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At least 1,315 records · Page 73Linked to original sources
PubMed2006

Integrative analysis of metabolic networks: from peaks to flux models?

Recent developments in genomic and post-genomic technologies have led to the amassment of data describing genome sequences, transcript, protein and metabolite abundances, protein modifications, and protein-protein and protein-DNA interactions. Such technologies have vastly expanded the inventory of detectable molecular species and can be used to describe their interdependence, but they have yet to fulfill their promise in enhancing our knowledge of how flux through metabolic pathways is regulated. A convergence of traditional reductionistic and novel holistic experimental approaches could aid in elucidating flux control.

Databases, Genetic↗
PubMed2002

Hydroxyethylcellulose as an effective polymer network for DNA analysis in uncoated glass microchips: optimization and application to mutation detection via heteroduplex analysis.

The nature of the sieving matrix for DNA fragment separation is of immense importance in capillary and microchip electrophoresis. The chemical nature of the surface of the capillary or microchannel wall is equally as important, particularly with DNA electrophoresis where a substantial electroosmotic flow (EOF) may be detrimental to the separation. Although DNA analysis has been carried out successfully in both coated and uncoated capillaries, analysis of unpurified polymerase chain reaction products has been carried out primarily with covalently coated surfaces, especially with microchip electrophoresis. In this report, double-stranded (ds) DNA fragment analysis using hydroxyethylcellulose (HEC) buffered in 1xTris-borate-EDTA is demonstrated both in uncoated capillaries and in microchips. EOF was suppressed 20% in the presence of 1.5% HEC, and the effectiveness of HEC as a polymer for dsDNA fragment analysis was dependent on the pH, with pH 8.6 being optimal. Using separation efficiency (number of theoretical plates) and resolution to gauge the effectiveness of a variety of polymers for the capillary separation of dsDNA fragments in the size range 60-587bp, HEC was found to be comparable in performance to polydimethylacrylamide (PDMA), and superior to linear polyacrylamide and polyethylene oxide for DNA analysis. With respect to longevity and robust performance, HEC could be used effectively in an uncoated capillary for more than 40 runs and for more than 90 runs (without replenishing the polymer) in an uncoated microchip. Application of the optimized HEC conditions is demonstrated through its ability to facilitate heteroduplex analysis.

Buffers↗
PubMed2002

Low viscosity dimethacrylate comonomer compositions [Bis-GMA and CH3Bis-GMA] for novel dental composites; analysis of the network by stray-field MRI, solid-state NMR and DSC & FTIR.

The effect of dilution of 2,2-bis (4-(2-hydroxy-3-methacryloxyprop-1-oxy) phenyl) propane (Bis-GMA) with 2,2-bis(4-(2-methacryloxyprop-1-oxy)phenyl) propane (CH3Bis-GMA) on extent of polymerization (Ep) was investigated by FTIR and NMR. The results correlate well with Ep values of the system and its flexibility probed by Tg (obtained by DSC). Spatially resolved photopolymerization kinetics and polymerization shrinkage (PS, i.e. volumetric polymerization contraction) was also studied by stray-field imaging (STRAFI-MRI). PS was obtained in the presence of oxygen from the atmosphere as the total volumetric contraction. All the results were compared with those obtained for the Bis-GMA/TEGDMA (triethylene glycol dimethacrylate) system. Use of Bis-GMA mixed with hydrophobic low viscosity CH3Bis-GMA comonomer, as a substitute for the commonly used TEGDMA, resulted in improving significantly properties such as PS, water sorption and Ep, thereby reducing the unreacted double bond concentration.

Acrylates↗
PubMed1999

Analysis of fibrous network fluid permeation data using the theory of ultracentrifugation: application to fibrin gels.

A new and alternative method for calculating the strand diameter of fibrous gel networks from fluid permeation data is developed and used to analyze and compare previous Darcy constant measurements of fibrin gels. The calculated diameters from the various sets of experimental data using this method gives for a coarse fibrin clot a strand diameter of approximately 1000 A and for a fine fibrin clot a strand diameter of 170 A.

Journal Article↗
PubMed1997

Odor, drug and toxin analysis with neuronal networks in vitro: extracellular array recording of network responses.

Neurons, by virtue of intrinsic electrophysiological mechanisms, represent transducers that report the dynamics of cell death, receptor-ligand interactions, alterations in metabolism, and generic membrane perforation processes. In cell culture, mammalian neurons form fault-tolerant, spontaneously active systems with great sensitivity to their chemical environment and generate response profiles that are often concentration- and substance-specific. Changes in action potential patterns are usually detected before morphological changes and cell damage occur, which provides sensitivity and reversibility. Such biological systems can be used to screen rapidly for novel pharmacological substances, toxic agents, and for the detection of certain odorants. Existing simple culture preparations can already be employed effectively for the detection of chemical compounds. So far, three strategies have been investigated in pilot experiments: (1) Substance-dependent major changes in spontaneous native activity patterns. All synaptically active agents (e.g. glutamate, strychnine, N-methyl D-aspartic acid) as well as metabolic poisons generate such changes. (2) Substance-dependent changes in network oscillations via disinhibition. The regularized, oscillatory activity is altered by synaptically and metabolically active substances, ion channel blockers, and toxins. (3) Detection of paroxysmal responses indicating major, pathological membrane currents in large subpopulation of cells. We have explored these three strategies via 64 channel array recordings using spontaneously active murine spinal cord cultures. The glycine receptor blocker strychnine reliably generated increased multichannel bursting at 5-20 nM and regular, coordinated bursting above 5 microM. During biculline-induced network oscillations many compounds alter oscillation frequencies or terminate activity in a substance-specific manner. Finally, the gp120 protein of the AIDS virus (at 1 microgram/ml) produces massive, unique paroxysmal discharges that may last as long as 2 min. These results indicate that cultured neuronal networks are practical systems that can be used for the detection and identification of a great variety of chemical substances. The concept of dynamic fingerprinting to identify specific compounds is discussed.

Animals↗
PubMed1998

Analysis and neural network modeling of the nonlinear correlates of habituation in the vestibulo-ocular reflex.

Through the process of habituation, continued exposure to low-frequency (0.01 Hz) rotation in the dark produced suppression of the low-frequency response of the vestibulo-ocular reflex (VOR) in goldfish. The response did not decay gradually, as might be expected from an error-driven learning process, but displayed several nonlinear and nonstationary features. They included asymmetrical response suppression, magnitude-dependent suppression for lower- but not higher-magnitude head rotations, and abrupt-onset suppressions suggestive of a switching mechanism. Microinjection of lidocaine into the vestibulocerebellum of habituated goldfish resulted in a temporary dishabituation. This suggests that the vestibulocerebellum mediates habituation, presumably through Purkinje cell inhibition of vestibular nuclei neurons. The habituated VOR data were simulated with a feed-forward, nonlinear neural network model of the VOR in which only Purkinje cell inhibition of vestibular nuclei neurons was varied. The model suggests that Purkinje cell inhibition may switch in to introduce nonstationarities, and cause asymmetry and magnitude-dependency in the VOR to emerge from the essential nonlinearity of vestibular nuclei neurons.

Animals↗
PubMedDate not supplied

Coarse-grained reduction and analysis of a network model of cortical response: I. Drifting grating stimuli.

We present a reduction of a large-scale network model of visual cortex developed by McLaughlin, Shapley, Shelley, and Wielaard. The reduction is from many integrate-and-fire neurons to a spatially coarse-grained system for firing rates of neuronal subpopulations. It accounts explicitly for spatially varying architecture, ordered cortical maps (such as orientation preference) that vary regularly across the cortical layer, and disordered cortical maps (such as spatial phase preference or stochastic input conductances) that may vary widely from cortical neuron to cortical neuron. The result of the reduction is a set of nonlinear spatiotemporal integral equations for "phase-averaged" firing rates of neuronal subpopulations across the model cortex, derived asymptotically from the full model without the addition of any extra phenomological constants. This reduced system is used to study the response of the model to drifting grating stimuli-where it is shown to be useful for numerical investigations that reproduce, at far less computational cost, the salient features of the point-neuron network and for analytical investigations that unveil cortical mechanisms behind the responses observed in the simulations of the large-scale computational model. For example, the reduced equations clearly show (1) phase averaging as the source of the time-invariance of cortico-cortical conductances, (2) the mechanisms in the model for higher firing rates and better orientation selectivity of simple cells which are near pinwheel centers, (3) the effects of the length-scales of cortico-cortical coupling, and (4) the role of noise in improving the contrast invariance of orientation selectivity.

Animals↗
PubMed2002

Using DEA to evaluate efficiency and formulate policy within a Greek national primary health care network. Data Envelopment Analysis.

The purpose of this paper is to critically evaluate the relative efficiency of primary health care centers of the principal Greek public insurance provider, the Social Security Institute (IKA). The source of the efficiency data was the Statistical Unit of IKA. Using Data Envelopment Analysis, we analyzed data from 133 centers nationwide. Input variables included the number of personnel, stratified in different categories, and the number of people covered by each health center. The number of pensioners enlisted to each health care facility was used as an index of aging and vulnerability of the covered population. According to the results of the study, centers with the technological infrastructure to perform laboratory and/or radiographic examinations exhibited higher efficiency scores. In addition, centers with eligible covered populations from 10,000 to 50,000 were found as the most efficient. Health sector reforms should be planned on the basis of such analyses. If the model is supplemented with valid demographic, socioeconomic, and epidemiological data, it may become the basis for the creation of a national health care chart, matching available resources to the population and its health care needs.

Efficiency, Organizational↗
PubMed2004

SmartCell, a framework to simulate cellular processes that combines stochastic approximation with diffusion and localisation: analysis of simple networks.

SmartCell has been developed to be a general framework for modelling and simulation of diffusion-reaction networks in a whole-cell context. It supports localisation and diffusion by using a mesoscopic stochastic reaction model. The SmartCell package can handle any cell geometry, considers different cell compartments, allows localisation of species, supports DNA transcription and translation, membrane diffusion and multistep reactions, as well as cell growth. Moreover, different temporal and spatial constraints can be applied to the model. A GUI interface that facilitates model making is also available. In this work we discuss limitations and advantages arising from the approach used in SmartCell and determine the impact of localisation on the behaviour of simple well-defined networks, previously analysed with differential equations. Our results show that this factor might play an important role in the response of networks and cannot be neglected in cell simulations.

Animals↗
PubMed2004

Bayesian analysis of signaling networks governing embryonic stem cell fate decisions.

MOTIVATION: Signaling events that direct mouse embryonic stem (ES) cell self-renewal and differentiation are complex and accordingly difficult to understand in an integrated manner. We address this problem by adapting a Bayesian network learning algorithm to model proteomic signaling data for ES cell fate responses to external cues. Using this model we were able to characterize the signaling pathway influences as quantitative, logic-circuit type interactions. Our experimental dataset includes measurements for 28 signaling protein phosphorylation states across 16 different factorial combinations of cytokine and matrix stimuli as reported previously. RESULTS: The Bayesian network modeling approach allows us to uncover previously reported signaling activities related to mouse ES cell self-renewal, such as the roles of LIF and STAT3 in maintaining undifferentiated ES cell populations. Furthermore, the network predicts novel influences such as between ERK phosphorylation and differentiation, or RAF phosphorylation and differentiated cell proliferation. Visualization of the influences detected by the Bayesian network provides intuition about the underlying physiology of the signaling pathways. We demonstrate that the Bayesian networks can capture the linear, nonlinear and multistate logic interactions that connect extracellular cues, intracellular signals and consequent cell functional responses.

Algorithms↗
PubMed2000

Likelihood analysis of phylogenetic networks using directed graphical models.

A method for computing the likelihood of a set of sequences assuming a phylogenetic network as an evolutionary hypothesis is presented. The approach applies directed graphical models to sequence evolution on networks and is a natural generalization of earlier work by Felsenstein on evolutionary trees, including it as a special case. The likelihood computation involves several steps. First, the phylogenetic network is rooted to form a directed acyclic graph (DAG). Then, applying standard models for nucleotide/amino acid substitution, the DAG is converted into a Bayesian network from which the joint probability distribution involving all nodes of the network can be directly read. The joint probability is explicitly dependent on branch lengths and on recombination parameters (prior probability of a parent sequence). The likelihood of the data assuming no knowledge of hidden nodes is obtained by marginalization, i.e., by summing over all combinations of unknown states. As the number of terms increases exponentially with the number of hidden nodes, a Markov chain Monte Carlo procedure (Gibbs sampling) is used to accurately approximate the likelihood by summing over the most important states only. Investigating a human T-cell lymphotropic virus (HTLV) data set and optimizing both branch lengths and recombination parameters, we find that the likelihood of a corresponding phylogenetic network outperforms a set of competing evolutionary trees. In general, except for the case of a tree, the likelihood of a network will be dependent on the choice of the root, even if a reversible model of substitution is applied. Thus, the method also provides a way in which to root a phylogenetic network by choosing a node that produces a most likely network.

Computer Graphics↗