A Molecular Network That Produces Spontaneous Oscillations in Excitable Cells of Dictyostelium

A network of interacting proteins has been found that can account for the spontaneous oscillations in adenylyl cyclase activity that are observed in homogenous populations of Dictyostelium cells 4 h after the initiation of development. Previous biochemical assays have shown that when extracellular adenosine 3′,5′-cyclic monophosphate (cAMP) binds to the surface receptor CAR1, adenylyl cyclase and the MAP kinase ERK2 are transiently activated. A rise in the internal concentration of cAMP activates protein kinase A such that it inhibits ERK2 and leads to a loss-of-ligand binding by CAR1. ERK2 phosphorylates the cAMP phosphodiesterase REG A that reduces the internal concentration of cAMP. A secreted phosphodiesterase reduces external cAMP concentrations between pulses. Numerical solutions to a series of nonlinear differential equations describing these activities faithfully account for the observed periodic changes in cAMP. The activity of each of the components is necessary for the network to generate oscillatory behavior; however, the model is robust in that 25-fold changes in the kinetic constants linking the activities have only minor effects on the predicted frequency. Moreover, constant high levels of external cAMP lead to attenuation, whereas a brief pulse of cAMP can advance or delay the phase such that interacting cells become entrained.

Inter-strand C-H...O hydrogen bonds stabilizing four-stranded intercalated molecules: stereoelectronic effects of O4' in cytosine-rich DNA.

DNA fragments with stretches of cytosine residues can fold into four-stranded structures in which two parallel duplexes, held together by hemiprotonated cytosine.cytosine+ (C.C+) base pairs, intercalate into each other with opposite polarity. The structural details of this intercalated DNA quadruplex have been assessed by solution NMR and single crystal x-ray diffraction studies of cytosine-rich sequences, including those present in metazoan telomeres. A conserved feature of these structures is the absence of stabilizing stacking interactions between the aromatic ring systems of adjacent C.C+ base pairs from intercalated duplexes. Effective stacking involves only the exocyclic keto groups and amino groups of the cytidine bases. The apparent absence of stability provided by stacking interactions between the bases in this intercalated DNA has prompted us to examine the available structures in detail, in particular with regard to unusual features that could compensate for the lack of base stacking. In addition to base-on-deoxyribose stacking and intra-cytidine C-H...O hydrogen bonds, this analysis reveals the presence of a hitherto unobserved, systematic intermolecular C-H...O hydrogen bonding network between the deoxyribose sugar moieties of antiparallel backbones in the four-stranded molecule.

Financial fragility, trade credit and contagion effects during the crisis: a spatial econometric approach to firm-level data

The number of distressed manufacturing firms increased sharply during recessionary phase 2009-13. Financial indebtness traditionally plays a key role in assessing firm solvency but contagion effects that originate from the supply chain are usually neglected in literature. Firm interconnections, captured via the trade credit channel, represent a primary vehicle of individual shocks’ propagation, especially during an economic downturn, when liquidity tensions arise. A representative sample of 11,920 Italian manufacturing firms is considered to model a two-step econometric design, where chain reactions in terms of trade credit accumulation (i.e. default of payments to suppliers) are primarily analyzed by resorting to a spatial autoregressive approach (SAR). Spatial interactions are modeled based on a unique dataset of firm-to-firm transactions registered before the outbreak of the crisis. The second step in instead a binary outcome model where trade credit chains are considered together with data on the bank-firm relationship to assess determinants of distress likelihoods in 2009-13. Results show that outstanding trade debt is affected by the liquidity position of a firm and by positive spatial effects. Trade credit chain reactions are found to exert, in turn, a positive impact on distress likelihoods during the crisis. The latter effect is comparable in magnitude to the one exerted by individual financial rigidity, and stresses the importance to include complex interactions between firms in the analysis of the solvency behavior.

Technology diffusion and its effects on social inequalities

We develop a dynamic general-equilibrium framework in which growth is driven by skill-biased technology diffusion. The model incorporates leisure–labor decisions and human capital accumulation through education. We are able to reproduce the trends in income inequality and labor and skills supplies observed in the United States between 1969 and 1996. The paper also provides an explanation for why more individuals invest in human capital when the investment premium is going down, and why the skill-premium goes up when the skills supply is increasing.

Epileptic networks are strongly connected with and without the effects of interictal discharges

OBJECTIVE Epilepsy is increasingly considered as the dysfunction of a pathologic neuronal network (epileptic network) rather than a single focal source. We aimed to assess the interactions between the regions that comprise the epileptic network and to investigate their dependence on the occurrence of interictal epileptiform discharges (IEDs). METHODS We analyzed resting state simultaneous electroencephalography-functional magnetic resonance imaging (EEG-fMRI) recordings in 10 patients with drug-resistant focal epilepsy with multifocal IED-related blood oxygen level-dependent (BOLD) responses and a maximum t-value in the IED field. We computed functional connectivity (FC) maps of the epileptic network using two types of seed: (1) a 10-mm diameter sphere centered in the global maximum of IED-related BOLD map, and (2) the independent component with highest correlation to the IED-related BOLD map, named epileptic component. For both approaches, we compared FC maps before and after regressing out the effect of IEDs in terms of maximum and mean t-values and percentage of map overlap. RESULTS Maximum and mean FC maps t-values were significantly lower after regressing out IEDs at the group level (p < 0.01). Overlap extent was 85% ± 12% and 87% ± 12% when the seed was the 10-mm diameter sphere and the epileptic component, respectively. SIGNIFICANCE Regions involved in a specific epileptic network show coherent BOLD fluctuations independent of scalp EEG IEDs. FC topography and strength is largely preserved by removing the IED effect. This could represent a signature of a sustained pathologic network with contribution from epileptic activity invisible to the scalp EEG.

Accounting for residential and non-residential environments to measure contextual effects on health behavior : the case of recreational walking behavior

Thèse réalisée en cotutelle entre l'Université de Montréal et l'Université Pierre et Marie Curie, Paris 06, Sorbonne Universités.

The European Narcolepsy Network (EU-NN) database.

Narcolepsy with cataplexy is a rare disease with an estimated prevalence of 0.02% in European populations. Narcolepsy shares many features of rare disorders, in particular the lack of awareness of the disease with serious consequences for healthcare supply. Similar to other rare diseases, only a few European countries have registered narcolepsy cases in databases of the International Classification of Diseases or in registries of the European health authorities. A promising approach to identify disease-specific adverse health effects and needs in healthcare delivery in the field of rare diseases is to establish a distributed expert network. A first and important step is to create a database that allows collection, storage and dissemination of data on narcolepsy in a comprehensive and systematic way. Here, the first prospective web-based European narcolepsy database hosted by the European Narcolepsy Network is introduced. The database structure, standardization of data acquisition and quality control procedures are described, and an overview provided of the first 1079 patients from 18 European specialized centres. Due to its standardization this continuously increasing data pool is most promising to provide a better insight into many unsolved aspects of narcolepsy and related disorders, including clear phenotype characterization of subtypes of narcolepsy, more precise epidemiological data and knowledge on the natural history of narcolepsy, expectations about treatment effects, identification of post-marketing medication side-effects, and will contribute to improve clinical trial designs and provide facilities to further develop phase III trials.

Certain observations concerning the effects of epistasis on complex traits and the evolution of genomes.

Thesis (Ph.D.)--University of Washington, 2016-05

Typing mineral deposits using their grades and tonnages in an artificial neural network

A test of the ability of a probabilistic neural network to classify deposits into types on the basis of deposit tonnage and average Cu, Mo, Ag, Au, Zn, and Pb grades is conducted. The purpose is to examine whether this type of system might serve as a basis for integrating geoscience information available in large mineral databases to classify sites by deposit type. Benefits of proper classification of many sites in large regions are relatively rapid identification of terranes permissive for deposit types and recognition of specific sites perhaps worthy of exploring further. Total tonnages and average grades of 1,137 well-explored deposits identified in published grade and tonnage models representing 13 deposit types were used to train and test the network. Tonnages were transformed by logarithms and grades by square roots to reduce effects of skewness. All values were scaled by subtracting the variable's mean and dividing by its standard deviation. Half of the deposits were selected randomly to be used in training the probabilistic neural network and the other half were used for independent testing. Tests were performed with a probabilistic neural network employing a Gaussian kernel and separate sigma weights for each class (type) and each variable (grade or tonnage). Deposit types were selected to challenge the neural network. For many types, tonnages or average grades are significantly different from other types, but individual deposits may plot in the grade and tonnage space of more than one type. Porphyry Cu, porphyry Cu-Au, and porphyry Cu-Mo types have similar tonnages and relatively small differences in grades. Redbed Cu deposits typically have tonnages that could be confused with porphyry Cu deposits, also contain Cu and, in some situations, Ag. Cyprus and kuroko massive sulfide types have about the same tonnages. Cu, Zn, Ag, and Au grades. Polymetallic vein, sedimentary exhalative Zn-Pb, and Zn-Pb skarn types contain many of the same metals. Sediment-hosted Au, Comstock Au-Ag, and low-sulfide Au-quartz vein types are principally Au deposits with differing amounts of Ag. Given the intent to test the neural network under the most difficult conditions, an overall 75% agreement between the experts and the neural network is considered excellent. Among the largestclassification errors are skarn Zn-Pb and Cyprus massive sulfide deposits classed by the neuralnetwork as kuroko massive sulfides—24 and 63% error respectively. Other large errors are the classification of 92% of porphyry Cu-Mo as porphyry Cu deposits. Most of the larger classification errors involve 25 or fewer training deposits, suggesting that some errors might be the result of small sample size. About 91% of the gold deposit types were classed properly and 98% of porphyry Cu deposits were classes as some type of porphyry Cu deposit. An experienced economic geologist would not make many of the classification errors that were made by the neural network because the geologic settings of deposits would be used to reduce errors. In a separate test, the probabilistic neural network correctly classed 93% of 336 deposits in eight deposit types when trained with presence or absence of 58 minerals and six generalized rock types. The overall success rate of the probabilistic neural network when trained on tonnage and average grades would probably be more than 90% with additional information on the presence of a few rock types.

GPNN: Power studies and applications of a neural network method for detecting gene-gene interactions in studies of human disease

Background The identification and characterization of genes that influence the risk of common, complex multifactorial disease primarily through interactions with other genes and environmental factors remains a statistical and computational challenge in genetic epidemiology. We have previously introduced a genetic programming optimized neural network (GPNN) as a method for optimizing the architecture of a neural network to improve the identification of gene combinations associated with disease risk. The goal of this study was to evaluate the power of GPNN for identifying high-order gene-gene interactions. We were also interested in applying GPNN to a real data analysis in Parkinson's disease. Results We show that GPNN has high power to detect even relatively small genetic effects (2–3% heritability) in simulated data models involving two and three locus interactions. The limits of detection were reached under conditions with very small heritability (

Effects of structural variation in xyloglucan polymers on interactions with bacterial cellulose

A cellulose/xyloglucan framework is considered to form the basis for the mechanical properties of primary plant cell walls and hence to have a major influence on the biomechanical properties of growing, fleshy plant tissues. In this study, structural variants of xyloglucan have been investigated as components of composites with bacterial cellulose as a simplified model for the cellulose/xyloglucan framework of primary plant cell walls. Evidence for molecular binding to cellulose with perturbation of cellulose crystallinity was found for all xyloglucan types. High molecular mass samples gave homogeneous centimeter-scale composites with extensive cross-linking of cellulose with xyloglucan. Lower molecular mass xyloglucans gave heterogeneous composites having a range of microscopic structures with little, if any, cross-linking. Xyloglucans with reduced levels of galactose substitution had evidence of self-association, competitive with cellulose binding. At comparable molecular mass, fucose substitution resulted in a modest promotion of microscopic features characteristic of primary cell walls. Taken together, the data are evidence that galactose substitution of the xyloglucan core structure is a major determinant of cellulose composite formation and properties, with additional fucose substitution acting as a secondary modulator. These conclusions are consistent with reported structural and mechanical properties of Arabidopsis mutants lacking specific facose and/or galactose residues.

GPNN: Power studies and applications of a neural network method for detecting gene-gene interactions in studies of human disease

Background: The identification and characterization of genes that influence the risk of common, complex multifactorial disease primarily through interactions with other genes and environmental factors remains a statistical and computational challenge in genetic epidemiology. We have previously introduced a genetic programming optimized neural network (GPNN) as a method for optimizing the architecture of a neural network to improve the identification of gene combinations associated with disease risk. The goal of this study was to evaluate the power of GPNN for identifying high-order gene-gene interactions. We were also interested in applying GPNN to a real data analysis in Parkinson's disease. Results: We show that GPNN has high power to detect even relatively small genetic effects (2-3% heritability) in simulated data models involving two and three locus interactions. The limits of detection were reached under conditions with very small heritability (

Tourism crisis and disasters: Enhancing understanding of system effects

This paper examines the definitions and conceptual foundations of crises and distinguishes between crises and disasters. It takes a systems view of these concepts and uses the perspective of systems as organizational networks to examine implications for tourism managers. A tourism destination is perceived as consisting of a network of interacting organizations. This perspective questions the boundaries that should be used to study crisis and disasters. The paper also discusses the possibility of a crisis having a positive outcome for a destination.

Spontaneous combustion and simulation of mine fires and their effects on mine ventilation systems

The structure of a comprehensive research project into mine fires study applying the Ventgraph mine fire simulation software, preplanning of escape scenarios and general interaction with rescue responses is outlined. The project has Australian Coal Association Research Program (ACARP) funding and also relies on substantial mining company site support. This practical input from mine operators is essential and allows the approach to be introduced in the most creditable way. The effort is built around the introduction of fire simulation computer software to the Australian mining industry and the consequent modelling of fire scenarios in selected different mine layouts. Application of the simulation software package to the changing mine layouts requires experience to achieve realistic outcomes. Most Australian mines of size currently use a ventilation network simulation program. Under the project a small subroutine has been written to transfer the input data from the existing mine ventilation network simulation program to ‘Ventgraph’. This has been tested successfully. To understand fire simulation behaviour on the mine ventilation system, it is necessary to understood the possible effects of mine fires on various mine ventilation systems correctly first. Case studies demonstrating the possible effects of fires on some typical Australian coal mine ventilation circuits have been examined. The situation in which there is some gas make at the face and effects with fire have also been developed to emphasise how unstable and dangerous situations may arise. The primary objective of the part of the study described in this paper is to use mine fire simulation software to gain better understanding of how spontaneous combustion initiated fires can interact with the complex ventilation behaviour underground during a substantial fire. It focuses on the simulation of spontaneous combustion sourced heatings that develop into open fires. Further, it examines ventilation behaviour effects of spontaneous combustion initiated pillar fires and examines the difficulties these can be present if a ventilation reversal occurs. It also briefly examines simulation of use of the inertisation to assist in mine recovery. Mine fires are recognised across the world as a major hazard issue. New approaches allowing improvement in understanding their consequences have been developed as an aid in handling this complex area.

Modulation of neuronal network activity in the primary motor cortex

In the present study I investigated the mechanisms of modulation of neuronal network activity in rat primary motor cortex using pharmacological manipulations employing the in vitro brain slice technique. Preparation of the brain slice in sucrose-based aCSF produced slices with low viability. Introducing the neuroprotectants N-acetyl-cysteine, taurine and aminoguanidine to the preparatory method saw viability of slices increase significantly. Co-application of low dose kainic acid and carbachol consistently generated beta oscillatory activity in M1. Analyses indicated that network activity in M1 relied on the involvement of GABAA receptors. Dose-response experiments performed in M1 showed that beta activity can be modulated by benzodiazepine site ligands. Low doses of positive allosteric modulators consistently desynchronised beta oscillatory activity, a mechanism that may be driven by a1-subunit containing GABAA receptors. Higher doses increased the power of beta oscillatory activity. Whole-cell recordings in M1 uncovered three interneuronal subtypes regularly encountered in M1; Fast-spiking, regular-spiking non-Pyramidal and low threshold spiking. With the paradoxical effects of positive allosteric modulators in mind, subsequent voltage-clamp recordings in FS cells revealed a constitutively active tonic inhibitory current that could be modulated by zolpidem in two different ways. Low dose zolpidem increased the tonic inhibitory current in FS cells, consistent with the desynchronisation of network oscillatory activity seen at this concentration. High dose zolpidem decreased the inhibitory tonic current seen in FS cells, coinciding with an increase in oscillatory power. These studies indicate a fundamental role for a tonic inhibitory current in the modulation of network activity. Furthermore, desynchronisation of beta activity in M1 decreased as viability of the in vitro brain slice increased, suggesting that the extent of desynchronisation is dependent upon the pathophysiological state of the network. This indicates that low dose zolpidem could be used as a therapeutic agent specifically for the desynchronisation of pathological oscillations in oscillopathies such as Parkinson’s disease.