Molecular Aspects of Secretory Granule Exocytosis by Neurons and Endocrine Cells

Neuronal communication and endocrine signaling are fundamental for integrating the function of tissues and cells in the body. Hormones released by endocrine cells are transported to the target cells through the circulation. By contrast, transmitter release from neurons occurs at specialized intercellular junctions, the synapses. Nevertheless, the mechanisms by which signal molecules are synthesized, stored, and eventually secreted by neurons and endocrine cells are very similar. Neurons and endocrine cells have in common two different types of secretory organelles, indicating the presence of two distinct secretory pathways. The synaptic vesicles of neurons contain excitatory or inhibitory neurotransmitters, whereas the secretory granules (also referred to as dense core vesicles, because of their electron dense content) are filled with neuropeptides and amines. In endocrine cells, peptide hormones and amines predominate in secretory granules. The function and content of vesicles, which share antigens with synaptic vesicles, are unknown for most endocrine cells. However, in B cells of the pancreatic islet, these vesicles contain GABA, which may be involved in intrainsular signaling.' Exocytosis of both synaptic vesicles and secretory granules is controlled by cytoplasmic calcium. However, the precise mechanisms of the subsequent steps, such as docking of vesicles and fusion of their membranes with the plasma membrane, are still incompletely understood. This contribution summarizes recent observations that elucidate components in neurons and endocrine cells involved in exocytosis. Emphasis is put on the intracellular aspects of the release of secretory granules that recently have been analyzed in detail

Pareto versus lognormal: a maximum entropy test

It is commonly found that distributions that seem to be lognormal over a broad range change to a power-law (Pareto) distribution for the last few percentiles. The distributions of many physical, natural, and social events (earthquake size, species abundance, income and wealth, as well as file, city, and firm sizes) display this structure. We present a test for the occurrence of power-law tails in statistical distributions based on maximum entropy. This methodology allows one to identify the true data-generating processes even in the case when it is neither lognormal nor Pareto. The maximum entropy approach is then compared with other widely used methods and applied to different levels of aggregation of complex systems. Our results provide support for the theory that distributions with lognormal body and Pareto tail can be generated as mixtures of lognormally distributed units

The World-Trade Web: Topological Properties, Dynamics, and Evolution

This paper studies the statistical properties of the web of import-export relationships among world countries using a weighted-network approach. We analyze how the distributions of the most important network statistics measuring connectivity, assortativity, clustering and centrality have co-evolved over time. We show that all node-statistic distributions and their correlation structure have remained surprisingly stable in the last 20 years -- and are likely to do so in the future. Conversely, the distribution of (positive) link weights is slowly moving from a log-normal density towards a power law. We also characterize the autoregressive properties of network-statistics dynamics. We find that network-statistics growth rates are well-proxied by fat-tailed densities like the Laplace or the asymmetric exponential-power. Finally, we find that all our results are reasonably robust to a few alternative, economically-meaningful, weighting schemes.Comment: 44 pages, 39 eps figure

Global Networks of Trade and Bits

Considerable efforts have been made in recent years to produce detailed topologies of the Internet. Although Internet topology data have been brought to the attention of a wide and somewhat diverse audience of scholars, so far they have been overlooked by economists. In this paper, we suggest that such data could be effectively treated as a proxy to characterize the size of the "digital economy" at country level and outsourcing: thus, we analyse the topological structure of the network of trade in digital services (trade in bits) and compare it with that of the more traditional flow of manufactured goods across countries. To perform meaningful comparisons across networks with different characteristics, we define a stochastic benchmark for the number of connections among each country-pair, based on hypergeometric distribution. Original data are thus filtered by means of different thresholds, so that we only focus on the strongest links, i.e., statistically significant links. We find that trade in bits displays a sparser and less hierarchical network structure, which is more similar to trade in high-skill manufactured goods than total trade. Lastly, distance plays a more prominent role in shaping the network of international trade in physical goods than trade in digital services.Comment: 25 pages, 6 figure

The International Trade Network: weighted network analysis and modelling

Tools of the theory of critical phenomena, namely the scaling analysis and universality, are argued to be applicable to large complex web-like network structures. Using a detailed analysis of the real data of the International Trade Network we argue that the scaled link weight distribution has an approximate log-normal distribution which remains robust over a period of 53 years. Another universal feature is observed in the power-law growth of the trade strength with gross domestic product, the exponent being similar for all countries. Using the 'rich-club' coefficient measure of the weighted networks it has been shown that the size of the rich-club controlling half of the world's trade is actually shrinking. While the gravity law is known to describe well the social interactions in the static networks of population migration, international trade, etc, here for the first time we studied a non-conservative dynamical model based on the gravity law which excellently reproduced many empirical features of the ITN.Comment: 5 pages, 5 figure

HOX D13 expression across 79 tumor tissue types.

HOX genes control normal development, primary cellular processes and are characterized by a unique genomic network organization. Locus D HOX genes play an important role in limb generation and mesenchymal condensation. Dysregulated HOXD13 expression has been detected in breast cancer, melanoma, cervical cancer and astrocytomas. We have investigated the epidemiology of HOXD13 expression in human tissues and its potential deregulation in the carcinogenesis of specific tumors. HOXD13 homeoprotein expression has been detected using microarray technology comprising more than 4,000 normal and neoplastic tissue samples including 79 different tumor categories. Validation of HOXD13 expression has been performed, at mRNA level, for selected tumor types. Significant differences are detectable between specific normal tissues and corresponding tumor types with the majority of cancers showing an increase in HOXD13 expression (16.1% normal vs. 57.7% cancers). In contrast, pancreas and stomach tumor subtypes display the opposite trend. Interestingly, detection of the HOXD13 homeoprotein in pancreas-tissue microarrays shows that its negative expression has a significant and adverse effect on the prognosis of patients with pancreatic cancer independent of the T or N stage at the time of diagnosis. Our study provides, for the first time, an overview of a HOX protein expression in a large series of normal and neoplastic tissue types, identifies pancreatic cancer as one of the most affected by the HOXD13 hoemoprotein and underlines the way homeoproteins can be associated to human cancerogenesis

Rabies screen reveals GPe control of cocaine-triggered plasticity.

Identification of neural circuit changes that contribute to behavioural plasticity has routinely been conducted on candidate circuits that were preselected on the basis of previous results. Here we present an unbiased method for identifying experience-triggered circuit-level changes in neuronal ensembles in mice. Using rabies virus monosynaptic tracing, we mapped cocaine-induced global changes in inputs onto neurons in the ventral tegmental area. Cocaine increased rabies-labelled inputs from the globus pallidus externus (GPe), a basal ganglia nucleus not previously known to participate in behavioural plasticity triggered by drugs of abuse. We demonstrated that cocaine increased GPe neuron activity, which accounted for the increase in GPe labelling. Inhibition of GPe activity revealed that it contributes to two forms of cocaine-triggered behavioural plasticity, at least in part by disinhibiting dopamine neurons in the ventral tegmental area. These results suggest that rabies-based unbiased screening of changes in input populations can identify previously unappreciated circuit elements that critically support behavioural adaptations

Modelling opinion formation by means of kinetic equations

In this chapter, we review some mechanisms of opinion dynamics that can be modelled by kinetic equations. Beside the sociological phenomenon of compromise, naturally linked to collisional operators of Boltzmann kind, many other aspects, already mentioned in the sociophysical literature or no, can enter in this framework. While describing some contributions appeared in the literature, we enlighten some mathematical tools of kinetic theory that can be useful in the context of sociophysics