. The quantitative information obtained from the two-phase model simulation results helped to develop a CFD control algorithm for low temperature PEM fuel cell stacks which opens up a route in designing improvement of PEMFC for better operational efficiency and performance.« less

Simulations of the plasma dynamics in high-current ion diodes

NASA Astrophysics Data System (ADS)

Boine-Frankenheim, O.; Pointon, T. D.; Mehlhorn, T. A.

Our time-implicit fluid/Particle-In-Cell (PIC) code DYNAID [1]is applied to problems relevant for applied- B ion diode operation. We present simulations of the laser ion source, which will soon be employed on the SABRE accelerator at SNL, and of the dynamics of the anode source plasma in the applied electric and magnetic fields. DYNAID is still a test-bed for a higher-dimensional simulation code. Nevertheless, the code can already give new theoretical insight into the dynamics of plasmas in pulsed power devices.

Liquid crystal dynamic flow control by bidirectional alignment surface

NASA Astrophysics Data System (ADS)

Li, Y. W.; Lee, C. Y.; Kwok, H. S.

2009-02-01

We investigate the behavior of liquid crystal dynamic flow in a cell with a bidirectional alignment (BDA) surface. Numerical simulations show that with a BDA surface having a pitch comparable to the cell gap d, the liquid crystal dynamic flow direction can be controlled by the driving voltage. Such an effect can be applied to bistable twisted nematic displays without the need for anchoring breaking.

Peculiarities of Vibration Characteristics of Amorphous Ices

NASA Astrophysics Data System (ADS)

Gets, Kirill V.; Subbotin, Oleg S.; Belosludov, Vladimir R.

2012-03-01

Dynamic properties of low (LDA), high (HDA) and very high (VHDA) density amorphous ices were investigated within the approach based on Lattice Dynamics simulations. In this approach, we assume that the short-range molecular order mainly determines the dynamic and thermodynamic properties of amorphous ices. Simulation cell of 512 water molecules with periodical boundary conditions and disordering allows us to study dynamical properties and dispersion curves in the Brillouin zone of pseudo-crystal. Existence of collective phenomena in amorphous ices which is usual for crystals but anomalous for disordered phase was confirmed in our simulations. Molecule amplitudes of delocalized (collective) as well as localized vibrations have been considered.

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.

A comprehensive model of the spatio-temporal stem cell and tissue organisation in the intestinal crypt.

PubMed

Buske, Peter; Galle, Jörg; Barker, Nick; Aust, Gabriela; Clevers, Hans; Loeffler, Markus

2011-01-06

We introduce a novel dynamic model of stem cell and tissue organisation in murine intestinal crypts. Integrating the molecular, cellular and tissue level of description, this model links a broad spectrum of experimental observations encompassing spatially confined cell proliferation, directed cell migration, multiple cell lineage decisions and clonal competition.Using computational simulations we demonstrate that the model is capable of quantitatively describing and predicting the dynamic behaviour of the intestinal tissue during steady state as well as after cell damage and following selective gain or loss of gene function manipulations affecting Wnt- and Notch-signalling. Our simulation results suggest that reversibility and flexibility of cellular decisions are key elements of robust tissue organisation of the intestine. We predict that the tissue should be able to fully recover after complete elimination of cellular subpopulations including subpopulations deemed to be functional stem cells. This challenges current views of tissue stem cell organisation.

A mathematical model for mesenchymal and chemosensitive cell dynamics.

PubMed

Häcker, Anita

2012-01-01

The structure of an underlying tissue network has a strong impact on cell dynamics. If, in addition, cells alter the network by mechanical and chemical interactions, their movement is called mesenchymal. Important examples for mesenchymal movement include fibroblasts in wound healing and metastatic tumour cells. This paper is focused on the latter. Based on the anisotropic biphasic theory of Barocas and Tranquillo, which models a fibre network and interstitial solution as two-component fluid, a mathematical model for the interactions of cells with a fibre network is developed. A new description for fibre reorientation is given and orientation-dependent proteolysis is added to the model. With respect to cell dynamics, the equation, based on anisotropic diffusion, is extended by haptotaxis and chemotaxis. The chemoattractants are the solute network fragments, emerging from proteolysis, and the epidermal growth factor which may guide the cells to a blood vessel. Moreover the cell migration is impeded at either high or low network density. This new model enables us to study chemotactic cell migration in a complex fibre network and the consequential network deformation. Numerical simulations for the cell migration and network deformation are carried out in two space dimensions. Simulations of cell migration in underlying tissue networks visualise the impact of the network structure on cell dynamics. In a scenario for fibre reorientation between cell clusters good qualitative agreement with experimental results is achieved. The invasion speeds of cells in an aligned and an isotropic fibre network are compared. © Springer-Verlag 2011

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

Vassilevska, Tanya

This is the first code, designed to run on a desktop, which models the intracellular replication and the cell-to-cell infection and demonstrates virus evolution at the molecular level. This code simulates the infection of a population of "idealized biological cells" (represented as objects that do not divide or have metabolism) with "virus" (represented by its genetic sequence), the replication and simultaneous mutation of the virus which leads to evolution of the population of genetically diverse viruses. The code is built to simulate single-stranded RNA viruses. The input for the code is 1. the number of biological cells in the culture,more » 2. the initial composition of the virus population, 3. the reference genome of the RNA virus, 4. the coordinates of the genome regions and their significance and, 5. parameters determining the dynamics of virus replication, such as the mutation rate. The simulation ends when all cells have been infected or when no more infections occurs after a given number of attempts. The code has the ability to simulate the evolution of the virus in serial passage of cell "cultures", i.e. after the end of a simulation, a new one is immediately scheduled with a new culture of infected cells. The code outputs characteristics of the resulting virus population dynamics and genetic composition of the virus population, such as the top dominant genomes, percentage of a genome with specific characteristics.« less

Exploring the Dynamics of Cell Processes through Simulations of Fluorescence Microscopy Experiments

PubMed Central

Angiolini, Juan; Plachta, Nicolas; Mocskos, Esteban; Levi, Valeria

2015-01-01

Fluorescence correlation spectroscopy (FCS) methods are powerful tools for unveiling the dynamical organization of cells. For simple cases, such as molecules passively moving in a homogeneous media, FCS analysis yields analytical functions that can be fitted to the experimental data to recover the phenomenological rate parameters. Unfortunately, many dynamical processes in cells do not follow these simple models, and in many instances it is not possible to obtain an analytical function through a theoretical analysis of a more complex model. In such cases, experimental analysis can be combined with Monte Carlo simulations to aid in interpretation of the data. In response to this need, we developed a method called FERNET (Fluorescence Emission Recipes and Numerical routines Toolkit) based on Monte Carlo simulations and the MCell-Blender platform, which was designed to treat the reaction-diffusion problem under realistic scenarios. This method enables us to set complex geometries of the simulation space, distribute molecules among different compartments, and define interspecies reactions with selected kinetic constants, diffusion coefficients, and species brightness. We apply this method to simulate single- and multiple-point FCS, photon-counting histogram analysis, raster image correlation spectroscopy, and two-color fluorescence cross-correlation spectroscopy. We believe that this new program could be very useful for predicting and understanding the output of fluorescence microscopy experiments. PMID:26039162

Oscillatory Protein Expression Dynamics Endows Stem Cells with Robust Differentiation Potential

PubMed Central

Kaneko, Kunihiko

2011-01-01

The lack of understanding of stem cell differentiation and proliferation is a fundamental problem in developmental biology. Although gene regulatory networks (GRNs) for stem cell differentiation have been partially identified, the nature of differentiation dynamics and their regulation leading to robust development remain unclear. Herein, using a dynamical system modeling cell approach, we performed simulations of the developmental process using all possible GRNs with a few genes, and screened GRNs that could generate cell type diversity through cell-cell interactions. We found that model stem cells that both proliferated and differentiated always exhibited oscillatory expression dynamics, and the differentiation frequency of such stem cells was regulated, resulting in a robust number distribution. Moreover, we uncovered the common regulatory motifs for stem cell differentiation, in which a combination of regulatory motifs that generated oscillatory expression dynamics and stabilized distinct cellular states played an essential role. These findings may explain the recently observed heterogeneity and dynamic equilibrium in cellular states of stem cells, and can be used to predict regulatory networks responsible for differentiation in stem cell systems. PMID:22073296

Phase diagram and breathing dynamics of a single red blood cell and a biconcave capsule in dilute shear flow.

PubMed

Yazdani, Alireza Z K; Bagchi, Prosenjit

2011-08-01

We present phase diagrams of the single red blood cell and biconcave capsule dynamics in dilute suspension using three-dimensional numerical simulations. The computational geometry replicates an in vitro linear shear flow apparatus. Our model includes all essential properties of the cell membrane, namely, the resistance against shear deformation, area dilatation, and bending, as well as the viscosity difference between the cell interior and suspending fluids. By considering a wide range of shear rate and interior-to-exterior fluid viscosity ratio, it is shown that the cell dynamics is often more complex than the well-known tank-treading, tumbling, and swinging motion and is characterized by an extreme variation of the cell shape. As a result, it is often difficult to clearly establish whether the cell is swinging or tumbling. Identifying such complex shape dynamics, termed here as "breathing" dynamics, is the focus of this article. During the breathing motion at moderate bending rigidity, the cell either completely aligns with the flow direction and the membrane folds inward, forming two cusps, or it undergoes large swinging motion while deep, craterlike dimples periodically emerge and disappear. At lower bending rigidity, the breathing motion occurs over a wider range of shear rates, and is often characterized by the emergence of a quad-concave shape. The effect of the breathing dynamics on the tank-treading-to-tumbling transition is illustrated by detailed phase diagrams which appear to be more complex and richer than those of vesicles. In a remarkable departure from the vesicle dynamics, and from the classical theory of nondeformable cells, we find that there exists a critical viscosity ratio below which the transition is independent of the viscosity ratio, and dependent on shear rate only. Further, unlike the reduced-order models, the present simulations do not predict any intermittent dynamics of the red blood cells.

Exploring Instructive Physiological Signaling with the Bioelectric Tissue Simulation Engine

PubMed Central

Pietak, Alexis; Levin, Michael

2016-01-01

Bioelectric cell properties have been revealed as powerful targets for modulating stem cell function, regenerative response, developmental patterning, and tumor reprograming. Spatio-temporal distributions of endogenous resting potential, ion flows, and electric fields are influenced not only by the genome and external signals but also by their own intrinsic dynamics. Ion channels and electrical synapses (gap junctions) both determine, and are themselves gated by, cellular resting potential. Thus, the origin and progression of bioelectric patterns in multicellular tissues is complex, which hampers the rational control of voltage distributions for biomedical interventions. To improve understanding of these dynamics and facilitate the development of bioelectric pattern control strategies, we developed the BioElectric Tissue Simulation Engine (BETSE), a finite volume method multiphysics simulator, which predicts bioelectric patterns and their spatio-temporal dynamics by modeling ion channel and gap junction activity and tracking changes to the fundamental property of ion concentration. We validate performance of the simulator by matching experimentally obtained data on membrane permeability, ion concentration and resting potential to simulated values, and by demonstrating the expected outcomes for a range of well-known cases, such as predicting the correct transmembrane voltage changes for perturbation of single cell membrane states and environmental ion concentrations, in addition to the development of realistic transepithelial potentials and bioelectric wounding signals. In silico experiments reveal factors influencing transmembrane potential are significantly different in gap junction-networked cell clusters with tight junctions, and identify non-linear feedback mechanisms capable of generating strong, emergent, cluster-wide resting potential gradients. The BETSE platform will enable a deep understanding of local and long-range bioelectrical dynamics in tissues, and assist the development of specific interventions to achieve greater control of pattern during morphogenesis and remodeling. PMID:27458581

Modelling and Simulation of the Dynamics of the Antigen-Specific T Cell Response Using Variable Structure Control Theory.

PubMed

Anelone, Anet J N; Spurgeon, Sarah K

2016-01-01

Experimental and mathematical studies in immunology have revealed that the dynamics of the programmed T cell response to vigorous infection can be conveniently modelled using a sigmoidal or a discontinuous immune response function. This paper hypothesizes strong synergies between this existing work and the dynamical behaviour of engineering systems with a variable structure control (VSC) law. These findings motivate the interpretation of the immune system as a variable structure control system. It is shown that dynamical properties as well as conditions to analytically assess the transition from health to disease can be developed for the specific T cell response from the theory of variable structure control. In particular, it is shown that the robustness properties of the specific T cell response as observed in experiments can be explained analytically using a VSC perspective. Further, the predictive capacity of the VSC framework to determine the T cell help required to overcome chronic Lymphocytic Choriomeningitis Virus (LCMV) infection is demonstrated. The findings demonstrate that studying the immune system using variable structure control theory provides a new framework for evaluating immunological dynamics and experimental observations. A modelling and simulation tool results with predictive capacity to determine how to modify the immune response to achieve healthy outcomes which may have application in drug development and vaccine design.

Dynamic characterization of HLA-B*44 Alleles: A comparative molecular dynamics simulation study.

PubMed

Ozbek, Pemra

2016-06-01

Human Leukocyte Antigens (HLA) are highly polymorphic proteins that play a key role in the immune system. HLA molecule is present on the cell membrane of antigen-presenting cells of the immune system and presents short peptides, originating from the proteins of invading pathogens or self-proteins, to the T-cell Receptor (TCR) molecule of the T-cells. In this study, peptide-binding characteristics of HLA-B*44:02, 44:03, 44:05 alleles bound to three nonameric peptides were studied using molecular dynamics simulations. Polymorphisms among these alleles (Asp116Tyr and Asp156Leu) result in major differences in the allele characteristics. While HLA-B*44:02 (Asp116, Asp156) and HLA-B*44:03 (Asp116, Leu156) depend on tapasin for efficient peptide loading, HLA-B*44:05 (Tyr116, Asp156) is tapasin independent. On the other hand, HLA-B*44:02 and HLA-B*44:03 mismatch is closely related to transplant rejection and acute-graft-versus-host disease. In order to understand the dynamic characteristics, the simulation trajectories were analyzed by applying Root Mean Square Deviation (RMSD) and Root Mean Square Fluctuation (RMSF) calculations and hydrogen bonding analysis. Binding dynamics of the three HLA-B*44 alleles and peptide sequences are comparatively discussed. In general, peptide binding stability is found to depend on the peptide rather than the allele type for HLA-B*44 alleles. Copyright © 2016 Elsevier Ltd. All rights reserved.

Efficient massively parallel simulation of dynamic channel assignment schemes for wireless cellular communications

NASA Technical Reports Server (NTRS)

Greenberg, Albert G.; Lubachevsky, Boris D.; Nicol, David M.; Wright, Paul E.

1994-01-01

Fast, efficient parallel algorithms are presented for discrete event simulations of dynamic channel assignment schemes for wireless cellular communication networks. The driving events are call arrivals and departures, in continuous time, to cells geographically distributed across the service area. A dynamic channel assignment scheme decides which call arrivals to accept, and which channels to allocate to the accepted calls, attempting to minimize call blocking while ensuring co-channel interference is tolerably low. Specifically, the scheme ensures that the same channel is used concurrently at different cells only if the pairwise distances between those cells are sufficiently large. Much of the complexity of the system comes from ensuring this separation. The network is modeled as a system of interacting continuous time automata, each corresponding to a cell. To simulate the model, conservative methods are used; i.e., methods in which no errors occur in the course of the simulation and so no rollback or relaxation is needed. Implemented on a 16K processor MasPar MP-1, an elegant and simple technique provides speedups of about 15 times over an optimized serial simulation running on a high speed workstation. A drawback of this technique, typical of conservative methods, is that processor utilization is rather low. To overcome this, new methods were developed that exploit slackness in event dependencies over short intervals of time, thereby raising the utilization to above 50 percent and the speedup over the optimized serial code to about 120 times.

Coarse-grained hydrodynamics from correlation functions

NASA Astrophysics Data System (ADS)

Palmer, Bruce

2018-02-01

This paper will describe a formalism for using correlation functions between different grid cells as the basis for determining coarse-grained hydrodynamic equations for modeling the behavior of mesoscopic fluid systems. Configurations from a molecular dynamics simulation or other atomistic simulation are projected onto basis functions representing grid cells in a continuum hydrodynamic simulation. Equilibrium correlation functions between different grid cells are evaluated from the molecular simulation and used to determine the evolution operator for the coarse-grained hydrodynamic system. The formalism is demonstrated on a discrete particle simulation of diffusion with a spatially dependent diffusion coefficient. Correlation functions are calculated from the particle simulation and the spatially varying diffusion coefficient is recovered using a fitting procedure.

A particle-based model to simulate the micromechanics of single-plant parenchyma cells and aggregates

NASA Astrophysics Data System (ADS)

Van Liedekerke, P.; Ghysels, P.; Tijskens, E.; Samaey, G.; Smeedts, B.; Roose, D.; Ramon, H.

2010-06-01

This paper is concerned with addressing how plant tissue mechanics is related to the micromechanics of cells. To this end, we propose a mesh-free particle method to simulate the mechanics of both individual plant cells (parenchyma) and cell aggregates in response to external stresses. The model considers two important features in the plant cell: (1) the cell protoplasm, the interior liquid phase inducing hydrodynamic phenomena, and (2) the cell wall material, a viscoelastic solid material that contains the protoplasm. In this particle framework, the cell fluid is modeled by smoothed particle hydrodynamics (SPH), a mesh-free method typically used to address problems with gas and fluid dynamics. In the solid phase (cell wall) on the other hand, the particles are connected by pairwise interactions holding them together and preventing the fluid to penetrate the cell wall. The cell wall hydraulic conductivity (permeability) is built in as well through the SPH formulation. Although this model is also meant to be able to deal with dynamic and even violent situations (leading to cell wall rupture or cell-cell debonding), we have concentrated on quasi-static conditions. The results of single-cell compression simulations show that the conclusions found by analytical models and experiments can be reproduced at least qualitatively. Relaxation tests revealed that plant cells have short relaxation times (1 µs-10 µs) compared to mammalian cells. Simulations performed on cell aggregates indicated an influence of the cellular organization to the tissue response, as was also observed in experiments done on tissues with a similar structure.

A 3-D model of tumor progression based on complex automata driven by particle dynamics.

PubMed

Wcisło, Rafał; Dzwinel, Witold; Yuen, David A; Dudek, Arkadiusz Z

2009-12-01

The dynamics of a growing tumor involving mechanical remodeling of healthy tissue and vasculature is neglected in most of the existing tumor models. This is due to the lack of efficient computational framework allowing for simulation of mechanical interactions. Meanwhile, just these interactions trigger critical changes in tumor growth dynamics and are responsible for its volumetric and directional progression. We describe here a novel 3-D model of tumor growth, which combines particle dynamics with cellular automata concept. The particles represent both tissue cells and fragments of the vascular network. They interact with their closest neighbors via semi-harmonic central forces simulating mechanical resistance of the cell walls. The particle dynamics is governed by both the Newtonian laws of motion and the cellular automata rules. These rules can represent cell life-cycle and other biological interactions involving smaller spatio-temporal scales. We show that our complex automata, particle based model can reproduce realistic 3-D dynamics of the entire system consisting of the tumor, normal tissue cells, blood vessels and blood flow. It can explain phenomena such as the inward cell motion in avascular tumor, stabilization of tumor growth by the external pressure, tumor vascularization due to the process of angiogenesis, trapping of healthy cells by invading tumor, and influence of external (boundary) conditions on the direction of tumor progression. We conclude that the particle model can serve as a general framework for designing advanced multiscale models of tumor dynamics and it is very competitive to the modeling approaches presented before.

Electrolytic hydrogen production: An analysis and review

NASA Technical Reports Server (NTRS)

Evangelista, J.; Phillips, B.; Gordon, L.

1975-01-01

The thermodynamics of water electrolysis cells is presented, followed by a review of current and future technology of commercial cells. The irreversibilities involved are analyzed and the resulting equations assembled into a computer simulation model of electrolysis cell efficiency. The model is tested by comparing predictions based on the model to actual commercial cell performance, and a parametric investigation of operating conditions is performed. Finally, the simulation model is applied to a study of electrolysis cell dynamics through consideration of an ideal pulsed electrolyzer.

Optical control demonstrates switch-like PIP3 dynamics underlying the initiation of immune cell migration

PubMed Central

Karunarathne, W. K. Ajith; Giri, Lopamudra; Patel, Anilkumar K.; Venkatesh, Kareenhalli V.; Gautam, N.

2013-01-01

There is a dearth of approaches to experimentally direct cell migration by continuously varying signal input to a single cell, evoking all possible migratory responses and quantitatively monitoring the cellular and molecular response dynamics. Here we used a visual blue opsin to recruit the endogenous G-protein network that mediates immune cell migration. Specific optical inputs to this optical trigger of signaling helped steer migration in all possible directions with precision. Spectrally selective imaging was used to monitor cell-wide phosphatidylinositol (3,4,5)-triphosphate (PIP3), cytoskeletal, and cellular dynamics. A switch-like PIP3 increase at the cell front and a decrease at the back were identified, underlying the decisive migratory response. Migration was initiated at the rapidly increasing switch stage of PIP3 dynamics. This result explains how a migratory cell filters background fluctuations in the intensity of an extracellular signal but responds by initiating directionally sensitive migration to a persistent signal gradient across the cell. A two-compartment computational model incorporating a localized activator that is antagonistic to a diffusible inhibitor was able to simulate the switch-like PIP3 response. It was also able simulate the slow dissipation of PIP3 on signal termination. The ability to independently apply similar signaling inputs to single cells detected two cell populations with distinct thresholds for migration initiation. Overall the optical approach here can be applied to understand G-protein–coupled receptor network control of other cell behaviors. PMID:23569254

Optical control demonstrates switch-like PIP3 dynamics underlying the initiation of immune cell migration.

PubMed

Karunarathne, W K Ajith; Giri, Lopamudra; Patel, Anilkumar K; Venkatesh, Kareenhalli V; Gautam, N

2013-04-23

There is a dearth of approaches to experimentally direct cell migration by continuously varying signal input to a single cell, evoking all possible migratory responses and quantitatively monitoring the cellular and molecular response dynamics. Here we used a visual blue opsin to recruit the endogenous G-protein network that mediates immune cell migration. Specific optical inputs to this optical trigger of signaling helped steer migration in all possible directions with precision. Spectrally selective imaging was used to monitor cell-wide phosphatidylinositol (3,4,5)-triphosphate (PIP3), cytoskeletal, and cellular dynamics. A switch-like PIP3 increase at the cell front and a decrease at the back were identified, underlying the decisive migratory response. Migration was initiated at the rapidly increasing switch stage of PIP3 dynamics. This result explains how a migratory cell filters background fluctuations in the intensity of an extracellular signal but responds by initiating directionally sensitive migration to a persistent signal gradient across the cell. A two-compartment computational model incorporating a localized activator that is antagonistic to a diffusible inhibitor was able to simulate the switch-like PIP3 response. It was also able simulate the slow dissipation of PIP3 on signal termination. The ability to independently apply similar signaling inputs to single cells detected two cell populations with distinct thresholds for migration initiation. Overall the optical approach here can be applied to understand G-protein-coupled receptor network control of other cell behaviors.

Deformation and dynamics of red blood cells in flow through cylindrical microchannels.

PubMed

Fedosov, Dmitry A; Peltomäki, Matti; Gompper, Gerhard

2014-06-28

The motion of red blood cells (RBCs) in microcirculation plays an important role in blood flow resistance and in the cell partitioning within a microvascular network. Different shapes and dynamics of RBCs in microvessels have been previously observed experimentally including the parachute and slipper shapes. We employ mesoscale hydrodynamic simulations to predict the phase diagram of shapes and dynamics of RBCs in cylindrical microchannels, which serve as idealized microvessels, for a wide range of channel confinements and flow rates. A rich dynamical behavior is found, with snaking and tumbling discocytes, slippers performing a swinging motion, and stationary parachutes. We discuss the effects of different RBC states on the flow resistance, and the influence of RBC properties, characterized by the Föppl-von Kármán number, on the shape diagram. The simulations are performed using the same viscosity for both external and internal fluids surrounding a RBC; however, we discuss how the viscosity contrast would affect the shape diagram.

Joshua Vermaas | NREL

Science.gov Websites

molecular dynamics simulations to explore biological interfaces, such as those found at the cell membrane or in lignocellulosic biomass. In particular, molecular dynamics can see in molecular detail the research toward fruitful results. Areas of Expertise Molecular dynamics Compound parameterization

Atomistic molecular dynamics simulations of bioactive engrailed 1 interference peptides (EN1-iPeps).

PubMed

Gandhi, Neha S; Blancafort, Pilar; Mancera, Ricardo L

2018-04-27

The neural-specific transcription factor Engrailed 1 - is overexpressed in basal-like breast tumours. Synthetic interference peptides - comprising a cell-penetrating peptide/nuclear localisation sequence and the Engrailed 1-specific sequence from the N-terminus have been engineered to produce a strong apoptotic response in tumour cells overexpressing EN1, with no toxicity to normal or non Engrailed 1-expressing cells. Here scaled molecular dynamics simulations were used to study the conformational dynamics of these interference peptides in aqueous solution to characterise their structure and dynamics. Transitions from disordered to α-helical conformation, stabilised by hydrogen bonds and proline-aromatic interactions, were observed throughout the simulations. The backbone of the wild-type peptide folds to a similar conformation as that found in ternary complexes of anterior Hox proteins with conserved hexapeptide motifs important for recognition of pre-B-cell leukemia Homeobox 1, indicating that the motif may possess an intrinsic preference for helical structure. The predicted NMR chemical shifts of these peptides are consistent with the Hox hexapeptides in solution and Engrailed 2 NMR data. These findings highlight the importance of aromatic residues in determining the structure of Engrailed 1 interference peptides, shedding light on the rational design strategy of molecules that could be adopted to inhibit other transcription factors overexpressed in other cancer types, potentially including other transcription factor families that require highly conserved and cooperative protein-protein partnerships for biological activity.

A mathematical and experimental simulation of the hematological response to weightlessness

NASA Technical Reports Server (NTRS)

Kimzey, S. L.; Leonard, J. I.; Johnson, P. C.

1979-01-01

A mathematical model of erythropoiesis control was used to simulate the effects of bedrest and zero-g on the circulating red cell mass. The model incorporates the best current understanding of the dynamics of red cell production and destruction and the associated feedback regulation. Specifically studied were the hemodynamic responses of a 28-day bedrest study devised to simulate Skylab experience. The results support the hypothesis that red cell loss during supine bedrest is a normal physiological feedback process in response to hemoconcentration enhanced tissue oxygenation and suppression of red cell production. Model simulation suggested the possibilities that this period was marked by some combination of increased oxygen-hemoglobin affinity, small reduction in mean red cell life span, ineffective erythropoiesis, or abnormal reticulocytosis.

On the importance of cloud—cloud interaction to invigorate convective extremes

NASA Astrophysics Data System (ADS)

Berg, Peter; Moseley, Christopher; Hohenegger, Cathy; Haerter, Jan

2017-04-01

Observational studies have shown that convective extremes are invigorated with increasing temperatures beyond thermodynamic constraints through the Clausius-Clapeyron relationship (e.g. Lenderink and van Meijgaard, Nature Geosci., 2008; Berg et al., Nature Geosci., 2013). This implies that there are changes in the dynamics of the convective showers that are dependent on the environmental conditions. Observations of convective cells lack sufficient resolution to investigate the dynamics in detail. We have therefore applied a large eddy simulator (LES) at a 200 m horizontal resolution to study the dynamical interaction between convective cells in a set of idealized simulations of a full diurnal cycle with a vertical profile of a typical day with convective showers (Moseley et al., Nature Geosci., 2016). The simulations show that the convective cells are subjected to a gradual self-organization over the day, forming larger cell clusters and more intense precipitation. Further, by tracking rain cells, we find that cells that collide with other cells during their lifetime have a different response to changes in the environmental conditions, such as an increase in temperature, than cells that do not interact. Whereas the non-interacting cells remain almost unaffected by the boundary conditions, the colliding cells show a strong invigoration. Interestingly, granting more time for the self-organization to occur has a similar effect as increasing the temperature. We therefore speculate that self-organization is a key element to explain the strong response of convective extremes to increasing temperature. Our results suggest that proper modeling and predicting of convective extremes requires the description of the interaction between convective clouds.

The CD4+ T cell regulatory network mediates inflammatory responses during acute hyperinsulinemia: a simulation study.

PubMed

Martinez-Sanchez, Mariana E; Hiriart, Marcia; Alvarez-Buylla, Elena R

2017-06-26

Obesity is frequently linked to insulin resistance, high insulin levels, chronic inflammation, and alterations in the behaviour of CD4+ T cells. Despite the biomedical importance of this condition, the system-level mechanisms that alter CD4+ T cell differentiation and plasticity are not well understood. We model how hyperinsulinemia alters the dynamics of the CD4+ T regulatory network, and this, in turn, modulates cell differentiation and plasticity. Different polarizing microenvironments are simulated under basal and high levels of insulin to assess impacts on cell-fate attainment and robustness in response to transient perturbations. In the presence of high levels of insulin Th1 and Th17 become more stable to transient perturbations, and their basin sizes are augmented, Tr1 cells become less stable or disappear, while TGFβ producing cells remain unaltered. Hence, the model provides a dynamic system-level framework and explanation to further understand the documented and apparently paradoxical role of TGFβ in both inflammation and regulation of immune responses, as well as the emergence of the adipose Treg phenotype. Furthermore, our simulations provide new predictions on the impact of the microenvironment in the coexistence of the different cell types, suggesting that in pro-Th1, pro-Th2 and pro-Th17 environments effector and regulatory cells can coexist, but that high levels of insulin severely diminish regulatory cells, especially in a pro-Th17 environment. This work provides a first step towards a system-level formal and dynamic framework to integrate further experimental data in the study of complex inflammatory diseases.

Brownian dynamics simulations of lipid bilayer membrane with hydrodynamic interactions in LAMMPS

NASA Astrophysics Data System (ADS)

Fu, Szu-Pei; Young, Yuan-Nan; Peng, Zhangli; Yuan, Hongyan

2016-11-01

Lipid bilayer membranes have been extensively studied by coarse-grained molecular dynamics simulations. Numerical efficiencies have been reported in the cases of aggressive coarse-graining, where several lipids are coarse-grained into a particle of size 4 6 nm so that there is only one particle in the thickness direction. Yuan et al. proposed a pair-potential between these one-particle-thick coarse-grained lipid particles to capture the mechanical properties of a lipid bilayer membrane (such as gel-fluid-gas phase transitions of lipids, diffusion, and bending rigidity). In this work we implement such interaction potential in LAMMPS to simulate large-scale lipid systems such as vesicles and red blood cells (RBCs). We also consider the effect of cytoskeleton on the lipid membrane dynamics as a model for red blood cell (RBC) dynamics, and incorporate coarse-grained water molecules to account for hydrodynamic interactions. The interaction between the coarse-grained water molecules (explicit solvent molecules) is modeled as a Lennard-Jones (L-J) potential. We focus on two sets of LAMMPS simulations: 1. Vesicle shape transitions with varying enclosed volume; 2. RBC shape transitions with different enclosed volume. This work is funded by NSF under Grant DMS-1222550.

Brownian dynamics simulations of lipid bilayer membrane with hydrodynamic interactions in LAMMPS

NASA Astrophysics Data System (ADS)

Fu, Szu-Pei; Young, Yuan-Nan; Peng, Zhangli; Yuan, Hongyan

Lipid bilayer membranes have been extensively studied by coarse-grained molecular dynamics simulations. Numerical efficiency has been reported in the cases of aggressive coarse-graining, where several lipids are coarse-grained into a particle of size 4 6 nm so that there is only one particle in the thickness direction. Yuan et al. proposed a pair-potential between these one-particle-thick coarse-grained lipid particles to capture the mechanical properties of a lipid bilayer membrane (such as gel-fluid-gas phase transitions of lipids, diffusion, and bending rigidity). In this work we implement such interaction potential in LAMMPS to simulate large-scale lipid systems such as vesicles and red blood cells (RBCs). We also consider the effect of cytoskeleton on the lipid membrane dynamics as a model for red blood cell (RBC) dynamics, and incorporate coarse-grained water molecules to account for hydrodynamic interactions. The interaction between the coarse-grained water molecules (explicit solvent molecules) is modeled as a Lennard-Jones (L-J) potential. We focus on two sets of LAMMPS simulations: 1. Vesicle shape transitions with varying enclosed volume; 2. RBC shape transitions with different enclosed volume.

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.

Numerical modelling of closed-cell aluminium foam under dynamic loading

NASA Astrophysics Data System (ADS)

Hazell, Paul; Kader, M. A.; Islam, M. A.; Escobedo, J. P.; Saadatfar, M.

2015-06-01

Closed-cell aluminium foams are extensively used in aerospace and automobile industries. The understanding of their behaviour under impact loading conditions is extremely important since impact problems are directly related to design of these engineering structures. This research investigates the response of a closed-cell aluminium foam (CYMAT) subjected to dynamic loading using the finite element software ABAQUS/explicit. The aim of this research is to numerically investigate the material and structural properties of closed-cell aluminium foam under impact loading conditions with interest in shock propagation and its effects on cell wall deformation. A μ-CT based 3D foam geometry is developed to simulate the local cell collapse behaviours. A number of numerical techniques are applied for modelling the crush behaviour of aluminium foam to obtain the more accurate results. The simulation results are compared with experimental data. Comparison of the results shows a good correlation between the experimental results and numerical predictions.

Role of flexural stiffness of leukocyte microvilli in adhesion dynamics

NASA Astrophysics Data System (ADS)

Wu, Tai-Hsien; Qi, Dewei

2018-03-01

Previous work reported that microvillus deformation has an important influence on dynamics of cell adhesion. However, the existing studies were limited to the extensional deformation of microvilli and did not consider the effects of their bending deformation on cell adhesion. This Rapid Communication investigates the effects of flexural stiffness of microvilli on the rolling process related to adhesion of leukocytes by using a lattice-Boltzmann lattice-spring method (LLM) combined with adhesive dynamics (AD) simulations. The simulation results reveal that the flexural stiffness of microvilli and their bending deformation have a profound effect on rolling velocity and adhesive forces. As the flexural stiffness of the microvilli decreases, their bending angles increase, resulting in an increase in the number of receptor-ligand bonds and adhesive bonding force and a decrease in the rolling velocity of leukocytes. The effects of flexural stiffness on deformation and adhesion represent crucial factors involved in cell adhesion.

Coarse-grained hydrodynamics from correlation functions

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

Palmer, Bruce

This paper will describe a formalism for using correlation functions between different grid cells as the basis for determining coarse-grained hydrodynamic equations for modeling the behavior of mesoscopic fluid systems. Configuration from a molecular dynamics simulation are projected onto basis functions representing grid cells in a continuum hydrodynamic simulation. Equilbrium correlation functions between different grid cells are evaluated from the molecular simulation and used to determine the evolution operator for the coarse-grained hydrodynamic system. The formalism is applied to some simple hydrodynamic cases to determine the feasibility of applying this to realistic nanoscale systems.

Reflections from a Computer Simulations Program on Cell Division in Selected Kenyan Secondary Schools

ERIC Educational Resources Information Center

Ndirangu, Mwangi; Kiboss, Joel K.; Wekesa, Eric W.

2005-01-01

The application of computer technology in education is a relatively new approach that is trying to justify inclusion in the Kenyan school curriculum. Being abstract, with a dynamic nature that does not manifest itself visibly, the process of cell division has posed difficulties for teachers. Consequently, a computer simulation program, using…

Molecular dynamics simulations of polarizable DNA in crystal environment

NASA Astrophysics Data System (ADS)

Babin, Volodymyr; Baucom, Jason; Darden, Thomas A.; Sagui, Celeste

We have investigated the role of the electrostatic description and cell environment in molecular dynamics (MD) simulations of DNA. Multiple unrestrained MD simulations of the DNA duplex d(CCAACGTTGG)2 have been carried out using two different force fields: a traditional description based on atomic point charges and a polarizable force field. For the time scales probed, and given the ?right? distribution of divalent ions, the latter performs better than the nonpolarizable force field. In particular, by imposing the experimental unit cell environment, an initial configuration with ideal B-DNA duplexes in the unit cell acquires sequence-dependent features that very closely resemble the crystallographic ones. Simultaneously, the all-atom root-mean-square coordinates deviation (RMSD) with respect to the crystallographic structure is seen to decay. At later times, the polarizable force field is able to maintain this lower RMSD, while the nonpolarizable force field starts to drift away.

Impact of release dynamics of laser-irradiated polymer micropallets on the viability of selected adherent cells

PubMed Central

Ma, Huan; Mismar, Wael; Wang, Yuli; Small, Donald W.; Ras, Mat; Allbritton, Nancy L.; Sims, Christopher E.; Venugopalan, Vasan

2012-01-01

We use time-resolved interferometry, fluorescence assays and computational fluid dynamics (CFD) simulations to examine the viability of confluent adherent cell monolayers to selection via laser microbeam release of photoresist polymer micropallets. We demonstrate the importance of laser microbeam pulse energy and focal volume position relative to the glass–pallet interface in governing the threshold energies for pallet release as well as the pallet release dynamics. Measurements using time-resolved interferometry show that increases in laser pulse energy result in increasing pallet release velocities that can approach 10 m s−1 through aqueous media. CFD simulations reveal that the pallet motion results in cellular exposure to transient hydrodynamic shear stress amplitudes that can exceed 100 kPa on microsecond timescales, and which produces reduced cell viability. Moreover, CFD simulation results show that the maximum shear stress on the pallet surface varies spatially, with the largest shear stresses occurring on the pallet periphery. Cell viability of confluent cell monolayers on the pallet surface confirms that the use of larger pulse energies results in increased rates of necrosis for those cells situated away from the pallet centre, while cells situated at the pallet centre remain viable. Nevertheless, experiments that examine the viability of these cell monolayers following pallet release show that proper choices for laser microbeam pulse energy and focal volume position lead to the routine achievement of cell viability in excess of 90 per cent. These laser microbeam parameters result in maximum pallet release velocities below 6 m s−1 and cellular exposure of transient hydrodynamic shear stresses below 20 kPa. Collectively, these results provide a mechanistic understanding that relates pallet release dynamics and associated transient shear stresses with subsequent cellular viability. This provides a quantitative, mechanistic basis for determining optimal operating conditions for laser microbeam-based pallet release systems for the isolation and selection of adherent cells. PMID:22158840

Impact of release dynamics of laser-irradiated polymer micropallets on the viability of selected adherent cells.

PubMed

Ma, Huan; Mismar, Wael; Wang, Yuli; Small, Donald W; Ras, Mat; Allbritton, Nancy L; Sims, Christopher E; Venugopalan, Vasan

2012-06-07

We use time-resolved interferometry, fluorescence assays and computational fluid dynamics (CFD) simulations to examine the viability of confluent adherent cell monolayers to selection via laser microbeam release of photoresist polymer micropallets. We demonstrate the importance of laser microbeam pulse energy and focal volume position relative to the glass-pallet interface in governing the threshold energies for pallet release as well as the pallet release dynamics. Measurements using time-resolved interferometry show that increases in laser pulse energy result in increasing pallet release velocities that can approach 10 m s(-1) through aqueous media. CFD simulations reveal that the pallet motion results in cellular exposure to transient hydrodynamic shear stress amplitudes that can exceed 100 kPa on microsecond timescales, and which produces reduced cell viability. Moreover, CFD simulation results show that the maximum shear stress on the pallet surface varies spatially, with the largest shear stresses occurring on the pallet periphery. Cell viability of confluent cell monolayers on the pallet surface confirms that the use of larger pulse energies results in increased rates of necrosis for those cells situated away from the pallet centre, while cells situated at the pallet centre remain viable. Nevertheless, experiments that examine the viability of these cell monolayers following pallet release show that proper choices for laser microbeam pulse energy and focal volume position lead to the routine achievement of cell viability in excess of 90 per cent. These laser microbeam parameters result in maximum pallet release velocities below 6 m s(-1) and cellular exposure of transient hydrodynamic shear stresses below 20 kPa. Collectively, these results provide a mechanistic understanding that relates pallet release dynamics and associated transient shear stresses with subsequent cellular viability. This provides a quantitative, mechanistic basis for determining optimal operating conditions for laser microbeam-based pallet release systems for the isolation and selection of adherent cells.

Accounting for Space—Quantification of Cell-To-Cell Transmission Kinetics Using Virus Dynamics Models.

PubMed

Kumberger, Peter; Durso-Cain, Karina; Uprichard, Susan L; Dahari, Harel; Graw, Frederik

2018-04-17

Mathematical models based on ordinary differential equations (ODE) that describe the population dynamics of viruses and infected cells have been an essential tool to characterize and quantify viral infection dynamics. Although an important aspect of viral infection is the dynamics of viral spread, which includes transmission by cell-free virions and direct cell-to-cell transmission, models used so far ignored cell-to-cell transmission completely, or accounted for this process by simple mass-action kinetics between infected and uninfected cells. In this study, we show that the simple mass-action approach falls short when describing viral spread in a spatially-defined environment. Using simulated data, we present a model extension that allows correct quantification of cell-to-cell transmission dynamics within a monolayer of cells. By considering the decreasing proportion of cells that can contribute to cell-to-cell spread with progressing infection, our extension accounts for the transmission dynamics on a single cell level while still remaining applicable to standard population-based experimental measurements. While the ability to infer the proportion of cells infected by either of the transmission modes depends on the viral diffusion rate, the improved estimates obtained using our novel approach emphasize the need to correctly account for spatial aspects when analyzing viral spread.

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

SPH simulations of WBC adhesion to the endothelium: the role of haemodynamics and endothelial binding kinetics.

PubMed

Gholami, Babak; Comerford, Andrew; Ellero, Marco

2015-11-01

A multiscale Lagrangian particle solver introduced in our previous work is extended to model physiologically realistic near-wall cell dynamics. Three-dimensional simulation of particle trajectories is combined with realistic receptor-ligand adhesion behaviour to cover full cell interactions in the vicinity of the endothelium. The selected stochastic adhesion model, which is based on a Monte Carlo acceptance-rejection method, fits in our Lagrangian framework and does not compromise performance. Additionally, appropriate inflow/outflow boundary conditions are implemented for our SPH solver to enable realistic pulsatile flow simulation. The model is tested against in-vitro data from a 3D geometry with a stenosis and sudden expansion. In both steady and pulsatile flow conditions, results show close agreement with the experimental ones. Furthermore we demonstrate, in agreement with experimental observations, that haemodynamics alone does not account for adhesion of white blood cells, in this case U937 monocytic human cells. Our findings suggest that the current framework is fully capable of modelling cell dynamics in large arteries in a realistic and efficient manner.

Dynamics of the Glycophorin A Dimer in Membranes of Native-Like Composition Uncovered by Coarse-Grained Molecular Dynamics Simulations.

PubMed

Flinner, Nadine; Schleiff, Enrico

2015-01-01

Membranes are central for cells as borders to the environment or intracellular organelle definition. They are composed of and harbor different molecules like various lipid species and sterols, and they are generally crowded with proteins. The membrane system is very dynamic and components show lateral, rotational and translational diffusion. The consequence of the latter is that phase separation can occur in membranes in vivo and in vitro. It was documented that molecular dynamics simulations of an idealized plasma membrane model result in formation of membrane areas where either saturated lipids and cholesterol (liquid-ordered character, Lo) or unsaturated lipids (liquid-disordered character, Ld) were enriched. Furthermore, current discussions favor the idea that proteins are sorted into the liquid-disordered phase of model membranes, but experimental support for the behavior of isolated proteins in native membranes is sparse. To gain insight into the protein behavior we built a model of the red blood cell membrane with integrated glycophorin A dimer. The sorting and the dynamics of the dimer were subsequently explored by coarse-grained molecular dynamics simulations. In addition, we inspected the impact of lipid head groups and the presence of cholesterol within the membrane on the dynamics of the dimer within the membrane. We observed that cholesterol is important for the formation of membrane areas with Lo and Ld character. Moreover, it is an important factor for the reproduction of the dynamic behavior of the protein found in its native environment. The protein dimer was exclusively sorted into the domain of Ld character in the model red blood cell plasma membrane. Therefore, we present structural information on the glycophorin A dimer distribution in the plasma membrane in the absence of other factors like e.g. lipid anchors in a coarse grain resolution.

Beam dynamics validation of the Halbach Technology FFAG Cell for Cornell-BNL Energy Recovery Linac

NASA Astrophysics Data System (ADS)

Méot, F.; Tsoupas, N.; Brooks, S.; Trbojevic, D.

2018-07-01

The Cornell-BNL Electron Test Accelerator (CBETA), a 150 MeV energy recovery linac (ERL) now in construction at Cornell, employs a fixed-field alternating gradient optics return loop: a single beam line comprised of FFAG cells, which accepts four recirculated energies. CBETA FFAG cell uses Halbach permanent magnet technology, its design studies have covered an extended period of time supported by extensive particle dynamics simulations using computed 3-D field map models. This approach is discussed, and illustrated here, based on the final stage in these beam dynamics studies, namely the validation of a ultimate, optimized design of the Halbach cell.

Noise facilitates transcriptional control under dynamic inputs.

PubMed

Kellogg, Ryan A; Tay, Savaş

2015-01-29

Cells must respond sensitively to time-varying inputs in complex signaling environments. To understand how signaling networks process dynamic inputs into gene expression outputs and the role of noise in cellular information processing, we studied the immune pathway NF-κB under periodic cytokine inputs using microfluidic single-cell measurements and stochastic modeling. We find that NF-κB dynamics in fibroblasts synchronize with oscillating TNF signal and become entrained, leading to significantly increased NF-κB oscillation amplitude and mRNA output compared to non-entrained response. Simulations show that intrinsic biochemical noise in individual cells improves NF-κB oscillation and entrainment, whereas cell-to-cell variability in NF-κB natural frequency creates population robustness, together enabling entrainment over a wider range of dynamic inputs. This wide range is confirmed by experiments where entrained cells were measured under all input periods. These results indicate that synergy between oscillation and noise allows cells to achieve efficient gene expression in dynamically changing signaling environments. Copyright © 2015 Elsevier Inc. All rights reserved.

Agent-Based Modeling of Cancer Stem Cell Driven Solid Tumor Growth.

PubMed

Poleszczuk, Jan; Macklin, Paul; Enderling, Heiko

2016-01-01

Computational modeling of tumor growth has become an invaluable tool to simulate complex cell-cell interactions and emerging population-level dynamics. Agent-based models are commonly used to describe the behavior and interaction of individual cells in different environments. Behavioral rules can be informed and calibrated by in vitro assays, and emerging population-level dynamics may be validated with both in vitro and in vivo experiments. Here, we describe the design and implementation of a lattice-based agent-based model of cancer stem cell driven tumor growth.

Relevant interactions of antimicrobial iron chelators and membrane models revealed by nuclear magnetic resonance and molecular dynamics simulations.

PubMed

Coimbra, João T S; Moniz, Tânia; Brás, Natércia F; Ivanova, Galya; Fernandes, Pedro A; Ramos, Maria J; Rangel, Maria

2014-12-18

The dynamics and interaction of 3-hydroxy-4-pyridinone fluorescent iron chelators, exhibiting antimicrobial properties, with biological membranes were evaluated through NMR and molecular dynamics simulations. Both NMR and MD simulation results support a strong interaction of the chelators with the lipid bilayers that seems to be strengthened for the rhodamine containing compounds, in particular for compounds that include ethyl groups and a thiourea link. For the latter type of compounds the interaction reaches the hydrophobic core of the lipid bilayer. The molecular docking and MD simulations performed for the potential interaction of the chelators with DC-SIGN receptors provide valuable information regarding the cellular uptake of these compounds since the results show that the fluorophore fragment of the molecular framework is essential for an efficient binding. Putting together our previous and present results, we put forward the hypothesis that all the studied fluorescent chelators have access to the cell, their uptake occurs through different pathways and their permeation properties correlate with a better access to the cell and its compartments and, consequently, with the chelators antimicrobial properties.

Particle-In-Cell simulations of electron beam microbunching instability in three dimensions

NASA Astrophysics Data System (ADS)

Huang, Chengkun; Zeng, Y.; Meyers, M. D.; Yi, S.; Albright, B. J.; Kwan, T. J. T.

2013-10-01

Microbunching instability due to Coherent Synchrotron Radiation (CSR) in a magnetic chicane is one of the major effects that can degrade the electron beam quality in an X-ray Free Electron Laser. Self-consistent simulation using the Particle-In-Cell (PIC) method for the CSR fields of the beam and their effects on beam dynamics have been elusive due to the excessive dispersion error on the grid. We have implemented a high-order finite-volume PIC scheme that models the propagation of the CSR fields accurately. This new scheme is characterized and optimized through a detailed dispersion analysis. The CSR fields from our improved PIC calculation are compared to the extended CSR numerical model based on the Lienard-Wiechert formula in 2D/3D. We also conduct beam dynamics simulation of the microbunching instability using our new PIC capability. Detailed self-consistent PIC simulations of the CSR fields and beam dynamics will be presented and discussed. Work supported by the U.S. Department of Energy through the LDRD program at Los Alamos National Laboratory.

Ensemble MD simulations restrained via crystallographic data: Accurate structure leads to accurate dynamics

PubMed Central

Xue, Yi; Skrynnikov, Nikolai R

2014-01-01

Currently, the best existing molecular dynamics (MD) force fields cannot accurately reproduce the global free-energy minimum which realizes the experimental protein structure. As a result, long MD trajectories tend to drift away from the starting coordinates (e.g., crystallographic structures). To address this problem, we have devised a new simulation strategy aimed at protein crystals. An MD simulation of protein crystal is essentially an ensemble simulation involving multiple protein molecules in a crystal unit cell (or a block of unit cells). To ensure that average protein coordinates remain correct during the simulation, we introduced crystallography-based restraints into the MD protocol. Because these restraints are aimed at the ensemble-average structure, they have only minimal impact on conformational dynamics of the individual protein molecules. So long as the average structure remains reasonable, the proteins move in a native-like fashion as dictated by the original force field. To validate this approach, we have used the data from solid-state NMR spectroscopy, which is the orthogonal experimental technique uniquely sensitive to protein local dynamics. The new method has been tested on the well-established model protein, ubiquitin. The ensemble-restrained MD simulations produced lower crystallographic R factors than conventional simulations; they also led to more accurate predictions for crystallographic temperature factors, solid-state chemical shifts, and backbone order parameters. The predictions for 15N R1 relaxation rates are at least as accurate as those obtained from conventional simulations. Taken together, these results suggest that the presented trajectories may be among the most realistic protein MD simulations ever reported. In this context, the ensemble restraints based on high-resolution crystallographic data can be viewed as protein-specific empirical corrections to the standard force fields. PMID:24452989

Dynamics of electrical double layer formation in room-temperature ionic liquids under constant-current charging conditions

NASA Astrophysics Data System (ADS)

Jiang, Xikai; Huang, Jingsong; Zhao, Hui; Sumpter, Bobby G.; Qiao, Rui

2014-07-01

We report detailed simulation results on the formation dynamics of an electrical double layer (EDL) inside an electrochemical cell featuring room-temperature ionic liquids (RTILs) enclosed between two planar electrodes. Under relatively small charging currents, the evolution of cell potential from molecular dynamics (MD) simulations during charging can be suitably predicted by the Landau-Ginzburg-type continuum model proposed recently (Bazant et al 2011 Phys. Rev. Lett. 106 046102). Under very large charging currents, the cell potential from MD simulations shows pronounced oscillation during the initial stage of charging, a feature not captured by the continuum model. Such oscillation originates from the sequential growth of the ionic space charge layers near the electrode surface. This allows the evolution of EDLs in RTILs with time, an atomistic process difficult to visualize experimentally, to be studied by analyzing the cell potential under constant-current charging conditions. While the continuum model cannot predict the potential oscillation under such far-from-equilibrium charging conditions, it can nevertheless qualitatively capture the growth of cell potential during the later stage of charging. Improving the continuum model by introducing frequency-dependent dielectric constant and density-dependent ion diffusion coefficients may help to further extend the applicability of the model. The evolution of ion density profiles is also compared between the MD and the continuum model, showing good agreement.

Dynamics of electrical double layer formation in room-temperature ionic liquids under constant-current charging conditions.

PubMed

Jiang, Xikai; Huang, Jingsong; Zhao, Hui; Sumpter, Bobby G; Qiao, Rui

2014-07-16

We report detailed simulation results on the formation dynamics of an electrical double layer (EDL) inside an electrochemical cell featuring room-temperature ionic liquids (RTILs) enclosed between two planar electrodes. Under relatively small charging currents, the evolution of cell potential from molecular dynamics (MD) simulations during charging can be suitably predicted by the Landau-Ginzburg-type continuum model proposed recently (Bazant et al 2011 Phys. Rev. Lett. 106 046102). Under very large charging currents, the cell potential from MD simulations shows pronounced oscillation during the initial stage of charging, a feature not captured by the continuum model. Such oscillation originates from the sequential growth of the ionic space charge layers near the electrode surface. This allows the evolution of EDLs in RTILs with time, an atomistic process difficult to visualize experimentally, to be studied by analyzing the cell potential under constant-current charging conditions. While the continuum model cannot predict the potential oscillation under such far-from-equilibrium charging conditions, it can nevertheless qualitatively capture the growth of cell potential during the later stage of charging. Improving the continuum model by introducing frequency-dependent dielectric constant and density-dependent ion diffusion coefficients may help to further extend the applicability of the model. The evolution of ion density profiles is also compared between the MD and the continuum model, showing good agreement.

Modeling the dynamics of chromosomal alteration progression in cervical cancer: A computational model

PubMed Central

2017-01-01

Computational modeling has been applied to simulate the heterogeneity of cancer behavior. The development of Cervical Cancer (CC) is a process in which the cell acquires dynamic behavior from non-deleterious and deleterious mutations, exhibiting chromosomal alterations as a manifestation of this dynamic. To further determine the progression of chromosomal alterations in precursor lesions and CC, we introduce a computational model to study the dynamics of deleterious and non-deleterious mutations as an outcome of tumor progression. The analysis of chromosomal alterations mediated by our model reveals that multiple deleterious mutations are more frequent in precursor lesions than in CC. Cells with lethal deleterious mutations would be eliminated, which would mitigate cancer progression; on the other hand, cells with non-deleterious mutations would become dominant, which could predispose them to cancer progression. The study of somatic alterations through computer simulations of cancer progression provides a feasible pathway for insights into the transformation of cell mechanisms in humans. During cancer progression, tumors may acquire new phenotype traits, such as the ability to invade and metastasize or to become clinically important when they develop drug resistance. Non-deleterious chromosomal alterations contribute to this progression. PMID:28723940

The pivotal role of angiogenesis in a multi-scale modeling of tumor growth exhibiting the avascular and vascular phases.

PubMed

Salavati, Hooman; Soltani, M; Amanpour, Saeid

2018-05-06

The mechanisms involved in tumor growth mainly occur at the microenvironment, where the interactions between the intracellular, intercellular and extracellular scales mediate the dynamics of tumor. In this work, we present a multi-scale model of solid tumor dynamics to simulate the avascular and vascular growth as well as tumor-induced angiogenesis. The extracellular and intercellular scales are modeled using partial differential equations and cellular Potts model, respectively. Also, few biochemical and biophysical rules control the dynamics of intracellular level. On the other hand, the growth of melanoma tumors is modeled in an animal in-vivo study to evaluate the simulation. The simulation shows that the model successfully reproduces a completed image of processes involved in tumor growth such as avascular and vascular growth as well as angiogenesis. The model incorporates the phenotypes of cancerous cells including proliferating, quiescent and necrotic cells, as well as endothelial cells during angiogenesis. The results clearly demonstrate the pivotal effect of angiogenesis on the progression of cancerous cells. Also, the model exhibits important events in tumor-induced angiogenesis like anastomosis. Moreover, the computational trend of tumor growth closely follows the observations in the experimental study. Copyright © 2018 Elsevier Inc. All rights reserved.

Single cell model for simultaneous drug delivery and efflux.

PubMed

Yi, C; Saidel, G M; Gratzl, M

1999-01-01

Multidrug resistance (MDR) of some cancer cells is a major challenge for chemotherapy of systemic cancers to overcome. To experimentally uncover the cellular mechanisms leading to MDR, it is necessary to quantitatively assess both drug influx into, and efflux from, the cells exposed to drug treatment. By using a novel molecular microdelivery system to enforce continuous and adjustable drug influx into single cells by controlled diffusion through a gel plug in a micropipet tip, drug resistance studies can now be performed on the single cell level. Our dynamic model of this scheme incorporates drug delivery, diffusive mixing, and accumulation inside the cytoplasm, and efflux by both passive and active membrane transport. Model simulations using available experimental information on these processes can assist in the design of MDR related experiments on single cancer cells which are expected to lead to a quantitative evaluation of mechanisms. Simulations indicate that drug resistance of a cancer cell can be quantified better by its dynamic response than by steady-state analysis.

Study on dynamic performance of SOFC

NASA Astrophysics Data System (ADS)

Zhan, Haiyang; Liang, Qianchao; Wen, Qiang; Zhu, Runkai

2017-05-01

In order to solve the problem of real-time matching of load and fuel cell power, it is urgent to study the dynamic response process of SOFC in the case of load mutation. The mathematical model of SOFC is constructed, and its performance is simulated. The model consider the influence factors such as polarization effect, ohmic loss. It also takes the diffusion effect, thermal effect, energy exchange, mass conservation, momentum conservation. One dimensional dynamic mathematical model of SOFC is constructed by using distributed lumped parameter method. The simulation results show that the I-V characteristic curves are in good agreement with the experimental data, and the accuracy of the model is verified. The voltage response curve, power response curve and the efficiency curve are obtained by this way. It lays a solid foundation for the research of dynamic performance and optimal control in power generation system of high power fuel cell stack.

T-cell epitope prediction and immune complex simulation using molecular dynamics: state of the art and persisting challenges

PubMed Central

2010-01-01

Atomistic Molecular Dynamics provides powerful and flexible tools for the prediction and analysis of molecular and macromolecular systems. Specifically, it provides a means by which we can measure theoretically that which cannot be measured experimentally: the dynamic time-evolution of complex systems comprising atoms and molecules. It is particularly suitable for the simulation and analysis of the otherwise inaccessible details of MHC-peptide interaction and, on a larger scale, the simulation of the immune synapse. Progress has been relatively tentative yet the emergence of truly high-performance computing and the development of coarse-grained simulation now offers us the hope of accurately predicting thermodynamic parameters and of simulating not merely a handful of proteins but larger, longer simulations comprising thousands of protein molecules and the cellular scale structures they form. We exemplify this within the context of immunoinformatics. PMID:21067546

A dynamic plug flow reactor model for a vanadium redox flow battery cell

NASA Astrophysics Data System (ADS)

Li, Yifeng; Skyllas-Kazacos, Maria; Bao, Jie

2016-04-01

A dynamic plug flow reactor model for a single cell VRB system is developed based on material balance, and the Nernst equation is employed to calculate cell voltage with consideration of activation and concentration overpotentials. Simulation studies were conducted under various conditions to investigate the effects of several key operation variables including electrolyte flow rate, upper SOC limit and input current magnitude on the cell charging performance. The results show that all three variables have a great impact on performance, particularly on the possibility of gassing during charging at high SOCs or inadequate flow rates. Simulations were also carried out to study the effects of electrolyte imbalance during long term charging and discharging cycling. The results show the minimum electrolyte flow rate needed for operation within a particular SOC range in order to avoid gassing side reactions during charging. The model also allows scheduling of partial electrolyte remixing operations to restore capacity and also avoid possible gassing side reactions during charging. Simulation results also suggest the proper placement for cell voltage monitoring and highlight potential problems associated with setting the upper charging cut-off limit based on the inlet SOC calculated from the open-circuit cell voltage measurement.

Dynamic motion of red blood cells in simple shear flow

NASA Astrophysics Data System (ADS)

Sui, Y.; Chew, Y. T.; Roy, P.; Cheng, Y. P.; Low, H. T.

2008-11-01

A three-dimensional numerical model is proposed to simulate the dynamic motion of red blood cells (RBCs) in simple shear flow. The RBCs are approximated by ghost cells consisting of Newtonian liquid drops enclosed by Skalak membranes which take into account the membrane shear elasticity and the membrane area incompressibility. The RBCs have an initially biconcave discoid resting shape, and the internal liquid is assumed to have the same physical properties as the matrix fluid. The simulation is based on a hybrid method, in which the immersed boundary concept is introduced into the framework of the lattice Boltzmann method, and a finite element model is incorporated to obtain the forces acting on the nodes of the cell membrane which is discretized into flat triangular elements. The dynamic motion of RBCs is investigated in simple shear flow under a broad range of shear rates. At large shear rates, the cells are found to carry out a swinging motion, in which periodic inclination oscillation and shape deformation superimpose on the membrane tank treading motion. With the shear rate decreasing, the swinging amplitude of the cell increases, and finally triggers a transition to tumbling motion. This is the first direct numerical simulation that predicts both the swinging motion of the RBCs and the shear rate induced transition, which have been observed in a recent experiment. It is also found that as the mode changes from swinging to tumbling, the apparent viscosity of the suspension increases monotonically.

A CONTINUUM HARD-SPHERE MODEL OF PROTEIN ADSORPTION

PubMed Central

Finch, Craig; Clarke, Thomas; Hickman, James J.

2012-01-01

Protein adsorption plays a significant role in biological phenomena such as cell-surface interactions and the coagulation of blood. Two-dimensional random sequential adsorption (RSA) models are widely used to model the adsorption of proteins on solid surfaces. Continuum equations have been developed so that the results of RSA simulations can be used to predict the kinetics of adsorption. Recently, Brownian dynamics simulations have become popular for modeling protein adsorption. In this work a continuum model was developed to allow the results from a Brownian dynamics simulation to be used as the boundary condition in a computational fluid dynamics (CFD) simulation. Brownian dynamics simulations were used to model the diffusive transport of hard-sphere particles in a liquid and the adsorption of the particles onto a solid surface. The configuration of the adsorbed particles was analyzed to quantify the chemical potential near the surface, which was found to be a function of the distance from the surface and the fractional surface coverage. The near-surface chemical potential was used to derive a continuum model of adsorption that incorporates the results from the Brownian dynamics simulations. The equations of the continuum model were discretized and coupled to a CFD simulation of diffusive transport to the surface. The kinetics of adsorption predicted by the continuum model closely matched the results from the Brownian dynamics simulation. This new model allows the results from mesoscale simulations to be incorporated into micro- or macro-scale CFD transport simulations of protein adsorption in practical devices. PMID:23729843

Integrating open-source software applications to build molecular dynamics systems.

PubMed

Allen, Bruce M; Predecki, Paul K; Kumosa, Maciej

2014-04-05

Three open-source applications, NanoEngineer-1, packmol, and mis2lmp are integrated using an open-source file format to quickly create molecular dynamics (MD) cells for simulation. The three software applications collectively make up the open-source software (OSS) suite known as MD Studio (MDS). The software is validated through software engineering practices and is verified through simulation of the diglycidyl ether of bisphenol-a and isophorone diamine (DGEBA/IPD) system. Multiple simulations are run using the MDS software to create MD cells, and the data generated are used to calculate density, bulk modulus, and glass transition temperature of the DGEBA/IPD system. Simulation results compare well with published experimental and numerical results. The MDS software prototype confirms that OSS applications can be analyzed against real-world research requirements and integrated to create a new capability. Copyright © 2014 Wiley Periodicals, Inc.

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

Spatial simulation of forest succession and timber harvesting using LANDIS

Treesearch

Eric J. Gustafson; Stephen R. Shifley; David J. Mladenoff; Kevin K. Nimerfro; Hong S. He

2000-01-01

The LANDIS model simulates ecological dynamics, including forest succession, disturbance, seed dispersal and establishment, fire and wind disturbance, and their interactions. We describe the addition to LANDIS of capabilities to simulate forest vegetation management, including harvest. Stands (groups of cells) are prioritized for harvest using one of four ranking...

Dynamical System Modeling to Simulate Donor T Cell Response to Whole Exome Sequencing-Derived Recipient Peptides Demonstrates Different Alloreactivity Potential in HLA-Matched and -Mismatched Donor-Recipient Pairs.

PubMed

Abdul Razzaq, Badar; Scalora, Allison; Koparde, Vishal N; Meier, Jeremy; Mahmood, Musa; Salman, Salman; Jameson-Lee, Max; Serrano, Myrna G; Sheth, Nihar; Voelkner, Mark; Kobulnicky, David J; Roberts, Catherine H; Ferreira-Gonzalez, Andrea; Manjili, Masoud H; Buck, Gregory A; Neale, Michael C; Toor, Amir A

2016-05-01

Immune reconstitution kinetics and subsequent clinical outcomes in HLA-matched recipients of allogeneic stem cell transplantation (SCT) are variable and difficult to predict. Considering SCT as a dynamical system may allow sequence differences across the exomes of the transplant donors and recipients to be used to simulate an alloreactive T cell response, which may allow better clinical outcome prediction. To accomplish this, whole exome sequencing was performed on 34 HLA-matched SCT donor-recipient pairs (DRPs) and the nucleotide sequence differences translated to peptides. The binding affinity of the peptides to the relevant HLA in each DRP was determined. The resulting array of peptide-HLA binding affinity values in each patient was considered as an operator modifying a hypothetical T cell repertoire vector, in which each T cell clone proliferates in accordance with the logistic equation of growth. Using an iterating system of matrices, each simulated T cell clone's growth was calculated with the steady-state population being proportional to the magnitude of the binding affinity of the driving HLA-peptide complex. Incorporating competition between T cell clones responding to different HLA-peptide complexes reproduces a number of features of clinically observed T cell clonal repertoire in the simulated repertoire, including sigmoidal growth kinetics of individual T cell clones and overall repertoire, Power Law clonal frequency distribution, increase in repertoire complexity over time with increasing clonal diversity, and alteration of clonal dominance when a different antigen array is encountered, such as in SCT. The simulated, alloreactive T cell repertoire was markedly different in HLA-matched DRPs. The patterns were differentiated by rate of growth and steady-state magnitude of the simulated T cell repertoire and demonstrate a possible correlation with survival. In conclusion, exome wide sequence differences in DRPs may allow simulation of donor alloreactive T cell response to recipient antigens and may provide a quantitative basis for refining donor selection and titration of immunosuppression after SCT. Copyright © 2016 American Society for Blood and Marrow Transplantation. Published by Elsevier Inc. All rights reserved.

Stabilization of Model Membrane Systems by Disaccharides. Quasielastic Neutron Scattering Experiments and Atomistic Simulations

NASA Astrophysics Data System (ADS)

Doxastakis, Emmanouil; Garcia Sakai, Victoria; Ohtake, Satoshi; Maranas, Janna K.; de Pablo, Juan J.

2006-03-01

Trehalose, a disaccharide of glucose, is often used for the stabilization of cell membranes in the absence of water. This work studies the effects of trehalose on model membrane systems as they undergo a melting transition using a combination of experimental methods and atomistic molecular simulations. Quasielastic neutron scattering experiments on selectively deuterated samples provide the incoherent dynamic structure over a wide time range. Elastic scans probing the lipid tail dynamics display clear evidence of a main melting transition that is significantly lowered in the presence of trehalose. Lipid headgroup mobility is considerably restricted at high temperatures and directly associated with the dynamics of the sugar in the mixture. Molecular simulations provide a detailed overview of the dynamics and their spatial and time dependence. The combined simulation and experimental methodology offers a unique, molecular view of the physics of systems commonly employed in cryopreservation and lyophilization processes.

Integration of Multiple Data Sources to Simulate the Dynamics of Land Systems

PubMed Central

Deng, Xiangzheng; Su, Hongbo; Zhan, Jinyan

2008-01-01

In this paper we present and develop a new model, which we have called Dynamics of Land Systems (DLS). The DLS model is capable of integrating multiple data sources to simulate the dynamics of a land system. Three main modules are incorporated in DLS: a spatial regression module, to explore the relationship between land uses and influencing factors, a scenario analysis module of the land uses of a region during the simulation period and a spatial disaggregation module, to allocate land use changes from a regional level to disaggregated grid cells. A case study on Taips County in North China is incorporated in this paper to test the functionality of DLS. The simulation results under the baseline, economic priority and environmental scenarios help to understand the land system dynamics and project near future land-use trajectories of a region, in order to focus management decisions on land uses and land use planning. PMID:27879726

Swimming motility plays a key role in the stochastic dynamics of cell clumping

NASA Astrophysics Data System (ADS)

Qi, Xianghong; Nellas, Ricky B.; Byrn, Matthew W.; Russell, Matthew H.; Bible, Amber N.; Alexandre, Gladys; Shen, Tongye

2013-04-01

Dynamic cell-to-cell interactions are a prerequisite to many biological processes, including development and biofilm formation. Flagellum induced motility has been shown to modulate the initial cell-cell or cell-surface interaction and to contribute to the emergence of macroscopic patterns. While the role of swimming motility in surface colonization has been analyzed in some detail, a quantitative physical analysis of transient interactions between motile cells is lacking. We examined the Brownian dynamics of swimming cells in a crowded environment using a model of motorized adhesive tandem particles. Focusing on the motility and geometry of an exemplary motile bacterium Azospirillum brasilense, which is capable of transient cell-cell association (clumping), we constructed a physical model with proper parameters for the computer simulation of the clumping dynamics. By modulating mechanical interaction (‘stickiness’) between cells and swimming speed, we investigated how equilibrium and active features affect the clumping dynamics. We found that the modulation of active motion is required for the initial aggregation of cells to occur at a realistic time scale. Slowing down the rotation of flagellar motors (and thus swimming speeds) is correlated to the degree of clumping, which is consistent with the experimental results obtained for A. brasilense.

Weighted Ensemble Simulation: Review of Methodology, Applications, and Software

PubMed Central

Zuckerman, Daniel M.; Chong, Lillian T.

2018-01-01

The weighted ensemble (WE) methodology orchestrates quasi-independent parallel simulations run with intermittent communication that can enhance sampling of rare events such as protein conformational changes, folding, and binding. The WE strategy can achieve superlinear scaling—the unbiased estimation of key observables such as rate constants and equilibrium state populations to greater precision than would be possible with ordinary parallel simulation. WE software can be used to control any dynamics engine, such as standard molecular dynamics and cell-modeling packages. This article reviews the theoretical basis of WE and goes on to describe successful applications to a number of complex biological processes—protein conformational transitions, (un)binding, and assembly processes, as well as cell-scale processes in systems biology. We furthermore discuss the challenges that need to be overcome in the next phase of WE methodological development. Overall, the combined advances in WE methodology and software have enabled the simulation of long-timescale processes that would otherwise not be practical on typical computing resources using standard simulation. PMID:28301772

Dynamic Performance Comparison for MPPT-PV Systems using Hybrid Pspice/Matlab Simulation

NASA Astrophysics Data System (ADS)

Aouchiche, N.; Becherif, M.; HadjArab, A.; Aitcheikh, M. S.; Ramadan, H. S.; Cheknane, A.

2016-10-01

The power generated by solar photovoltaic (PV) module depends on the surrounding irradiance and temperature. This paper presents a hybrid Matlab™/Pspice™ simulation model of PV system, combined with Cadence software SLPS. The hybridization is performed in order to gain the advantages of both simulation tools such as accuracy and efficiency in both Pspice electronic circuit and Matlab™ mathematical modelling respectively. For this purpose, the PV panel and the boost converter are developed using Pspice™ and hybridized with the mathematical Matlab™ model of maximum power point method controller (MPPT) through SLPS. The main objective is verify the significance of using the proposed hybrid simulation techniques in comparing the different MPPT algorithms such as the perturbation and observation (P&O), incremental of conductance (Inc-Cond) and counter reaction voltage using pilot cell (Pilot-Cell). Various simulations are performed under different atmospheric conditions in order to evaluate the dynamic behaviour for the system under study in terms of stability, efficiency and rapidity.

Weighted Ensemble Simulation: Review of Methodology, Applications, and Software.

PubMed

Zuckerman, Daniel M; Chong, Lillian T

2017-05-22

The weighted ensemble (WE) methodology orchestrates quasi-independent parallel simulations run with intermittent communication that can enhance sampling of rare events such as protein conformational changes, folding, and binding. The WE strategy can achieve superlinear scaling-the unbiased estimation of key observables such as rate constants and equilibrium state populations to greater precision than would be possible with ordinary parallel simulation. WE software can be used to control any dynamics engine, such as standard molecular dynamics and cell-modeling packages. This article reviews the theoretical basis of WE and goes on to describe successful applications to a number of complex biological processes-protein conformational transitions, (un)binding, and assembly processes, as well as cell-scale processes in systems biology. We furthermore discuss the challenges that need to be overcome in the next phase of WE methodological development. Overall, the combined advances in WE methodology and software have enabled the simulation of long-timescale processes that would otherwise not be practical on typical computing resources using standard simulation.

Voxel based parallel post processor for void nucleation and growth analysis of atomistic simulations of material fracture.

PubMed

Hemani, H; Warrier, M; Sakthivel, N; Chaturvedi, S

2014-05-01

Molecular dynamics (MD) simulations are used in the study of void nucleation and growth in crystals that are subjected to tensile deformation. These simulations are run for typically several hundred thousand time steps depending on the problem. We output the atom positions at a required frequency for post processing to determine the void nucleation, growth and coalescence due to tensile deformation. The simulation volume is broken up into voxels of size equal to the unit cell size of crystal. In this paper, we present the algorithm to identify the empty unit cells (voids), their connections (void size) and dynamic changes (growth and coalescence of voids) for MD simulations of large atomic systems (multi-million atoms). We discuss the parallel algorithms that were implemented and discuss their relative applicability in terms of their speedup and scalability. We also present the results on scalability of our algorithm when it is incorporated into MD software LAMMPS. Copyright © 2014 Elsevier Inc. All rights reserved.

In Silico Dynamics: computer simulation in a Virtual Embryo (SOT)

EPA Science Inventory

Abstract: Utilizing cell biological information to predict higher order biological processes is a significant challenge in predictive toxicology. This is especially true for highly dynamical systems such as the embryo where morphogenesis, growth and differentiation require preci...

Simulations of transient membrane behavior in cells subjected to a high-intensity ultrashort electric pulse.

PubMed

Hu, Q; Viswanadham, S; Joshi, R P; Schoenbach, K H; Beebe, S J; Blackmore, P F

2005-03-01

A molecular dynamics (MD) scheme is combined with a distributed circuit model for a self-consistent analysis of the transient membrane response for cells subjected to an ultrashort (nanosecond) high-intensity (approximately 0.01-V/nm spatially averaged field) voltage pulse. The dynamical, stochastic, many-body aspects are treated at the molecular level by resorting to a course-grained representation of the membrane lipid molecules. Coupling the Smoluchowski equation to the distributed electrical model for current flow provides the time-dependent transmembrane fields for the MD simulations. A good match between the simulation results and available experimental data is obtained. Predictions include pore formation times of about 5-6 ns. It is also shown that the pore formation process would tend to begin from the anodic side of an electrically stressed membrane. Furthermore, the present simulations demonstrate that ions could facilitate pore formation. This could be of practical importance and have direct relevance to the recent observations of calcium release from the endoplasmic reticulum in cells subjected to such ultrashort, high-intensity pulses.

Modelling and simulation of fuel cell dynamics for electrical energy usage of Hercules airplanes.

PubMed

Radmanesh, Hamid; Heidari Yazdi, Seyed Saeid; Gharehpetian, G B; Fathi, S H

2014-01-01

Dynamics of proton exchange membrane fuel cells (PEMFC) with hydrogen storage system for generating part of Hercules airplanes electrical energy is presented. Feasibility of using fuel cell (FC) for this airplane is evaluated by means of simulations. Temperature change and dual layer capacity effect are considered in all simulations. Using a three-level 3-phase inverter, FC's output voltage is connected to the essential bus of the airplane. Moreover, it is possible to connect FC's output voltage to airplane DC bus alternatively. PID controller is presented to control flow of hydrogen and oxygen to FC and improve transient and steady state responses of the output voltage to load disturbances. FC's output voltage is regulated via an ultracapacitor. Simulations are carried out via MATLAB/SIMULINK and results show that the load tracking and output voltage regulation are acceptable. The proposed system utilizes an electrolyser to generate hydrogen and a tank for storage. Therefore, there is no need for batteries. Moreover, the generated oxygen could be used in other applications in airplane.

Modelling and Simulation of Fuel Cell Dynamics for Electrical Energy Usage of Hercules Airplanes

PubMed Central

Radmanesh, Hamid; Heidari Yazdi, Seyed Saeid; Gharehpetian, G. B.; Fathi, S. H.

2014-01-01

Dynamics of proton exchange membrane fuel cells (PEMFC) with hydrogen storage system for generating part of Hercules airplanes electrical energy is presented. Feasibility of using fuel cell (FC) for this airplane is evaluated by means of simulations. Temperature change and dual layer capacity effect are considered in all simulations. Using a three-level 3-phase inverter, FC's output voltage is connected to the essential bus of the airplane. Moreover, it is possible to connect FC's output voltage to airplane DC bus alternatively. PID controller is presented to control flow of hydrogen and oxygen to FC and improve transient and steady state responses of the output voltage to load disturbances. FC's output voltage is regulated via an ultracapacitor. Simulations are carried out via MATLAB/SIMULINK and results show that the load tracking and output voltage regulation are acceptable. The proposed system utilizes an electrolyser to generate hydrogen and a tank for storage. Therefore, there is no need for batteries. Moreover, the generated oxygen could be used in other applications in airplane. PMID:24782664

A Huygens immersed-finite-element particle-in-cell method for modeling plasma-surface interactions with moving interface

NASA Astrophysics Data System (ADS)

Cao, Huijun; Cao, Yong; Chu, Yuchuan; He, Xiaoming; Lin, Tao

2018-06-01

Surface evolution is an unavoidable issue in engineering plasma applications. In this article an iterative method for modeling plasma-surface interactions with moving interface is proposed and validated. In this method, the plasma dynamics is simulated by an immersed finite element particle-in-cell (IFE-PIC) method, and the surface evolution is modeled by the Huygens wavelet method which is coupled with the iteration of the IFE-PIC method. Numerical experiments, including prototypical engineering applications, such as the erosion of Hall thruster channel wall, are presented to demonstrate features of this Huygens IFE-PIC method for simulating the dynamic plasma-surface interactions.

Multipole Algorithms for Molecular Dynamics Simulation on High Performance Computers.

NASA Astrophysics Data System (ADS)

Elliott, William Dewey

1995-01-01

A fundamental problem in modeling large molecular systems with molecular dynamics (MD) simulations is the underlying N-body problem of computing the interactions between all pairs of N atoms. The simplest algorithm to compute pair-wise atomic interactions scales in runtime {cal O}(N^2), making it impractical for interesting biomolecular systems, which can contain millions of atoms. Recently, several algorithms have become available that solve the N-body problem by computing the effects of all pair-wise interactions while scaling in runtime less than {cal O}(N^2). One algorithm, which scales {cal O}(N) for a uniform distribution of particles, is called the Greengard-Rokhlin Fast Multipole Algorithm (FMA). This work describes an FMA-like algorithm called the Molecular Dynamics Multipole Algorithm (MDMA). The algorithm contains several features that are new to N-body algorithms. MDMA uses new, efficient series expansion equations to compute general 1/r^{n } potentials to arbitrary accuracy. In particular, the 1/r Coulomb potential and the 1/r^6 portion of the Lennard-Jones potential are implemented. The new equations are based on multivariate Taylor series expansions. In addition, MDMA uses a cell-to-cell interaction region of cells that is closely tied to worst case error bounds. The worst case error bounds for MDMA are derived in this work also. These bounds apply to other multipole algorithms as well. Several implementation enhancements are described which apply to MDMA as well as other N-body algorithms such as FMA and tree codes. The mathematics of the cell -to-cell interactions are converted to the Fourier domain for reduced operation count and faster computation. A relative indexing scheme was devised to locate cells in the interaction region which allows efficient pre-computation of redundant information and prestorage of much of the cell-to-cell interaction. Also, MDMA was integrated into the MD program SIgMA to demonstrate the performance of the program over several simulation timesteps. One MD application described here highlights the utility of including long range contributions to Lennard-Jones potential in constant pressure simulations. Another application shows the time dependence of long range forces in a multiple time step MD simulation.

Numerical simulation of a mini PEMFC stack

NASA Astrophysics Data System (ADS)

Liu, Zhixiang; Mao, Zongqiang; Wang, Cheng; Zhuge, Weilin; Zhang, Yangjun

Fuel cell modeling and simulation has aroused much attention recently because it can probe transport and reaction mechanism. In this paper, a computational fuel cell dynamics (CFCD) method was applied to simulate a proton exchange membrane fuel cell (PEMFC) stack for the first time. The air cooling mini fuel cell stack consisted of six cells, in which the active area was 8 cm 2 (2 cm × 4 cm). With reasonable simplification, the computational elements were effectively reduced and allowed a simulation which could be conducted on a personal computer without large-scale parallel computation. The results indicated that the temperature gradient inside the fuel cell stack was determined by the flow rate of the cooling air. If the air flow rate is too low, the stack could not be effectively cooled and the temperature will rise to a range that might cause unstable stack operation.

Beam dynamics validation of the Halbach Technology FFAG Cell for Cornell-BNL Energy Recovery Linac

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

Meot, Francois; Tsoupas, N.; Brooks, S.

The Cornell-BNL Electron Test Accelerator (CBETA), a 150 MeV energy recovery linac (ERL) now in construction at Cornell, employs a fixed-field alternating gradient optics return loop: a single beam line comprised of FFAG cells, which accepts four recirculated energies. CBETA FFAG cell uses Halbach permanent magnet technology, its design studies have covered an extended period of time supported by extensive particle dynamics simulations using computed 3-D field map models. As a result, this approach is discussed, and illustrated here, based on the final stage in these beam dynamics studies, namely the validation of a ultimate, optimized design of the Halbachmore » cell.« less

Beam dynamics validation of the Halbach Technology FFAG Cell for Cornell-BNL Energy Recovery Linac

DOE PAGES

Meot, Francois; Tsoupas, N.; Brooks, S.; ...

2018-04-16

The Cornell-BNL Electron Test Accelerator (CBETA), a 150 MeV energy recovery linac (ERL) now in construction at Cornell, employs a fixed-field alternating gradient optics return loop: a single beam line comprised of FFAG cells, which accepts four recirculated energies. CBETA FFAG cell uses Halbach permanent magnet technology, its design studies have covered an extended period of time supported by extensive particle dynamics simulations using computed 3-D field map models. As a result, this approach is discussed, and illustrated here, based on the final stage in these beam dynamics studies, namely the validation of a ultimate, optimized design of the Halbachmore » cell.« less

Mathematical model of the glucose-insulin regulatory system: From the bursting electrical activity in pancreatic β-cells to the glucose dynamics in the whole body

NASA Astrophysics Data System (ADS)

Han, Kyungreem; Kang, Hyuk; Choi, M. Y.; Kim, Jinwoong; Lee, Myung-Shik

2012-10-01

A theoretical approach to the glucose-insulin regulatory system is presented. By means of integrated mathematical modeling and extensive numerical simulations, we probe the cell-level dynamics of the membrane potential, intracellular Ca2+ concentration, and insulin secretion in pancreatic β-cells, together with the whole-body level glucose-insulin dynamics in the liver, brain, muscle, and adipose tissues. In particular, the three oscillatory modes of insulin secretion are reproduced successfully. Such comprehensive mathematical modeling may provide a theoretical basis for the simultaneous assessment of the β-cell function and insulin resistance in clinical examination.

Multiscale Modeling of Multiphase Fluid Flow

DTIC Science & Technology

2016-08-01

the disparate time and length scales involved in modeling fluid flow and heat transfer. Molecular dynamics simulations were carried out to provide a...fluid dynamics methods were used to investigate the heat transfer process in open-cell micro-foam with phase change material; enhancement of natural...Computational fluid dynamics, Heat transfer, Phase change material in Micro-foam, Molecular Dynamics, Multiphase flow, Multiscale modeling, Natural

Computational Model of Population Dynamics Based on the Cell Cycle and Local Interactions

NASA Astrophysics Data System (ADS)

Oprisan, Sorinel Adrian; Oprisan, Ana

2005-03-01

Our study bridges cellular (mesoscopic) level interactions and global population (macroscopic) dynamics of carcinoma. The morphological differences and transitions between well and smooth defined benign tumors and tentacular malignat tumors suggest a theoretical analysis of tumor invasion based on the development of mathematical models exhibiting bifurcations of spatial patterns in the density of tumor cells. Our computational model views the most representative and clinically relevant features of oncogenesis as a fight between two distinct sub-systems: the immune system of the host and the neoplastic system. We implemented the neoplastic sub-system using a three-stage cell cycle: active, dormant, and necrosis. The second considered sub-system consists of cytotoxic active (effector) cells — EC, with a very broad phenotype ranging from NK cells to CTL cells, macrophages, etc. Based on extensive numerical simulations, we correlated the fractal dimensions for carcinoma, which could be obtained from tumor imaging, with the malignat stage. Our computational model was able to also simulate the effects of surgical, chemotherapeutical, and radiotherapeutical treatments.

Implementing a modeling software for animated protein-complex interactions using a physics simulation library.

PubMed

Ueno, Yutaka; Ito, Shuntaro; Konagaya, Akihiko

2014-12-01

To better understand the behaviors and structural dynamics of proteins within a cell, novel software tools are being developed that can create molecular animations based on the findings of structural biology. This study proposes our method developed based on our prototypes to detect collisions and examine the soft-body dynamics of molecular models. The code was implemented with a software development toolkit for rigid-body dynamics simulation and a three-dimensional graphics library. The essential functions of the target software system included the basic molecular modeling environment, collision detection in the molecular models, and physical simulations of the movement of the model. Taking advantage of recent software technologies such as physics simulation modules and interpreted scripting language, the functions required for accurate and meaningful molecular animation were implemented efficiently.

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

Romanov, Gennady

Typically the RFQs are designed using the Parmteq, DesRFQ and other similar specialized codes, which produces the files containing the field and geometrical parameters for every cell. The beam dynamic simulations with these analytical fields a re, of course, ideal realizations of the designed RFQs. The new advanced computing capabilities made it possible to simulate beam and even dark current in the realistic 3D electromagnetic fields in the RFQs that may reflect cavity tuning, presence of tune rs and couplers, RFQ segmentation etc. The paper describes the utilization of full 3D field distribution obtained with CST Studio Suite for beammore » dynamic simulations using both PIC solver of CST Particle Studio and the beam dynamic code TRACK.« less

Characterization of Hydrophobic Interactions of Polymers with Water and Phospholipid Membranes Using Molecular Dynamics Simulations

NASA Astrophysics Data System (ADS)

Drenscko, Mihaela

Polymers and lipid membranes are both essential soft materials. The structure and hydrophobicity/hydrophilicity of polymers, as well as the solvent they are embedded in, ultimately determines their size and shape. Understating the variation of shape of the polymer as well as its interactions with model biological membranes can assist in understanding the biocompatibility of the polymer itself. Computer simulations, in particular molecular dynamics, can aid in characterization of the interaction of polymers with solvent, as well as polymers with model membranes. In this thesis, molecular dynamics serve to describe polymer interactions with a solvent (water) and with a lipid membrane. To begin with, we characterize the hydrophobic collapse of single polystyrene chains in water using molecular dynamics simulations. Specifically, we calculate the potential of mean force for the collapse of a single polystyrene chain in water using metadynamics, comparing the results between all atomistic with coarse-grained molecular simulation. We next explore the scaling behavior of the collapsed globular shape at the minimum energy configuration, characterized by the radius of gyration, as a function of chain length. The exponent is close to one third, consistent with that predicted for a polymer chain in bad solvent. We also explore the scaling behavior of the Solvent Accessible Surface Area (SASA) as a function of chain length, finding a similar exponent for both all-atomistic and coarse-grained simulations. Furthermore, calculation of the local water density as a function of chain length near the minimum energy configuration suggests that intermediate chain lengths are more likely to form dewetted states, as compared to shorter or longer chain lengths. Next, in order to investigate the molecular interactions between single hydrophobic polymer chains and lipids in biological membranes and at lipid membrane/solvent interface, we perform a series of molecular dynamics simulations of small membranes using all atomistic and coarse-grained methods. The molecular interaction between common polymer chains used in biomedical applications and the cell membrane is unknown. This interaction may affect the biocompatibility of the polymer chains. Molecular dynamics simulations offer an emerging tool to characterize the interaction between common degradable polymer chains used in biomedical applications, such as polycaprolactone, and model cell membranes. We systematically characterize with long-time all-atomistic molecular dynamics simulations the interaction between single polycaprolactone chains of varying chain lengths with a model phospholipid membrane. We find that the length of polymer chain greatly affects the nature of interaction with the membrane, as well as the membrane properties. Furthermore, we next utilize advanced sampling techniques in molecular dynamics to characterize the two-dimensional free energy surface for the interaction of varying polymer chain lengths (short, intermediate, and long) with model cell membranes. We find that the free energy minimum shifts from the membrane-water interface to the hydrophobic core of the phospholipid membrane as a function of chain length. These results can be used to design polymer chain lengths and chemistries to optimize their interaction with cell membranes at the molecular level.

Crystal water dynamics of guanosine dihydrate: analysis of atomic displacement parameters, time profile of hydrogen-bonding probability, and translocation of water by MD simulation.

PubMed

Yoneda, Shigetaka; Sugawara, Yoko; Urabe, Hisako

2005-01-27

The dynamics of crystal water molecules of guanosine dihydrate are investigated in detail by molecular dynamics (MD) simulation. A 2 ns simulation is performed using a periodic boundary box composed of 4 x 5 x 8 crystallographic unit cells and using the particle-mesh Ewald method for calculation of electrostatic energy. The simulated average atomic positions and atomic displacement parameters are remarkably coincident with the experimental values determined by X-ray analysis, confirming the high accuracy of this simulation. The dynamics of crystal water are analyzed in terms of atomic displacement parameters, orientation vectors, order parameters, self-correlation functions of the orientation vectors, time profiles of hydrogen-bonding probability, and translocations. The simulation clarifies that the average structure is composed of various stable and transient structures of the molecules. The simulated guanosine crystal forms a layered structure, with four water sites per asymmetric unit, classified as either interlayer water or intralayer water. From a detailed analysis of the translocations of water molecules in the simulation, columns of intralayer water molecules along the c axis appear to represent a pathway for hydration and dehydration by a kind of molecular valve mechanism.

Study on the After Cavity Interaction in a 140 GHz Gyrotron Using 3D CFDTD PIC Simulations

NASA Astrophysics Data System (ADS)

Lin, M. C.; Illy, S.; Avramidis, K.; Thumm, M.; Jelonnek, J.

2016-10-01

A computational study on after cavity interaction (ACI) in a 140 GHz gryotron for fusion research has been performed using a 3-D conformal finite-difference time-domain (CFDTD) particle-in-cell (PIC) method. The ACI, i.e. beam wave interaction in the non-linear uptaper after the cavity has attracted a lot of attention and been widely investigated in recent years. In a dynamic ACI, a TE mode is excited by the electron beam at the same frequency as in the cavity, and the same mode is also interacting with the spent electron beam at a different frequency in the non-linear uptaper after the cavity while in a static ACI, a mode interacts with the beam both at the cavity and at the uptaper, but at the same frequency. A previous study on the dynamic ACI on a 140 GHz gyrotron has concluded that more advanced numerical simulations such as particle-in-cell (PIC) modeling should be employed to study or confirm the dynamic ACI in addition to using trajectory codes. In this work, we use a 3-D full wave time domain simulation based on the CFDTD PIC method to include the rippled-wall launcher of the quasi-optical output coupler into the simulations which breaks the axial symmetry of the original model employing a symmetric one. A preliminary simulation result has confirmed the dynamic ACI effect in this 140 GHz gyrotron in good agreement with the former study. A realistic launcher will be included in the model for studying the dynamic ACI and compared with the homogenous one.

Interaction of Francisella tularensis bacterial cells with dynamic speckles

NASA Astrophysics Data System (ADS)

Ulianova, Onega V.; Ulyanov, Sergey S.; Sazanova, Elena V.; Zudina, Irina; Zhang, Zhihong; Sibo, Zhou; Luo, Qingming

2006-08-01

Influence of low-coherent speckles on the colonies grows is investigated. It has been demonstrated that effects of light on the inhibition of cells (Francisella Tularensis) are caused by speckle dynamics. The regimes of illumination of cell suspension with purpose of devitalization of hazard bacteria, caused very dangerous infections, such as tularemia, are found. Mathematical model of interaction of low-coherent laser radiation with bacteria suspension has been proposed. Computer simulations of the processes of laser-cells interaction have been carried out. Role of coherence of light in the processes of laser-cell interaction is analyzed.

Parameter setting and analysis of a dynamic tubular SOFC model

NASA Astrophysics Data System (ADS)

Jiang, Wei; Fang, Ruixian; Khan, Jamil A.; Dougal, Roger A.

An improved one-dimensional dynamic model of a tubular SOFC stack capable of system simulation in the virtual test bed (VTB) simulation environment is presented in this paper. This model is based on the electrochemical and thermal modeling, accounting for the voltage losses and temperature dynamics. The modeling of an external reformer is also included in this study. A detailed parametric analysis of working conditions and cell configuration of the solid oxide fuel cell (SOFC) stack is the main focus of this paper. The following operating parameters are investigated: pressure ratio, temperature, mass flow rate, external reforming degree and stream to carbon (S/C) ratio. The cell geometric parameters studied include cell diameter and cell length. Elevated operating pressure improves the cell performance. Whereas, higher operating temperature decreases both the Nernst potential and the irreversible losses, resulting in an initial increase then a decrease in cell efficiency. It was found that a higher S/C ratio yields a lower H 2 concentration and partial pressure, which has a negative effect on the Nernst potential. Increased cell diameter is found to increase the power due to a larger activation area at the same time and due to longer current path length there is an increase in the ohmic loss. Increased length of the cell has the undesired affect of an increased pressure drop.

Numerical Simulation of Multiphase Magnetohydrodynamic Flow and Deformation of Electrolyte-Metal Interface in Aluminum Electrolysis Cells

NASA Astrophysics Data System (ADS)

Hua, Jinsong; Rudshaug, Magne; Droste, Christian; Jorgensen, Robert; Giskeodegard, Nils-Haavard

2018-06-01

A computational fluid dynamics based multiphase magnetohydrodynamic (MHD) flow model for simulating the melt flow and bath-metal interface deformation in realistic aluminum reduction cells is presented. The model accounts for the complex physics of the MHD problem in aluminum reduction cells by coupling two immiscible fluids, electromagnetic field, Lorentz force, flow turbulence, and complex cell geometry with large length scale. Especially, the deformation of bath-metal interface is tracked directly in the simulation, and the condition of constant anode-cathode distance (ACD) is maintained by moving anode bottom dynamically with the deforming bath-metal interface. The metal pad deformation and melt flow predicted by the current model are compared to the predictions using a simplified model where the bath-metal interface is assumed flat. The effects of the induced electric current due to fluid flow and the magnetic field due to the interior cell current on the metal pad deformation and melt flow are investigated. The presented model extends the conventional simplified box model by including detailed cell geometry such as the ledge profile and all channels (side, central, and cross-channels). The simulations show the model sensitivity to different side ledge profiles and the cross-channel width by comparing the predicted melt flow and metal pad heaving. In addition, the model dependencies upon the reduction cell operation conditions such as ACD, current distribution on cathode surface and open/closed channel top, are discussed.

Simulating Heterogeneous Tumor Cell Populations

PubMed Central

Bar-Sagi, Dafna; Mishra, Bud

2016-01-01

Certain tumor phenomena, like metabolic heterogeneity and local stable regions of chronic hypoxia, signify a tumor’s resistance to therapy. Although recent research has shed light on the intracellular mechanisms of cancer metabolic reprogramming, little is known about how tumors become metabolically heterogeneous or chronically hypoxic, namely the initial conditions and spatiotemporal dynamics that drive these cell population conditions. To study these aspects, we developed a minimal, spatially-resolved simulation framework for modeling tissue-scale mixed populations of cells based on diffusible particles the cells consume and release, the concentrations of which determine their behavior in arbitrarily complex ways, and on stochastic reproduction. We simulate cell populations that self-sort to facilitate metabolic symbiosis, that grow according to tumor-stroma signaling patterns, and that give rise to stable local regions of chronic hypoxia near blood vessels. We raise two novel questions in the context of these results: (1) How will two metabolically symbiotic cell subpopulations self-sort in the presence of glucose, oxygen, and lactate gradients? We observe a robust pattern of alternating striations. (2) What is the proper time scale to observe stable local regions of chronic hypoxia? We observe the stability is a function of the balance of three factors related to O2—diffusion rate, local vessel release rate, and viable and hypoxic tumor cell consumption rate. We anticipate our simulation framework will help researchers design better experiments and generate novel hypotheses to better understand dynamic, emergent whole-tumor behavior. PMID:28030620

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.

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.

Two-way coupling of magnetohydrodynamic simulations with embedded particle-in-cell simulations

NASA Astrophysics Data System (ADS)

Makwana, K. D.; Keppens, R.; Lapenta, G.

2017-12-01

We describe a method for coupling an embedded domain in a magnetohydrodynamic (MHD) simulation with a particle-in-cell (PIC) method. In this two-way coupling we follow the work of Daldorff et al. (2014) [19] in which the PIC domain receives its initial and boundary conditions from MHD variables (MHD to PIC coupling) while the MHD simulation is updated based on the PIC variables (PIC to MHD coupling). This method can be useful for simulating large plasma systems, where kinetic effects captured by particle-in-cell simulations are localized but affect global dynamics. We describe the numerical implementation of this coupling, its time-stepping algorithm, and its parallelization strategy, emphasizing the novel aspects of it. We test the stability and energy/momentum conservation of this method by simulating a steady-state plasma. We test the dynamics of this coupling by propagating plasma waves through the embedded PIC domain. Coupling with MHD shows satisfactory results for the fast magnetosonic wave, but significant distortion for the circularly polarized Alfvén wave. Coupling with Hall-MHD shows excellent coupling for the whistler wave. We also apply this methodology to simulate a Geospace Environmental Modeling (GEM) challenge type of reconnection with the diffusion region simulated by PIC coupled to larger scales with MHD and Hall-MHD. In both these cases we see the expected signatures of kinetic reconnection in the PIC domain, implying that this method can be used for reconnection studies.

Guided self-assembly of magnetic beads for biomedical applications

NASA Astrophysics Data System (ADS)

Gusenbauer, Markus; Nguyen, Ha; Reichel, Franz; Exl, Lukas; Bance, Simon; Fischbacher, Johann; Özelt, Harald; Kovacs, Alexander; Brandl, Martin; Schrefl, Thomas

2014-02-01

Micromagnetic beads are widely used in biomedical applications for cell separation, drug delivery, and hyperthermia cancer treatment. Here we propose to use self-organized magnetic bead structures which accumulate on fixed magnetic seeding points to isolate circulating tumor cells. The analysis of circulating tumor cells is an emerging tool for cancer biology research and clinical cancer management including the detection, diagnosis and monitoring of cancer. Microfluidic chips for isolating circulating tumor cells use either affinity, size or density capturing methods. We combine multiphysics simulation techniques to understand the microscopic behavior of magnetic beads interacting with soft magnetic accumulation points used in lab-on-chip technologies. Our proposed chip technology offers the possibility to combine affinity and size capturing with special antibody-coated bead arrangements using a magnetic gradient field created by Neodymium Iron Boron permanent magnets. The multiscale simulation environment combines magnetic field computation, fluid dynamics and discrete particle dynamics.

Towards predictive molecular dynamics simulations of DNA: electrostatics and solution/crystal environments

NASA Astrophysics Data System (ADS)

Babin, Volodymr; Baucom, Jason; Darden, Thomas; Sagui, Celeste

2006-03-01

We have investigated to what extend molecular dynamics (MD) simulatons can reproduce DNA sequence-specific features, given different electrostatic descriptions and different cell environments. For this purpose, we have carried out multiple unrestrained MD simulations of the duplex d(CCAACGTTGG)2. With respect to the electrostatic descriptions, two different force fields were studied: a traditional description based on atomic point charges and a polarizable force field. With respect to the cell environment, the difference between crystal and solution environments is emphasized, as well as the structural importance of divalent ions. By imposing the correct experimental unit cell environment, an initial configuration with two ideal B-DNA duplexes in the unit cell is shown to converge to the crystallographic structure. To the best of our knowledge, this provides the first example of a multiple nanosecond MD trajectory that shows and ideal structure converging to an experimental one, with a significant decay of the RMSD.

Multiscale simulations of patchy particle systems combining Molecular Dynamics, Path Sampling and Green's Function Reaction Dynamics

NASA Astrophysics Data System (ADS)

Bolhuis, Peter

Important reaction-diffusion processes, such as biochemical networks in living cells, or self-assembling soft matter, span many orders in length and time scales. In these systems, the reactants' spatial dynamics at mesoscopic length and time scales of microns and seconds is coupled to the reactions between the molecules at microscopic length and time scales of nanometers and milliseconds. This wide range of length and time scales makes these systems notoriously difficult to simulate. While mean-field rate equations cannot describe such processes, the mesoscopic Green's Function Reaction Dynamics (GFRD) method enables efficient simulation at the particle level provided the microscopic dynamics can be integrated out. Yet, many processes exhibit non-trivial microscopic dynamics that can qualitatively change the macroscopic behavior, calling for an atomistic, microscopic description. The recently developed multiscale Molecular Dynamics Green's Function Reaction Dynamics (MD-GFRD) approach combines GFRD for simulating the system at the mesocopic scale where particles are far apart, with microscopic Molecular (or Brownian) Dynamics, for simulating the system at the microscopic scale where reactants are in close proximity. The association and dissociation of particles are treated with rare event path sampling techniques. I will illustrate the efficiency of this method for patchy particle systems. Replacing the microscopic regime with a Markov State Model avoids the microscopic regime completely. The MSM is then pre-computed using advanced path-sampling techniques such as multistate transition interface sampling. I illustrate this approach on patchy particle systems that show multiple modes of binding. MD-GFRD is generic, and can be used to efficiently simulate reaction-diffusion systems at the particle level, including the orientational dynamics, opening up the possibility for large-scale simulations of e.g. protein signaling networks.

A cut-cell immersed boundary technique for fire dynamics simulation

NASA Astrophysics Data System (ADS)

Vanella, Marcos; McDermott, Randall; Forney, Glenn

2015-11-01

Fire simulation around complex geometry is gaining increasing attention in performance based design of fire protection systems, fire-structure interaction and pollutant transport in complex terrains, among others. This presentation will focus on our present effort in improving the capability of FDS (Fire Dynamics Simulator, developed at the Fire Research Division, NIST. https://github.com/firemodels/fds-smv) to represent fire scenarios around complex bodies. Velocities in the vicinity of the bodies are reconstructed using a classical immersed boundary scheme (Fadlun and co-workers, J. Comput. Phys., 161:35-60, 2000). Also, a conservative treatment of scalar transport equations (i.e. for chemical species) will be presented. In our method, discrete conservation and no penetration of species across solid boundaries are enforced using a cut-cell finite volume scheme. The small cell problem inherent to the method is tackled using explicit-implicit domain decomposition for scalar, within the FDS time integration scheme. Some details on the derivation, implementation and numerical tests of this numerical scheme will be discussed.

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

Current status and future challenges in T-cell receptor/peptide/MHC molecular dynamics simulations.

PubMed

Knapp, Bernhard; Demharter, Samuel; Esmaielbeiki, Reyhaneh; Deane, Charlotte M

2015-11-01

The interaction between T-cell receptors (TCRs) and major histocompatibility complex (MHC)-bound epitopes is one of the most important processes in the adaptive human immune response. Several hypotheses on TCR triggering have been proposed. Many of them involve structural and dynamical adjustments in the TCR/peptide/MHC interface. Molecular Dynamics (MD) simulations are a computational technique that is used to investigate structural dynamics at atomic resolution. Such simulations are used to improve understanding of signalling on a structural level. Here we review how MD simulations of the TCR/peptide/MHC complex have given insight into immune system reactions not achievable with current experimental methods. Firstly, we summarize methods of TCR/peptide/MHC complex modelling and TCR/peptide/MHC MD trajectory analysis methods. Then we classify recently published simulations into categories and give an overview of approaches and results. We show that current studies do not come to the same conclusions about TCR/peptide/MHC interactions. This discrepancy might be caused by too small sample sizes or intrinsic differences between each interaction process. As computational power increases future studies will be able to and should have larger sample sizes, longer runtimes and additional parts of the immunological synapse included. © The Author 2015. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

Molecular dynamics simulation reveals how phosphorylation of tyrosine 26 of phosphoglycerate mutase 1 upregulates glycolysis and promotes tumor growth.

PubMed

Wang, Yan; Cai, Wen-Sheng; Chen, Luonan; Wang, Guanyu

2017-02-14

Phosphoglycerate mutase 1 (PGAM1) catalyzes the eighth step of glycolysis and is often found upregulated in cancer cells. To test the hypothesis that the phosphorylation of tyrosine 26 residue of PGAM1 greatly enhances its activity, we performed both conventional and steered molecular dynamics simulations on the binding and unbinding of PGAM1 to its substrates, with tyrosine 26 either phosphorylated or not. We analyzed the simulated data in terms of structural stability, hydrogen bond formation, binding free energy, etc. We found that tyrosine 26 phosphorylation enhances the binding of PGAM1 to its substrates through generating electrostatic environment and structural features that are advantageous to the binding. Our results may provide valuable insights into computer-aided design of drugs that specifically target cancer cells with PGAM1 tyrosine 26 phosphorylated.

Systematic reconstruction of TRANSPATH data into Cell System Markup Language

PubMed Central

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

2008-01-01

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

Systematic reconstruction of TRANSPATH data into cell system markup language.

PubMed

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

2008-06-23

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

Hardware simulation of fuel cell/gas turbine hybrids

NASA Astrophysics Data System (ADS)

Smith, Thomas Paul

Hybrid solid oxide fuel cell/gas turbine (SOFC/GT) systems offer high efficiency power generation, but face numerous integration and operability challenges. This dissertation addresses the application of hardware-in-the-loop simulation (HILS) to explore the performance of a solid oxide fuel cell stack and gas turbine when combined into a hybrid system. Specifically, this project entailed developing and demonstrating a methodology for coupling a numerical SOFC subsystem model with a gas turbine that has been modified with supplemental process flow and control paths to mimic a hybrid system. This HILS approach was implemented with the U.S. Department of Energy Hybrid Performance Project (HyPer) located at the National Energy Technology Laboratory. By utilizing HILS the facility provides a cost effective and capable platform for characterizing the response of hybrid systems to dynamic variations in operating conditions. HILS of a hybrid system was accomplished by first interfacing a numerical model with operating gas turbine hardware. The real-time SOFC stack model responds to operating turbine flow conditions in order to predict the level of thermal effluent from the SOFC stack. This simulated level of heating then dynamically sets the turbine's "firing" rate to reflect the stack output heat rate. Second, a high-speed computer system with data acquisition capabilities was integrated with the existing controls and sensors of the turbine facility. In the future, this will allow for the utilization of high-fidelity fuel cell models that infer cell performance parameters while still computing the simulation in real-time. Once the integration of the numeric and the hardware simulation components was completed, HILS experiments were conducted to evaluate hybrid system performance. The testing identified non-intuitive transient responses arising from the large thermal capacitance of the stack that are inherent to hybrid systems. Furthermore, the tests demonstrated the capabilities of HILS as a research tool for investigating the dynamic behavior of SOFC/GT hybrid power generation systems.

Dissipative particle dynamics simulations of deformation and aggregation of healthy and diseased red blood cells in a tube flow

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

Ye, Ting; Phan-Thien, Nhan, E-mail: Nhan@nus.edu.sg; Khoo, Boo Cheong

In this paper, we report simulation results assessing the deformation and aggregation of mixed healthy and malaria-infected red blood cells (RBCs) in a tube flow. A three dimensional particle model based on Dissipative Particle Dynamics (DPD) is developed to predict the tube flow containing interacting cells. The cells are also modelled by DPD, with a Morse potential to characterize the cell-cell interaction. As validation tests, a single RBC in a tube flow and two RBCs in a static flow are simulated to examine the cell deformation and intercellular interaction, respectively. The study of two cells, one healthy and the othermore » malaria-infected RBCs in a tube flow demonstrates that the malaria-infected RBC (in the leading position along flow direction) has different effects on the healthy RBC (in the trailing position) at the different stage of parasite development or at the different capillary number. With parasitic development, the malaria-infected RBC gradually loses its deformability, and in turn the corresponding trailing healthy RBC also deforms less due to the intercellular interaction. With increasing capillary number, both the healthy and malaria-infected RBCs are likely to undergo an axisymmetric motion. The minimum intercellular distance becomes small enough so that rouleaux is easily formed, i.e., the healthy and malaria-infected RBCs are difficultly disaggregated.« less

A novel approach for extracting viscoelastic parameters of living cells through combination of inverse finite element simulation and Atomic Force Microscopy.

PubMed

Wei, Fanan; Yang, Haitao; Liu, Lianqing; Li, Guangyong

2017-03-01

Dynamic mechanical behaviour of living cells has been described by viscoelasticity. However, quantitation of the viscoelastic parameters for living cells is far from sophisticated. In this paper, combining inverse finite element (FE) simulation with Atomic Force Microscope characterization, we attempt to develop a new method to evaluate and acquire trustworthy viscoelastic index of living cells. First, influence of the experiment parameters on stress relaxation process is assessed using FE simulation. As suggested by the simulations, cell height has negligible impact on shape of the force-time curve, i.e. the characteristic relaxation time; and the effect originates from substrate can be totally eliminated when stiff substrate (Young's modulus larger than 3 GPa) is used. Then, so as to develop an effective optimization strategy for the inverse FE simulation, the parameters sensitivity evaluation is performed for Young's modulus, Poisson's ratio, and characteristic relaxation time. With the experiment data obtained through typical stress relaxation measurement, viscoelastic parameters are extracted through the inverse FE simulation by comparing the simulation results and experimental measurements. Finally, reliability of the acquired mechanical parameters is verified with different load experiments performed on the same cell.

Dynamical buoyancy of hydrodynamic eddies. [in solar atmosphere

NASA Technical Reports Server (NTRS)

Parker, E. N.

1991-01-01

The dynamical pressure reduction within a vortex tube produces both a tension along the tube and a general buoyancy, analogous to magnetic flux tubes. The dynamical buoyancy causes convective cells to rise at speeds comparable to the rms fluid velocity within the cell. Consequently, the convective cells in a stratified atmosphere are more active than indicated by the standard anelastic approximation. The coherent convective cells at each level actively crowd upward into the convective cells above, elbowing weaker cells out of the way and flattening themselves and others against the upper surface of the convective region. These effects can be seen in the recent SOUP observations of the solar granulation. Deeper in the convective zone the inhomogeneity of the buoyancy may explain the random character of the convective motions that turns up in recent numerical simulations.

Computational Fluid Dynamics-Population Balance Model Simulation of Effects of Cell Design and Operating Parameters on Gas-Liquid Two-Phase Flows and Bubble Distribution Characteristics in Aluminum Electrolysis Cells

NASA Astrophysics Data System (ADS)

Zhan, Shuiqing; Wang, Junfeng; Wang, Zhentao; Yang, Jianhong

2018-02-01

The effects of different cell design and operating parameters on the gas-liquid two-phase flows and bubble distribution characteristics under the anode bottom regions in aluminum electrolysis cells were analyzed using a three-dimensional computational fluid dynamics-population balance model. These parameters include inter-anode channel width, anode-cathode distance (ACD), anode width and length, current density, and electrolyte depth. The simulations results show that the inter-anode channel width has no significant effect on the gas volume fraction, electrolyte velocity, and bubble size. With increasing ACD, the above values decrease and more uniform bubbles can be obtained. Different effects of the anode width and length can be concluded in different cell regions. With increasing current density, the gas volume fraction and electrolyte velocity increase, but the bubble size keeps nearly the same. Increasing electrolyte depth decreased the gas volume fraction and bubble size in particular areas and the electrolyte velocity increased.

Structure and dynamics of human vimentin intermediate filament dimer and tetramer in explicit and implicit solvent models.

PubMed

Qin, Zhao; Buehler, Markus J

2011-01-01

Intermediate filaments, in addition to microtubules and microfilaments, are one of the three major components of the cytoskeleton in eukaryotic cells, and play an important role in mechanotransduction as well as in providing mechanical stability to cells at large stretch. The molecular structures, mechanical and dynamical properties of the intermediate filament basic building blocks, the dimer and the tetramer, however, have remained elusive due to persistent experimental challenges owing to the large size and fibrillar geometry of this protein. We have recently reported an atomistic-level model of the human vimentin dimer and tetramer, obtained through a bottom-up approach based on structural optimization via molecular simulation based on an implicit solvent model (Qin et al. in PLoS ONE 2009 4(10):e7294, 9). Here we present extensive simulations and structural analyses of the model based on ultra large-scale atomistic-level simulations in an explicit solvent model, with system sizes exceeding 500,000 atoms and simulations carried out at 20 ns time-scales. We report a detailed comparison of the structural and dynamical behavior of this large biomolecular model with implicit and explicit solvent models. Our simulations confirm the stability of the molecular model and provide insight into the dynamical properties of the dimer and tetramer. Specifically, our simulations reveal a heterogeneous distribution of the bending stiffness along the molecular axis with the formation of rather soft and highly flexible hinge-like regions defined by non-alpha-helical linker domains. We report a comparison of Ramachandran maps and the solvent accessible surface area between implicit and explicit solvent models, and compute the persistence length of the dimer and tetramer structure of vimentin intermediate filaments for various subdomains of the protein. Our simulations provide detailed insight into the dynamical properties of the vimentin dimer and tetramer intermediate filament building blocks, which may guide the development of novel coarse-grained models of intermediate filaments, and could also help in understanding assembly mechanisms.

Study of the interaction of potassium ion channel protein with micelle by molecular dynamics simulation

NASA Astrophysics Data System (ADS)

Shantappa, Anil; Talukdar, Keka

2018-04-01

Ion channels are proteins forming pore inside the body of all living organisms. This potassium ion channel known as KcsA channel and it is found in the each cell and nervous system. Flow of various ions is regulated by the function of the ion channels. The nerve ion channel protein with protein data bank entry 1BL8, which is basically an ion channel protein in Streptomyces Lividans and which is taken up to form micelle-protein system and the system is analyzed by using molecular dynamics simulation. Firstly, ion channel pore is engineered by CHARMM potential and then Micelle-protein system is subjected to molecular dynamics simulation. For some specific micelle concentration, the protein unfolding is observed.

The Application of Ligand-Mapping Molecular Dynamics Simulations to the Rational Design of Peptidic Modulators of Protein-Protein Interactions.

PubMed

Tan, Yaw Sing; Spring, David R; Abell, Chris; Verma, Chandra S

2015-07-14

A computational ligand-mapping approach to detect protein surface pockets that interact with hydrophobic moieties is presented. In this method, we incorporated benzene molecules into explicit solvent molecular dynamics simulations of various protein targets. The benzene molecules successfully identified the binding locations of hydrophobic hot-spot residues and all-hydrocarbon cross-links from known peptidic ligands. They also unveiled cryptic binding sites that are occluded by side chains and the protein backbone. Our results demonstrate that ligand-mapping molecular dynamics simulations hold immense promise to guide the rational design of peptidic modulators of protein-protein interactions, including that of stapled peptides, which show promise as an exciting new class of cell-penetrating therapeutic molecules.

Biological evaluation, docking and molecular dynamic simulation of some novel diaryl urea derivatives bearing quinoxalindione moiety

PubMed Central

Sadeghian-Rizi, Sedighe; Khodarahmi, Ghadamali Ali; Sakhteman, Amirhossein; Jahanian-Najafabadi, Ali; Rostami, Mahboubeh; Mirzaei, Mahmoud; Hassanzadeh, Farshid

2017-01-01

In this study a series of diarylurea derivatives containing quinoxalindione group were biologically evaluated for their cytotoxic activities using MTT assay against MCF-7 and HepG2 cell lines. Antibacterial activities of these compounds were also evaluated by Microplate Alamar Blue Assay (MABA) against three Gram-negative (Escherichia coli, Pseudomonas aeruginosa and Salmonella typhi), three Gram-positive (Staphylococcus aureus, Bacillus subtilis and Listeria monocitogenes) and one yeast-like fungus (Candida albicans) strain. Furthermore, molecular docking was carried out to study the binding pattern of the compounds to the active site of B-RAF kinase (PDB code: 1UWH). Molecular dynamics simulation was performed on the best ligand (16e) to investigate the ligand binding dynamics in the physiological environment. Cytotoxic evaluation revealed the most prominent cytotoxicity for 6 compounds with IC50 values of 10-18 μM against two mentioned cell lines. None of the synthesized compounds showed significant antimicrobial activity. The obtained results of the molecular docking study showed that all compounds fitted in the binding site of enzyme with binding energy range of -11.22 to -12.69 kcal/mol vs sorafenib binding energy -11.74 kcal/mol as the lead compound. Molecular dynamic simulation indicated that the binding of ligand (16e) was stable in the active site of B-RAF during the simulation. PMID:29204178

Using stroboscopic flow imaging to validate large-scale computational fluid dynamics simulations

NASA Astrophysics Data System (ADS)

Laurence, Ted A.; Ly, Sonny; Fong, Erika; Shusteff, Maxim; Randles, Amanda; Gounley, John; Draeger, Erik

2017-02-01

The utility and accuracy of computational modeling often requires direct validation against experimental measurements. The work presented here is motivated by taking a combined experimental and computational approach to determine the ability of large-scale computational fluid dynamics (CFD) simulations to understand and predict the dynamics of circulating tumor cells in clinically relevant environments. We use stroboscopic light sheet fluorescence imaging to track the paths and measure the velocities of fluorescent microspheres throughout a human aorta model. Performed over complex physiologicallyrealistic 3D geometries, large data sets are acquired with microscopic resolution over macroscopic distances.

Dynamics of the Glycophorin A Dimer in Membranes of Native-Like Composition Uncovered by Coarse-Grained Molecular Dynamics Simulations

PubMed Central

Flinner, Nadine; Schleiff, Enrico

2015-01-01

Membranes are central for cells as borders to the environment or intracellular organelle definition. They are composed of and harbor different molecules like various lipid species and sterols, and they are generally crowded with proteins. The membrane system is very dynamic and components show lateral, rotational and translational diffusion. The consequence of the latter is that phase separation can occur in membranes in vivo and in vitro. It was documented that molecular dynamics simulations of an idealized plasma membrane model result in formation of membrane areas where either saturated lipids and cholesterol (liquid-ordered character, Lo) or unsaturated lipids (liquid-disordered character, Ld) were enriched. Furthermore, current discussions favor the idea that proteins are sorted into the liquid-disordered phase of model membranes, but experimental support for the behavior of isolated proteins in native membranes is sparse. To gain insight into the protein behavior we built a model of the red blood cell membrane with integrated glycophorin A dimer. The sorting and the dynamics of the dimer were subsequently explored by coarse-grained molecular dynamics simulations. In addition, we inspected the impact of lipid head groups and the presence of cholesterol within the membrane on the dynamics of the dimer within the membrane. We observed that cholesterol is important for the formation of membrane areas with Lo and Ld character. Moreover, it is an important factor for the reproduction of the dynamic behavior of the protein found in its native environment. The protein dimer was exclusively sorted into the domain of Ld character in the model red blood cell plasma membrane. Therefore, we present structural information on the glycophorin A dimer distribution in the plasma membrane in the absence of other factors like e.g. lipid anchors in a coarse grain resolution. PMID:26222139

Formation of fivefold deformation twins in nanocrystalline face-centered-cubic copper based on molecular dynamics simulations

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

Cao, A. J.; Wei, Y. G.

2006-07-24

Fivefold deformation twins were reported recently to be observed in the experiment of the nanocrystalline face-centered-cubic metals and alloys. However, they were not predicted previously based on the molecular dynamics (MD) simulations and the reason was thought to be a uniaxial tension considered in the simulations. In the present investigation, through introducing pretwins in grain regions, using the MD simulations, the authors predict out the fivefold deformation twins in the grain regions of the nanocrystal grain cell, which undergoes a uniaxial tension. It is shown in their simulation results that series of Shockley partial dislocations emitted from grain boundaries providemore » sequential twining mechanism, which results in fivefold deformation twins.« less

Comparison of the uptake of methacrylate-based nanoparticles in static and dynamic in vitro systems as well as in vivo.

PubMed

Rinkenauer, Alexandra C; Press, Adrian T; Raasch, Martin; Pietsch, Christian; Schweizer, Simon; Schwörer, Simon; Rudolph, Karl L; Mosig, Alexander; Bauer, Michael; Traeger, Anja; Schubert, Ulrich S

2015-10-28

Polymer-based nanoparticles are promising drug delivery systems allowing the development of new drug and treatment strategies with reduced side effects. However, it remains a challenge to screen for new and effective nanoparticle-based systems in vitro. Important factors influencing the behavior of nanoparticles in vivo cannot be simulated in screening assays in vitro, which still represent the main tools in academic research and pharmaceutical industry. These systems have serious drawbacks in the development of nanoparticle-based drug delivery systems, since they do not consider the highly complex processes influencing nanoparticle clearance, distribution, and uptake in vivo. In particular, the transfer of in vitro nanoparticle performance to in vivo models often fails, demonstrating the urgent need for novel in vitro tools that can imitate aspects of the in vivo situation more accurate. Dynamic cell culture, where cells are cultured and incubated in the presence of shear stress has the potential to bridge this gap by mimicking key-features of organs and vessels. Our approach implements and compares a chip-based dynamic cell culture model to the common static cell culture and mouse model to assess its capability to predict the in vivo success more accurately, by using a well-defined poly((methyl methacrylate)-co-(methacrylic acid)) and poly((methyl methacrylate)-co-(2-dimethylamino ethylmethacrylate)) based nanoparticle library. After characterization in static and dynamic in vitro cell culture we were able to show that physiological conditions such as cell-cell communication of co-cultured endothelial cells and macrophages as well as mechanotransductive signaling through shear stress significantly alter cellular nanoparticle uptake. In addition, it could be demonstrated by using dynamic cell cultures that the in vivo situation is simulated more accurately and thereby can be applied as a novel system to investigate the performance of nanoparticle systems in vivo more reliable. Copyright © 2015. Published by Elsevier B.V.

Fundamental limits on dynamic inference from single-cell snapshots

PubMed Central

Weinreb, Caleb; Tusi, Betsabeh K.; Socolovsky, Merav

2018-01-01

Single-cell expression profiling reveals the molecular states of individual cells with unprecedented detail. Because these methods destroy cells in the process of analysis, they cannot measure how gene expression changes over time. However, some information on dynamics is present in the data: the continuum of molecular states in the population can reflect the trajectory of a typical cell. Many methods for extracting single-cell dynamics from population data have been proposed. However, all such attempts face a common limitation: for any measured distribution of cell states, there are multiple dynamics that could give rise to it, and by extension, multiple possibilities for underlying mechanisms of gene regulation. Here, we describe the aspects of gene expression dynamics that cannot be inferred from a static snapshot alone and identify assumptions necessary to constrain a unique solution for cell dynamics from static snapshots. We translate these constraints into a practical algorithmic approach, population balance analysis (PBA), which makes use of a method from spectral graph theory to solve a class of high-dimensional differential equations. We use simulations to show the strengths and limitations of PBA, and then apply it to single-cell profiles of hematopoietic progenitor cells (HPCs). Cell state predictions from this analysis agree with HPC fate assays reported in several papers over the past two decades. By highlighting the fundamental limits on dynamic inference faced by any method, our framework provides a rigorous basis for dynamic interpretation of a gene expression continuum and clarifies best experimental designs for trajectory reconstruction from static snapshot measurements. PMID:29463712

Theoretical Analysis of Novel Quasi-3D Microscopy of Cell Deformation

PubMed Central

Qiu, Jun; Baik, Andrew D.; Lu, X. Lucas; Hillman, Elizabeth M. C.; Zhuang, Zhuo; Guo, X. Edward

2012-01-01

A novel quasi-three-dimensional (quasi-3D) microscopy technique has been developed to enable visualization of a cell under dynamic loading in two orthogonal planes simultaneously. The three-dimensional (3D) dynamics of the mechanical behavior of a cell under fluid flow can be examined at a high temporal resolution. In this study, a numerical model of a fluorescently dyed cell was created in 3D space, and the cell was subjected to uniaxial deformation or unidirectional fluid shear flow via finite element analysis (FEA). Therefore, the intracellular deformation in the simulated cells was exactly prescribed. Two-dimensional fluorescent images simulating the quasi-3D technique were created from the cell and its deformed states in 3D space using a point-spread function (PSF) and a convolution operation. These simulated original and deformed images were processed by a digital image correlation technique to calculate quasi-3D-based intracellular strains. The calculated strains were compared to the prescribed strains, thus providing a theoretical basis for the measurement of the accuracy of quasi-3D and wide-field microscopy-based intracellular strain measurements against the true 3D strains. The signal-to-noise ratio (SNR) of the simulated quasi-3D images was also modulated using additive Gaussian noise, and a minimum SNR of 12 was needed to recover the prescribed strains using digital image correlation. Our computational study demonstrated that quasi-3D strain measurements closely recovered the true 3D strains in uniform and fluid flow cellular strain states to within 5% strain error. PMID:22707985

Complex disruption effect of natural polyphenols on Bcl-2-Bax: molecular dynamics simulation and essential dynamics study.

PubMed

Verma, Sharad; Singh, Amit; Mishra, Abha

2015-01-01

Apoptosis (programmed cell death) is a process by which cells died after completing physiological function or after a severe genetic damage. Apoptosis is mainly regulated by the Bcl-2 family of proteins. Anti apoptotic protein Bcl-2 prevents the Bax activation/oligomerization to form heterodimer which is responsible for release of the cytochrome c from mitochondria to the cytosol in response to death signal. Quercetin and taxifolin (natural polyphenols) efficiently bound to hydrophobic groove of Bcl-2 and altered the structure by inducing conformational changes. Taxifolin was found more efficient when compared to quercetin in terms of interaction energy and collapse of hydrophobic groove. Taxifolin and quercetin were found to dissociate the Bcl-2-Bax complex during 12 ns MD simulation. The effect of taxifolin and quercetin was, further validated by the MD simulation of ligand-unbound Bcl-2-Bax which showed stability during the simulation. Obatoclax (an inhibitor of Bcl-2) had no significant dissociation effect on Bcl-2-Bax during simulation which favored the previous experimental results and disruption effect of taxifolin and quercetin.

A fast platform for simulating semi-flexible fiber suspensions applied to cell mechanics

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

Nazockdast, Ehssan, E-mail: ehssan@cims.nyu.edu; Center for Computational Biology, Simons Foundation, New York, NY 10010; Rahimian, Abtin, E-mail: arahimian@acm.org

We present a novel platform for the large-scale simulation of three-dimensional fibrous structures immersed in a Stokesian fluid and evolving under confinement or in free-space in three dimensions. One of the main motivations for this work is to study the dynamics of fiber assemblies within biological cells. For this, we also incorporate the key biophysical elements that determine the dynamics of these assemblies, which include the polymerization and depolymerization kinetics of fibers, their interactions with molecular motors and other objects, their flexibility, and hydrodynamic coupling. This work, to our knowledge, is the first technique to include many-body hydrodynamic interactions (HIs),more » and the resulting fluid flows, in cellular assemblies of flexible fibers. We use non-local slender body theory to compute the fluid–structure interactions of the fibers and a second-kind boundary integral formulation for other rigid bodies and the confining boundary. A kernel-independent implementation of the fast multipole method is utilized for efficient evaluation of HIs. The deformation of the fibers is described by nonlinear Euler–Bernoulli beam theory and their polymerization is modeled by the reparametrization of the dynamic equations in the appropriate non-Lagrangian frame. We use a pseudo-spectral representation of fiber positions and implicit time-stepping to resolve large fiber deformations, and to allow time-steps not excessively constrained by temporal stiffness or fiber–fiber interactions. The entire computational scheme is parallelized, which enables simulating assemblies of thousands of fibers. We use our method to investigate two important questions in the mechanics of cell division: (i) the effect of confinement on the hydrodynamic mobility of microtubule asters; and (ii) the dynamics of the positioning of mitotic spindle in complex cell geometries. Finally to demonstrate the general applicability of the method, we simulate the sedimentation of a cloud of semi-flexible fibers.« less

A fast platform for simulating semi-flexible fiber suspensions applied to cell mechanics

NASA Astrophysics Data System (ADS)

Nazockdast, Ehssan; Rahimian, Abtin; Zorin, Denis; Shelley, Michael

2017-01-01

We present a novel platform for the large-scale simulation of three-dimensional fibrous structures immersed in a Stokesian fluid and evolving under confinement or in free-space in three dimensions. One of the main motivations for this work is to study the dynamics of fiber assemblies within biological cells. For this, we also incorporate the key biophysical elements that determine the dynamics of these assemblies, which include the polymerization and depolymerization kinetics of fibers, their interactions with molecular motors and other objects, their flexibility, and hydrodynamic coupling. This work, to our knowledge, is the first technique to include many-body hydrodynamic interactions (HIs), and the resulting fluid flows, in cellular assemblies of flexible fibers. We use non-local slender body theory to compute the fluid-structure interactions of the fibers and a second-kind boundary integral formulation for other rigid bodies and the confining boundary. A kernel-independent implementation of the fast multipole method is utilized for efficient evaluation of HIs. The deformation of the fibers is described by nonlinear Euler-Bernoulli beam theory and their polymerization is modeled by the reparametrization of the dynamic equations in the appropriate non-Lagrangian frame. We use a pseudo-spectral representation of fiber positions and implicit time-stepping to resolve large fiber deformations, and to allow time-steps not excessively constrained by temporal stiffness or fiber-fiber interactions. The entire computational scheme is parallelized, which enables simulating assemblies of thousands of fibers. We use our method to investigate two important questions in the mechanics of cell division: (i) the effect of confinement on the hydrodynamic mobility of microtubule asters; and (ii) the dynamics of the positioning of mitotic spindle in complex cell geometries. Finally to demonstrate the general applicability of the method, we simulate the sedimentation of a cloud of semi-flexible fibers.

A Versatile Bioreactor for Dynamic Suspension Cell Culture. Application to the Culture of Cancer Cell Spheroids

PubMed Central

Madeddu, Denise; Cerino, Giulia; Falco, Angela; Frati, Caterina; Gallo, Diego; Deriu, Marco A.; Falvo D’Urso Labate, Giuseppe; Quaini, Federico; Audenino, Alberto; Morbiducci, Umberto

2016-01-01

A versatile bioreactor suitable for dynamic suspension cell culture under tunable shear stress conditions has been developed and preliminarily tested culturing cancer cell spheroids. By adopting simple technological solutions and avoiding rotating components, the bioreactor exploits the laminar hydrodynamics establishing within the culture chamber enabling dynamic cell suspension in an environment favourable to mass transport, under a wide range of tunable shear stress conditions. The design phase of the device has been supported by multiphysics modelling and has provided a comprehensive analysis of the operating principles of the bioreactor. Moreover, an explanatory example is herein presented with multiphysics simulations used to set the proper bioreactor operating conditions for preliminary in vitro biological tests on a human lung carcinoma cell line. The biological results demonstrate that the ultralow shear dynamic suspension provided by the device is beneficial for culturing cancer cell spheroids. In comparison to the static suspension control, dynamic cell suspension preserves morphological features, promotes intercellular connection, increases spheroid size (2.4-fold increase) and number of cycling cells (1.58-fold increase), and reduces double strand DNA damage (1.5-fold reduction). It is envisioned that the versatility of this bioreactor could allow investigation and expansion of different cell types in the future. PMID:27144306

A Versatile Bioreactor for Dynamic Suspension Cell Culture. Application to the Culture of Cancer Cell Spheroids.

PubMed

Massai, Diana; Isu, Giuseppe; Madeddu, Denise; Cerino, Giulia; Falco, Angela; Frati, Caterina; Gallo, Diego; Deriu, Marco A; Falvo D'Urso Labate, Giuseppe; Quaini, Federico; Audenino, Alberto; Morbiducci, Umberto

2016-01-01

A versatile bioreactor suitable for dynamic suspension cell culture under tunable shear stress conditions has been developed and preliminarily tested culturing cancer cell spheroids. By adopting simple technological solutions and avoiding rotating components, the bioreactor exploits the laminar hydrodynamics establishing within the culture chamber enabling dynamic cell suspension in an environment favourable to mass transport, under a wide range of tunable shear stress conditions. The design phase of the device has been supported by multiphysics modelling and has provided a comprehensive analysis of the operating principles of the bioreactor. Moreover, an explanatory example is herein presented with multiphysics simulations used to set the proper bioreactor operating conditions for preliminary in vitro biological tests on a human lung carcinoma cell line. The biological results demonstrate that the ultralow shear dynamic suspension provided by the device is beneficial for culturing cancer cell spheroids. In comparison to the static suspension control, dynamic cell suspension preserves morphological features, promotes intercellular connection, increases spheroid size (2.4-fold increase) and number of cycling cells (1.58-fold increase), and reduces double strand DNA damage (1.5-fold reduction). It is envisioned that the versatility of this bioreactor could allow investigation and expansion of different cell types in the future.

Simulation of Escherichia coli O157:H7 behavior in fresh-cut lettuce under dynamic temperature conditions during distribution from processing to retail.

PubMed

McKellar, Robin C; LeBlanc, Denyse I; Lu, Jianbo; Delaquis, Pascal

2012-03-01

The temperature of packaged lettuce was recorded throughout a retail supply chain in Canada during the various stages of storage and shipping from the processor to retail. Temperatures were monitored in 27 cases of lettuce destined for three stores in three replicate trials conducted during the winter. A dynamic model that predicts the effect of temperature on the growth or die-off of Escherichia coli O157:H7 in packaged fresh-cut lettuce was applied to simulate the behavior of E. coli O157:H7 in the system. Simulations were carried out using distributions to account for variation in the temperature parameter and the die-off coefficient of the dynamic growth/death model. The results indicate that there was a predicted overall mean decline in cell numbers of 0.983 log cfu g⁻¹ and that the extent of cell death was proportional to the total time spent in the cold chain. Slight growth was predicted in a few instances when the dynamic temperature was above the permissive temperature of 5°C. These results suggest that generally there would be little or no growth of E. coli O157:H7 in product maintained at the proper temperature in the chain. Moreover, the predicted decline in cell numbers at refrigeration temperatures suggests that storage at 5°C or below prior to consumption would reduce populations of the pathogen in fresh-cut lettuce.

Nonadiabatic Dynamics of Photoinduced Proton-Coupled Electron Transfer Processes

DTIC Science & Technology

devices and photoelectrochemical cells. Theoretical methodology for simulating the nonadiabatic dynamics of photoinduced PCET reactions in solution has...tuning and control of the ultrafast dynamics is crucial for designing renewable and sustainable energy sources, such as artificial photosynthesis...describes the solute with a multiconfigurational method in a bath of explicit solvent molecules. The transferring hydrogen nucleus is represented as a

Dynamics of an HBV/HCV infection model with intracellular delay and cell proliferation

NASA Astrophysics Data System (ADS)

Zhang, Fengqin; Li, Jianquan; Zheng, Chongwu; Wang, Lin

2017-01-01

A new mathematical model of hepatitis B/C virus (HBV/HCV) infection which incorporates the proliferation of healthy hepatocyte cells and the latent period of infected hepatocyte cells is proposed and studied. The dynamics is analyzed via Pontryagin's method and a newly proposed alternative geometric stability switch criterion. Sharp conditions ensuring stability of the infection persistent equilibrium are derived by applying Pontryagin's method. Using the intracellular delay as the bifurcation parameter and applying an alternative geometric stability switch criterion, we show that the HBV/HCV infection model undergoes stability switches. Furthermore, numerical simulations illustrate that the intracellular delay can induce complex dynamics such as persistence bubbles and chaos.

Tracking molecular dynamics without tracking: image correlation of photo-activation microscopy

NASA Astrophysics Data System (ADS)

Pandžić, Elvis; Rossy, Jérémie; Gaus, Katharina

2015-03-01

Measuring protein dynamics in the plasma membrane can provide insights into the mechanisms of receptor signaling and other cellular functions. To quantify protein dynamics on the single molecule level over the entire cell surface, sophisticated approaches such as single particle tracking (SPT), photo-activation localization microscopy (PALM) and fluctuation-based analysis have been developed. However, analyzing molecular dynamics of fluorescent particles with intermittent excitation and low signal-to-noise ratio present at high densities has remained a challenge. We overcame this problem by applying spatio-temporal image correlation spectroscopy (STICS) analysis to photo-activated (PA) microscopy time series. In order to determine under which imaging conditions this approach is valid, we simulated PA images of diffusing particles in a homogeneous environment and varied photo-activation, reversible blinking and irreversible photo-bleaching rates. Further, we simulated data with high particle densities that populated mobile objects (such as adhesions and vesicles) that often interfere with STICS and fluctuation-based analysis. We demonstrated in experimental measurements that the diffusion coefficient of the epidermal growth factor receptor (EGFR) fused to PAGFP in live COS-7 cells can be determined in the plasma membrane and revealed differences in the time-dependent diffusion maps between wild-type and mutant Lck in activated T cells. In summary, we have developed a new analysis approach for live cell photo-activation microscopy data based on image correlation spectroscopy to quantify the spatio-temporal dynamics of single proteins.

Tracking molecular dynamics without tracking: image correlation of photo-activation microscopy.

PubMed

Pandžić, Elvis; Rossy, Jérémie; Gaus, Katharina

2015-03-09

Measuring protein dynamics in the plasma membrane can provide insights into the mechanisms of receptor signaling and other cellular functions. To quantify protein dynamics on the single molecule level over the entire cell surface, sophisticated approaches such as single particle tracking (SPT), photo-activation localization microscopy (PALM) and fluctuation-based analysis have been developed. However, analyzing molecular dynamics of fluorescent particles with intermittent excitation and low signal-to-noise ratio present at high densities has remained a challenge. We overcame this problem by applying spatio-temporal image correlation spectroscopy (STICS) analysis to photo-activated (PA) microscopy time series. In order to determine under which imaging conditions this approach is valid, we simulated PA images of diffusing particles in a homogeneous environment and varied photo-activation, reversible blinking and irreversible photo-bleaching rates. Further, we simulated data with high particle densities that populated mobile objects (such as adhesions and vesicles) that often interfere with STICS and fluctuation-based analysis. We demonstrated in experimental measurements that the diffusion coefficient of the epidermal growth factor receptor (EGFR) fused to PAGFP in live COS-7 cells can be determined in the plasma membrane and revealed differences in the time-dependent diffusion maps between wild-type and mutant Lck in activated T cells. In summary, we have developed a new analysis approach for live cell photo-activation microscopy data based on image correlation spectroscopy to quantify the spatio-temporal dynamics of single proteins.

Accelerating population balance-Monte Carlo simulation for coagulation dynamics from the Markov jump model, stochastic algorithm and GPU parallel computing

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

Xu, Zuwei; Zhao, Haibo, E-mail: klinsmannzhb@163.com; Zheng, Chuguang

2015-01-15

This paper proposes a comprehensive framework for accelerating population balance-Monte Carlo (PBMC) simulation of particle coagulation dynamics. By combining Markov jump model, weighted majorant kernel and GPU (graphics processing unit) parallel computing, a significant gain in computational efficiency is achieved. The Markov jump model constructs a coagulation-rule matrix of differentially-weighted simulation particles, so as to capture the time evolution of particle size distribution with low statistical noise over the full size range and as far as possible to reduce the number of time loopings. Here three coagulation rules are highlighted and it is found that constructing appropriate coagulation rule providesmore » a route to attain the compromise between accuracy and cost of PBMC methods. Further, in order to avoid double looping over all simulation particles when considering the two-particle events (typically, particle coagulation), the weighted majorant kernel is introduced to estimate the maximum coagulation rates being used for acceptance–rejection processes by single-looping over all particles, and meanwhile the mean time-step of coagulation event is estimated by summing the coagulation kernels of rejected and accepted particle pairs. The computational load of these fast differentially-weighted PBMC simulations (based on the Markov jump model) is reduced greatly to be proportional to the number of simulation particles in a zero-dimensional system (single cell). Finally, for a spatially inhomogeneous multi-dimensional (multi-cell) simulation, the proposed fast PBMC is performed in each cell, and multiple cells are parallel processed by multi-cores on a GPU that can implement the massively threaded data-parallel tasks to obtain remarkable speedup ratio (comparing with CPU computation, the speedup ratio of GPU parallel computing is as high as 200 in a case of 100 cells with 10 000 simulation particles per cell). These accelerating approaches of PBMC are demonstrated in a physically realistic Brownian coagulation case. The computational accuracy is validated with benchmark solution of discrete-sectional method. The simulation results show that the comprehensive approach can attain very favorable improvement in cost without sacrificing computational accuracy.« less

A Partially-Stirred Batch Reactor Model for Under-Ventilated Fire Dynamics

NASA Astrophysics Data System (ADS)

McDermott, Randall; Weinschenk, Craig

2013-11-01

A simple discrete quadrature method is developed for closure of the mean chemical source term in large-eddy simulations (LES) and implemented in the publicly available fire model, Fire Dynamics Simulator (FDS). The method is cast as a partially-stirred batch reactor model for each computational cell. The model has three distinct components: (1) a subgrid mixing environment, (2) a mixing model, and (3) a set of chemical rate laws. The subgrid probability density function (PDF) is described by a linear combination of Dirac delta functions with quadrature weights set to satisfy simple integral constraints for the computational cell. It is shown that under certain limiting assumptions, the present method reduces to the eddy dissipation concept (EDC). The model is used to predict carbon monoxide concentrations in direct numerical simulation (DNS) of a methane slot burner and in LES of an under-ventilated compartment fire.

Three-Dimensional Simulation of Liquid Drop Dynamics Within Unsaturated Vertical Hele-Shaw Cells

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

Hai Huang; Paul Meakin

A three-dimensional, multiphase fluid flow model with volume of fluid-interface tracking was developed and applied to study the multiphase dynamics of moving liquid drops of different sizes within vertical Hele-Shaw cells. The simulated moving velocities are significantly different from those obtained from a first-order analytical approximation, based on simple force-balance concepts. The simulation results also indicate that the moving drops can exhibit a variety of shapes and that the transition among these different shapes is largely determined by the moving velocities. More important, there is a transition from a linear moving regime at small capillary numbers, in which the capillarymore » number scales linearly with the Bond number, to a nonlinear moving regime at large capillary numbers, in which the moving drop releases a train of droplets from its trailing edge. The train of droplets forms a variety of patterns at different moving velocities.« less

PICsar: Particle in cell pulsar magnetosphere simulator

NASA Astrophysics Data System (ADS)

Belyaev, Mikhail A.

2016-07-01

PICsar simulates the magnetosphere of an aligned axisymmetric pulsar and can be used to simulate other arbitrary electromagnetics problems in axisymmetry. Written in Fortran, this special relativistic, electromagnetic, charge conservative particle in cell code features stretchable body-fitted coordinates that follow the surface of a sphere, simplifying the application of boundary conditions in the case of the aligned pulsar; a radiation absorbing outer boundary, which allows a steady state to be set up dynamically and maintained indefinitely from transient initial conditions; and algorithms for injection of charged particles into the simulation domain. PICsar is parallelized using MPI and has been used on research problems with 1000 CPUs.

Atomistic Simulations of Surface Cross-Slip Nucleation in Face-Centered Cubic Nickel and Copper (Postprint)

DTIC Science & Technology

2013-02-15

molecular dynamics code, LAMMPS [9], developed at Sandia National Laboratory. The simulation cell is a rectangular parallelepiped, with the z-axis...with assigned energies within LAMMPs of greater than 4.42 eV (Ni) or 3.52 eV (Cu) (the energy of atoms in the stacking fault region), the partial...molecular dynamics code LAMMPS , which was developed at Sandia National Laboratory by Dr. Steve Plimpton and co-workers. This work was supported by the

Structure and dynamics of solvated polyethylenimine chains

NASA Astrophysics Data System (ADS)

Beu, Titus A.; Farcaş, Alexandra

2017-12-01

Polimeric gene-delivery carriers have attracted great interest in recent years, owing to their applicability in gene therapy. In particular, cationic polymers represent the most promising delivery vectors for nucleic acids into the cells. This study presents extensive atomistic molecular dynamics simulations of linear polyethylenimine chains. The simulations show that the variation of the chain size and protonation fraction causes a substantial change of the diffusion coefficient. Examination of the solvated chains suggests the possibility of controlling the polymer diffusion mobility in solution.

A ReaxFF-based molecular dynamics study of the mechanisms of interactions between reactive oxygen plasma species and the Candida albicans cell wall

NASA Astrophysics Data System (ADS)

Zhao, T.; Shi, L.; Zhang, Y. T.; Zou, L.; Zhang, L.

2017-10-01

Atmospheric pressure non-equilibrium plasmas have attracted significant attention and have been widely used to inactivate pathogens, yet the mechanisms underlying the interactions between plasma-generated species and bio-organisms have not been elucidated clearly. In this paper, reactive molecular dynamics simulations are employed to investigate the mechanisms of interactions between reactive oxygen plasma species (O, OH, and O2) and β-1,6-glucan (a model for the C. albicans cell wall) from a microscopic point of view. Our simulations show that O and OH species can break structurally important C-C and C-O bonds, while O2 molecules exhibit only weak, non-bonded interactions with β-1,6-glucan. Hydrogen abstraction from hydroxyl or CH groups occurs first in all bond cleavage mechanisms. This is followed by a cascade of bond cleavage and double bond formation events. These lead to the destruction of the fungal cell wall. O and OH have similar effects related to their bond cleavage mechanisms. Our simulation results provide fundamental insights into the mechanisms underlying the interactions between reactive oxygen plasma species and the fungal cell wall of C. albicans at the atomic level.

Biological Effects of Protracted Exposure to Ionizing Radiation: Review, Analysis, and Model Development

DTIC Science & Technology

1991-11-01

dynamics, physiological changes, morphologi- cal changes, cell/tissue damage and recovery mechanisms, and existing radiobiological injury and recovery...humans and the ferret. The gut injury model (GIM) is a three-compartment hierarchial- type tissue model to simulate radiation-induced changes in the...Prodromal Symptoms Diarrhea Gastrointestinal Symptoms Dose Rate Cell Survival Intestinal Injury Fatigability Cell Damage Cell Repair Cell Proliferation

A multiscale computational model of spatially resolved calcium cycling in cardiac myocytes: from detailed cleft dynamics to the whole cell concentration profiles

PubMed Central

Vierheller, Janine; Neubert, Wilhelm; Falcke, Martin; Gilbert, Stephen H.; Chamakuri, Nagaiah

2015-01-01

Mathematical modeling of excitation-contraction coupling (ECC) in ventricular cardiac myocytes is a multiscale problem, and it is therefore difficult to develop spatially detailed simulation tools. ECC involves gradients on the length scale of 100 nm in dyadic spaces and concentration profiles along the 100 μm of the whole cell, as well as the sub-millisecond time scale of local concentration changes and the change of lumenal Ca2+ content within tens of seconds. Our concept for a multiscale mathematical model of Ca2+ -induced Ca2+ release (CICR) and whole cardiomyocyte electrophysiology incorporates stochastic simulation of individual LC- and RyR-channels, spatially detailed concentration dynamics in dyadic clefts, rabbit membrane potential dynamics, and a system of partial differential equations for myoplasmic and lumenal free Ca2+ and Ca2+-binding molecules in the bulk of the cell. We developed a novel computational approach to resolve the concentration gradients from dyadic space to cell level by using a quasistatic approximation within the dyad and finite element methods for integrating the partial differential equations. We show whole cell Ca2+-concentration profiles using three previously published RyR-channel Markov schemes. PMID:26441674

The dynamic and steady state behavior of a PEM fuel cell as an electric energy source

NASA Astrophysics Data System (ADS)

Costa, R. A.; Camacho, J. R.

The main objective of this work is to extract information on the internal behavior of three small polymer electrolyte membrane fuel cells under static and dynamic load conditions. A computational model was developed using Scilab [SCILAB 4, Scilab-a free scientific software package, http://www.scilab.org/, INRIA, France, December, 2005] to simulate the static and dynamic performance [J.M. Correa, A.F. Farret, L.N. Canha, An analysis of the dynamic performance of proton exchange membrane fuel cells using an electrochemical model, in: 27th Annual Conference of IEEE Industrial Electronics Society, 2001, pp. 141-146] of this particular type of fuel cell. This dynamic model is based on electrochemical equations and takes into consideration most of the chemical and physical characteristics of the device in order to generate electric power. The model takes into consideration the operating, design parameters and physical material properties. The results show the internal losses and concentration effects behavior, which are of interest for power engineers and researchers.

Power output and carrier dynamics studies of perovskite solar cells under working conditions.

PubMed

Yu, Man; Wang, Hao-Yi; Hao, Ming-Yang; Qin, Yujun; Fu, Li-Min; Zhang, Jian-Ping; Ai, Xi-Cheng

2017-08-02

Perovskite solar cells have emerged as promising photovoltaic systems with superb power conversion efficiency. For the practical application of perovskite devices, the greatest concerns are the power output density and the related dynamics under working conditions. In this study, the working conditions of planar and mesoscopic perovskite solar cells are simulated and the power output density evolutions with the working voltage are highlighted. The planar device exhibits higher capability of outputting power than the mesoscopic one. The transient photoelectric conversion dynamics are investigated under the open circuit, short circuit and working conditions. It is found that the power output and dynamic processes are correlated intrinsically, which suggests that the power output is the competitive result of the charge carrier recombination and transport. The present work offers a unique view to elucidating the relationship between the power output and the charge carrier dynamics for perovskite solar cells in a comprehensive manner, which would be beneficial to their future practical applications.

Clinical study and numerical simulation of brain cancer dynamics under radiotherapy

NASA Astrophysics Data System (ADS)

Nawrocki, S.; Zubik-Kowal, B.

2015-05-01

We perform a clinical and numerical study of the progression of brain cancer tumor growth dynamics coupled with the effects of radiotherapy. We obtained clinical data from a sample of brain cancer patients undergoing radiotherapy and compare it to our numerical simulations to a mathematical model of brain tumor cell population growth influenced by radiation treatment. We model how the body biologically receives a physically delivered dose of radiation to the affected tumorous area in the form of a generalized LQ model, modified to account for the conversion process of sublethal lesions into lethal lesions at high radiation doses. We obtain good agreement between our clinical data and our numerical simulations of brain cancer progression given by the mathematical model, which couples tumor growth dynamics and the effect of irradiation. The correlation, spanning a wide dataset, demonstrates the potential of the mathematical model to describe the dynamics of brain tumor growth influenced by radiotherapy.

Mechanism of vaso-occlusion in sickle cell anemia

NASA Astrophysics Data System (ADS)

Lei, Huan; Karniadakis, George

2012-11-01

Vaso-occlusion crisis is one of the key hallmark of sickle cell anemia. While early studies suggested that the crisis is caused by blockage of a single elongated cell, recent experimental investigations indicate that vaso-occlusion is a complex process triggered by adhesive interactions among different cell groups in multiple stages. Based on dissipative particle dynamics, a multi-scale model for the sickle red blood cells (SS-RBCs), accounting for diversity in both shapes and cell rigidities, is developed to investigate the mechanism of vaso-occlusion crisis. Using this model, the adhesive dynamics of single SS-RBC was investigated in arterioles. Simulation results indicate that the different cell groups (deformable SS2 RBCs, rigid SS4 RBCs, leukocytes, etc.) exhibit heterogeneous adhesive behavior due to the different cell morphologies and membrane rigidities. We further simulate the tube flow of SS-RBC suspensions with different cell fractions. The more adhesive SS2 cells interact with the vascular endothelium and further trap rigid SS4 cells, resulting in vaso-occlusion in vessels less than 15 μm . Under inflammation, adherent leukocytes may also trap SS4 cells, resulting in vaso-occlusion in even larger vessels. This work was supported by the NSF grant CBET-0852948 and the NIH grant R01HL094270.

A Simulation Environment for the Dynamic Evaluation of Disaster Preparedness Policies and Interventions

PubMed Central

Lewis, Bryan; Swarup, Samarth; Bisset, Keith; Eubank, Stephen; Marathe, Madhav; Barrett, Chris

2013-01-01

Disasters affect a society at many levels. Simulation based studies often evaluate the effectiveness of one or two response policies in isolation and are unable to represent impact of the policies to coevolve with others. Similarly, most in-depth analyses are based on a static assessment of the “aftermath” rather than capturing dynamics. We have developed a data-centric simulation environment for applying a systems approach to a dynamic analysis of complex combinations of disaster responses. We analyze an improvised nuclear detonation in Washington DC with this environment. The simulated blast affects the transportation system, communications infrastructure, electrical power system, behaviors and motivations of population, and health status of survivors. The effectiveness of partially restoring wireless communications capacity is analyzed in concert with a range of other disaster response policies. Despite providing a limited increase in cell phone communication, overall health was improved. PMID:23903394

Multiscale molecular dynamics simulation approaches to the structure and dynamics of viruses.

PubMed

Huber, Roland G; Marzinek, Jan K; Holdbrook, Daniel A; Bond, Peter J

2017-09-01

Viral pathogens are a significant source of human morbidity and mortality, and have a major impact on societies and economies around the world. One of the challenges inherent in targeting these pathogens with drugs is the tight integration of the viral life cycle with the host's cellular machinery. However, the reliance of the virus on the host cell replication machinery is also an opportunity for therapeutic targeting, as successful entry- and exit-inhibitors have demonstrated. An understanding of the extracellular and intracellular structure and dynamics of the virion - as well as of the entry and exit pathways in host and vector cells - is therefore crucial to the advancement of novel antivirals. In recent years, advances in computing architecture and algorithms have begun to allow us to use simulations to study the structure and dynamics of viral ultrastructures at various stages of their life cycle in atomistic or near-atomistic detail. In this review, we outline specific challenges and solutions that have emerged to allow for structurally detailed modelling of viruses in silico. We focus on the history and state of the art of atomistic and coarse-grained approaches to simulate the dynamics of the large, macromolecular structures associated with viral infection, and on their usefulness in explaining and expanding upon experimental data. We discuss the types of interactions that need to be modeled to describe major components of the virus particle and advances in modelling techniques that allow for the treatment of these systems, highlighting recent key simulation studies. Copyright © 2016 Elsevier Ltd. All rights reserved.

Multiscale molecular dynamics simulations of membrane remodeling by Bin/Amphiphysin/Rvs family proteins

NASA Astrophysics Data System (ADS)

Chun, Chan; Haohua, Wen; Lanyuan, Lu; Jun, Fan

2016-01-01

Membrane curvature is no longer thought of as a passive property of the membrane; rather, it is considered as an active, regulated state that serves various purposes in the cell such as between cells and organelle definition. While transport is usually mediated by tiny membrane bubbles known as vesicles or membrane tubules, such communication requires complex interplay between the lipid bilayers and cytosolic proteins such as members of the Bin/Amphiphysin/Rvs (BAR) superfamily of proteins. With rapid developments in novel experimental techniques, membrane remodeling has become a rapidly emerging new field in recent years. Molecular dynamics (MD) simulations are important tools for obtaining atomistic information regarding the structural and dynamic aspects of biological systems and for understanding the physics-related aspects. The availability of more sophisticated experimental data poses challenges to the theoretical community for developing novel theoretical and computational techniques that can be used to better interpret the experimental results to obtain further functional insights. In this review, we summarize the general mechanisms underlying membrane remodeling controlled or mediated by proteins. While studies combining experiments and molecular dynamics simulations recall existing mechanistic models, concurrently, they extend the role of different BAR domain proteins during membrane remodeling processes. We review these recent findings, focusing on how multiscale molecular dynamics simulations aid in understanding the physical basis of BAR domain proteins, as a representative of membrane-remodeling proteins. Project supported by the National Natural Science Foundation of China (Grant No. 21403182) and the Research Grants Council of Hong Kong, China (Grant No. CityU 21300014).

Dynamic x-ray imaging of laser-driven nanoplasmas

NASA Astrophysics Data System (ADS)

Fennel, Thomas

2016-05-01

A major promise of current x-ray science at free electron lasers is the realization of unprecedented imaging capabilities for resolving the structure and ultrafast dynamics of matter with nanometer spatial and femtosecond temporal resolution or even below via single-shot x-ray diffraction. Laser-driven atomic clusters and nanoparticles provide an ideal platform for developing and demonstrating the required technology to extract the ultrafast transient spatiotemporal dynamics from the diffraction images. In this talk, the perspectives and challenges of dynamic x-ray imaging will be discussed using complete self-consistent microscopic electromagnetic simulations of IR pump x-ray probe imaging for the example of clusters. The results of the microscopic particle-in-cell simulations (MicPIC) enable the simulation-assisted reconstruction of corresponding experimental data. This capability is demonstrated by converting recently measured LCLS data into a ultrahigh resolution movie of laser-induced plasma expansion. Finally, routes towards reaching attosecond time resolution in the visualization of complex dynamical processes in matter by x-ray diffraction will be discussed.

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.

Theoretical modeling of cellular and dendritic solidification microstructures

NASA Astrophysics Data System (ADS)

Song, Younggil

In this dissertation, we use three-dimensional (3D) phase-field (PF) modeling to investigate (i) 3D solid-liquid interface dynamics observed in microgravity experiments, and (ii) array patterns in a thin-sample geometry. In addition, using the two-dimensional (2D) dendritic-needle-network (DNN) model, we explore (iii) secondary sidebranching dynamics. Recently, solidification experiments are carried out in the DSI (Directional Solidification Insert) of the DECLIC (Device for the study of Critical LIquids and Crystallization) facility aboard the International Space Station (ISS). Thus, the directional solidification experiments are achieved under limited convective currents, and the experimental observations reveal unique dynamics of 3D microstructure in a purely diffusive growth regime. In this directional solidification setup, a temperature field between heat sources could evolve due to two main factors: (i) heat transfer within an adiabatic zone and (ii) latent heat rejection at the interface. These two thermal effects are phenomenologically characterized using a time-dependent thermal shift. In addition, we could quantitatively account for these thermal factors using a numerical calculation of the evolution of temperature field. We introduce these phenomenological and quantitative thermal representations into the PF model. The performed simulations using different thermal descriptions are compared to the experimental measurements from the initial planar interface dynamics to the final spacing selection. The DECLIC-DSI experimental observations exhibit complex grain boundary (GB) dynamics between large grains with a small misorientation. In the observations, several large grains with a small misorientation with respect to the temperature gradient are formed during solidification. Specifically, at a convergent GB, a localized group of misoriented cells penetrates into a nearby grain, which yields the morphological instability of grain boundaries. Remarkably, while the invasion process starts with a group of cells, the leader cell can detach itself from the group and grow continuously as a misoriented solitary cell in the other grain with a different misorientation. We use PF simulations to investigate the GB morphology and dynamics of a solitary cell. Solidification experiments on earth are typically performed in a thin-sample geometry to avoid fluid convection. Thus, we consider various influences on cellular and dendritic array patterns in thin samples. First, we explore the influence of crystal orientation. When a grain in a thin-sample geometry is misoriented with respect to the temperature gradient, primary cells and dendrites drift laterally in both experiments and simulations. At the same time, grain boundaries are systematically formed at the edges of the misoriented grain. The misoriented primary branches move away from the divergent grain boundary. At this boundary, cells/dendrites are generated continuously, and their spacings are larger than the dynamically selected spacings. Primary branches run into the other convergent GB, which leads to their elimination. Thus, at a stationary state, a spacing distribution is uniform with the spacing selected at the divergent GB until it decreases near the convergent GB. We perform simulations to illustrate the global evolutions of a primary spacing. In addition, we suggest a simple geometrical model and a nonlinear advection equation for the dynamics of the primary spacing evolution, which can predict the slow evolution of a primary spacing in a quasi-2D array. Experimental observations point out that the primary spacing selection could be affected by the sample thickness; however, the detailed description for the link between the primary spacing selection and a sample thickness is still missing. Here, we use PF simulations to investigate the primary cellular and dendritic spacing selection mechanisms under the influence of a sample thickness. A thin-sample geometry can limit thermal and solutal convective currents effectively. However, as the sample thickness increases, the convective currents can influence the solid- liquid interface dynamics. Then, the microstructure selection mechanisms can be different from the classical theories that are valid in a diffusive regime. We propose a simple approach for the PF model to demonstrate the microstructure selection when liquid convection is present. These simulations are compared to experimental results. Columnar microstructures with cells and dendrites typically form polycrystalline materials during directional solidification. Then, convergent and divergent grain boundaries form systematically between grains, which are misoriented with respect to the temperature gradient. Moreover, the GB is dynamically selected during the competition between two nearby misoriented grains. In order to investigate the GB orientation selection, we carry out 3D PF simulations in a thin-sample geometry. These simulations reveal the influence of the 3D GB bi-crystallography on grain competition. The results highlight the importance of considering the orientation of the orthogonal planes containing secondary branches in addition to the growth direction of primary branches. Finally, we propose three growth steps to demonstrate the secondary sidebranching growth dynamics under isothermal dendritic growth condition. (Abstract shortened by ProQuest.).

Sampling the isothermal-isobaric ensemble by Langevin dynamics

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

Gao, Xingyu; Institute of Applied Physics and Computational Mathematics, Fenghao East Road 2, Beijing 100094; CAEP Software Center for High Performance Numerical Simulation, Huayuan Road 6, Beijing 100088

2016-03-28

We present a new method of conducting fully flexible-cell molecular dynamics simulation in isothermal-isobaric ensemble based on Langevin equations of motion. The stochastic coupling to all particle and cell degrees of freedoms is introduced in a correct way, in the sense that the stationary configurational distribution is proved to be consistent with that of the isothermal-isobaric ensemble. In order to apply the proposed method in computer simulations, a second order symmetric numerical integration scheme is developed by Trotter’s splitting of the single-step propagator. Moreover, a practical guide of choosing working parameters is suggested for user specified thermo- and baro-coupling timemore » scales. The method and software implementation are carefully validated by a numerical example.« less

How far in-silico computing meets real experiments. A study on the structure and dynamics of spin labeled vinculin tail protein by molecular dynamics simulations and EPR spectroscopy

PubMed Central

2013-01-01

Background Investigation of conformational changes in a protein is a prerequisite to understand its biological function. To explore these conformational changes in proteins we developed a strategy with the combination of molecular dynamics (MD) simulations and electron paramagnetic resonance (EPR) spectroscopy. The major goal of this work is to investigate how far computer simulations can meet the experiments. Methods Vinculin tail protein is chosen as a model system as conformational changes within the vinculin protein are believed to be important for its biological function at the sites of cell adhesion. MD simulations were performed on vinculin tail protein both in water and in vacuo environments. EPR experimental data is compared with those of the simulated data for corresponding spin label positions. Results The calculated EPR spectra from MD simulations trajectories of selected spin labelled positions are comparable to experimental EPR spectra. The results show that the information contained in the spin label mobility provides a powerful means of mapping protein folds and their conformational changes. Conclusions The results suggest the localization of dynamic and flexible regions of the vinculin tail protein. This study shows MD simulations can be used as a complementary tool to interpret experimental EPR data. PMID:23445506

Dynamic Modeling, Model-Based Control, and Optimization of Solid Oxide Fuel Cells

NASA Astrophysics Data System (ADS)

Spivey, Benjamin James

2011-07-01

Solid oxide fuel cells are a promising option for distributed stationary power generation that offers efficiencies ranging from 50% in stand-alone applications to greater than 80% in cogeneration. To advance SOFC technology for widespread market penetration, the SOFC should demonstrate improved cell lifetime and load-following capability. This work seeks to improve lifetime through dynamic analysis of critical lifetime variables and advanced control algorithms that permit load-following while remaining in a safe operating zone based on stress analysis. Control algorithms typically have addressed SOFC lifetime operability objectives using unconstrained, single-input-single-output control algorithms that minimize thermal transients. Existing SOFC controls research has not considered maximum radial thermal gradients or limits on absolute temperatures in the SOFC. In particular, as stress analysis demonstrates, the minimum cell temperature is the primary thermal stress driver in tubular SOFCs. This dissertation presents a dynamic, quasi-two-dimensional model for a high-temperature tubular SOFC combined with ejector and prereformer models. The model captures dynamics of critical thermal stress drivers and is used as the physical plant for closed-loop control simulations. A constrained, MIMO model predictive control algorithm is developed and applied to control the SOFC. Closed-loop control simulation results demonstrate effective load-following, constraint satisfaction for critical lifetime variables, and disturbance rejection. Nonlinear programming is applied to find the optimal SOFC size and steady-state operating conditions to minimize total system costs.

A Non-Cut Cell Immersed Boundary Method for Use in Icing Simulations

NASA Technical Reports Server (NTRS)

Sarofeen, Christian M.; Noack, Ralph W.; Kreeger, Richard E.

2013-01-01

This paper describes a computational fluid dynamic method used for modelling changes in aircraft geometry due to icing. While an aircraft undergoes icing, the accumulated ice results in a geometric alteration of the aerodynamic surfaces. In computational simulations for icing, it is necessary that the corresponding geometric change is taken into consideration. The method used, herein, for the representation of the geometric change due to icing is a non-cut cell Immersed Boundary Method (IBM). Computational cells that are in a body fitted grid of a clean aerodynamic geometry that are inside a predicted ice formation are identified. An IBM is then used to change these cells from being active computational cells to having properties of viscous solid bodies. This method has been implemented in the NASA developed node centered, finite volume computational fluid dynamics code, FUN3D. The presented capability is tested for two-dimensional airfoils including a clean airfoil, an iced airfoil, and an airfoil in harmonic pitching motion about its quarter chord. For these simulations velocity contours, pressure distributions, coefficients of lift, coefficients of drag, and coefficients of pitching moment about the airfoil's quarter chord are computed and used for comparison against experimental results, a higher order panel method code with viscous effects, XFOIL, and the results from FUN3D's original solution process. The results of the IBM simulations show that the accuracy of the IBM compares satisfactorily with the experimental results, XFOIL results, and the results from FUN3D's original solution process.

The Dynamics of HPV Infection and Cervical Cancer Cells.

PubMed

Asih, Tri Sri Noor; Lenhart, Suzanne; Wise, Steven; Aryati, Lina; Adi-Kusumo, F; Hardianti, Mardiah S; Forde, Jonathan

2016-01-01

The development of cervical cells from normal cells infected by human papillomavirus into invasive cancer cells can be modeled using population dynamics of the cells and free virus. The cell populations are separated into four compartments: susceptible cells, infected cells, precancerous cells and cancer cells. The model system of differential equations also has a free virus compartment in the system, which infect normal cells. We analyze the local stability of the equilibrium points of the model and investigate the parameters, which play an important role in the progression toward invasive cancer. By simulation, we investigate the boundary between initial conditions of solutions, which tend to stable equilibrium point, representing controlled infection, and those which tend to unbounded growth of the cancer cell population. Parameters affected by drug treatment are varied, and their effect on the risk of cancer progression is explored.

A DISCRETE-EVENT SIMULATION APPROACH TO IDENTIFY RULES THAT GOVERN ARBOR REMODELING FOR BRANCHING CUTANEOUS AFFERENTS IN HAIRY SKIN.

PubMed

Kang, Hyojung; Orlowsky, Rachel L; Gerling, Gregory J

2017-12-01

In mammals, touch is encoded by sensory receptors embedded in the skin. For one class of receptors in the mouse, the architecture of its Merkel cells, unmyelinated neurites, and heminodes follow particular renewal and remodeling trends over hair cycle stages from ages 4 to 10 weeks. As it is currently impossible to observe such trends across a single animal's hair cycle, this work employs discrete event simulation to identify and evaluate policies of Merkel cell and heminode dynamics. Well matching the observed data, the results show that the baseline model replicates dynamic remodeling behaviors between stages of the hair cycle - based on particular addition and removal polices and estimated probabilities tied to constituent parts of Merkel cells, terminal branch neurites and heminodes. The analysis shows further that certain policies hold greater influence than others. This use of computation is a novel approach to understanding neuronal development.

Interaction of PLGA and trimethyl chitosan modified PLGA nanoparticles with mixed anionic/zwitterionic phospholipid bilayers studied using molecular dynamics simulations

NASA Astrophysics Data System (ADS)

Novak, Brian; Astete, Carlos; Sabliov, Cristina; Moldovan, Dorel

2012-02-01

Poly(lactic-co-glycolic acid) (PLGA) is a biodegradable polymer. Nanoparticles of PLGA are commonly used for drug delivery applications. The interaction of the nanoparticles with the cell membrane may influence the rate of their uptake by cells. Both PLGA and cell membranes are negatively charged, so adding positively charged polymers such as trimethyl chitosan (TMC) which adheres to the PLGA particles improves their cellular uptake. The interaction of 3 nm PLGA and TMC-modified-PLGA nanoparticles with lipid bilayers composed of mixtures of phosphatidylcholine and phosphatidylserine lipids was studied using molecular dynamics simulations. The free energy profiles as function of nanoparticles position along the normal direction to the bilayers were calculated, the distribution of phosphatidylserine lipids as a function of distance of the particle from the bilayer was calculated, and the time scale for particle motion in the directions parallel to the bilayer surface was estimated.

Kinetic Monte Carlo and cellular particle dynamics simulations of multicellular systems

NASA Astrophysics Data System (ADS)

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

2012-03-01

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

Liquid water breakthrough location distances on a gas diffusion layer of polymer electrolyte membrane fuel cells

NASA Astrophysics Data System (ADS)

Yu, Junliang; Froning, Dieter; Reimer, Uwe; Lehnert, Werner

2018-06-01

The lattice Boltzmann method is adopted to simulate the three dimensional dynamic process of liquid water breaking through the gas diffusion layer (GDL) in the polymer electrolyte membrane fuel cell. 22 micro-structures of Toray GDL are built based on a stochastic geometry model. It is found that more than one breakthrough locations are formed randomly on the GDL surface. Breakthrough location distance (BLD) are analyzed statistically in two ways. The distribution is evaluated statistically by the Lilliefors test. It is concluded that the BLD can be described by the normal distribution with certain statistic characteristics. Information of the shortest neighbor breakthrough location distance can be the input modeling setups on the cell-scale simulations in the field of fuel cell simulation.

Predict the glass transition temperature of glycerol-water binary cryoprotectant by molecular dynamic simulation.

PubMed

Li, Dai-Xi; Liu, Bao-Lin; Liu, Yi-shu; Chen, Cheng-lung

2008-04-01

Vitrification is proposed to be the best way for the cryopreservation of organs. The glass transition temperature (T(g)) of vitrification solutions is a critical parameter of fundamental importance for cryopreservation by vitrification. The instruments that can detect the thermodynamic, mechanical and dielectric changes of a substance may be used to determine the glass transition temperature. T(g) is usually measured by using differential scanning calorimetry (DSC). In this study, the T(g) of the glycerol-aqueous solution (60%, wt/%) was determined by isothermal-isobaric molecular dynamic simulation (NPT-MD). The software package Discover in Material Studio with the Polymer Consortium Force Field (PCFF) was used for the simulation. The state parameters of heat capacity at constant pressure (C(p)), density (rho), amorphous cell volume (V(cell)) and specific volume (V(specific)) and radial distribution function (rdf) were obtained by NPT-MD in the temperature range of 90-270K. These parameters showed a discontinuity at a specific temperature in the plot of state parameter versus temperature. The temperature at the discontinuity is taken as the simulated T(g) value for glycerol-water binary solution. The T(g) values determined by simulation method were compared with the values in the literatures. The simulation values of T(g) (160.06-167.51K) agree well with the DSC results (163.60-167.10K) and the DMA results (159.00K). We drew the conclusion that molecular dynamic simulation (MDS) is a potential method for investigating the glass transition temperature (T(g)) of glycerol-water binary cryoprotectants and may be used for other vitrification solutions.

Bringing consistency to simulation of population models--Poisson simulation as a bridge between micro and macro simulation.

PubMed

Gustafsson, Leif; Sternad, Mikael

2007-10-01

Population models concern collections of discrete entities such as atoms, cells, humans, animals, etc., where the focus is on the number of entities in a population. Because of the complexity of such models, simulation is usually needed to reproduce their complete dynamic and stochastic behaviour. Two main types of simulation models are used for different purposes, namely micro-simulation models, where each individual is described with its particular attributes and behaviour, and macro-simulation models based on stochastic differential equations, where the population is described in aggregated terms by the number of individuals in different states. Consistency between micro- and macro-models is a crucial but often neglected aspect. This paper demonstrates how the Poisson Simulation technique can be used to produce a population macro-model consistent with the corresponding micro-model. This is accomplished by defining Poisson Simulation in strictly mathematical terms as a series of Poisson processes that generate sequences of Poisson distributions with dynamically varying parameters. The method can be applied to any population model. It provides the unique stochastic and dynamic macro-model consistent with a correct micro-model. The paper also presents a general macro form for stochastic and dynamic population models. In an appendix Poisson Simulation is compared with Markov Simulation showing a number of advantages. Especially aggregation into state variables and aggregation of many events per time-step makes Poisson Simulation orders of magnitude faster than Markov Simulation. Furthermore, you can build and execute much larger and more complicated models with Poisson Simulation than is possible with the Markov approach.

Electro-mechanical dynamics of spiral waves in a discrete 2D model of human atrial tissue.

PubMed

Brocklehurst, Paul; Ni, Haibo; Zhang, Henggui; Ye, Jianqiao

2017-01-01

We investigate the effect of mechano-electrical feedback and atrial fibrillation induced electrical remodelling (AFER) of cellular ion channel properties on the dynamics of spiral waves in a discrete 2D model of human atrial tissue. The tissue electro-mechanics are modelled using the discrete element method (DEM). Millions of bonded DEM particles form a network of coupled atrial cells representing 2D cardiac tissue, allowing simulations of the dynamic behaviour of electrical excitation waves and mechanical contraction in the tissue. In the tissue model, each cell is modelled by nine particles, accounting for the features of individual cellular geometry; and discrete inter-cellular spatial arrangement of cells is also considered. The electro-mechanical model of a human atrial single-cell was constructed by strongly coupling the electrophysiological model of Colman et al. to the mechanical myofilament model of Rice et al., with parameters modified based on experimental data. A stretch-activated channel was incorporated into the model to simulate the mechano-electrical feedback. In order to investigate the effect of mechano-electrical feedback on the dynamics of spiral waves, simulations of spiral waves were conducted in both the electromechanical model and the electrical-only model in normal and AFER conditions, to allow direct comparison of the results between the models. Dynamics of spiral waves were characterized by tracing their tip trajectories, stability, excitation frequencies and meandering range of tip trajectories. It was shown that the developed DEM method provides a stable and efficient model of human atrial tissue with considerations of the intrinsically discrete and anisotropic properties of the atrial tissue, which are challenges to handle in traditional continuum mechanics models. This study provides mechanistic insights into the complex behaviours of spiral waves and the genesis of atrial fibrillation by showing an important role of the mechano-electrical feedback in facilitating and promoting atrial fibrillation.

Electro-mechanical dynamics of spiral waves in a discrete 2D model of human atrial tissue

PubMed Central

Zhang, Henggui

2017-01-01

We investigate the effect of mechano-electrical feedback and atrial fibrillation induced electrical remodelling (AFER) of cellular ion channel properties on the dynamics of spiral waves in a discrete 2D model of human atrial tissue. The tissue electro-mechanics are modelled using the discrete element method (DEM). Millions of bonded DEM particles form a network of coupled atrial cells representing 2D cardiac tissue, allowing simulations of the dynamic behaviour of electrical excitation waves and mechanical contraction in the tissue. In the tissue model, each cell is modelled by nine particles, accounting for the features of individual cellular geometry; and discrete inter-cellular spatial arrangement of cells is also considered. The electro-mechanical model of a human atrial single-cell was constructed by strongly coupling the electrophysiological model of Colman et al. to the mechanical myofilament model of Rice et al., with parameters modified based on experimental data. A stretch-activated channel was incorporated into the model to simulate the mechano-electrical feedback. In order to investigate the effect of mechano-electrical feedback on the dynamics of spiral waves, simulations of spiral waves were conducted in both the electromechanical model and the electrical-only model in normal and AFER conditions, to allow direct comparison of the results between the models. Dynamics of spiral waves were characterized by tracing their tip trajectories, stability, excitation frequencies and meandering range of tip trajectories. It was shown that the developed DEM method provides a stable and efficient model of human atrial tissue with considerations of the intrinsically discrete and anisotropic properties of the atrial tissue, which are challenges to handle in traditional continuum mechanics models. This study provides mechanistic insights into the complex behaviours of spiral waves and the genesis of atrial fibrillation by showing an important role of the mechano-electrical feedback in facilitating and promoting atrial fibrillation. PMID:28510575

Shock-induced poration, cholesterol flip-flop and small interfering RNA transfection in a phospholipid membrane: Multimillion atom, microsecond molecular dynamics simulations

NASA Astrophysics Data System (ADS)

Choubey, Amit

Biological cell membranes provide mechanical stability to cells and understanding their structure, dynamics and mechanics are important biophysics problems. Experiments coupled with computational methods such as molecular dynamics (MD) have provided insight into the physics of membranes. We use long-time and large-scale MD simulations to study the structure, dynamics and mechanical behavior of membranes. We investigate shock-induced collapse of nanobubbles in water using MD simulations based on a reactive force field. We observe a focused jet at the onset of bubble shrinkage and a secondary shock wave upon bubble collapse. The jet length scales linearly with the nanobubble radius, as observed in experiments on micron-to-millimeter size bubbles. Shock induces dramatic structural changes, including an ice-VII-like structural motif at a particle velocity of 1 km/s. The incipient ice VII formation and the calculated Hugoniot curve are in good agreement with experimental results. We also investigate molecular mechanisms of poration in lipid bilayers due to shock-induced collapse of nanobubbles. Our multimillion-atom MD simulations reveal that the jet impact generates shear flow of water on bilayer leaflets and pressure gradients across them. This transiently enhances the bilayer permeability by creating nanopores through which water molecules translocate rapidly across the bilayer. Effects of nanobubble size and temperature on the porosity of lipid bilayers are examined. The second research project focuses on cholesterol (CHOL) dynamics in phospholipid bilayers. Several experimental and computational studies have been performed on lipid bilayers consisting of dipalmitoylphosphatidylcholine (DPPC) and CHOL molecules. CHOL interleaflet transport (flip-flop) plays an important role in interleaflet coupling and determining CHOL flip-flop rate has been elusive. Various studies report that the rate ranges between milliseconds to seconds. We calculate CHOL flip-flop rates by performing a 15 mus all-atom MD simulation of a DPPC-CHOL bilayer. We find that the CHOL flip-flop rates are on the sub microsecond timescale. These results are verified by performing various independent parallel replica (PR) simulations. Our PR simulations provide significant boost in sampling of the flip-flop events. We observe that the CHOL flip-flop can induce membrane order, regulate membrane-bending energy, and facilitate membrane relaxation. The rapid flip-flop rates reported here have important implications for the role of CHOL in mechanical properties of cell membranes, formation of domains, and maintaining CHOL concentration asymmetry in plasma membrane. Our PR approach can reach submillisecond time scales and bridge the gap between MD simulations and Nuclear Magnetic Resonance (NMR) experiments on CHOL flip-flop dynamics in membranes. The last project deals with transfection barriers encountered by a bare small interfering RNA (siRNA) in a phospholipid bilayer. SiRNA molecules play a pivotal role in therapeutic applications. A key limitation to the widespread implementation of siRNA-based therapeutics is the difficulty of delivering siRNA-based drugs to cells. We have examined structural and mechanical barriers to siRNA passage across a phospholipid bilayer using all-atom MD simulations. We find that the electrostatic interaction between the anionic siRNA and head groups of phospholipid molecules induces a phase transformation from the liquid crystalline to ripple phase. Steered MD simulations reveal that the siRNA transfection through the ripple phase requires a force of ˜ 1.5 nN.

A New Improved and Extended Version of the Multicell Bacterial Simulator gro.

PubMed

Gutiérrez, Martín; Gregorio-Godoy, Paula; Pérez Del Pulgar, Guillermo; Muñoz, Luis E; Sáez, Sandra; Rodríguez-Patón, Alfonso

2017-08-18

gro is a cell programming language developed in Klavins Lab for simulating colony growth and cell-cell communication. It is used as a synthetic biology prototyping tool for simulating multicellular biocircuits and microbial consortia. In this work, we present several extensions made to gro that improve the performance of the simulator, make it easier to use, and provide new functionalities. The new version of gro is between 1 and 2 orders of magnitude faster than the original version. It is able to grow microbial colonies with up to 10 5 cells in less than 10 min. A new library, CellEngine, accelerates the resolution of spatial physical interactions between growing and dividing cells by implementing a new shoving algorithm. A genetic library, CellPro, based on Probabilistic Timed Automata, simulates gene expression dynamics using simplified and easy to compute digital proteins. We also propose a more convenient language specification layer, ProSpec, based on the idea that proteins drive cell behavior. CellNutrient, another library, implements Monod-based growth and nutrient uptake functionalities. The intercellular signaling management was improved and extended in a library called CellSignals. Finally, bacterial conjugation, another local cell-cell communication process, was added to the simulator. To show the versatility and potential outreach of this version of gro, we provide studies and novel examples ranging from synthetic biology to evolutionary microbiology. We believe that the upgrades implemented for gro have made it into a powerful and fast prototyping tool capable of simulating a large variety of systems and synthetic biology designs.

Evolutionary dynamics of imatinib-treated leukemic cells by stochastic approach

NASA Astrophysics Data System (ADS)

Pizzolato, Nicola; Valenti, Davide; Adorno, Dominique Persano; Spagnolo, Bernardo

2009-09-01

The evolutionary dynamics of a system of cancerous cells in a model of chronic myeloid leukemia (CML) is investigated by a statistical approach. Cancer progression is explored by applying a Monte Carlo method to simulate the stochastic behavior of cell reproduction and death in a population of blood cells which can experience genetic mutations. In CML front line therapy is represented by the tyrosine kinase inhibitor imatinib which strongly affects the reproduction of leukemic cells only. In this work, we analyze the effects of a targeted therapy on the evolutionary dynamics of normal, first-mutant and cancerous cell populations. Several scenarios of the evolutionary dynamics of imatinib-treated leukemic cells are described as a consequence of the efficacy of the different modelled therapies. We show how the patient response to the therapy changes when a high value of the mutation rate from healthy to cancerous cells is present. Our results are in agreement with clinical observations. Unfortunately, development of resistance to imatinib is observed in a fraction of patients, whose blood cells are characterized by an increasing number of genetic alterations. We find that the occurrence of resistance to the therapy can be related to a progressive increase of deleterious mutations.

Dynamics of human T-cell lymphotropic virus I (HTLV-I) infection of CD4+ T-cells.

PubMed

Katri, Patricia; Ruan, Shigui

2004-11-01

Stilianakis and Seydel (Bull. Math. Biol., 1999) proposed an ODE model that describes the T-cell dynamics of human T-cell lymphotropic virus I (HTLV-I) infection and the development of adult T-cell leukemia (ATL). Their model consists of four components: uninfected healthy CD4+ T-cells, latently infected CD4+ T-cells, actively infected CD4+ T-cells, and ATL cells. Mathematical analysis that completely determines the global dynamics of this model has been done by Wang et al. (Math. Biosci., 2002). In this note, we first modify the parameters of the model to distinguish between contact and infectivity rates. Then we introduce a discrete time delay to the model to describe the time between emission of contagious particles by active CD4+ T-cells and infection of pure cells. Using the results in Culshaw and Ruan (Math. Biosci., 2000) in the analysis of time delay with respect to cell-free viral spread of HIV, we study the effect of time delay on the stability of the endemically infected equilibrium. Numerical simulations are presented to illustrate the results.

Organization and Dynamics of Receptor Proteins in a Plasma Membrane.

PubMed

Koldsø, Heidi; Sansom, Mark S P

2015-11-25

The interactions of membrane proteins are influenced by their lipid environment, with key lipid species able to regulate membrane protein function. Advances in high-resolution microscopy can reveal the organization and dynamics of proteins and lipids within living cells at resolutions <200 nm. Parallel advances in molecular simulations provide near-atomic-resolution models of the dynamics of the organization of membranes of in vivo-like complexity. We explore the dynamics of proteins and lipids in crowded and complex plasma membrane models, thereby closing the gap in length and complexity between computations and experiments. Our simulations provide insights into the mutual interplay between lipids and proteins in determining mesoscale (20-100 nm) fluctuations of the bilayer, and in enabling oligomerization and clustering of membrane proteins.

Thermal decomposition of solid phase nitromethane under various heating rates and target temperatures based on ab initio molecular dynamics simulations.

PubMed

Xu, Kai; Wei, Dong-Qing; Chen, Xiang-Rong; Ji, Guang-Fu

2014-10-01

The Car-Parrinello molecular dynamics simulation was applied to study the thermal decomposition of solid phase nitromethane under gradual heating and fast annealing conditions. In gradual heating simulations, we found that, rather than C-N bond cleavage, intermolecular proton transfer is more likely to be the first reaction in the decomposition process. At high temperature, the first reaction in fast annealing simulation is intermolecular proton transfer leading to CH3NOOH and CH2NO2, whereas the initial chemical event at low temperature tends to be a unimolecular C-N bond cleavage, producing CH3 and NO2 fragments. It is the first time to date that the direct rupture of a C-N bond has been reported as the first reaction in solid phase nitromethane. In addition, the fast annealing simulations on a supercell at different temperatures are conducted to validate the effect of simulation cell size on initial reaction mechanisms. The results are in qualitative agreement with the simulations on a unit cell. By analyzing the time evolution of some molecules, we also found that the time of first water molecule formation is clearly sensitive to heating rates and target temperatures when the first reaction is an intermolecular proton transfer.

Design and testing of a unique randomized gravity, continuous flow bioreactor

NASA Technical Reports Server (NTRS)

Lassiter, Carroll B.

1993-01-01

A rotating, null gravity simulator, or Couette bioreactor was successfully used for the culture of mammalian cells in a simulated microgravity environment. Two limited studies using Lipomyces starkeyi and Streptomyces clavuligerus were also conducted under conditions of simulated weightlessness. Although these studies with microorganisms showed promising preliminary results, oxygen limitations presented significant limitations in studying the biochemical and cultural characteristics of these cell types. Microbial cell systems such as bacteria and yeast promise significant potential as investigative models to study the effects of microgravity on membrane transport, as well as substrate induction of inactive enzyme systems. Additionally, the smaller size of the microorganisms should further reduce the gravity induced oscillatory particle motion and thereby improve the microgravity simulation on earth. Focus is on the unique conceptual design, and subsequent development of a rotating bioreactor that is compatible with the culture and investigation of microgravity effects on microbial systems. The new reactor design will allow testing of highly aerobic cell types under simulated microgravity conditions. The described reactor affords a mechanism for investigating the long term effects of reduced gravity on cellular respiration, membrane transfer, ion exchange, and substrate conversions. It offers the capability of dynamically altering nutrients, oxygenation, pH, carbon dioxide, and substrate concentration without disturbing the microgravity simulation, or Couette flow, of the reactor. All progeny of the original cell inoculum may be acclimated to the simulated microgravity in the absence of a substrate or nutrient. The reactor has the promise of allowing scientists to probe the long term effects of weightlessness on cell interactions in plants, bacteria, yeast, and fungi. The reactor is designed to have a flow field growth chamber with uniform shear stress, yet transfer high concentrations of oxygen into the culture medium. The system described allows for continuous, on line sampling for production of product without disturbing fluid and particle dynamics in the reaction chamber. It provides for the introduction of substrate, or control substances after cell adaptation to simulated microgravity has been accomplished. The reactor system provides for the nondisruptive, continuous flow replacement of nutrient and removal of product. On line monitoring and control of growth conditions such as pH and nutrient status are provided. A rotating distribution valve allows cessation of growth chamber rotation, thereby preserving the simulated microgravity conditions over longer periods of time.

Autoinhibitory mechanisms of ERG studied by molecular dynamics simulations

NASA Astrophysics Data System (ADS)

Lu, Yan; Salsbury, Freddie R.

2015-01-01

ERG, an ETS-family transcription factor, acts as a regulator of differentiation of early hematopoietic cells. It contains an autoinhibitory domain, which negatively regulates DNA-binding. The mechanism of autoinhibitory is still illusive. To understand the mechanism, we study the dynamical properties of ERG protein by molecular dynamics simulations. These simulations suggest that DNA binding autoinhibition associates with the internal dynamics of ERG. Specifically, we find that (1), The N-C terminal correlation in the inhibited ERG is larger than that in uninhibited ERG that contributes to the autoinhibition of DNA-binding. (2), DNA-binding changes the property of the N-C terminal correlation from being anti-correlated to correlated, that is, changing the relative direction of the correlated motions and (3), For the Ets-domain specifically, the inhibited and uninhibited forms exhibit essentially the same dynamics, but the binding of the DNA decreases the fluctuation of the Ets-domain. We also find from PCA analysis that the three systems, even with quite different dynamics, do have highly similar free energy surfaces, indicating that they share similar conformations.

Chemotaxis in densely populated tissue determines germinal center anatomy and cell motility: a new paradigm for the development of complex tissues.

PubMed

Hawkins, Jared B; Jones, Mark T; Plassmann, Paul E; Thorley-Lawson, David A

2011-01-01

Germinal centers (GCs) are complex dynamic structures that form within lymph nodes as an essential process in the humoral immune response. They represent a paradigm for studying the regulation of cell movement in the development of complex anatomical structures. We have developed a simulation of a modified cyclic re-entry model of GC dynamics which successfully employs chemotaxis to recapitulate the anatomy of the primary follicle and the development of a mature GC, including correctly structured mantle, dark and light zones. We then show that correct single cell movement dynamics (including persistent random walk and inter-zonal crossing) arise from this simulation as purely emergent properties. The major insight of our study is that chemotaxis can only achieve this when constrained by the known biological properties that cells are incompressible, exist in a densely packed environment, and must therefore compete for space. It is this interplay of chemotaxis and competition for limited space that generates all the complex and biologically accurate behaviors described here. Thus, from a single simple mechanism that is well documented in the biological literature, we can explain both higher level structure and single cell movement behaviors. To our knowledge this is the first GC model that is able to recapitulate both correctly detailed anatomy and single cell movement. This mechanism may have wide application for modeling other biological systems where cells undergo complex patterns of movement to produce defined anatomical structures with sharp tissue boundaries.

Integration of Weather Avoidance and Traffic Separation

NASA Technical Reports Server (NTRS)

Consiglio, Maria C.; Chamberlain, James P.; Wilson, Sara R.

2011-01-01

This paper describes a dynamic convective weather avoidance concept that compensates for weather motion uncertainties; the integration of this weather avoidance concept into a prototype 4-D trajectory-based Airborne Separation Assurance System (ASAS) application; and test results from a batch (non-piloted) simulation of the integrated application with high traffic densities and a dynamic convective weather model. The weather model can simulate a number of pseudo-random hazardous weather patterns, such as slow- or fast-moving cells and opening or closing weather gaps, and also allows for modeling of onboard weather radar limitations in range and azimuth. The weather avoidance concept employs nested "core" and "avoid" polygons around convective weather cells, and the simulations assess the effectiveness of various avoid polygon sizes in the presence of different weather patterns, using traffic scenarios representing approximately two times the current traffic density in en-route airspace. Results from the simulation experiment show that the weather avoidance concept is effective over a wide range of weather patterns and cell speeds. Avoid polygons that are only 2-3 miles larger than their core polygons are sufficient to account for weather uncertainties in almost all cases, and traffic separation performance does not appear to degrade with the addition of weather polygon avoidance. Additional "lessons learned" from the batch simulation study are discussed in the paper, along with insights for improving the weather avoidance concept. Introduction

Alignment of cell division axes in directed epithelial cell migration

NASA Astrophysics Data System (ADS)

Marel, Anna-Kristina; Podewitz, Nils; Zorn, Matthias; Oskar Rädler, Joachim; Elgeti, Jens

2014-11-01

Cell division is an essential dynamic event in tissue remodeling during wound healing, cancer and embryogenesis. In collective migration, tensile stresses affect cell shape and polarity, hence, the orientation of the cell division axis is expected to depend on cellular flow patterns. Here, we study the degree of orientation of cell division axes in migrating and resting epithelial cell sheets. We use microstructured channels to create a defined scenario of directed cell invasion and compare this situation to resting but proliferating cell monolayers. In experiments, we find a strong alignment of the axis due to directed flow while resting sheets show very weak global order, but local flow gradients still correlate strongly with the cell division axis. We compare experimental results with a previously published mesoscopic particle based simulation model. Most of the observed effects are reproduced by the simulations.

Competing dynamic phases of active polymer networks

NASA Astrophysics Data System (ADS)

Freedman, Simon; Banerjee, Shiladitya; Dinner, Aaron R.

Recent experiments on in-vitro reconstituted assemblies of F-actin, myosin-II motors, and cross-linking proteins show that tuning local network properties can changes the fundamental biomechanical behavior of the system. For example, by varying cross-linker density and actin bundle rigidity, one can switch between contractile networks useful for reshaping cells, polarity sorted networks ideal for directed molecular transport, and frustrated networks with robust structural properties. To efficiently investigate the dynamic phases of actomyosin networks, we developed a coarse grained non-equilibrium molecular dynamics simulation of model semiflexible filaments, molecular motors, and cross-linkers with phenomenologically defined interactions. The simulation's accuracy was verified by benchmarking the mechanical properties of its individual components and collective behavior against experimental results at the molecular and network scales. By adjusting the model's parameters, we can reproduce the qualitative phases observed in experiment and predict the protein characteristics where phase crossovers could occur in collective network dynamics. Our model provides a framework for understanding cells' multiple uses of actomyosin networks and their applicability in materials research. Supported by the Department of Defense (DoD) through the National Defense Science & Engineering Graduate Fellowship (NDSEG) Program.

Multiscale modeling and simulation of microtubule-motor-protein assemblies

NASA Astrophysics Data System (ADS)

Gao, Tong; Blackwell, Robert; Glaser, Matthew A.; Betterton, M. D.; Shelley, Michael J.

2015-12-01

Microtubules and motor proteins self-organize into biologically important assemblies including the mitotic spindle and the centrosomal microtubule array. Outside of cells, microtubule-motor mixtures can form novel active liquid-crystalline materials driven out of equilibrium by adenosine triphosphate-consuming motor proteins. Microscopic motor activity causes polarity-dependent interactions between motor proteins and microtubules, but how these interactions yield larger-scale dynamical behavior such as complex flows and defect dynamics is not well understood. We develop a multiscale theory for microtubule-motor systems in which Brownian dynamics simulations of polar microtubules driven by motors are used to study microscopic organization and stresses created by motor-mediated microtubule interactions. We identify polarity-sorting and crosslink tether relaxation as two polar-specific sources of active destabilizing stress. We then develop a continuum Doi-Onsager model that captures polarity sorting and the hydrodynamic flows generated by these polar-specific active stresses. In simulations of active nematic flows on immersed surfaces, the active stresses drive turbulent flow dynamics and continuous generation and annihilation of disclination defects. The dynamics follow from two instabilities, and accounting for the immersed nature of the experiment yields unambiguous characteristic length and time scales. When turning off the hydrodynamics in the Doi-Onsager model, we capture formation of polar lanes as observed in the Brownian dynamics simulation.

Multiscale modeling and simulation of microtubule-motor-protein assemblies.

PubMed

Gao, Tong; Blackwell, Robert; Glaser, Matthew A; Betterton, M D; Shelley, Michael J

2015-01-01

Microtubules and motor proteins self-organize into biologically important assemblies including the mitotic spindle and the centrosomal microtubule array. Outside of cells, microtubule-motor mixtures can form novel active liquid-crystalline materials driven out of equilibrium by adenosine triphosphate-consuming motor proteins. Microscopic motor activity causes polarity-dependent interactions between motor proteins and microtubules, but how these interactions yield larger-scale dynamical behavior such as complex flows and defect dynamics is not well understood. We develop a multiscale theory for microtubule-motor systems in which Brownian dynamics simulations of polar microtubules driven by motors are used to study microscopic organization and stresses created by motor-mediated microtubule interactions. We identify polarity-sorting and crosslink tether relaxation as two polar-specific sources of active destabilizing stress. We then develop a continuum Doi-Onsager model that captures polarity sorting and the hydrodynamic flows generated by these polar-specific active stresses. In simulations of active nematic flows on immersed surfaces, the active stresses drive turbulent flow dynamics and continuous generation and annihilation of disclination defects. The dynamics follow from two instabilities, and accounting for the immersed nature of the experiment yields unambiguous characteristic length and time scales. When turning off the hydrodynamics in the Doi-Onsager model, we capture formation of polar lanes as observed in the Brownian dynamics simulation.

Multiscale modeling and simulation of microtubule–motor-protein assemblies

PubMed Central

Gao, Tong; Blackwell, Robert; Glaser, Matthew A.; Betterton, M. D.; Shelley, Michael J.

2016-01-01

Microtubules and motor proteins self-organize into biologically important assemblies including the mitotic spindle and the centrosomal microtubule array. Outside of cells, microtubule-motor mixtures can form novel active liquid-crystalline materials driven out of equilibrium by adenosine triphosphate–consuming motor proteins. Microscopic motor activity causes polarity-dependent interactions between motor proteins and microtubules, but how these interactions yield larger-scale dynamical behavior such as complex flows and defect dynamics is not well understood. We develop a multiscale theory for microtubule-motor systems in which Brownian dynamics simulations of polar microtubules driven by motors are used to study microscopic organization and stresses created by motor-mediated microtubule interactions. We identify polarity-sorting and crosslink tether relaxation as two polar-specific sources of active destabilizing stress. We then develop a continuum Doi-Onsager model that captures polarity sorting and the hydrodynamic flows generated by these polar-specific active stresses. In simulations of active nematic flows on immersed surfaces, the active stresses drive turbulent flow dynamics and continuous generation and annihilation of disclination defects. The dynamics follow from two instabilities, and accounting for the immersed nature of the experiment yields unambiguous characteristic length and time scales. When turning off the hydrodynamics in the Doi-Onsager model, we capture formation of polar lanes as observed in the Brownian dynamics simulation. PMID:26764729

Climatology of convective showers dynamics in a convection-permitting model

NASA Astrophysics Data System (ADS)

Brisson, Erwan; Brendel, Christoph; Ahrens, Bodo

2017-04-01

Convection-permitting simulations have proven their usefulness in improving both the representation of convective rain and the uncertainty range of climate projections. However, most studies have focused on temporal scales greater or equal to convection cell lifetime. A large knowledge gap remains on the model's performance in representing the temporal dynamic of convective showers and how could this temporal dynamic be altered in a warmer climate. In this study, we proposed to fill this gap by analyzing 5-minute convection-permitting model (CPM) outputs. In total, more than 1200 one-day cases are simulated at the resolution of 0.01° using the regional climate model COSMO-CLM over central Europe. The analysis follows a Lagrangian approach and consists of tracking showers characterized by five-minute intensities greater than 20 mm/hour. The different features of these showers (e.g., temporal evolution, horizontal speed, lifetime) are investigated. These features as modeled by an ERA-Interim forced simulation are evaluated using a radar dataset for the period 2004-2010. The model shows good performance in representing most features observed in the radar dataset. Besides, the observed relation between the temporal evolution of precipitation and temperature are well reproduced by the CPM. In a second modeling experiment, the impact of climate change on convective cell features are analyzed based on an EC-Earth RCP8.5 forced simulation for the period 2071-2100. First results show only minor changes in the temporal structure and size of showers. The increase in convective precipitation found in previous studies seems to be mainly due to an increase in the number of convective cells.

4D Biofabrication of Branching Multicellular Structures: A Morphogenesis Simulation Based on Turing’s Reaction-Diffusion Dynamics

NASA Astrophysics Data System (ADS)

Zhu, Xiaolu; Yang, Hao

2017-12-01

The recently emerged four-dimensional (4D) biofabrication technique aims to create dynamic three-dimensional (3D) biological structures that can transform their shapes or functionalities with time when an external stimulus is imposed or when cell postprinting self-assembly occurs. The evolution of 3D pattern of branching geometry via self-assembly of cells is critical for 4D biofabrication of artificial organs or tissues with branched geometry. However, it is still unclear that how the formation and evolution of these branching pattern are biologically encoded. We study the 4D fabrication of lung branching structures utilizing a simulation model on the reaction-diffusion mechanism, which is established using partial differential equations of four variables, describing the reaction and diffusion process of morphogens with time during the development process of lung branching. The simulation results present the forming process of 3D branching pattern, and also interpret the behaviors of side branching and tip splitting as the stalk growing, through 3D visualization of numerical simulation.

Particle-In-Cell Simulations of Asymmetric Dual Frequency Capacitive Discharge Physics

NASA Astrophysics Data System (ADS)

Wu, Alan; Lichtenberg, A. J.; Lieberman, M. A.; Verboncoeur, J. P.

2003-10-01

Dual frequency capacitive discharges are finding increasing use for etching in the microelectronics industry. In the ideal case, the high frequency power (typically 27.1-160 MHz) controls the plasma density and the low frequency power (typically 2-13.56 MHz) controls the ion energy. The electron power deposition and the dynamics of dual frequency rf sheaths are not well understood. We report on particle-in-cell computer simulations of an asymmetric dual frequency argon discharge. The simulations are performed in 1D (radial) geometry using the bounded electrostatic code XPDP1. Operating parameters are 27.1/2 MHz high/low frequencies, 10/13 cm inner/outer radii, 3-200 mTorr pressures, and 10^9-10^11 cm-3 densities. We determine the power deposition and sheath dynamics for the high frequency power alone, and with various added low frequency powers. We compare the simulation results to simple global models of dual frequency discharges. Support provided by Lam Research, NSF Grant ECS-0139956, California industries, and UC-SMART Contract SM99-10051.

Dynamic simulation of stent deployment - effects of design, material and coating

NASA Astrophysics Data System (ADS)

Schiavone, A.; Zhao, L. G.; Abdel-Wahab, A. A.

2013-07-01

Dynamic finite-element simulations have been carried out to study the effects of cell design, material choice and drug eluting coating on the mechanical behaviour of stents during deployment. Four representative stent designs have been considered, i.e., Palmaz-Schatz, Cypher, Xience and Endeavor. The former two are made of stainless steel while the latter two made of Co-Cr alloy. Geometric model for each design was created using ProEngineer software, and then imported into Abaqus for simulation of the full process of stent deployment within a diseased artery. In all cases, the delivery system was based on the dynamic expansion of a polyurethane balloon under applied internal pressure. Results showed that the expansion is mainly governed by the design, in particular open-cell design (e.g. Endeavor) tends to have greater expansion than closed-cell design (e.g. Cypher). Dogboning effect was strong for slotted tube design (e.g. Palmaz-Schatz) but reduced significantly for sinusoidal design (e.g. Cypher). Under the same pressure, the maximum von Mises stress in the stent was higher for the open-cell designs and located mostly at the inner corners of each cell. For given deformation, stents made of Co-Cr alloys tend to experience higher stress level than those made of stainless steels, mainly due to the difference in material properties. For artery-plaque system, the maximum stress occurred on the stenosis and dogboning led to stress concentration at the ends of the plaque. The drug eluting coating affected the stent expansion by reducing the recoiling phenomenon considerably, but also raised the stress level on the stent due to property mismatch.

From Databases to Modelling of Functional Pathways

PubMed Central

2004-01-01

This short review comments on current informatics resources and methodologies in the study of functional pathways in cell biology. It highlights recent achievements in unveiling the structural design of protein and gene networks and discusses current approaches to model and simulate the dynamics of regulatory pathways in the cell. PMID:18629070

From databases to modelling of functional pathways.

PubMed

Nasi, Sergio

2004-01-01

This short review comments on current informatics resources and methodologies in the study of functional pathways in cell biology. It highlights recent achievements in unveiling the structural design of protein and gene networks and discusses current approaches to model and simulate the dynamics of regulatory pathways in the cell.

Research Symposium I

NASA Technical Reports Server (NTRS)

2004-01-01

The proceedings of this symposium consist of abstracts of talks presented by interns at NASA Glenn Research Center (GRC). The interns assisted researchers at GRC in projects which primarily address the following topics: aircraft engines and propulsion, spacecraft propulsion, fuel cells, thin film photovoltaic cells, aerospace materials, computational fluid dynamics, aircraft icing, management, and computerized simulation.

Modelling and simulation techniques for membrane biology.

PubMed

Burrage, Kevin; Hancock, John; Leier, André; Nicolau, Dan V

2007-07-01

One of the most important aspects of Computational Cell Biology is the understanding of the complicated dynamical processes that take place on plasma membranes. These processes are often so complicated that purely temporal models cannot always adequately capture the dynamics. On the other hand, spatial models can have large computational overheads. In this article, we review some of these issues with respect to chemistry, membrane microdomains and anomalous diffusion and discuss how to select appropriate modelling and simulation paradigms based on some or all the following aspects: discrete, continuous, stochastic, delayed and complex spatial processes.

Initial Beam Dynamics Simulations of a High-Average-Current Field-Emission Electron Source in a Superconducting RadioFrequency Gun

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

Mohsen, O.; Gonin, I.; Kephart, R.

High-power electron beams are sought-after tools in support to a wide array of societal applications. This paper investigates the production of high-power electron beams by combining a high-current field-emission electron source to a superconducting radio-frequency (SRF) cavity. We especially carry out beam-dynamics simulations that demonstrate the viability of the scheme to formmore » $$\\sim$$ 300 kW average-power electron beam using a 1+1/2-cell SRF gun.« less

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.

Modeling the locomotion of the African trypanosome using multi-particle collision dynamics

NASA Astrophysics Data System (ADS)

Babu, Sujin B.; Stark, Holger

2012-08-01

The African trypanosome is a single flagellated micro-organism that causes the deadly sleeping sickness in humans and animals. We study the locomotion of a model trypanosome by modeling the spindle-shaped cell body using an elastic network of vertices with additional bending rigidity. The flagellum firmly attached to the model cell body is either straight or helical. A bending wave propagates along the flagellum and pushes the trypanosome forward in its viscous environment, which we simulate with the method of multi-particle collision dynamics. The relaxation dynamics of the model cell body due to a static bending wave reveals the sperm number from elastohydrodynamics as the relevant parameter. Characteristic cell body conformations for the helically attached flagellum resemble experimental observations. We show that the swimming velocity scales as the root of the angular frequency of the bending wave reminiscent of predictions for an actuated slender rod attached to a large viscous load. The swimming velocity for one geometry collapses on a single master curve when plotted versus the sperm number. The helically attached flagellum leads to a helical swimming path and a rotation of the model trypanosome about its long axis as observed in experiments. The simulated swimming velocity agrees with the experimental value.

Stochastic simulation of biological reactions, and its applications for studying actin polymerization.

PubMed

Ichikawa, Kazuhisa; Suzuki, Takashi; Murata, Noboru

2010-11-30

Molecular events in biological cells occur in local subregions, where the molecules tend to be small in number. The cytoskeleton, which is important for both the structural changes of cells and their functions, is also a countable entity because of its long fibrous shape. To simulate the local environment using a computer, stochastic simulations should be run. We herein report a new method of stochastic simulation based on random walk and reaction by the collision of all molecules. The microscopic reaction rate P(r) is calculated from the macroscopic rate constant k. The formula involves only local parameters embedded for each molecule. The results of the stochastic simulations of simple second-order, polymerization, Michaelis-Menten-type and other reactions agreed quite well with those of deterministic simulations when the number of molecules was sufficiently large. An analysis of the theory indicated a relationship between variance and the number of molecules in the system, and results of multiple stochastic simulation runs confirmed this relationship. We simulated Ca²(+) dynamics in a cell by inward flow from a point on the cell surface and the polymerization of G-actin forming F-actin. Our results showed that this theory and method can be used to simulate spatially inhomogeneous events.

Accelerated molecular dynamics and protein conformational change: a theoretical and practical guide using a membrane embedded model neurotransmitter transporter.

PubMed

Gedeon, Patrick C; Thomas, James R; Madura, Jeffry D

2015-01-01

Molecular dynamics simulation provides a powerful and accurate method to model protein conformational change, yet timescale limitations often prevent direct assessment of the kinetic properties of interest. A large number of molecular dynamic steps are necessary for rare events to occur, which allow a system to overcome energy barriers and conformationally transition from one potential energy minimum to another. For many proteins, the energy landscape is further complicated by a multitude of potential energy wells, each separated by high free-energy barriers and each potentially representative of a functionally important protein conformation. To overcome these obstacles, accelerated molecular dynamics utilizes a robust bias potential function to simulate the transition between different potential energy minima. This straightforward approach more efficiently samples conformational space in comparison to classical molecular dynamics simulation, does not require advanced knowledge of the potential energy landscape and converges to the proper canonical distribution. Here, we review the theory behind accelerated molecular dynamics and discuss the approach in the context of modeling protein conformational change. As a practical example, we provide a detailed, step-by-step explanation of how to perform an accelerated molecular dynamics simulation using a model neurotransmitter transporter embedded in a lipid cell membrane. Changes in protein conformation of relevance to the substrate transport cycle are then examined using principle component analysis.

Non-Brownian dynamics and strategy of amoeboid cell locomotion.

PubMed

Nishimura, Shin I; Ueda, Masahiro; Sasai, Masaki

2012-04-01

Amoeboid cells such as Dictyostelium discoideum and Madin-Darby canine kidney cells show the non-Brownian dynamics of migration characterized by the superdiffusive increase of mean-squared displacement. In order to elucidate the physical mechanism of this non-Brownian dynamics, a computational model is developed which highlights a group of inhibitory molecules for actin polymerization. Based on this model, we propose a hypothesis that inhibitory molecules are sent backward in the moving cell to accumulate at the rear of cell. The accumulated inhibitory molecules at the rear further promote cell locomotion to form a slow positive feedback loop of the whole-cell scale. The persistent straightforward migration is stabilized with this feedback mechanism, but the fluctuation in the distribution of inhibitory molecules and the cell shape deformation concurrently interrupt the persistent motion to turn the cell into a new direction. A sequence of switching behaviors between persistent motions and random turns gives rise to the superdiffusive migration in the absence of the external guidance signal. In the complex environment with obstacles, this combined process of persistent motions and random turns drives the simulated amoebae to solve the maze problem in a highly efficient way, which suggests the biological advantage for cells to bear the non-Brownian dynamics.

Finite element simulation of location- and time-dependent mechanical behavior of chondrocytes in unconfined compression tests.

PubMed

Wu, J Z; Herzog, W

2000-03-01

Experimental evidence suggests that cells are extremely sensitive to their mechanical environment and react directly to mechanical stimuli. At present, it is technically difficult to measure fluid pressure, stress, and strain in cells, and to determine the time-dependent deformation of chondrocytes. For this reason, there are no data in the published literature that show the dynamic behavior of chondrocytes in articular cartilage. Similarly, the dynamic chondrocyte mechanics have not been calculated using theoretical models that account for the influence of cell volumetric fraction on cartilage mechanical properties. In the present investigation, the location- and time-dependent stress-strain state and fluid pressure distribution in chondrocytes in unconfined compression tests were simulated numerically using a finite element method. The technique involved two basic steps: first, cartilage was approximated as a macroscopically homogenized material and the mechanical behavior of cartilage was obtained using the homogenized model; second, the solution of the time-dependent displacements and fluid pressure fields of the homogenized model was used as the time-dependent boundary conditions for a microscopic submodel to obtain average location- and time-dependent mechanical behavior of cells. Cells and extracellular matrix were assumed to be biphasic materials composed of a fluid phase and a hyperelastic solid phase. The hydraulic permeability was assumed to be deformation dependent and the analysis was performed using a finite deformation approach. Numerical tests were made using configurations similar to those of experiments described in the literature. Our simulations show that the mechanical response of chondrocytes to cartilage loading depends on time, fluid boundary conditions, and the locations of the cells within the specimen. The present results are the first to suggest that chondrocyte deformation in a stress-relaxation type test may exceed the imposed system deformation by a factor of 3-4, that chondrocyte deformations are highly dynamic and do not reach a steady state within about 20 min of steady compression (in an unconfined test), and that cell deformations are very much location dependent.

A deterministic and stochastic model for the system dynamics of tumor-immune responses to chemotherapy

NASA Astrophysics Data System (ADS)

Liu, Xiangdong; Li, Qingze; Pan, Jianxin

2018-06-01

Modern medical studies show that chemotherapy can help most cancer patients, especially for those diagnosed early, to stabilize their disease conditions from months to years, which means the population of tumor cells remained nearly unchanged in quite a long time after fighting against immune system and drugs. In order to better understand the dynamics of tumor-immune responses under chemotherapy, deterministic and stochastic differential equation models are constructed to characterize the dynamical change of tumor cells and immune cells in this paper. The basic dynamical properties, such as boundedness, existence and stability of equilibrium points, are investigated in the deterministic model. Extended stochastic models include stochastic differential equations (SDEs) model and continuous-time Markov chain (CTMC) model, which accounts for the variability in cellular reproduction, growth and death, interspecific competitions, and immune response to chemotherapy. The CTMC model is harnessed to estimate the extinction probability of tumor cells. Numerical simulations are performed, which confirms the obtained theoretical results.

Bubbly vertex dynamics: A dynamical and geometrical model for epithelial tissues with curved cell shapes

NASA Astrophysics Data System (ADS)

Ishimoto, Yukitaka; Morishita, Yoshihiro

2014-11-01

In order to describe two-dimensionally packed cells in epithelial tissues both mathematically and physically, there have been developed several sorts of geometrical models, such as the vertex model, the finite element model, the cell-centered model, and the cellular Potts model. So far, in any case, pressures have not neatly been dealt with and the curvatures of the cell boundaries have been even omitted through their approximations. We focus on these quantities and formulate them in the vertex model. Thus, a model with the curvatures is constructed, and its algorithm for simulation is provided. The possible extensions and applications of this model are also discussed.

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

PubMed

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

2013-06-01

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

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

PubMed

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

2013-04-02

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

A model for including thermal conduction in molecular dynamics simulations

NASA Technical Reports Server (NTRS)

Wu, Yue; Friauf, Robert J.

1989-01-01

A technique is introduced for including thermal conduction in molecular dynamics simulations for solids. A model is developed to allow energy flow between the computational cell and the bulk of the solid when periodic boundary conditions cannot be used. Thermal conduction is achieved by scaling the velocities of atoms in a transitional boundary layer. The scaling factor is obtained from the thermal diffusivity, and the results show good agreement with the solution for a continuous medium at long times. The effects of different temperature and size of the system, and of variations in strength parameter, atomic mass, and thermal diffusivity were investigated. In all cases, no significant change in simulation results has been found.

Impact of Dynamic Specimen Shape Evolution on the Atom Probe Tomography Results of Doped Epitaxial Oxide Multilayers: Comparison of Experiment and Simulation

DOE PAGES

Madaan, Nitesh; Bao, Jie; Nandasiri, Manjula I.; ...

2015-08-31

The experimental atom probe tomography results from two different specimen orientations (top-down and side-ways) of a high oxygen ion conducting Samaria-doped-ceria/Scandia-stabilized-zirconia multilayer thin film solid oxide fuel cell electrolyte was correlated with level-set method based field evaporation simulations for the same specimen orientations. This experiment-theory correlation explains the dynamic specimen shape evolution and ion trajectory aberrations that can induce density artifacts in final reconstruction leading to inaccurate estimation of interfacial intermixing. This study highlights the need and importance of correlating experimental results with field evaporation simulations when using atom probe tomography for studying oxide heterostructure interfaces.

A Stochastic Framework for Modeling the Population Dynamics of Convective Clouds

DOE PAGES

Hagos, Samson; Feng, Zhe; Plant, Robert S.; ...

2018-02-20

A stochastic prognostic framework for modeling the population dynamics of convective clouds and representing them in climate models is proposed. The framework follows the nonequilibrium statistical mechanical approach to constructing a master equation for representing the evolution of the number of convective cells of a specific size and their associated cloud-base mass flux, given a large-scale forcing. In this framework, referred to as STOchastic framework for Modeling Population dynamics of convective clouds (STOMP), the evolution of convective cell size is predicted from three key characteristics of convective cells: (i) the probability of growth, (ii) the probability of decay, and (iii)more » the cloud-base mass flux. STOMP models are constructed and evaluated against CPOL radar observations at Darwin and convection permitting model (CPM) simulations. Multiple models are constructed under various assumptions regarding these three key parameters and the realisms of these models are evaluated. It is shown that in a model where convective plumes prefer to aggregate spatially and the cloud-base mass flux is a nonlinear function of convective cell area, the mass flux manifests a recharge-discharge behavior under steady forcing. Such a model also produces observed behavior of convective cell populations and CPM simulated cloud-base mass flux variability under diurnally varying forcing. Finally, in addition to its use in developing understanding of convection processes and the controls on convective cell size distributions, this modeling framework is also designed to serve as a nonequilibrium closure formulations for spectral mass flux parameterizations.« less

A Stochastic Framework for Modeling the Population Dynamics of Convective Clouds

NASA Astrophysics Data System (ADS)

Hagos, Samson; Feng, Zhe; Plant, Robert S.; Houze, Robert A.; Xiao, Heng

2018-02-01

A stochastic prognostic framework for modeling the population dynamics of convective clouds and representing them in climate models is proposed. The framework follows the nonequilibrium statistical mechanical approach to constructing a master equation for representing the evolution of the number of convective cells of a specific size and their associated cloud-base mass flux, given a large-scale forcing. In this framework, referred to as STOchastic framework for Modeling Population dynamics of convective clouds (STOMP), the evolution of convective cell size is predicted from three key characteristics of convective cells: (i) the probability of growth, (ii) the probability of decay, and (iii) the cloud-base mass flux. STOMP models are constructed and evaluated against CPOL radar observations at Darwin and convection permitting model (CPM) simulations. Multiple models are constructed under various assumptions regarding these three key parameters and the realisms of these models are evaluated. It is shown that in a model where convective plumes prefer to aggregate spatially and the cloud-base mass flux is a nonlinear function of convective cell area, the mass flux manifests a recharge-discharge behavior under steady forcing. Such a model also produces observed behavior of convective cell populations and CPM simulated cloud-base mass flux variability under diurnally varying forcing. In addition to its use in developing understanding of convection processes and the controls on convective cell size distributions, this modeling framework is also designed to serve as a nonequilibrium closure formulations for spectral mass flux parameterizations.

A Stochastic Framework for Modeling the Population Dynamics of Convective Clouds

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

Hagos, Samson; Feng, Zhe; Plant, Robert S.

A stochastic prognostic framework for modeling the population dynamics of convective clouds and representing them in climate models is proposed. The framework follows the nonequilibrium statistical mechanical approach to constructing a master equation for representing the evolution of the number of convective cells of a specific size and their associated cloud-base mass flux, given a large-scale forcing. In this framework, referred to as STOchastic framework for Modeling Population dynamics of convective clouds (STOMP), the evolution of convective cell size is predicted from three key characteristics of convective cells: (i) the probability of growth, (ii) the probability of decay, and (iii)more » the cloud-base mass flux. STOMP models are constructed and evaluated against CPOL radar observations at Darwin and convection permitting model (CPM) simulations. Multiple models are constructed under various assumptions regarding these three key parameters and the realisms of these models are evaluated. It is shown that in a model where convective plumes prefer to aggregate spatially and the cloud-base mass flux is a nonlinear function of convective cell area, the mass flux manifests a recharge-discharge behavior under steady forcing. Such a model also produces observed behavior of convective cell populations and CPM simulated cloud-base mass flux variability under diurnally varying forcing. Finally, in addition to its use in developing understanding of convection processes and the controls on convective cell size distributions, this modeling framework is also designed to serve as a nonequilibrium closure formulations for spectral mass flux parameterizations.« less

A two-scale model for correlation between B cell VDJ usage in zebrafish

NASA Astrophysics Data System (ADS)

Pan, Keyao; Deem, Michael

2011-03-01

The zebrafish (Danio rerio) is one of the model animals for study of immunology. The dynamics of the adaptive immune system in zebrafish is similar to that in higher animals. In this work, we built a two-scale model to simulate the dynamics of B cells in primary and secondary immune reactions in zebrafish and to explain the reported correlation between VDJ usage of B cell repertoires in distinct zebrafish. The first scale of the model consists of a generalized NK model to simulate the B cell maturation process in the 10-day primary immune response. The second scale uses a delay ordinary differential equation system to model the immune responses in the 6-month lifespan of zebrafish. The generalized NK model shows that mature B cells specific to one antigen mostly possess a single VDJ recombination. The probability that mature B cells in two zebrafish have the same VDJ recombination increases with the B cell population size or the B cell selection intensity and decreases with the B cell hypermutation rate. The ODE model shows a distribution of correlation in the VDJ usage of the B cell repertoires in two six-month-old zebrafish that is highly similar to that from experiment. This work presents a simple theory to explain the experimentally observed correlation in VDJ usage of distinct zebrafish B cell repertoires after an immune response.

Emergent 1d Ising Behavior in AN Elementary Cellular Automaton Model

NASA Astrophysics Data System (ADS)

Kassebaum, Paul G.; Iannacchione, Germano S.

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

Prediction and validation of protein intermediate states from structurally rich ensembles and coarse-grained simulations

NASA Astrophysics Data System (ADS)

Orellana, Laura; Yoluk, Ozge; Carrillo, Oliver; Orozco, Modesto; Lindahl, Erik

2016-08-01

Protein conformational changes are at the heart of cell functions, from signalling to ion transport. However, the transient nature of the intermediates along transition pathways hampers their experimental detection, making the underlying mechanisms elusive. Here we retrieve dynamic information on the actual transition routes from principal component analysis (PCA) of structurally-rich ensembles and, in combination with coarse-grained simulations, explore the conformational landscapes of five well-studied proteins. Modelling them as elastic networks in a hybrid elastic-network Brownian dynamics simulation (eBDIMS), we generate trajectories connecting stable end-states that spontaneously sample the crystallographic motions, predicting the structures of known intermediates along the paths. We also show that the explored non-linear routes can delimit the lowest energy passages between end-states sampled by atomistic molecular dynamics. The integrative methodology presented here provides a powerful framework to extract and expand dynamic pathway information from the Protein Data Bank, as well as to validate sampling methods in general.

Evaluation of Cathode Air Flow Transients in a SOFC/GT Hybrid System Using Hardware in the Loop Simulation.

PubMed

Zhou, Nana; Yang, Chen; Tucker, David

2015-02-01

Thermal management in the fuel cell component of a direct fired solid oxide fuel cell gas turbine (SOFC/GT) hybrid power system can be improved by effective management and control of the cathode airflow. The disturbances of the cathode airflow were accomplished by diverting air around the fuel cell system through the manipulation of a hot-air bypass valve in open loop experiments, using a hardware-based simulation facility designed and built by the U.S. Department of Energy, National Energy Technology Laboratory (NETL). The dynamic responses of the fuel cell component and hardware component of the hybrid system were studied in this paper.

Atomistic polarizable force field for molecular dynamics simulations of azide anion containing ionic liquids and crystals.

NASA Astrophysics Data System (ADS)

Starovoytov, Oleg; Hooper, Justin; Borodin, Oleg; Smith, Grant

2010-03-01

Atomistic polarizable force field has been developed for a number of azide anion containing ionic liquids and crystals. Hybrid Molecular Dynamics/Monte Carlo (MD/MC) simulations were performed on methylguanazinium azide and 1-(2-butynyl)-3-methyl-imidazolium azide crystals, while 1-butyl-2,3-dimethylimidazolium azide and 1-amino-3-methyl-1,2,3-triazolium azide ionic liquids were investigated using MD simulations. Crystal cell parameters and crystal structures of 1-(2-butynyl)-3-methyl-imidazolium azide were found in good agreement with X-ray experimental data. Density and ion transport of 1-butyl-2,3-dimethylimidazolium azide predicted from MD simulations were in good agreement with experiments. Details of the ionic liquid structure and relaxation mechanism will be discussed.

Atomic detail brownian dynamics simulations of concentrated protein solutions with a mean field treatment of hydrodynamic interactions.

PubMed

Mereghetti, Paolo; Wade, Rebecca C

2012-07-26

High macromolecular concentrations are a distinguishing feature of living organisms. Understanding how the high concentration of solutes affects the dynamic properties of biological macromolecules is fundamental for the comprehension of biological processes in living systems. In this paper, we describe the implementation of mean field models of translational and rotational hydrodynamic interactions into an atomically detailed many-protein brownian dynamics simulation method. Concentrated solutions (30-40% volume fraction) of myoglobin, hemoglobin A, and sickle cell hemoglobin S were simulated, and static structure factors, oligomer formation, and translational and rotational self-diffusion coefficients were computed. Good agreement of computed properties with available experimental data was obtained. The results show the importance of both solvent mediated interactions and weak protein-protein interactions for accurately describing the dynamics and the association properties of concentrated protein solutions. Specifically, they show a qualitative difference in the translational and rotational dynamics of the systems studied. Although the translational diffusion coefficient is controlled by macromolecular shape and hydrodynamic interactions, the rotational diffusion coefficient is affected by macromolecular shape, direct intermolecular interactions, and both translational and rotational hydrodynamic interactions.

A computational framework for testing arrhythmia marker sensitivities to model parameters in functionally calibrated populations of atrial cells

NASA Astrophysics Data System (ADS)

Vagos, Márcia R.; Arevalo, Hermenegild; de Oliveira, Bernardo Lino; Sundnes, Joakim; Maleckar, Mary M.

2017-09-01

Models of cardiac cell electrophysiology are complex non-linear systems which can be used to gain insight into mechanisms of cardiac dynamics in both healthy and pathological conditions. However, the complexity of cardiac models can make mechanistic insight difficult. Moreover, these are typically fitted to averaged experimental data which do not incorporate the variability in observations. Recently, building populations of models to incorporate inter- and intra-subject variability in simulations has been combined with sensitivity analysis (SA) to uncover novel ionic mechanisms and potentially clarify arrhythmogenic behaviors. We used the Koivumäki human atrial cell model to create two populations, representing normal Sinus Rhythm (nSR) and chronic Atrial Fibrillation (cAF), by varying 22 key model parameters. In each population, 14 biomarkers related to the action potential and dynamic restitution were extracted. Populations were calibrated based on distributions of biomarkers to obtain reasonable physiological behavior, and subjected to SA to quantify correlations between model parameters and pro-arrhythmia markers. The two populations showed distinct behaviors under steady state and dynamic pacing. The nSR population revealed greater variability, and more unstable dynamic restitution, as compared to the cAF population, suggesting that simulated cAF remodeling rendered cells more stable to parameter variation and rate adaptation. SA revealed that the biomarkers depended mainly on five ionic currents, with noted differences in sensitivities to these between nSR and cAF. Also, parameters could be selected to produce a model variant with no alternans and unaltered action potential morphology, highlighting that unstable dynamical behavior may be driven by specific cell parameter settings. These results ultimately suggest that arrhythmia maintenance in cAF may not be due to instability in cell membrane excitability, but rather due to tissue-level effects which promote initiation and maintenance of reentrant arrhythmia.

Molecular dynamics studies on the DNA-binding process of ERG.

PubMed

Beuerle, Matthias G; Dufton, Neil P; Randi, Anna M; Gould, Ian R

2016-11-15

The ETS family of transcription factors regulate gene targets by binding to a core GGAA DNA-sequence. The ETS factor ERG is required for homeostasis and lineage-specific functions in endothelial cells, some subset of haemopoietic cells and chondrocytes; its ectopic expression is linked to oncogenesis in multiple tissues. To date details of the DNA-binding process of ERG including DNA-sequence recognition outside the core GGAA-sequence are largely unknown. We combined available structural and experimental data to perform molecular dynamics simulations to study the DNA-binding process of ERG. In particular we were able to reproduce the ERG DNA-complex with a DNA-binding simulation starting in an unbound configuration with a final root-mean-square-deviation (RMSD) of 2.1 Å to the core ETS domain DNA-complex crystal structure. This allowed us to elucidate the relevance of amino acids involved in the formation of the ERG DNA-complex and to identify Arg385 as a novel key residue in the DNA-binding process. Moreover we were able to show that water-mediated hydrogen bonds are present between ERG and DNA in our simulations and that those interactions have the potential to achieve sequence recognition outside the GGAA core DNA-sequence. The methodology employed in this study shows the promising capabilities of modern molecular dynamics simulations in the field of protein DNA-interactions.

An experimental-computational platform for investigating microbial interactions and dynamics in communities with two codependent species

NASA Astrophysics Data System (ADS)

Fuentes-Cabrera, Miguel; Anderson, John D.; Wilmoth, Jared; Ginovart, Marta; Prats, Clara; Portell-Canal, Xavier; Retterer, Scott

Microbial interactions are critical for governing community behavior and structure in natural environments. Examination of microbial interactions in the lab involves growth under ideal conditions in batch culture; conditions that occur in nature are, however, characterized by disequilibrium. Of particular interest is the role that system variables play in shaping cell-to-cell interactions and organization at ultrafine spatial scales. We seek to use experiments and agent-based modeling to help discover mechanisms relevant to microbial dynamics and interactions in the environment. Currently, we are using an agent-based model to simulate microbial growth, dynamics and interactions that occur on a microwell-array device developed in our lab. Bacterial cells growing in the microwells of this platform can be studied with high-throughput and high-content image analyses using brightfield and fluorescence microscopy. The agent-based model is written in the language Netlogo, which in turn is ''plugged into'' a computational framework that allows submitting many calculations in parallel for different initial parameters; visualizing the outcomes in an interactive phase-like diagram; and searching, with a genetic algorithm, for the parameters that lead to the most optimal simulation outcome.

A Role for the Juxtamembrane Cytoplasm in the Molecular Dynamics of Focal Adhesions

PubMed Central

Wolfenson, Haguy; Lubelski, Ariel; Regev, Tamar; Klafter, Joseph; Henis, Yoav I.; Geiger, Benjamin

2009-01-01

Focal adhesions (FAs) are specialized membrane-associated multi-protein complexes that link the cell to the extracellular matrix and play crucial roles in cell-matrix sensing. Considerable information is available on the complex molecular composition of these sites, yet the regulation of FA dynamics is largely unknown. Based on a combination of FRAP studies in live cells, with in silico simulations and mathematical modeling, we show that the FA plaque proteins paxillin and vinculin exist in four dynamic states: an immobile FA-bound fraction, an FA-associated fraction undergoing exchange, a juxtamembrane fraction experiencing attenuated diffusion, and a fast-diffusing cytoplasmic pool. The juxtamembrane region surrounding FAs displays a gradient of FA plaque proteins with respect to both concentration and dynamics. Based on these findings, we propose a new model for the regulation of FA dynamics in which this juxtamembrane domain acts as an intermediary layer, enabling an efficient regulation of FA formation and reorganization. PMID:19172999

Advanced Hybrid Modeling of Hall Thruster Plumes

DTIC Science & Technology

2010-06-16

Hall thruster operated in the Large Vacuum Test Facility at the University of Michigan. The approach utilizes the direct simulation Monte Carlo method and the Particle-in-Cell method to simulate the collision and plasma dynamics of xenon neutrals and ions. The electrons are modeled as a fluid using conservation equations. A second code is employed to model discharge chamber behavior to provide improved input conditions at the thruster exit for the plume simulation. Simulation accuracy is assessed using experimental data previously

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

A derivation and scalable implementation of the synchronous parallel kinetic Monte Carlo method for simulating long-time dynamics

NASA Astrophysics Data System (ADS)

Byun, Hye Suk; El-Naggar, Mohamed Y.; Kalia, Rajiv K.; Nakano, Aiichiro; Vashishta, Priya

2017-10-01

Kinetic Monte Carlo (KMC) simulations are used to study long-time dynamics of a wide variety of systems. Unfortunately, the conventional KMC algorithm is not scalable to larger systems, since its time scale is inversely proportional to the simulated system size. A promising approach to resolving this issue is the synchronous parallel KMC (SPKMC) algorithm, which makes the time scale size-independent. This paper introduces a formal derivation of the SPKMC algorithm based on local transition-state and time-dependent Hartree approximations, as well as its scalable parallel implementation based on a dual linked-list cell method. The resulting algorithm has achieved a weak-scaling parallel efficiency of 0.935 on 1024 Intel Xeon processors for simulating biological electron transfer dynamics in a 4.2 billion-heme system, as well as decent strong-scaling parallel efficiency. The parallel code has been used to simulate a lattice of cytochrome complexes on a bacterial-membrane nanowire, and it is broadly applicable to other problems such as computational synthesis of new materials.

Conformational Transition Pathways of Epidermal Growth Factor Receptor Kinase Domain from Multiple Molecular Dynamics Simulations and Bayesian Clustering.

PubMed

Li, Yan; Li, Xiang; Ma, Weiya; Dong, Zigang

2014-08-12

The epidermal growth factor receptor (EGFR) is aberrantly activated in various cancer cells and an important target for cancer treatment. Deep understanding of EGFR conformational changes between the active and inactive states is of pharmaceutical interest. Here we present a strategy combining multiply targeted molecular dynamics simulations, unbiased molecular dynamics simulations, and Bayesian clustering to investigate transition pathways during the activation/inactivation process of EGFR kinase domain. Two distinct pathways between the active and inactive forms are designed, explored, and compared. Based on Bayesian clustering and rough two-dimensional free energy surfaces, the energy-favorable pathway is recognized, though DFG-flip happens in both pathways. In addition, another pathway with different intermediate states appears in our simulations. Comparison of distinct pathways also indicates that disruption of the Lys745-Glu762 interaction is critically important in DFG-flip while movement of the A-loop significantly facilitates the conformational change. Our simulations yield new insights into EGFR conformational transitions. Moreover, our results verify that this approach is valid and efficient in sampling of protein conformational changes and comparison of distinct pathways.

A nonlinear cochlear model with the outer hair cell piezoelectric activity

NASA Astrophysics Data System (ADS)

Jiang, Xiaoai; Grosh, Karl

2003-10-01

In this paper we present a simple cochlear model which captures the most important aspect of nonlinearity in the cochlea-the nonlinearity caused by the piezoelectric-like activity of outer hair cells and the variable conductance of the outer hair cell stereocilia. A one-dimensional long-wave model is built to simulate the dynamic response of the fluid-loaded basilar membrane. The basilar membrane is simulated as isolated linear oscillators along the cochlear length, and its motion is coupled with the fluid pressure and the nonlinear force produced by the outer hair cells. As the basilar membrane moves, the fluid shears stereocilia, and the resulting ion flow changes the transmembrane potential of the outer hair cells and subsequently their length, leading to further movement of the basilar membrane. The piezoelectric-like activity of the outer hair cell is simulated by a current source, and stereocilia motion is modeled as a varying conductance that changes as the basilar membrane moves. A solution in the time domain will be presented. [Work supported by NIH.

Shock waves simulated using the dual domain material point method combined with molecular dynamics

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

Zhang, Duan Z.; Dhakal, Tilak Raj

Here in this work we combine the dual domain material point method with molecular dynamics in an attempt to create a multiscale numerical method to simulate materials undergoing large deformations with high strain rates. In these types of problems, the material is often in a thermodynamically nonequilibrium state, and conventional constitutive relations or equations of state are often not available. In this method, the closure quantities, such as stress, at each material point are calculated from a molecular dynamics simulation of a group of atoms surrounding the material point. Rather than restricting the multiscale simulation in a small spatial region,more » such as phase interfaces, or crack tips, this multiscale method can be used to consider nonequilibrium thermodynamic effects in a macroscopic domain. This method takes the advantage that the material points only communicate with mesh nodes, not among themselves; therefore molecular dynamics simulations for material points can be performed independently in parallel. The dual domain material point method is chosen for this multiscale method because it can be used in history dependent problems with large deformation without generating numerical noise as material points move across cells, and also because of its convergence and conservation properties. In conclusion, to demonstrate the feasibility and accuracy of this method, we compare the results of a shock wave propagation in a cerium crystal calculated using the direct molecular dynamics simulation with the results from this combined multiscale calculation.« less

Shock waves simulated using the dual domain material point method combined with molecular dynamics

DOE PAGES

Zhang, Duan Z.; Dhakal, Tilak Raj

2017-01-17

Here in this work we combine the dual domain material point method with molecular dynamics in an attempt to create a multiscale numerical method to simulate materials undergoing large deformations with high strain rates. In these types of problems, the material is often in a thermodynamically nonequilibrium state, and conventional constitutive relations or equations of state are often not available. In this method, the closure quantities, such as stress, at each material point are calculated from a molecular dynamics simulation of a group of atoms surrounding the material point. Rather than restricting the multiscale simulation in a small spatial region,more » such as phase interfaces, or crack tips, this multiscale method can be used to consider nonequilibrium thermodynamic effects in a macroscopic domain. This method takes the advantage that the material points only communicate with mesh nodes, not among themselves; therefore molecular dynamics simulations for material points can be performed independently in parallel. The dual domain material point method is chosen for this multiscale method because it can be used in history dependent problems with large deformation without generating numerical noise as material points move across cells, and also because of its convergence and conservation properties. In conclusion, to demonstrate the feasibility and accuracy of this method, we compare the results of a shock wave propagation in a cerium crystal calculated using the direct molecular dynamics simulation with the results from this combined multiscale calculation.« less

Modeling Cancer Cell Growth Dynamics In vitro in Response to Antimitotic Drug Treatment

PubMed Central

Lorz, Alexander; Botesteanu, Dana-Adriana; Levy, Doron

2017-01-01

Investigating the role of intrinsic cell heterogeneity emerging from variations in cell-cycle parameters and apoptosis is a crucial step toward better informing drug administration. Antimitotic agents, widely used in chemotherapy, target exclusively proliferative cells and commonly induce a prolonged mitotic arrest followed by cell death via apoptosis. In this paper, we developed a physiologically motivated mathematical framework for describing cancer cell growth dynamics that incorporates the intrinsic heterogeneity in the time individual cells spend in the cell-cycle and apoptosis process. More precisely, our model comprises two age-structured partial differential equations for the proliferative and apoptotic cell compartments and one ordinary differential equation for the quiescent compartment. To reflect the intrinsic cell heterogeneity that governs the growth dynamics, proliferative and apoptotic cells are structured in “age,” i.e., the amount of time remaining to be spent in each respective compartment. In our model, we considered an antimitotic drug whose effect on the cellular dynamics is to induce mitotic arrest, extending the average cell-cycle length. The prolonged mitotic arrest induced by the drug can trigger apoptosis if the time a cell will spend in the cell cycle is greater than the mitotic arrest threshold. We studied the drug’s effect on the long-term cancer cell growth dynamics using different durations of prolonged mitotic arrest induced by the drug. Our numerical simulations suggest that at confluence and in the absence of the drug, quiescence is the long-term asymptotic behavior emerging from the cancer cell growth dynamics. This pattern is maintained in the presence of small increases in the average cell-cycle length. However, intermediate increases in cell-cycle length markedly decrease the total number of cells and can drive the cancer population to extinction. Intriguingly, a large “switch-on/switch-off” increase in the average cell-cycle length maintains an active cell population in the long term, with oscillating numbers of proliferative cells and a relatively constant quiescent cell number. PMID:28913178

Improvement of CFD Methods for Modeling Full Scale Circulating Fluidized Bed Combustion Systems

NASA Astrophysics Data System (ADS)

Shah, Srujal; Klajny, Marcin; Myöhänen, Kari; Hyppänen, Timo

With the currently available methods of computational fluid dynamics (CFD), the task of simulating full scale circulating fluidized bed combustors is very challenging. In order to simulate the complex fluidization process, the size of calculation cells should be small and the calculation should be transient with small time step size. For full scale systems, these requirements lead to very large meshes and very long calculation times, so that the simulation in practice is difficult. This study investigates the requirements of cell size and the time step size for accurate simulations, and the filtering effects caused by coarser mesh and longer time step. A modeling study of a full scale CFB furnace is presented and the model results are compared with experimental data.

Enhanced Sampling of Molecular Dynamics Simulations of a Polyalanine Octapeptide: Effects of the Periodic Boundary Conditions on Peptide Conformation.

PubMed

Kasahara, Kota; Sakuraba, Shun; Fukuda, Ikuo

2018-03-08

We investigate the problem of artifacts caused by the periodic boundary conditions (PBC) used in molecular simulation studies. Despite the long history of simulations with PBCs, the existence of measurable artifacts originating from PBCs applied to inherently nonperiodic physical systems remains controversial. Specifically, these artifacts appear as differences between simulations of the same system but with different simulation-cell sizes. Earlier studies have implied that, even in the simple case of a small model peptide in water, sampling inefficiency is a major obstacle to understanding these artifacts. In this study, we have resolved the sampling issue using the replica exchange molecular dynamics (REMD) enhanced-sampling method to explore PBC artifacts. Explicitly solvated zwitterionic polyalanine octapeptides with three different cubic-cells, having dimensions of L = 30, 40, and 50 Å, were investigated to elucidate the differences with 64 replica × 500 ns REMD simulations using the AMBER parm99SB force field. The differences among them were not large overall, and the results for the L = 30 and 40 Å simulations in the conformational free energy landscape were found to be very similar at room temperature. However, a small but statistically significant difference was seen for L = 50 Å. We observed that extended conformations were slightly overstabilized in the smaller systems. The origin of these artifacts is discussed by comparison to an electrostatic calculation method without PBCs.

The bacterial actin MreB rotates, and rotation depends on cell-wall assembly.

PubMed

van Teeffelen, Sven; Wang, Siyuan; Furchtgott, Leon; Huang, Kerwyn Casey; Wingreen, Ned S; Shaevitz, Joshua W; Gitai, Zemer

2011-09-20

Bacterial cells possess multiple cytoskeletal proteins involved in a wide range of cellular processes. These cytoskeletal proteins are dynamic, but the driving forces and cellular functions of these dynamics remain poorly understood. Eukaryotic cytoskeletal dynamics are often driven by motor proteins, but in bacteria no motors that drive cytoskeletal motion have been identified to date. Here, we quantitatively study the dynamics of the Escherichia coli actin homolog MreB, which is essential for the maintenance of rod-like cell shape in bacteria. We find that MreB rotates around the long axis of the cell in a persistent manner. Whereas previous studies have suggested that MreB dynamics are driven by its own polymerization, we show that MreB rotation does not depend on its own polymerization but rather requires the assembly of the peptidoglycan cell wall. The cell-wall synthesis machinery thus either constitutes a novel type of extracellular motor that exerts force on cytoplasmic MreB, or is indirectly required for an as-yet-unidentified motor. Biophysical simulations suggest that one function of MreB rotation is to ensure a uniform distribution of new peptidoglycan insertion sites, a necessary condition to maintain rod shape during growth. These findings both broaden the view of cytoskeletal motors and deepen our understanding of the physical basis of bacterial morphogenesis.

Chemical equilibria model of strontium-90 adsorption and transport in soil in response to dynamic alkaline conditions.

PubMed

Spalding, B P; Spalding, I R

2001-01-15

Strontium-90 is a major hazardous contaminant of radioactive wastewater and its processing sludges at many Department of Energy (DOE) facilities. In the past, such contaminated wastewater and sludge have been disposed in soil seepage pits, lagoons, or cribs often under highly perturbed alkaline conditions (pH > 12) where 90Sr solubility is low and its adsorption to surrounding soil is high. As natural weathering returns these soils to near-neutral or slightly acidic conditions, the adsorbed and precipitated calcium and magnesium phases, in which 90Sr is carried, change significantly in both nature and amounts. No comprehensive computational method has been formulated previously to quantitatively simulate the dynamics of 90Sr in the soil-groundwater environment under such dynamic and wide-ranging conditions. A computational code, the Hydrologic Utility Model for Demonstrating Integrated Nuclear Geochemical Environmental Responses (HUMDINGER), was composed to describe the changing equilibria of 90Sr in soil based on its causative chemical reactions including soil buffering, pH-dependent cation-exchange capacity, cation selectivity, and the precipitation/dissolution of calcium carbonate, calcium hydroxide, and magnesium hydroxide in response to leaching groundwater characteristics including pH, acid-neutralizing capacity, dissolved cations, and inorganic carbonate species. The code includes a simulation of one-dimensional transport of 90Sr through a soil column as a series of soil mixing cells where the equilibrium soluble output from one cell is applied to the next cell. Unamended soil leaching and highly alkaline soil treatments, including potassium hydroxide, sodium silicate, and sodium aluminate, were simulated and compared with experimental findings using large (10 kg) soil columns that were leached with 90Sr-contaminated groundwater after treatment. HUMDINGER's simulations were in good agreement with dynamic experimental observations of soil exchange capacity, exchangeable cations, total 90Sr, and pH values of layers within the soil columns and of column effluents.

Generalized image charge solvation model for electrostatic interactions in molecular dynamics simulations of aqueous solutions

PubMed Central

Deng, Shaozhong; Xue, Changfeng; Baumketner, Andriy; Jacobs, Donald; Cai, Wei

2013-01-01

This paper extends the image charge solvation model (ICSM) [J. Chem. Phys. 131, 154103 (2009)], a hybrid explicit/implicit method to treat electrostatic interactions in computer simulations of biomolecules formulated for spherical cavities, to prolate spheroidal and triaxial ellipsoidal cavities, designed to better accommodate non-spherical solutes in molecular dynamics (MD) simulations. In addition to the utilization of a general truncated octahedron as the MD simulation box, central to the proposed extension is an image approximation method to compute the reaction field for a point charge placed inside such a non-spherical cavity by using a single image charge located outside the cavity. The resulting generalized image charge solvation model (GICSM) is tested in simulations of liquid water, and the results are analyzed in comparison with those obtained from the ICSM simulations as a reference. We find that, for improved computational efficiency due to smaller simulation cells and consequently a less number of explicit solvent molecules, the generalized model can still faithfully reproduce known static and dynamic properties of liquid water at least for systems considered in the present paper, indicating its great potential to become an accurate but more efficient alternative to the ICSM when bio-macromolecules of irregular shapes are to be simulated. PMID:23913979

Comparing a discrete and continuum model of the intestinal crypt

PubMed Central

Murray, Philip J.; Walter, Alex; Fletcher, Alex G.; Edwards, Carina M.; Tindall, Marcus J.; Maini, Philip K.

2011-01-01

The integration of processes at different scales is a key problem in the modelling of cell populations. Owing to increased computational resources and the accumulation of data at the cellular and subcellular scales, the use of discrete, cell-level models, which are typically solved using numerical simulations, has become prominent. One of the merits of this approach is that important biological factors, such as cell heterogeneity and noise, can be easily incorporated. However, it can be difficult to efficiently draw generalisations from the simulation results, as, often, many simulation runs are required to investigate model behaviour in typically large parameter spaces. In some cases, discrete cell-level models can be coarse-grained, yielding continuum models whose analysis can lead to the development of insight into the underlying simulations. In this paper we apply such an approach to the case of a discrete model of cell dynamics in the intestinal crypt. An analysis of the resulting continuum model demonstrates that there is a limited region of parameter space within which steady-state (and hence biologically realistic) solutions exist. Continuum model predictions show good agreement with corresponding results from the underlying simulations and experimental data taken from murine intestinal crypts. PMID:21411869

Ensemble methods for stochastic networks with special reference to the biological clock of Neurospora crassa.

PubMed

Caranica, C; Al-Omari, A; Deng, Z; Griffith, J; Nilsen, R; Mao, L; Arnold, J; Schüttler, H-B

2018-01-01

A major challenge in systems biology is to infer the parameters of regulatory networks that operate in a noisy environment, such as in a single cell. In a stochastic regime it is hard to distinguish noise from the real signal and to infer the noise contribution to the dynamical behavior. When the genetic network displays oscillatory dynamics, it is even harder to infer the parameters that produce the oscillations. To address this issue we introduce a new estimation method built on a combination of stochastic simulations, mass action kinetics and ensemble network simulations in which we match the average periodogram and phase of the model to that of the data. The method is relatively fast (compared to Metropolis-Hastings Monte Carlo Methods), easy to parallelize, applicable to large oscillatory networks and large (~2000 cells) single cell expression data sets, and it quantifies the noise impact on the observed dynamics. Standard errors of estimated rate coefficients are typically two orders of magnitude smaller than the mean from single cell experiments with on the order of ~1000 cells. We also provide a method to assess the goodness of fit of the stochastic network using the Hilbert phase of single cells. An analysis of phase departures from the null model with no communication between cells is consistent with a hypothesis of Stochastic Resonance describing single cell oscillators. Stochastic Resonance provides a physical mechanism whereby intracellular noise plays a positive role in establishing oscillatory behavior, but may require model parameters, such as rate coefficients, that differ substantially from those extracted at the macroscopic level from measurements on populations of millions of communicating, synchronized cells.

Improving dynamic phytoplankton reserve-utilization models with an indirect proxy for internal nitrogen.

PubMed

Malerba, Martino E; Heimann, Kirsten; Connolly, Sean R

2016-09-07

Ecologists have often used indirect proxies to represent variables that are difficult or impossible to measure directly. In phytoplankton, the internal concentration of the most limiting nutrient in a cell determines its growth rate. However, directly measuring the concentration of nutrients within cells is inaccurate, expensive, destructive, and time-consuming, substantially impairing our ability to model growth rates in nutrient-limited phytoplankton populations. The red chlorophyll autofluorescence (hereafter "red fluorescence") signal emitted by a cell is highly correlated with nitrogen quota in nitrogen-limited phytoplankton species. The aim of this study was to evaluate the reliability of including flow cytometric red fluorescence as a proxy for internal nitrogen status to model phytoplankton growth rates. To this end, we used the classic Quota model and designed three approaches to calibrate its model parameters to data: where empirical observations on cell internal nitrogen quota were used to fit the model ("Nitrogen-Quota approach"), where quota dynamics were inferred only from changes in medium nutrient depletion and population density ("Virtual-Quota approach"), or where red fluorescence emission of a cell was used as an indirect proxy for its internal nitrogen quota ("Fluorescence-Quota approach"). Two separate analyses were carried out. In the first analysis, stochastic model simulations were parameterized from published empirical relationships and used to generate dynamics of phytoplankton communities reared under nitrogen-limited conditions. Quota models were fitted to the dynamics of each simulated species with the three different approaches and the performance of each model was compared. In the second analysis, we fit Quota models to laboratory time-series and we calculate the ability of each calibration approach to describe the observed trajectories of internal nitrogen quota in the culture. Results from both analyses concluded that the Fluorescence-Quota approach including per-cell red fluorescence as a proxy of internal nitrogen substantially improved the ability of Quota models to describe phytoplankton dynamics, while still accounting for the biologically important process of cell nitrogen storage. More broadly, many population models in ecology implicitly recognize the importance of accounting for storage mechanisms to describe the dynamics of individual organisms. Hence, the approach documented here with phytoplankton dynamics may also be useful for evaluating the potential of indirect proxies in other ecological systems. Copyright © 2016 Elsevier Ltd. All rights reserved.

Dynamic modeling for flow-activated chloride-selective membrane current in vascular endothelial cells.

PubMed

Qin, Kai-Rong; Xiang, Cheng; Cao, Ling-Ling

2011-10-01

In this paper, a dynamic model is proposed to quantify the relationship between fluid flow and Cl(-)-selective membrane current in vascular endothelial cells (VECs). It is assumed that the external shear stress would first induce channel deformation in VECs. This deformation could activate the Cl(-) channels on the membrane, thus allowing Cl(-) transport across the membrane. A modified Hodgkin-Huxley model is embedded into our dynamic system to describe the electrophysiological properties of the membrane, such as the Cl(-)-selective membrane current (I), voltage (V) and conductance. Three flow patterns, i. e., steady flow, oscillatory flow, and pulsatile flow, are applied in our simulation studies. When the extracellular Cl(-) concentration is constant, the I-V characteristics predicted by our dynamic model shows strong consistency with the experimental observations. It is also interesting to note that the Cl(-) currents under different flow patterns show some differences, indicating that VECs distinguish among and respond differently to different types of flows. When the extracellular Cl(-) concentration keeps constant or varies slowly with time (i.e. oscillates at 0.02 Hz), the convection and diffusion of Cl(-) in extracellular space can be ignored and the Cl(-) current is well captured by the modified Hodgkin-Huxley model alone. However, when the extracellular Cl(-) varies fast (i.e., oscillates at 0.2 Hz), the convection and diffusion effect should be considered because the Cl(-) current dynamics is different from the case where the convection-diffusion effect is simply ignored. The proposed dynamic model along with the simulation results could not only provide more insights into the flow-regulated electrophysiological behavior of the cell membrane but also help to reveal new findings in the electrophysiological experimental investigations of VECs in response to dynamic flow and biochemical stimuli.

Emergent Behaviors from a Cellular Automaton Model for Invasive Tumor Growth in Heterogeneous Microenvironments

PubMed Central

Jiao, Yang; Torquato, Salvatore

2011-01-01

Understanding tumor invasion and metastasis is of crucial importance for both fundamental cancer research and clinical practice. In vitro experiments have established that the invasive growth of malignant tumors is characterized by the dendritic invasive branches composed of chains of tumor cells emanating from the primary tumor mass. The preponderance of previous tumor simulations focused on non-invasive (or proliferative) growth. The formation of the invasive cell chains and their interactions with the primary tumor mass and host microenvironment are not well understood. Here, we present a novel cellular automaton (CA) model that enables one to efficiently simulate invasive tumor growth in a heterogeneous host microenvironment. By taking into account a variety of microscopic-scale tumor-host interactions, including the short-range mechanical interactions between tumor cells and tumor stroma, degradation of the extracellular matrix by the invasive cells and oxygen/nutrient gradient driven cell motions, our CA model predicts a rich spectrum of growth dynamics and emergent behaviors of invasive tumors. Besides robustly reproducing the salient features of dendritic invasive growth, such as least-resistance paths of cells and intrabranch homotype attraction, we also predict nontrivial coupling between the growth dynamics of the primary tumor mass and the invasive cells. In addition, we show that the properties of the host microenvironment can significantly affect tumor morphology and growth dynamics, emphasizing the importance of understanding the tumor-host interaction. The capability of our CA model suggests that sophisticated in silico tools could eventually be utilized in clinical situations to predict neoplastic progression and propose individualized optimal treatment strategies. PMID:22215996

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.

Molecular Modeling, Docking, Dynamics and simulation of Gefitinib and its derivatives with EGFR in Non-Small Cell Lung Cancer.

PubMed

Reddy, Pulakuntla Swetha; Lokhande, Kiran Bharat; Nagar, Shuchi; Reddy, Vaddi Damodara; Murthy, P Sushma; Swamy, K Venkateswara

2018-02-27

Gefitinib (lressa) is the most prescribed drug, highly effective to treat of non-small cell lung cancer; primarily it was considered targeted therapy is a kinase inhibitor. The non-small cell lung cancer caused by the mutation in the Epithelial Growth Factor Receptor (EGFR) gene, Iressa works by blocking the EGFR protein that helps the cancer cell growth. EGFR protein has lead to the development of anticancer therapeutics directed against EGFR inhibitor including Gefitinib for non-small cell lung cancer. To explore research on Gefitinib and its derivatives interaction with crystal structure EGFR to understand the better molecular insights interaction strategies. Molecular modeling of ligands (Gefitinib and its derivatives) was carried out by Avogadro software till atomic angle stable confirmation obtained. The partial charges for the ligands were assigned as per standard protocol for molecular docking. All docking simulations were performed with AutoDockVina. Virtual screening carried out based on binding energy and hydrogen bonding affinity. Molecular dynamics (MD) and Simulation EGFR was done using GROMACS 5.1.1 software to explore the interaction stability in a cell. The stable conformation for EGFR protein trajectories were captured at various time intervals 0-20ns. Few compounds screen based on high affinity as the inhibitor for EGFR may inhibit the cell cycle signalling in non-small cell lung cancer. These result suggested that a computer aided screening approach of a Gefitinib derivatives compounds with regard to their binding to EGFR for identifying novel drugs for the treatment of non-small cell lung cancer. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Dynamics of tissue topology during cancer invasion and metastasis

NASA Astrophysics Data System (ADS)

Munn, Lance L.

2013-12-01

During tumor progression, cancer cells mix with other cell populations including epithelial and endothelial cells. Although potentially important clinically as well as for our understanding of basic tumor biology, the process of mixing is largely a mystery. Furthermore, there is no rigorous, analytical measure available for quantifying the mixing of compartments within a tumor. I present here a mathematical model of tissue repair and tumor growth based on collective cell migration that simulates a wide range of observed tumor behaviors with correct tissue compartmentalization and connectivity. The resulting dynamics are analyzed in light of the Euler characteristic number (χ), which describes key topological features such as fragmentation, looping and cavities. The analysis predicts a number of regimes in which the cancer cells can encapsulate normal tissue, form a co-interdigitating mass, or become fragmented and encapsulated by endothelial or epithelial structures. Key processes that affect the topological changes are the production of provisional matrix in the tumor, and the migration of endothelial or epithelial cells on this matrix. Furthermore, the simulations predict that topological changes during tumor invasion into blood vessels may contribute to metastasis. The topological analysis outlined here could be useful for tumor diagnosis or monitoring response to therapy and would only require high resolution, 3D image data to resolve and track the various cell compartments.

An Agent-Based Model of a Hepatic Inflammatory Response to Salmonella: A Computational Study under a Large Set of Experimental Data.

PubMed

Shi, Zhenzhen; Chapes, Stephen K; Ben-Arieh, David; Wu, Chih-Hang

2016-01-01

We present an agent-based model (ABM) to simulate a hepatic inflammatory response (HIR) in a mouse infected by Salmonella that sometimes progressed to problematic proportions, known as "sepsis". Based on over 200 published studies, this ABM describes interactions among 21 cells or cytokines and incorporates 226 experimental data sets and/or data estimates from those reports to simulate a mouse HIR in silico. Our simulated results reproduced dynamic patterns of HIR reported in the literature. As shown in vivo, our model also demonstrated that sepsis was highly related to the initial Salmonella dose and the presence of components of the adaptive immune system. We determined that high mobility group box-1, C-reactive protein, and the interleukin-10: tumor necrosis factor-α ratio, and CD4+ T cell: CD8+ T cell ratio, all recognized as biomarkers during HIR, significantly correlated with outcomes of HIR. During therapy-directed silico simulations, our results demonstrated that anti-agent intervention impacted the survival rates of septic individuals in a time-dependent manner. By specifying the infected species, source of infection, and site of infection, this ABM enabled us to reproduce the kinetics of several essential indicators during a HIR, observe distinct dynamic patterns that are manifested during HIR, and allowed us to test proposed therapy-directed treatments. Although limitation still exists, this ABM is a step forward because it links underlying biological processes to computational simulation and was validated through a series of comparisons between the simulated results and experimental studies.

An Agent-Based Model of a Hepatic Inflammatory Response to Salmonella: A Computational Study under a Large Set of Experimental Data

PubMed Central

Chapes, Stephen K.; Ben-Arieh, David; Wu, Chih-Hang

2016-01-01

We present an agent-based model (ABM) to simulate a hepatic inflammatory response (HIR) in a mouse infected by Salmonella that sometimes progressed to problematic proportions, known as “sepsis”. Based on over 200 published studies, this ABM describes interactions among 21 cells or cytokines and incorporates 226 experimental data sets and/or data estimates from those reports to simulate a mouse HIR in silico. Our simulated results reproduced dynamic patterns of HIR reported in the literature. As shown in vivo, our model also demonstrated that sepsis was highly related to the initial Salmonella dose and the presence of components of the adaptive immune system. We determined that high mobility group box-1, C-reactive protein, and the interleukin-10: tumor necrosis factor-α ratio, and CD4+ T cell: CD8+ T cell ratio, all recognized as biomarkers during HIR, significantly correlated with outcomes of HIR. During therapy-directed silico simulations, our results demonstrated that anti-agent intervention impacted the survival rates of septic individuals in a time-dependent manner. By specifying the infected species, source of infection, and site of infection, this ABM enabled us to reproduce the kinetics of several essential indicators during a HIR, observe distinct dynamic patterns that are manifested during HIR, and allowed us to test proposed therapy-directed treatments. Although limitation still exists, this ABM is a step forward because it links underlying biological processes to computational simulation and was validated through a series of comparisons between the simulated results and experimental studies. PMID:27556404

GPU-enabled molecular dynamics simulations of ankyrin kinase complex

NASA Astrophysics Data System (ADS)

Gautam, Vertika; Chong, Wei Lim; Wisitponchai, Tanchanok; Nimmanpipug, Piyarat; Zain, Sharifuddin M.; Rahman, Noorsaadah Abd.; Tayapiwatana, Chatchai; Lee, Vannajan Sanghiran

2014-10-01

The ankyrin repeat (AR) protein can be used as a versatile scaffold for protein-protein interactions. It has been found that the heterotrimeric complex between integrin-linked kinase (ILK), PINCH, and parvin is an essential signaling platform, serving as a convergence point for integrin and growth-factor signaling and regulating cell adhesion, spreading, and migration. Using ILK-AR with high affinity for the PINCH1 as our model system, we explored a structure-based computational protocol to probe and characterize binding affinity hot spots at protein-protein interfaces. In this study, the long time scale dynamics simulations with GPU accelerated molecular dynamics (MD) simulations in AMBER12 have been performed to locate the hot spots of protein-protein interaction by the analysis of the Molecular Mechanics-Poisson-Boltzmann Surface Area/Generalized Born Solvent Area (MM-PBSA/GBSA) of the MD trajectories. Our calculations suggest good binding affinity of the complex and also the residues critical in the binding.

Edge Detection Based On the Characteristic of Primary Visual Cortex Cells

NASA Astrophysics Data System (ADS)

Zhu, M. M.; Xu, Y. L.; Ma, H. Q.

2018-01-01

Aiming at the problem that it is difficult to balance the accuracy of edge detection and anti-noise performance, and referring to the dynamic and static perceptions of the primary visual cortex (V1) cells, a V1 cell model is established to perform edge detection. A spatiotemporal filter is adopted to simulate the receptive field of V1 simple cells, the model V1 cell is obtained after integrating the responses of simple cells by half-wave rectification and normalization, Then the natural image edge is detected by using static perception of V1 cells. The simulation results show that, the V1 model can basically fit the biological data and has the universality of biology. What’s more, compared with other edge detection operators, the proposed model is more effective and has better robustness

Regulatory T cell effects in antitumor laser immunotherapy: a mathematical model and analysis

NASA Astrophysics Data System (ADS)

Dawkins, Bryan A.; Laverty, Sean M.

2016-03-01

Regulatory T cells (Tregs) have tremendous influence on treatment outcomes in patients receiving immunotherapy for cancerous tumors. We present a mathematical model incorporating the primary cellular and molecular components of antitumor laser immunotherapy. We explicitly model developmental classes of dendritic cells (DCs), cytotoxic T cells (CTLs), primary and metastatic tumor cells, and tumor antigen. Regulatory T cells have been shown to kill antigen presenting cells, to influence dendritic cell maturation and migration, to kill activated killer CTLs in the tumor microenvironment, and to influence CTL proliferation. Since Tregs affect explicitly modeled cells, but we do not explicitly model dynamics of Treg themselves, we use model parameters to analyze effects of Treg immunosuppressive activity. We will outline a systematic method for assigning clinical outcomes to model simulations and use this condition to associate simulated patient treatment outcome with Treg activity.

An equation-free probabilistic steady-state approximation: dynamic application to the stochastic simulation of biochemical reaction networks.

PubMed

Salis, Howard; Kaznessis, Yiannis N

2005-12-01

Stochastic chemical kinetics more accurately describes the dynamics of "small" chemical systems, such as biological cells. Many real systems contain dynamical stiffness, which causes the exact stochastic simulation algorithm or other kinetic Monte Carlo methods to spend the majority of their time executing frequently occurring reaction events. Previous methods have successfully applied a type of probabilistic steady-state approximation by deriving an evolution equation, such as the chemical master equation, for the relaxed fast dynamics and using the solution of that equation to determine the slow dynamics. However, because the solution of the chemical master equation is limited to small, carefully selected, or linear reaction networks, an alternate equation-free method would be highly useful. We present a probabilistic steady-state approximation that separates the time scales of an arbitrary reaction network, detects the convergence of a marginal distribution to a quasi-steady-state, directly samples the underlying distribution, and uses those samples to accurately predict the state of the system, including the effects of the slow dynamics, at future times. The numerical method produces an accurate solution of both the fast and slow reaction dynamics while, for stiff systems, reducing the computational time by orders of magnitude. The developed theory makes no approximations on the shape or form of the underlying steady-state distribution and only assumes that it is ergodic. We demonstrate the accuracy and efficiency of the method using multiple interesting examples, including a highly nonlinear protein-protein interaction network. The developed theory may be applied to any type of kinetic Monte Carlo simulation to more efficiently simulate dynamically stiff systems, including existing exact, approximate, or hybrid stochastic simulation techniques.

Computer simulations of the energy dissipation rate in a fluorescence-activated cell sorter: Implications to cells.

PubMed

Mollet, Mike; Godoy-Silva, Ruben; Berdugo, Claudia; Chalmers, Jeffrey J

2008-06-01

Fluorescence activated cell sorting, FACS, is a widely used method to sort subpopulations of cells to high purities. To achieve relatively high sorting speeds, FACS instruments operate by forcing suspended cells to flow in a single file line through a laser(s) beam(s). Subsequently, this flow stream breaks up into individual drops which can be charged and deflected into multiple collection streams. Previous work by Ma et al. (2002) and Mollet et al. (2007; Biotechnol Bioeng 98:772-788) indicates that subjecting cells to hydrodynamic forces consisting of both high extensional and shear components in micro-channels results in significant cell damage. Using the fluid dynamics software FLUENT, computer simulations of typical fluid flow through the nozzle of a BD FACSVantage indicate that hydrodynamic forces, quantified using the scalar parameter energy dissipation rate, are similar in the FACS nozzle to levels reported to create significant cell damage in micro-channels. Experimental studies in the FACSVantage, operated under the same conditions as the simulations confirmed significant cell damage in two cell lines, Chinese Hamster Ovary cells (CHO) and THP1, a human acute monocytic leukemia cell line.

A DISCRETE-EVENT SIMULATION APPROACH TO IDENTIFY RULES THAT GOVERN ARBOR REMODELING FOR BRANCHING CUTANEOUS AFFERENTS IN HAIRY SKIN

PubMed Central

Kang, Hyojung; Orlowsky, Rachel L.; Gerling, Gregory J.

2018-01-01

In mammals, touch is encoded by sensory receptors embedded in the skin. For one class of receptors in the mouse, the architecture of its Merkel cells, unmyelinated neurites, and heminodes follow particular renewal and remodeling trends over hair cycle stages from ages 4 to 10 weeks. As it is currently impossible to observe such trends across a single animal’s hair cycle, this work employs discrete event simulation to identify and evaluate policies of Merkel cell and heminode dynamics. Well matching the observed data, the results show that the baseline model replicates dynamic remodeling behaviors between stages of the hair cycle – based on particular addition and removal polices and estimated probabilities tied to constituent parts of Merkel cells, terminal branch neurites and heminodes. The analysis shows further that certain policies hold greater influence than others. This use of computation is a novel approach to understanding neuronal development. PMID:29527094

Intercalation of Li Ions into a Graphite Anode Material: Molecular Dynamics Simulations

NASA Astrophysics Data System (ADS)

Abou Hamad, Ibrahim; Novotny, Mark

2008-03-01

Large-scale molecular dynamics simulations of the anode half-cell of a lithium-ion battery are presented. The model system is composed of an anode represented by a stack of graphite sheets, an electrolyte of ethylene carbonate and propylene carbonate molecules, and lithium and hexafluorophosphate ions. The simulations are done in the NVT ensemble and at room temperature. One charging scheme explored is normal charging in which intercalation is enhanced by electric charges on the graphitic sheets. The second charging mechanism has an external applied oscillatory electric field of amplitude A and frequency f. The simulations were performed on 2.6 GHz Opteron processors, using 160 processors at a time. Our simulation results show an improvement in the intercalation time of the lithium ions for the second charging mechanism. The dependence of the intercalation time on A and f will be discussed.

Intermediate-band dynamics of quantum dots solar cell in concentrator photovoltaic modules

PubMed Central

Sogabe, Tomah; Shoji, Yasushi; Ohba, Mitsuyoshi; Yoshida, Katsuhisa; Tamaki, Ryo; Hong, Hwen-Fen; Wu, Chih-Hung; Kuo, Cherng-Tsong; Tomić, Stanko; Okada, Yoshitaka

2014-01-01

We report for the first time a successful fabrication and operation of an InAs/GaAs quantum dot based intermediate band solar cell concentrator photovoltaic (QD-IBSC-CPV) module to the IEC62108 standard with recorded power conversion efficiency of 15.3%. Combining the measured experimental results at Underwriters Laboratory (UL®) licensed testing laboratory with theoretical simulations, we confirmed that the operational characteristics of the QD-IBSC-CPV module are a consequence of the carrier dynamics via the intermediate-band at room temperature. PMID:24762433

Particle in cell simulation on plasma grating contrast enhancement induced by infrared laser pulse

NASA Astrophysics Data System (ADS)

Li, M.; Yuan, T.; Xu, Y. X.; Wang, J. X.; Luo, S. N.

2018-05-01

The dynamics of plasma grating contrast enhancement (PGCE) irradiated by an infrared laser pulse is investigated with one dimensional particle-in-cell simulation where field ionization and impact ionization are simultaneously considered for the first time. The numeric results show that the impact ionization dominates the PGCE process. Upon the interaction with the laser pulse, abundant free electrons are efficiently accelerated and subsequently triggered massive impact ionizations in the density ridges of the plasma grating for the higher local plasma energy density, which efficiently enhances the grating contrast. Besides the dynamic analysis of PGCE, we explore the parameter space of the incident infrared laser pulse to optimize the PGCE effect, which can provide useful guidance to experiments related to laser-plasma-grating interactions and may find applications in prolonging the duration of the plasma grating.

Intrinsic noise analysis and stochastic simulation on transforming growth factor beta signal pathway

NASA Astrophysics Data System (ADS)

Wang, Lu; Ouyang, Qi

2010-10-01

A typical biological cell lives in a small volume at room temperature; the noise effect on the cell signal transduction pathway may play an important role in its dynamics. Here, using the transforming growth factor-β signal transduction pathway as an example, we report our stochastic simulations of the dynamics of the pathway and introduce a linear noise approximation method to calculate the transient intrinsic noise of pathway components. We compare the numerical solutions of the linear noise approximation with the statistic results of chemical Langevin equations, and find that they are quantitatively in agreement with the other. When transforming growth factor-β dose decreases to a low level, the time evolution of noise fluctuation of nuclear Smad2—Smad4 complex indicates the abnormal enhancement in the transient signal activation process.

Molecular docking and dynamic simulation studies evidenced plausible immunotherapeutic anticancer property by Withaferin A targeting indoleamine 2,3-dioxygenase.

PubMed

Reddy, S V G; Reddy, K Thammi; Kumari, V Valli; Basha, Syed Hussain

2015-01-01

Indoleamine 2,3-dioxygenase (IDO) is emerging as an important new therapeutic drug target for the treatment of cancer characterized by pathological immune suppression. IDO catalyzes the rate-limiting step of tryptophan degradation along the kynurenine pathway. Reduction in local tryptophan concentration and the production of immunomodulatory tryptophan metabolites contribute to the immunosuppressive effects of IDO. Presence of IDO on dentritic cells in tumor-draining lymph nodes leading to the activation of T cells toward forming immunosuppressive microenvironment for the survival of tumor cells has confirmed the importance of IDO as a promising novel anticancer immunotherapy drug target. On the other hand, Withaferin A (WA) - active constituent of Withania Somnifera ayurvedic herb has shown to be having a wide range of targeted anticancer properties. In the present study conducted here is an attempt to explore the potential of WA in attenuating IDO for immunotherapeutic tumor arresting activity and to elucidate the underlying mode of action in a computational approach. Our docking and molecular dynamic simulation results predict high binding affinity of the ligand to the receptor with up to -11.51 kcal/mol of energy and 3.63 nM of IC50 value. Further, de novo molecular dynamic simulations predicted stable ligand interactions with critically important residues SER167; ARG231; LYS377, and heme moiety involved in IDO's activity. Conclusively, our results strongly suggest WA as a valuable small ligand molecule with strong binding affinity toward IDO.

Biomechanics and dynamics of red blood cells probed by optical tweezers and digital holographic microscopy

NASA Astrophysics Data System (ADS)

Cardenas, Nelson; Thomas, Pattrick; Yu, Lingfeng; Mohanty, Samarendra

2011-03-01

Red blood cells (RBC), with their unique viscoelastic properties, can undergo large deformations during interaction with fluid flow and migration through narrow capillaries. Both local and overall viscoelastic property is important for cellular function and change in these properties indicate diseased condition. Though biomechanics of the cells have been studied using variety of physical techniques (AFM, optically-trapped anchoring beads and microcapilary aspiration) in force regime 10pN, little is studied at low force regime <1pN. Such perturbations are not only hard to exercise on the cell membrane, but quantification of such deformations becomes extremely difficult. By application of low power optical tweezers directly on cell membrane, we could locally perturb discotic RBC along the axial direction, which was monitored dynamically by digital holographic microscopy-a real time, wide-field imaging method having nm axial resolution. The viscoelastic property of the RBC at low force regime was found to be significantly different from that of high-force regime. The results were found to be in good agreement with the simulation results obtained using finite element model of the axially-stretched RBC. The simulations and results of viscoelestic measurements will be presented.

Organization of the cytokeratin network in an epithelial cell.

PubMed

Portet, Stéphanie; Arino, Ovide; Vassy, Jany; Schoëvaërt, Damien

2003-08-07

The cytoskeleton is a dynamic three-dimensional structure mainly located in the cytoplasm. It is involved in many cell functions such as mechanical signal transduction and maintenance of cell integrity. Among the three cytoskeletal components, intermediate filaments (the cytokeratin in epithelial cells) are the best candidates for this mechanical role. A model of the establishment of the cytokeratin network of an epithelial cell is proposed to study the dependence of its structural organization on extracellular mechanical environment. To implicitly describe the latter and its effects on the intracellular domain, we use mechanically regulated protein synthesis. Our model is a hybrid of a partial differential equation of parabolic type, governing the evolution of the concentration of cytokeratin, and a set of stochastic differential equations describing the dynamics of filaments. Each filament is described by a stochastic differential equation that reflects both the local interactions with the environment and the non-local interactions via the past history of the filament. A three-dimensional simulation model is derived from this mathematical model. This simulation model is then used to obtain examples of cytokeratin network architectures under given mechanical conditions, and to study the influence of several parameters.

Micro-scale dynamic simulation of erythrocyte-platelet interaction in blood flow.

PubMed

AlMomani, T; Udaykumar, H S; Marshall, J S; Chandran, K B

2008-06-01

Platelet activation, adhesion, and aggregation on the blood vessel and implants result in the formation of mural thrombi. Platelet dynamics in blood flow is influenced by the far more numerous erythrocytes (RBCs). This is particularly the case in the smaller blood vessels (arterioles) and in constricted regions of blood flow (such as in valve leakage and hinge regions) where the dimensions of formed elements of blood become comparable with that of the flow geometry. In such regions, models to predict platelet motion, activation, aggregation and adhesion must account for platelet-RBC interactions. This paper studies platelet-RBC interactions in shear flows by performing simulations of micro-scale dynamics using a computational fluid dynamics (CFD) model. A level-set sharp-interface immersed boundary method is employed in the computations in which RBC and platelet boundaries are tracked on a two-dimensional Cartesian grid. The RBCs are assumed to have an elliptical shape and to deform elastically under fluid forces while the platelets are assumed to behave as rigid particles of circular shape. Forces and torques between colliding blood cells are modeled using an extension of the soft-sphere model for elliptical particles. RBCs and platelets are transported under the forces and torques induced by fluid flow and cell-cell and cell-platelet collisions. The simulations show that platelet migration toward the wall is enhanced with increasing hematocrit, in agreement with past experimental observations. This margination is seen to occur due to hydrodynamic forces rather than collisional forces or volumetric exclusion effects. The effect of fluid shear forces on the platelets increases exponentially as a function of hematocrit for the range of parameters covered in this study. The micro-scale analysis can be potentially employed to obtain a deterministic relationship between fluid forces and platelet activation and aggregation in blood flow past cardiovascular implants.

Structural Changes in Lipid Vesicles Generated by the Shock Blast Waves: Coarse-Grained Molecular Dynamics Simulation

DTIC Science & Technology

2013-11-01

duration, or shock-pulse shape. Used in this computational study is a coarse-grained model of the lipid vesicle as a simplified model of a cell...Figures iv List of Tables iv 1. Introduction 1 2. Model and Methods 3 3. Results and Discussion 6 3.1 Simulation of the Blast Waves with Low Peak...realistic detail but to focus on a simple model of the major constituent of a cell membrane, the phospholipid bilayer. In this work, we studied the

A multiscale computational approach to dissect early events in the Erb family receptor mediated activation, differential signaling, and relevance to oncogenic transformations.

PubMed

Liu, Yingting; Purvis, Jeremy; Shih, Andrew; Weinstein, Joshua; Agrawal, Neeraj; Radhakrishnan, Ravi

2007-06-01

We describe a hierarchical multiscale computational approach based on molecular dynamics simulations, free energy-based molecular docking simulations, deterministic network-based kinetic modeling, and hybrid discrete/continuum stochastic dynamics protocols to study the dimer-mediated receptor activation characteristics of the Erb family receptors, specifically the epidermal growth factor receptor (EGFR). Through these modeling approaches, we are able to extend the prior modeling of EGF-mediated signal transduction by considering specific EGFR tyrosine kinase (EGFRTK) docking interactions mediated by differential binding and phosphorylation of different C-terminal peptide tyrosines on the RTK tail. By modeling signal flows through branching pathways of the EGFRTK resolved on a molecular basis, we are able to transcribe the effects of molecular alterations in the receptor (e.g., mutant forms of the receptor) to differing kinetic behavior and downstream signaling response. Our molecular dynamics simulations show that the drug sensitizing mutation (L834R) of EGFR stabilizes the active conformation to make the system constitutively active. Docking simulations show preferential characteristics (for wildtype vs. mutant receptors) in inhibitor binding as well as preferential enhancement of phosphorylation of particular substrate tyrosines over others. We find that in comparison to the wildtype system, the L834R mutant RTK preferentially binds the inhibitor erlotinib, as well as preferentially phosphorylates the substrate tyrosine Y1068 but not Y1173. We predict that these molecular level changes result in preferential activation of the Akt signaling pathway in comparison to the Erk signaling pathway for cells with normal EGFR expression. For cells with EGFR over expression, the mutant over activates both Erk and Akt pathways, in comparison to wildtype. These results are consistent with qualitative experimental measurements reported in the literature. We discuss these consequences in light of how the network topology and signaling characteristics of altered (mutant) cell lines are shaped differently in relationship to native cell lines.

Cellular reprogramming dynamics follow a simple 1D reaction coordinate

NASA Astrophysics Data System (ADS)

Teja Pusuluri, Sai; Lang, Alex H.; Mehta, Pankaj; Castillo, Horacio E.

2018-01-01

Cellular reprogramming, the conversion of one cell type to another, induces global changes in gene expression involving thousands of genes, and understanding how cells globally alter their gene expression profile during reprogramming is an ongoing problem. Here we reanalyze time-course data on cellular reprogramming from differentiated cell types to induced pluripotent stem cells (iPSCs) and show that gene expression dynamics during reprogramming follow a simple 1D reaction coordinate. This reaction coordinate is independent of both the time it takes to reach the iPSC state as well as the details of the experimental protocol used. Using Monte-Carlo simulations, we show that such a reaction coordinate emerges from epigenetic landscape models where cellular reprogramming is viewed as a ‘barrier-crossing’ process between cell fates. Overall, our analysis and model suggest that gene expression dynamics during reprogramming follow a canonical trajectory consistent with the idea of an ‘optimal path’ in gene expression space for reprogramming.

Arnold Tongues in Cell Dynamics

NASA Astrophysics Data System (ADS)

Jensen, Mogens

In a recent work with Leo Kadanoff we studied the synchronization between an internal and an external frequency. One obtains a highly structured diagram with details that in essence are related to the difference between rational and irrational number. The synchronized regions appear as Arnold tongues that widen as the coupling between the frequencies increases. Such tongues have been observed in many physical systems, like in the Libchaber convective cell in the basement of the University of Chicago. In biological systems, where oscillators appear in in a broad variety, very little research on Arnold tongues has been performed. We discuss single cell oscillating dynamics triggered by an external cytokine signal. When this signal is overlaid by an oscillating variation, the two oscillators might couple leading to Arnold tongue diagram. When the tongues overlap, the cell dynamics can shift between the tongues eventually leading to a chaotic response. We quantify such switching in single cell experiments and in model systems based on Gillespie simulations. Kadanoff session.

Extended Magnetohydrodynamics with Embedded Particle-in-Cell Simulation of Ganymede's Magnetosphere

NASA Technical Reports Server (NTRS)

Toth, Gabor; Jia, Xianzhe; Markidis, Stefano; Peng, Ivy Bo; Chen, Yuxi; Daldorff, Lars K. S.; Tenishev, Valeriy M.; Borovikov, Dmitry; Haiducek, John D.; Gombosi, Tamas I.;

Molecular dynamics modelling of solidification in metals

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

Boercker, D.B.; Belak, J.; Glosli, J.

1997-12-31

Molecular dynamics modeling is used to study the solidification of metals at high pressure and temperature. Constant pressure MD is applied to a simulation cell initially filled with both solid and molten metal. The solid/liquid interface is tracked as a function of time, and the data are used to estimate growth rates of crystallites at high pressure and temperature in Ta and Mg.

High-Frequency Stimulation of Dorsal Column Axons: Potential Underlying Mechanism of Paresthesia-Free Neuropathic Pain Relief.

PubMed

Arle, Jeffrey E; Mei, Longzhi; Carlson, Kristen W; Shils, Jay L

2016-06-01

Spinal cord stimulation (SCS) treats neuropathic pain through retrograde stimulation of dorsal column axons and their inhibitory effects on wide dynamic range (WDR) neurons. Typical SCS uses frequencies from 50-100 Hz. Newer stimulation paradigms use high-frequency stimulation (HFS) up to 10 kHz and produce pain relief but without paresthesia. Our hypothesis is that HFS preferentially blocks larger diameter axons (12-15 µm) based on dynamics of ion channel gates and the electric potential gradient seen along the axon, resulting in inhibition of WDR cells without paresthesia. We input field potential values from a finite element model of SCS into an active axon model with ion channel subcomponents for fiber diameters 1-20 µm and simulated dynamics on a 0.001 msec time scale. Assuming some degree of wave rectification seen at the axon, action potential (AP) blockade occurs as hypothesized, preferentially in larger over smaller diameters with blockade in most medium and large diameters occurring between 4.5 and 10 kHz. Simulations show both ion channel gate and virtual anode dynamics are necessary. At clinical HFS frequencies and pulse widths, HFS preferentially blocks larger-diameter fibers and concomitantly recruits medium and smaller fibers. These effects are a result of interaction between ion gate dynamics and the "activating function" (AF) deriving from current distribution over the axon. The larger fibers that cause paresthesia in low-frequency simulation are blocked, while medium and smaller fibers are recruited, leading to paresthesia-free neuropathic pain relief by inhibiting WDR cells. © 2016 International Neuromodulation Society.

A novel grid-based mesoscopic model for evacuation dynamics

NASA Astrophysics Data System (ADS)

Shi, Meng; Lee, Eric Wai Ming; Ma, Yi

2018-05-01

This study presents a novel grid-based mesoscopic model for evacuation dynamics. In this model, the evacuation space is discretised into larger cells than those used in microscopic models. This approach directly computes the dynamic changes crowd densities in cells over the course of an evacuation. The density flow is driven by the density-speed correlation. The computation is faster than in traditional cellular automata evacuation models which determine density by computing the movements of each pedestrian. To demonstrate the feasibility of this model, we apply it to a series of practical scenarios and conduct a parameter sensitivity study of the effect of changes in time step δ. The simulation results show that within the valid range of δ, changing δ has only a minor impact on the simulation. The model also makes it possible to directly acquire key information such as bottleneck areas from a time-varied dynamic density map, even when a relatively large time step is adopted. We use the commercial software AnyLogic to evaluate the model. The result shows that the mesoscopic model is more efficient than the microscopic model and provides more in-situ details (e.g., pedestrian movement pattern) than the macroscopic models.

A Model for the Epigenetic Switch Linking Inflammation to Cell Transformation: Deterministic and Stochastic Approaches

PubMed Central

Gérard, Claude; Gonze, Didier; Lemaigre, Frédéric; Novák, Béla

2014-01-01

Recently, a molecular pathway linking inflammation to cell transformation has been discovered. This molecular pathway rests on a positive inflammatory feedback loop between NF-κB, Lin28, Let-7 microRNA and IL6, which leads to an epigenetic switch allowing cell transformation. A transient activation of an inflammatory signal, mediated by the oncoprotein Src, activates NF-κB, which elicits the expression of Lin28. Lin28 decreases the expression of Let-7 microRNA, which results in higher level of IL6 than achieved directly by NF-κB. In turn, IL6 can promote NF-κB activation. Finally, IL6 also elicits the synthesis of STAT3, which is a crucial activator for cell transformation. Here, we propose a computational model to account for the dynamical behavior of this positive inflammatory feedback loop. By means of a deterministic model, we show that an irreversible bistable switch between a transformed and a non-transformed state of the cell is at the core of the dynamical behavior of the positive feedback loop linking inflammation to cell transformation. The model indicates that inhibitors (tumor suppressors) or activators (oncogenes) of this positive feedback loop regulate the occurrence of the epigenetic switch by modulating the threshold of inflammatory signal (Src) needed to promote cell transformation. Both stochastic simulations and deterministic simulations of a heterogeneous cell population suggest that random fluctuations (due to molecular noise or cell-to-cell variability) are able to trigger cell transformation. Moreover, the model predicts that oncogenes/tumor suppressors respectively decrease/increase the robustness of the non-transformed state of the cell towards random fluctuations. Finally, the model accounts for the potential effect of competing endogenous RNAs, ceRNAs, on the dynamics of the epigenetic switch. Depending on their microRNA targets, the model predicts that ceRNAs could act as oncogenes or tumor suppressors by regulating the occurrence of cell transformation. PMID:24499937

Multiscale Hy3S: hybrid stochastic simulation for supercomputers.

PubMed

Salis, Howard; Sotiropoulos, Vassilios; Kaznessis, Yiannis N

2006-02-24

Stochastic simulation has become a useful tool to both study natural biological systems and design new synthetic ones. By capturing the intrinsic molecular fluctuations of "small" systems, these simulations produce a more accurate picture of single cell dynamics, including interesting phenomena missed by deterministic methods, such as noise-induced oscillations and transitions between stable states. However, the computational cost of the original stochastic simulation algorithm can be high, motivating the use of hybrid stochastic methods. Hybrid stochastic methods partition the system into multiple subsets and describe each subset as a different representation, such as a jump Markov, Poisson, continuous Markov, or deterministic process. By applying valid approximations and self-consistently merging disparate descriptions, a method can be considerably faster, while retaining accuracy. In this paper, we describe Hy3S, a collection of multiscale simulation programs. Building on our previous work on developing novel hybrid stochastic algorithms, we have created the Hy3S software package to enable scientists and engineers to both study and design extremely large well-mixed biological systems with many thousands of reactions and chemical species. We have added adaptive stochastic numerical integrators to permit the robust simulation of dynamically stiff biological systems. In addition, Hy3S has many useful features, including embarrassingly parallelized simulations with MPI; special discrete events, such as transcriptional and translation elongation and cell division; mid-simulation perturbations in both the number of molecules of species and reaction kinetic parameters; combinatorial variation of both initial conditions and kinetic parameters to enable sensitivity analysis; use of NetCDF optimized binary format to quickly read and write large datasets; and a simple graphical user interface, written in Matlab, to help users create biological systems and analyze data. We demonstrate the accuracy and efficiency of Hy3S with examples, including a large-scale system benchmark and a complex bistable biochemical network with positive feedback. The software itself is open-sourced under the GPL license and is modular, allowing users to modify it for their own purposes. Hy3S is a powerful suite of simulation programs for simulating the stochastic dynamics of networks of biochemical reactions. Its first public version enables computational biologists to more efficiently investigate the dynamics of realistic biological systems.

Immersed Boundary Simulations of Active Fluid Droplets

PubMed Central

Hawkins, Rhoda J.

2016-01-01

We present numerical simulations of active fluid droplets immersed in an external fluid in 2-dimensions using an Immersed Boundary method to simulate the fluid droplet interface as a Lagrangian mesh. We present results from two example systems, firstly an active isotropic fluid boundary consisting of particles that can bind and unbind from the interface and generate surface tension gradients through active contractility. Secondly, a droplet filled with an active polar fluid with homeotropic anchoring at the droplet interface. These two systems demonstrate spontaneous symmetry breaking and steady state dynamics resembling cell motility and division and show complex feedback mechanisms with minimal degrees of freedom. The simulations outlined here will be useful for quantifying the wide range of dynamics observable in these active systems and modelling the effects of confinement in a consistent and adaptable way. PMID:27606609

Improving the off-axis spatial resolution and dynamic range of the NIF X-ray streak cameras (invited).

PubMed

MacPhee, A G; Dymoke-Bradshaw, A K L; Hares, J D; Hassett, J; Hatch, B W; Meadowcroft, A L; Bell, P M; Bradley, D K; Datte, P S; Landen, O L; Palmer, N E; Piston, K W; Rekow, V V; Hilsabeck, T J; Kilkenny, J D

2016-11-01

We report simulations and experiments that demonstrate an increase in spatial resolution of the NIF core diagnostic x-ray streak cameras by at least a factor of two, especially off axis. A design was achieved by using a corrector electron optic to flatten the field curvature at the detector plane and corroborated by measurement. In addition, particle in cell simulations were performed to identify the regions in the streak camera that contribute the most to space charge blurring. These simulations provide a tool for convolving synthetic pre-shot spectra with the instrument function so signal levels can be set to maximize dynamic range for the relevant part of the streak record.

Modeling and 2-D discrete simulation of dislocation dynamics for plastic deformation of metal

NASA Astrophysics Data System (ADS)

Liu, Juan; Cui, Zhenshan; Ou, Hengan; Ruan, Liqun

2013-05-01

Two methods are employed in this paper to investigate the dislocation evolution during plastic deformation of metal. One method is dislocation dynamic simulation of two-dimensional discrete dislocation dynamics (2D-DDD), and the other is dislocation dynamics modeling by means of nonlinear analysis. As screw dislocation is prone to disappear by cross-slip, only edge dislocation is taken into account in simulation. First, an approach of 2D-DDD is used to graphically simulate and exhibit the collective motion of a large number of discrete dislocations. In the beginning, initial grains are generated in the simulation cells according to the mechanism of grain growth and the initial dislocation is randomly distributed in grains and relaxed under the internal stress. During the simulation process, the externally imposed stress, the long range stress contribution of all dislocations and the short range stress caused by the grain boundaries are calculated. Under the action of these forces, dislocations begin to glide, climb, multiply, annihilate and react with each other. Besides, thermal activation process is included. Through the simulation, the distribution of dislocation and the stress-strain curves can be obtained. On the other hand, based on the classic dislocation theory, the variation of the dislocation density with time is described by nonlinear differential equations. Finite difference method (FDM) is used to solve the built differential equations. The dislocation evolution at a constant strain rate is taken as an example to verify the rationality of the model.

A Stochastic Framework for Modeling the Population Dynamics of Convective Clouds

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

Hagos, Samson; Feng, Zhe; Plant, Robert S.

A stochastic prognostic framework for modeling the population dynamics of convective clouds and representing them in climate models is proposed. The approach used follows the non-equilibrium statistical mechanical approach through a master equation. The aim is to represent the evolution of the number of convective cells of a specific size and their associated cloud-base mass flux, given a large-scale forcing. In this framework, referred to as STOchastic framework for Modeling Population dynamics of convective clouds (STOMP), the evolution of convective cell size is predicted from three key characteristics: (i) the probability of growth, (ii) the probability of decay, and (iii)more » the cloud-base mass flux. STOMP models are constructed and evaluated against CPOL radar observations at Darwin and convection permitting model (CPM) simulations. Multiple models are constructed under various assumptions regarding these three key parameters and the realisms of these models are evaluated. It is shown that in a model where convective plumes prefer to aggregate spatially and mass flux is a non-linear function of convective cell area, mass flux manifests a recharge-discharge behavior under steady forcing. Such a model also produces observed behavior of convective cell populations and CPM simulated mass flux variability under diurnally varying forcing. Besides its use in developing understanding of convection processes and the controls on convective cell size distributions, this modeling framework is also designed to be capable of providing alternative, non-equilibrium, closure formulations for spectral mass flux parameterizations.« less

3D Spatially Resolved Models of the Intracellular Dynamics of the Hepatitis C Genome Replication Cycle

PubMed Central

Reiter, Sebastian; Grillo, Alfio; Herrmann, Eva; Wittum, Gabriel

2017-01-01

Mathematical models of virus dynamics have not previously acknowledged spatial resolution at the intracellular level despite substantial arguments that favor the consideration of intracellular spatial dependence. The replication of the hepatitis C virus (HCV) viral RNA (vRNA) occurs within special replication complexes formed from membranes derived from endoplasmatic reticulum (ER). These regions, termed membranous webs, are generated primarily through specific interactions between nonstructural virus-encoded proteins (NSPs) and host cellular factors. The NSPs are responsible for the replication of the vRNA and their movement is restricted to the ER surface. Therefore, in this study we developed fully spatio-temporal resolved models of the vRNA replication cycle of HCV. Our simulations are performed upon realistic reconstructed cell structures—namely the ER surface and the membranous webs—based on data derived from immunostained cells replicating HCV vRNA. We visualized 3D simulations that reproduced dynamics resulting from interplay of the different components of our models (vRNA, NSPs, and a host factor), and we present an evaluation of the concentrations for the components within different regions of the cell. Thus far, our model is restricted to an internal portion of a hepatocyte and is qualitative more than quantitative. For a quantitative adaption to complete cells, various additional parameters will have to be determined through further in vitro cell biology experiments, which can be stimulated by the results described in the present study. PMID:28973992

High Performance Simulations of Accretion Disk Dynamics and Jet Formations Around Kerr Black Holes

NASA Technical Reports Server (NTRS)

Nishikawa, Ken-Ichi; Mizuno, Yosuke; Watson, Michael

2007-01-01

We investigate jet formation in black-hole systems using 3-D General Relativistic Particle-In-Cell (GRPIC) and 3-D GRMHD simulations. GRPIC simulations, which allow charge separations in a collisionless plasma, do not need to invoke the frozen condition as in GRMHD simulations. 3-D GRPIC simulations show that jets are launched from Kerr black holes as in 3-D GRMHD simulations, but jet formation in the two cases may not be identical. Comparative study of black hole systems with GRPIC and GRMHD simulations with the inclusion of radiate transfer will further clarify the mechanisms that drive the evolution of disk-jet systems.

Transient responses of phosphoric acid fuel cell power plant system. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Lu, Cheng-Yi

1983-01-01

An analytical and computerized study of the steady state and transient response of a phosphoric acid fuel cell (PAFC) system was completed. Parametric studies and sensitivity analyses of the PAFC system's operation were accomplished. Four non-linear dynamic models of the fuel cell stack, reformer, shift converters, and heat exchangers were developed based on nonhomogeneous non-linear partial differential equations, which include the material, component, energy balance, and electrochemical kinetic features. Due to a lack of experimental data for the dynamic response of the components only the steady state results were compared with data from other sources, indicating reasonably good agreement. A steady state simulation of the entire system was developed using, nonlinear ordinary differential equations. The finite difference method and trial-and-error procedures were used to obtain a solution. Using the model, a PAFC system, that was developed under NASA Grant, NCC3-17, was improved through the optimization of the heat exchanger network. Three types of cooling configurations for cell plates were evaluated to obtain the best current density and temperature distributions. The steady state solutions were used as the initial conditions in the dynamic model. The transient response of a simplified PAFC system, which included all of the major components, subjected to a load change was obtained. Due to the length of the computation time for the transient response calculations, analysis on a real-time computer was not possible. A simulation of the real-time calculations was developed on a batch type computer. The transient response characteristics are needed for the optimization of the design and control of the whole PAFC system. All of the models, procedures and simulations were programmed in Fortran and run on IBM 370 computers at Cleveland State University and the NASA Lewis Research Center.

Spontaneous Athermal Cross-Slip Nucleation at Screw Dislocation Intersections in FCC Metals and L1(2) Intermetallics Investigated via Atomistic Simulations

DTIC Science & Technology

2013-01-01

LAMMPS [12], developed at Sandia National Labora- tory. The simulation cell is a rectangular parallelepiped having the x-axis oriented along the [1 1 0...cross-slip during deformation. Acknowledgements The authors acknowledge use of the 3d molecular dynamics code, LAMMPS , which was developed at Sandia

Spin glass model for cell reprogramming

NASA Astrophysics Data System (ADS)

Pusuluri, Sai Teja; Castillo, Horacio E.

2014-03-01

Recent experiments show that differentiated cells can be reprogrammed to become pluripotent stem cells. The possible cell fates can be modeled as attractors in a dynamical system, the ``epigenetic landscape.'' Both cellular differentiation and reprogramming can be described in the landscape picture as motion from one attractor state to another attractor state. We use a simple model based on spin glass theory that can construct a simulated epigenetic landscape starting from the experimental genomic data. We modify the model to incorporate experimental reprogramming protocols. Our simulations successfully reproduce several reprogramming experiments. We probe the robustness of the results against random changes in the model, explore the importance of asymmetric interactions between transcription factors and study the importance of histone modification errors in reprogramming.

Self-consistent simulation of high-frequency driven plasma sheaths

NASA Astrophysics Data System (ADS)

Shihab, Mohammed; Eremin, Denis; Mussenbrock, Thomas; Brinkmann, Ralf

2011-10-01

Low pressure capacitively coupled plasmas are widely used in plasma processing and microelectronics industry. Understanding the dynamics of the boundary sheath is a fundamental problem. It controls the energy and angular distribution of ions bombarding the electrode, which in turn affects the surface reaction rate and the profile of microscopic features. In this contribution, we investigate the dynamics of plasma boundary sheaths by means of a kinetic self-consistent model, which is able to resolve the ion dynamics. Asymmetric sheath dynamics is observed for the intermediate RF regime, i.e., in the regime where the ion plasma frequency is equal to the driving frequency. The ion inertia causes an additional phase difference between the expansion and the contraction phase of the plasma sheath and an asymmetry for the ion energy distribution bimodal shape. A comparison with experimental results and particle in cell simulations is performed. Low pressure capacitively coupled plasmas are widely used in plasma processing and microelectronics industry. Understanding the dynamics of the boundary sheath is a fundamental problem. It controls the energy and angular distribution of ions bombarding the electrode, which in turn affects the surface reaction rate and the profile of microscopic features. In this contribution, we investigate the dynamics of plasma boundary sheaths by means of a kinetic self-consistent model, which is able to resolve the ion dynamics. Asymmetric sheath dynamics is observed for the intermediate RF regime, i.e., in the regime where the ion plasma frequency is equal to the driving frequency. The ion inertia causes an additional phase difference between the expansion and the contraction phase of the plasma sheath and an asymmetry for the ion energy distribution bimodal shape. A comparison with experimental results and particle in cell simulations is performed. The financial support from the Federal Ministry of Education and Research within the frame of the project ``Plasma-Technology-Grid'' and the support of the DFG via the collaborative research center SFB-TR87 is gratefully acknowledged.

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.

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.

Simulation of nanopowder compaction in terms of granular dynamics

NASA Astrophysics Data System (ADS)

Boltachev, G. Sh.; Volkov, N. B.

2011-07-01

The uniaxial compaction of nanopowders is simulated using the granular dynamics in the 2D geometry. The initial arrangement of particles is represented by (i) a layer of particles executing Brownian motion (isotropic structures) and (ii) particles falling in the gravity field (anisotropic structures). The influence of size effects and the size of a model cell on the properties of the structures are studied. The compaction of the model cell is simulated with regard to Hertz elastic forces between particles, Cattaneo-Mindlin-Deresiewicz shear friction forces, and van der Waals-Hamaker dispersion forces of attraction. Computation is performed for monodisperse powders with particle sizes ranging from 10 to 400 nm and for "cohesionless" powder, in which attractive forces are absent. It is shown that taking into account dispersion forces makes it possible to simulate the size effect in the nanopowder compaction: the compressibility of the nanopowder drops as the particles get finer. The mean coordination number and the axial and lateral pressures in the powder systems are found, and the effect of the density and isotropy of the initial structure on the compressibility is analyzed. The applicability of well-known Rumpf's formula for the size effect is discussed.

Blood-plasma separation in Y-shaped bifurcating microfluidic channels: A dissipative particle dynamics simulation study

PubMed Central

Li, Xuejin; Popel, Aleksander S.; Karniadakis, George Em

2012-01-01

The motion of a suspension of red blood cells (RBCs) flowing in a Y-shaped bifurcating microfluidic channel is investigated using a validated low-dimensional RBC (LD-RBC) model based on dissipative particle dynamics (DPD). Specifically, the RBC is represented as a closed torus-like ring of ten colloidal particles, which leads to efficient simulations of blood flow in microcirculation over a wide range of hematocrits. Adaptive no-slip wall boundary conditions were implemented to model hydrodynamic flow within a specific wall structure of diverging 3D microfluidic channels, paying attention to controlling density fluctuations. Plasma skimming and the all-or-nothing phenomenon of RBCs in a bifurcating microfluidic channel have been investigated in our simulations for healthy and diseased blood, including the size of cell-free layer on the daughter branches. The feed hematocrit level in the parent channel has considerable influence on blood-plasma separation. Compared to the blood-plasma separation efficiencies of healthy RBCs, malaria-infected stiff RBCs (iRBCs) have a tendency to travel into the low flowrate daughter branch because of their different initial distribution in the parent channel. Our simulation results are consistent with previously published experimental results and theoretical predictions. PMID:22476709

SunLine Expands Horizons with Fuel Cell Bus Demo

DOT National Transportation Integrated Search

2006-05-01

The primary objective of this project is to develop multiple simulation Testbeds/transportation models to evaluate the impacts of DMA connected vehicle applications and the active and dynamic transportation management (ATDM) strategies. The outputs (...

Dispersing Zwitterions into Comb Polymers for Nonviral Transfection: Experiments and Molecular Simulation.

PubMed

Ghobadi, Ahmadreza F; Letteri, Rachel; Parelkar, Sangram S; Zhao, Yue; Chan-Seng, Delphine; Emrick, Todd; Jayaraman, Arthi

2016-02-08

Polymer-based gene delivery vehicles benefit from the presence of hydrophilic groups that mitigate the inherent toxicity of polycations and that provide tunable polymer-DNA binding strength and stable complexes (polyplexes). However, hydrophilic groups screen charge, and as such can reduce cell uptake and transfection efficiency. We report the effect of embedding zwitterionic sulfobetaine (SB) groups in cationic comb polymers, using a combination of experiments and molecular simulations. Ring-opening metathesis polymerization (ROMP) produced comb polymers with tetralysine (K4) and SB pendent groups. Dynamic light scattering, zeta potential measurements, and fluorescence-based experiments, together with coarse-grained molecular dynamics simulations, described the effect of SB groups on the size, shape, surface charge, composition, and DNA binding strength of polyplexes formed using these comb polymers. Experiments and simulations showed that increasing SB composition in the comb polymers decreased polymer-DNA binding strength, while simulations indicated that the SB groups distributed throughout the polyplex. This allows polyplexes to maintain a positive surface charge and provide high levels of gene expression in live cells. Notably, comb polymers with nearly 50 mol % SB form polyplexes that exhibit positive surface charge similarly as polyplexes formed from purely cationic comb polymers, indicating the ability to introduce an appreciable amount of SB functionality without screening surface charge. This integrated simulation-experimental study demonstrates the effectiveness of incorporating zwitterions in polyplexes, while guiding the design of new and effective gene delivery vectors.

20170312 - In Silico Dynamics: computer simulation in a ...

EPA Pesticide Factsheets

Abstract: Utilizing cell biological information to predict higher order biological processes is a significant challenge in predictive toxicology. This is especially true for highly dynamical systems such as the embryo where morphogenesis, growth and differentiation require precisely orchestrated interactions between diverse cell populations. In patterning the embryo, genetic signals setup spatial information that cells then translate into a coordinated biological response. This can be modeled as ‘biowiring diagrams’ representing genetic signals and responses. Because the hallmark of multicellular organization resides in the ability of cells to interact with one another via well-conserved signaling pathways, multiscale computational (in silico) models that enable these interactions provide a platform to translate cellular-molecular lesions perturbations into higher order predictions. Just as ‘the Cell’ is the fundamental unit of biology so too should it be the computational unit (‘Agent’) for modeling embryogenesis. As such, we constructed multicellular agent-based models (ABM) with ‘CompuCell3D’ (www.compucell3d.org) to simulate kinematics of complex cell signaling networks and enable critical tissue events for use in predictive toxicology. Seeding the ABMs with HTS/HCS data from ToxCast demonstrated the potential to predict, quantitatively, the higher order impacts of chemical disruption at the cellular or bioche

In Silico Dynamics: computer simulation in a Virtual Embryo ...

EPA Pesticide Factsheets

Abstract: Utilizing cell biological information to predict higher order biological processes is a significant challenge in predictive toxicology. This is especially true for highly dynamical systems such as the embryo where morphogenesis, growth and differentiation require precisely orchestrated interactions between diverse cell populations. In patterning the embryo, genetic signals setup spatial information that cells then translate into a coordinated biological response. This can be modeled as ‘biowiring diagrams’ representing genetic signals and responses. Because the hallmark of multicellular organization resides in the ability of cells to interact with one another via well-conserved signaling pathways, multiscale computational (in silico) models that enable these interactions provide a platform to translate cellular-molecular lesions perturbations into higher order predictions. Just as ‘the Cell’ is the fundamental unit of biology so too should it be the computational unit (‘Agent’) for modeling embryogenesis. As such, we constructed multicellular agent-based models (ABM) with ‘CompuCell3D’ (www.compucell3d.org) to simulate kinematics of complex cell signaling networks and enable critical tissue events for use in predictive toxicology. Seeding the ABMs with HTS/HCS data from ToxCast demonstrated the potential to predict, quantitatively, the higher order impacts of chemical disruption at the cellular or biochemical level. This is demonstrate

Reduced Osteogenesis of Human Osteogenic Precursors' Cells Cultured in the Random Positioning Machine

NASA Astrophysics Data System (ADS)

Gershovich, J. G.; Buravkova, L. B.

2008-06-01

Recent studies have shown that simulated microgravity (SMG) results in altered proliferation and differentiation not only osteoblasts but also affects on osteogenic capacity of mesenchymal stem cells (MSCs) from various sources. For present study we used system that simulates effects of microgravity produced by the Random Positioning Machine (RPM). Cultured MCSs from human bone marrow and human osteoblasts (OBs) were exposed to SMG at RPM for 10-40 days. Induced osteogenesis of these progenitor cells was compared with the appropriate static (1g) and dynamic (horizontal shaker) controls. Clinorotated OBs and MSCs showed proliferation rate lower than static and dynamic control groups of cells in the early terms of SMG. Significant reduction of ALP activity was detected after 10 days of clinorotation of MSCs. There was no such dramatic difference in ALP activity of MSCs derived cells between SMG and control groups after 20 days of clinorotation but the expression of ALP was still reduced. However, virtually no matrix mineralization was found in OBs cultured under SMG conditions in the presence of differentiation stimuli. The similar effect was observed when we assayed matrix calcification of MSCs derived cultures. Thus, our results confirm low gravity mediated reduction of osteogenesis of different osteogenic precursors' cells and can clarify the mechanisms of bone loss during spaceflight.

DynaMiTES - A dynamic cell culture platform for in vitro drug testing PART 1 - Engineering of microfluidic system and technical simulations.

PubMed

Mattern, Kai; Beißner, Nicole; Reichl, Stephan; Dietzel, Andreas

2018-05-01

Conventional safety and efficacy test models, such as animal experiments or static in vitro cell culture models, can often not reliably predict the most promising drug candidates. Therefore, a novel microfluidic cell culture platform, called Dynamic Micro Tissue Engineering System (DynaMiTES), was designed to allow online analysis of drugs permeating through barrier forming tissues under dynamic conditions combined with monitoring of the transepithelial electrical resistance (TEER) by electrodes optimized for homogeneous current distribution. A variety of pre-cultivated cell culture inserts can be integrated and exposed to well controlled dynamic micro flow conditions, resulting in a tightly regulated exposure of the cells to tested drugs, drug formulations and shear forces. With these qualities, the new system can provide more relevant information compared to static measurements. As a first in vitro model, a three-dimensional hemicornea construct consisting of human keratocytes (HCK-Ca) and epithelial cells (HCE-T) was successfully tested in the DynaMiTES. Thereby, we were able to demonstrate the functionality and cell compatibility of this new organ on chip test platform. The modular design of the DynaMiTES allows fast adaptation suitable for the investigation of drug permeation through other important cellular barriers. Copyright © 2017. Published by Elsevier B.V.

Performance of the Cell processor for biomolecular simulations

NASA Astrophysics Data System (ADS)

De Fabritiis, G.

2007-06-01

The new Cell processor represents a turning point for computing intensive applications. Here, I show that for molecular dynamics it is possible to reach an impressive sustained performance in excess of 30 Gflops with a peak of 45 Gflops for the non-bonded force calculations, over one order of magnitude faster than a single core standard processor.

Flower Development as an Interplay between Dynamical Physical Fields and Genetic Networks

PubMed Central

Barrio, Rafael Ángel; Hernández-Machado, Aurora; Varea, C.; Romero-Arias, José Roberto; Álvarez-Buylla, Elena

2010-01-01

In this paper we propose a model to describe the mechanisms by which undifferentiated cells attain gene configurations underlying cell fate determination during morphogenesis. Despite the complicated mechanisms that surely intervene in this process, it is clear that the fundamental fact is that cells obtain spatial and temporal information that bias their destiny. Our main hypothesis assumes that there is at least one macroscopic field that breaks the symmetry of space at a given time. This field provides the information required for the process of cell differentiation to occur by being dynamically coupled to a signal transduction mechanism that, in turn, acts directly upon the gene regulatory network (GRN) underlying cell-fate decisions within cells. We illustrate and test our proposal with a GRN model grounded on experimental data for cell fate specification during organ formation in early Arabidopsis thaliana flower development. We show that our model is able to recover the multigene configurations characteristic of sepal, petal, stamen and carpel primordial cells arranged in concentric rings, in a similar pattern to that observed during actual floral organ determination. Such pattern is robust to alterations of the model parameters and simulated failures predict altered spatio-temporal patterns that mimic those described for several mutants. Furthermore, simulated alterations in the physical fields predict a pattern equivalent to that found in Lacandonia schismatica, the only flowering species with central stamens surrounded by carpels. PMID:21048956

Flower development as an interplay between dynamical physical fields and genetic networks.

PubMed

Barrio, Rafael Ángel; Hernández-Machado, Aurora; Varea, C; Romero-Arias, José Roberto; Alvarez-Buylla, Elena

2010-10-27

In this paper we propose a model to describe the mechanisms by which undifferentiated cells attain gene configurations underlying cell fate determination during morphogenesis. Despite the complicated mechanisms that surely intervene in this process, it is clear that the fundamental fact is that cells obtain spatial and temporal information that bias their destiny. Our main hypothesis assumes that there is at least one macroscopic field that breaks the symmetry of space at a given time. This field provides the information required for the process of cell differentiation to occur by being dynamically coupled to a signal transduction mechanism that, in turn, acts directly upon the gene regulatory network (GRN) underlying cell-fate decisions within cells. We illustrate and test our proposal with a GRN model grounded on experimental data for cell fate specification during organ formation in early Arabidopsis thaliana flower development. We show that our model is able to recover the multigene configurations characteristic of sepal, petal, stamen and carpel primordial cells arranged in concentric rings, in a similar pattern to that observed during actual floral organ determination. Such pattern is robust to alterations of the model parameters and simulated failures predict altered spatio-temporal patterns that mimic those described for several mutants. Furthermore, simulated alterations in the physical fields predict a pattern equivalent to that found in Lacandonia schismatica, the only flowering species with central stamens surrounded by carpels.

Modeling the Epithelial Morphogenesis of Germ Band Retraction in Three Dimensions

NASA Astrophysics Data System (ADS)

McCleery, W. Tyler; Veldhuis, Jim; Brodland, G. Wayne; Crews, Sarah M.; Hutson, M. Shane

2015-03-01

Embryogenesis of higher-order organisms is driven by an intricate coordination of cellular mechanics. Mechanical analysis of certain developmental events, e.g., dorsal closure in the fruit fly D. melanogaster, has been sufficiently described using two-dimensional models. Here, we present a three-dimensional modeling technique to investigate germ band retraction (GBR) - a whole-embryo, irreducibly 3D morphogenetic event. At the start of GBR, the epithelial tissue known as the germ band is initially wrapped around the posterior end of an ellipsoidal fly embryo. This tissue then retracts as an adjacent epithelial tissue, the amnioserosa, simultaneously contracts. We hypothesize that proper GBR requires maintenance of cell-cell connectivity in the amnioserosa, as well as both cell and tissue topology on the embryo's ellipsoidal surface. The exact interfacial tensions are less important. We test the dynamic interactions between these two tissues on a 3D ellipsoidal last. To speed simulation run times and focus on the relevant tissues, epithelial cells are defined as polygons constrained to lie on the surface of the ellipsoidal last. These cells have adjustable parameters such as edge tensions and cell pressures. Tissue movements are simulated by balancing these dynamic cell-level forces with viscous resistance and allowing cells to exchange neighbors. This modeling approach helps elucidate the multicellular stress fields in normal and aberrant development, providing deeper insight into the mechanical interdependence of developing tissues.

Direct Numerical Simulation of Cell Printing

NASA Astrophysics Data System (ADS)

Qiao, Rui; He, Ping

2010-11-01

Structural cell printing, i.e., printing three dimensional (3D) structures of cells held in a tissue matrix, is gaining significant attention in the biomedical community. The key idea is to use desktop printer or similar devices to print cells into 3D patterns with a resolution comparable to the size of mammalian cells, similar to that in living organs. Achieving such a resolution in vitro can lead to breakthroughs in areas such as organ transplantation and understanding of cell-cell interactions in truly 3D spaces. Although the feasibility of cell printing has been demonstrated in the recent years, the printing resolution and cell viability remain to be improved. In this work, we investigate one of the unit operations in cell printing, namely, the impact of a cell-laden droplet into a pool of highly viscous liquids using direct numerical simulations. The dynamics of droplet impact (e.g., crater formation and droplet spreading and penetration) and the evolution of cell shape and internal stress are quantified in details.

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.

Effects of stiffness and volume on the transit time of an erythrocyte through a slit.

PubMed

Salehyar, Sara; Zhu, Qiang

2017-06-01

By using a fully coupled fluid-cell interaction model, we numerically simulate the dynamic process of a red blood cell passing through a slit driven by an incoming flow. The model is achieved by combining a multiscale model of the composite cell membrane with a boundary element fluid dynamics model based on the Stokes flow assumption. Our concentration is on the correlation between the transit time (the time it takes to finish the whole translocation process) and different conditions (flow speed, cell orientation, cell stiffness, cell volume, etc.) that are involved. According to the numerical prediction (with some exceptions), the transit time rises as the cell is stiffened. It is also highly sensitive to volume increase inside the cell. In general, even slightly swollen cells (i.e., the internal volume is increased while the surface area of the cell kept unchanged) travel dramatically slower through the slit. For these cells, there is also an increased chance of blockage.

Using experimental human influenza infections to validate a viral dynamic model and the implications for prediction.

PubMed

Chen, S C; You, S H; Liu, C Y; Chio, C P; Liao, C M

2012-09-01

The aim of this work was to use experimental infection data of human influenza to assess a simple viral dynamics model in epithelial cells and better understand the underlying complex factors governing the infection process. The developed study model expands on previous reports of a target cell-limited model with delayed virus production. Data from 10 published experimental infection studies of human influenza was used to validate the model. Our results elucidate, mechanistically, the associations between epithelial cells, human immune responses, and viral titres and were supported by the experimental infection data. We report that the maximum total number of free virions following infection is 10(3)-fold higher than the initial introduced titre. Our results indicated that the infection rates of unprotected epithelial cells probably play an important role in affecting viral dynamics. By simulating an advanced model of viral dynamics and applying it to experimental infection data of human influenza, we obtained important estimates of the infection rate. This work provides epidemiologically meaningful results, meriting further efforts to understand the causes and consequences of influenza A infection.

Application of two-dimensional NMR spectroscopy and molecular dynamics simulations to the conformational analysis of oligosaccharides corresponding to the cell-wall polysaccharide of Streptococcus group A.

PubMed

Kreis, U C; Varma, V; Pinto, B M

1995-06-01

This paper describes the use of a protocol for conformational analysis of oligosaccharide structures related to the cell-wall polysaccharide of Streptococcus group A. The polysaccharide features a branched structure with an L-rhamnopyranose (Rhap) backbone consisting of alternating alpha-(1-->2) and alpha-(1-->3) links and D-N-acetylglucosamine (GlcpNAc) residues beta-(1-->3)-connected to alternating rhamnose rings: [formula: see text] Oligomers consisting of three to six residues have been synthesized and nuclear magnetic resonance (NMR) assignments have been made. The protocol for conformational analysis of the solution structure of these oligosaccharides involves experimental and theoretical methods. Two-dimensional NMR spectroscopy methods (TOCSY, ROESY and NOESY) are utilized to obtain chemical shift data and proton-proton distances. These distances are used as constraints in 100 ps molecular dynamics simulations in water using QUANTA and CHARMm. In addition, the dynamics simulations are performed without constraints. ROE build-up curves are computed from the averaged structures of the molecular dynamics simulations using the CROSREL program and compared with the experimental curves. Thus, a refinement of the initial structure may be obtained. The alpha-(1-->2) and the beta-(1-->3) links are unambiguously defined by the observed ROE cross peaks between the A-B',A'-B and C-B,C'-B' residues, respectively. The branch-point of the trisaccharide CBA' is conformationally well-defined. Assignment of the conformation of the B-A linkage (alpha-(1-->3)) was problematic due to TOCSY relay, but could be solved by NOESY and T-ROESY techniques. A conformational model for the polysaccharide is proposed.

The state diagram for cell adhesion under flow: leukocyte rolling and firm adhesion.

PubMed

Chang, K C; Tees, D F; Hammer, D A

2000-10-10

Leukocyte adhesion under flow in the microvasculature is mediated by binding between cell surface receptors and complementary ligands expressed on the surface of the endothelium. Leukocytes adhere to endothelium in a two-step mechanism: rolling (primarily mediated by selectins) followed by firm adhesion (primarily mediated by integrins). Using a computational method called "Adhesive Dynamics," we have simulated the adhesion of a cell to a surface in flow, and elucidated the relationship between receptor-ligand functional properties and the dynamics of adhesion. We express this relationship in a state diagram, a one-to-one map between the biophysical properties of adhesion molecules and various adhesive behaviors. Behaviors that are observed in simulations include firm adhesion, transient adhesion (rolling), and no adhesion. We varied the dissociative properties, association rate, bond elasticity, and shear rate and found that the unstressed dissociation rate, k(r)(o), and the bond interaction length, gamma, are the most important molecular properties controlling the dynamics of adhesion. Experimental k(r)(o) and gamma values from the literature for molecules that are known to mediate rolling adhesion fall within the rolling region of the state diagram. We explain why L-selectin-mediated rolling, which has faster k(r)(o) than other selectins, is accompanied by a smaller value for gamma. We also show how changes in association rate, shear rate, and bond elasticity alter the dynamics of adhesion. The state diagram (which must be mapped for each receptor-ligand system) presents a concise and comprehensive means of understanding the relationship between bond functional properties and the dynamics of adhesion mediated by receptor-ligand bonds.

The bacterial actin MreB rotates, and rotation depends on cell-wall assembly

PubMed Central

van Teeffelen, Sven; Wang, Siyuan; Furchtgott, Leon; Huang, Kerwyn Casey; Wingreen, Ned S.; Shaevitz, Joshua W.; Gitai, Zemer

2011-01-01

Bacterial cells possess multiple cytoskeletal proteins involved in a wide range of cellular processes. These cytoskeletal proteins are dynamic, but the driving forces and cellular functions of these dynamics remain poorly understood. Eukaryotic cytoskeletal dynamics are often driven by motor proteins, but in bacteria no motors that drive cytoskeletal motion have been identified to date. Here, we quantitatively study the dynamics of the Escherichia coli actin homolog MreB, which is essential for the maintenance of rod-like cell shape in bacteria. We find that MreB rotates around the long axis of the cell in a persistent manner. Whereas previous studies have suggested that MreB dynamics are driven by its own polymerization, we show that MreB rotation does not depend on its own polymerization but rather requires the assembly of the peptidoglycan cell wall. The cell-wall synthesis machinery thus either constitutes a novel type of extracellular motor that exerts force on cytoplasmic MreB, or is indirectly required for an as-yet-unidentified motor. Biophysical simulations suggest that one function of MreB rotation is to ensure a uniform distribution of new peptidoglycan insertion sites, a necessary condition to maintain rod shape during growth. These findings both broaden the view of cytoskeletal motors and deepen our understanding of the physical basis of bacterial morphogenesis. PMID:21903929

Global Particle-in-Cell Simulations of Mercury's Magnetosphere

NASA Astrophysics Data System (ADS)

Schriver, D.; Travnicek, P. M.; Lapenta, G.; Amaya, J.; Gonzalez, D.; Richard, R. L.; Berchem, J.; Hellinger, P.

2017-12-01

Spacecraft observations of Mercury's magnetosphere have shown that kinetic ion and electron particle effects play a major role in the transport, acceleration, and loss of plasma within the magnetospheric system. Kinetic processes include reconnection, the breakdown of particle adiabaticity and wave-particle interactions. Because of the vast range in spatial scales involved in magnetospheric dynamics, from local electron Debye length scales ( meters) to solar wind/planetary magnetic scale lengths (tens to hundreds of planetary radii), fully self-consistent kinetic simulations of a global planetary magnetosphere remain challenging. Most global simulations of Earth's and other planet's magnetosphere are carried out using MHD, enhanced MHD (e.g., Hall MHD), hybrid, or a combination of MHD and particle in cell (PIC) simulations. Here, 3D kinetic self-consistent hybrid (ion particle, electron fluid) and full PIC (ion and electron particle) simulations of the solar wind interaction with Mercury's magnetosphere are carried out. Using the implicit PIC and hybrid simulations, Mercury's relatively small, but highly kinetic magnetosphere will be examined to determine how the self-consistent inclusion of electrons affects magnetic reconnection, particle transport and acceleration of plasma at Mercury. Also the spatial and energy profiles of precipitating magnetospheric ions and electrons onto Mercury's surface, which can strongly affect the regolith in terms of space weathering and particle outflow, will be examined with the PIC and hybrid codes. MESSENGER spacecraft observations are used both to initiate and validate the global kinetic simulations to achieve a deeper understanding of the role kinetic physics play in magnetospheric dynamics.

Cost efficient CFD simulations: Proper selection of domain partitioning strategies

NASA Astrophysics Data System (ADS)

Haddadi, Bahram; Jordan, Christian; Harasek, Michael

2017-10-01

Computational Fluid Dynamics (CFD) is one of the most powerful simulation methods, which is used for temporally and spatially resolved solutions of fluid flow, heat transfer, mass transfer, etc. One of the challenges of Computational Fluid Dynamics is the extreme hardware demand. Nowadays super-computers (e.g. High Performance Computing, HPC) featuring multiple CPU cores are applied for solving-the simulation domain is split into partitions for each core. Some of the different methods for partitioning are investigated in this paper. As a practical example, a new open source based solver was utilized for simulating packed bed adsorption, a common separation method within the field of thermal process engineering. Adsorption can for example be applied for removal of trace gases from a gas stream or pure gases production like Hydrogen. For comparing the performance of the partitioning methods, a 60 million cell mesh for a packed bed of spherical adsorbents was created; one second of the adsorption process was simulated. Different partitioning methods available in OpenFOAM® (Scotch, Simple, and Hierarchical) have been used with different numbers of sub-domains. The effect of the different methods and number of processor cores on the simulation speedup and also energy consumption were investigated for two different hardware infrastructures (Vienna Scientific Clusters VSC 2 and VSC 3). As a general recommendation an optimum number of cells per processor core was calculated. Optimized simulation speed, lower energy consumption and consequently the cost effects are reported here.

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

PubMed

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

2017-01-01

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

Computational Modeling and Simulation of Developmental ...

EPA Pesticide Factsheets

SYNOPSIS: The question of how tissues and organs are shaped during development is crucial for understanding human birth defects. Data from high-throughput screening assays on human stem cells may be utilized predict developmental toxicity with reasonable accuracy. Other types of models are necessary, however, for mechanism-specific analysis because embryogenesis requires precise timing and control. Agent-based modeling and simulation (ABMS) is an approach to virtually reconstruct these dynamics, cell-by-cell and interaction-by-interaction. Using ABMS, HTS lesions from ToxCast can be integrated with patterning systems heuristically to propagate key events This presentation to FDA-CFSAN will update progress on the applications of in silico modeling tools and approaches for assessing developmental toxicity.

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

PubMed

Galle, J; Hoffmann, M; Aust, G

2009-01-01

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

Early-Aggregation Studies of Polyglutamine in Solution

NASA Astrophysics Data System (ADS)

Fluitt, Aaron; de Pablo, Juan

2012-02-01

Several neurodegenerative diseases, notably Huntington's disease, are associated with certain proteins containing extended polyglutamine tracts. In all polyglutamine diseases, the age of onset is inversely correlated with the length of the polyglutamine domain beyond some pathological threshold. Diseased cells are characterized by intranuclear inclusions rich in aggregated polyglutamine. Experimental evidence suggests that oligomeric aggregate species, not mature amyloid fibrils, are the species most toxic to the cell. Little is known about the structures and aggregation dynamics of polyglutamine oligomers due to their short lifetimes. A better understanding of the pathway through which polyglutamine peptides form oligomeric aggregates will aid the design of therapies to inhibit their toxic activity. In this work, we report structural characterization of polyglutamine monomers and dimers from atomistic molecular dynamics simulations in explicit water. Umbrella sampling simulations reveal that the stability of the dimer species with respect to the disassociated monomers is an increasing function of the chain length.

Membrane tension controls the assembly of curvature-generating proteins

PubMed Central

Simunovic, Mijo; Voth, Gregory A.

2015-01-01

Proteins containing a Bin/Amphiphysin/Rvs (BAR) domain regulate membrane curvature in the cell. Recent simulations have revealed that BAR proteins assemble into linear aggregates, strongly affecting membrane curvature and its in-plane stress profile. Here, we explore the opposite question: do mechanical properties of the membrane impact protein association? By using coarse-grained molecular dynamics simulations, we show that increased surface tension significantly impacts the dynamics of protein assembly. While tensionless membranes promote a rapid formation of long-living linear aggregates of N-BAR proteins, increase in tension alters the geometry of protein association. At high tension, protein interactions are strongly inhibited. Increasing surface density of proteins leads to a wider range of protein association geometries, promoting the formation of meshes, which can be broken apart with membrane tension. Our work indicates that surface tension may play a key role in recruiting proteins to membrane-remodelling sites in the cell. PMID:26008710

The Dornier 328 Acoustic Test Cell (ATC) for interior noise tests and selected test results

NASA Technical Reports Server (NTRS)

Hackstein, H. Josef; Borchers, Ingo U.; Renger, Klaus; Vogt, Konrad

1992-01-01

To perform acoustic studies for achieving low noise levels for the Dornier 328, an acoustic test cell (ATC) of the Dornier 328 has been built. The ATC consists of a fuselage section, a realistic fuselage suspension system, and three exterior noise simulation rings. A complex digital 60 channel computer/amplifier noise generation system as well as multichannel digital data acquisition and evaluation system have been used. The noise control tests started with vibration measurements for supporting acoustic data interpretation. In addition, experiments have been carried out on dynamic vibration absorbers, the most important passive noise reduction measure for low frequency propeller noise. The design and arrangement of the current ATC are presented. Furthermore, exterior noise simulation as well as data acquisition are explained. The most promising results show noise reduction due to synchrophasing and dynamic vibration absorbers.

Multibillion-atom Molecular Dynamics Simulations of Plasticity, Spall, and Ejecta

NASA Astrophysics Data System (ADS)

Germann, Timothy C.

2007-06-01

Modern supercomputing platforms, such as the IBM BlueGene/L at Lawrence Livermore National Laboratory and the Roadrunner hybrid supercomputer being built at Los Alamos National Laboratory, are enabling large-scale classical molecular dynamics simulations of phenomena that were unthinkable just a few years ago. Using either the embedded atom method (EAM) description of simple (close-packed) metals, or modified EAM (MEAM) models of more complex solids and alloys with mixed covalent and metallic character, simulations containing billions to trillions of atoms are now practical, reaching volumes in excess of a cubic micron. In order to obtain any new physical insights, however, it is equally important that the analysis of such systems be tractable. This is in fact possible, in large part due to our highly efficient parallel visualization code, which enables the rendering of atomic spheres, Eulerian cells, and other geometric objects in a matter of minutes, even for tens of thousands of processors and billions of atoms. After briefly describing the BlueGene/L and Roadrunner architectures, and the code optimization strategies that were employed, results obtained thus far on BlueGene/L will be reviewed, including: (1) shock compression and release of a defective EAM Cu sample, illustrating the plastic deformation accompanying void collapse as well as the subsequent void growth and linkup upon release; (2) solid-solid martensitic phase transition in shock-compressed MEAM Ga; and (3) Rayleigh-Taylor fluid instability modeled using large-scale direct simulation Monte Carlo (DSMC) simulations. I will also describe our initial experiences utilizing Cell Broadband Engine processors (developed for the Sony PlayStation 3), and planned simulation studies of ejecta and spall failure in polycrystalline metals that will be carried out when the full Petaflop Opteron/Cell Roadrunner supercomputer is assembled in mid-2008.

Exact and approximate stochastic simulation of intracellular calcium dynamics.

PubMed

Wieder, Nicolas; Fink, Rainer H A; Wegner, Frederic von

2011-01-01

In simulations of chemical systems, the main task is to find an exact or approximate solution of the chemical master equation (CME) that satisfies certain constraints with respect to computation time and accuracy. While Brownian motion simulations of single molecules are often too time consuming to represent the mesoscopic level, the classical Gillespie algorithm is a stochastically exact algorithm that provides satisfying results in the representation of calcium microdomains. Gillespie's algorithm can be approximated via the tau-leap method and the chemical Langevin equation (CLE). Both methods lead to a substantial acceleration in computation time and a relatively small decrease in accuracy. Elimination of the noise terms leads to the classical, deterministic reaction rate equations (RRE). For complex multiscale systems, hybrid simulations are increasingly proposed to combine the advantages of stochastic and deterministic algorithms. An often used exemplary cell type in this context are striated muscle cells (e.g., cardiac and skeletal muscle cells). The properties of these cells are well described and they express many common calcium-dependent signaling pathways. The purpose of the present paper is to provide an overview of the aforementioned simulation approaches and their mutual relationships in the spectrum ranging from stochastic to deterministic algorithms.

Tetramethylpyrazine-Loaded Hydrogels: Preparation, Penetration Through a Subcutaneous-Mucous-Membrane Model, and a Molecular Dynamics Simulation.

PubMed

Xia, Hongmei; Xu, Yinxiang; Cheng, Zhiqing; Cheng, Yongfeng

2017-07-01

Tetramethylpyrazine (TMP) was extracted from Ligusticum chuanxiong hort. The compound is known to have a variety of medicinal functions; in particular, it is used for the treatment of cerebral ischemic diseases. TMP-loaded hydrogels offer an excellent preparation with the capacity to bypass the blood-brain barrier, allowing treatment of the brain through intranasal administration. We prepared TMP-loaded hydrogels using carbomer 940 and evaluated the release of TMP from the hydrogel. We determined the release rate using Franz-type diffusion cell experiments with a subcutaneous-mucous-membrane model and also by a molecular dynamics (MD) simulation. In general, the former method was more complicated than the latter was. The dynamic behavior of TMP release from the hydrogel was revealed by analysis of the mean square displacement of the trajectory in the MD simulation. The coefficient of TMP diffusion from the hydrogel was calculated at different temperatures (277, 298, and 310 K) by using MD software. The results showed that the coefficient of diffusion increased with an increase in temperature. This trend was observed both experimentally and in the MD simulation. Therefore, the MD simulation was a complementary method to verify the experimental data.

Biological Dynamics Markup Language (BDML): an open format for representing quantitative biological dynamics data

PubMed Central

Kyoda, Koji; Tohsato, Yukako; Ho, Kenneth H. L.; Onami, Shuichi

2015-01-01

Motivation: Recent progress in live-cell imaging and modeling techniques has resulted in generation of a large amount of quantitative data (from experimental measurements and computer simulations) on spatiotemporal dynamics of biological objects such as molecules, cells and organisms. Although many research groups have independently dedicated their efforts to developing software tools for visualizing and analyzing these data, these tools are often not compatible with each other because of different data formats. Results: We developed an open unified format, Biological Dynamics Markup Language (BDML; current version: 0.2), which provides a basic framework for representing quantitative biological dynamics data for objects ranging from molecules to cells to organisms. BDML is based on Extensible Markup Language (XML). Its advantages are machine and human readability and extensibility. BDML will improve the efficiency of development and evaluation of software tools for data visualization and analysis. Availability and implementation: A specification and a schema file for BDML are freely available online at http://ssbd.qbic.riken.jp/bdml/. Contact: sonami@riken.jp Supplementary Information: Supplementary data are available at Bioinformatics online. PMID:25414366

Biological Dynamics Markup Language (BDML): an open format for representing quantitative biological dynamics data.

PubMed

Kyoda, Koji; Tohsato, Yukako; Ho, Kenneth H L; Onami, Shuichi

2015-04-01

Recent progress in live-cell imaging and modeling techniques has resulted in generation of a large amount of quantitative data (from experimental measurements and computer simulations) on spatiotemporal dynamics of biological objects such as molecules, cells and organisms. Although many research groups have independently dedicated their efforts to developing software tools for visualizing and analyzing these data, these tools are often not compatible with each other because of different data formats. We developed an open unified format, Biological Dynamics Markup Language (BDML; current version: 0.2), which provides a basic framework for representing quantitative biological dynamics data for objects ranging from molecules to cells to organisms. BDML is based on Extensible Markup Language (XML). Its advantages are machine and human readability and extensibility. BDML will improve the efficiency of development and evaluation of software tools for data visualization and analysis. A specification and a schema file for BDML are freely available online at http://ssbd.qbic.riken.jp/bdml/. Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press.

Molecular Dynamics Simulations of the Permeation of Bisphenol A and Pore Formation in a Lipid Membrane

NASA Astrophysics Data System (ADS)

Chen, Liang; Chen, Junlang; Zhou, Guoquan; Wang, Yu; Xu, Can; Wang, Xiaogang

2016-09-01

Bisphenol A (BPA) is particularly considered as one of the most suspicious endocrine disruptors. Exposure to BPA may bring about possible human toxicities, such as cancerous tumors, birth defects and neoteny. One of the key issues to understand its toxicities is how BPA enters cells. In this paper, we perform molecular dynamics simulations to explore the interactions between BPA and a phospholipid membrane (dipalmitoylphosphatidylcholine, DPPC bilayer). The simulation results show that BPA can easily enter the membrane from the aqueous phase. With the increasing concentrations of BPA in the membrane, BPA tends to aggregate and form into cluster. Meanwhile, several DPPC lipids are pulled out from each leaflet and adsorbed on the cluster surface, leading to pore formation. Detailed observations indicate that the lipid extraction results mainly from the dispersion interactions between BPA cluster and lipid tails, as well as weak electrostatic attractions between lipid headgroups and the two hydroxyl groups on BPA. The lipid extraction and pore formation may cause cell membrane damage and are of great importance to uncover BPA’s cytotoxicity.

The mechanism by which P250L mutation impairs flavivirus-NS1 dimerization: an investigation based on molecular dynamics simulations.

PubMed

Oliveira, Edson R A; de Alencastro, Ricardo B; Horta, Bruno A C

2016-09-01

The flavivirus non-structural protein 1 (NS1) is a conserved glycoprotein with as yet undefined biological function. This protein dimerizes when inside infected cells or associated to cell membranes but also forms lipid-associated hexamers when secreted to the extracellular space. A single amino acid substitution (P250L) is capable of preventing the dimerization of NS1 resulting in lower virulence and slower virus replication. In this work, based on molecular dynamics simulations of the dengue-2 virus NS1 [Formula: see text]-ladder monomer as a core model, we found that this mutation can induce several conformational changes that importantly affect critical monomer-monomer interactions. Based on additional simulations, we suggest a mechanism by which a highly orchestrated sequence of events propagate the local perturbations around the mutation site towards the dimer interface. The elucidation of such a mechanism could potentially support new strategies for rational production of live-attenuated vaccines and highlights a step forward in the development of novel anti-flavivirus measures.

A network model for the specification of vulval precursor cells and cell fusion control in Caenorhabditis elegans

PubMed Central

Weinstein, Nathan; Mendoza, Luis

2013-01-01

The vulva of Caenorhabditis elegans has been long used as an experimental model of cell differentiation and organogenesis. While it is known that the signaling cascades of Wnt, Ras/MAPK, and NOTCH interact to form a molecular network, there is no consensus regarding its precise topology and dynamical properties. We inferred the molecular network, and developed a multivalued synchronous discrete dynamic model to study its behavior. The model reproduces the patterns of activation reported for the following types of cell: vulval precursor, first fate, second fate, second fate with reversed polarity, third fate, and fusion fate. We simulated the fusion of cells, the determination of the first, second, and third fates, as well as the transition from the second to the first fate. We also used the model to simulate all possible single loss- and gain-of-function mutants, as well as some relevant double and triple mutants. Importantly, we associated most of these simulated mutants to multivulva, vulvaless, egg-laying defective, or defective polarity phenotypes. The model shows that it is necessary for RAL-1 to activate NOTCH signaling, since the repression of LIN-45 by RAL-1 would not suffice for a proper second fate determination in an environment lacking DSL ligands. We also found that the model requires the complex formed by LAG-1, LIN-12, and SEL-8 to inhibit the transcription of eff-1 in second fate cells. Our model is the largest reconstruction to date of the molecular network controlling the specification of vulval precursor cells and cell fusion control in C. elegans. According to our model, the process of fate determination in the vulval precursor cells is reversible, at least until either the cells fuse with the ventral hypoderm or divide, and therefore the cell fates must be maintained by the presence of extracellular signals. PMID:23785384

Extended dynamic model for ion diffusion in all-vanadium redox flow battery including the effects of temperature and bulk electrolyte transfer

NASA Astrophysics Data System (ADS)

Badrinarayanan, Rajagopalan; Zhao, Jiyun; Tseng, K. J.; Skyllas-Kazacos, Maria

2014-12-01

As with all redox flow batteries, the Vanadium Redox flow Battery (VRB) can suffer from capacity loss as the vanadium ions diffuse at different rates leading to a build-up on one half-cell and dilution on the other. In this paper an extended dynamic model of the vanadium ion transfer is developed including the effect of temperature and bulk electrolyte transfer. The model is used to simulate capacity decay for a range of different ion exchange membranes that are being used in the VRB. The simulations show that Selemion CMV and Nafion 115 membranes have similar behavior where the impact of temperature on capacity loss is highest within the first 100 cycles. The results for Selemion AMV membrane however are seen to be very different where the capacity loss at different temperatures observed to increase linearly with increasing charging/discharging cycles. The model is made more comprehensive by including the effect of bulk electrolyte transfer. A volume change of 19% is observed in each half-cell for Nafion 115 membrane based on the simulation parameters. The effect of this change in volume directly affects concentration, and the characteristics are analyzed for each vanadium species as well as the overall concentration in the half-cells.

Numerical simulation of fluid field and in vitro three-dimensional fabrication of tissue-engineered bones in a rotating bioreactor and in vivo implantation for repairing segmental bone defects.

PubMed

Song, Kedong; Wang, Hai; Zhang, Bowen; Lim, Mayasari; Liu, Yingchao; Liu, Tianqing

2013-03-01

In this paper, two-dimensional flow field simulation was conducted to determine shear stresses and velocity profiles for bone tissue engineering in a rotating wall vessel bioreactor (RWVB). In addition, in vitro three-dimensional fabrication of tissue-engineered bones was carried out in optimized bioreactor conditions, and in vivo implantation using fabricated bones was performed for segmental bone defects of Zelanian rabbits. The distribution of dynamic pressure, total pressure, shear stress, and velocity within the culture chamber was calculated for different scaffold locations. According to the simulation results, the dynamic pressure, velocity, and shear stress around the surface of cell-scaffold construction periodically changed at different locations of the RWVB, which could result in periodical stress stimulation for fabricated tissue constructs. However, overall shear stresses were relatively low, and the fluid velocities were uniform in the bioreactor. Our in vitro experiments showed that the number of cells cultured in the RWVB was five times higher than those cultured in a T-flask. The tissue-engineered bones grew very well in the RWVB. This study demonstrates that stress stimulation in an RWVB can be beneficial for cell/bio-derived bone constructs fabricated in an RWVB, with an application for repairing segmental bone defects.

Dynamic states of a unidirectional ring of chen oscillators

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

Carvalho, Ana; Pinto, Carla M.A.

2015-03-10

We study curious dynamical patterns appearing in a network of a unidirectional ring of Chen oscillators coupled to a ‘buffer’ cell. The network has Z{sub 3} exact symmetry group. We simulate the coupled cell systems associated to the two networks and obtain steady-states, rotating waves, quasiperiodic behavior, and chaos. The different patterns appear to arise through a sequence of Hopf, period-doubling and period-halving bifurcations. The network architecture appears to explain some patterns, whereas the properties of the chaotic oscillator may explain others. We use XPPAUT and MATLAB to compute numerically the relevant states.

Model-Based Phenotypic Signatures Governing the Dynamics of the Stem and Semi-differentiated Cell Populations in Dysplastic Colonic Crypts.

PubMed

Nikolov, Svetoslav; Santos, Guido; Wolkenhauer, Olaf; Vera, Julio

2018-02-01

Mathematical modeling of cell differentiated in colonic crypts can contribute to a better understanding of basic mechanisms underlying colonic tissue organization, but also its deregulation during carcinogenesis and tumor progression. Here, we combined bifurcation analysis to assess the effect that time delay has in the complex interplay of stem cells and semi-differentiated cells at the niche of colonic crypts, and systematic model perturbation and simulation to find model-based phenotypes linked to cancer progression. The models suggest that stem cell and semi-differentiated cell population dynamics in colonic crypts can display chaotic behavior. In addition, we found that clinical profiling of colorectal cancer correlates with the in silico phenotypes proposed by the mathematical model. Further, potential therapeutic targets for chemotherapy resistant phenotypes are proposed, which in any case will require experimental validation.

Fluid Dynamics Appearing during Simulated Microgravity Using Random Positioning Machines

PubMed Central

Stern, Philip; Casartelli, Ernesto; Egli, Marcel

2017-01-01

Random Positioning Machines (RPMs) are widely used as tools to simulate microgravity on ground. They consist of two gimbal mounted frames, which constantly rotate biological samples around two perpendicular axes and thus distribute the Earth’s gravity vector in all directions over time. In recent years, the RPM is increasingly becoming appreciated as a laboratory instrument also in non-space-related research. For instance, it can be applied for the formation of scaffold-free spheroid cell clusters. The kinematic rotation of the RPM, however, does not only distribute the gravity vector in such a way that it averages to zero, but it also introduces local forces to the cell culture. These forces can be described by rigid body analysis. Although RPMs are commonly used in laboratories, the fluid motion in the cell culture flasks on the RPM and the possible effects of such on cells have not been examined until today; thus, such aspects have been widely neglected. In this study, we used a numerical approach to describe the fluid dynamic characteristic occurring inside a cell culture flask turning on an operating RPM. The simulations showed that the fluid motion within the cell culture flask never reached a steady state or neared a steady state condition. The fluid velocity depends on the rotational velocity of the RPM and is in the order of a few centimeters per second. The highest shear stresses are found along the flask walls; depending of the rotational velocity, they can reach up to a few 100 mPa. The shear stresses in the “bulk volume,” however, are always smaller, and their magnitude is in the order of 10 mPa. In conclusion, RPMs are highly appreciated as reliable tools in microgravity research. They have even started to become useful instruments in new research fields of mechanobiology. Depending on the experiment, the fluid dynamic on the RPM cannot be neglected and needs to be taken into consideration. The results presented in this study elucidate the fluid motion and provide insight into the convection and shear stresses that occur inside a cell culture flask during RPM experiments. PMID:28135286

Time-dependent Computational Studies of Premixed Flames in Microgravity

NASA Technical Reports Server (NTRS)

Kailasanath, K.; Patnaik, Gopal; Oran, Elaine S.

1993-01-01

This report describes the research performed at the Center for Reactive Flow and Dynamical Systems in the Laboratory for Computational Physics and Fluid Dynamics, at the Naval Research Laboratory, in support of NASA Microgravity Science and Applications Program. The primary focus of this research is on investigating fundamental questions concerning the propagation and extinction of premixed flames in earth gravity and in microgravity environments. Our approach is to use detailed time-dependent, multispecies, numerical models as tools to simulate flames in different gravity environments. The models include a detailed chemical kinetics mechanism consisting of elementary reactions among the eight reactive species involved in hydrogen combustion, coupled to algorithms for convection, thermal conduction, viscosity, molecular and thermal diffusion, and external forces. The external force, gravity, can be put in any direction relative to flame propagation and can have a range of values. Recently more advanced wall boundary conditions such as isothermal and no-slip have been added to the model. This enables the simulation of flames propagating in more practical systems than before. We have used the numerical simulations to investigate the effects of heat losses and buoyancy forces on the structure and stability of flames, to help resolve fundamental questions on the existence of flammability limits when there are no external losses or buoyancy forces in the system, to understand the interaction between the various processes leading to flame instabilities and extinguishment, and to study the dynamics of cell formation and splitting. Our studies have been able to bring out the differences between upward- and downward-propagating flames and predict the zero-gravity behavior of these flames. The simulations have also highlighted the dominant role of wall heat losses in the case of downward-propagating flames. The simulations have been able to qualitatively predict the formation of multiple cells and the cessation of cell-splitting. Our studies have also shown that some flames in a microgravity environment can be extinguished due to a chemical instability and without any external losses. However, further simulations are needed to more completely understand upward-propagating and zero-gravity flames as well as to understand the potential effect of radiative heat losses.

QwikMD — Integrative Molecular Dynamics Toolkit for Novices and Experts

PubMed Central

Ribeiro, João V.; Bernardi, Rafael C.; Rudack, Till; Stone, John E.; Phillips, James C.; Freddolino, Peter L.; Schulten, Klaus

2016-01-01

The proper functioning of biomolecules in living cells requires them to assume particular structures and to undergo conformational changes. Both biomolecular structure and motion can be studied using a wide variety of techniques, but none offers the level of detail as do molecular dynamics (MD) simulations. Integrating two widely used modeling programs, namely NAMD and VMD, we have created a robust, user-friendly software, QwikMD, which enables novices and experts alike to address biomedically relevant questions, where often only molecular dynamics simulations can provide answers. Performing both simple and advanced MD simulations interactively, QwikMD automates as many steps as necessary for preparing, carrying out, and analyzing simulations while checking for common errors and enabling reproducibility. QwikMD meets also the needs of experts in the field, increasing the efficiency and quality of their work by carrying out tedious or repetitive tasks while enabling easy control of every step. Whether carrying out simulations within the live view mode on a small laptop or performing complex and large simulations on supercomputers or Cloud computers, QwikMD uses the same steps and user interface. QwikMD is freely available by download on group and personal computers. It is also available on the cloud at Amazon Web Services. PMID:27216779

QwikMD — Integrative Molecular Dynamics Toolkit for Novices and Experts

NASA Astrophysics Data System (ADS)

Ribeiro, João V.; Bernardi, Rafael C.; Rudack, Till; Stone, John E.; Phillips, James C.; Freddolino, Peter L.; Schulten, Klaus

2016-05-01

The proper functioning of biomolecules in living cells requires them to assume particular structures and to undergo conformational changes. Both biomolecular structure and motion can be studied using a wide variety of techniques, but none offers the level of detail as do molecular dynamics (MD) simulations. Integrating two widely used modeling programs, namely NAMD and VMD, we have created a robust, user-friendly software, QwikMD, which enables novices and experts alike to address biomedically relevant questions, where often only molecular dynamics simulations can provide answers. Performing both simple and advanced MD simulations interactively, QwikMD automates as many steps as necessary for preparing, carrying out, and analyzing simulations while checking for common errors and enabling reproducibility. QwikMD meets also the needs of experts in the field, increasing the efficiency and quality of their work by carrying out tedious or repetitive tasks while enabling easy control of every step. Whether carrying out simulations within the live view mode on a small laptop or performing complex and large simulations on supercomputers or Cloud computers, QwikMD uses the same steps and user interface. QwikMD is freely available by download on group and personal computers. It is also available on the cloud at Amazon Web Services.

Molecular Dynamics Simulations of Creatine Kinase and Adenine Nucleotide Translocase in Mitochondrial Membrane Patch*

PubMed Central

Karo, Jaanus; Peterson, Pearu; Vendelin, Marko

2012-01-01

Interaction between mitochondrial creatine kinase (MtCK) and adenine nucleotide translocase (ANT) can play an important role in determining energy transfer pathways in the cell. Although the functional coupling between MtCK and ANT has been demonstrated, the precise mechanism of the coupling is not clear. To study the details of the coupling, we turned to molecular dynamics simulations. We introduce a new coarse-grained molecular dynamics model of a patch of the mitochondrial inner membrane containing a transmembrane ANT and an MtCK above the membrane. The membrane model consists of three major types of lipids (phosphatidylcholine, phosphatidylethanolamine, and cardiolipin) in a roughly 2:1:1 molar ratio. A thermodynamics-based coarse-grained force field, termed MARTINI, has been used together with the GROMACS molecular dynamics package for all simulated systems in this work. Several physical properties of the system are reproduced by the model and are in agreement with known data. This includes membrane thickness, dimension of the proteins, and diffusion constants. We have studied the binding of MtCK to the membrane and demonstrated the effect of cardiolipin on the stabilization of the binding. In addition, our simulations predict which part of the MtCK protein sequence interacts with the membrane. Taken together, the model has been verified by dynamical and structural data and can be used as the basis for further studies. PMID:22241474

In-vitro analysis of APA microcapsules for oral delivery of live bacterial cells.

PubMed

Chen, H; Ouyang, W; Jones, M; Haque, T; Lawuyi, B; Prakash, S

2005-08-01

Oral administration of microcapsules containing live bacterial cells has potential as an alternative therapy for several diseases. This article evaluates the suitability of the alginate-poly-L-lysine-alginate (APA) microcapsules for oral delivery of live bacterial cells, in-vitro, using a dynamic simulated human gastro-intestinal (GI) model. Results showed that the APA microcapsules were morphologically stable in the simulated stomach conditions, but did not retain their structural integrity after a 3-day exposure in simulated human GI media. The microbial populations of the tested bacterial cells and the activities of the tested enzymes in the simulated human GI suspension were not substantially altered by the presence of the APA microcapsules, suggesting that there were no significant adverse effects of oral administration of the APA microcapsules on the flora of the human gastrointestinal tract. When the APA microcapsules containing Lactobacillus plantarum 80 (LP80) were challenged in the simulated gastric medium (pH = 2.0), 80.0% of the encapsulated cells remained viable after a 5-min incubation; however, the viability decreased considerably (8.3%) after 15 min and dropped to 2.6% after 30 min and lower than 0.2% after 60 min, indicating the limitations of the currently obtainable APA membrane for oral delivery of live bacteria. Further in-vivo studies are required before conclusions can be made concerning the inadequacy of APA microcapsules for oral delivery of live bacterial cells.

Nonlinear Dynamic Theory of Acute Cell Injuries and Brain Ischemia

NASA Astrophysics Data System (ADS)

Taha, Doaa; Anggraini, Fika; Degracia, Donald; Huang, Zhi-Feng

2015-03-01

Cerebral ischemia in the form of stroke and cardiac arrest brain damage affect over 1 million people per year in the USA alone. In spite of close to 200 clinical trials and decades of research, there are no treatments to stop post-ischemic neuron death. We have argued that a major weakness of current brain ischemia research is lack of a deductive theoretical framework of acute cell injury to guide empirical studies. A previously published autonomous model based on the concept of nonlinear dynamic network was shown to capture important facets of cell injury, linking the concept of therapeutic to bistable dynamics. Here we present an improved, non-autonomous formulation of the nonlinear dynamic model of cell injury that allows multiple acute injuries over time, thereby allowing simulations of both therapeutic treatment and preconditioning. Our results are connected to the experimental data of gene expression and proteomics of neuron cells. Importantly, this new model may be construed as a novel approach to pharmacodynamics of acute cell injury. The model makes explicit that any pro-survival therapy is always a form of sub-lethal injury. This insight is expected to widely influence treatment of acute injury conditions that have defied successful treatment to date. This work is supported by NIH NINDS (NS081347) and Wayne State University President's Research Enhancement Award.

Dynamics of an HIV-1 infection model with cell mediated immunity

NASA Astrophysics Data System (ADS)

Yu, Pei; Huang, Jianing; Jiang, Jiao

2014-10-01

In this paper, we study the dynamics of an improved mathematical model on HIV-1 virus with cell mediated immunity. This new 5-dimensional model is based on the combination of a basic 3-dimensional HIV-1 model and a 4-dimensional immunity response model, which more realistically describes dynamics between the uninfected cells, infected cells, virus, the CTL response cells and CTL effector cells. Our 5-dimensional model may be reduced to the 4-dimensional model by applying a quasi-steady state assumption on the variable of virus. However, it is shown in this paper that virus is necessary to be involved in the modeling, and that a quasi-steady state assumption should be applied carefully, which may miss some important dynamical behavior of the system. Detailed bifurcation analysis is given to show that the system has three equilibrium solutions, namely the infection-free equilibrium, the infectious equilibrium without CTL, and the infectious equilibrium with CTL, and a series of bifurcations including two transcritical bifurcations and one or two possible Hopf bifurcations occur from these three equilibria as the basic reproduction number is varied. The mathematical methods applied in this paper include characteristic equations, Routh-Hurwitz condition, fluctuation lemma, Lyapunov function and computation of normal forms. Numerical simulation is also presented to demonstrate the applicability of the theoretical predictions.

Digital holographic microscopy long-term and real-time monitoring of cell division and changes under simulated zero gravity.

PubMed

Pan, Feng; Liu, Shuo; Wang, Zhe; Shang, Peng; Xiao, Wen

2012-05-07

The long-term and real-time monitoring the cell division and changes of osteoblasts under simulated zero gravity condition were succeed by combing a digital holographic microscopy (DHM) with a superconducting magnet (SM). The SM could generate different magnetic force fields in a cylindrical cavity, where the gravitational force of biological samples could be canceled at a special gravity position by a high magnetic force. Therefore the specimens were levitated and in a simulated zero gravity environment. The DHM was modified to fit with SM by using single mode optical fibers and a vertically-configured jig designed to hold specimens and integrate optical device in the magnet's bore. The results presented the first-phase images of living cells undergoing dynamic divisions and changes under simulated zero gravity environment for a period of 10 hours. The experiments demonstrated that the SM-compatible DHM setup could provide a highly efficient and versatile method for research on the effects of microgravity on biological samples.

Improving the off-axis spatial resolution and dynamic range of the NIF X-ray streak cameras (invited)

DOE PAGES

MacPhee, A. G.; Dymoke-Bradshaw, A. K. L.; Hares, J. D.; ...

2016-08-08

Here, we report simulationsand experiments that demonstrate an increasein spatial resolution ofthe NIF core diagnostic x-ray streak camerasby a factor of two, especially off axis. A designwas achieved by usinga corrector electron optic to flatten the field curvature at the detector planeand corroborated by measurement. In addition, particle in cell simulations were performed to identify theregions in the streak camera that contribute most to space charge blurring. Our simulations provide a tool for convolving syntheticpre-shot spectra with the instrument functionso signal levels can be set to maximize dynamic range for the relevant part of the streak record.

Virtual reality in urban water management: communicating urban flooding with particle-based CFD simulations.

PubMed

Winkler, Daniel; Zischg, Jonatan; Rauch, Wolfgang

2018-01-01

For communicating urban flood risk to authorities and the public, a realistic three-dimensional visual display is frequently more suitable than detailed flood maps. Virtual reality could also serve to plan short-term flooding interventions. We introduce here an alternative approach for simulating three-dimensional flooding dynamics in large- and small-scale urban scenes by reaching out to computer graphics. This approach, denoted 'particle in cell', is a particle-based CFD method that is used to predict physically plausible results instead of accurate flow dynamics. We exemplify the approach for the real flooding event in July 2016 in Innsbruck.

Molecular Dynamics Simulation of Telomere and TRF1

NASA Astrophysics Data System (ADS)

Kaburagi, Masaaki; Fukuda, Masaki; Yamada, Hironao; Miyakawa, Takeshi; Morikawa, Ryota; Takasu, Masako; Kato, Takamitsu A.; Uesaka, Mitsuru

Telomeres play a central role in determining longevity of a cell. Our study focuses on the interaction between telomeric guanines and TRF1 as a means to observe the telomeric based mechanism of the genome protection. In this research, we performed molecular dynamics simulations of a telomeric DNA and TRF1. Our results show a stable structure with a high affinity for the specific protein. Additionally, we calculated the distance between guanines and the protein in their complex state. From this comparison, we found the calculated values of distance to be very similar, and the angle of guanines in their complex states was larger than that in their single state.

Comparison of amino acids interaction with gold nanoparticle.

PubMed

Ramezani, Fatemeh; Amanlou, Massoud; Rafii-Tabar, Hashem

2014-04-01

The study of nanomaterial/biomolecule interface is an important emerging field in bionanoscience, and additionally in many biological processes such as hard-tissue growth and cell-surface adhesion. To have a deeper understanding of the amino acids/gold nanoparticle assemblies, the adsorption of these amino acids on the gold nanoparticles (GNPs) has been investigated via molecular dynamics simulation. In these simulations, all the constituent atoms of the nanoparticles were considered to be dynamic. The geometries of amino acids, when adsorbed on the nanoparticle, were studied and their flexibilities were compared with one another. The interaction of each of 20 amino acids was considered with 3 and 8 nm gold GNPs.

Best Practices for Operando Battery Experiments: Influences of X-ray Experiment Design on Observed Electrochemical Reactivity

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

Borkiewicz, O. J.; Wiaderek, Kamila M.; Chupas, Peter J.

Dynamic properties and multiscale complexities governing electrochemical energy storage in batteries are most ideally interrogated under simulated operating conditions within an electrochemical cell. We assess how electrochemical reactivity can be impacted by experiment design, including the X-ray measurements or by common features or adaptations of electrochemical cells that enable X-ray measurements.

Transport of diseased red blood cells in the spleen

NASA Astrophysics Data System (ADS)

Peng, Zhangli; Pivkin, Igor; Dao, Ming

2012-11-01

A major function of the spleen is to remove old and diseased red blood cells (RBCs) with abnormal mechanical properties. We investigated this mechanical filtering mechanism by combining experiments and computational modeling, especially for red blood cells in malaria and sickle cell disease (SCD). First, utilizing a transgenic line for 3D confocal live imaging, in vitro capillary assays and 3D finite element modeling, we extracted the mechanical properties of both the RBC membrane and malaria parasites for different asexual malaria stages. Secondly, using a non-invasive laser interferometric technique, we optically measured the dynamic membrane fluctuations of SCD RBCs. By simulating the membrane fluctuation experiment using the dissipative particle dynamics (DPD) model, we retrieved mechanical properties of SCD RBCs with different shapes. Finally, based on the mechanical properties obtained from these experiments, we simulated the full fluid-structure interaction problem of diseased RBCs passing through endothelial slits in the spleen under different fluid pressure gradients using the DPD model. The effects of the mechanical properties of the lipid bilayer, the cytoskeleton and the parasite on the critical pressure of splenic passage of RBCs were investigated separately. This work is supported by NIH and Singapore-MIT Alliance for Science and Technology (SMART).

Computer Simulation of Embryonic Systems: What can a ...

EPA Pesticide Factsheets

(1) Standard practice for assessing developmental toxicity is the observation of apical endpoints (intrauterine death, fetal growth retardation, structural malformations) in pregnant rats/rabbits following exposure during organogenesis. EPA’s computational toxicology research program (ToxCast) generated vast in vitro cellular and molecular effects data on >1858 chemicals in >600 high-throughput screening (HTS) assays. The diversity of assays has been increased for developmental toxicity with several HTS platforms, including the devTOX-quickPredict assay from Stemina Biomarker Discovery utilizing the human embryonic stem cell line (H9). Translating these HTS data into higher order-predictions of developmental toxicity is a significant challenge. Here, we address the application of computational systems models that recapitulate the kinematics of dynamical cell signaling networks (e.g., SHH, FGF, BMP, retinoids) in a CompuCell3D.org modeling environment. Examples include angiogenesis (angiodysplasia) and dysmorphogenesis. Being numerically responsive to perturbation, these models are amenable to data integration for systems Toxicology and Adverse Outcome Pathways (AOPs). The AOP simulation outputs predict potential phenotypes based on the in vitro HTS data ToxCast. A heuristic computational intelligence framework that recapitulates the kinematics of dynamical cell signaling networks in the embryo, together with the in vitro profiling data, produce quantitative pr

Computational Modeling and Simulation of Developmental ...

EPA Pesticide Factsheets

Standard practice for assessing developmental toxicity is the observation of apical endpoints (intrauterine death, fetal growth retardation, structural malformations) in pregnant rats/rabbits following exposure during organogenesis. EPA’s computational toxicology research program (ToxCast) generated vast in vitro cellular and molecular effects data on >1858 chemicals in >600 high-throughput screening (HTS) assays. The diversity of assays has been increased for developmental toxicity with several HTS platforms, including the devTOX-quickPredict assay from Stemina Biomarker Discovery utilizing the human embryonic stem cell line (H9). Translating these HTS data into higher order-predictions of developmental toxicity is a significant challenge. Here, we address the application of computational systems models that recapitulate the kinematics of dynamical cell signaling networks (e.g., SHH, FGF, BMP, retinoids) in a CompuCell3D.org modeling environment. Examples include angiogenesis (angiodysplasia) and dysmorphogenesis. Being numerically responsive to perturbation, these models are amenable to data integration for systems Toxicology and Adverse Outcome Pathways (AOPs). The AOP simulation outputs predict potential phenotypes based on the in vitro HTS data ToxCast. A heuristic computational intelligence framework that recapitulates the kinematics of dynamical cell signaling networks in the embryo, together with the in vitro profiling data, produce quantitative predic

Screening and structure-based modeling of T-cell epitopes of Nipah virus proteome: an immunoinformatic approach for designing peptide-based vaccine.

PubMed

Kamthania, Mohit; Sharma, D K

2015-12-01

Identification of Nipah virus (NiV) T-cell-specific antigen is urgently needed for appropriate diagnostic and vaccination. In the present study, prediction and modeling of T-cell epitopes of Nipah virus antigenic proteins nucleocapsid, phosphoprotein, matrix, fusion, glycoprotein, L protein, W protein, V protein and C protein followed by the binding simulation studies of predicted highest binding scorers with their corresponding MHC class I alleles were done. Immunoinformatic tool ProPred1 was used to predict the promiscuous MHC class I epitopes of viral antigenic proteins. The molecular modelings of the epitopes were done by PEPstr server. And alleles structure were predicted by MODELLER 9.10. Molecular dynamics (MD) simulation studies were performed through the NAMD graphical user interface embedded in visual molecular dynamics. Epitopes VPATNSPEL, NPTAVPFTL and LLFVFGPNL of Nucleocapsid, V protein and Fusion protein have considerable binding energy and score with HLA-B7, HLA-B*2705 and HLA-A2MHC class I allele, respectively. These three predicted peptides are highly potential to induce T-cell-mediated immune response and are expected to be useful in designing epitope-based vaccines against Nipah virus after further testing by wet laboratory studies.

Dynamic Resource Adjustment to Provide Seamless Streaming Services on Multimedia Mobile Cellular Networks

NASA Astrophysics Data System (ADS)

Lin, Chow-Sing; Yen, Fang-Zhi

With the rapid advances in wireless network communication, multimedia presentation has become more applicable. However, due to the limited wireless network resource and the mobility of Mobile Host (MH), QoS for wireless streaming is much more difficult to maintain. How to decrease Call Dropping Probability (CDP) in multimedia traffic while still keeping acceptable Call Block Probability (CBP) without sacrificing QoS has become an significant issue in providing wireless streaming services. In this paper, we propose a novel Dynamic Resources Adjustment (DRA) algorithm, which can dynamically borrow idle reserved resources in the serving cell or the target cell for handoffing MHs to compensate the shortage of bandwidth in media streaming. The experimental simulation results show that compared with traditional No Reservation (NR), and Resource Reservation in the six neighboring cells (RR-nb), and Resource Reservation in the target cell (RR-t), our proposed DRA algorithm can fully utilize unused reserved resources to effectively decrease the CDP while still keeping acceptable CBP with high bandwidth utilization.

On the global dynamics of a chronic myelogenous leukemia model

NASA Astrophysics Data System (ADS)

Krishchenko, Alexander P.; Starkov, Konstantin E.

2016-04-01

In this paper we analyze some features of global dynamics of a three-dimensional chronic myelogenous leukemia (CML) model with the help of the stability analysis and the localization method of compact invariant sets. The behavior of CML model is defined by concentrations of three cellpopulations circulating in the blood: naive T cells, effector T cells specific to CML and CML cancer cells. We prove that the dynamics of the CML system around the tumor-free equilibrium point is unstable. Further, we compute ultimate upper bounds for all three cell populations and provide the existence conditions of the positively invariant polytope. One ultimate lower bound is obtained as well. Moreover, we describe the iterative localization procedure for refining localization bounds; this procedure is based on cyclic using of localizing functions. Applying this procedure we obtain conditions under which the internal tumor equilibrium point is globally asymptotically stable. Our theoretical analyses are supplied by results of the numerical simulation.

Quantifying the biophysical characteristics of Plasmodium-falciparum-parasitized red blood cells in microcirculation

PubMed Central

Fedosov, D. A.; Caswell, B.; Suresh, S.; Karniadakis, G. E.

2011-01-01

The pathogenicity of Plasmodium falciparum (Pf) malaria results from the stiffening of red blood cells (RBCs) and its ability to adhere to endothelial cells (cytoadherence). The dynamics of Pf-parasitized RBCs is studied by three-dimensional mesoscopic simulations of flow in cylindrical capillaries in order to predict the flow resistance enhancement at different parasitemia levels. In addition, the adhesive dynamics of Pf-RBCs is explored for various parameters revealing several types of cell dynamics such as firm adhesion, very slow slipping along the wall, and intermittent flipping. The parasite inside the RBC is modeled explicitly in order to capture phenomena such as “hindered tumbling” motion of the RBC and the sudden transition from firm RBC cytoadherence to flipping on the endothelial surface. These predictions are in quantitative agreement with recent experimental observations, and thus the three-dimensional modeling method presented here provides new capabilities for guiding and interpreting future in vitro and in vivo studies of malaria. PMID:21173269

Study of dynamic fluid-structure coupling with application to human phonation

NASA Astrophysics Data System (ADS)

Saurabh, Shakti; Faber, Justin; Bodony, Daniel

2013-11-01

Two-dimensional direct numerical simulations of a compressible, viscous fluid interacting with a non-linear, viscoelastic solid are used to study the generation of the human voice. The vocal fold (VF) tissues are modeled using a finite-strain fractional derivative constitutive model implemented in a quadratic finite element code and coupled to a high-order compressible Navier-Stokes solver through a boundary-fitted fluid-solid interface. The viscoelastic solver is validated through in-house experiments using Agarose Gel, a human tissue simulant, undergoing static and harmonic deformation measured with load cell and optical diagnostics. The phonation simulations highlight the role tissue nonlinearity and viscosity play in the glottal jet dynamics and in the radiated sound. Supported by the National Science Foundation (CAREER award number 1150439).

A gas-dynamical approach to radiation pressure acceleration

NASA Astrophysics Data System (ADS)

Schmidt, Peter; Boine-Frankenheim, Oliver

2016-06-01

The study of high intensity ion beams driven by high power pulsed lasers is an active field of research. Of particular interest is the radiation pressure acceleration, for which simulations predict narrow band ion energies up to GeV. We derive a laser-piston model by applying techniques for non-relativistic gas-dynamics. The model reveals a laser intensity limit, below which sufficient laser-piston acceleration is impossible. The relation between target thickness and piston velocity as a function of the laser pulse length yields an approximation for the permissible target thickness. We performed one-dimensional Particle-In-Cell simulations to confirm the predictions of the analytical model. These simulations also reveal the importance of electromagnetic energy transport. We find that this energy transport limits the achievable compression and rarefies the plasma.

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

PubMed Central

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

2012-01-01

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

A Parametric Computational Model of the Action Potential of Pacemaker Cells.

PubMed

Ai, Weiwei; Patel, Nitish D; Roop, Partha S; Malik, Avinash; Andalam, Sidharta; Yip, Eugene; Allen, Nathan; Trew, Mark L

2018-01-01

A flexible, efficient, and verifiable pacemaker cell model is essential to the design of real-time virtual hearts that can be used for closed-loop validation of cardiac devices. A new parametric model of pacemaker action potential is developed to address this need. The action potential phases are modeled using hybrid automaton with one piecewise-linear continuous variable. The model can capture rate-dependent dynamics, such as action potential duration restitution, conduction velocity restitution, and overdrive suppression by incorporating nonlinear update functions. Simulated dynamics of the model compared well with previous models and clinical data. The results show that the parametric model can reproduce the electrophysiological dynamics of a variety of pacemaker cells, such as sinoatrial node, atrioventricular node, and the His-Purkinje system, under varying cardiac conditions. This is an important contribution toward closed-loop validation of cardiac devices using real-time heart models.

Modeling the effect of dynamic surfaces on membrane penetration

NASA Astrophysics Data System (ADS)

van Lehn, Reid; Alexander-Katz, Alfredo

2011-03-01

The development of nanoscale materials for targeted drug delivery is an important current pursuit in materials science. One task of drug carriers is to release therapeutic agents within cells by bypassing the cell membrane to maximize the effectiveness of their payload and minimize bodily exposure. In this work, we use coarse-grained simulations to study nanoparticles (NPs) grafted with hydrophobic and hydrophilic ligands that rearrange in response to the amphiphilic lipid bilayer. We demonstrate that this dynamic surface permits the NP to spontaneously penetrate to the bilayer midplane when the surface ligands are near an order-disorder transition. We believe that this work will lead to the design of new drug carriers capable of non-specifically accessing cell interiors based solely on their dynamic surface properties. Our work is motivated by existing nanoscale systems such as micelles, or NPs grafted with highly mobile ligands or polymer brushes.

Electroporating Fields Target Oxidatively Damaged Areas in the Cell Membrane

PubMed Central

Vernier, P. Thomas; Levine, Zachary A.; Wu, Yu-Hsuan; Joubert, Vanessa; Ziegler, Matthew J.; Mir, Lluis M.; Tieleman, D. Peter

2009-01-01

Reversible electropermeabilization (electroporation) is widely used to facilitate the introduction of genetic material and pharmaceutical agents into living cells. Although considerable knowledge has been gained from the study of real and simulated model membranes in electric fields, efforts to optimize electroporation protocols are limited by a lack of detailed understanding of the molecular basis for the electropermeabilization of the complex biomolecular assembly that forms the plasma membrane. We show here, with results from both molecular dynamics simulations and experiments with living cells, that the oxidation of membrane components enhances the susceptibility of the membrane to electropermeabilization. Manipulation of the level of oxidative stress in cell suspensions and in tissues may lead to more efficient permeabilization procedures in the laboratory and in clinical applications such as electrochemotherapy and electrotransfection-mediated gene therapy. PMID:19956595

The Australian Computational Earth Systems Simulator

NASA Astrophysics Data System (ADS)

Mora, P.; Muhlhaus, H.; Lister, G.; Dyskin, A.; Place, D.; Appelbe, B.; Nimmervoll, N.; Abramson, D.

2001-12-01

Numerical simulation of the physics and dynamics of the entire earth system offers an outstanding opportunity for advancing earth system science and technology but represents a major challenge due to the range of scales and physical processes involved, as well as the magnitude of the software engineering effort required. However, new simulation and computer technologies are bringing this objective within reach. Under a special competitive national funding scheme to establish new Major National Research Facilities (MNRF), the Australian government together with a consortium of Universities and research institutions have funded construction of the Australian Computational Earth Systems Simulator (ACcESS). The Simulator or computational virtual earth will provide the research infrastructure to the Australian earth systems science community required for simulations of dynamical earth processes at scales ranging from microscopic to global. It will consist of thematic supercomputer infrastructure and an earth systems simulation software system. The Simulator models and software will be constructed over a five year period by a multi-disciplinary team of computational scientists, mathematicians, earth scientists, civil engineers and software engineers. The construction team will integrate numerical simulation models (3D discrete elements/lattice solid model, particle-in-cell large deformation finite-element method, stress reconstruction models, multi-scale continuum models etc) with geophysical, geological and tectonic models, through advanced software engineering and visualization technologies. When fully constructed, the Simulator aims to provide the software and hardware infrastructure needed to model solid earth phenomena including global scale dynamics and mineralisation processes, crustal scale processes including plate tectonics, mountain building, interacting fault system dynamics, and micro-scale processes that control the geological, physical and dynamic behaviour of earth systems. ACcESS represents a part of Australia's contribution to the APEC Cooperation for Earthquake Simulation (ACES) international initiative. Together with other national earth systems science initiatives including the Japanese Earth Simulator and US General Earthquake Model projects, ACcESS aims to provide a driver for scientific advancement and technological breakthroughs including: quantum leaps in understanding of earth evolution at global, crustal, regional and microscopic scales; new knowledge of the physics of crustal fault systems required to underpin the grand challenge of earthquake prediction; new understanding and predictive capabilities of geological processes such as tectonics and mineralisation.

Chemo-elastic modeling of invasive carcinoma development accompanied by oncogenic epithelial-mesenchymal transition

NASA Astrophysics Data System (ADS)

Bratsun, D. A.; Krasnyakov, I. V.; Pismen, L.

2017-09-01

We present a further development of a multiscale chemo-mechanical model of carcinoma growth in the epithelium tissue proposed earlier. The epithelium is represented by an elastic 2D array of polygonal cells, each with its own gene regulation dynamics. The model allows the simulation of evolution of multiple cells interacting via the chemical signaling or mechanically induced strain. The algorithm takes into account the division and intercalation of cells. The latter is most important since, first of all, carcinoma cells lose cell-cell adhesion and polarity via the oncogenic variant of the epithelial-mesenchymal transition (EMT) at which cells gain migratory and invasive properties. This process is mediated by E-cadherin repression and requires the differentiation of tumor cells with respect to the edge of the tumor that means that front cells should be most mobile. Taking into account this suggestion, we present the results of simulations demonstrating different patterns of carcinoma invasion. The comparison of our results with recent experimental observations is given and discussed.

Monte Carlo radiotherapy simulations of accelerated repopulation and reoxygenation for hypoxic head and neck cancer

PubMed Central

Harriss-Phillips, W M; Bezak, E; Yeoh, E K

2011-01-01

Objective A temporal Monte Carlo tumour growth and radiotherapy effect model (HYP-RT) simulating hypoxia in head and neck cancer has been developed and used to analyse parameters influencing cell kill during conventionally fractionated radiotherapy. The model was designed to simulate individual cell division up to 108 cells, while incorporating radiobiological effects, including accelerated repopulation and reoxygenation during treatment. Method Reoxygenation of hypoxic tumours has been modelled using randomised increments of oxygen to tumour cells after each treatment fraction. The process of accelerated repopulation has been modelled by increasing the symmetrical stem cell division probability. Both phenomena were onset immediately or after a number of weeks of simulated treatment. Results The extra dose required to control (total cell kill) hypoxic vs oxic tumours was 15–25% (8–20 Gy for 5×2 Gy per week) depending on the timing of accelerated repopulation onset. Reoxygenation of hypoxic tumours resulted in resensitisation and reduction in total dose required by approximately 10%, depending on the time of onset. When modelled simultaneously, accelerated repopulation and reoxygenation affected cell kill in hypoxic tumours in a similar manner to when the phenomena were modelled individually; however, the degree was altered, with non-additive results. Simulation results were in good agreement with standard linear quadratic theory; however, differed for more complex comparisons where hypoxia, reoxygenation as well as accelerated repopulation effects were considered. Conclusion Simulations have quantitatively confirmed the need for patient individualisation in radiotherapy for hypoxic head and neck tumours, and have shown the benefits of modelling complex and dynamic processes using Monte Carlo methods. PMID:21933980

A study of overflow simulations using MPAS-Ocean: Vertical grids, resolution, and viscosity

NASA Astrophysics Data System (ADS)

Reckinger, Shanon M.; Petersen, Mark R.; Reckinger, Scott J.

2015-12-01

MPAS-Ocean is used to simulate an idealized, density-driven overflow using the dynamics of overflow mixing and entrainment (DOME) setup. Numerical simulations are carried out using three of the vertical coordinate types available in MPAS-Ocean, including z-star with partial bottom cells, z-star with full cells, and sigma coordinates. The results are first benchmarked against other models, including the MITgcm's z-coordinate model and HIM's isopycnal coordinate model, which are used to set the base case used for this work. A full parameter study is presented that looks at how sensitive overflow simulations are to vertical grid type, resolution, and viscosity. Horizontal resolutions with 50 km grid cells are under-resolved and produce poor results, regardless of other parameter settings. Vertical grids ranging in thickness from 15 m to 120 m were tested. A horizontal resolution of 10 km and a vertical resolution of 60 m are sufficient to resolve the mesoscale dynamics of the DOME configuration, which mimics real-world overflow parameters. Mixing and final buoyancy are least sensitive to horizontal viscosity, but strongly sensitive to vertical viscosity. This suggests that vertical viscosity could be adjusted in overflow water formation regions to influence mixing and product water characteristics. Lastly, the study shows that sigma coordinates produce much less mixing than z-type coordinates, resulting in heavier plumes that go further down slope. Sigma coordinates are less sensitive to changes in resolution but as sensitive to vertical viscosity compared to z-coordinates.

Predicting lymph node output efficiency using systems biology

PubMed Central

Gong, Chang; Mattila, Joshua T.; Miller, Mark; Flynn, JoAnne L.; Linderman, Jennifer J.; Kirschner, D.

2013-01-01

Dendritic cells (DCs) capture pathogens and foreign antigen (Ag) in peripheral tissues and migrate to secondary lymphoid tissues, such as lymph nodes (LNs), where they present processed Ag as MHC-bound peptide (pMHC) to naïve T cells. Interactions between DCs and T cells result, over periods of hours, in activation, clonal expansion and differentiation of antigen-specific T cells, leading to primed cells that can now participate in immune responses. Two-photon microscopy (2PM) has been widely adopted to analyze lymphocyte dynamics and can serve as a powerful in vivo assay for cell trafficking and activation over short length and time scales. Linking biological phenomena between vastly different spatiotemporal scales can be achieved using a systems biology approach. We developed a 3D agent-based cellular model of a LN that allows for the simultaneous in silico simulation of T cell trafficking, activation and production of effector cells under different antigen (Ag) conditions. The model anatomy is based on in situ analysis of LN sections (from primates and mice) and cell dynamics based on quantitative measurements from 2PM imaging of mice. Our simulations make three important predictions. First, T cell encounters by DCs and T cell receptor (TCR) repertoire scanning are more efficient in a 3D model compared with 2D, suggesting that a 3D model is needed to analyze LN function. Second, LNs are able to produce primed CD4+T cells at the same efficiency over broad ranges of cognate frequencies (from 10−5 to 10−2). Third, reducing the time that naïve T cells are required to bind DCs before becoming activated will increase the rate at which effector cells are produced. This 3D model provides a robust platform to study how T cell trafficking and activation dynamics relate to the efficiency of T cell priming and clonal expansion. We envision that this systems biology approach will provide novel insights for guiding vaccine development and understanding immune responses to infection. PMID:23816876

Particle-in-cell numerical simulations of a cylindrical Hall thruster with permanent magnets

NASA Astrophysics Data System (ADS)

Miranda, Rodrigo A.; Martins, Alexandre A.; Ferreira, José L.

2017-10-01

The cylindrical Hall thruster (CHT) is a propulsion device that offers high propellant utilization and performance at smaller dimensions and lower power levels than traditional Hall thrusters. In this paper we present first results of a numerical model of a CHT. This model solves particle and field dynamics self-consistently using a particle-in-cell approach. We describe a number of techniques applied to reduce the execution time of the numerical simulations. The specific impulse and thrust computed from our simulations are in agreement with laboratory experiments. This simplified model will allow for a detailed analysis of different thruster operational parameters and obtain an optimal configuration to be implemented at the Plasma Physics Laboratory at the University of Brasília.

Binomial tau-leap spatial stochastic simulation algorithm for applications in chemical kinetics.

PubMed

Marquez-Lago, Tatiana T; Burrage, Kevin

2007-09-14

In cell biology, cell signaling pathway problems are often tackled with deterministic temporal models, well mixed stochastic simulators, and/or hybrid methods. But, in fact, three dimensional stochastic spatial modeling of reactions happening inside the cell is needed in order to fully understand these cell signaling pathways. This is because noise effects, low molecular concentrations, and spatial heterogeneity can all affect the cellular dynamics. However, there are ways in which important effects can be accounted without going to the extent of using highly resolved spatial simulators (such as single-particle software), hence reducing the overall computation time significantly. We present a new coarse grained modified version of the next subvolume method that allows the user to consider both diffusion and reaction events in relatively long simulation time spans as compared with the original method and other commonly used fully stochastic computational methods. Benchmarking of the simulation algorithm was performed through comparison with the next subvolume method and well mixed models (MATLAB), as well as stochastic particle reaction and transport simulations (CHEMCELL, Sandia National Laboratories). Additionally, we construct a model based on a set of chemical reactions in the epidermal growth factor receptor pathway. For this particular application and a bistable chemical system example, we analyze and outline the advantages of our presented binomial tau-leap spatial stochastic simulation algorithm, in terms of efficiency and accuracy, in scenarios of both molecular homogeneity and heterogeneity.

Ef: Software for Nonrelativistic Beam Simulation by Particle-in-Cell Algorithm

NASA Astrophysics Data System (ADS)

Boytsov, A. Yu.; Bulychev, A. A.

2018-04-01

Understanding of particle dynamics is crucial in construction of electron guns, ion sources and other types of nonrelativistic beam devices. Apart from external guiding and focusing systems, a prominent role in evolution of such low-energy beams is played by particle-particle interaction. Numerical simulations taking into account these effects are typically accomplished by a well-known particle-in-cell method. In practice, for convenient work a simulation program should not only implement this method, but also support parallelization, provide integration with CAD systems and allow access to details of the simulation algorithm. To address the formulated requirements, development of a new open source code - Ef - has been started. It's current features and main functionality are presented. Comparison with several analytical models demonstrates good agreement between the numerical results and the theory. Further development plans are discussed.

Simulation of magnetic active polymers for versatile microfluidic devices

NASA Astrophysics Data System (ADS)

Gusenbauer, Markus; Özelt, Harald; Fischbacher, Johann; Reichel, Franz; Exl, Lukas; Bance, Simon; Kataeva, Nadezhda; Binder, Claudia; Brückl, Hubert; Schrefl, Thomas

2013-01-01

We propose to use a compound of magnetic nanoparticles (20-100 nm) embedded in a flexible polymer (Polydimethylsiloxane PDMS) to filter circulating tumor cells (CTCs). The analysis of CTCs is an emerging tool for cancer biology research and clinical cancer management including the detection, diagnosis and monitoring of cancer. The combination of experiments and simulations lead to a versatile microfluidic lab-on-chip device. Simulations are essential to understand the influence of the embedded nanoparticles in the elastic PDMS when applying a magnetic gradient field. It combines finite element calculations of the polymer, magnetic simulations of the embedded nanoparticles and the fluid dynamic calculations of blood plasma and blood cells. With the use of magnetic active polymers a wide range of tunable microfluidic structures can be created. The method can help to increase the yield of needed isolated CTCs.

Simulating the Response of a Composite Honeycomb Energy Absorber. Part 1; Dynamic Crushing of Components and Multi-Terrain Impacts

NASA Technical Reports Server (NTRS)

Jackson, Karen E.; Fasanella, Edwin L.; Polanco, Michael A.

2012-01-01

This paper describes the experimental and analytical evaluation of an externally deployable composite honeycomb structure that is designed to attenuate impact energy during helicopter crashes. The concept, designated the Deployable Energy Absorber (DEA), utilizes an expandable Kevlar (Registered Trademark) honeycomb to dissipate kinetic energy through crushing. The DEA incorporates a unique flexible hinge design that allows the honeycomb to be packaged and stowed until needed for deployment. Experimental evaluation of the DEA included dynamic crush tests of multi-cell components and vertical drop tests of a composite fuselage section, retrofitted with DEA blocks, onto multi-terrain. Finite element models of the test articles were developed and simulations were performed using the transient dynamic code, LSDYNA (Registered Trademark). In each simulation, the DEA was represented using shell elements assigned two different material properties: Mat 24, an isotropic piecewise linear plasticity model, and Mat 58, a continuum damage mechanics model used to represent laminated composite fabrics. DEA model development and test-analysis comparisons are presented.

Numerical Simulation and Scaling Analysis of Cell Printing

NASA Astrophysics Data System (ADS)

Qiao, Rui; He, Ping

2011-11-01

Cell printing, i.e., printing three dimensional (3D) structures of cells held in a tissue matrix, is gaining significant attention in the biomedical community. The key idea is to use inkjet printer or similar devices to print cells into 3D patterns with a resolution comparable to the size of mammalian cells. Achieving such a resolution in vitro can lead to breakthroughs in areas such as organ transplantation. Although the feasibility of cell printing has been demonstrated recently, the printing resolution and cell viability remain to be improved. Here we investigate a unit operation in cell printing, namely, the impact of a cell-laden droplet into a pool of highly viscous liquids. The droplet and cell dynamics are quantified using both direct numerical simulation and scaling analysis. These studies indicate that although cell experienced significant stress during droplet impact, the duration of such stress is very short, which helps explain why many cells can survive the cell printing process. These studies also revealed that cell membrane can be temporarily ruptured during cell printing, which is supported by indirect experimental evidence.

MioLab, a rat cardiac contractile force simulator: Applications to teaching cardiac cell physiology and biophysics.

PubMed

da Silva, Robson Rodrigues; Bissaco, Marcia Aparecida Silva; Goroso, Daniel Gustavo

2015-12-01

Understanding the basic concepts of physiology and biophysics of cardiac cells can be improved by virtual experiments that illustrate the complex excitation-contraction coupling process in cardiac cells. The aim of this study is to propose a rat cardiac myocyte simulator, with which calcium dynamics in excitation-contraction coupling of an isolated cell can be observed. This model has been used in the course "Mathematical Modeling and Simulation of Biological Systems". In this paper we present the didactic utility of the simulator MioLab(®). The simulator enables virtual experiments that can help studying inhibitors and activators in the sarcoplasmic reticulum sodium-calcium exchanger, thus corroborating a better understanding of the effects of medications, which are used to treat arrhythmias, on these compartments. The graphical interfaces were developed not only to facilitate the use of the simulator, but also to promote a constructive learning on the subject, since there are animations and videos for each stage of the simulation. The effectiveness of the simulator was tested by a group of graduate students. Some examples of simulations were presented in order to describe the overall structure of the simulator. Part of these virtual experiments became an activity for Biomedical Engineering graduate students, who evaluated the simulator based on its didactic quality. As a result, students answered a questionnaire on the usability and functionality of the simulator as a teaching tool. All students performed the proposed activities and classified the simulator as an optimal or good learning tool. In their written questions, students indicated as negative characteristics some problems with visualizing graphs; as positive characteristics, they indicated the simulator's didactic function, especially tutorials and videos on the topic of this study. The results show that the simulator complements the study of the physiology and biophysics of the cardiac cell. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Combining cell-based hydrodynamics with hybrid particle-field simulations: efficient and realistic simulation of structuring dynamics.

PubMed

Sevink, G J A; Schmid, F; Kawakatsu, T; Milano, G

2017-02-22

We have extended an existing hybrid MD-SCF simulation technique that employs a coarsening step to enhance the computational efficiency of evaluating non-bonded particle interactions. This technique is conceptually equivalent to the single chain in mean-field (SCMF) method in polymer physics, in the sense that non-bonded interactions are derived from the non-ideal chemical potential in self-consistent field (SCF) theory, after a particle-to-field projection. In contrast to SCMF, however, MD-SCF evolves particle coordinates by the usual Newton's equation of motion. Since collisions are seriously affected by the softening of non-bonded interactions that originates from their evaluation at the coarser continuum level, we have devised a way to reinsert the effect of collisions on the structural evolution. Merging MD-SCF with multi-particle collision dynamics (MPCD), we mimic particle collisions at the level of computational cells and at the same time properly account for the momentum transfer that is important for a realistic system evolution. The resulting hybrid MD-SCF/MPCD method was validated for a particular coarse-grained model of phospholipids in aqueous solution, against reference full-particle simulations and the original MD-SCF model. We additionally implemented and tested an alternative and more isotropic finite difference gradient. Our results show that efficiency is improved by merging MD-SCF with MPCD, as properly accounting for hydrodynamic interactions considerably speeds up the phase separation dynamics, with negligible additional computational costs compared to efficient MD-SCF. This new method enables realistic simulations of large-scale systems that are needed to investigate the applications of self-assembled structures of lipids in nanotechnologies.

Consistent kinetic simulation of plasma and sputtering in low temperature plasmas

NASA Astrophysics Data System (ADS)

Schmidt, Frederik; Trieschmann, Jan; Mussenbrock, Thomas

2016-09-01

Plasmas are commonly used in sputtering applications for the deposition of thin films. Although magnetron sources are a prominent choice, capacitively coupled plasmas have certain advantages (e.g., sputtering of non-conducting and/or ferromagnetic materials, aside of excellent control of the ion energy distribution). In order to understand the collective plasma and sputtering dynamics, a kinetic simulation model is helpful. Particle-in-Cell has been proven to be successful in simulating the plasma dynamics, while the Test-Multi-Particle-Method can be used to describe the sputtered neutral species. In this talk a consistent combination of these methods is presented by consistently coupling the simulated ion flux as input to a neutral particle transport model. The combined model is used to simulate and discuss the spatially dependent densities, fluxes and velocity distributions of all particles. This work is supported by the German Research Foundation (DFG) in the frame of Transregional Collaborative Research Center (SFB) TR-87.

Structural Properties of Human IAPP Dimer in Membrane Environment Studied by All-Atom Molecular Dynamics Simulations.

PubMed

Liu, Na; Duan, Mojie; Yang, Minghui

2017-08-11

The aggregation of human islet amyloid polypeptide (hIAPP) can damage the membrane of the β-cells in the pancreatic islets and induce type 2 diabetes (T2D). Growing evidences indicated that the major toxic species are small oligomers of IAPP. Due to the fast aggregation nature, it is hard to characterize the structures of IAPP oligomers by experiments, especially in the complex membrane environment. On the other side, molecular dynamics simulation can provide atomic details of the structure and dynamics of the aggregation of IAPP. In this study, all-atom bias-exchange metadynamics (BE-Meta) and unbiased molecular dynamics simulations were employed to study the structural properties of IAPP dimer in the membranes environments. A number of intermediates, including α-helical states, β-sheet states, and fully disordered states, are identified. The formation of N-terminal β-sheet structure is prior to the C-terminal β-sheet structure towards the final fibril-like structures. The α-helical intermediates have lower propensity in the dimeric hIAPP and are off-pathway intermediates. The simulations also demonstrate that the β-sheet intermediates induce more perturbation on the membrane than the α-helical and disordered states and thus pose higher disruption ability.

Matching the reaction-diffusion simulation to dynamic [18F]FMISO PET measurements in tumors: extension to a flow-limited oxygen-dependent model.

PubMed

Shi, Kuangyu; Bayer, Christine; Gaertner, Florian C; Astner, Sabrina T; Wilkens, Jan J; Nüsslin, Fridtjof; Vaupel, Peter; Ziegler, Sibylle I

2017-02-01

Positron-emission tomography (PET) with hypoxia specific tracers provides a noninvasive method to assess the tumor oxygenation status. Reaction-diffusion models have advantages in revealing the quantitative relation between in vivo imaging and the tumor microenvironment. However, there is no quantitative comparison of the simulation results with the real PET measurements yet. The lack of experimental support hampers further applications of computational simulation models. This study aims to compare the simulation results with a preclinical [ 18 F]FMISO PET study and to optimize the reaction-diffusion model accordingly. Nude mice with xenografted human squamous cell carcinomas (CAL33) were investigated with a 2 h dynamic [ 18 F]FMISO PET followed by immunofluorescence staining using the hypoxia marker pimonidazole and the endothelium marker CD 31. A large data pool of tumor time-activity curves (TAC) was simulated for each mouse by feeding the arterial input function (AIF) extracted from experiments into the model with different configurations of the tumor microenvironment. A measured TAC was considered to match a simulated TAC when the difference metric was below a certain, noise-dependent threshold. As an extension to the well-established Kelly model, a flow-limited oxygen-dependent (FLOD) model was developed to improve the matching between measurements and simulations. The matching rate between the simulated TACs of the Kelly model and the mouse PET data ranged from 0 to 28.1% (on average 9.8%). By modifying the Kelly model to an FLOD model, the matching rate between the simulation and the PET measurements could be improved to 41.2-84.8% (on average 64.4%). Using a simulation data pool and a matching strategy, we were able to compare the simulated temporal course of dynamic PET with in vivo measurements. By modifying the Kelly model to a FLOD model, the computational simulation was able to approach the dynamic [ 18 F]FMISO measurements in the investigated tumors.

SR-XRD in situ monitoring of copper-IUD corrosion in simulated uterine fluid using a portable spectroelectrochemical cell.

PubMed

Grayburn, Rosie A; Dowsett, Mark G; Sabbe, Pieter-Jan; Wermeille, Didier; Anjos, Jorge Alves; Flexer, Victoria; De Keersmaecker, Michel; Wildermeersch, Dirk; Adriaens, Annemie

2016-08-01

The objective of this work is to study the initial corrosion of copper in the presence of gold when placed in simulated uterine fluid in order to better understand the evolution of active components of copper-IUDs. In order to carry out this study, a portable cell was designed to partially simulate the uterine environment and provide a way of tracking the chemical changes occurring in the samples in situ within a controlled environment over a long period of time using synchrotron spectroelectrochemistry. The dynamically forming crystalline corrosion products are determined in situ for a range of copper-gold surface ratios over the course of a 10-day experiment in the cell. It is concluded that the insoluble deposits forming over this time are not the origin of the anticonception mechanism. Copyright © 2016 Elsevier B.V. All rights reserved.

Hadley cell dynamics of a cold and virtually dry Snowball Earth atmosphere

NASA Astrophysics Data System (ADS)

Voigt, Aiko; Held, Isaac; Marotzke, Jochem

2010-05-01

We use the full-physics atmospheric general circulation model ECHAM5 to investigate a cold and virtually dry Snowball Earth atmosphere that results from specifying sea ice as the surface boundary condition everywhere, corresponding to a frozen aquaplanet, while keeping total solar irradiance at its present-day value of 1365 Wm-2. The aim of this study is the investigation of the zonal-mean circulation of a Snowball Earth atmosphere, which, due to missing moisture, might constitute an ideal though yet unexplored testbed for theories of atmospheric dynamics. To ease comparison with theories, incoming solar insolation follows permanent equinox conditions with disabled diurnal cycle. The meridional circulation consists of a thermally direct cell extending from the equator to 45 N/S with ascent in the equatorial region, and a weak thermally indirect cell with descent between 45 and 65 N/S and ascent in the polar region. The former cell corresponds to the present-day Earth's Hadley cell, while the latter can be viewed as an eddy-driven Ferrell cell; the present-day Earth's direct polar cell is missing. The Hadley cell itself is subdivided into a vigorous cell confined to the troposphere and a weak deep cell reaching well into the stratosphere. The dynamics of the vigorous Snowball Earth Hadley cell differ substantially from the dynamics of the present-day Hadley cell. The zonal momentum balance shows that in the poleward branch of the vigorous Hadley cell, mean flow meridional advection of absolute vorticity is not only balanced by eddy momentum flux convergence but also by vertical diffusion. Inside the poleward branch, eddies are more important in the upper part and vertical diffusion is more important in the lower part. Vertical diffusion also contributes to the meridional momentum balance as it decelerates the vigorous Hadley cell by downgradient momentum mixing between its poleward and equatorward branch. Zonal winds, therefore, are not in thermal wind balance in the vigorous Hadley cell. Suppressing vertical momentum diffusion above 870 hPa results in a doubling of the vigorous Hadley cell strength. Simulations where we only suppress either vertical diffusion of zonal or meridional momentum show that this doubling can be understood from the decelerating effect of vertical diffusion in the meridional momentum balance. Comparing our simulations with theories, we conclude that neither the axisymmetric Hadley cell model of Held & Hou (1980) nor the eddy-permitting model of T. Schneider et al. (2005, 2006, 2008) are applicable to a Snowball Earth atmosphere since both assume an inviscid upper Hadley cell branch.

Voltage instability in a simulated fuel cell stack correlated to cathode water accumulation

NASA Astrophysics Data System (ADS)

Owejan, J. P.; Trabold, T. A.; Gagliardo, J. J.; Jacobson, D. L.; Carter, R. N.; Hussey, D. S.; Arif, M.

Single fuel cells running independently are often used for fundamental studies of water transport. It is also necessary to assess the dynamic behavior of fuel cell stacks comprised of multiple cells arranged in series, thus providing many paths for flow of reactant hydrogen on the anode and air (or pure oxygen) on the cathode. In the current work, the flow behavior of a fuel cell stack is simulated by using a single-cell test fixture coupled with a bypass flow loop for the cathode flow. This bypass simulates the presence of additional cells in a stack and provides an alternate path for airflow, thus avoiding forced convective purging of cathode flow channels. Liquid water accumulation in the cathode is shown to occur in two modes; initially nearly all the product water is retained in the gas diffusion layer until a critical saturation fraction is reached and then water accumulation in the flow channels begins. Flow redistribution and fuel cell performance loss result from channel slug formation. The application of in-situ neutron radiography affords a transient correlation of performance loss to liquid water accumulation. The current results identify a mechanism whereby depleted cathode flow on a single cell leads to performance loss, which can ultimately cause an operating proton exchange membrane fuel cell stack to fail.

Obtaining a Pragmatic Representation of Fire Disturbance in Dynamic Vegetation Models by Assimilating Earth Observation Data

NASA Astrophysics Data System (ADS)

Kantzas, Euripides; Quegan, Shaun

2015-04-01

Fire constitutes a violent and unpredictable pathway of carbon from the terrestrial biosphere into the atmosphere. Despite fire emissions being in many biomes of similar magnitude to that of Net Ecosystem Exchange, even the most complex Dynamic Vegetation Models (DVMs) embedded in IPCC General Circulation Models poorly represent fire behavior and dynamics, a fact which still remains understated. As DVMs operate on a deterministic, grid cell-by-grid cell basis they are unable to describe a host of important fire characteristics such as its propagation, magnitude of area burned and stochastic nature. Here we address these issues by describing a model-independent methodology which assimilates Earth Observation (EO) data by employing image analysis techniques and algorithms to offer a realistic fire disturbance regime in a DVM. This novel approach, with minimum model restructuring, manages to retain the Fire Return Interval produced by the model whilst assigning pragmatic characteristics to its fire outputs thus allowing realistic simulations of fire-related processes such as carbon injection into the atmosphere and permafrost degradation. We focus our simulations in the Arctic and specifically Canada and Russia and we offer a snippet of how this approach permits models to engage in post-fire dynamics hitherto absent from any other model regardless of complexity.

Effects of aging in catastrophe on the steady state and dynamics of a microtubule population

NASA Astrophysics Data System (ADS)

Jemseena, V.; Gopalakrishnan, Manoj

2015-05-01

Several independent observations have suggested that the catastrophe transition in microtubules is not a first-order process, as is usually assumed. Recent in vitro observations by Gardner et al. [M. K. Gardner et al., Cell 147, 1092 (2011), 10.1016/j.cell.2011.10.037] showed that microtubule catastrophe takes place via multiple steps and the frequency increases with the age of the filament. Here we investigate, via numerical simulations and mathematical calculations, some of the consequences of the age dependence of catastrophe on the dynamics of microtubules as a function of the aging rate, for two different models of aging: exponential growth, but saturating asymptotically, and purely linear growth. The boundary demarcating the steady-state and non-steady-state regimes in the dynamics is derived analytically in both cases. Numerical simulations, supported by analytical calculations in the linear model, show that aging leads to nonexponential length distributions in steady state. More importantly, oscillations ensue in microtubule length and velocity. The regularity of oscillations, as characterized by the negative dip in the autocorrelation function, is reduced by increasing the frequency of rescue events. Our study shows that the age dependence of catastrophe could function as an intrinsic mechanism to generate oscillatory dynamics in a microtubule population, distinct from hitherto identified ones.

Transport and collision dynamics in periodic asymmetric obstacle arrays: Rational design of microfluidic rare-cell immunocapture devices

NASA Astrophysics Data System (ADS)

Gleghorn, Jason P.; Smith, James P.; Kirby, Brian J.

2013-09-01

Microfluidic obstacle arrays have been used in numerous applications, and their ability to sort particles or capture rare cells from complex samples has broad and impactful applications in biology and medicine. We have investigated the transport and collision dynamics of particles in periodic obstacle arrays to guide the design of convective, rather than diffusive, transport-based immunocapture microdevices. Ballistic and full computational fluid dynamics simulations are used to understand the collision modes that evolve in cylindrical obstacle arrays with various geometries. We identify previously unrecognized collision mode structures and differential size-based collision frequencies that emerge from these arrays. Previous descriptions of transverse displacements that assume unidirectional flow in these obstacle arrays cannot capture mode transitions properly as these descriptions fail to capture the dependence of the mode transitions on column spacing and the attendant change in the flow field. Using these analytical and computational simulations, we elucidate design parameters that induce high collision rates for all particles larger than a threshold size or selectively increase collision frequencies for a narrow range of particle sizes within a polydisperse population. Furthermore, we investigate how the particle Péclet number affects collision dynamics and mode transitions and demonstrate that experimental observations from various obstacle array geometries are well described by our computational model.

Feasibility study of solid oxide fuel cell engines integrated with sprinter gas turbines: Modeling, design and control

NASA Astrophysics Data System (ADS)

Jia, Zhenzhong; Sun, Jing; Dobbs, Herb; King, Joel

2015-02-01

Conventional recuperating solid oxide fuel cell (SOFC)/gas turbine (GT) system suffers from its poor dynamic capability and load following performance. To meet the fast, safe and efficient load following requirements for mobile applications, a sprinter SOFC/GT system concept is proposed in this paper. In the proposed system, an SOFC stack operating at fairly constant temperature provides the baseline power with high efficiency while the fast dynamic capability of the GT-generator is fully explored for fast dynamic load following. System design and control studies have been conducted by using an SOFC/GT system model consisting of experimentally-verified component models. In particular, through analysis of the steady-state simulation results, an SOFC operation strategy is proposed to maintain fairly constant SOFC power (less than 2% power variation) and temperature (less than 2 K temperature variation) over the entire load range. A system design procedure well-suited to the proposed system has also been developed to help determining component sizes and the reference steady-state operation line. In addition, control analysis has been studied for both steady-state and transient operations. Simulation results suggest that the proposed system holds the promise to achieve fast and safe transient operations by taking full advantage of the fast dynamics of the GT-generator.

Role of dynamic capsomere supply for viral capsid self-assembly

NASA Astrophysics Data System (ADS)

Boettcher, Marvin A.; Klein, Heinrich C. R.; Schwarz, Ulrich S.

2015-02-01

Many viruses rely on the self-assembly of their capsids to protect and transport their genomic material. For many viral systems, in particular for human viruses like hepatitis B, adeno or human immunodeficiency virus, that lead to persistent infections, capsomeres are continuously produced in the cytoplasm of the host cell while completed capsids exit the cell for a new round of infection. Here we use coarse-grained Brownian dynamics simulations of a generic patchy particle model to elucidate the role of the dynamic supply of capsomeres for the reversible self-assembly of empty T1 icosahedral virus capsids. We find that for high rates of capsomere influx only a narrow range of bond strengths exists for which a steady state of continuous capsid production is possible. For bond strengths smaller and larger than this optimal value, the reaction volume becomes crowded by small and large intermediates, respectively. For lower rates of capsomere influx a broader range of bond strengths exists for which a steady state of continuous capsid production is established, although now the production rate of capsids is smaller. Thus our simulations suggest that the importance of an optimal bond strength for viral capsid assembly typical for in vitro conditions can be reduced by the dynamic influx of capsomeres in a cellular environment.

Large-Scale Conformational Changes of Trypanosoma cruzi Proline Racemase Predicted by Accelerated Molecular Dynamics Simulation

PubMed Central

McCammon, J. Andrew

2011-01-01

Chagas' disease, caused by the protozoan parasite Trypanosoma cruzi (T. cruzi), is a life-threatening illness affecting 11–18 million people. Currently available treatments are limited, with unacceptable efficacy and safety profiles. Recent studies have revealed an essential T. cruzi proline racemase enzyme (TcPR) as an attractive candidate for improved chemotherapeutic intervention. Conformational changes associated with substrate binding to TcPR are believed to expose critical residues that elicit a host mitogenic B-cell response, a process contributing to parasite persistence and immune system evasion. Characterization of the conformational states of TcPR requires access to long-time-scale motions that are currently inaccessible by standard molecular dynamics simulations. Here we describe advanced accelerated molecular dynamics that extend the effective simulation time and capture large-scale motions of functional relevance. Conservation and fragment mapping analyses identified potential conformational epitopes located in the vicinity of newly identified transient binding pockets. The newly identified open TcPR conformations revealed by this study along with knowledge of the closed to open interconversion mechanism advances our understanding of TcPR function. The results and the strategy adopted in this work constitute an important step toward the rationalization of the molecular basis behind the mitogenic B-cell response of TcPR and provide new insights for future structure-based drug discovery. PMID:22022240

Large-scale conformational changes of Trypanosoma cruzi proline racemase predicted by accelerated molecular dynamics simulation.

PubMed

de Oliveira, César Augusto F; Grant, Barry J; Zhou, Michelle; McCammon, J Andrew

2011-10-01

Chagas' disease, caused by the protozoan parasite Trypanosoma cruzi (T. cruzi), is a life-threatening illness affecting 11-18 million people. Currently available treatments are limited, with unacceptable efficacy and safety profiles. Recent studies have revealed an essential T. cruzi proline racemase enzyme (TcPR) as an attractive candidate for improved chemotherapeutic intervention. Conformational changes associated with substrate binding to TcPR are believed to expose critical residues that elicit a host mitogenic B-cell response, a process contributing to parasite persistence and immune system evasion. Characterization of the conformational states of TcPR requires access to long-time-scale motions that are currently inaccessible by standard molecular dynamics simulations. Here we describe advanced accelerated molecular dynamics that extend the effective simulation time and capture large-scale motions of functional relevance. Conservation and fragment mapping analyses identified potential conformational epitopes located in the vicinity of newly identified transient binding pockets. The newly identified open TcPR conformations revealed by this study along with knowledge of the closed to open interconversion mechanism advances our understanding of TcPR function. The results and the strategy adopted in this work constitute an important step toward the rationalization of the molecular basis behind the mitogenic B-cell response of TcPR and provide new insights for future structure-based drug discovery.

Fluid models and simulations of biological cell phenomena

NASA Technical Reports Server (NTRS)

Greenspan, H. P.

1982-01-01

The dynamics of coated droplets are examined within the context of biofluids. Of specific interest is the manner in which the shape of a droplet, the motion within it as well as that of aggregates of droplets can be controlled by the modulation of surface properties and the extent to which such fluid phenomena are an intrinsic part of cellular processes. From the standpoint of biology, an objective is to elucidate some of the general dynamical features that affect the disposition of an entire cell, cell colonies and tissues. Conventionally averaged field variables of continuum mechanics are used to describe the overall global effects which result from the myriad of small scale molecular interactions. An attempt is made to establish cause and effect relationships from correct dynamical laws of motion rather than by what may have been unnecessary invocation of metabolic or life processes. Several topics are discussed where there are strong analogies droplets and cells including: encapsulated droplets/cell membranes; droplet shape/cell shape; adhesion and spread of a droplet/cell motility and adhesion; and oams and multiphase flows/cell aggregates and tissues. Evidence is presented to show that certain concepts of continuum theory such as suface tension, surface free energy, contact angle, bending moments, etc. are relevant and applicable to the study of cell biology.

Equivalent circuit-based analysis of CMUT cell dynamics in arrays.

PubMed

Oguz, H K; Atalar, Abdullah; Köymen, Hayrettin

2013-05-01

Capacitive micromachined ultrasonic transducers (CMUTs) are usually composed of large arrays of closely packed cells. In this work, we use an equivalent circuit model to analyze CMUT arrays with multiple cells. We study the effects of mutual acoustic interactions through the immersion medium caused by the pressure field generated by each cell acting upon the others. To do this, all the cells in the array are coupled through a radiation impedance matrix at their acoustic terminals. An accurate approximation for the mutual radiation impedance is defined between two circular cells, which can be used in large arrays to reduce computational complexity. Hence, a performance analysis of CMUT arrays can be accurately done with a circuit simulator. By using the proposed model, one can very rapidly obtain the linear frequency and nonlinear transient responses of arrays with an arbitrary number of CMUT cells. We performed several finite element method (FEM) simulations for arrays with small numbers of cells and showed that the results are very similar to those obtained by the equivalent circuit model.

Active Signal Propagation and Imaging Using Vortex Beams

DTIC Science & Technology

2014-08-01

Though this method of OV beam generation allows dynamic control it also results in poor power conversion efficiency (~< 15%) and relatively low power...rectangular quart cell (1cm x 10 cm x 10cm). Various TM conditions are simulated inside the cell by diluting deionized water with polystyrene spheres...c). Both beams were then focused into a 1cm x 1cm x 10cm glass cell comprising a solution of latex spheres and ionized water . Different particle

Dynamics of myosin II organization into cortical contractile networks and fibers

NASA Astrophysics Data System (ADS)

Nie, Wei; Wei, Ming-Tzo; Ou-Yang, Daniel; Jedlicka, Sabrina; Vavylonis, Dimitrios

2014-03-01

The morphology of adhered cells critically depends on the formation of a contractile meshwork of parallel and cross-linked stress fibers along the contacting surface. The motor activity and mini-filament assembly of non-muscle myosin II is an important component of cell-level cytoskeletal remodeling during mechanosensing. To monitor the dynamics of myosin II, we used confocal microscopy to image cultured HeLa cells that stably express myosin regulatory light chain tagged with GFP (MRLC-GFP). MRLC-GFP was monitored in time-lapse movies at steady state and during the response of cells to varying concentrations of blebbistatin which disrupts actomyosin stress fibers. Using image correlation spectroscopy analysis, we quantified the kinetics of disassembly and reassembly of actomyosin networks and compared them to studies by other groups. This analysis suggested that the following processes contribute to the assembly of cortical actomyosin into fibers: random myosin mini-filament assembly and disassembly along the cortex; myosin mini-filament aligning and contraction; stabilization of cortical myosin upon increasing contractile tension. We developed simple numerical simulations that include those processes. The results of simulations of cells at steady state and in response to blebbistatin capture some of the main features observed in the experiments. This study provides a framework to help interpret how different cortical myosin remodeling kinetics may contribute to different cell shape and rigidity depending on substrate stiffness.

Synthetic Biology Outside the Cell: Linking Computational Tools to Cell-Free Systems

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

Lewis, Daniel D.; Department of Biomedical Engineering, University of California Davis, Davis, CA; Villarreal, Fernando D.

As mathematical models become more commonly integrated into the study of biology, a common language for describing biological processes is manifesting. Many tools have emerged for the simulation of in vivo synthetic biological systems, with only a few examples of prominent work done on predicting the dynamics of cell-free synthetic systems. At the same time, experimental biologists have begun to study dynamics of in vitro systems encapsulated by amphiphilic molecules, opening the door for the development of a new generation of biomimetic systems. In this review, we explore both in vivo and in vitro models of biochemical networks with amore » special focus on tools that could be applied to the construction of cell-free expression systems. We believe that quantitative studies of complex cellular mechanisms and pathways in synthetic systems can yield important insights into what makes cells different from conventional chemical systems.« less

Synthetic Biology Outside the Cell: Linking Computational Tools to Cell-Free Systems

PubMed Central

Lewis, Daniel D.; Villarreal, Fernando D.; Wu, Fan; Tan, Cheemeng

2014-01-01

As mathematical models become more commonly integrated into the study of biology, a common language for describing biological processes is manifesting. Many tools have emerged for the simulation of in vivo synthetic biological systems, with only a few examples of prominent work done on predicting the dynamics of cell-free synthetic systems. At the same time, experimental biologists have begun to study dynamics of in vitro systems encapsulated by amphiphilic molecules, opening the door for the development of a new generation of biomimetic systems. In this review, we explore both in vivo and in vitro models of biochemical networks with a special focus on tools that could be applied to the construction of cell-free expression systems. We believe that quantitative studies of complex cellular mechanisms and pathways in synthetic systems can yield important insights into what makes cells different from conventional chemical systems. PMID:25538941

Synthetic biology outside the cell: linking computational tools to cell-free systems.

PubMed

Lewis, Daniel D; Villarreal, Fernando D; Wu, Fan; Tan, Cheemeng

2014-01-01

As mathematical models become more commonly integrated into the study of biology, a common language for describing biological processes is manifesting. Many tools have emerged for the simulation of in vivo synthetic biological systems, with only a few examples of prominent work done on predicting the dynamics of cell-free synthetic systems. At the same time, experimental biologists have begun to study dynamics of in vitro systems encapsulated by amphiphilic molecules, opening the door for the development of a new generation of biomimetic systems. In this review, we explore both in vivo and in vitro models of biochemical networks with a special focus on tools that could be applied to the construction of cell-free expression systems. We believe that quantitative studies of complex cellular mechanisms and pathways in synthetic systems can yield important insights into what makes cells different from conventional chemical systems.

CPV cells cooling system based on submerged jet impingement: CFD modeling and experimental validation

NASA Astrophysics Data System (ADS)

Montorfano, Davide; Gaetano, Antonio; Barbato, Maurizio C.; Ambrosetti, Gianluca; Pedretti, Andrea

2014-09-01

Concentrating photovoltaic (CPV) cells offer higher efficiencies with regard to the PV ones and allow to strongly reduce the overall solar cell area. However, to operate correctly and exploit their advantages, their temperature has to be kept low and as uniform as possible and the cooling circuit pressure drops need to be limited. In this work an impingement water jet cooling system specifically designed for an industrial HCPV receiver is studied. Through the literature and by means of accurate computational fluid dynamics (CFD) simulations, the nozzle to plate distance, the number of jets and the nozzle pitch, i.e. the distance between adjacent jets, were optimized. Afterwards, extensive experimental tests were performed to validate pressure drops and cooling power simulation results.

Bridging the gap between computation and clinical biology: validation of cable theory in humans

PubMed Central

Finlay, Malcolm C.; Xu, Lei; Taggart, Peter; Hanson, Ben; Lambiase, Pier D.

2013-01-01

Introduction: Computerized simulations of cardiac activity have significantly contributed to our understanding of cardiac electrophysiology, but techniques of simulations based on patient-acquired data remain in their infancy. We sought to integrate data acquired from human electrophysiological studies into patient-specific models, and validated this approach by testing whether electrophysiological responses to sequential premature stimuli could be predicted in a quantitatively accurate manner. Methods: Eleven patients with structurally normal hearts underwent electrophysiological studies. Semi-automated analysis was used to reconstruct activation and repolarization dynamics for each electrode. This S2 extrastimuli data was used to inform individualized models of cardiac conduction, including a novel derivation of conduction velocity restitution. Activation dynamics of multiple premature extrastimuli were then predicted from this model and compared against measured patient data as well as data derived from the ten-Tusscher cell-ionic model. Results: Activation dynamics following a premature S3 were significantly different from those after an S2. Patient specific models demonstrated accurate prediction of the S3 activation wave, (Pearson's R2 = 0.90, median error 4%). Examination of the modeled conduction dynamics allowed inferences into the spatial dispersion of activation delay. Further validation was performed against data from the ten-Tusscher cell-ionic model, with our model accurately recapitulating predictions of repolarization times (R2 = 0.99). Conclusions: Simulations based on clinically acquired data can be used to successfully predict complex activation patterns following sequential extrastimuli. Such modeling techniques may be useful as a method of incorporation of clinical data into predictive models. PMID:24027527

Glycosylated linkers in multimodular lignocellulose-degrading enzymes dynamically bind to cellulose

PubMed Central

Payne, Christina M.; Resch, Michael G.; Chen, Liqun; Crowley, Michael F.; Himmel, Michael E.; Taylor, Larry E.; Sandgren, Mats; Ståhlberg, Jerry; Stals, Ingeborg; Tan, Zhongping; Beckham, Gregg T.

2013-01-01

Plant cell-wall polysaccharides represent a vast source of food in nature. To depolymerize polysaccharides to soluble sugars, many organisms use multifunctional enzyme mixtures consisting of glycoside hydrolases, lytic polysaccharide mono-oxygenases, polysaccharide lyases, and carbohydrate esterases, as well as accessory, redox-active enzymes for lignin depolymerization. Many of these enzymes that degrade lignocellulose are multimodular with carbohydrate-binding modules (CBMs) and catalytic domains connected by flexible, glycosylated linkers. These linkers have long been thought to simply serve as a tether between structured domains or to act in an inchworm-like fashion during catalytic action. To examine linker function, we performed molecular dynamics (MD) simulations of the Trichoderma reesei Family 6 and Family 7 cellobiohydrolases (TrCel6A and TrCel7A, respectively) bound to cellulose. During these simulations, the glycosylated linkers bind directly to cellulose, suggesting a previously unknown role in enzyme action. The prediction from the MD simulations was examined experimentally by measuring the binding affinity of the Cel7A CBM and the natively glycosylated Cel7A CBM-linker. On crystalline cellulose, the glycosylated linker enhances the binding affinity over the CBM alone by an order of magnitude. The MD simulations before and after binding of the linker also suggest that the bound linker may affect enzyme action due to significant damping in the enzyme fluctuations. Together, these results suggest that glycosylated linkers in carbohydrate-active enzymes, which are intrinsically disordered proteins in solution, aid in dynamic binding during the enzymatic deconstruction of plant cell walls. PMID:23959893

Electron-beam-ion-source (EBIS) modeling progress at FAR-TECH, Inc

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

Kim, J. S., E-mail: kim@far-tech.com; Zhao, L., E-mail: kim@far-tech.com; Spencer, J. A., E-mail: kim@far-tech.com

FAR-TECH, Inc. has been developing a numerical modeling tool for Electron-Beam-Ion-Sources (EBISs). The tool consists of two codes. One is the Particle-Beam-Gun-Simulation (PBGUNS) code to simulate a steady state electron beam and the other is the EBIS-Particle-In-Cell (EBIS-PIC) code to simulate ion charge breeding with the electron beam. PBGUNS, a 2D (r,z) electron gun and ion source simulation code, has been extended for efficient modeling of EBISs and the work was presented previously. EBIS-PIC is a space charge self-consistent PIC code and is written to simulate charge breeding in an axisymmetric 2D (r,z) device allowing for full three-dimensional ion dynamics.more » This 2D code has been successfully benchmarked with Test-EBIS measurements at Brookhaven National Laboratory. For long timescale (< tens of ms) ion charge breeding, the 2D EBIS-PIC simulations take a long computational time making the simulation less practical. Most of the EBIS charge breeding, however, may be modeled in 1D (r) as the axial dependence of the ion dynamics may be ignored in the trap. Where 1D approximations are valid, simulations of charge breeding in an EBIS over long time scales become possible, using EBIS-PIC together with PBGUNS. Initial 1D results are presented. The significance of the magnetic field to ion dynamics, ion cooling effects due to collisions with neutral gas, and the role of Coulomb collisions are presented.« less

A Simulation Tool for Dynamic Contrast Enhanced MRI

PubMed Central

Mauconduit, Franck; Christen, Thomas; Barbier, Emmanuel Luc

2013-01-01

The quantification of bolus-tracking MRI techniques remains challenging. The acquisition usually relies on one contrast and the analysis on a simplified model of the various phenomena that arise within a voxel, leading to inaccurate perfusion estimates. To evaluate how simplifications in the interstitial model impact perfusion estimates, we propose a numerical tool to simulate the MR signal provided by a dynamic contrast enhanced (DCE) MRI experiment. Our model encompasses the intrinsic and relaxations, the magnetic field perturbations induced by susceptibility interfaces (vessels and cells), the diffusion of the water protons, the blood flow, the permeability of the vessel wall to the the contrast agent (CA) and the constrained diffusion of the CA within the voxel. The blood compartment is modeled as a uniform compartment. The different blocks of the simulation are validated and compared to classical models. The impact of the CA diffusivity on the permeability and blood volume estimates is evaluated. Simulations demonstrate that the CA diffusivity slightly impacts the permeability estimates ( for classical blood flow and CA diffusion). The effect of long echo times is investigated. Simulations show that DCE-MRI performed with an echo time may already lead to significant underestimation of the blood volume (up to 30% lower for brain tumor permeability values). The potential and the versatility of the proposed implementation are evaluated by running the simulation with realistic vascular geometry obtained from two photons microscopy and with impermeable cells in the extravascular environment. In conclusion, the proposed simulation tool describes DCE-MRI experiments and may be used to evaluate and optimize acquisition and processing strategies. PMID:23516414

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

Som, Sibendu; Wang, Zihan; Pei, Yuanjiang

A state-of-the-art spray modeling methodology, recently presented by Senecal et al. [ , , ], is applied to Large Eddy Simulations (LES) of vaporizing gasoline sprays. Simulations of non-combusting Spray G (gasoline fuel) from the Engine Combustion Network are performed. Adaptive mesh refinement (AMR) with cell sizes from 0.09 mm to 0.5 mm are utilized to further demonstrate grid convergence of the dynamic structure LES model for the gasoline sprays. Grid settings are recommended to optimize the accuracy/runtime tradeoff for LES-based spray simulations at different injection pressure conditions typically encountered in gasoline direct injection (GDI) applications. The influence of LESmore » sub-grid scale (SGS) models is explored by comparing the results from dynamic structure and Smagorinsky based models against simulations without any SGS model. Twenty different realizations are simulated by changing the random number seed used in the spray sub-models. It is shown that for global quantities such as spray penetration, comparing a single LES simulation to experimental data is reasonable. Through a detailed analysis using the relevance index (RI) criteria, recommendations are made regarding the minimum number of LES realizations required for accurate prediction of the gasoline sprays.« less

Potential toxicity of graphene to cell functions via disrupting protein-protein interactions.

PubMed

Luan, Binquan; Huynh, Tien; Zhao, Lin; Zhou, Ruhong

2015-01-27

While carbon-based nanomaterials such as graphene and carbon nanotubes (CNTs) have become popular in state-of-the-art nanotechnology, their biological safety and underlying molecular mechanism is still largely unknown. Experimental studies have been focused at the cellular level and revealed good correlations between cell's death and the application of CNTs or graphene. Using large-scale all-atom molecular dynamics simulations, we theoretically investigate the potential toxicity of graphene to a biological cell at molecular level. Simulation results show that the hydrophobic protein-protein interaction (or recognition) that is essential to biological functions can be interrupted by a graphene nanosheet. Due to the hydrophobic nature of graphene, it is energetically favorable for a graphene nanosheet to enter the hydrophobic interface of two contacting proteins, such as a dimer. The forced separation of two functional proteins can disrupt the cell's metabolism and even lead to the cell's mortality.

Bonded-cell model for particle fracture.

PubMed

Nguyen, Duc-Hanh; Azéma, Emilien; Sornay, Philippe; Radjai, Farhang

2015-02-01

Particle degradation and fracture play an important role in natural granular flows and in many applications of granular materials. We analyze the fracture properties of two-dimensional disklike particles modeled as aggregates of rigid cells bonded along their sides by a cohesive Mohr-Coulomb law and simulated by the contact dynamics method. We show that the compressive strength scales with tensile strength between cells but depends also on the friction coefficient and a parameter describing cell shape distribution. The statistical scatter of compressive strength is well described by the Weibull distribution function with a shape parameter varying from 6 to 10 depending on cell shape distribution. We show that this distribution may be understood in terms of percolating critical intercellular contacts. We propose a random-walk model of critical contacts that leads to particle size dependence of the compressive strength in good agreement with our simulation data.

Anomalous dynamics of intruders in a crowded environment of mobile obstacles

PubMed Central

Sentjabrskaja, Tatjana; Zaccarelli, Emanuela; De Michele, Cristiano; Sciortino, Francesco; Tartaglia, Piero; Voigtmann, Thomas; Egelhaaf, Stefan U.; Laurati, Marco

2016-01-01

Many natural and industrial processes rely on constrained transport, such as proteins moving through cells, particles confined in nanocomposite materials or gels, individuals in highly dense collectives and vehicular traffic conditions. These are examples of motion through crowded environments, in which the host matrix may retain some glass-like dynamics. Here we investigate constrained transport in a colloidal model system, in which dilute small spheres move in a slowly rearranging, glassy matrix of large spheres. Using confocal differential dynamic microscopy and simulations, here we discover a critical size asymmetry, at which anomalous collective transport of the small particles appears, manifested as a logarithmic decay of the density autocorrelation functions. We demonstrate that the matrix mobility is central for the observed anomalous behaviour. These results, crucially depending on size-induced dynamic asymmetry, are of relevance for a wide range of phenomena ranging from glassy systems to cell biology. PMID:27041068

A coarse-grained model of microtubule self-assembly

NASA Astrophysics Data System (ADS)

Regmi, Chola; Cheng, Shengfeng

Microtubules play critical roles in cell structures and functions. They also serve as a model system to stimulate the next-generation smart, dynamic materials. A deep understanding of their self-assembly process and biomechanical properties will not only help elucidate how microtubules perform biological functions, but also lead to exciting insight on how microtubule dynamics can be altered or even controlled for specific purposes such as suppressing the division of cancer cells. Combining all-atom molecular dynamics (MD) simulations and the essential dynamics coarse-graining method, we construct a coarse-grained (CG) model of the tubulin protein, which is the building block of microtubules. In the CG model a tubulin dimer is represented as an elastic network of CG sites, the locations of which are determined by examining the protein dynamics of the tubulin and identifying the essential dynamic domains. Atomistic MD modeling is employed to directly compute the tubulin bond energies in the surface lattice of a microtubule, which are used to parameterize the interactions between CG building blocks. The CG model is then used to study the self-assembly pathways, kinetics, dynamics, and nanomechanics of microtubules.

Exploration of factors affecting the onset and maturation course of follicular lymphoma through simulations of the germinal center.

PubMed

Fenwick, Michael K; Escobedo, Fernando A

2009-08-01

Genetic mutations frequently observed in human follicular lymphoma (FL) B-cells result in aberrant expression of the anti-apoptotic protein bcl-2 and surface immunoglobulins (Igs) which display one or more novel variable (V) region N-glycosylation motifs. In the present study, we develop a simulation model of the germinal center (GC) to explore how these mutations might influence the emergence and clonal expansion of key mutants which provoke FL development. The simulations employ a stochastic method for calculating the cellular dynamics, which incorporates actual IgV region sequences and a simplified hypermutation scheme. We first bring our simulations into agreement with experimental data for well-characterized normal and bcl-2(+) anti-hapten GC responses in mice to provide a model for understanding how bcl-2 expression leads to permissive selection and memory cell differentiation of weakly competitive B-cells. However, as bcl-2 expression in the GC alone is thought to be insufficient for FL development, we next monitor simulated IgV region mutations to determine the emergence times of key mutants displaying aberrant N-glycosylation motifs recurrently observed in human FL IgV regions. Simulations of 26 germline V(H) gene segments indicate that particular IgV regions have a dynamical selective advantage by virtue of the speed with which one or more of their key sites can generate N-glycosylation motifs upon hypermutation. Separate calculations attribute the high occurrence frequency of such IgV regions in FL to an ability to produce key mutants at a fast enough rate to overcome stochastic processes in the GC that hinder clonal expansion. Altogether, these simulations characterize three pathways for FL maturation through positively selected N-glycosylations, namely, via one of two key sites within germline V(H) region gene segments, or via a site in the third heavy chain complementarity-determining region (CDR-H3) that is generated from VDJ recombination.

Frequent mechanical stress suppresses proliferation of mesenchymal stem cells from human bone marrow without loss of multipotency

NASA Astrophysics Data System (ADS)

Frank, Viktoria; Kaufmann, Stefan; Wright, Rebecca; Horn, Patrick; Yoshikawa, Hiroshi Y.; Wuchter, Patrick; Madsen, Jeppe; Lewis, Andrew L.; Armes, Steven P.; Ho, Anthony D.; Tanaka, Motomu

2016-04-01

Mounting evidence indicated that human mesenchymal stem cells (hMSCs) are responsive not only to biochemical but also to physical cues, such as substrate topography and stiffness. To simulate the dynamic structures of extracellular environments of the marrow in vivo, we designed a novel surrogate substrate for marrow derived hMSCs based on physically cross-linked hydrogels whose elasticity can be adopted dynamically by chemical stimuli. Under frequent mechanical stress, hMSCs grown on our hydrogel substrates maintain the expression of STRO-1 over 20 d, irrespective of the substrate elasticity. On exposure to the corresponding induction media, these cultured hMSCs can undergo adipogenesis and osteogenesis without requiring cell transfer onto other substrates. Moreover, we demonstrated that our surrogate substrate suppresses the proliferation of hMSCs by up to 90% without any loss of multiple lineage potential by changing the substrate elasticity every 2nd days. Such “dynamic in vitro niche” can be used not only for a better understanding of the role of dynamic mechanical stresses on the fate of hMSCs but also for the synchronized differentiation of adult stem cells to a specific lineage.

Microenvironmental independence associated with tumor progression.

PubMed

Anderson, Alexander R A; Hassanein, Mohamed; Branch, Kevin M; Lu, Jenny; Lobdell, Nichole A; Maier, Julie; Basanta, David; Weidow, Brandy; Narasanna, Archana; Arteaga, Carlos L; Reynolds, Albert B; Quaranta, Vito; Estrada, Lourdes; Weaver, Alissa M

2009-11-15

Tumor-microenvironment interactions are increasingly recognized to influence tumor progression. To understand the competitive dynamics of tumor cells in diverse microenvironments, we experimentally parameterized a hybrid discrete-continuum mathematical model with phenotypic trait data from a set of related mammary cell lines with normal, transformed, or tumorigenic properties. Surprisingly, in a resource-rich microenvironment, with few limitations on proliferation or migration, transformed (but not tumorigenic) cells were most successful and outcompeted other cell types in heterogeneous tumor simulations. Conversely, constrained microenvironments with limitations on space and/or growth factors gave a selective advantage to phenotypes derived from tumorigenic cell lines. Analysis of the relative performance of each phenotype in constrained versus unconstrained microenvironments revealed that, although all cell types grew more slowly in resource-constrained microenvironments, the most aggressive cells were least affected by microenvironmental constraints. A game theory model testing the relationship between microenvironment resource availability and competitive cellular dynamics supports the concept that microenvironmental independence is an advantageous cellular trait in resource-limited microenvironments.

Investigating the performances of a 1 MV high pulsed power linear transformer driver: from beam dynamics to x radiation

NASA Astrophysics Data System (ADS)

Maisonny, R.; Ribière, M.; Toury, M.; Plewa, J. M.; Caron, M.; Auriel, G.; d'Almeida, T.

2016-12-01

The performance of a 1 MV pulsed high-power linear transformer driver accelerator were extensively investigated based on a numerical approach which utilizes both electromagnetic and Monte Carlo simulations. Particle-in-cell calculations were employed to examine the beam dynamics throughout the magnetically insulated transmission line which governs the coupling between the generator and the electron diode. Based on the information provided by the study of the beam dynamics, and using Monte Carlo methods, the main properties of the resulting x radiation were predicted. Good agreement was found between these simulations and experimental results. This work provides a detailed understanding of mechanisms affecting the performances of this type of high current, high-voltage pulsed accelerator, which are very promising for a growing number of applications.

Quantum Mechanics/Molecular Mechanics Free Energy Maps and Nonadiabatic Simulations for a Photochemical Reaction in DNA: Cyclobutane Thymine Dimer.

PubMed

Mendieta-Moreno, Jesús I; Trabada, Daniel G; Mendieta, Jesús; Lewis, James P; Gómez-Puertas, Paulino; Ortega, José

2016-11-03

The absorption of ultraviolet radiation by DNA may result in harmful genetic lesions that affect DNA replication and transcription, ultimately causing mutations, cancer, and/or cell death. We analyze the most abundant photochemical reaction in DNA, the cyclobutane thymine dimer, using hybrid quantum mechanics/molecular mechanics (QM/MM) techniques and QM/MM nonadiabatic molecular dynamics. We find that, due to its double helix structure, DNA presents a free energy barrier between nonreactive and reactive conformations leading to the photolesion. Moreover, our nonadiabatic simulations show that most of the photoexcited reactive conformations return to standard B-DNA conformations after an ultrafast nonradiative decay to the ground state. This work highlights the importance of dynamical effects (free energy, excited-state dynamics) for the study of photochemical reactions in biological systems.

High resolution simulations of energy absorption in dynamically loaded cellular structures

NASA Astrophysics Data System (ADS)

Winter, R. E.; Cotton, M.; Harris, E. J.; Eakins, D. E.; McShane, G.

2017-03-01

Cellular materials have potential application as absorbers of energy generated by high velocity impact. CTH, a Sandia National Laboratories Code which allows very severe strains to be simulated, has been used to perform very high resolution simulations showing the dynamic crushing of a series of two-dimensional, stainless steel metal structures with varying architectures. The structures are positioned to provide a cushion between a solid stainless steel flyer plate with velocities ranging from 300 to 900 m/s, and an initially stationary stainless steel target. Each of the alternative architectures under consideration was formed by an array of identical cells each of which had a constant volume and a constant density. The resolution of the simulations was maximised by choosing a configuration in which one-dimensional conditions persisted for the full period over which the specimen densified, a condition which is most readily met by impacting high density specimens at high velocity. It was found that the total plastic flow and, therefore, the irreversible energy dissipated in the fully densified energy absorbing cell, increase (a) as the structure becomes more rodlike and less platelike and (b) as the impact velocity increases. Sequential CTH images of the deformation processes show that the flow of the cell material may be broadly divided into macroscopic flow perpendicular to the compression direction and jetting-type processes (microkinetic flow) which tend to predominate in rod and rodlike configurations and also tend to play an increasing role at increased strain rates. A very simple analysis of a configuration in which a solid flyer impacts a solid target provides a baseline against which to compare and explain features seen in the simulations. The work provides a basis for the development of energy absorbing structures for application in the 200-1000 m/s impact regime.

The Slow Dynamics of Intracellular Sodium Concentration Increase the Time Window of Neuronal Integration: A Simulation Study

PubMed Central

Zylbertal, Asaph; Yarom, Yosef; Wagner, Shlomo

2017-01-01

Changes in intracellular Na+ concentration ([Na+]i) are rarely taken into account when neuronal activity is examined. As opposed to Ca2+, [Na+]i dynamics are strongly affected by longitudinal diffusion, and therefore they are governed by the morphological structure of the neurons, in addition to the localization of influx and efflux mechanisms. Here, we examined [Na+]i dynamics and their effects on neuronal computation in three multi-compartmental neuronal models, representing three distinct cell types: accessory olfactory bulb (AOB) mitral cells, cortical layer V pyramidal cells, and cerebellar Purkinje cells. We added [Na+]i as a state variable to these models, and allowed it to modulate the Na+ Nernst potential, the Na+-K+ pump current, and the Na+-Ca2+ exchanger rate. Our results indicate that in most cases [Na+]i dynamics are significantly slower than [Ca2+]i dynamics, and thus may exert a prolonged influence on neuronal computation in a neuronal type specific manner. We show that [Na+]i dynamics affect neuronal activity via three main processes: reduction of EPSP amplitude in repeatedly active synapses due to reduction of the Na+ Nernst potential; activity-dependent hyperpolarization due to increased activity of the Na+-K+ pump; specific tagging of active synapses by extended Ca2+ elevation, intensified by concurrent back-propagating action potentials or complex spikes. Thus, we conclude that [Na+]i dynamics should be considered whenever synaptic plasticity, extensive synaptic input, or bursting activity are examined. PMID:28970791

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

PubMed Central

2010-01-01

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

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

PubMed

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

2010-12-01

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

Dynamical mechanisms of conducted vasoreactivity: minimalistic modeling study

NASA Astrophysics Data System (ADS)

Kuryshova, Ekaterina A.; Rogatina, Kristina V.; Postnov, Dmitry E.

2018-04-01

Endothelial cells are cells lining the inner surface of the blood and lymphatic vessels, they separate the bloodstream from the deeper layers of the vascular wall. Earlier endothelium was considered only as a passive barrier between blood and tissues. However, it has now become apparent that endothelial cells, specifically reacting to different molecular signals generated locally and remotely, perform a variety of functions. Simulation of large vascular networks requires the development of specialized models of autoregulation of vascular tone. On the one hand, such models should have a strong support for cellular dynamics, on the other - be as computationally efficient as possible. A model of a two-dimensional cylindrical array of endothelial cells is proposed on the basis of the integral description by means of the whole-cell CVC. The process of propagation of hyperpolarizing and depolarizing pulses is investigated depending on the statistics of cell distribution between the two main types. Endothelial cells are considered as a dynamic system possessing bistability. Based on the articles, the results of the distribution of the resting-potential values were repeated, the propagation of the hyperpolarizing pulse was observed, the endothelial cell chain supported the propagation of the wave switching to a hyperpolarized state, and then the return wave returned to its original state.

Multi-phase models for water and thermal management of proton exchange membrane fuel cell: A review

NASA Astrophysics Data System (ADS)

Zhang, Guobin; Jiao, Kui

2018-07-01

The 3D (three-dimensional) multi-phase CFD (computational fluid dynamics) model is widely utilized in optimizing water and thermal management of PEM (proton exchange membrane) fuel cell. However, a satisfactory 3D multi-phase CFD model which is able to simulate the detailed gas and liquid two-phase flow in channels and reflect its effect on performance precisely is still not developed due to the coupling difficulties and computation amount. Meanwhile, the agglomerate model of CL (catalyst layer) should also be added in 3D CFD model so as to better reflect the concentration loss and optimize CL structure in macroscopic scale. Besides, the effect of thermal management is perhaps underestimated in current 3D multi-phase CFD simulations due to the lack of coolant channel in computation domain and constant temperature boundary condition. Therefore, the 3D CFD simulations in cell and stack levels with convection boundary condition are suggested to simulate the water and thermal management more accurately. Nevertheless, with the rapid development of PEM fuel cell, current 3D CFD simulations are far from practical demand, especially at high current density and low to zero humidity and for the novel designs developed recently, such as: metal foam flow field, 3D fine mesh flow field, anode circulation etc.

Simulations For Investigating the Contrast Mechanism of Biological Cells with High Frequency Scanning Acoustic Microscopy

NASA Astrophysics Data System (ADS)

Juntarapaso, Yada

Scanning Acoustic Microscopy (SAM) is one of the most powerful techniques for nondestructive evaluation and it is a promising tool for characterizing the elastic properties of biological tissues/cells. Exploring a single cell is important since there is a connection between single cell biomechanics and human cancer. Scanning acoustic microscopy (SAM) has been accepted and extensively utilized for acoustical cellular and tissue imaging including measurements of the mechanical and elastic properties of biological specimens. SAM provides superb advantages in that it is non-invasive, can measure mechanical properties of biological cells or tissues, and fixation/chemical staining is not necessary. The first objective of this research is to develop a program for simulating the images and contrast mechanism obtained by high-frequency SAM. Computer simulation algorithms based on MatlabRTM were built for simulating the images and contrast mechanisms. The mechanical properties of HeLa and MCF-7 cells were computed from the measurement data of the output signal amplitude as a function of distance from the focal planes of the acoustics lens which is known as V(z) . Algorithms for simulating V(z) responses involved the calculation of the reflectance function and were created based on ray theory and wave theory. The second objective is to design transducer arrays for SAM. Theoretical simulations based on Field II(c) programs of the high frequency ultrasound array designs were performed to enhance image resolution and volumetric imaging capabilities. Phased array beam forming and dynamic apodization and focusing were employed in the simulations. The new transducer array design will be state-of-the-art in improving the performance of SAM by electronic scanning and potentially providing a 4-D image of the specimen.

Limitations in electrophysiological model development and validation caused by differences between simulations and experimental protocols.

PubMed

Carro, Jesús; Rodríguez-Matas, José F; Monasterio, Violeta; Pueyo, Esther

2017-10-01

Models of ion channel dynamics are usually built by fitting isolated cell experimental values of individual parameters while neglecting the interaction between them. Another shortcoming regards the estimation of ionic current conductances, which is often based on quantification of Action Potential (AP)-derived markers. Although this procedure reduces the uncertainty in the calculation of conductances, many studies evaluate electrophysiological AP-derived markers from single cell simulations, whereas experimental measurements are obtained from tissue preparations. In this work, we explore the limitations of these approaches to estimate ion channel dynamics and maximum current conductances and how they could be overcome by using multiscale simulations of experimental protocols. Four human ventricular cell models, namely ten Tusscher and Panfilov (2006), Grandi et al. (2010), O'Hara et al. (2011), and Carro et al. (2011), were used. Two problems involving scales from ion channels to tissue were investigated: 1) characterization of L-type calcium voltage-dependent inactivation I Ca,L ; 2) identification of major ionic conductance contributors to steady-state AP markers, including APD 90 , APD 75 , APD 50 , APD 25 , Triangulation and maximal and minimal values of V and dV/dt during the AP (V max , V min , dV/dt max , dV/dt min ). Our results show that: 1) I Ca,L inactivation characteristics differed significantly when calculated from model equations and from simulations reproducing the experimental protocols. 2) Large differences were found in the ionic currents contributors to APD 25 , Triangulation, V max , dV/dt max and dV/dt min between single cells and 1D-tissue. When proposing any new model formulation, or evaluating an existing model, consistency between simulated and experimental data should be verified considering all involved effects and scales. Copyright © 2016 Elsevier Ltd. All rights reserved.

Complete wetting of graphene by biological lipids

NASA Astrophysics Data System (ADS)

Luan, Binquan; Huynh, Tien; Zhou, Ruhong

2016-03-01

Graphene nanosheets have been demonstrated to extract large amounts of lipid molecules directly out of the cell membrane of bacteria and thus cause serious damage to the cell's integrity. This interesting phenomenon, however, is so far not well understood theoretically. Here through extensive molecular dynamics simulations and theoretical analyses, we show that this phenomenon can be categorized as a complete wetting of graphene by membrane lipids in water. A wetting-based theory was utilized to associate the free energy change during the microscopic extraction of a lipid with the spreading parameter for the macroscopic wetting. With a customized thermodynamic cycle for detailed energetics, we show that the dispersive adhesion between graphene and lipids plays a dominant role during this extraction as manifested by the curved graphene. Our simulation results suggest that biological lipids can completely wet the concave, flat or even convex (with a small curvature) surface of a graphene sheet.Graphene nanosheets have been demonstrated to extract large amounts of lipid molecules directly out of the cell membrane of bacteria and thus cause serious damage to the cell's integrity. This interesting phenomenon, however, is so far not well understood theoretically. Here through extensive molecular dynamics simulations and theoretical analyses, we show that this phenomenon can be categorized as a complete wetting of graphene by membrane lipids in water. A wetting-based theory was utilized to associate the free energy change during the microscopic extraction of a lipid with the spreading parameter for the macroscopic wetting. With a customized thermodynamic cycle for detailed energetics, we show that the dispersive adhesion between graphene and lipids plays a dominant role during this extraction as manifested by the curved graphene. Our simulation results suggest that biological lipids can completely wet the concave, flat or even convex (with a small curvature) surface of a graphene sheet. Electronic supplementary information (ESI) available: The movie showing the simulation trajectory for the extraction of lipids from the membrane. See DOI: 10.1039/C6NR00202A

MOLSIM: A modular molecular simulation software

PubMed Central

Jurij, Reščič

2015-01-01

The modular software MOLSIM for all‐atom molecular and coarse‐grained simulations is presented with focus on the underlying concepts used. The software possesses four unique features: (1) it is an integrated software for molecular dynamic, Monte Carlo, and Brownian dynamics simulations; (2) simulated objects are constructed in a hierarchical fashion representing atoms, rigid molecules and colloids, flexible chains, hierarchical polymers, and cross‐linked networks; (3) long‐range interactions involving charges, dipoles and/or anisotropic dipole polarizabilities are handled either with the standard Ewald sum, the smooth particle mesh Ewald sum, or the reaction‐field technique; (4) statistical uncertainties are provided for all calculated observables. In addition, MOLSIM supports various statistical ensembles, and several types of simulation cells and boundary conditions are available. Intermolecular interactions comprise tabulated pairwise potentials for speed and uniformity and many‐body interactions involve anisotropic polarizabilities. Intramolecular interactions include bond, angle, and crosslink potentials. A very large set of analyses of static and dynamic properties is provided. The capability of MOLSIM can be extended by user‐providing routines controlling, for example, start conditions, intermolecular potentials, and analyses. An extensive set of case studies in the field of soft matter is presented covering colloids, polymers, and crosslinked networks. © 2015 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc. PMID:25994597

Lennard-Jones type pair-potential method for coarse-grained lipid bilayer membrane simulations in LAMMPS

NASA Astrophysics Data System (ADS)

Fu, S.-P.; Peng, Z.; Yuan, H.; Kfoury, R.; Young, Y.-N.

2017-01-01

Lipid bilayer membranes have been extensively studied by coarse-grained molecular dynamics simulations. Numerical efficiencies have been reported in the cases of aggressive coarse-graining, where several lipids are coarse-grained into a particle of size 4 ∼ 6 nm so that there is only one particle in the thickness direction. Yuan et al. proposed a pair-potential between these one-particle-thick coarse-grained lipid particles to capture the mechanical properties of a lipid bilayer membrane, such as gel-fluid-gas phase transitions of lipids, diffusion, and bending rigidity Yuan et al. (2010). In this work we implement such an interaction potential in LAMMPS to simulate large-scale lipid systems such as a giant unilamellar vesicle (GUV) and red blood cells (RBCs). We also consider the effect of cytoskeleton on the lipid membrane dynamics as a model for RBC dynamics, and incorporate coarse-grained water molecules to account for hydrodynamic interactions. The interaction between the coarse-grained water molecules (explicit solvent molecules) is modeled as a Lennard-Jones (L-J) potential. To demonstrate that the proposed methods do capture the observed dynamics of vesicles and RBCs, we focus on two sets of LAMMPS simulations: 1. Vesicle shape transitions with enclosed volume; 2. RBC shape transitions with different enclosed volume. Finally utilizing the parallel computing capability in LAMMPS, we provide some timing results for parallel coarse-grained simulations to illustrate that it is possible to use LAMMPS to simulate large-scale realistic complex biological membranes for more than 1 ms.

Research on fuel cell and battery hybrid bus system parameters based on ADVISOR

NASA Astrophysics Data System (ADS)

Lai, Lianfeng; Lu, Youwen; Guo, Weiwei; Lin, Yuxiang; Xie, Yichun; Zheng, Liping; Chen, Wei; Liang, Boshan

2018-06-01

This paper aims at the fuel cell and battery hybrid automobile, based on one bus parameters, considers their own characteristics of fuel cell and battery and power demand when automobiles start, accelerate, climb, brake and other different working conditions, calculate the hybrid bus system parameters that match the fuel cell/battery., and ADVISOR is used is to verify simulation. The results show that the parameters of power drive system of this electric automobile are reasonable, and can meet the requirements of dynamic design indexes.

Receptor-mediated membrane adhesion of lipid-polymer hybrid (LPH) nanoparticles studied by dissipative particle dynamics simulations

NASA Astrophysics Data System (ADS)

Li, Zhenlong; Gorfe, Alemayehu A.

2014-12-01

Lipid-polymer hybrid (LPH) nanoparticles represent a novel class of targeted drug delivery platforms that combine the advantages of liposomes and biodegradable polymeric nanoparticles. However, the molecular details of the interaction between LPHs and their target cell membranes remain poorly understood. We have investigated the receptor-mediated membrane adhesion process of a ligand-tethered LPH nanoparticle using extensive dissipative particle dynamics (DPD) simulations. We found that the spontaneous adhesion process follows a first-order kinetics characterized by two distinct stages: a rapid nanoparticle-membrane engagement, followed by a slow growth in the number of ligand-receptor pairs coupled with structural re-organization of both the nanoparticle and the membrane. The number of ligand-receptor pairs increases with the dynamic segregation of ligands and receptors toward the adhesion zone causing an out-of-plane deformation of the membrane. Moreover, the fluidity of the lipid shell allows for strong nanoparticle-membrane interactions to occur even when the ligand density is low. The LPH-membrane avidity is enhanced by the increased stability of each receptor-ligand pair due to the geometric confinement and the cooperative effect arising from multiple binding events. Thus, our results reveal the unique advantages of LPH nanoparticles as active cell-targeting nanocarriers and provide some general principles governing nanoparticle-cell interactions that may aid future design of LPHs with improved affinity and specificity for a given target of interest.

On magnetic field amplification and particle acceleration near non-relativistic collisionless shocks: Particles in MHD Cells simulations

NASA Astrophysics Data System (ADS)

Casse, F.; van Marle, A. J.; Marcowith, A.

2018-01-01

We present simulations of magnetized astrophysical shocks taking into account the interplay between the thermal plasma of the shock and supra-thermal particles. Such interaction is depicted by combining a grid-based magneto-hydrodynamics description of the thermal fluid with particle-in-cell techniques devoted to the dynamics of supra-thermal particles. This approach, which incorporates the use of adaptive mesh refinement features, is potentially a key to simulate astrophysical systems on spatial scales that are beyond the reach of pure particle-in-cell simulations. We consider non-relativistic super-Alfénic shocks with various magnetic field obliquity. We recover all the features from previous studies when the magnetic field is parallel to the normal to the shock. In contrast with previous particle-in-cell and hybrid simulations, we find that particle acceleration and magnetic field amplification also occur when the magnetic field is oblique to the normal to the shock but on larger timescales than in the parallel case. We show that in our oblique shock simulations the streaming of supra-thermal particles induces a corrugation of the shock front. Such oscillations of both the shock front and the magnetic field then locally helps the particles to enter the upstream region and to initiate a non-resonant streaming instability and finally to induce diffuse particle acceleration.

Atomistic Simulation of Interfaces in Materials of Solid State Ionics

NASA Astrophysics Data System (ADS)

Ivanov-Schitz, A. K.; Mazo, G. N.

2018-01-01

The possibilities of describing correctly interfaces of different types in solids within a computer experiment using molecular statics simulation, molecular dynamics simulation, and quantum chemical calculations are discussed. Heterophase boundaries of various types, including grain boundaries and solid electrolyte‒solid electrolyte and ionic conductor‒electrode material interfaces, are considered. Specific microstructural features and mechanisms of the ion transport in real heterophase structures (cationic conductor‒metal anode and anionic conductor‒cathode) existing in solid state ionics devices (such as solid-state batteries and fuel cells) are discussed.

Quantitative comparison between full-spectrum and filter-based imaging in hyperspectral fluorescence microscopy

PubMed Central

GAO, L.; HAGEN, N.; TKACZYK, T.S.

2012-01-01

Summary We implement a filterless illumination scheme on a hyperspectral fluorescence microscope to achieve full-range spectral imaging. The microscope employs polarisation filtering, spatial filtering and spectral unmixing filtering to replace the role of traditional filters. Quantitative comparisons between full-spectrum and filter-based microscopy are provided in the context of signal dynamic range and accuracy of measured fluorophores’ emission spectra. To show potential applications, a five-colour cell immunofluorescence imaging experiment is theoretically simulated. Simulation results indicate that the use of proposed full-spectrum imaging technique may result in three times improvement in signal dynamic range compared to that can be achieved in the filter-based imaging. PMID:22356127

Spontaneous assembly of HSP90 inhibitors at water/octanol interface: A molecular dynamics simulation study

NASA Astrophysics Data System (ADS)

Zolghadr, Amin Reza; Boroomand, Samaneh

2017-02-01

Drug absorption at an acceptable dose depends on the pair of solubility and permeability. There are many potent therapeutics that are not active in vivo, presumably due to the lack of capability to cross the cell membrane. Molecular dynamics simulation of radicicol, diol-radicicol, cyclopropane-radicicol and 17-DMAG were performed at water/octanol interface to suggest interfacial activity as a physico-chemical characteristic of these heat shock protein 90 (HSP90) inhibitors. We have observed that orally active HSP90 inhibitors form aggregates at the water/octanol and DPPC-lipid/water interfaces by starting from an initial configuration with HSP90 inhibitors embedded in the water matrix.

Coupling Cellular Automata Land Use Change with Distributed Hydrologic Models

NASA Astrophysics Data System (ADS)

Shu, L.; Duffy, C.

2017-12-01

There has been extensive research on LUC modeling with broad applications to simulating urban growth and changing demographic patterns across multiple scales. The importance of land conversion is a critical issue in watershed scale studies and is generally not treated in most watershed modeling approaches. In this study we apply spatially explicit hydrologic and landuse change models and the Conestoga Watershed in Lancaster County, Pennsylvania. The Penn State Integrated Hydrologic Model (PIHM) partitions the water balance in space and time over the urban catchment, the coupled Cellular Automata Land Use Change model (CALUC) dynamically simulates the evolution of land use classes based on physical measures associated with population change and land use demand factors. The CALUC model is based on iteratively applying discrete rules to each individual spatial cell. The essence the CA modeling involves calculation of the Transition Potential (TP) for conversion of a grid cell from one land use class to another. This potential includes five factors: random perturbation, suitability, accessibility, neighborhood effect, inertia effects and zonal factors. In spite of simplicity, this CALUC model has been shown to be very effective for simulating LUC leading to the emergence of complex spatial patterns. The components of TP are derived from present land use data for landuse reanalysis and for realistic future land use scenarios. For the CALUC we use early-settlement (circa 1790) initial land class values and final or present-day (2010) land classes to calibrate the model. CALUC- PIHM dynamically simulates the hydrologic response of conversion from pre-settlement to present landuse. The simulations highlight the capability and value of dynamic coupling of catchment hydrology with land use change over long time periods. Analysis of the simulation uses various metrics such as the distributed water balance, flow duration curves, etc. to show how deforestation, urbanization and agricultural land development interact for the period 1790- present.

Modelling and simulation of [18F]fluoromisonidazole dynamics based on histology-derived microvessel maps

NASA Astrophysics Data System (ADS)

Mönnich, David; Troost, Esther G. C.; Kaanders, Johannes H. A. M.; Oyen, Wim J. G.; Alber, Markus; Thorwarth, Daniela

2011-04-01

Hypoxia can be assessed non-invasively by positron emission tomography (PET) using radiotracers such as [18F]fluoromisonidazole (Fmiso) accumulating in poorly oxygenated cells. Typical features of dynamic Fmiso PET data are high signal variability in the first hour after tracer administration and slow formation of a consistent contrast. The purpose of this study is to investigate whether these characteristics can be explained by the current conception of the underlying microscopic processes and to identify fundamental effects. This is achieved by modelling and simulating tissue oxygenation and tracer dynamics on the microscopic scale. In simulations, vessel structures on histology-derived maps act as sources and sinks for oxygen as well as tracer molecules. Molecular distributions in the extravascular space are determined by reaction-diffusion equations, which are solved numerically using a two-dimensional finite element method. Simulated Fmiso time activity curves (TACs), though not directly comparable to PET TACs, reproduce major characteristics of clinical curves, indicating that the microscopic model and the parameter values are adequate. Evidence for dependence of the early PET signal on the vascular fraction is found. Further, possible effects leading to late contrast formation and potential implications on the quantification of Fmiso PET data are discussed.

Simulating shock-bubble interactions at water-gelatin interfaces

NASA Astrophysics Data System (ADS)

Adami, Stefan; Kaiser, Jakob; Bermejo-Moreno, Ivan; Adams, Nikolaus

2016-11-01

Biomedical problems are often driven by fluid dynamics, as in vivo organisms are usually composed of or filled with fluids that (strongly) affected their physics. Additionally, fluid dynamical effects can be used to enhance certain phenomena or destroy organisms. As examples, we highlight the benign potential of shockwave-driven kidney-stone lithotripsy or sonoporation (acoustic cavitation of microbubbles) to improve drug delivery into cells. During the CTR SummerProgram 2016 we have performed axisymmetric three-phase simulations of a shock hitting a gas bubble in water near a gelatin interface mimicking the fundamental process during sonoporation. We used our multi-resolution finite volume method with sharp interface representation (level-set), WENO-5 shock capturing and interface scale-separation and compared the results with a diffuse-interface method. Qualitatively our simulation results agree well with the reference. Due to the interface treatment the pressure profiles are sharper in our simulations and bubble collapse dynamics are predicted at shorter time-scales. Validation with free-field collapse (Rayleigh collapse) shows very good agreement. The project leading to this application has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (Grant agreement No 667483).

All-atomic simulations on human telomeric G-quadruplex DNA binding with thioflavin T.

PubMed

Luo, Di; Mu, Yuguang

2015-04-16

Ligand-stabilized human telomeric G-quadruplex DNA is believed to be an anticancer agent, as it can impede the continuous elongation of telomeres by telomerase in cancer cells. In this study, five well-established human telomeric G-quadruplex DNA models were probed on their binding behaviors with thioflavin T (ThT) via both conventional molecular dynamics (MD) and well-tempered metadynamics (WT-MetaD) simulations. Novel dynamics and characteristic binding patterns were disclosed by the MD simulations. It was observed that the K(+) promoted parallel and hybridized human telomeric G-quadruplex conformations pose higher binding affinities to ThT than the Na(+) and K(+) promoted basket conformations. It is the end, sandwich, and base stacking driven by π-π interactions that are identified as the major binding mechanisms. As the most energy favorable binding mode, the sandwich stacking observed in (3 + 1) hybridized form 1 G-quadruplex conformation is triggered by reversible conformational change of the G-quadruplex. To further examine the free energy landscapes, WT-MetaD simulations were utilized on G-quadruplex-ThT systems. It is found that all of the major binding modes predicted by the MD simulations are confirmed by the WT-MetaD simulations. The results in this work not only accord with existing experimental findings, but also reinforce our understanding on the dynamics of G-quadruplexes and aid future drug developments for G-quadruplex stabilization ligands.

Numerical simulation of photocurrent generation in bilayer organic solar cells: Comparison of master equation and kinetic Monte Carlo approaches

NASA Astrophysics Data System (ADS)

Casalegno, Mosè; Bernardi, Andrea; Raos, Guido

2013-07-01

Numerical approaches can provide useful information about the microscopic processes underlying photocurrent generation in organic solar cells (OSCs). Among them, the Kinetic Monte Carlo (KMC) method is conceptually the simplest, but computationally the most intensive. A less demanding alternative is potentially represented by so-called Master Equation (ME) approaches, where the equations describing particle dynamics rely on the mean-field approximation and their solution is attained numerically, rather than stochastically. The description of charge separation dynamics, the treatment of electrostatic interactions and numerical stability are some of the key issues which have prevented the application of these methods to OSC modelling, despite of their successes in the study of charge transport in disordered system. Here we describe a three-dimensional ME approach to photocurrent generation in OSCs which attempts to deal with these issues. The reliability of the proposed method is tested against reference KMC simulations on bilayer heterojunction solar cells. Comparison of the current-voltage curves shows that the model well approximates the exact result for most devices. The largest deviations in current densities are mainly due to the adoption of the mean-field approximation for electrostatic interactions. The presence of deep traps, in devices characterized by strong energy disorder, may also affect result quality. Comparison of the simulation times reveals that the ME algorithm runs, on the average, one order of magnitude faster than KMC.

Application of a computationally efficient method to approximate gap model results with a probabilistic approach

NASA Astrophysics Data System (ADS)

Scherstjanoi, M.; Kaplan, J. O.; Lischke, H.

2014-07-01

To be able to simulate climate change effects on forest dynamics over the whole of Switzerland, we adapted the second-generation DGVM (dynamic global vegetation model) LPJ-GUESS (Lund-Potsdam-Jena General Ecosystem Simulator) to the Alpine environment. We modified model functions, tuned model parameters, and implemented new tree species to represent the potential natural vegetation of Alpine landscapes. Furthermore, we increased the computational efficiency of the model to enable area-covering simulations in a fine resolution (1 km) sufficient for the complex topography of the Alps, which resulted in more than 32 000 simulation grid cells. To this aim, we applied the recently developed method GAPPARD (approximating GAP model results with a Probabilistic Approach to account for stand Replacing Disturbances) (Scherstjanoi et al., 2013) to LPJ-GUESS. GAPPARD derives mean output values from a combination of simulation runs without disturbances and a patch age distribution defined by the disturbance frequency. With this computationally efficient method, which increased the model's speed by approximately the factor 8, we were able to faster detect the shortcomings of LPJ-GUESS functions and parameters. We used the adapted LPJ-GUESS together with GAPPARD to assess the influence of one climate change scenario on dynamics of tree species composition and biomass throughout the 21st century in Switzerland. To allow for comparison with the original model, we additionally simulated forest dynamics along a north-south transect through Switzerland. The results from this transect confirmed the high value of the GAPPARD method despite some limitations towards extreme climatic events. It allowed for the first time to obtain area-wide, detailed high-resolution LPJ-GUESS simulation results for a large part of the Alpine region.

Coupled particle-in-cell and Monte Carlo transport modeling of intense radiographic sources

NASA Astrophysics Data System (ADS)

Rose, D. V.; Welch, D. R.; Oliver, B. V.; Clark, R. E.; Johnson, D. L.; Maenchen, J. E.; Menge, P. R.; Olson, C. L.; Rovang, D. C.

2002-03-01

Dose-rate calculations for intense electron-beam diodes using particle-in-cell (PIC) simulations along with Monte Carlo electron/photon transport calculations are presented. The electromagnetic PIC simulations are used to model the dynamic operation of the rod-pinch and immersed-B diodes. These simulations include algorithms for tracking electron scattering and energy loss in dense materials. The positions and momenta of photons created in these materials are recorded and separate Monte Carlo calculations are used to transport the photons to determine the dose in far-field detectors. These combined calculations are used to determine radiographer equations (dose scaling as a function of diode current and voltage) that are compared directly with measured dose rates obtained on the SABRE generator at Sandia National Laboratories.

Asymmetric breathing motions of nucleosomal DNA and the role of histone tails

NASA Astrophysics Data System (ADS)

Chakraborty, Kaushik; Loverde, Sharon M.

2017-08-01

The most important packing unit of DNA in the eukaryotic cell is the nucleosome. It undergoes large-scale structural re-arrangements during different cell cycles. For example, the disassembly of the nucleosome is one of the key steps for DNA replication, whereas reassembly occurs after replication. Thus, conformational dynamics of the nucleosome is crucial for different DNA metabolic processes. We perform three different sets of atomistic molecular dynamics simulations of the nucleosome core particle at varying degrees of salt conditions for a total of 0.7 μs simulation time. We find that the conformational dynamics of the nucleosomal DNA tails are oppositely correlated from each other during the initial breathing motions. Furthermore, the strength of the interaction of the nucleosomal DNA tail with the neighboring H2A histone tail modulates the conformational state of the nucleosomal DNA tail. With increasing salt concentration, the degree of asymmetry in the conformation of the nucleosomal DNA tails decreases as both tails tend to unwrap. This direct correlation between the asymmetric breathing motions of the DNA tails and the H2A histone tails, and its decrease at higher salt concentrations, may play a significant role in the molecular pathway of unwrapping.

A Program for Solving the Brain Ischemia Problem

PubMed Central

DeGracia, Donald J.

2013-01-01

Our recently described nonlinear dynamical model of cell injury is here applied to the problems of brain ischemia and neuroprotection. We discuss measurement of global brain ischemia injury dynamics by time course analysis. Solutions to proposed experiments are simulated using hypothetical values for the model parameters. The solutions solve the global brain ischemia problem in terms of “master bifurcation diagrams” that show all possible outcomes for arbitrary durations of all lethal cerebral blood flow (CBF) decrements. The global ischemia master bifurcation diagrams: (1) can map to a single focal ischemia insult, and (2) reveal all CBF decrements susceptible to neuroprotection. We simulate measuring a neuroprotectant by time course analysis, which revealed emergent nonlinear effects that set dynamical limits on neuroprotection. Using over-simplified stroke geometry, we calculate a theoretical maximum protection of approximately 50% recovery. We also calculate what is likely to be obtained in practice and obtain 38% recovery; a number close to that often reported in the literature. The hypothetical examples studied here illustrate the use of the nonlinear cell injury model as a fresh avenue of approach that has the potential, not only to solve the brain ischemia problem, but also to advance the technology of neuroprotection. PMID:24961411

Large scale atomistic simulation of single-layer graphene growth on Ni(111) surface: molecular dynamics simulation based on a new generation of carbon-metal potential

NASA Astrophysics Data System (ADS)

Xu, Ziwei; Yan, Tianying; Liu, Guiwu; Qiao, Guanjun; Ding, Feng

2015-12-01

To explore the mechanism of graphene chemical vapor deposition (CVD) growth on a catalyst surface, a molecular dynamics (MD) simulation of carbon atom self-assembly on a Ni(111) surface based on a well-designed empirical reactive bond order potential was performed. We simulated single layer graphene with recorded size (up to 300 atoms per super-cell) and reasonably good quality by MD trajectories up to 15 ns. Detailed processes of graphene CVD growth, such as carbon atom dissolution and precipitation, formation of carbon chains of various lengths, polygons and small graphene domains were observed during the initial process of the MD simulation. The atomistic processes of typical defect healing, such as the transformation from a pentagon into a hexagon and from a pentagon-heptagon pair (5|7) to two adjacent hexagons (6|6), were revealed as well. The study also showed that higher temperature and longer annealing time are essential to form high quality graphene layers, which is in agreement with experimental reports and previous theoretical results.To explore the mechanism of graphene chemical vapor deposition (CVD) growth on a catalyst surface, a molecular dynamics (MD) simulation of carbon atom self-assembly on a Ni(111) surface based on a well-designed empirical reactive bond order potential was performed. We simulated single layer graphene with recorded size (up to 300 atoms per super-cell) and reasonably good quality by MD trajectories up to 15 ns. Detailed processes of graphene CVD growth, such as carbon atom dissolution and precipitation, formation of carbon chains of various lengths, polygons and small graphene domains were observed during the initial process of the MD simulation. The atomistic processes of typical defect healing, such as the transformation from a pentagon into a hexagon and from a pentagon-heptagon pair (5|7) to two adjacent hexagons (6|6), were revealed as well. The study also showed that higher temperature and longer annealing time are essential to form high quality graphene layers, which is in agreement with experimental reports and previous theoretical results. Electronic supplementary information (ESI) available. See DOI: 10.1039/c5nr06016h

Elucidating the Functional Roles of Spatial Organization in Cross-Membrane Signal Transduction by a Hybrid Simulation Method.

PubMed

Chen, Jiawen; Xie, Zhong-Ru; Wu, Yinghao

2016-07-01

The ligand-binding of membrane receptors on cell surfaces initiates the dynamic process of cross-membrane signal transduction. It is an indispensable part of the signaling network for cells to communicate with external environments. Recent experiments revealed that molecular components in signal transduction are not randomly mixed, but spatially organized into distinctive patterns. These patterns, such as receptor clustering and ligand oligomerization, lead to very different gene expression profiles. However, little is understood about the molecular mechanisms and functional impacts of this spatial-temporal regulation in cross-membrane signal transduction. In order to tackle this problem, we developed a hybrid computational method that decomposes a model of signaling network into two simulation modules. The physical process of binding between receptors and ligands on cell surfaces are simulated by a diffusion-reaction algorithm, while the downstream biochemical reactions are modeled by stochastic simulation of Gillespie algorithm. These two processes are coupled together by a synchronization framework. Using this method, we tested the dynamics of a simple signaling network in which the ligand binding of cell surface receptors triggers the phosphorylation of protein kinases, and in turn regulates the expression of target genes. We found that spatial aggregation of membrane receptors at cellular interfaces is able to either amplify or inhibit downstream signaling outputs, depending on the details of clustering mechanism. Moreover, by providing higher binding avidity, the co-localization of ligands into multi-valence complex modulates signaling in very different ways that are closely related to the binding affinity between ligand and receptor. We also found that the temporal oscillation of the signaling pathway that is derived from genetic feedback loops can be modified by the spatial clustering of membrane receptors. In summary, our method demonstrates the functional importance of spatial organization in cross-membrane signal transduction. The method can be applied to any specific signaling pathway in cells.

How large can the electron to proton mass ratio be in particle-in-cell simulations of unstable systems?

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

Bret, A.; Dieckmann, M. E.

2010-03-15

Particle-in-cell simulations are widely used as a tool to investigate instabilities that develop between a collisionless plasma and beams of charged particles. However, even on contemporary supercomputers, it is not always possible to resolve the ion dynamics in more than one spatial dimension with such simulations. The ion mass is thus reduced below 1836 electron masses, which can affect the plasma dynamics during the initial exponential growth phase of the instability and during the subsequent nonlinear saturation. The goal of this article is to assess how far the electron to ion mass ratio can be increased, without changing qualitatively themore » physics. It is first demonstrated that there can be no exact similarity law, which balances a change in the mass ratio with that of another plasma parameter, leaving the physics unchanged. Restricting then the analysis to the linear phase, a criterion allowing to define a maximum ratio is explicated in terms of the hierarchy of the linear unstable modes. The criterion is applied to the case of a relativistic electron beam crossing an unmagnetized electron-ion plasma.« less

Molecular docking and dynamics simulations of A.niger RNase from Aspergillus niger ATCC26550: for potential prevention of human cancer.

PubMed

Kumar, Gundampati Ravi; Chikati, Rajasekhar; Pandrangi, Santhi Latha; Kandapal, Manoj; Sonkar, Kirti; Gupta, Neeraj; Mulakayala, Chaitanya; Jagannadham, Medicherla V; Kumar, Chitta Suresh; Saxena, Sunita; Das, Mira Debnath

2013-02-01

The aim of the present research was to study the anticancer effects of Aspergillus niger (A.niger) RNase. We found that RNase (A.niger RNase) significantly and dose dependently inhibited invasiveness of breast cancer cell line MDA MB 231 by 55 % (P<0.01) at 1 μM concentration. At a concentration of 2 μM, the anti invasive effect of the enzyme increased to 90 % (P<0.002). Keeping the aim to determine molecular level interactions (molecular simulations and protein docking) of human actin with A.niger RNase we extended our work in-vitro to in-silico studies. To gain better relaxation and accurate arrangement of atoms, refinement was done on the human actin and A.niger RNase by energy minimization (EM) and molecular dynamics (MD) simulations using 43A(2) force field of Gromacs96 implemented in the Gromacs 4.0.5 package, finally the interaction energies were calculated by protein-protein docking using the HEX. These in vitro and in-silico structural studies prove the effective inhibition of actin activity by A.niger RNase in neoplastic cells and thereby provide new insights for the development of novel anti cancer drugs.

Modeling and simulation of a low-grade urinary bladder carcinoma.

PubMed

Bunimovich-Mendrazitsky, Svetlana; Pisarev, Vladimir; Kashdan, Eugene

2015-03-01

In this work, we present a mathematical model of the initiation and progression of a low-grade urinary bladder carcinoma. We simulate the crucial processes affecting tumor growth, such as oxygen diffusion, carcinogen penetration, and angiogenesis, within the framework of the urothelial cell dynamics. The cell dynamics are modeled using the discrete technique of cellular automata, while the continuous processes of carcinogen penetration and oxygen diffusion are described by nonlinear diffusion-absorption equations. As the availability of oxygen is necessary for tumor progression, processes of oxygen transport to the tumor growth site seem most important. Our model yields a theoretical insight into the main stages of development and growth of urinary bladder carcinoma with emphasis on the two most common types: bladder polyps and carcinoma in situ. Analysis of histological structure of bladder tumor is important to avoid misdiagnosis and wrong treatment. We expect our model to be a valuable tool in the study of bladder cancer progression due to the exposure to carcinogens and the oxygen dependent expression of genes promoting tumor growth. Our numerical simulations have good qualitative agreement with in vivo results reported in the corresponding medical literature. Copyright © 2015 Elsevier Ltd. All rights reserved.

Large Eddy Simulation of "turbulent-like" flow in intracranial aneurysms

NASA Astrophysics Data System (ADS)

Khan, Muhammad Owais; Chnafa, Christophe; Steinman, David A.; Mendez, Simon; Nicoud, Franck

2016-11-01

Hemodynamic forces are thought to contribute to pathogenesis and rupture of intracranial aneurysms (IA). Recent high-resolution patient-specific computational fluid dynamics (CFD) simulations have highlighted the presence of "turbulent-like" flow features, characterized by transient high-frequency flow instabilities. In-vitro studies have shown that such "turbulent-like" flows can lead to lack of endothelial cell orientation and cell depletion, and thus, may also have relevance to IA rupture risk assessment. From a modelling perspective, previous studies have relied on DNS to resolve the small-scale structures in these flows. While accurate, DNS is clinically infeasible due to high computational cost and long simulation times. In this study, we present the applicability of LES for IAs using a LES/blood flow dedicated solver (YALES2BIO) and compare against respective DNS. As a qualitative analysis, we compute time-averaged WSS and OSI maps, as well as, novel frequency-based WSS indices. As a quantitative analysis, we show the differences in POD eigenspectra for LES vs. DNS and wavelet analysis of intra-saccular velocity traces. Differences in two SGS models (i.e. Dynamic Smagorinsky vs. Sigma) are also compared against DNS, and computational gains of LES are discussed.

Tensegrity and motor-driven effective interactions in a model cytoskeleton

NASA Astrophysics Data System (ADS)

Wang, Shenshen; Wolynes, Peter G.

2012-04-01

Actomyosin networks are major structural components of the cell. They provide mechanical integrity and allow dynamic remodeling of eukaryotic cells, self-organizing into the diverse patterns essential for development. We provide a theoretical framework to investigate the intricate interplay between local force generation, network connectivity, and collective action of molecular motors. This framework is capable of accommodating both regular and heterogeneous pattern formation, arrested coarsening and macroscopic contraction in a unified manner. We model the actomyosin system as a motorized cat's cradle consisting of a crosslinked network of nonlinear elastic filaments subjected to spatially anti-correlated motor kicks acting on motorized (fibril) crosslinks. The phase diagram suggests there can be arrested phase separation which provides a natural explanation for the aggregation and coalescence of actomyosin condensates. Simulation studies confirm the theoretical picture that a nonequilibrium many-body system driven by correlated motor kicks can behave as if it were at an effective equilibrium, but with modified interactions that account for the correlation of the motor driven motions of the actively bonded nodes. Regular aster patterns are observed both in Brownian dynamics simulations at effective equilibrium and in the complete stochastic simulations. The results show that large-scale contraction requires correlated kicking.

An IBM PC-based math model for space station solar array simulation

NASA Technical Reports Server (NTRS)

Emanuel, E. M.

1986-01-01

This report discusses and documents the design, development, and verification of a microcomputer-based solar cell math model for simulating the Space Station's solar array Initial Operational Capability (IOC) reference configuration. The array model is developed utilizing a linear solar cell dc math model requiring only five input parameters: short circuit current, open circuit voltage, maximum power voltage, maximum power current, and orbit inclination. The accuracy of this model is investigated using actual solar array on orbit electrical data derived from the Solar Array Flight Experiment/Dynamic Augmentation Experiment (SAFE/DAE), conducted during the STS-41D mission. This simulator provides real-time simulated performance data during the steady state portion of the Space Station orbit (i.e., array fully exposed to sunlight). Eclipse to sunlight transients and shadowing effects are not included in the analysis, but are discussed briefly. Integrating the Solar Array Simulator (SAS) into the Power Management and Distribution (PMAD) subsystem is also discussed.

A DYNAMIC SIMULATOR OF ENVIRONMENTAL CHEMICAL PARTITIONING

EPA Science Inventory

A version of the Community Multiscale Air Quality (CMAQ) model has been developed by the U.S. EPA that is capable of addressing the atmospheric fate, transport and deposition of some common trace toxics. An initial, 36-km rectangular grid-cell application for atrazine has been...

Molecular binding of black tea theaflavins to biological membranes: relationship to bioactivities

USDA-ARS?s Scientific Manuscript database

Molecular dynamics simulations were used to study the interactions of three theaflavin compounds with lipid bilayers. Experimental studies have linked theaflavins to beneficial health effects, some of which are related to interactions with the cell membrane. The molecular interaction of theaflavin...

Predicting Essential Components of Signal Transduction Networks: A Dynamic Model of Guard Cell Abscisic Acid Signaling

PubMed Central

Li, Song; Assmann, Sarah M; Albert, Réka

2006-01-01

Plants both lose water and take in carbon dioxide through microscopic stomatal pores, each of which is regulated by a surrounding pair of guard cells. During drought, the plant hormone abscisic acid (ABA) inhibits stomatal opening and promotes stomatal closure, thereby promoting water conservation. Dozens of cellular components have been identified to function in ABA regulation of guard cell volume and thus of stomatal aperture, but a dynamic description is still not available for this complex process. Here we synthesize experimental results into a consistent guard cell signal transduction network for ABA-induced stomatal closure, and develop a dynamic model of this process. Our model captures the regulation of more than 40 identified network components, and accords well with previous experimental results at both the pathway and whole-cell physiological level. By simulating gene disruptions and pharmacological interventions we find that the network is robust against a significant fraction of possible perturbations. Our analysis reveals the novel predictions that the disruption of membrane depolarizability, anion efflux, actin cytoskeleton reorganization, cytosolic pH increase, the phosphatidic acid pathway, or K+ efflux through slowly activating K+ channels at the plasma membrane lead to the strongest reduction in ABA responsiveness. Initial experimental analysis assessing ABA-induced stomatal closure in the presence of cytosolic pH clamp imposed by the weak acid butyrate is consistent with model prediction. Simulations of stomatal response as derived from our model provide an efficient tool for the identification of candidate manipulations that have the best chance of conferring increased drought stress tolerance and for the prioritization of future wet bench analyses. Our method can be readily applied to other biological signaling networks to identify key regulatory components in systems where quantitative information is limited. PMID:16968132

Evaluation of Material Models within LS-DYNA(Registered TradeMark) for a Kevlar/Epoxy Composite Honeycomb

NASA Technical Reports Server (NTRS)

Polanco, Michael A.; Kellas, Sotiris; Jackson, Karen

2009-01-01

The performance of material models to simulate a novel composite honeycomb Deployable Energy Absorber (DEA) was evaluated using the nonlinear explicit dynamic finite element code LS-DYNA(Registered TradeMark). Prototypes of the DEA concept were manufactured using a Kevlar/Epoxy composite material in which the fibers are oriented at +/-45 degrees with respect to the loading axis. The development of the DEA has included laboratory tests at subcomponent and component levels such as three-point bend testing of single hexagonal cells, dynamic crush testing of single multi-cell components, and impact testing of a full-scale fuselage section fitted with a system of DEA components onto multi-terrain environments. Due to the thin nature of the cell walls, the DEA was modeled using shell elements. In an attempt to simulate the dynamic response of the DEA, it was first represented using *MAT_LAMINATED_COMPOSITE_FABRIC, or *MAT_58, in LS-DYNA. Values for each parameter within the material model were generated such that an in-plane isotropic configuration for the DEA material was assumed. Analytical predictions showed that the load-deflection behavior of a single-cell during three-point bending was within the range of test data, but predicted the DEA crush response to be very stiff. In addition, a *MAT_PIECEWISE_LINEAR_PLASTICITY, or *MAT_24, material model in LS-DYNA was developed, which represented the Kevlar/Epoxy composite as an isotropic elastic-plastic material with input from +/-45 degrees tensile coupon data. The predicted crush response matched that of the test and localized folding patterns of the DEA were captured under compression, but the model failed to predict the single-cell three-point bending response.

SELF-HEALING NANOMATERIALS: MULTIMILLION-ATOM REACTIVE MOLECULAR DYNAMICS SIMULATIONS

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

Hakamata, Tomoya; Shimamura, Kohei; Shimojo, Fuyuki

Organometal halide perovskites are attracting great attention as promising material for solar cells because of their high power conversion efficiency. The high performance has been attributed to the existence of free charge carriers and their large diffusion lengths, but the nature of carrier transport at the atomistic level remains elusive. Here, nonadiabatic quantum molecular dynamics simulations elucidate the mechanisms underlying the excellent free-carrier transport in CH 3NH 3PbI 3. Pb and I sublattices act as disjunct pathways for rapid and balanced transport of photoexcited electrons and holes, respectively, while minimizing efficiency-degrading charge recombination. On the other hand, CH 3NH 3more » sublattice quickly screens out electrostatic electron-hole attraction to generate free carriers within 1 ps. Together this nano-architecture lets photoexcited electrons and holes dissociate instantaneously and travel far away to be harvested before dissipated as heat. As a result, this work provides much needed structure-property relationships and time-resolved information that potentially lead to rational design of efficient solar cells.« less

Pharmacophore-based virtual screening, molecular docking, molecular dynamics simulation, and biological evaluation for the discovery of novel BRD4 inhibitors.

PubMed

Yan, Guoyi; Hou, Manzhou; Luo, Jiang; Pu, Chunlan; Hou, Xueyan; Lan, Suke; Li, Rui

2018-02-01

Bromodomain is a recognition module in the signal transduction of acetylated histone. BRD4, one of the bromodomain members, is emerging as an attractive therapeutic target for several types of cancer. Therefore, in this study, an attempt has been made to screen compounds from an integrated database containing 5.5 million compounds for BRD4 inhibitors using pharmacophore-based virtual screening, molecular docking, and molecular dynamics simulations. As a result, two molecules of twelve hits were found to be active in bioactivity tests. Among the molecules, compound 5 exhibited potent anticancer activity, and the IC 50 values against human cancer cell lines MV4-11, A375, and HeLa were 4.2, 7.1, and 11.6 μm, respectively. After that, colony formation assay, cell cycle, apoptosis analysis, wound-healing migration assay, and Western blotting were carried out to learn the bioactivity of compound 5. © 2017 John Wiley & Sons A/S.

Molecular dynamics simulation analysis of the effect of T790M mutation on epidermal growth factor receptor protein architecture in non-small cell lung carcinoma.

PubMed

Peng, Xiao-Nu; Wang, Jing; Zhang, Wei

2017-08-01

Non-small cell lung cancer etiology and its treatment failure are due to epidermal growth factor receptor (EGFR) kinase domain mutations at amino acid position 790. The mutational change from threonine to methionine at position 790 (T790M) is responsible for tyrosine kinase inhibition failure. Using molecular dynamic simulation, the present study investigated the architectural changes occurring at the atomic scale. The 50-nsec runs using a GROMOS force field for wild-type and mutant EGFR's kinase domains were investigated for contrasting variations using Gromacs inbuilt tools. The adenosine triphosphate binding domain and the active site of EGFR were studied extensively in order to understand the structural changes. All the parameters investigated in the present study revealed considerable changes in the studied structures, and the knowledge gained from this may be used to develop novel kinase inhibitors that will be effective irrespective of the structural alterations in kinase domain.

Towards robust algorithms for current deposition and dynamic load-balancing in a GPU particle in cell code

NASA Astrophysics Data System (ADS)

Rossi, Francesco; Londrillo, Pasquale; Sgattoni, Andrea; Sinigardi, Stefano; Turchetti, Giorgio

2012-12-01

We present `jasmine', an implementation of a fully relativistic, 3D, electromagnetic Particle-In-Cell (PIC) code, capable of running simulations in various laser plasma acceleration regimes on Graphics-Processing-Units (GPUs) HPC clusters. Standard energy/charge preserving FDTD-based algorithms have been implemented using double precision and quadratic (or arbitrary sized) shape functions for the particle weighting. When porting a PIC scheme to the GPU architecture (or, in general, a shared memory environment), the particle-to-grid operations (e.g. the evaluation of the current density) require special care to avoid memory inconsistencies and conflicts. Here we present a robust implementation of this operation that is efficient for any number of particles per cell and particle shape function order. Our algorithm exploits the exposed GPU memory hierarchy and avoids the use of atomic operations, which can hurt performance especially when many particles lay on the same cell. We show the code multi-GPU scalability results and present a dynamic load-balancing algorithm. The code is written using a python-based C++ meta-programming technique which translates in a high level of modularity and allows for easy performance tuning and simple extension of the core algorithms to various simulation schemes.

Modeling Yeast Cell Polarization Induced by Pheromone Gradients

NASA Astrophysics Data System (ADS)

Yi, Tau-Mu; Chen, Shanqin; Chou, Ching-Shan; Nie, Qing

2007-07-01

Yeast cells respond to spatial gradients of mating pheromones by polarizing and projecting up the gradient toward the source. It is thought that they employ a spatial sensing mechanism in which the cell compares the concentration of pheromone at different points on the cell surface and determines the maximum point, where the projection forms. Here we constructed the first spatial mathematical model of the yeast pheromone response that describes the dynamics of the heterotrimeric and Cdc42p G-protein cycles, which are linked in a cascade. Two key performance objectives of this system are (1) amplification—converting a shallow external gradient of ligand to a steep internal gradient of protein components and (2) tracking—following changes in gradient direction. We used simulations to investigate amplification mechanisms that allow tracking. We identified specific strategies for regulating the spatial dynamics of the protein components (i.e. their changing location in the cell) that would enable the cell to achieve both objectives.

Hydrodynamic modelling of a tidal delta wetland using an enhanced quasi-2D model

NASA Astrophysics Data System (ADS)

Wester, Sjoerd J.; Grimson, Rafael; Minotti, Priscilla G.; Booija, Martijn J.; Brugnach, Marcela

2018-04-01

Knowledge about the hydrological regime of wetlands is key to understand their physical and biological properties. Modelling hydrological and hydrodynamic processes within a wetland is therefore becoming increasingly important. 3D models have successfully modelled wetland dynamics but depend on very detailed bathymetry and land topography. Many 1D and 2D models of river deltas highly simplify the interaction between the river and wetland area or simply neglect the wetland area. This study proposes an enhanced quasi-2D modelling strategy that captures the interaction between river discharge and moon tides and the resulting hydrodynamics, while using the scarce data available. The water flow equations are discretised with an interconnected irregular cell scheme, in which a simplification of the 1D Saint-Venant equations is used to define the water flow between cells. The spatial structure of wetlands is based on the ecogeomorphology in complex estuarine deltas. The islands within the delta are modelled with levee cells, creek cells and an interior cell representing a shallow marsh wetland. The model is calibrated for an average year and the model performance is evaluated for another average year and additionally an extreme dry three-month period and an extreme wet three-month period. The calibration and evaluation are done based on two water level measurement stations and two discharge measurement stations, all located in the main rivers. Additional calibration is carried out with field water level measurements in a wetland area. Accurate simulations are obtained for both calibration and evaluation with high correlations between observed and simulated water levels and simulated discharges in the same order of magnitude as observed discharges. Calibration against field measurements showed that the model can successfully simulate the overflow mechanism in wetland areas. A sensitivity analysis for several wetland parameters showed that these parameters are all influencing the water level fluctuation within the wetlands to varying degrees. The enhanced quasi-2D model has the potential to accurately simulate river and wetland dynamics for large wetland areas and help to understand their hydrodynamics.

Model of the initiation of signal transduction by ligands in a cell culture: Simulation of molecules near a plane membrane comprising receptors

NASA Astrophysics Data System (ADS)

Plante, Ianik; Cucinotta, Francis A.

2011-11-01

Cell communication is a key mechanism in tissue responses to radiation. Several molecules are implicated in radiation-induced signaling between cells, but their contributions to radiation risk are poorly understood. Meanwhile, Green's functions for diffusion-influenced reactions have appeared in the literature, which are applied to describe the diffusion of molecules near a plane membrane comprising bound receptors with the possibility of reversible binding of a ligand and activation of signal transduction proteins by the ligand-receptor complex. We have developed Brownian dynamics algorithms to simulate particle histories in this system which can accurately reproduce the theoretical distribution of distances of a ligand from the membrane, the number of reversibly bound particles, and the number of receptor complexes activating signaling proteins as a function of time, regardless of the number of time steps used for the simulation. These simulations will be of great importance to model interactions at low doses where stochastic effects induced by a small number of molecules or interactions come into play.

Shock-induced transformations in crystalline RDX: a uniaxial constant-stress Hugoniostat molecular dynamics simulation study.

PubMed

Bedrov, Dmitry; Hooper, Justin B; Smith, Grant D; Sewell, Thomas D

2009-07-21

Molecular dynamics (MD) simulations of uniaxial shock compression along the [100] and [001] directions in the alpha polymorph of hexahydro-1,3,5-trinitro-1,3,5-triazine (alpha-RDX) have been conducted over a wide range of shock pressures using the uniaxial constant stress Hugoniostat method [Ravelo et al., Phys. Rev. B 70, 014103 (2004)]. We demonstrate that the Hugoniostat method is suitable for studying shock compression in atomic-scale models of energetic materials without the necessity to consider the extremely large simulation cells required for an explicit shock wave simulation. Specifically, direct comparison of results obtained using the Hugoniostat approach to those reported by Thompson and co-workers [Phys. Rev. B 78, 014107 (2008)] based on large-scale MD simulations of shocks using the shock front absorbing boundary condition (SFABC) approach indicates that Hugoniostat simulations of systems containing several thousand molecules reproduced the salient features observed in the SFABC simulations involving roughly a quarter-million molecules, namely, nucleation and growth of nanoscale shear bands for shocks propagating along the [100] direction and the polymorphic alpha-gamma phase transition for shocks directed along the [001] direction. The Hugoniostat simulations yielded predictions of the Hugoniot elastic limit for the [100] shock direction consistent with SFABC simulation results.

Mathematical Modeling and Nonlinear Dynamical Analysis of Cell Growth in Response to Antibiotics

NASA Astrophysics Data System (ADS)

Jin, Suoqin; Niu, Lili; Wang, Gang; Zou, Xiufen

2015-06-01

This study is devoted to the revelation of the dynamical mechanisms of cell growth in response to antibiotics. We establish a mathematical model of ordinary differential equations for an antibiotic-resistant growth system with one positive feedback loop. We perform a dynamical analysis of the behavior of this model system. We present adequate sets of conditions that can guarantee the existence and stability of biologically-reasonable steady states. Using bifurcation analysis and numerical simulation, we show that the relative growth rate, which is defined as the ratio of the cell growth rate to the basal cell growth rate in the absence of antibiotics, can exhibit bistable behavior in an extensive range of parameters that correspond to a growth state and a nongrowth state in biology. We discover that both antibiotic and antibiotic resistance genes can cooperatively enhance bistability, whereas the cooperative coefficient of feedback can contribute to the onset of bistability. These results would contribute to a better understanding of not only the evolution of antibiotics but also the emergence of drug resistance in other diseases.

Metabolic interactions and dynamics in microbial communities

NASA Astrophysics Data System (ADS)

Segre', Daniel

Metabolism, in addition to being the engine of every living cell, plays a major role in the cell-cell and cell-environment relations that shape the dynamics and evolution of microbial communities, e.g. by mediating competition and cross-feeding interactions between different species. Despite the increasing availability of metagenomic sequencing data for numerous microbial ecosystems, fundamental aspects of these communities, such as the unculturability of many isolates, and the conditions necessary for taxonomic or functional stability, are still poorly understood. We are developing mechanistic computational approaches for studying the interactions between different organisms based on the knowledge of their entire metabolic networks. In particular, we have recently built an open source platform for the Computation of Microbial Ecosystems in Time and Space (COMETS), which combines metabolic models with convection-diffusion equations to simulate the spatio-temporal dynamics of metabolism in microbial communities. COMETS has been experimentally tested on small artificial communities, and is scalable to hundreds of species in complex environments. I will discuss recent developments and challenges towards the implementation of models for microbiomes and synthetic microbial communities.

Mathematical modeling on T-cell mediated adaptive immunity in primary dengue infections.

PubMed

Sasmal, Sourav Kumar; Dong, Yueping; Takeuchi, Yasuhiro

2017-09-21

At present, dengue is the most common mosquito-borne viral disease in the world, and the global dengue incidence is increasing day by day due to climate changing. Here, we present a mathematical model of dengue viruses (DENVs) dynamics in micro-environment (cellular level) consisting of healthy cells, infected cells, virus particles and T-cell mediated adaptive immunity. We have considered the explicit role of cytokines and antibody in our model. We find that the virus load goes down to zero within 6 days as it is common for DENV infection. From our analysis, we have identified the important model parameters and done the numerical simulation with respect to such important parameters. We have shown that the cytokine mediated virus clearance plays a very important role in dengue dynamics. It can change the dynamical behavior of the system and causes essential extinction of the virus. Finally, we have incorporated the antiviral treatment for dengue in our model and shown that the basic reproduction number is directly proportional to the antiviral treatment effects. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

PubMed Central

Maruta, Naomichi; Marumoto, Moegi

2017-01-01

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

Parallel Adaptive High-Order CFD Simulations Characterizing Cavity Acoustics for the Complete SOFIA Aircraft

NASA Technical Reports Server (NTRS)

Barad, Michael F.; Brehm, Christoph; Kiris, Cetin C.; Biswas, Rupak

2014-01-01

This paper presents one-of-a-kind MPI-parallel computational fluid dynamics simulations for the Stratospheric Observatory for Infrared Astronomy (SOFIA). SOFIA is an airborne, 2.5-meter infrared telescope mounted in an open cavity in the aft of a Boeing 747SP. These simulations focus on how the unsteady flow field inside and over the cavity interferes with the optical path and mounting of the telescope. A temporally fourth-order Runge-Kutta, and spatially fifth-order WENO-5Z scheme was used to perform implicit large eddy simulations. An immersed boundary method provides automated gridding for complex geometries and natural coupling to a block-structured Cartesian adaptive mesh refinement framework. Strong scaling studies using NASA's Pleiades supercomputer with up to 32,000 cores and 4 billion cells shows excellent scaling. Dynamic load balancing based on execution time on individual AMR blocks addresses irregularities caused by the highly complex geometry. Limits to scaling beyond 32K cores are identified, and targeted code optimizations are discussed.

Automatic Selection of Order Parameters in the Analysis of Large Scale Molecular Dynamics Simulations.

PubMed

Sultan, Mohammad M; Kiss, Gert; Shukla, Diwakar; Pande, Vijay S

2014-12-09

Given the large number of crystal structures and NMR ensembles that have been solved to date, classical molecular dynamics (MD) simulations have become powerful tools in the atomistic study of the kinetics and thermodynamics of biomolecular systems on ever increasing time scales. By virtue of the high-dimensional conformational state space that is explored, the interpretation of large-scale simulations faces difficulties not unlike those in the big data community. We address this challenge by introducing a method called clustering based feature selection (CB-FS) that employs a posterior analysis approach. It combines supervised machine learning (SML) and feature selection with Markov state models to automatically identify the relevant degrees of freedom that separate conformational states. We highlight the utility of the method in the evaluation of large-scale simulations and show that it can be used for the rapid and automated identification of relevant order parameters involved in the functional transitions of two exemplary cell-signaling proteins central to human disease states.

Local dynamics of glass-forming polystyrene thin films from atomistic simulation

NASA Astrophysics Data System (ADS)

Zhou, Yuxing; Milner, Scott

Despite a wide technological application ranging from protective coatings to organic solar cells, there still no consensus on the mechanism for the glass transition in polymer thin films a manifestation of the infamous glass problem under confinement. Many experimental and computational studies have observed a large deviation of nanoscale dynamical properties in thin films from the corresponding properties in bulk. In this work, we perform extensive united-atom simulations on atactic polystyrene free-standing thin films near the glass transition temperature and focus on the effect of free surface on the local dynamics. We study the segmental dynamics as a function of distance from the surface for different temperatures, from which relaxation time and thereby local Tg is obtained for each layer. We find the dynamics near free surface is not only enhanced but becomes less strongly temperature dependent as Tg is approached compared to the bulk. We find an increasing length scale associated with mobility propagation from the free surface as temperature decreases, but no correlation between local structure and enhanced relaxation rates near the surface, consistent with studies on bead-spring chains.

An Unstructured Finite Volume Approach for Structural Dynamics in Response to Fluid Motions.

PubMed

Xia, Guohua; Lin, Ching-Long

2008-04-01

A new cell-vortex unstructured finite volume method for structural dynamics is assessed for simulations of structural dynamics in response to fluid motions. A robust implicit dual-time stepping method is employed to obtain time accurate solutions. The resulting system of algebraic equations is matrix-free and allows solid elements to include structure thickness, inertia, and structural stresses for accurate predictions of structural responses and stress distributions. The method is coupled with a fluid dynamics solver for fluid-structure interaction, providing a viable alternative to the finite element method for structural dynamics calculations. A mesh sensitivity test indicates that the finite volume method is at least of second-order accuracy. The method is validated by the problem of vortex-induced vibration of an elastic plate with different initial conditions and material properties. The results are in good agreement with existing numerical data and analytical solutions. The method is then applied to simulate a channel flow with an elastic wall. The effects of wall inertia and structural stresses on the fluid flow are investigated.

Rate-equation modelling and ensemble approach to extraction of parameters for viral infection-induced cell apoptosis and necrosis

NASA Astrophysics Data System (ADS)

Domanskyi, Sergii; Schilling, Joshua E.; Gorshkov, Vyacheslav; Libert, Sergiy; Privman, Vladimir

2016-09-01

We develop a theoretical approach that uses physiochemical kinetics modelling to describe cell population dynamics upon progression of viral infection in cell culture, which results in cell apoptosis (programmed cell death) and necrosis (direct cell death). Several model parameters necessary for computer simulation were determined by reviewing and analyzing available published experimental data. By comparing experimental data to computer modelling results, we identify the parameters that are the most sensitive to the measured system properties and allow for the best data fitting. Our model allows extraction of parameters from experimental data and also has predictive power. Using the model we describe interesting time-dependent quantities that were not directly measured in the experiment and identify correlations among the fitted parameter values. Numerical simulation of viral infection progression is done by a rate-equation approach resulting in a system of "stiff" equations, which are solved by using a novel variant of the stochastic ensemble modelling approach. The latter was originally developed for coupled chemical reactions.

Rate-equation modelling and ensemble approach to extraction of parameters for viral infection-induced cell apoptosis and necrosis

NASA Astrophysics Data System (ADS)

Domanskyi, Sergii; Schilling, Joshua; Gorshkov, Vyacheslav; Libert, Sergiy; Privman, Vladimir

We develop a theoretical approach that uses physiochemical kinetics modelling to describe cell population dynamics upon progression of viral infection in cell culture, which results in cell apoptosis (programmed cell death) and necrosis (direct cell death). Several model parameters necessary for computer simulation were determined by reviewing and analyzing available published experimental data. By comparing experimental data to computer modelling results, we identify the parameters that are the most sensitive to the measured system properties and allow for the best data fitting. Our model allows extraction of parameters from experimental data and also has predictive power. Using the model we describe interesting time-dependent quantities that were not directly measured in the experiment and identify correlations among the fitted parameter values. Numerical simulation of viral infection progression is done by a rate-equation approach resulting in a system of ``stiff'' equations, which are solved by using a novel variant of the stochastic ensemble modelling approach. The latter was originally developed for coupled chemical reactions.

Kinetic modeling of multi-feed simultaneous saccharification and co-fermentation of pretreated birch to ethanol.

PubMed

Wang, Ruifei; Koppram, Rakesh; Olsson, Lisbeth; Franzén, Carl Johan

2014-11-01

Fed-batch simultaneous saccharification and fermentation (SSF) is a feasible option for bioethanol production from lignocellulosic raw materials at high substrate concentrations. In this work, a segregated kinetic model was developed for simulation of fed-batch simultaneous saccharification and co-fermentation (SSCF) of steam-pretreated birch, using substrate, enzymes and cell feeds. The model takes into account the dynamics of the cellulase-cellulose system and the cell population during SSCF, and the effects of pre-cultivation of yeast cells on fermentation performance. The model was cross-validated against experiments using different feed schemes. It could predict fermentation performance and explain observed differences between measured total yeast cells and dividing cells very well. The reproducibility of the experiments and the cell viability were significantly better in fed-batch than in batch SSCF at 15% and 20% total WIS contents. The model can be used for simulation of fed-batch SSCF and optimization of feed profiles. Copyright © 2014 Elsevier Ltd. All rights reserved.

Chemo-mechanical modeling of tumor growth in elastic epithelial tissue

NASA Astrophysics Data System (ADS)

Bratsun, Dmitry A.; Zakharov, Andrey P.; Pismen, Len

2016-08-01

We propose a multiscale chemo-mechanical model of the cancer tumor development in the epithelial tissue. The epithelium is represented by an elastic 2D array of polygonal cells with its own gene regulation dynamics. The model allows the simulation of the evolution of multiple cells interacting via the chemical signaling or mechanically induced strain. The algorithm includes the division and intercalation of cells as well as the transformation of normal cells into a cancerous state triggered by a local failure of the spatial synchronization of the cellular rhythms driven by transcription/translation processes. Both deterministic and stochastic descriptions of the system are given for chemical signaling. The transformation of cells means the modification of their respective parameters responsible for chemo-mechanical interactions. The simulations reproduce a distinct behavior of invasive and localized carcinoma. Generally, the model is designed in such a way that it can be readily modified to take account of any newly understood gene regulation processes and feedback mechanisms affecting chemo-mechanical properties of cells.

Multiscale dynamics of biological cells with chemotactic interactions: From a discrete stochastic model to a continuous description

NASA Astrophysics Data System (ADS)

Alber, Mark; Chen, Nan; Glimm, Tilmann; Lushnikov, Pavel M.

2006-05-01

The cellular Potts model (CPM) has been used for simulating various biological phenomena such as differential adhesion, fruiting body formation of the slime mold Dictyostelium discoideum, angiogenesis, cancer invasion, chondrogenesis in embryonic vertebrate limbs, and many others. We derive a continuous limit of a discrete one-dimensional CPM with the chemotactic interactions between cells in the form of a Fokker-Planck equation for the evolution of the cell probability density function. This equation is then reduced to the classical macroscopic Keller-Segel model. In particular, all coefficients of the Keller-Segel model are obtained from parameters of the CPM. Theoretical results are verified numerically by comparing Monte Carlo simulations for the CPM with numerics for the Keller-Segel model.

Investigation of phase transitions of saturated phosphocholine lipid bilayers via molecular dynamics simulations.

PubMed

Khakbaz, Pouyan; Klauda, Jeffery B

2018-08-01

Lipid bilayers play an important role in biological systems as they protect cells against unwanted chemicals and provide a barrier for material inside a cell from leaking out. In this paper, nearly 30 μs of molecular dynamics (MD) simulations were performed to investigate phase transitions of 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC) and 1,2-dipalmitoyl-sn-glycero-phosphocholine (DPPC) lipid bilayers from the liquid crystalline (L α ) to the ripple (P β ) and to the gel phase (L β ). Our MD simulations accurately predict the main transition temperature for the single-component bilayers. A key focus of this work is to quantify the structure of the P β phase for DMPC and compare with measures from x-ray experiments. The P β major arm has similar structure to that of the L β , while the thinner minor arm has interdigitated chains and the transition region between these two regions has large chain splay and disorder. At lower temperatures, our MD simulations predict the formation of the L β phase with tilted fatty acid chains. The P β and L β phases are studied for mixtures of DMPC and DPPC and compare favorably with experiment. Overall, our MD simulations provide evidence for the relevancy of the CHARMM36 lipid force field for structures and add to our understanding of the less-defined P β phase. Copyright © 2018 Elsevier B.V. All rights reserved.

Mathematical modeling of bone marrow--peripheral blood dynamics in the disease state based on current emerging paradigms, part I.

PubMed

Afenya, Evans K; Ouifki, Rachid; Camara, Baba I; Mundle, Suneel D

2016-04-01

Stemming from current emerging paradigms related to the cancer stem cell hypothesis, an existing mathematical model is expanded and used to study cell interaction dynamics in the bone marrow and peripheral blood. The proposed mathematical model is described by a system of nonlinear differential equations with delay, to quantify the dynamics in abnormal hematopoiesis. The steady states of the model are analytically and numerically obtained. Some conditions for the local asymptotic stability of such states are investigated. Model analyses suggest that malignancy may be irreversible once it evolves from a nonmalignant state into a malignant one and no intervention takes place. This leads to the proposition that a great deal of emphasis be placed on cancer prevention. Nevertheless, should malignancy arise, treatment programs for its containment or curtailment may have to include a maximum and extensive level of effort to protect normal cells from eventual destruction. Further model analyses and simulations predict that in the untreated disease state, there is an evolution towards a situation in which malignant cells dominate the entire bone marrow - peripheral blood system. Arguments are then advanced regarding requirements for quantitatively understanding cancer stem cell behavior. Among the suggested requirements are, mathematical frameworks for describing the dynamics of cancer initiation and progression, the response to treatment, the evolution of resistance, and malignancy prevention dynamics within the bone marrow - peripheral blood architecture. Copyright © 2016 Elsevier Inc. All rights reserved.

Simulation of Cell Patterning Triggered by Cell Death and Differential Adhesion in Drosophila Wing.

PubMed

Nagai, Tatsuzo; Honda, Hisao; Takemura, Masahiko

2018-02-27

The Drosophila wing exhibits a well-ordered cell pattern, especially along the posterior margin, where hair cells are arranged in a zigzag pattern in the lateral view. Based on an experimental result observed during metamorphosis of Drosophila, we considered that a pattern of initial cells autonomously develops to the zigzag pattern through cell differentiation, intercellular communication, and cell death (apoptosis) and performed computer simulations of a cell-based model of vertex dynamics for tissues. The model describes the epithelial tissue as a monolayer cell sheet of polyhedral cells. Their vertices move according to equations of motion, minimizing the sum total of the interfacial and elastic energies of cells. The interfacial energy densities between cells are introduced consistently with an ideal zigzag cell pattern, extracted from the experimental result. The apoptosis of cells is modeled by gradually reducing their equilibrium volume to zero and by assuming that the hair cells prohibit neighboring cells from undergoing apoptosis. Based on experimental observations, we also assumed wing elongation along the proximal-distal axis. Starting with an initial cell pattern similar to the micrograph experimentally obtained just before apoptosis, we carried out the simulations according to the model mentioned above and successfully reproduced the ideal zigzag cell pattern. This elucidates a physical mechanism of patterning triggered by cell apoptosis theoretically and exemplifies, to our knowledge, a new framework to study apoptosis-induced patterning. We conclude that the zigzag cell pattern is formed by an autonomous communicative process among the participant cells. Copyright © 2018 Biophysical Society. All rights reserved.

Modeling cardiovascular hemodynamics using the lattice Boltzmann method on massively parallel supercomputers

NASA Astrophysics Data System (ADS)

Randles, Amanda Elizabeth

Accurate and reliable modeling of cardiovascular hemodynamics has the potential to improve understanding of the localization and progression of heart diseases, which are currently the most common cause of death in Western countries. However, building a detailed, realistic model of human blood flow is a formidable mathematical and computational challenge. The simulation must combine the motion of the fluid, the intricate geometry of the blood vessels, continual changes in flow and pressure driven by the heartbeat, and the behavior of suspended bodies such as red blood cells. Such simulations can provide insight into factors like endothelial shear stress that act as triggers for the complex biomechanical events that can lead to atherosclerotic pathologies. Currently, it is not possible to measure endothelial shear stress in vivo, making these simulations a crucial component to understanding and potentially predicting the progression of cardiovascular disease. In this thesis, an approach for efficiently modeling the fluid movement coupled to the cell dynamics in real-patient geometries while accounting for the additional force from the expansion and contraction of the heart will be presented and examined. First, a novel method to couple a mesoscopic lattice Boltzmann fluid model to the microscopic molecular dynamics model of cell movement is elucidated. A treatment of red blood cells as extended structures, a method to handle highly irregular geometries through topology driven graph partitioning, and an efficient molecular dynamics load balancing scheme are introduced. These result in a large-scale simulation of the cardiovascular system, with a realistic description of the complex human arterial geometry, from centimeters down to the spatial resolution of red-blood cells. The computational methods developed to enable scaling of the application to 294,912 processors are discussed, thus empowering the simulation of a full heartbeat. Second, further extensions to enable the modeling of fluids in vessels with smaller diameters and a method for introducing the deformational forces exerted on the arterial flows from the movement of the heart by borrowing concepts from cosmodynamics are presented. These additional forces have a great impact on the endothelial shear stress. Third, the fluid model is extended to not only recover Navier-Stokes hydrodynamics, but also a wider range of Knudsen numbers, which is especially important in micro- and nano-scale flows. The tradeoffs of many optimizations methods such as the use of deep halo level ghost cells that, alongside hybrid programming models, reduce the impact of such higher-order models and enable efficient modeling of extreme regimes of computational fluid dynamics are discussed. Fourth, the extension of these models to other research questions like clogging in microfluidic devices and determining the severity of co-arctation of the aorta is presented. Through this work, a validation of these methods by taking real patient data and the measured pressure value before the narrowing of the aorta and predicting the pressure drop across the co-arctation is shown. Comparison with the measured pressure drop in vivo highlights the accuracy and potential impact of such patient specific simulations. Finally, a method to enable the simulation of longer trajectories in time by discretizing both spatially and temporally is presented. In this method, a serial coarse iterator is used to initialize data at discrete time steps for a fine model that runs in parallel. This coarse solver is based on a larger time step and typically a coarser discretization in space. Iterative refinement enables the compute-intensive fine iterator to be modeled with temporal parallelization. The algorithm consists of a series of prediction-corrector iterations completing when the results have converged within a certain tolerance. Combined, these developments allow large fluid models to be simulated for longer time durations than previously possible.

From retinal waves to activity-dependent retinogeniculate map development.

PubMed

Markowitz, Jeffrey; Cao, Yongqiang; Grossberg, Stephen

2012-01-01

A neural model is described of how spontaneous retinal waves are formed in infant mammals, and how these waves organize activity-dependent development of a topographic map in the lateral geniculate nucleus, with connections from each eye segregated into separate anatomical layers. The model simulates the spontaneous behavior of starburst amacrine cells and retinal ganglion cells during the production of retinal waves during the first few weeks of mammalian postnatal development. It proposes how excitatory and inhibitory mechanisms within individual cells, such as Ca(2+)-activated K(+) channels, and cAMP currents and signaling cascades, can modulate the spatiotemporal dynamics of waves, notably by controlling the after-hyperpolarization currents of starburst amacrine cells. Given the critical role of the geniculate map in the development of visual cortex, these results provide a foundation for analyzing the temporal dynamics whereby the visual cortex itself develops.

Mass-conserved volumetric lattice Boltzmann method for complex flows with willfully moving boundaries.

PubMed

Yu, Huidan; Chen, Xi; Wang, Zhiqiang; Deep, Debanjan; Lima, Everton; Zhao, Ye; Teague, Shawn D

2014-06-01

In this paper, we develop a mass-conserved volumetric lattice Boltzmann method (MCVLBM) for numerically solving fluid dynamics with willfully moving arbitrary boundaries. In MCVLBM, fluid particles are uniformly distributed in lattice cells and the lattice Boltzmann equations deal with the time evolution of the particle distribution function. By introducing a volumetric parameter P(x,y,z,t) defined as the occupation of solid volume in the cell, we distinguish three types of lattice cells in the simulation domain: solid cell (pure solid occupation, P=1), fluid cell (pure fluid occupation, P=0), and boundary cell (partial solid and partial fluid, 0

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.

An individual-based modeling approach to simulate the effects of cellular nutrient competition on Escherichia coli K-12 MG1655 colony behavior and interactions in aerobic structured food systems.

PubMed

Tack, Ignace L M M; Logist, Filip; Noriega Fernández, Estefanía; Van Impe, Jan F M

2015-02-01

Traditional kinetic models in predictive microbiology reliably predict macroscopic dynamics of planktonically-growing cell cultures in homogeneous liquid food systems. However, most food products have a semi-solid structure, where microorganisms grow locally in colonies. Individual colony cells exhibit strongly different and non-normally distributed behavior due to local nutrient competition. As a result, traditional models considering average population behavior in a homogeneous system do not describe colony dynamics in full detail. To incorporate local resource competition and individual cell differences, an individual-based modeling approach has been applied to Escherichia coli K-12 MG1655 colonies, considering the microbial cell as modeling unit. The first contribution of this individual-based model is to describe single colony growth under nutrient-deprived conditions. More specifically, the linear and stationary phase in the evolution of the colony radius, the evolution from a disk-like to branching morphology, and the emergence of a starvation zone in the colony center are simulated and compared to available experimental data. These phenomena occur earlier at more severe nutrient depletion conditions, i.e., at lower nutrient diffusivity and initial nutrient concentration in the medium. Furthermore, intercolony interactions have been simulated. Higher inoculum densities lead to stronger intercolony interactions, such as colony merging and smaller colony sizes, due to nutrient competition. This individual-based model contributes to the elucidation of characteristic experimentally observed colony behavior from mechanistic information about cellular physiology and interactions. Copyright © 2014 Elsevier Ltd. All rights reserved.

Emergence of diversity in homogeneous coupled Boolean networks

NASA Astrophysics Data System (ADS)

Kang, Chris; Aguilar, Boris; Shmulevich, Ilya

2018-05-01

The origin of multicellularity in metazoa is one of the fundamental questions of evolutionary biology. We have modeled the generic behaviors of gene regulatory networks in isogenic cells as stochastic nonlinear dynamical systems—coupled Boolean networks with perturbation. Model simulations under a variety of dynamical regimes suggest that the central characteristic of multicellularity, permanent spatial differentiation (diversification), indeed can arise. Additionally, we observe that diversification is more likely to occur near the critical regime of Lyapunov stability.

TOWARDS A MULTI-SCALE AGENT-BASED PROGRAMMING LANGUAGE METHODOLOGY

PubMed Central

Somogyi, Endre; Hagar, Amit; Glazier, James A.

2017-01-01

Living tissues are dynamic, heterogeneous compositions of objects, including molecules, cells and extra-cellular materials, which interact via chemical, mechanical and electrical process and reorganize via transformation, birth, death and migration processes. Current programming language have difficulty describing the dynamics of tissues because: 1: Dynamic sets of objects participate simultaneously in multiple processes, 2: Processes may be either continuous or discrete, and their activity may be conditional, 3: Objects and processes form complex, heterogeneous relationships and structures, 4: Objects and processes may be hierarchically composed, 5: Processes may create, destroy and transform objects and processes. Some modeling languages support these concepts, but most cannot translate models into executable simulations. We present a new hybrid executable modeling language paradigm, the Continuous Concurrent Object Process Methodology (CCOPM) which naturally expresses tissue models, enabling users to visually create agent-based models of tissues, and also allows computer simulation of these models. PMID:29282379

TOWARDS A MULTI-SCALE AGENT-BASED PROGRAMMING LANGUAGE METHODOLOGY.

PubMed

Somogyi, Endre; Hagar, Amit; Glazier, James A

2016-12-01

Living tissues are dynamic, heterogeneous compositions of objects , including molecules, cells and extra-cellular materials, which interact via chemical, mechanical and electrical process and reorganize via transformation, birth, death and migration processes . Current programming language have difficulty describing the dynamics of tissues because: 1: Dynamic sets of objects participate simultaneously in multiple processes, 2: Processes may be either continuous or discrete, and their activity may be conditional, 3: Objects and processes form complex, heterogeneous relationships and structures, 4: Objects and processes may be hierarchically composed, 5: Processes may create, destroy and transform objects and processes. Some modeling languages support these concepts, but most cannot translate models into executable simulations. We present a new hybrid executable modeling language paradigm, the Continuous Concurrent Object Process Methodology ( CCOPM ) which naturally expresses tissue models, enabling users to visually create agent-based models of tissues, and also allows computer simulation of these models.