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At least 253 records · Page 14Linked to original sources
PubMed1995

The role of PRP8 protein in nuclear pre-mRNA splicing in yeast.

The removal of introns from precursor messenger RNAs occurs in a large complex, the spliceosome, that contains many proteins and five small nuclear RNAs (snRNAs). The snRNAs interact with the intron-containing substrate RNA and with each other to form a dynamic network of RNA interactions that define the intron and promote splicing. There is evidence that protein splicing factors play important roles in regulating RNA interactions in the spliceosome. PRP8 is a highly conserved protein that is associated in particles with the U5 snRNA and directly binds the substrate RNA in spliceosomes. UV crosslinking has been used to map the binding sites, and shows extensive interaction between PRP8 protein and the 5' exon prior to the first step of splicing and with the 3' splice site region subsequently. It is proposed that PRP8 protein may stabilize fragile interactions between the U5 snRNA and exon sequences at the splice sites, to anchor and align them in the catalytic centre of the spliceosome.

Exons↗
PubMed2002

DNA testing for familial hypercholesterolemia: improving disease recognition and patient care.

Cardiovascular disease is the leading cause of death worldwide and, like most chronic diseases, it has major genetic and environmental components. Among patients with coronary heart disease onset before the age of 55, about 5% of cases are attributable to heterozygous familial hypercholesterolemia (FH), a disease following autosomal dominant inheritance. About 50% of individuals with FH die before the age of 60 due to myocardial infarction. The frequency of FH is estimated to be 1 : 500. FH is related to mutations in the low-density lipoprotein (LDL)-cholesterol LDL-receptor gene and apolipoprotein B (apoB) gene. The identification of individuals with FH has been based on lipid levels and segregation of lipid levels within the family. However, phenotypes are overlapping and family history is not always informative. Therefore, a DNA-based genetic test for FH appears to offer the best alternative. The DNA test gives a simple yes/no answer. The FH test is a definitive tool for the identification of affected family members. The approach of targeted family genetic screening to find new patients is faster and more reliable compared with a biochemical form of screening. Early identification and efficient treatment of such patients is important and highly cost effective. There is evidence to suggest that the nature of the LDL-receptor (LDLR) mutation influences the degree of cholesterol lowering achieved by HMG-CoA reductase inhibitors (statins). The observed differences in the LDL-cholesterol (LDL-C) responses to these drugs among the various LDLR gene mutations are not yet completely understood. The relationships shown between LDLR mutation types and lipid levels, and the response of lipid levels to HMG-CoA reductase inhibitor treatment, will have to be investigated within the framework of pharmacogenetic studies. The variables, which are important in determining the overall atherosclerosis risk, are the result of combined activity in a dynamic network of numerous genes and environment. Candidate genes for atherosclerosis need to be further tested and validated. Future research should be directed at determining the significance of such targets, which patients with FH are at particularly high risk of premature cardiovascular disease, and which environmental factors are effective in modulating this risk. Genetics-based diagnostics will complement identification of FH while improving cardiovascular risk prediction, prevention of disease and treatment efficacy.

Animals↗
PubMed1996

Auditory cortical neurons in vitro: initial pharmacological studies.

Dissociated embryonic tissue from murine auditory cortex formed spontaneously active monolayer networks in culture that were maintained for up to 113 days in vitro (div). As a first step in determining whether neurons retain histiotypic properties, we subjected a set of 10 cultures to a sequence of 4 synaptically active substances. The test sequence consisted of 50 microM bicuculline, 10 microM strychnine, 5 microM NMDA, and 20 microM GABA. Recordings were made for 5-30 min under each condition followed by complete medium changes. Six to 14 channels with the best signal-to-noise ratios were selected for analysis that consisted of continual chart recordings of integrated burst data and further analysis of short data segments after digitizing and processing. All networks showed spontaneous activity, but had greatly varying native activity ranging from organized, quasi-periodic bursting on all channels to more complex spatio-temporal patterns with less coordination among channels. Bicuculline triggered oscillatory activity, simplified bursting, increased burst amplitude, and enhanced burst regularity among electrodes. Strychnine also changed the burst activity to a simpler pattern and enhanced the burst amplitude, indicating presence of glycine receptors in cortical tissue. Application of NMDA increased burst frequencies, but reduced burst regularity and coordination among channels. 20 microM of GABA inhibited all bursting activity in the networks. These results suggest that monolayer networks cultured on multi-electrode arrays retain some basic histiotypic pharmacological responses and may provide useful platforms for the study of network dynamics in the auditory cortex.

Animals↗
PubMed2000

Mild spherocytic hereditary elliptocytosis and altered levels of alpha- and gamma-adducins in beta-adducin-deficient mice.

The membrane skeleton, a dynamic network of proteins associated with the plasma membrane, determines the shape and mechanical properties of erythrocytes. Deficiencies or defects in membrane skeletal proteins are associated with inherited disorders of erythrocyte morphology and function. Adducin is one of the proteins localized at the spectrin-actin junction of the membrane skeleton. In this work we show that deficiency of beta-adducin produces an 80% decrease of alpha-adducin and a fourfold up-regulation of gamma-adducin in erythrocytes. beta-Adducin or any other isoform generated by translation of abnormally spliced messenger RNAs could not be detected by our antibodies either in ghosts or in cytoplasm of -/- erythrocytes. Actin levels were diminished in mutant mice, suggesting alterations in the actin-spectrin junctional complexes due to the absence of adducin. Elliptocytes, ovalocytes, and occasionally spherocytes were found in the blood film of -/- mice. Hematological values showed an increase in reticulocyte counts and mean corpuscular hemoglobin concentration, decreased mean corpuscular volume and hematocrit, and normal erythrocyte counts that, associated to splenomegaly, indicate that the mice suffer from mild anemia with compensated hemolysis. These modifications are due to a loss of membrane surface and dehydration that result in an increase in the osmotic fragility of red blood cells. The marked alteration in osmotic fragility together with the predominant presence of elliptocytes is reminiscent of the human disorder called spherocytic hereditary elliptocytosis. Our results suggest that the amount of adducin remaining in the mutant animals (presumably alphagamma adducin) could be functional and might account for the mild phenotype. (Blood. 2000;95:3978-3985)

Animals↗
PubMed2001

Precise burst synchrony in the superior colliculus of the awake cat during moving stimulus presentation.

This study aimed to characterize the synchrony that occurs between cell discharges in the superior colliculus of the awake cat. We trained cats to perform a visual fixation in the presence of a visual moving stimulus and then recorded 686 pairs of neighboring cells in the superior colliculus during task performance. A new method to assess the significance of precise discharge synchronization is described, which permits analysis of nonstationary data. Of 181 pairs with sufficient data for quantitative analysis, 125 showed a cross-correlation histogram (CCH) with features assessed as significant using this approach. CCHs frequently showed an isolated central peak (41 of 125) or a peak flanked by one or two troughs (68 of 125), and in a few cases an oscillatory pattern of approximately 65 Hz (16 of 125). This is in contrast to the oscillation frequency reported for the visual cortex and shows that oscillations in the superior colliculus probably arise from a cortex-independent mechanism. Our method also permits direct quantification of the correlation shift predictors, assessing precise time locking of spikes to the stimulus. Only 1 of 125 cross-correlation shift predictors had a significant central peak, meaning that most of the CCH features were not related to cell discharges time-locked to the stimulus presentation. Further investigation using a burst-jittering method showed that synchrony in the superior colliculus is attributable to precise synchronization of short bursts of spikes. Such synchrony could be related to the network dynamics and the common inhibitory feedback from local interneurons, which would act as temporal selectors of the cells with greatest or fastest response.

Action Potentials↗
PubMed1994

Cultural values and immigrant entrepreneurship: the Chinese in Singapore.

"It is the intent of this paper to examine the interrelationships between early socialisation into core Chinese cultural values, international migration and Chinese immigrant entrepreneurship.... It is through a developmental socialisation process by which [cultural] values are articulated in family and kin network dynamics that social organisations begin to develop and define what is popularly understood as the 'Chinese way of doing business'. We argue that among the overseas Chinese, this way of doing business must be viewed historically and developmentally, as it is intimately intertwined with transmigration experiences and their consequences in shaping values necessary for the emergence and development of entrepreneurship." (SUMMARY IN FRE AND SPA)

Asia↗
PubMedDate not supplied

[Professional image and identity in the building of nursing knowledge].

Based on a historic qualitative study, using documental analyse we searched for the dispersions in the construction of knowledge in the articles of the Anais do Congresso Brasileiro de Enfermagem, from 1977 through 1987. The dispersions emerged as categories that repeat themselves as subjects of note or as smaller punctuation. Our analyze converged into two main categories: professional image and professional identity. These categories took the shape of a complex and dynamic network, in which there were two explicit sub-categories: professional status and professional role.

Education, Nursing↗
PubMed1996

The HeLa 200 kDa U5 snRNP-specific protein and its homologue in Saccharomyces cerevisiae are members of the DEXH-box protein family of putative RNA helicases.

The primary structure of the 200 kDa protein of purified HeLa U5 snRNPs (U5-200kD) was characterized by cloning and sequencing of its cDNA. In order to confirm that U5-200kD is distinct from U5-220kD we demonstrate by protein sequencing that the human U5-specific 220 kDa protein is homologous to the yeast U5-specific protein Prp8p. A 246 kDa protein (Snu246p) homologous to U5-200kD was identified in Saccharomyces cerevisiae. Both proteins contain two conserved domains characteristic of the DEXH-box protein family of putative RNA helicases and RNA-stimulated ATPases. Antibodies raised against fusion proteins produced from fragments of the cloned mammalian cDNA interact specifically with the HeLa U5-200kD protein on Western blots and co-immunoprecipitate U5 snRNA and to a lesser extent U4 and U6 snRNAs from HeLa snRNPs. Similarly, U4, U5 and U6 snRNAs can be co-immunoprecipitated from yeast splicing extracts containing an HA-tagged derivative of Snu246p with HA-tag specific antibodies. U5-200kD and Snu246p are thus the first putative RNA helicases shown to be intrinsic components of snRNPs. Disruption of the SNU246 gene in yeast is lethal and leads to a splicing defect in vivo, indicating that the protein is essential for splicing. Anti-U5-200kD antibodies specifically block the second step of mammalian splicing in vitro, demonstrating for the first time that a DEXH-box protein is involved in mammalian splicing. We propose that U5-200kD and Snu246p promote one or more conformational changes in the dynamic network of RNA-RNA interactions in the spliceosome.

Amino Acid Sequence↗
PubMedDate not supplied

A computational model of the progression of Alzheimer's disease.

Computational modeling allows analysis of the role of network dynamics in the initiation and progression of neuropathology in Alzheimer's disease. The model focuses on a final common breakdown in function, termed runaway synaptic modification. This phenomenon could account for evidence that neuropathological markers associated with neuronal death in Alzheimer's disease first appear and attain their highest concentration in subregions of the hippocampal formation, and then successively spread into the temporal lobe cortex and the cortex of the frontal and parietal lobes. The model demonstrates how the spread of neuropathology from the hippocampus into neocortical structures could result from the mechanisms of consolidation. Initial sensitivity of the hippocampus and entorhinal cortex to the neuropathological process is proposed to result from an imbalance of variables regulating the influence of synaptic transmission on synaptic modification. Memory deficits are described as due to increased interference effects on recent memory caused by runaway synaptic modification, which ultimately leads to impairments of remote and semantic memory.

Alzheimer Disease↗
PubMed2001

Epidemic spread and bifurcation effects in two-dimensional network models with viral dynamics.

We extend a previous network model of viral dynamics to include host populations distributed in two space dimensions. The basic dynamical equations for the individual viral and immune effector densities within a host are bilinear with a natural threshold condition. In the general model, transmission between individuals is governed by three factors: a saturating function g( small middle dot) describing emission as a function of originating host virion level; a four-dimensional array B that determines transmission from each individual to every other individual; and a nonlinear function F, which describes the absorption of virions by a host for a given net arrival rate. A summary of the properties of the viral-effector dynamical system in a single host is given. In the numerical network studies, individuals are placed at the mesh points of a uniform rectangular grid and are connected with an m(2)xn(2) four-dimensional array with terms that decay exponentially with distance between hosts; g is linear and F has a simple step threshold. In a population of N=mn individuals, N0 are chosen randomly to be initially infected with the virus. We examine the dependence of maximal population viral load on the population dynamical parameters and find threshold effects that can be related to a transcritical bifurcation in the system of equations for individual virus and host effector populations. The effects of varying demographic parameters are also examined. Changes in alpha, which is related to mobility, and contact rate beta also show threshold effects. We also vary the density of (randomly chosen) initially infected individuals. The distribution of final size of the epidemic depends strongly on N0 but is invariably bimodal with mass concentrated mainly near either or both ends of the interval [1,N]. Thus large outbreaks may occur, with small probability, even with only very few initially infected hosts. The effects of immunization of various fractions of the population on the final size of the epidemic are also explored. The distribution of the final percentage infected is estimated by simulation. The mean of this quantity is obtained as a function of immunization rate and shows an almost linear decline for immunization rates up to about 0.2. When the immunization rate is increased past 0.2, the extra benefit accrues more slowly. We include a discussion of some approximations that illuminate threshold effects in demographic parameters and indicate how a mean-field approximation and more detailed studies of various geometries and rates of immunization could be a useful direction for future analysis.

Algorithms↗
PubMed2001

A dynamical model for the analysis and acceleration of learning in feedforward networks.

A dynamical system model is derived for feedforward neural networks with one layer of hidden nodes. The model is valid in the vicinity of flat minima of the cost function that rise due to the formation of clusters of redundant hidden nodes with nearly identical outputs. The derivation is carried out for networks with an arbitrary number of hidden and output nodes and is, therefore, a generalization of previous work valid for networks with only two hidden nodes and one output node. The Jacobian matrix of the system is obtained, whose eigenvalues characterize the evolution of learning. Flat minima correspond to critical points of the phase plane trajectories and the bifurcation of the eigenvalues signifies their abandonment. Following the derivation of the dynamical model, we show that identification of the hidden nodes clusters using unsupervised learning techniques enables the application of a constrained application (Dynamically Constrained Back Propagation-DCBP) whose purpose is to facilitate prompt bifurcation of the eigenvalues of the Jacobian matrix and, thus, accelerate learning. DCBP is applied to standard benchmark tasks either autonomously or as an aid to other standard learning algorithms in the vicinity of flat minima. Its application leads to significant reduction in the number of required epochs for convergence.

Acceleration↗
PubMed2001

From topology to dynamics in biochemical networks.

Abstract formulations of the regulation of gene expression as random Boolean switching networks have been studied extensively over the past three decades. These models have been developed to make statistical predictions of the types of dynamics observed in biological networks based on network topology and interaction bias, p. For values of mean connectivity chosen to correspond to real biological networks, these models predict disordered dynamics. However, chaotic dynamics seems to be absent from the functioning of a normal cell. While these models use a fixed number of inputs for each element in the network, recent experimental evidence suggests that several biological networks have distributions in connectivity. We therefore study randomly constructed Boolean networks with distributions in the number of inputs, K, to each element. We study three distributions: delta function, Poisson, and power law (scale free). We analytically show that the critical value of the interaction bias parameter, p, above which steady state behavior is observed, is independent of the distribution in the limit of the number of elements N--> infinity. We also study these networks numerically. Using three different measures (types of attractors, fraction of elements that are active, and length of period), we show that finite, scale-free networks are more ordered than either the Poisson or delta function networks below the critical point. Thus the topology of scale-free biochemical networks, characterized by a wide distribution in the number of inputs per element, may provide a source of order in living cells. (c) 2001 American Institute of Physics.

Journal Article↗
PubMed2002

Coexistence of regular and irregular dynamics in complex networks of pulse-coupled oscillators.

For general networks of pulse-coupled oscillators, including regular, random, and more complex networks, we develop an exact stability analysis of synchronous states. As opposed to conventional stability analysis, here stability is determined by a multitude of linear operators. We treat this multioperator problem exactly and show that for inhibitory interactions the synchronous state is stable, independent of the parameters and the network connectivity. In randomly connected networks with strong interactions this synchronous state, displaying regular dynamics, coexists with a balanced state exhibiting irregular dynamics. External signals may switch the network between qualitatively distinct states.

Biological Clocks↗
PubMed2000

Multi-step-ahead prediction using dynamic recurrent neural networks.

A method for the development of empirical predictive models for complex processes is presented. The models are capable of performing accurate multi-step-ahead (MS) predictions, while maintaining acceptable single-step-ahead (SS) prediction accuracy. Such predictors find applications in model predictive controllers and in fault diagnosis systems. The proposed method makes use of dynamic recurrent neural networks in the form of a nonlinear infinite impulse response (IIR) filter. A learning algorithm is presented, which is based on a dynamic gradient descent approach. The effectiveness of the method for accurate MS prediction is tested on an artificial problem and on a complex, open-loop unstable process. Comparative results are presented with polynomial Nonlinear AutoRegressive with eXogeneous (NARX) predictors, and with recurrent networks trained using teacher forcing. Validation studies indicate that excellent generalization is obtained for the range of operational dynamics studied. The research demonstrates that the proposed network architecture and the associated learning algorithm are quite effective in modeling the dynamics of complex processes and performing accurate MS predictions.

Algorithms↗
PubMed2002

Spatiotemporal forward solution of the EEG and MEG using network modeling.

Dynamic systems have proven to be well suited to describe a broad spectrum of human coordination behavior such synchronization with auditory stimuli. Simultaneous measurements of the spatiotemporal dynamics of electroencephalographic (EEG) and magnetoencephalographic (MEG) data reveals that the dynamics of the brain signals is highly ordered and also accessible by dynamic systems theory. However, models of EEG and MEG dynamics have typically been formulated only in terms of phenomenological modeling such as fixed-current dipoles or spatial EEG and MEG patterns. In this paper, it is our goal to connect three levels of organization, that is the level of coordination behavior, the level of patterns observed in the EEG and MEG and the level of neuronal network dynamics. To do so, we develop a methodological framework, which defines the spatiotemporal dynamics of neural ensembles, the neural field, on a sphere in three dimensions. Using magnetic resonance imaging we map the neural field dynamics from the sphere onto the folded cortical surface of a hemisphere. The neural field represents the current flow perpendicular to the cortex and, thus, allows for the calculation of the electric potentials on the surface of the skull and the magnetic fields outside the skull to be measured by EEG and MEG, respectively. For demonstration of the dynamics, we present the propagation of activation at a single cortical site resulting from a transient input. Finally, a mapping between finger movement profile and EEG/MEG patterns is obtained using Volterra integrals.

Algorithms↗
PubMed1998

Learning persistent dynamics with neural networks.

Persistence is one of the most common characteristics of real-world time series. In this work we investigate the process of learning persistent dynamics by neural networks. We show that for chaotic times series the network can get stuck for long training periods in a trivial minimum of the error function related to the long-term autocorrelation in the series. Remarkably, in these cases the transition to the trained phase is quite abrupt. For noisy dynamics the training process is smooth. We also consider the effectiveness of two of the most frequently used decorrelation methods in avoiding the problems related to persistence. Copyright 1997 Elsevier Science Ltd.

Journal Article↗
PubMed1994

Waves and stimulus-modulated dynamics in an oscillating olfactory network.

The temporal dynamics of electrical activity in an olfactory organ, the procerebral lobe of the terrestrial mollusc Limax maximus, is studied. The lobe exhibits intrinsic oscillations in its field potential. Intracellular recordings show that the lobe contains two classes of neurons, both with activity phase-locked to the oscillation. Neurons in one class produce periodic bursts of spikes while those in the other class fire infrequently but receive strong, periodic inhibition whose onset coincides with the burst. The large-scale activity of these neurons is imaged in preparations stained with voltage-sensitive dyes. We observe waves of electrical activity that span the width of the lobe and travel its full length along a longitudinal axis. Simultaneous optical and intracellular recordings show that the form of the wave reflects the electrical activity of both classes of neurons. The application of natural odor stimuli causes the electrical activity along the lobe to transiently switch from the state with propagating waves to one with spatially uniform oscillations. The behavioral and computational relevance of this change in global timing is discussed.

Animals↗
PubMed1979

Structure and dynamics of neural network oscillators.

Techniques are given to represent oscillating neural networks by asynchronous logical switching networks, and to analyze the oscillating networks using a directed graph called a state transition diagram. Consideration is restricted to network oscillators containing no rhythm determining pacemaker neurons, and no neurons exhibiting self-limiting properties such as post-inhibitory rebound or accumulating refractoriness. In the state transition diagrams, stable oscillations are associated with a particular geometric configuration called a cyclic attractor (the heavy cycle in Fig. 2). We show that given the network connectivity it is possible to predict autonomous dynamic behaviour, as well as behaviour following hyperpolarizing or depolarizing inputs to neurons of the network. Conversely, given information about patterns of firing activity during cycles and transients of neural networks, the network connectivity can be predicted. The theoretical techniques can be used to generate a census of network structures capable of generating stable oscillations. Several representative network oscillators are discussed in the context of previous theoretical and experimental studies of the structure of neural network oscillators. Although the number of theoretically possile network oscillators capable of generating sustained oscillations is very large, the techniques which are given should be useful in the design of experiments capable of distinguishing between equally plausible hypotheses.

Action Potentials↗