Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “Dynamic network”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,459 records · Page 81Linked to original sources
PubMed1999

The contractile vacuole network of Dictyostelium as a distinct organelle: its dynamics visualized by a GFP marker protein.

The contractile vacuole system is an osmoregulatory organelle composed of cisternae and interconnecting ducts. Large cisternae act as bladders that periodically fuse with the plasma membrane, forming pores to expel water. To visualize the entire network in vivo and to identify constituents of the vacuolar complex in cell fractions, we introduced a specific marker into Dictyostelium cells, GFP-tagged dajumin. The C-terminal, GFP-tagged region of this transmembrane protein is responsible for sorting to the contractile vacuole complex. Dajumin-GFP negligibly associates with the plasma membrane, indicating its retention during discharge of the bladder. Fluorescent labeled cell-surface constituents are efficiently internalized by endocytosis, while no significant cycling through the contractile vacuole is observed. Endosomes loaded with yeast particles or a fluid-phase marker indicate sharp separation of the endocytic pathway from the contractile vacuole compartment. Even after dispersion of the contractile vacuole system during mitosis, dajumin-GFP distinguishes the vesicles from endosomes, and visualizes post-mitotic re-organization of the network around the nucleus. Highly discriminative sorting and membrane fusion mechanisms are proposed to account for the sharp separation of the contractile vacuole and endosomal compartments. Evidence for a similar compartment in other eukaryotic cells is discussed.

Animals↗
PubMed2005

Development of a software tool for in silico simulation of Escherichia coli using a visual programming environment.

This study describes the development of a software tool, EcoSim, to assist users in implementing quantitative in silico simulation easily. It consists of four parts: extracellular environment and constraints setting mode, table for optimal metabolic flux distribution and chart for changes of substrate concentration, dynamic flux distribution viewer and dynamic hierarchical regulatory network viewer. Representation of a hierarchical regulatory network was constructed with defined modeling symbols and weight in the central Escherichia coli metabolism. All programming procedures for EcoSim were accomplished in a visual programming environment (LabVIEW). To illustrate quantitative in silico simulation with EcoSim, this program was performed on E. coli using glucose and acetate as carbon sources. The simulation results were in agreement with the experimental data obtained from the literature. EcoSim can be used to assist biologists and engineers in predicting and interpreting dynamic behaviors of E. coli under a variety of environmental conditions.

Acetates↗
PubMed2002

Unequal autonegative feedback by GH models the sexual dimorphism in GH secretory dynamics.

Growth hormone (GH) secretion, controlled principally by a GH-releasing hormone (GHRH) and GH release-inhibiting hormone [somatostatin (SRIF)] displays vivid sexual dimorphism in many species. We hypothesized that relatively small differences within a dynamic core GH network driven by regulatory interactions among GH, GHRH, and SRIF explain the gender contrast. To investigate this notion, we implemented a minimal biomathematical model based on two coupled oscillators: time-delayed reciprocal interactions between GH and GHRH, which endow high-frequency (40-60 min) GH oscillations, and time-lagged bidirectional GH-SRIF interactions, which mediate low-frequency (occurring every 3.3 h) GH volleys. We show that this basic formulation, sufficient to explain GH dynamics in the male rat [Farhy LS, Straume M, Johnson ML, Kovatchev BP, and Veldhuis JD. Am J Physiol Regulatory Integrative Comp Physiol 281: R38-R51, 2001], emulates the female pattern of GH release, if autofeedback of GH on SRIF is relaxed. Relief of GH-stimulated SRIF release damps the slower volleylike oscillator, allowing emergence of the underlying high-frequency oscillations that are sustained by the GH-GHRH interactions. Concurrently, increasing variability of basal somatostatin outflow introduces quantifiable, sex-specific disorderliness of the release process typical of female GH dynamics. Accordingly, modulation of GH autofeedback on SRIF within the interactive GH-GHRH-SRIF ensemble and heightened basal SRIF variability are sufficient to transform the well-ordered, 3.3-h-interval, multiphasic, volleylike male GH pattern into a femalelike profile with irregular pulses of higher frequency.

Animals↗
PubMed2004

Spike-timing dynamics of neuronal groups.

A neuronal network inspired by the anatomy of the cerebral cortex was simulated to study the self-organization of spiking neurons into neuronal groups. The network consisted of 100 000 reentrantly interconnected neurons exhibiting known types of cortical firing patterns, receptor kinetics, short-term plasticity and long-term spike-timing-dependent plasticity (STDP), as well as a distribution of axonal conduction delays. The dynamics of the network allowed us to study the fine temporal structure of emerging firing patterns with millisecond resolution. We found that the interplay between STDP and conduction delays gave rise to the spontaneous formation of neuronal groups--sets of strongly connected neurons capable of firing time-locked, although not necessarily synchronous, spikes. Despite the noise present in the model, such groups repeatedly generated patterns of activity with millisecond spike-timing precision. Exploration of the model allowed us to characterize various group properties, including spatial distribution, size, growth, rate of birth, lifespan, and persistence in the presence of synaptic turnover. Localized coherent input resulted in shifts of receptive and projective fields in the model similar to those observed in vivo.

Action Potentials↗
PubMed2003

Genomic binding by the Drosophila Myc, Max, Mad/Mnt transcription factor network.

The Myc/Max/Mad transcription factor network is critically involved in cell behavior; however, there is relatively little information on its genomic binding sites. We have employed the DamID method to carry out global genomic mapping of the Drosophila Myc, Max, and Mad/Mnt proteins. Each protein was tethered to Escherichia coli DNA adenine-methyltransferase (Dam) permitting methylation proximal to in vivo binding sites in Kc cells. Microarray analyses of methylated DNA fragments reveals binding to multiple loci on all major Drosophila chromosomes. This approach also reveals dynamic interactions among network members as we find that increased levels of dMax influence the extent of dMyc, but not dMnt, binding. Computer analysis using the REDUCE algorithm demonstrates that binding regions correlate with the presence of E-boxes, CG repeats, and other sequence motifs. The surprisingly large number of directly bound loci ( approximately 15% of coding regions) suggests that the network interacts widely with the genome. Furthermore, we employ microarray expression analysis to demonstrate that hundreds of DamID-binding loci correspond to genes whose expression is directly regulated by dMyc in larvae. These results suggest that a fundamental aspect of Max network function involves widespread binding and regulation of gene expression.

Animals↗
PubMed1996

A columnar model of somatosensory reorganizational plasticity based on Hebbian and non-Hebbian learning rules.

Topographical and functional aspects of neuronal plasticity were studied in the primary somatosensory cortex of adult rats in acute electrophysiological experiments. Under these experimental conditions, we observed short-term reversible reorganization induced by intracortical microstimulation or by an associative pairing of peripheral tactile stimulation. Both types of stimulation generate large-scale and reversible changes of the representational topography and of single cell functional properties. We present a model to simulate the spatial and functional reorganizational aspects of this type of short-term and reversible plasticity. The columnar structure of the network architecture is described and discussed from a biological point of view. The simulated architecture contains three main levels of information processing. The first one is a sensor array corresponding to the sensory surface of the hind paw. The second level, a pre-cortical relay cell array, represents the thalamo-cortical projection with different levels of excitatory and inhibitory relay cells and inhibitory nuclei. The array of cortical columns, the third level, represents stellate, double bouquet, basket and pyramidal cell interactions. The dynamics of the network are ruled by two integro-differential equations of the lateral-inhibition type. In order to implement neuronal plasticity, synaptic weight parameters in those equations are variables. The learning rules are motivated by the original concept of Hebb, but include a combination of both Hebbian and non-Hebbian rules, which modifies different intra- and inter-columnar interactions. We discuss the implications of neuronal plasticity from a behavioral point of view in terms of information processing and computational resources.

Animals↗
PubMed2005

Dendrimer-based transient supramolecular networks.

Association of a 16-fold excess of a monodisperse telechelic oligo(THF) (Mw = 1270 g/mol) containing two end groups that selectively bind to the 32 binding sites of a fifth generation dendritic host (Mw = 18,511 g/mol and radius R(h) = 2.4 nm) results in the formation of reversible and dynamic supramolecular complexes. The structure of these complexes in solution depends strongly on the concentration. At low concentration, the two end groups of one guest are proposed to complex to the same host, and flowerlike structures are formed with a radius of R(h) = 3.7 nm. At higher concentrations, both end groups of one guest are complexed to different hosts, forming a bridge between them. This gives rise to the formation of larger associates, and eventually to a transient supramolecular network. Dynamic light scattering unequivocally showed that three distinct relaxation processes, associated with the proposed structures, are present in this system. In addition to the dynamics related to the flowerlike (fast) and the transient network structures (slow), an intermediate dynamic process is attributed to the cooperative motion of a few (approximately 6) connected flowerlike structures. Rheological data elucidate the nature of the intermittent network responsible for the slowest process. A monofunctional guest, not capable of forming a network structure, was used as a reference, and starlike supramolecular structures are formed at all concentrations, indeed.

Acetates↗
PubMed2004

Gap junctions: their importance for the dynamics of neural circuits.

Electrical coupling through gap junctions constitutes a mode of signal transmission between neurons (electrical synaptic transmission). Originally discovered in invertebrates and in lower vertebrates, electrical synapses have recently been reported in immature and adult mammalian nervous systems. This has renewed the interest in understanding the role of electrical synapses in neural circuit function and signal processing. The present review focuses on the role of gap junctions in shaping the dynamics of neural networks by forming electrical synapses between neurons. Electrical synapses have been shown to be important elements in coincidence detection mechanisms and they can produce complex input-output functions when arranged in combination with chemical synapses. We postulate that these synapses may also be important in redefining neuronal compartments, associating anatomically distinct cellular structures into functional units. The original view of electrical synapses as static connecting elements in neural circuits has been revised and a considerable amount of evidence suggests that electrical synapses substantially affect the dynamics of neural circuits.

Animals↗
PubMedDate not supplied

The fractal architecture of cytoplasmic organization: scaling, kinetics and emergence in metabolic networks.

In this work, we highlight the links between fractals and scaling in cells and explore the kinetic consequences for biochemical reactions operating in fractal media. Based on the proposal that the cytoskeletal architecture is organized as a percolation lattice, with clusters emerging as fractal forms, the analysis of kinetics in percolation clusters is especially emphasized. A key consequence of this spatiotemporal cytoplasmic organization is that enzyme reactions following Michaelis-Menten or allosteric type kinetics exhibit higher rates in fractal media (for short times and at lower substrate concentrations) at the percolation threshold than in Euclidean media. As a result, considerably faster and higher amplification of enzymatic activity is obtained. Finally, we describe some of the properties bestowed by cytoskeletal organization and dynamics on metabolic networks.

Algorithms↗
PubMed1999

Investigation of the dynamics underlying periodic complexes in the EEG.

Periodic complexes (PC), occurring lateralised or diffuse, are relatively rare EEG phenomena which reflect acute severe brain disease. The pathophysiology is still incompletely understood. One hypothesis suggested by the alpha rhythm model of Lopes da Silva is that periodic complexes reflect limit cycle dynamics of cortical networks caused by excessive excitatory feedback. We examined this hypothesis by applying a recently developed technique to EEGs displaying periodic complexes and to periodic complexes generated by the model. The technique, non-linear cross prediction, characterises how well a time series can be predicted, and how much amplitude and time asymmetry is present. Amplitude and time asymmetry are indications of non-linearity. In accordance with the model, most EEG channels with PC showed clear evidence of amplitude and time asymmetry, pointing to non-linear dynamics. However, the non-linear predictability of true PC was substantially lower than that of PC generated by the model. Furthermore, no finite value for the correlation dimension could be obtained for the real EEG data, whereas the model time series had a dimension slighter higher than one, consistent with a limit cycle attractor. Thus we can conclude that PC reflect non-linear dynamics, but a limit cycle attractor is too simple an explanation. The possibility of more complex (high dimensional and spatio-temporal) non-linear dynamics should be investigated.

Acute Disease↗
PubMed2006

Modern genome-wide genetic approaches to reveal intrinsic properties of stem cells.

PURPOSE OF REVIEW: The clinical use of hematopoietic stem cells, which produce all mature blood cell lineages in the circulation, is continuously increasing. Identification of genes and gene networks specifying either stemness or commitment will not only be of major relevance for a fundamental understanding of developmental biology, but also for the emerging fields of tissue engineering and regenerative medicine. Our appreciation of the transcriptional machinery that distinguishes stem cells from their nonstem cell progeny is, however, rudimentary. State-of-the art genome-wide tools are now becoming available to elucidate intrinsic properties of stem cells. Here, we review recent progress that has been made in this field. RECENT FINDINGS: Approaches to study stem cell-specific genes and gene networks include genetical genomics, mRNA and microRNA expression profiling of carefully selected cells, proteomics, chromatin studies using 'CHIP-on-chip' tools, genome-wide binding site analyses for transcription factors and chromatin-remodeling proteins, and tools to study the three-dimensional organization of gene loci. It is promising to see that the combined application of these tools has resulted in the identification of multiple novel genes that regulate stem cell self-renewal. SUMMARY: Exploitation of the available technology and integrating the data by translation into a dynamic model of networks, operating in all four dimensions, will be essential to fully comprehend the elusive concept of 'stemness'. It is time to harvest.

Animals↗
PubMed2000

Stimulus-based state control in the thalamocortical system.

Neural systems operate in various dynamic states that determine how they process information (Livingstone and Hubel, 1981; Funke and Eysel, 1992; Morrow and Casey, 1992; Abeles et al., 1995; Guido et al., 1995; Mukherjee and Kaplan, 1995; Kenmochi and Eggermont, 1997; Wörgötter et al., 1998; Kisley and Gerstein, 1999). To investigate the function of a brain area, it is therefore crucial to determine the state of that system. One grave difficulty is that even under well controlled conditions, the thalamocortical network may undergo random dynamic state fluctuations which alter the most basic spatial and temporal response properties of the neurons. These uncontrolled state changes hinder the evaluation of state-specific properties of neural processing and, consequently, the interpretation of thalamocortical function. Simultaneous extracellular recordings were made in the auditory thalamus and cortex of the ketamine-anesthetized cat under several stimulus conditions. By considering the cellular and network mechanisms that govern state changes, we develop a complex stimulus that controls the dynamic state of the thalamocortical network. Traditional auditory stimuli have ambivalent effects on thalamocortical state, sometimes eliciting an oscillatory state prevalent in sleeping animals and other times suppressing it. By contrast, our complex stimulus clamps the network in a dynamic state resembling that observed in the alert animal. It thus allows evaluation of neural information processing not confounded by uncontrolled variations. Stimulus-based state control illustrates a general and direct mechanism whereby the functional modes of the brain are influenced by structural features of the external world.

Acoustic Stimulation↗
PubMed1999

Nonlinear EEG analysis in early Alzheimer's disease.

Nonlinear EEG analysis attempts to characterize the dynamics of neural networks in the brain. Abnormalities in nonlinear EEG measures have been found repeatedly in Alzheimer's disease (AD). The present study was undertaken to investigate whether these abnormalities could already be found in the early stage of AD. In a representative sample of 49 community-dwelling elderly, Alzheimer's disease was diagnosed in 7 subjects. Correlation dimension (D2) and nonlinear prediction were measured at 16 electrodes and in two different activational states. Also, 10 surrogate data sets were generated for each EEG epoch in order to investigate the presence of nonlinear dynamics. Differences between nonlinear statistics derived from original and from surrogate data sets were expressed as Z-scores. We found lower D2 and higher predictability in the demented subjects compared to the normal subjects. The results obtained with the Z-scores pointed to changed nonlinear dynamics in frontal and temporal areas in demented subjects. However, the major differences between demented and healthy subjects are not due to nonlinearity. From this it appears that linear dynamics change first in the course of AD, followed by changes in nonlinear dynamics.

Aged↗
PubMed2006

A new paradigm for theory in integrative biology: the principle of auto-associative stabilization: biochemical networks and the selection of neuronal groups.

This paper discusses rationale for a theory in biology: what exactly is a theory in biology? Is it of a mathematical nature? How to conceive an integrative theory and why? Replies to these questions are offered for subsequent discussions as concerns the mathematical theory of integrative physiology (MTIP) proposed by the author. It is shown that such a theory is a theoretical framework built on a representation in terms of hierarchical functional interactions and a specific formalism, the S-Propagator, to traverse the levels of organization. As for all natural theories, the MTIP is based on a general principle specific to biology, the principle of auto-associative stabilization (PAAS). In this framework, two models are revisited for a novel interpretation: the first addresses the dynamics of biochemical networks, the second addresses the selection of groups of neurons (TSGN) as suggested by Edelman.

Algorithms↗
PubMed2005

Strain-induced reorientation and mobility in nematic liquid-crystalline elastomers as studied by time-resolved FTIR spectroscopy.

Polarized Fourier transform infrared (FTIR) spectroscopy is employed to study the segmental orientation and mobility of liquid-crystalline elastomers (LCEs) with a monodomain structure in response to external mechanical fields parallel and perpendicular to the initial nematic director. The mean orientation and the molecular order parameter of the different molecular moieties referring to the mesogen, the spacer and the network are analyzed in detail. Parallel stretch leaves the mean orientation of the different molecular moieties and its molecular order parameter nearly uninfluenced. Perpendicular stretch results in a threshold-like dependence: for elongation ratios lambda < or = lambda(c) = 1.3 (10 mol% crosslinker density), respectively lambda < or = lambda(c) = 1.6 (5 mol% crosslinker density) no change of the mean orientation and the molecular order parameters is observed, while for lambda > or = lambda(c) all molecular units reorient and their molecular order parameters are strongly decreased. The present studies give no indications that the reorientational dynamics of the network and the mesogens differ as long as the elongation ratio is smaller than lambda(c).

Journal Article↗
PubMed2001

Ca(2+) entry through L-type Ca(2+) channels helps terminate epileptiform activity by activation of a Ca(2+) dependent afterhyperpolarisation in hippocampal CA3.

In CA3 neurons of disinhibited hippocampal slice cultures the slow afterhyperpolarisation, following spontaneous epileptiform burst events, was confirmed to be Ca(2+) dependent and mediated by K(+) ions. Apamin, a selective blocker of the SK channels responsible for part of the slow afterhyperpolarisation reduced, but did not abolish, the amplitude of the post-burst afterhyperpolarisation. The result was an increased excitability of individual CA3 cells and the whole CA3 network, as measured by burst duration and burst frequency. Increases in excitability could also be achieved by strongly buffering intracellular Ca(2+) or by minimising Ca(2+) influx into the cell, specifically through L-type (but not N-type) voltage operated Ca(2+) channels. Notably the L-type Ca(2+) channel antagonist, nifedipine, was more effective than apamin at reducing the post-burst afterhyperpolarisation. Nifedipine also caused a greater increase in network excitability as determined from measurements of burst duration and frequency from whole cell and extracellular recordings. N-methyl D-aspartate receptor activation contributed to the depolarisations associated with the epileptiform activity but Ca(2+) entry via this route did not contribute to the activation of the post-burst afterhyperpolarisation. We suggest that Ca(2+) entry through L-type channels during an epileptiform event is selectively coupled to both apamin-sensitive and -insensitive Ca(2+) activated K(+) channels. Our findings have implications for how the route of Ca(2+) entry and subsequent Ca(2+) dynamics can influence network excitability during epileptiform discharges.

Animals↗
PubMed2002

Dynamic flux balance analysis of diauxic growth in Escherichia coli.

Flux Balance Analysis (FBA) has been used in the past to analyze microbial metabolic networks. Typically, FBA is used to study the metabolic flux at a particular steady state of the system. However, there are many situations where the reprogramming of the metabolic network is important. Therefore, the dynamics of these metabolic networks have to be studied. In this paper, we have extended FBA to account for dynamics and present two different formulations for dynamic FBA. These two approaches were used in the analysis of diauxic growth in Escherichia coli. Dynamic FBA was used to simulate the batch growth of E. coli on glucose, and the predictions were found to qualitatively match experimental data. The dynamic FBA formalism was also used to study the sensitivity to the objective function. It was found that an instantaneous objective function resulted in better predictions than a terminal-type objective function. The constraints that govern the growth at different phases in the batch culture were also identified. Therefore, dynamic FBA provides a framework for analyzing the transience of metabolism due to metabolic reprogramming and for obtaining insights for the design of metabolic networks.

Cell Division↗
PubMed2001

Sensor fusion by neural networks using spatially represented information.

A neural network model based on a lateral-inhibition-type feedback layer is analyzed with regard to its capabilities to fuse signals from two different sensors reporting the same event ("multisensory convergence"). The model consists of two processing stages. The input stage holds spatial representations of the sensor signals and transmits them to the second stage where they are fused. If the input signals differ, the model exhibits two different processing modes: with small differences it produces a weighted average of the input signals, whereas with large differences it enters a decision mode where one of the two signals is suppressed. The dynamics of the network can be described by a series of two first-order low-pass filters, whose bandwidth depends nonlinearly on the level of concordance of the input signals. The network reduces sensor noise by means of both its averaging and filtering properties. Hence noise suppression, too, depends on the level of concordance of the inputs. When the network's neurons have internal noise, sensor noise suppression is reduced but still effective as long as the input signals do not differ strongly. The possibility of extending the scheme to three and more inputs is discussed.

Artifacts↗