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PubMed2006

Actin polymerization serves as a membrane domain switch in model lipid bilayers.

The ability of cells to mount localized responses to external or internal stimuli is critically dependent on organization of lipids and proteins in the plasma membrane. Involvement of the actin cytoskeleton in membrane organization has been documented, but an active role for actin networks that directly links internal organization of the cytoskeleton with membrane organization has not yet been identified. Here we show that branched actin networks formed on model lipid membranes enriched with the lipid second messenger PIP(2) trigger both temporal and spatial rearrangement of membrane components. Using giant unilamellar vesicles able to separate into two coexisting liquid phases, we demonstrate that polymerization of dendritic actin networks on the membrane induces phase separation of initially homogenous vesicles. This switch-like behavior depends only on the PIP(2)-N-WASP link between the membrane and actin network, and we find that the presence of a preexisting actin network spatially biases the location of phase separation. These results show that dynamic, membrane-bound actin networks alone can control when and where membrane domains form and may actively contribute to membrane organization during cell signaling.

Actins↗
PubMed1992

The impact of IAIMS at Georgetown: strategies and outcomes.

Integration of multiple information systems of a medical center will change the way physicians work and practice medicine in the future. Several major steps must be taken by an institution to make this a reality. Since 1983, Georgetown has been engaged in an Integrated Academic Information Management System (IAIMS) project to bring together multiple sources of information that reside on different computers and database systems. Georgetown is developing a Biotechnology and Biomedical Knowledge Network that includes informational and clinical databases, scholar workstations, instruction on computer use, a campuswide network with local area network nodes, and a modular approach to systems integration. The IAIMS project, spearheaded by the medical library, has enabled a broad spectrum of health professionals to benefit directly from new, dynamic information services. The network is heavily used; in 1991, more than 2,100 individual users conducted more than 148,500 computer functions and more than 104,000 searches. There is economy of scale in high-volume use. Overall, the average search cost is $1.57; for high use databases the cost is $0.38, and for low use, it is $9.41. As described in this paper, IAIMS offers a cost-effective means of enhancing patient care by improving information services to physicians. At Georgetown, IAIMS has advanced the concept of integration, accelerated use of computers in education, increased user acceptance of advanced technologies, and established cost factors for providing information resources. While progress made in improving the transfer of medical information is impressive, it is clear that IAIMS requires several more years of support to achieve full implementation.

Academic Medical Centers↗
PubMed2004

Robustness, stability and efficiency of phage lambda genetic switch: dynamical structure analysis.

Based on the dynamical structure theory for complex networks recently developed by one of us and on the physical-chemical models for gene regulation, developed by Shea and Ackers in the 1980's, we formulate a direct and concise mathematical framework for the genetic switch controlling phage lambda life cycles, which naturally includes the stochastic effect. The dynamical structure theory states that the dynamics of a complex network is determined by its four elementary components: The dissipation (analogous to degradation), the stochastic force, the driving force determined by a potential, and the transverse force. The potential may be interpreted as a landscape for the phage development in terms of attractive basins, saddle points, peaks and valleys. The dissipation gives rise to the adaptivity of the phage in the landscape defined by the potential: The phage always has the tendency to approach the bottom of the nearby attractive basin. The transverse force tends to keep the network on the equal-potential contour of the landscape. The stochastic fluctuation gives the phage the ability to search around the potential landscape by passing through saddle points. With molecular parameters in our model fixed primarily by the experimental data on wild-type phage and supplemented by data on one mutant, our calculated results on mutants agree quantitatively with the available experimental observations on other mutants for protein number, lysogenization frequency, and a lysis frequency in lysogen culture. The calculation reproduces the observed robustness of the phage lambda genetic switch. This is the first mathematical description that successfully represents such a wide variety of major experimental phenomena. Specifically, we find: (1) The explanation for both the stability and the efficiency of phage lambda genetic switch is the exponential dependence of saddle point crossing rate on potential barrier height, a result of the stochastic motion in a landscape; and (2) The positive feedback of cI repressor gene transcription, enhanced by the CI dimer cooperative binding, is the key to the robustness of the phage lambda genetic switch against mutations and fluctuations in kinetic parameter values.

Bacteriophage lambda↗
PubMed1996

Circular nodes in neural networks.

In the usual construction of a neural network, the individual nodes store and transmit real numbers that lie in an interval on the real line; the values are often envisioned as amplitudes. In this article we present a design for a circular node, which is capable of storing and transmitting angular information. We develop the forward and backward propagation formulas for a network containing circular nodes. We show how the use of circular nodes may facilitate the characterization and parameterization of periodic phenomena in general. We describe applications to constructing circular self-maps, periodic compression, and one-dimensional manifold decomposition. We show that a circular node may be used to construct a homeomorphism between a trefoil knot in R3 and a unit circle. We give an application with a network that encodes the dynamic system on the limit cycle of the Kuramoto-Sivashinsky equation. This is achieved by incorporating a circular node in the bottleneck layer of a three-hidden-layer bottleneck network architecture. Exploiting circular nodes systematically offers a neural network alternative to Fourier series decomposition in approximating periodic or almost periodic functions.

Neural Networks, Computer↗
PubMed1996

Use of non-linear EEG measures to characterize EEG changes during mental activity.

Non-linear EEG analysis provides a possibility for studying the dynamical changes in cortical networks related to mental activity. In this study the correlation dimension D2 was used to study local changes in complexity, and the mutual dimension Dm was used to assess changes in the dynamical coupling between different brain areas. EEGs were recorded in 25 healthy subjects under three conditions: (1) eyes closed, (2) eyes open, and (3) mental arithmetic with eyes closed (serial subtraction of 7s from 1000). In the eyes-closed condition, D2 was lower at parieto-occipital sites. D2 increased during the eye-open and arithmetic conditions. Contrary to the D2, the Dm showed no regional differences in the eyes closed condition. A clear increase in Dm was seen during eyes open and arithmetic. We conclude that both the correlation dimension and the mutual dimension are very sensitive to EEG changes during simple visual information processing and during mental arithmetic. However, these measures seem to be relatively non-specific, and correlate only weakly with performance on the arithmetic task.

Adult↗
PubMed2004

Self-sustained activity in a small-world network of excitable neurons.

We study the dynamics of excitable integrate-and-fire neurons in a small-world network. At low densities p of directed random connections, a localized transient stimulus results either in self-sustained persistent activity or in a brief transient followed by failure. Averages over the quenched ensemble reveal that the probability of failure changes from 0 to 1 over a narrow range in p; this failure transition can be described analytically through an extension of an existing mean-field result. Exceedingly long transients emerge at higher densities p; their activity patterns are disordered, in contrast to the mostly periodic persistent patterns observed at low p. The times at which such patterns die out follow a stretched-exponential distribution, which depends sensitively on the propagation velocity of the excitation.

Action Potentials↗
PubMed2006

Supervisory control of mobile sensor networks: math formulation, simulation, and implementation.

This paper uses a novel discrete-event controller (DEC) for the coordination of cooperating heterogeneous wireless sensor networks (WSNs) containing both unattended ground sensors (UGSs) and mobile sensor robots. The DEC sequences the most suitable tasks for each agent and assigns sensor resources according to the current perception of the environment. A matrix formulation makes this DEC particularly useful for WSN, where missions change and sensor agents may be added or may fail. WSN have peculiarities that complicate their supervisory control. Therefore, this paper introduces several new tools for DEC design and operation, including methods for generating the required supervisory matrices based on mission planning, methods for modifying the matrices in the event of failed nodes, or nodes entering the network, and a novel dynamic priority assignment weighting approach for selecting the most appropriate and useful sensors for a given mission task. The resulting DEC represents a complete dynamical description of the WSN system, which allows a fast programming of deployable WSN, a computer simulation analysis, and an efficient implementation. The DEC is actually implemented on an experimental wireless-sensor-network prototyping system. Both simulation and experimental results are presented to show the effectiveness and versatility of the developed control architecture.

Algorithms↗
PubMedDate not supplied

Metabolic networks: a signal-oriented approach to cellular models.

Complete genomes, far advanced proteomes, and even 'metabolomes' are available for at least a few organisms, e.g., Escherichia coli. Systematic functional analyses of such complete data sets will produce a wealth of information and promise an understanding of the dynamics of complex biological networks and perhaps even of entire living organisms. Such complete and holistic descriptions of biological systems, however, will increasingly require a quantitative analysis and the help of mathematical models for simulating whole systems. In particular, new procedures are required that allow a meaningful reduction of the information derived from complex systems that will consequently be used in the modeling process. In this review the biological elements of such a modeling procedure will be described. In a first step, complex living systems must be structured into well-defined and clearly delimited functional units, the elements of which have a common physiological goal, belong to a single genetic unit, and respond to the signals of a signal transduction system that senses changes in physiological states of the organism. These functional units occur at each level of complexity and more complex units originate by grouping several lower level elements into a single, more complex unit. To each complexity level corresponds a global regulator that is epistatic over lower level regulators. After its structuring into modules (functional units), a biological system is converted in a second step into mathematical submodels that by progressive combination can also be assembled into more aggregated model structures. Such a simplification of a cell (an organism) reduces its complexity to a level amenable to present modeling capacities. The universal biochemistry, however, promises a set of rules valid for modeling biological systems, from unicellular microorganisms and cells, to multicellular organisms and to populations.

Animals↗
PubMed2003

Spike-driven synaptic dynamics generating working memory states.

The collective behavior of a network, modeling a cortical module of spiking neurons connected by plastic synapses is studied. A detailed spike-driven synaptic dynamics is simulated in a large network of spiking neurons, implementing the full double dynamics of neurons and synapses. The repeated presentation of a set of external stimuli is shown to structure the network to the point of sustaining working memory (selective delay activity). When the synaptic dynamics is analyzed as a function of pre- and postsynaptic spike rates in functionally defined populations, it reveals a novel variation of the Hebbian plasticity paradigm: in any functional set of synapses between pairs of neurons (e.g., stimulated-stimulated, stimulated-delay, stimulated-spontaneous), there is a finite probability of potentiation as well as of depression. This leads to a saturation of potentiation or depression at the level of the ratio of the two probabilities. When one of the two probabilities is very high relative to the other, the familiar Hebbian mechanism is recovered. But where correlated working memory is formed, it prevents overlearning. Constraints relevant to the stability of the acquired synaptic structure and the regimes of global activity allowing for structuring are expressed in terms of the parameters describing the single-synapse dynamics. The synaptic dynamics is discussed in the light of experiments observing precise spike timing effects and related issues of biological plausibility.

Action Potentials↗
PubMed2006

Network and graph analyses of folding free energy surfaces.

Protein folding is governed by a complex free energy surface whose entropic contributions are relevant because of the large number of degrees of freedom involved. Such complexity, in particular the conformational heterogeneity of the denatured state, is hidden in projections onto one or two order parameters (e.g. fraction of native contacts and/or radius of gyration), which usually results in relatively smooth surfaces. Recent approaches borrowed from network and graph theory have yielded quantitative unprojected representations of the free energy surfaces of a beta-hairpin and a three-stranded beta-sheet peptide using equilibrium folding-unfolding molecular dynamics simulations. Interestingly, the network and graph analyses of these structured peptides have revealed a very heterogeneous denatured state ensemble. It includes high-enthalpy, high-entropy conformations with fluctuating non-native secondary structure, as well as low-enthalpy, low-entropy traps.

Computational Biology↗
PubMed1987

Extending the quasi-steady state concept to analysis of metabolic networks.

A means is proposed for evaluating enzyme effectiveness in vivo via a simplified dynamic description of the metabolic reaction network within which the enzyme operates. The basis of the method is application of sensitivity analysis to a quasi-steady approximation of a complete dynamic model, and its implementation centers on interpreting the transient relations of selected intermediates following a perturbation to the system of interest: for many important situations such relations can be simply interpreted to give a useful global measure of enzyme effectiveness. This method is found to be successful for estimating phosphofructokinase and pyruvate kinase activity in the human red cell, and it appears promising as a basis for developing a means for detecting enzyme abnormalities caused by environmental or genetic factors. This method may also prove useful for comparative studies of glycolysis in different types of cells. The analysis presented is based on available models of red cell glycolysis, but the results are not highly sensitive to ambiguities in the system model. The approach suggested appears to provide an effective means for describing system dynamics and determining the behavior of an individual enzyme in an intact system by making a first-order allowance for interaction with the system as a whole. Requirements for success of this approach remain to be identified in detail, but effective time-scale separation is probably the key.

Erythrocytes↗
PubMed2001

Convergence in discrete-time neural networks with specific performance.

We analyze convergence in discrete-time neural networks with specific performance such as decay rate and trajectory bounds in terms of componentwise absolute (exponential) stability. Simple necessary and sufficient stability and positive invariance conditions are presented, which allow us to design a convergent network with prescribed performance. Our approach is based on a decomposition of competitive-cooperative connectivity or inhibitory-excitatory interaction that abounds in neural networks, without assuming symmetry of the connection matrices. The key idea is that through the decomposition, we can always relate a competitive-cooperative network with a cooperative dynamical system. The latter possesses significant order-preserving properties that are basic to our analysis. The explicit division of connection weights into inhibitory and excitatory types offers a higher potential for relating formal neural network models to neurophysiology.

Algorithms↗
PubMed2001

Atrial activity enhancement by Wiener filtering using an artificial neural network.

This paper describes a novel technique for the cancellation of the ventricular activity for applications such as P-wave or atrial fibrillation detection. The procedure was thoroughly tested and compared with a previously published method, using quantitative measures of performance. The novel approach estimates, by means of a dynamic time delay neural network (TDNN), a time-varying, nonlinear transfer function between two ECG leads. Best results were obtained using an Elman TDNN with nine input samples and 20 neurons, employing a sigmoidal tangencial activation in the hidden layer and one linear neuron in the output stage. The method does not require a previous stage of QRS detection. The technique was quantitatively evaluated using the MIT-BIH arrhythmia database and compared with an adaptive cancellation scheme proposed in the literature. Results show the advantages of the proposed approach, and its robustness during noisy episodes and QRS morphology variations.

Algorithms↗
PubMed2002

Computer simulation study on the swelling of a model polymer network by a chainlike solvent.

A molecular-dynamics-particle-transfer method was used to study the swelling of a model polymer network by a short chain solvent. The solvent chains were transferred depending on the difference between the solvent chemical potentials in the coupled simulation boxes, containing pure solvent and gel, respectively. The chemical potentials were computed via the Rosenbluth sampling method. The simulated swelling ratio of the network under subcritical and supercritical conditions is compared with the prediction of a modified Flory-Huggins theory. In addition, the chains exhibit markedly different structural and dynamic properties in the corresponding phases due to the constraint imposed by the network, which are discussed in detail.

Journal Article↗
PubMed2000

A neuronal network model of macaque primary visual cortex (V1): orientation selectivity and dynamics in the input layer 4Calpha.

In this paper, we offer an explanation for how selectivity for orientation could be produced by a model with circuitry that is based on the anatomy of V1 cortex. It is a network model of layer 4Calpha in macaque primary visual cortex (area V1). The model consists of a large number of integrate-and-fire conductance-based point neurons, both excitatory and inhibitory, which represent dynamics in a small patch of 4Calpha-1 mm(2) in lateral area-which contains four orientation hypercolumns. The physiological properties and coupling architectures of the model are derived from experimental data for layer 4Calpha of macaque. Convergent feed-forward input from many neurons of the lateral geniculate nucleus sets up an orientation preference, in a pinwheel pattern with an orientation preference singularity in the center of the pattern. Recurrent cortical connections cause the network to sharpen its selectivity. The pattern of local lateral connections is taken as isotropic, with the spatial range of monosynaptic excitation exceeding that of inhibition. The model (i) obtains sharpening, diversity in selectivity, and dynamics of orientation selectivity, each in qualitative agreement with experiment; and (ii) predicts more sharpening near orientation preference singularities.

Animals↗
PubMed1992

Quasielastic light scattering study of thermal excitations of F-actin solutions and of growth kinetics of actin filaments.

In the first part of this work we report quasielastic light scattering (QELS) studies of the internal dynamics of transient actin networks over a time range of 10(-6)-10(-2) s, scattering angles between zeta = 20 degrees and 150 degrees, and a concentration range of 0.015 (0.3) to 0.7 mg/mL (15 microM). We confirm our previous result that (1) the dynamic structure factor g(q,t) is determined by the thermally excited undulations of the actin filaments and (2) that the initial decay of g(q, t) scales as g(q, t) varies; is directly proportional to exp(-q alpha t) while the long time decay scales as g(q, t) varies; is directly proportional to exp [-(Aq alpha t) 2/3] with alpha = 2.75. The deviation of alpha from the theoretical value of alpha = 3 predicted for Rouse-Zimm chains is similar to that found for high molecular weight macromolecular solutions by QELS. A refined analysis of the dynamic structure factor showed that it can be interpreted in terms of three relaxation processes (besides the contribution of the residual monomer diffusion): (1) the dominant Rouse-Zimm dynamics, which comprises between 65 (at high concentrations) and 85% of the signal; (2) a fast relaxation process with a decay constant of gamma = 9 x 10(3) s-1, which contributes at all concentrations with the same amplitude; and (3) a nonexponential ultraslow contribution of the form g(us) varies; is directly proportional to exp [(-gamma ust)]1/4. The third contribution appears only at high concentrations and increases strongly with decreasing scattering angles. It is thus attributed to fluctuations of the mesh size of the transient actin network. In the second part we show that high sensitivity QELS may be applied to follow the actin polymerization process at low temperatures (10 degrees C). The apparent diffusion coefficient and the static scattering intensity of the actin filaments were determined as functions of polymerization time tpol. We show that the process consists of the rapid growth of a few filaments that become very long (approximately 10 microns; even at actin concentrations of 0.04 micrograms/mL) near the critical growth concentration of 0.012 micrograms/mL, as is expected for a growth process determined by nucleation. Finally, we studied actin networks polymerized in the presence of complexes of gelsolin with actin. By application of the CONTIN program we could determine the length distribution of the filaments.(ABSTRACT TRUNCATED AT 400 WORDS)

Actins↗
PubMed1982

Dynamic aspects of the supramolecular organization of intermediate filament networks in cultured epidermal cells.

We have shown, by indirect immunofluorescence microscopy using an antiserum against the mouse keratin subunit K2 and by electron microscopy, that transformed (PAM) and primary (PME) mouse epidermal cells possess extensive networks of IF bundles. Following trypsinization and replating of PAM cells, IF bundles are seen to move as a continuous network from a perinuclear zone into the peripheral cytoplasmic regions. In PAM cells lysed in high-ionic-strength solutions containing Triton X-100 and DNAase-1, IF bundles appear to be closely associated with nuclear envelope remnants and, in some cases, appear to be attached to nuclear pore complexes. PME cells cultivated in low Ca2+-containing medium possess perinuclear birefringent arrays of IF bundles. Within 2 hours of switching the cells to normal Ca2+ levels, the PME IF bundle network moves towards and establishes contact with the cell surface as desmosomes form. Live cells observed by phase contrast and fixed cells observed by immunofluorescence microscopy demonstrate that desmosomes can be distinguished as dark bands separating neighboring cells. There is little difference between the major proteins seen in SDS-polyacrylamide gel profiles of isolated IF bundle networks from PME cells before and after the Ca2+ switch. Therefore, a reorganization of relatively insoluble membrane-associated protein following the Ca2+ switch may be involved in desmosome formation. The isolated IF networks from PAM cells differ in protein composition compared to the PME IF networks. This may be related to the greatly reduced number of desmosomes in PAM cells. The IF bundle system in epidermal cells appears to be involved in shape formation, shape maintenance, the establishment of desmosomes, nuclear centration, and cell-cell contact.

Animals↗