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Find video protocols related to scientific articles indexed in Pubmed.
Reconstruction of network structures from repeating spike patterns in simulated bursting dynamics.
Phys Rev E Stat Nonlin Soft Matter Phys
PUBLISHED: 07-11-2014
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Repeating patterns of spike sequences from a neuronal network have been proposed to be useful in the reconstruction of the network topology. Reverberations in a physiologically realistic model with various physical connection topologies (from random to scale free) have been simulated to study the effectiveness of the pattern-matching method in the reconstruction of network topology from network dynamics. Simulation results show that functional networks reconstructed from repeating spike patterns can be quite different from the original physical networks; even global properties, such as the degree distribution, cannot always be recovered. However, the pattern-matching method can be effective in identifying hubs in the network. Since the form of reverberations is quite different for networks with and without hubs, the form of reverberations together with the reconstruction by repeating spike patterns might provide a reliable method to detect hubs in neuronal cultures.
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Intrinsic fluctuations of cell migration under different cellular densities.
Soft Matter
PUBLISHED: 03-19-2014
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The motility of the Dictyostelium discoideum (DD) cell is studied by video microscopy when the cells are plated on top of an agar plate at different densities, n. It is found that the fluctuating kinetics of the cells can be divided into two normal directions: the cell's forward-moving direction and its normal direction. Along the forward-moving direction, the slope of the amplitude of fluctuation vs. velocity (R||(v)) increases with n, while along the normal direction the slope of R? is independent of n. Both R|| and R? are functions of the cell speed v. The observed linearity in R?(v) indicated that the amplitude of orientational fluctuation (?) of DD cells is a constant independent of v. The independence of the slope of R?(v) on n indicated that ? is also not affected by cellular interactions. The independence of ? on both v and n suggests that orientational fluctuation originates from the intrinsic property of motion fluctuations in DD.
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Extracting connectivity from dynamics of networks with uniform bidirectional coupling.
Phys Rev E Stat Nonlin Soft Matter Phys
PUBLISHED: 06-17-2013
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In the study of networked systems, a method that can extract information about how the individual nodes are connected with one another would be valuable. In this paper, we present a method that can yield such information of network connectivity using measurements of the dynamics of the nodes as the only input data. Our method is built upon a noise-induced relation between the Laplacian matrix of the network and the dynamical covariance matrix of the nodes, and applies to networked dynamical systems in which the coupling between nodes is uniform and bidirectional. Using examples of different networks and dynamics, we demonstrate that the method can give accurate connectivity information for a wide range of noise amplitude and coupling strength. Moreover, we can calculate a parameter ? using again only the input of time-series data, and assess the accuracy of the extracted connectivity information based on the value of ?.
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Model on cell movement, growth, differentiation and de-differentiation: reaction-diffusion equation and wave propagation.
Eur Phys J E Soft Matter
PUBLISHED: 06-04-2013
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We construct a model for cell proliferation with differentiation into different cell types, allowing backward de-differentiation and cell movement. With different cell types labeled by state variables, the model can be formulated in terms of the associated transition probabilities between various states. The cell population densities can be described by coupled reaction-diffusion partial differential equations, allowing steady wavefront propagation solutions. The wavefront profile is calculated analytically for the simple pure growth case (2-states), and analytic expressions for the steady wavefront propagating speeds and population growth rates are obtained for the simpler cases of 2-, 3- and 4-states systems. These analytic results are verified by direct numerical solutions of the reaction-diffusion PDEs. Furthermore, in the absence of de-differentiation, it is found that, as the mobility and/or self-proliferation rate of the down-lineage descendant cells become sufficiently large, the propagation dynamics can switch from a steady propagating wavefront to the interesting situation of propagation of a faster wavefront with a slower waveback. For the case of a non-vanishing de-differentiation probability, the cell growth rate and wavefront propagation speed are both enhanced, and the wavefront speeds can be obtained analytically and confirmed by numerical solution of the reaction-diffusion equations.
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Suppression of cardiac alternans by alternating-period-feedback stimulations.
Phys Rev E Stat Nonlin Soft Matter Phys
PUBLISHED: 03-18-2013
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Alternans response, comprising a sequence of alternating long and short action potential durations in heart tissue, seen during rapid periodic pacing can lead to conduction block resulting in potentially fatal cardiac failure. A method of pacing with feedback control is proposed to reduce the alternans and therefore the probability of subsequent cardiac failure. The reduction is achieved by feedback control using small perturbations of constant magnitude to the original, alternans-generating pacing period T, viz., using sequences of two alternating periods of T+?T and T-?T, with ?T
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Effect of anticipation on knee kinematics during a stop-jump task.
Gait Posture
PUBLISHED: 03-04-2013
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Knee stability during a functional assessment of the stop-jump task is a key factor to determine if an athlete is adequately rehabilitated after knee ligamentous injury. This study aimed to investigate knee stability due to the effect of anticipation on landing maneuvers during planned and unplanned stop-jump tasks. Knee kinematics of ten healthy male participants were collected using an optical motion analysis system during stop-jump tasks. Stop jumps were performed in four different landing positions either in planned movement or in an unplanned movement on a signal triggered as participants passed through a photocell gate. Kinematic data at the time of foot strike at landing in the stop-jump considered for investigating the anticipation effect during the stop-jump tasks. Two-way multivariate analysis of variance (MANOVA) with repeated measures and stratified paired t-tests were conducted to compare the knee kinematics data between planned and unplanned tasks. Statistical significance was set at the p<0.05 level. External rotational angle showed a significant decrease in unplanned stop-jump tasks during forward (p<0.05) and right (p<0.05) jumps when compared to that of planned tasks. Flexion angle and abduction angle during forward, vertical and right jumps were significantly decreased in the unplanned tasks. Anticipation significantly influenced the landing maneuvers of stop-jump task. The results indicated that both planned and unplanned stop-jump tasks should be considered when monitoring the rehabilitation progress after a ligamentous injury.
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Simple models for quorum sensing: nonlinear dynamical analysis.
Phys Rev E Stat Nonlin Soft Matter Phys
PUBLISHED: 06-22-2011
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Quorum sensing refers to the change in the cooperative behavior of a collection of elements in response to the change in their population size or density. This behavior can be observed in chemical and biological systems. These elements or cells are coupled via chemicals in the surrounding environment. Here we focus on the change of dynamical behavior, in particular from quiescent to oscillatory, as the cell population changes. For instance, the silent behavior of the elements can become oscillatory as the system concentration or population increases. In this work, two simple models are constructed that can produce the essential representative properties in quorum sensing. The first is an excitable or oscillatory phase model, which is probably the simplest model one can construct to describe quorum sensing. Using the mean-field approximation, the parameter regime for quorum sensing behavior can be identified, and analytical results for the detailed dynamical properties, including the phase diagrams, are obtained and verified numerically. The second model consists of FitzHugh-Nagumo elements coupled to the signaling chemicals in the environment. Nonlinear dynamical analysis of this mean-field model exhibits rich dynamical behaviors, such as infinite period bifurcation, supercritical Hopf, fold bifurcation, and subcritical Hopf bifurcations as the population parameter changes for different coupling strengths. Analytical result is obtained for the Hopf bifurcation phase boundary. Furthermore, two elements coupled via the environment and their synchronization behavior for these two models are also investigated. For both models, it is found that the onset of oscillations is accompanied by the synchronized dynamics of the two elements. Possible applications and extension of these models are also discussed.
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Stretching and migration of DNA by solvent elasticity in an oscillatory flow.
Phys Rev E Stat Nonlin Soft Matter Phys
PUBLISHED: 04-04-2011
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A model with solution viscoelasticity is proposed to explain the ratchetlike stretching of DNA by a symmetric ac electric field in polymer solutions. In this model, DNA is stretched by the interaction between the fluid elasticity and the oscillatory flow induced by DNA. Predictions of the model are confirmed by DNA stretching experiments performed in various polymer solutions and the corresponding rheological measurements of the solutions. In particular, experiments have verified that a net migration of stretched DNA in polymer solutions can be induced by a zero-mean asymmetric ac electric field. This last finding cannot be explained by other existing models.
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Effects of glial release and somatic receptors on bursting in synchronized neuronal networks.
Phys Rev E Stat Nonlin Soft Matter Phys
PUBLISHED: 02-15-2011
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A model is constructed to study the phenomenon of bursting in cultured neuronal networks by considering the effects of glial release and the extrasynaptic receptors on neurons. In the frequently observed situations of synchronized bursting, the whole neuronal network can be described by a mean-field model. In this model, the dynamics of the synchronized network in the presence of glia is represented by an effective two-compartment neuron with stimulations on both the dendrite and soma. Numerical simulations of this model show that most of the experimental observations in bursting, in particular the high plateau and the slow repolarization, can be reproduced. Our findings suggest that the effects of glia release and extrasynaptic receptors, which are usually neglected in neuronal models, can become important in intense network activities. Furthermore, simulations of the model are also performed for the case of glia-suppressed cultures to compare with recent experimental results.
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Frequency enhancement in coupled noisy excitable elements.
Phys. Rev. Lett.
PUBLISHED: 01-20-2011
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Oscillatory dynamics of coupled excitable FitzHugh-Nagumo elements in the presence of noise is investigated as a function of the coupling strength g. For two such coupled elements, their frequencies are enhanced and will synchronize at a frequency higher than the uncoupled frequencies of each element. As g increases, there is an unexpected peak in the frequency enhancement before reaching synchronization. The results can be understood with an analytic model based on the excitation across a potential barrier whose height is controlled by g. Simulation results of a coupled square lattice can quantitatively reproduce the unexpected peak in the variation of the beating rates observed in cultured cardiac cells experiments.
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Zero-refractoriness spirals in phase-coupled excitable media.
Phys Rev E Stat Nonlin Soft Matter Phys
PUBLISHED: 05-07-2009
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Effects of excitability and coupling strength on plane and spiral waves in two-dimensional excitable lattices modeled by phase-coupled elements are investigated. The corresponding phase diagrams for stable plane waves and spiral waves are obtained by simulations. The parameters capable of supporting stable spiral waves are sorted out together with the spiral rotation frequencies. This discrete model corresponds to an excitable medium with zero refractoriness and in the continuum limit supports zero-core spiral waves. The associated wave propagating behaviors are also discussed analytically and verified.
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Robustness and adaptation reveal plausible cell cycle controlling subnetwork in Saccharomyces cerevisiae.
Gene
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Biological systems are often organized spatially and temporally by multi-scale functional subsystems (modules). A specific subcellular process often corresponds to a subsystem composed of some of these interconnected modules. Accurate identification of system-level modularity organization from the large scale networks can provide valuable information on subsystem models of subcellular processes or physiological phenomena. Computational identification of functional modules from the large scale network is the key approach to solve the complexity of modularity in the past decade, but the overlapping and multi-scale nature of modules often renders unsatisfactory results in these methods. Most current methods for modularity detection are optimization-based and suffered from the drawback of size resolution limit. It is difficult to trace the origin of the unsatisfactory results, which may be due to poor data, inappropriate objective function selection or simply resulted from natural evolution, and hence no system-level accurate modular models for subcellular processes can be offered. Motivated by the idea of evolution with robustness and adaption as guiding principles, we propose a novel approach that can identify significant multi-scale overlapping modules that are sufficiently accurate at the system and subsystem levels, giving biological insights for subcellular processes. The success of our evolution strategy method is demonstrated by applying to the yeast protein-protein interaction network. Functional subsystems of important physiological phenomena can be revealed. In particular, the cell cycle controlling network is selected for detailed discussion. The cell cycle subcellular processes in yeast can be successfully dissected into functional modules of cell cycle control, cell size check point, spindle assembly checkpoint, and DNA damage check point in G2/M and S phases. The interconnections between check points and cell cycle control modules provide clues on the signal stimulus entries of check points into the cell cycle, which are consistent with experimental findings. This evolution strategy method can be applied adequately to extract the plausible yeast cell cycle subnetworks from the whole network. Connections between modules in the obtained cell cycle subnetworks reveal significant cell cycle control mechanisms. This method can also be useful when applied to other biological systems at various temporal and spatial scales for example, the gene transcription networks, and biological systems from mesoscopic scale, e.g cortical network in brain, to subcellular molecular networks.
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Population dynamics and wave propagation in a Lotka-Volterra system with spatial diffusion.
Phys Rev E Stat Nonlin Soft Matter Phys
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We consider the competitive population dynamics of two species described by the Lotka-Volterra model in the presence of spatial diffusion. The model is described by the diffusion coefficient (d(?)) and proliferation rate (r(?)) of the species ? (? = 1,2 is the species label). Propagating wave front solutions in one dimension are investigated analytically and by numerical solutions. It is found that the wave profiles and wave speeds are determined by the speed parameters, v(?) ? 2 sqrt [d(?)r(?)], of the two species, and the phase diagrams for various inter- and intracompetitive scenarios are determined. The steady wave front speeds are obtained analytically via nonlinear dynamics analysis and verified by numerical solutions. The effect of the intermediate stationary state is investigated and propagating wave profiles beyond the simple Fisher wave fronts are revealed. The wave front speed of a species can display abrupt increase as its speed parameter is increased. In particular for the case in which both species are aggressive, our results show that the speed parameter is the deciding factor that determines the ultimate surviving species, in contrast to the case without diffusion in which the final surviving species is decided by its initial population advantage. Possible relations to the biological relevance of modeling cancer development and wound healing are also discussed.
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Uncontrolled growth resulting from dedifferentiation in a skin cell proliferation model.
Phys Rev E Stat Nonlin Soft Matter Phys
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By introducing a small backward dedifferentiation probability of postmitotic cells to progenitor cells in a recently proposed skin cell proliferation model, the homeostasis of the system can be disrupted resulting in uncontrolled growth. It is found that when the dedifferentiation probability exceeds a small critical value, the stable fixed point of the system vanishes leading to unlimited cell growth resembling scenarios in carcinogenesis. Explicit expression for the critical dedifferentiation probability and phase diagram are calculated analytically and the associated nonlinear dynamics is analyzed. In the presence of stochastic fluctuations, our model predicts that the escape rate from homeostatic growth to uncontrolled growth is greatly enhanced by a small but finite dedifferentiation probability. These results are verified by numerical solutions of the dynamical system and chemical Langevin equations.
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What is Visualize?

JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

How does it work?

We use abstracts found on PubMed and match them to JoVE videos to create a list of 10 to 30 related methods videos.

Video X seems to be unrelated to Abstract Y...

In developing our video relationships, we compare around 5 million PubMed articles to our library of over 4,500 methods videos. In some cases the language used in the PubMed abstracts makes matching that content to a JoVE video difficult. In other cases, there happens not to be any content in our video library that is relevant to the topic of a given abstract. In these cases, our algorithms are trying their best to display videos with relevant content, which can sometimes result in matched videos with only a slight relation.