5,532 research outputs found

    Pattern formation by lateral inhibition with feedback: a mathematical model of Delta-Notch intercellular signalling

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    In many developing tissues, adjacent cells diverge in character so as to create a fine-grained pattern of cells in contrasting states of differentiation. It has been proposed that such patterns can be generated through lateral inhibition—a type cells–cell interaction whereby a cell that adopts a particular fate inhibits its immediate neighbours from doing likewise. Lateral inhibition is well documented in flies, worms and vertebrates. In all of these organisms, the transmembrane proteins Notch and Delta (or their homologues) have been identified as mediators of the interaction—Notch as receptor, Delta as its ligand on adjacent cells. However, it is not clear under precisely what conditions the Delta-Notch mechanism of lateral inhibition can generate the observed types of pattern, or indeed whether this mechanism is capable of generating such patterns by itself. Here we construct and analyse a simple and general mathematical model of such contact-mediated lateral inhibition. In accordance with experimental data, the model postulates that receipt of inhibition (i.e. activation of Notch) diminishes the ability to deliver inhibition (i.e. to produce active Delta). This gives rise to a feedback loop that can amplify differences between adjacent cells. We investigate the pattern-forming potential and temporal behavior of this model both analytically and through numerical simulation. Inhomogeneities are self-amplifying and develop without need of any other machinery, provided the feedback is sufficiently strong. For a wide range of initial and boundary conditions, the model generates fine-grained patterns similar to those observed in living systems

    Deletion of Tsc2 in nociceptors reduces target innervation, ion channel expression, and sensitivity to heat

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    AbstractThe mechanistic target of rapamycin complex 1 (mTORC1) is known to regulate cellular growth pathways, and its genetic activation is sufficient to enhance regenerative axon growth following injury to the central or peripheral nervous systems. However, excess mTORC1 activation may promote innervation defects, and mTORC1 activity mediates injury-induced hypersensitivity, reducing enthusiasm for the pathway as a therapeutic target. While mTORC1 activity is required for full expression of some pain modalities, the effects of pathway activation on nociceptor phenotypes and sensory behaviors are currently unknown. To address this, we genetically activated mTORC1 in mouse peripheral sensory neurons by conditional deletion of its negative regulator Tuberous Sclerosis Complex 2 (Tsc2). Consistent with the well-known role of mTORC1 in regulating cell size, soma size and axon diameter of C-nociceptors were increased in Tsc2-deleted mice. Glabrous skin and spinal cord innervation by C-fiber neurons were also disrupted. Transcriptional profiling of nociceptors enriched by fluorescence-associated cell sorting (FACS) revealed downregulation of multiple classes of ion channels as well as reduced expression of markers for peptidergic nociceptors in Tsc2-deleted mice. In addition to these changes in innervation and gene expression, Tsc2-deleted mice exhibited reduced noxious heat sensitivity and decreased injury-induced cold hypersensitivity, but normal baseline sensitivity to cold and mechanical stimuli. Together, these data show that excess mTORC1 activity in sensory neurons produces changes in gene expression, neuron morphology and sensory behavior.</jats:p

    Central Stars of Planetary Nebulae in the Large Magellanic Cloud: A Far-UV Spectroscopic Analysis

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    We observed seven central stars of planetary nebulae (CSPN) in the Large Magellanic Cloud (LMC) with the Far Ultraviolet Spectroscopic Explorer (FUSE), and performed a model-based analysis of these spectra in conjunction with Hubble Space Telescope (HST) spectra in the UV and optical range to determine the stellar and nebular parameters. Most of the objects show wind features, and they have effective temperatures ranging from 38 to 60 kK with mass-loss rates of ~= 5x10^-8 Msun/yr. Five of the objects have typical LMC abundances. One object (SMP LMC 61) is a [WC4] star, and we fit its spectra with He/C/O-rich abundances typical of the [WC] class, and find its atmosphere to be iron-deficient. Most objects have very hot (T ~> 2000 K) molecular hydrogen in their nebulae, which may indicate a shocked environment. One of these (SMP LMC 62) also displays OVI 1032-38 nebular emission lines, rarely observed in PN.Comment: 53 pages, 15 figures (11 color). Accepted for publication in Ap

    Weighted network modules

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    The inclusion of link weights into the analysis of network properties allows a deeper insight into the (often overlapping) modular structure of real-world webs. We introduce a clustering algorithm (CPMw, Clique Percolation Method with weights) for weighted networks based on the concept of percolating k-cliques with high enough intensity. The algorithm allows overlaps between the modules. First, we give detailed analytical and numerical results about the critical point of weighted k-clique percolation on (weighted) Erdos-Renyi graphs. Then, for a scientist collaboration web and a stock correlation graph we compute three-link weight correlations and with the CPMw the weighted modules. After reshuffling link weights in both networks and computing the same quantities for the randomised control graphs as well, we show that groups of 3 or more strong links prefer to cluster together in both original graphs.Comment: 19 pages, 7 figure

    Identifying dynamical modules from genetic regulatory systems: applications to the segment polarity network

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    BACKGROUND It is widely accepted that genetic regulatory systems are 'modular', in that the whole system is made up of smaller 'subsystems' corresponding to specific biological functions. Most attempts to identify modules in genetic regulatory systems have relied on the topology of the underlying network. However, it is the temporal activity (dynamics) of genes and proteins that corresponds to biological functions, and hence it is dynamics that we focus on here for identifying subsystems. RESULTS Using Boolean network models as an exemplar, we present a new technique to identify subsystems, based on their dynamical properties. The main part of the method depends only on the stable dynamics (attractors) of the system, thus requiring no prior knowledge of the underlying network. However, knowledge of the logical relationships between the network components can be used to describe how each subsystem is regulated. To demonstrate its applicability to genetic regulatory systems, we apply the method to a model of the Drosophila segment polarity network, providing a detailed breakdown of the system. CONCLUSION We have designed a technique for decomposing any set of discrete-state, discrete-time attractors into subsystems. Having a suitable mathematical model also allows us to describe how each subsystem is regulated and how robust each subsystem is against perturbations. However, since the subsystems are found directly from the attractors, a mathematical model or underlying network topology is not necessarily required to identify them, potentially allowing the method to be applied directly to experimental expression data

    Parental Coping Socialization is Associated with Healthy and Anxious Early-Adolescents’ Neural and Real-World Response to Threat

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    The ways parents socialize their adolescents to cope with anxiety (i.e. coping socialization) may be instrumental in the development of threat processing and coping responses. Coping socialization may be important for anxious adolescents, as they show altered neural threat processing and over-reliance on disengaged coping (e.g., avoidance and distraction), which can maintain anxiety. We investigated whether coping socialization was associated with anxious and healthy adolescents’ neural response to threat, and whether neural activation was associated with disengaged coping. Healthy and clinically anxious early-adolescents (N=120; M=11.46 years; 71 girls) and a parent engaged in interactions designed to elicit adolescents’ anxiety and parents’ response to adolescents’ anxiety. Parents’ use of reframing and problem-solving statements was coded to measure coping socialization. In a subsequent visit, we assessed adolescents’ neural response to threat words during a neuroimaging task. Adolescents’ disengaged coping was measured using ecological momentary assessment. Greater coping socialization was associated with lower anterior insula and perigenual cingulate activation in healthy adolescents and higher activation in anxious adolescents. Coping socialization was indirectly associated with less disengaged coping for anxious adolescents through neural activation. Findings suggest that associations between coping socialization and early adolescents’ neural response to threat differ depending on clinical status and have implications for anxious adolescents’ coping
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