Synchronizing a multicellular system by external input: an artificial control strategy

MOTIVATION: Although there are significant advances on elucidating the collective behaviors on biological organisms in recent years, the essential mechanisms by which the collective rhythms arise remain to be fully understood, and further how to synchronize multicellular networks by artificial control strategy has not yet been well explored. RESULTS: A control strategy is developed to synchronize gene regulatory networks in a multicellular system when spontaneous synchronization cannot be achieved. We first construct an impulsive control system to model the process of periodically injecting coupling substances with constant or random impulsive control amounts into the common extracellular medium, and further study its effects on the dynamics of individual cells. We derive the threshold of synchronization induced by the periodic substance input. Therefore, we can synchronize the multicellular network to a specific collective behavior by changing the frequency and amplitude of the periodic stimuli. Moreover, a two-stage scheme is proposed to facilitate the synchronization in this paper. We show that the presence of the external input may also initiate different dynamics. The multicellular network of coupled repressilators is used to show the effectiveness of the proposed method. The results not only provide a perspective to understand the interactions between external stimuli and intrinsic physiological rhythms, but also may lead to development of realistic artificial control strategy and medical therapy. AVAILABILITY: CONTACT: aihara@sat.t.u-tokyo.ac.jp.     

Adaptive Control Based Harvesting Strategy for a Predator–Prey Dynamical System

This paper deals with designing a harvesting control strategy for a predator–prey dynamical system, with parametric uncertainties and exogenous disturbances. A feedback control law for the harvesting rate of the predator is formulated such that the population dynamics is asymptotically stabilized at a positive operating point, while maintaining a positive, steady state harvesting rate. The hierarchical block strict feedback structure of the dynamics is exploited in designing a backstepping control law, based on Lyapunov theory. In order to account for unknown parameters, an adaptive control strategy has been proposed in which the control law depends on an adaptive variable which tracks the unknown parameter. Further, a switching component has been incorporated to robustify the control performance against bounded disturbances. Proofs have been provided to show that the proposed adaptive control strategy ensures asymptotic stability of the dynamics at a desired operating point, as well as exact parameter learning in the disturbance-free case and learning with bounded error in the disturbance prone case. The dynamics, with uncertainty in the death rate of the predator, subjected to a bounded disturbance has been simulated with the proposed control strategy.     

Coherent Control of Gap Plasmons of a Complex Nanosystem by Shaping Driving Femtosecond Pulses

Geometry-based control of local field of coupled plasmonic nanostructures is efficient for optimization of the field intensity. However, it provides weak control over spatial and temporal dynamics of the field and thus unsuitable for experimental studies and practical applications where fixed geometries are needed. In this study, we report on pulsed excitation of strongly coupled plasmonic nanosystem comprised of nanorod and split-ring antenna. The near-field intensities are manipulated by controlling time delay, relative phase, and polarization of the ultrafast excitation pulses. We show that the spectral and spatial intensities of the local fields at the gap regions of the coupled nanosystem can be pronounced by using two identical pulses with least time delay and phase difference. The corresponding temporal intensities of electric near-fields for both parallel and orthogonal polarization of the illumination fields are also briefly discussed. These findings might have implications for controlled excitation of complexly coupled plasmonic nanosystems.     

Fuzzy subset approach in coupled population dynamics of blowflies

This paper is a study on the population dynamics of blowflies employing a density-dependent, non-linear mathematical model and a coupled population formalism. In this study, we investigated the coupled population dynamics applying fuzzy subsets to model the population trajectory, analyzing demographic parameters such as fecundity, survival, and migration. The main results suggest different possibilities in terms of dynamic behavior produced by migration in coupled populations between distinct environments and the rescue effect generated by the connection between populations. It was possible to conclude that environmental heterogeneity can play an important role in blowfly metapopulation systems. The implications of these results for population dynamics of blowflies are discussed.     

Pinning synchronization of coupled inertial delayed neural networks

The paper is devoted to the investigation of synchronization for an array of linearly and diffusively coupled inertial delayed neural networks (DNNs). By placing feedback control on a small fraction of network nodes, the entire coupled DNNs can be synchronized to a common objective trajectory asymptotically. Two different analysis methods, including matrix measure strategy and Lyapunov–Krasovskii function approach, are employed to provide sufficient criteria for the synchronization control problem. Comparisons of these two techniques are given at the end of the paper. Finally, an illustrative example is provided to show the effectiveness of the obtained theoretical results.     

Decentralized self-selection of swarm trajectories: from dynamical systems theory to robotic implementation

In this paper, we present a distributed control strategy, enabling agents to converge onto and travel along a consensually selected curve among a class of closed planar curves. Individual agents identify the number of neighbors within a finite circular sensing range and obtain information from their neighbors through local communication. The information is then processed to update the control parameters and force the swarm to converge onto and circulate along the aforementioned planar curve. The proposed mathematical framework is based on stochastic differential equations driven by white Gaussian noise (diffusion processes). Using this framework, there is maximum probability that the swarm dynamics will be driven toward the consensual closed planar curve. In the simplest configuration where a circular consensual curve is obtained, we are able to derive an analytical expression that relates the radius of the circular formation to the agent’s interaction range. Such an intimate relation is also illustrated numerically for more general curves. The agent-based control strategy is then translated into a distributed Braitenberg-inspired one. The proposed robotic control strategy is then validated by numerical simulations and by implementation on an actual robotic swarm. It can be used in applications that involve large numbers of locally interacting agents, such as traffic control, deployment of communication networks in hostile environments, or environmental monitoring.     

Evolutionary game theoretic strategy for optimal drug delivery to influence selection pressure in treatment of HIV-1

Cytotoxic T-lymphocyte (CTL) escape mutation is associated with long-term behaviors of human immunodeficiency virus type 1 (HIV-1). Recent studies indicate heterogeneous behaviors of reversible and conservative mutants while the selection pressure changes. The purpose of this study is to optimize the selection pressure to minimize the long-term virus load. The results can be used to assist in delivery of highly loaded cognate peptide-pulsed dendritic cells (DC) into lymph nodes that could change the selection pressure. This mechanism may be employed for controlled drug delivery. A mathematical model is proposed in this paper to describe the evolutionary dynamics involving viruses and T cells. We formulate the optimization problem into the framework of evolutionary game theory, and solve for the optimal control of the selection pressure as a neighborhood invader strategy. The strategy dynamics can be obtained to evolve the immune system to the best controlled state. The study may shed light on optimal design of HIV-1 therapy based on optimization of adaptive CTL immune response.     

Reconfigurable control system design for fault diagnosis and accommodation

The growing demand in system reliability and survivability under failures has urged ever-increasing research effort on the development of fault diagnosis and accommodation. In this paper, the on-line fault tolerant control problem for dynamic systems under unanticipated failures is investigated from a realistic point of view without any specific assumption on the type of system dynamical structure or failure scenarios. The sufficient conditions for system on-line stability under catastrophic failures have been derived using the discrete-time Lyapunov stability theory. Based upon the existing control theory and the modern computational intelligence techniques, an on-line fault accommodation control strategy is proposed to deal with the desired trajectory-tracking problems for systems suffering from various unknown and unanticipated catastrophic component failures. Theoretical analysis indicates that the control problem of interest can be solved on-line without a complete realization of the unknown failure dynamics provided an on-line estimator satisfies certain conditions. Through the on-line estimator, effective control signals to accommodate the dynamic failures can be computed using only the partially available information of the faults. Several on-line simulation studies have been presented to demonstrate the effectiveness of the proposed strategy. To investigate the feasibility of using the developed technique for unanticipated fault accommodation in hardware under the real-time environment, an on-line fault tolerant control test bed has been constructed to validate the proposed technology. Both on-line simulations and the real-time experiment show encouraging results and promising futures of on-line real-time fault tolerant control based solely upon insufficient information of the system dynamics and the failure dynamics.     

Formation of ordered structures in systems of charged thin cylindrical grains

Conditions for the formation of various orientational and spatial configurations of charged cylindrical particles in an external electric field are investigated both analytically and numerically. Analytical expressions allowing one to determine the tilt angle of cylinders relative to the symmetry axis/plane of the electric trap are proposed. A new algorithm for numerical modeling of the dynamics of interacting nonspherical particles is developed. Conditions for correct modeling of uniformly charged cylinders by means of “bipoles” consisting of two coupled point charges of the same sign are determined. The studies have been performed in a wide range of parameters close to those typical of laboratory experiments with dusty plasmas.     

Node vulnerability under finite perturbations in complex networks

A measure to quantify vulnerability under perturbations (attacks, failures, large fluctuations) in ensembles (networks) of coupled dynamical systems is proposed. Rather than addressing the issue of how the network properties change upon removal of elements of the graph (the strategy followed by most of the existing methods for studying the vulnerability of a network based on its topology), here a dynamical definition of vulnerability is introduced, referring to the robustness of a collective dynamical state to perturbing events occurring over a fixed topology. In particular, we study how the collective (synchronized) dynamics of a network of chaotic units is disrupted under the action of a finite size perturbation on one of its nodes. Illustrative examples are provided for three systems of identical chaotic oscillators coupled according to three distinct well-known network topologies. A quantitative comparison between the obtained vulnerability rankings and the classical connectivity/centrality rankings is made that yields conclusive results. Possible applications of the proposed strategy and conclusions are also discussed.     

Electro-Acoustic Behavior of the Mitotic Spindle: A Semi-Classical Coarse-Grained Model

The regulation of chromosome separation during mitosis is not fully understood yet. Microtubules forming mitotic spindles are targets of treatment strategies which are aimed at (i) the triggering of the apoptosis or (ii) the interruption of uncontrolled cell division. Despite these facts, only few physical models relating to the dynamics of mitotic spindles exist up to now. In this paper, we present the first electromechanical model which enables calculation of the electromagnetic field coupled to acoustic vibrations of the mitotic spindle. This electromagnetic field originates from the electrical polarity of microtubules which form the mitotic spindle. The model is based on the approximation of resonantly vibrating microtubules by a network of oscillating electric dipoles. Our computational results predict the existence of a rapidly changing electric field which is generated by either driven or endogenous vibrations of the mitotic spindle. For certain values of parameters, the intensity of the electric field and its gradient reach values which may exert a not-inconsiderable force on chromosomes which are aligned in the spindle midzone. Our model may describe possible mechanisms of the effects of ultra-short electrical and mechanical pulses on dividing cells—a strategy used in novel methods for cancer treatment.     

Recent Advances in Intervention in Markovian Regulatory Networks

Markovian regulatory networks constitute a class of discrete state-space models used to study gene regulatory dynamics and discover methods that beneficially alter those dynamics. Thereby, this class of models provides a framework to discover effective drug targets and design potent therapeutic strategies. The salient translational goal is to design therapeutic strategies that desirably modify network dynamics via external signals that vary the expressions of a control gene. The objective of an intervention strategy is to reduce the likelihood of the pathological cellular function related to a disease. The task of finding an effective intervention strategy can be formulated as a sequential decision making problem for a pre-defined cost of intervention and a cost-per-stage function that discriminates the gene-activity profiles. An effective intervention strategy prescribes the actions associated with an external signal that result in the minimum expected cost. This strategy in turn can be used as a treatment that reduces the long-run likelihood of gene expressions favorable to the disease. In this tutorial, we briefly summarize the first method proposed to design such therapeutic interventions, and then move on to some of the recent refinements that have been proposed. Each of these recent intervention methods is motivated by practical or analytical considerations. The presentation of the key ideas is facilitated with the help of two case studies.Key Words: Regulatory networks, markovian decision processes, translational genomics, systems biology.     

Noise effects on robust synchronization of a small pacemaker neuronal ensemble via nonlinear controller: electronic circuit design

In this paper, we report on the synchronization of a pacemaker neuronal ensemble constituted of an AB neuron electrically coupled to two PD neurons. By the virtue of this electrical coupling, they can fire synchronous bursts of action potential. An external master neuron is used to induce to the whole system the desired dynamics, via a nonlinear controller. Such controller is obtained by a combination of sliding mode and feedback control. The proposed controller is able to offset uncertainties in the synchronized systems. We show how noise affects the synchronization of the pacemaker neuronal ensemble, and briefly discuss its potential benefits in our synchronization scheme. An extended Hindmarsh–Rose neuronal model is used to represent a single cell dynamic of the network. Numerical simulations and Pspice implementation of the synchronization scheme are presented. We found that, the proposed controller reduces the stochastic resonance of the network when its gain increases.     

CFD simulation coupled with population balance equations for aerated stirred bioreactors

Mammalian cells have been widely used to produce therapeutic proteins in stirred bioreactors in suspension culture. Local hydrodynamics can have a great impact on cell proliferation and protein synthesis, but there are few reports on spatial heterogeneity of nutrients, gas bubbles, and mass transfer coefficients. We have employed computational fluid dynamics (CFD) coupled with population balance equations to study local hydrodynamics in a 20 L stirred bioreactor. The flow patterns, energy dissipation rates, gas volume fraction, gas bubble size distribution and local mass transfer coefficient have been displayed throughout the whole bioreactor. Their implications for mammalian cell culture have been discussed. This study provides an insight into rational design and optimum operation conditions in a stirred bioreactor for mammalian cell cultivation.     

A new method for the simulation of electric fields,generated by electric fish,and their distorsions by objects

Among the many species of fishes endowed with electric organs Mormyriformes and Gymnotoidei are known to emit and receive electric signals for the purposes of intraspecific communication and recognition of objects. Models which have been proposed for this electro-sensory system generally assume steady-state conditions. On the other hand, the very character of the signals itself and the idea that the cerebellum might be working as a clock point to the importance of the signal dynamics. Therefore a new approach to the simulation of electric fields is described in the paper. The basic idea is to superpose the fields of point charges in a way that the sum is in accordance with the fish's electric field. The same technique could be used to simulate the influence of objects on the electric field. Following a suggestion of Dr. E. Kasper I used a simpler but equal effective approach for object simulation consisting in the use of a dipole instead of point charges. The model described is easily applied to diverse situations and allows one to estimate the influence of various parameters (size, shape, and position) on the “electric image” of an object. Furthermore, the well-known behaviour of tailbending and its consequences in object recognition can be simulated. The results underline the importance of signal dynamics for species with pulse-type discharges.     

Analysis and design of asymmetric Hopfield networks with discrete-time dynamics

The retrieval properties of the asymmetric Hopfield neural networks (AHNNs) with discrete-time dynamics are studied in this paper. It is shown that the asymmetry degree is an important factor influencing the network dynamics. Furthermore, a strategy for designing AHNNs of different sparsities is proposed. Numerical simulations show that AHNNs can perform as well as symmetric ones, and the diluted AHNNs have the virtues of small wiring cost and high pattern recognition quality.     

The role of structural reorganization in charge carrier transfer in DNA molecule

A model of hole transfer in DNA molecules has been proposed, which takes into account changes in the reorganization energy and orbital coupling between the neighboring bases during the charge transfer in different molecular sequences. It is shown that the rate of hole transfer by the superexchange and hopping transfer mechanisms is limited by the relaxation of the geometries of nucleobases participating in charge migration and the dynamics of solvent molecules. The rate of charge transfer in the DNA molecule is found to be dependent on the height of the potential barriers between the nucleotide and the molecular sequences. The inclusion of the interchain charge transfer, which is characterized by weak coupling between the nucleotides located in opposite strands, does not affect the general charge transport in DNA. The increase in the number of the parallel components of the hopping mechanism leads to a rise in the charge transfer rate in the double helix.     

Elementary steps of proton translocation in the catalytic cycle of cytochrome oxidase

Proton translocation in the catalytic cycle of cytochrome c oxidase (CcO) proceeds sequentially in a four-stroke manner. Every electron donated by cytochrome c drives the enzyme from one of four relatively stable intermediates to another, and each of these transitions is coupled to proton translocation across the membrane, and to uptake of another proton for production of water in the catalytic site. Using cytochrome c oxidase from Paracoccus denitrificans we have studied the kinetics of electron transfer and electric potential generation during several such transitions, two of which are reported here. The extent of electric potential generation during initial electron equilibration between CuA and heme a confirms that this reaction is not kinetically linked to vectorial proton transfer, whereas oxidation of heme a is kinetically coupled to the main proton translocation events during functioning of the proton pump. We find that the rates and amplitudes in multiphase heme a oxidation are different in the OH-->EH and PM-->F steps of the catalytic cycle, and that this is reflected in the kinetics of electric potential generation. We discuss this difference in terms of different driving forces and relate our results, and data from the literature, to proposed mechanisms of proton pumping in cytochrome c oxidase.     

Spatial and temporal electroselection patterns in electric field stimulation of polarized luminescence from photosynthetic membrane vesicles

Electroselection processes of charge recombination are manifested in the study of electric field induced polarized emission from photosynthetic membrane vesicles. The study explores the coupled spatial-temporal characteristics of electric field induced charge recombination by examining the dependence of the integrated polarized emission and the time dependent polarization on electric field strength. The experimental results were fitted to theoretical models by computer simulations employing empirical parameters. Simulation of the dependence of the integrated polarized components of emission on electric field strength, suggests field-dependent increased ratio between radiative and nonradiative rates of charge recombination. The observation that the initial polarization values are independent of electric field strength supports the assumption that electric field induced emission originates from the pole area and then spreads away from it towards the equator. The propagation rate of this electric field induced charge recombination from the pole area towards the equator is reflected by the decay of polarization which increases upon raising the electric field strength. Simulation of the polarization's decay, based on a calculated angle of 26.3 ± 0.4° between the transition moment of emission and the plane of the membrane, establishes coupled temporal spatial patterns of electroselection in intramembrane electron transfer invoked by exposing preilluminated photosynthetic vesicles to a homogeneous electric field.     

All-Optical Strong Coupling Switches Based on a Coupled Meta-atom and MIM Nanocavity Configuration

Based on a coupled meta-atom and metal-nonlinear dielectric-metal nanocavity, nonlinear all-optical strong coupling switches are proposed and numerically investigated. In the absence of the external pumping light, the resonances of the meta-atom are continuously tuned across the one of the nanocavity by changing the size of the meta-atom. The meta-atomic electric dipole and quadrupole interaction with the plasmonic nanocavity is obtained. The characteristic anticrossing behaviors manifest the occurrence of the strong coupling. With the resonance of the meta-atom being tuned to the one of the nanocavity, we dynamically tune the coupled strength of the system by changing intensity (power) of the pumping light and realize the transition from the strong coupling regime to the weak one. This means that this system can be used as an on/off switch in which the strong coupling can be on/off with an external control light, and the on/off states correspond to strong/weak coupling regime, respectively. Such a strong coupling all-optical switching is of considerable interest for applications in nanoscale plasmonic circuits.