Mechanisms of intrinsic beating variability in cardiac cell cultures and model pacemaker networks

Heart rate variability (HRV) exhibits fluctuations characterized by a power law behavior of its power spectrum. The interpretation of this nonlinear HRV behavior, resulting from interactions between extracardiac regulatory mechanisms, could be clinically useful. However, the involvement of intrinsic variations of pacemaker rate in HRV has scarcely been investigated. We examined beating variability in spontaneously active incubating cultures of neonatal rat ventricular myocytes using microelectrode arrays. In networks of mathematical model pacemaker cells, we evaluated the variability induced by the stochastic gating of transmembrane currents and of calcium release channels and by the dynamic turnover of ion channels. In the cultures, spontaneous activity originated from a mobile focus. Both the beat-to-beat movement of the focus and beat rate variability exhibited a power law behavior. In the model networks, stochastic fluctuations in transmembrane currents and stochastic gating of calcium release channels did not reproduce the spatiotemporal patterns observed in vitro. In contrast, long-term correlations produced by the turnover of ion channels induced variability patterns with a power law behavior similar to those observed experimentally. Therefore, phenomena leading to long-term correlated variations in pacemaker cellular function may, in conjunction with extracardiac regulatory mechanisms, contribute to the nonlinear characteristics of HRV.

Riluzole-induced oscillations in spinal networks

We previously showed in dissociated cultures of fetal rat spinal cord that disinhibition-induced bursting is based on intrinsic spiking, network recruitment, and a network refractory period after the bursts. A persistent sodium current (I(NaP)) underlies intrinsic spiking, which, by recurrent excitation, generates the bursting activity. Although full blockade of I(NaP) with riluzole disrupts such bursting, the present study shows that partial blockade of I(NaP) with low doses of riluzole maintains bursting activity with unchanged burst rate and burst duration. More important, low doses of riluzole turned bursts composed of persistent activity into bursts composed of oscillatory activity at around 5 Hz. In a search for the mechanisms underlying the generation of such intraburst oscillations, we found that activity-dependent synaptic depression was not changed with low doses of riluzole. On the other hand, low doses of riluzole strongly increased spike-frequency adaptation and led to early depolarization block when bursts were simulated by injecting long current pulses into single neurons in the absence of fast synaptic transmission. Phenytoin is another I(NaP) blocker. When applied in doses that reduced intrinsic activity by 80-90%, as did low doses of riluzole, it had no effect either on spike-frequency adaptation or on depolarization block. Nor did phenytoin induce intraburst oscillations after disinhibition. A theoretical model incorporating a depolarization block mechanism could reproduce the generation of intraburst oscillations at the network level. From these findings we conclude that riluzole-induced intraburst oscillations are a network-driven phenomenon whose major accommodation mechanism is depolarization block arising from strong sodium channel inactivation.

DISSECTION OF STRESS RESPONSE NETWORKS REGULATING MULTIPLE STRESSES IN RICE

Important food crops like rice are constantly exposed to various stresses that can have devastating effect on their survival and productivity. Being sessile, these highly evolved organisms have developed elaborate molecular machineries to sense a mixture of stress signals and elicit a precise response to minimize the damage. However, recent discoveries revealed that the interplay of these stress regulatory and signaling molecules is highly complex and remains largely unknown. In this work, we conducted large scale analysis of differential gene expression using advanced computational methods to dissect regulation of stress response which is at the heart of all molecular changes leading to the observed phenotypic susceptibility. One of the most important stress conditions in terms of loss of productivity is drought. We performed genomic and proteomic analysis of epigenetic and miRNA mechanisms in regulation of drought responsive genes in rice and found subsets of genes with striking properties. Overexpressed genesets included higher number of epigenetic marks, miRNA targets and transcription factors which regulate drought tolerance. On the other hand, underexpressed genesets were poor in above features but were rich in number of metabolic genes with multiple co-expression partners contributing majorly towards drought resistance. Identification and characterization of the patterns exhibited by differentially expressed genes hold key to uncover the synergistic and antagonistic components of the cross talk between stress response mechanisms. We performed meta-analysis on drought and bacterial stresses in rice and Arabidopsis, and identified hundreds of shared genes. We found high level of conservation of gene expression between these stresses. Weighted co-expression network analysis detected two tight clusters of genes made up of master transcription factors and signaling genes showing strikingly opposite expression status. To comprehensively identify the shared stress responsive genes between multiple abiotic and biotic stresses in rice, we performed meta-analyses of microarray studies from seven different abiotic and six biotic stresses separately and found more than thirteen hundred shared stress responsive genes. Various machine learning techniques utilizing these genes classified the stresses into two major classes' namely abiotic and biotic stresses and multiple classes of individual stresses with high accuracy and identified the top genes showing distinct patterns of expression. Functional enrichment and co-expression network analysis revealed the different roles of plant hormones, transcription factors in conserved and non-conserved genesets in regulation of stress response.

Genetic networks controlling retinal injury.

PURPOSE: The present study defines genomic loci underlying coordinate changes in gene expression following retinal injury. METHODS: A group of acute phase genes expressed in diverse nervous system tissues was defined by combining microarray results from injury studies from rat retina, brain, and spinal cord. Genomic loci regulating the brain expression of acute phase genes were identified using a panel of BXD recombinant inbred (RI) mouse strains. Candidate upstream regulators within a locus were defined using single nucleotide polymorphism databases and promoter motif databases. RESULTS: The acute phase response of rat retina, brain, and spinal cord was dominated by transcription factors. Three genomic loci control transcript expression of acute phase genes in brains of BXD RI mouse strains. One locus was identified on chromosome 12 and was highly correlated with the expression of classic acute phase genes. Within the locus we identified the inhibitor of DNA binding 2 (Id2) as a candidate upstream regulator. Id2 was upregulated as an acute phase transcript in injury models of rat retina, brain, and spinal cord. CONCLUSIONS: We defined a group of transcriptional changes associated with the retinal acute injury response. Using genetic linkage analysis of natural transcript variation, we identified regulatory loci and candidate regulators that control transcript levels of acute phase genes.

Saturday Morning Television Advertisements Aired on English and Spanish Language Networks along the Texas-Mexico Border

Objectives: The aim of this content analysis study is to characterize the TV advertisements aired to an at-risk child population along the Texas-Mexico border. Methods: We characterized the early Saturday morning TV advertisements aired by three broadcast network categories (U.S. English language, U.S. Spanish language, and Mexican Spanish language) in Spring 2010. The number, type (food related vs. non-food related), target audience, and persuasion tactics used were recorded. Advertised foods, based on nutrition content, were categorized as meeting or not meeting current dietary guidelines. Results: Most commercials were non-food related (82.7%, 397 of 480). The majority of the prepared foods (e.g., cereals, snacks, and drinks) advertised did not meet the current U.S. Dietary Guidelines. Additionally, nutrition content information was not available for many of the foods advertised on the Mexican Spanish language broadcast network category. Conclusions: For U.S. children at risk for obesity along the Texas-Mexico border exposure to TV food advertisements may result in the continuation of sedentary behavior as well as an increased consumption of foods of poor nutritional quality. An international regulatory effort to monitor and enforce the reduction of child-oriented food advertising is needed. Editors' Note: This article was submitted in response to the first issue of the Journal of Applied Research on Children: Latino Children.

Developmental self-construction and -configuration of functional neocortical neuronal networks.

The prenatal development of neural circuits must provide sufficient configuration to support at least a set of core postnatal behaviors. Although knowledge of various genetic and cellular aspects of development is accumulating rapidly, there is less systematic understanding of how these various processes play together in order to construct such functional networks. Here we make some steps toward such understanding by demonstrating through detailed simulations how a competitive co-operative ('winner-take-all', WTA) network architecture can arise by development from a single precursor cell. This precursor is granted a simplified gene regulatory network that directs cell mitosis, differentiation, migration, neurite outgrowth and synaptogenesis. Once initial axonal connection patterns are established, their synaptic weights undergo homeostatic unsupervised learning that is shaped by wave-like input patterns. We demonstrate how this autonomous genetically directed developmental sequence can give rise to self-calibrated WTA networks, and compare our simulation results with biological data.

Studying functional brain networks with concurrent transcranical alternating current stimulation and EEG

Recently transcranial electric stimulation (tES) has been widely used as a mean to modulate brain activity. The modulatory effects of tES have been studied with the excitability of primary motor cortex. However, tES effects are not limited to the site of stimulation but extended to other brain areas, suggesting a need for the study of functional brain networks. Transcranial alternating current stimulation (tACS) applies sinusoidal current at a specified frequency, presumably modulating brain activity in a frequency-specific manner. At a behavioural level, tACS has been confirmed to modulate behaviour, but its neurophysiological effects are still elusive. In addition, neural oscillations are considered to reflect rhythmic changes in transmission efficacy across brain networks, suggesting that tACS would provide a mean to modulate brain networks. To study neurophysiological effects of tACS, we have been developing a methodological framework by combining transcranial magnetic stimulation (TMS), EEG and tACS. We have developed the optimized concurrent tACS-EEG recording protocol and powerful artefact removal method that allow us to study neurophysiological effects of tACS. We also established the concurrent tACS-TMS-EEG recording to study brain network connectivity while introducing extrinsic oscillatory activity by tACS. We show that tACS modulate brain activity in a phase-dependent manner. Our methodological advancement will open an opportunity to study causal role of oscillatory brain activity in neural transmissions in cortical brain networks.

An Analysis of Next Generation Access Networks Deployment in rural areas

Next generation access networks (NGAN) will support a renewed electronic communication market where main opportunities lie in the provision of ubiquitous broadband connectivity, applications and content. From their deployment it is expected a wealth of innovations. Within this framework, the project reviews the variety of NGAN deployment options available for rural environments, derives a simple method for approximate cost calculations, and then discusses and compares the results obtained. Data for Spain are used for practical calculations, but the model is applicable with minor modifications to most of the rural areas of European countries. The final part of the paper is devoted to review the techno-economic implications of a network deployment in a rural environment as well as the adequacy and possible developments of the regulatory framework involved

Oscillatory genetic circuits: new designs and mathematical models

Introduction and motivation: A wide variety of organisms have developed in-ternal biomolecular clocks in order to adapt to cyclic changes of the environment. Clock operation involves genetic networks. These genetic networks have to be mod¬eled in order to understand the underlying mechanism of oscillations and to design new synthetic cellular clocks. This doctoral thesis has resulted in two contributions to the fields of genetic clocks and systems and synthetic biology, generally. The first contribution is a new genetic circuit model that exhibits an oscillatory behav¬ior through catalytic RNA molecules. The second and major contribution is a new genetic circuit model demonstrating that a repressor molecule acting on the positive feedback of a self-activating gene produces reliable oscillations. First contribution: A new model of a synthetic genetic oscillator based on a typical two-gene motif with one positive and one negative feedback loop is pre¬sented. The originality is that the repressor is a catalytic RNA molecule rather than a protein or a non-catalytic RNA molecule. This catalytic RNA is a ribozyme that acts post-transcriptionally by binding to and cleaving target mRNA molecules. This genetic clock involves just two genes, a mRNA and an activator protein, apart from the ribozyme. Parameter values that produce a circadian period in both determin¬istic and stochastic simulations have been chosen as an example of clock operation. The effects of the stochastic fluctuations are quantified by a period histogram and autocorrelation function. The conclusion is that catalytic RNA molecules can act as repressor proteins and simplify the design of genetic oscillators. Second and major contribution: It is demonstrated that a self-activating gene in conjunction with a simple negative interaction can easily produce robust matically validated. This model is comprised of two clearly distinct parts. The first is a positive feedback created by a protein that binds to the promoter of its own gene and activates the transcription. The second is a negative interaction in which a repressor molecule prevents this protein from binding to its promoter. A stochastic study shows that the system is robust to noise. A deterministic study identifies that the oscillator dynamics are mainly driven by two types of biomolecules: the protein, and the complex formed by the repressor and this protein. The main conclusion of this study is that a simple and usual negative interaction, such as degradation, se¬questration or inhibition, acting on the positive transcriptional feedback of a single gene is a sufficient condition to produce reliable oscillations. One gene is enough and the positive transcriptional feedback signal does not need to activate a second repressor gene. At the genetic level, this means that an explicit negative feedback loop is not necessary. Unlike many genetic oscillators, this model needs neither cooperative binding reactions nor the formation of protein multimers. Applications and future research directions: Recently, RNA molecules have been found to play many new catalytic roles. The first oscillatory genetic model proposed in this thesis uses ribozymes as repressor molecules. This could provide new synthetic biology design principles and a better understanding of cel¬lular clocks regulated by RNA molecules. The second genetic model proposed here involves only a repression acting on a self-activating gene and produces robust oscil¬lations. Unlike current two-gene oscillators, this model surprisingly does not require a second repressor gene. This result could help to clarify the design principles of cellular clocks and constitute a new efficient tool for engineering synthetic genetic oscillators. Possible follow-on research directions are: validate models in vivo and in vitro, research the potential of second model as a genetic memory, investigate new genetic oscillators regulated by non-coding RNAs and design a biosensor of positive feedbacks in genetic networks based on the operation of the second model Resumen Introduccion y motivacion: Una amplia variedad de organismos han desarro-llado relojes biomoleculares internos con el fin de adaptarse a los cambios ciclicos del entorno. El funcionamiento de estos relojes involucra redes geneticas. El mo delado de estas redes geneticas es esencial tanto para entender los mecanismos que producen las oscilaciones como para diseiiar nuevos circuitos sinteticos en celulas. Esta tesis doctoral ha dado lugar a dos contribuciones dentro de los campos de los circuitos geneticos en particular, y biologia de sistemas y sintetica en general. La primera contribucion es un nuevo modelo de circuito genetico que muestra un comportamiento oscilatorio usando moleculas de ARN cataliticas. La segunda y principal contribucion es un nuevo modelo de circuito genetico que demuestra que una molecula represora actuando sobre el lazo de un gen auto-activado produce oscilaciones robustas. Primera contribucion: Es un nuevo modelo de oscilador genetico sintetico basado en una tipica red genetica compuesta por dos genes con dos lazos de retroa-limentacion, uno positivo y otro negativo. La novedad de este modelo es que el represor es una molecula de ARN catalftica, en lugar de una protefna o una molecula de ARN no-catalitica. Este ARN catalitico es una ribozima que actua despues de la transcription genetica uniendose y cortando moleculas de ARN mensajero (ARNm). Este reloj genetico involucra solo dos genes, un ARNm y una proteina activadora, aparte de la ribozima. Como ejemplo de funcionamiento, se han escogido valores de los parametros que producen oscilaciones con periodo circadiano (24 horas) tanto en simulaciones deterministas como estocasticas. El efecto de las fluctuaciones es-tocasticas ha sido cuantificado mediante un histograma del periodo y la función de auto-correlacion. La conclusion es que las moleculas de ARN con propiedades cataliticas pueden jugar el misnio papel que las protemas represoras, y por lo tanto, simplificar el diseno de los osciladores geneticos. Segunda y principal contribucion: Es un nuevo modelo de oscilador genetico que demuestra que un gen auto-activado junto con una simple interaction negativa puede producir oscilaciones robustas. Este modelo ha sido estudiado y validado matematicamente. El modelo esta compuesto de dos partes bien diferenciadas. La primera parte es un lazo de retroalimentacion positiva creado por una proteina que se une al promotor de su propio gen activando la transcription. La segunda parte es una interaction negativa en la que una molecula represora evita la union de la proteina con el promotor. Un estudio estocastico muestra que el sistema es robusto al ruido. Un estudio determinista muestra que la dinamica del sistema es debida principalmente a dos tipos de biomoleculas: la proteina, y el complejo formado por el represor y esta proteina. La conclusion principal de este estudio es que una simple y usual interaction negativa, tal como una degradation, un secuestro o una inhibition, actuando sobre el lazo de retroalimentacion positiva de un solo gen es una condition suficiente para producir oscilaciones robustas. Un gen es suficiente y el lazo de retroalimentacion positiva no necesita activar a un segundo gen represor, tal y como ocurre en los relojes actuales con dos genes. Esto significa que a nivel genetico un lazo de retroalimentacion negativa no es necesario de forma explicita. Ademas, este modelo no necesita reacciones cooperativas ni la formation de multimeros proteicos, al contrario que en muchos osciladores geneticos. Aplicaciones y futuras lineas de investigacion: En los liltimos anos, se han descubierto muchas moleculas de ARN con capacidad catalitica. El primer modelo de oscilador genetico propuesto en esta tesis usa ribozimas como moleculas repre¬soras. Esto podria proporcionar nuevos principios de diseno en biologia sintetica y una mejor comprension de los relojes celulares regulados por moleculas de ARN. El segundo modelo de oscilador genetico propuesto aqui involucra solo una represion actuando sobre un gen auto-activado y produce oscilaciones robustas. Sorprendente-mente, un segundo gen represor no es necesario al contrario que en los bien conocidos osciladores con dos genes. Este resultado podria ayudar a clarificar los principios de diseno de los relojes celulares naturales y constituir una nueva y eficiente he-rramienta para crear osciladores geneticos sinteticos. Algunas de las futuras lineas de investigation abiertas tras esta tesis son: (1) la validation in vivo e in vitro de ambos modelos, (2) el estudio del potential del segundo modelo como circuito base para la construction de una memoria genetica, (3) el estudio de nuevos osciladores geneticos regulados por ARN no codificante y, por ultimo, (4) el rediseno del se¬gundo modelo de oscilador genetico para su uso como biosensor capaz de detectar genes auto-activados en redes geneticas.

The generation of oscillations in networks of electrically coupled cells

In several biological systems, the electrical coupling of nonoscillating cells generates synchronized membrane potential oscillations. Because the isolated cell is nonoscillating and electrical coupling tends to equalize the membrane potentials of the coupled cells, the mechanism underlying these oscillations is unclear. Here we present a dynamic mechanism by which the electrical coupling of identical nonoscillating cells can generate synchronous membrane potential oscillations. We demonstrate this mechanism by constructing a biologically feasible model of electrically coupled cells, characterized by an excitable membrane and calcium dynamics. We show that strong electrical coupling in this network generates multiple oscillatory states with different spatio-temporal patterns and discuss their possible role in the cooperative computations performed by the system.

Peroxynitrite disables the tyrosine phosphorylation regulatory mechanism: Lymphocyte-specific tyrosine kinase fails to phosphorylate nitrated cdc2(6-20)NH2 peptide.

To determine if nitration of tyrosine residues by peroxynitrite (PN), which can be generated endogenously, can disrupt the phosphorylation of tyrosine residues in proteins involved in cell signaling networks, we studied the effect of PN-promoted nitration of tyrosine residues in a pentadecameric peptide, cdc2(6-20)NH2, on the ability of the peptide to be phosphorylated. cdc2(6-20)NH2 corresponds to the tyrosine phosphorylation site of p34cdc2 kinase, which is phosphorylated by lck kinase (lymphocyte-specific tyrosine kinase, p56lck). PN nitrates both Tyr-15 and Tyr-19 of the peptide in phosphate buffer (pH 7.5) at 37 degrees C. Nitration of Tyr-15. which is the phosphorylated amino acid residue, inhibits completely the phosphorylation of the peptide. The nitration reaction is enhanced by either Fe(III)EDTA or Cu(II)-Zn(II)-superoxide dismutase (Cu,Zn-SOD). The kinetic data are consistent with the view that reactions of Fe(111)EDTA or Cu,Zn-SOD with the cis form of PN yield complexes in which PN decomposes more slowly to form N02+, the nitrating agent. Thus, the nitration efficiency of PN is enhanced. These results are discussed from the point of view that PN-promoted nitration will result in permanent impairment of cyclic cascades that control signal transduction processes and regulate cell cycles.

Why is Europe lagging on next generation access networks? Bruegel Policy Contribution ISSUE 2015/14, September 2015

Why is Europe lagging on next generation access networks? Fibre-based next generation access (NGA) roll-out across the European Union is one of the goals of the European Commission’s Digital Agenda strategy, however, there remains considerable uncertainty about how the roll-out goal can best be achieved. The underlying differences between the economics of copper-based and new fibre-based broadband infrastructures should lead to a revision of the regulatory framework for telecommunications markets. While the current regulatory measures have been useful in the past decade to sustain competition and facilitate entry into a market with already-existing infrastructures, the need to create new, much faster broadband networks calls for a rethink of the scope and strictness of regulation.

Logical Modeling and Dynamical Analysis of Cellular Networks

The logical (or logic) formalism is increasingly used to model regulatory and signaling networks. Complementing these applications, several groups contributed various methods and tools to support the definition and analysis of logical models. After an introduction to the logical modeling framework and to several of its variants, we review here a number of recent methodological advances to ease the analysis of large and intricate networks. In particular, we survey approaches to determine model attractors and their reachability properties, to assess the dynamical impact of variations of external signals, and to consistently reduce large models. To illustrate these developments, we further consider several published logical models for two important biological processes, namely the differentiation of T helper cells and the control of mammalian cell cycle.

Inherent size constraints on prokaryote gene networks due to "accelerating" growth

Networks exhibiting accelerating growth have total link numbers growing faster than linearly with network size and either reach a limit or exhibit graduated transitions from nonstationary-to-stationary statistics and from random to scale-free to regular statistics as the network size grows. However, if for any reason the network cannot tolerate such gross structural changes then accelerating networks are constrained to have sizes below some critical value. This is of interest as the regulatory gene networks of single-celled prokaryotes are characterized by an accelerating quadratic growth and are size constrained to be less than about 10,000 genes encoded in DNA sequence of less than about 10 megabases. This paper presents a probabilistic accelerating network model for prokaryotic gene regulation which closely matches observed statistics by employing two classes of network nodes (regulatory and non-regulatory) and directed links whose inbound heads are exponentially distributed over all nodes and whose outbound tails are preferentially attached to regulatory nodes and described by a scale-free distribution. This model explains the observed quadratic growth in regulator number with gene number and predicts an upper prokaryote size limit closely approximating the observed value. (c) 2005 Elsevier GmbH. All rights reserved.

GANN: Genetic algorithm neural networks for the detection of conserved combinations of features in DNA

Background: The multitude of motif detection algorithms developed to date have largely focused on the detection of patterns in primary sequence. Since sequence-dependent DNA structure and flexibility may also play a role in protein-DNA interactions, the simultaneous exploration of sequence-and structure-based hypotheses about the composition of binding sites and the ordering of features in a regulatory region should be considered as well. The consideration of structural features requires the development of new detection tools that can deal with data types other than primary sequence. Results: GANN ( available at http://bioinformatics.org.au/gann) is a machine learning tool for the detection of conserved features in DNA. The software suite contains programs to extract different regions of genomic DNA from flat files and convert these sequences to indices that reflect sequence and structural composition or the presence of specific protein binding sites. The machine learning component allows the classification of different types of sequences based on subsamples of these indices, and can identify the best combinations of indices and machine learning architecture for sequence discrimination. Another key feature of GANN is the replicated splitting of data into training and test sets, and the implementation of negative controls. In validation experiments, GANN successfully merged important sequence and structural features to yield good predictive models for synthetic and real regulatory regions. Conclusion: GANN is a flexible tool that can search through large sets of sequence and structural feature combinations to identify those that best characterize a set of sequences.