The entropy of randomized network ensembles

Randomized network ensembles are the null models of real networks and are extensivelly used to compare a real system to a null hypothesis. In this paper we study network ensembles with the same degree distribution, the same degree-correlations or the same community structure of any given real network. We characterize these randomized network ensembles by their entropy, i.e. the normalized logarithm of the total number of networks which are part of these ensembles. We estimate the entropy of randomized ensembles starting from a large set of real directed and undirected networks. We propose entropy as an indicator to assess the role of each structural feature in a given real network.We observe that the ensembles with fixed scale-free degree distribution have smaller entropy than the ensembles with homogeneous degree distribution indicating a higher level of order in scale-free networks.Comment: (6 pages,1 figure,2 tables

Structural determinants of Rab11 activation by the guanine nucleotide exchange factor SH3BP5

Rab11 GTPases are involved in various cellular processes but their activation by guanine nucleotide exchange factors (GEFs) is not fully understood. Here, the authors present a structural and biochemical analysis of Rab11 bound to the GEF SH3BP5, providing insights how Rab-GEF specificity is achieved

Exploring the Hard X-/soft gamma-ray Continuum Spectra with Laue Lenses

The history of X-ray astronomy has shown that any advancement in our knowledge of the X-ray sky is strictly related to an increase in instrument sensitivity. At energies above 60 keV, there are interesting prospects for greatly improving the limiting sensitivity of the current generation of direct viewing telescopes (with or without coded masks), offered by the use of Laue lenses. We will discuss below the development status of a Hard X-Ray focusing Telescope (HAXTEL) based on Laue lenses with a broad bandpass (from 60 to 600 keV) for the study of the X-ray continuum of celestial sources. We show two examplesof multi-lens configurations with expected sensitivity orders of magnitude better ($\sim 1 \times 10^{-8}$ photons cm$^{-2}$ s$^{-1}$ keV$^{-1}$ at 200 keV) than that achieved so far. With this unprecedented sensitivity, very exciting astrophysical prospects are opened.Comment: 4 pages, 10 figures, to be published in the Proc. of the 39th ESLAB Symosium, 19-21 April 200

Reactive oxygen species and cellular interactions between Mycosphaerella fijiensis and banana.

Globally, the banana plant (Musa spp) is the fourth most important crop after rice, wheat and corn (based on production in tons). It is cultivated in more than 100 tropical and subtropical countries, mainly by small producers and is a fundamental food source for millions of people. Black leaf streak disease (BLSD), caused by Mycosphaerella fijiensis Morelet (sexual phase) or Paracercospora fijiensis (Morelet) Deighton (asexual phase), is the main disease affecting the world's banana culture. This disease has a wide geographical distribution accounting for losses exceeding 50% of global banana production. We conducted a comparative histocytological study on the kinetics of the infection process using three banana genotypes with phenotypes that differ in resistance to BLSD: Grand Naine (Susceptible), Pisang Madu (Partially Resistant) and Calcutta 4 (Resistant). Experiments were conducted under controlled conditions with the objective of characterizing the cellular interaction processes between M. fijiensis and Musa acuminata. Conidia germination occurred 24 hours after inoculation. Germination rates were high (97%) and there were no significant differences between the three genotypes (P>0.147). The Peroxidase enzyme and H2O2 were associated with a hypersensitivity-like reaction in the resistant genotype Calcutta 4, indicating a possible role of the enzyme or its product as defense mechanisms against M. fijiensis in banana plants

Rhythmogenic neuronal networks, pacemakers, and k-cores

Neuronal networks are controlled by a combination of the dynamics of individual neurons and the connectivity of the network that links them together. We study a minimal model of the preBotzinger complex, a small neuronal network that controls the breathing rhythm of mammals through periodic firing bursts. We show that the properties of a such a randomly connected network of identical excitatory neurons are fundamentally different from those of uniformly connected neuronal networks as described by mean-field theory. We show that (i) the connectivity properties of the networks determines the location of emergent pacemakers that trigger the firing bursts and (ii) that the collective desensitization that terminates the firing bursts is determined again by the network connectivity, through k-core clusters of neurons.Comment: 4+ pages, 4 figures, submitted to Phys. Rev. Let

The Huygens Atmospheric Structure Instrument (HASI): Expected Results at Titan and Performance Verification in Terrestrial Atmosphere

The Huygens ASI is a multi-sensor package resulting from an international cooperation, it has been designed to measure the physical quantities characterizing Titan's atmosphere during the Huygens probe mission. On 14th January, 2005, HASI will measure acceleration, pressure, temperature and electrical properties all along the Huygens probe descent on Titan in order to study Titan s atmospheric structure, dynamics and electric properties. Monitoring axial and normal accelerations and providing direct pressure and temperature measurements during the descent, HASI will mainly contribute to the Huygens probe entry and trajectory reconstruction. In order to simulate the Huygens probe descent and verify HASI sensors performance in terrestrial environment, stratospheric balloon flight experiment campaigns have been performed, in collaboration with the Italian Space Agency (ASI). The results of flight experiments have allowed to determine the atmospheric vertical profiles and to obtain a set of data for the analysis of probe trajectory and attitude reconstruction

Critical phenomena in complex networks

The combination of the compactness of networks, featuring small diameters, and their complex architectures results in a variety of critical effects dramatically different from those in cooperative systems on lattices. In the last few years, researchers have made important steps toward understanding the qualitatively new critical phenomena in complex networks. We review the results, concepts, and methods of this rapidly developing field. Here we mostly consider two closely related classes of these critical phenomena, namely structural phase transitions in the network architectures and transitions in cooperative models on networks as substrates. We also discuss systems where a network and interacting agents on it influence each other. We overview a wide range of critical phenomena in equilibrium and growing networks including the birth of the giant connected component, percolation, k-core percolation, phenomena near epidemic thresholds, condensation transitions, critical phenomena in spin models placed on networks, synchronization, and self-organized criticality effects in interacting systems on networks. We also discuss strong finite size effects in these systems and highlight open problems and perspectives.Comment: Review article, 79 pages, 43 figures, 1 table, 508 references, extende

Organization of modular networks

We examine the global organization of heterogeneous equilibrium networks consisting of a number of well distinguished interconnected parts--``communities'' or modules. We develop an analytical approach allowing us to obtain the statistics of connected components and an intervertex distance distribution in these modular networks, and to describe their global organization and structure. In particular, we study the evolution of the intervertex distance distribution with an increasing number of interlinks connecting two infinitely large uncorrelated networks. We demonstrate that even a relatively small number of shortcuts unite the networks into one. In more precise terms, if the number of the interlinks is any finite fraction of the total number of connections, then the intervertex distance distribution approaches a delta-function peaked form, and so the network is united.Comment: 9 pages, 3 figure

Mitotic Recombination and Rapid Genome Evolution in the Invasive Forest Pathogen Phytophthora ramorum

Invasive alien species often have reduced genetic diversity and must adapt to new environments. Given the success of many invasions, this is sometimes called the genetic paradox of invasion. Phytophthora ramorum is invasive, limited to asexual reproduction within four lineages, and presumed clonal. It is responsible for sudden oak death in the United States, sudden larch death in Europe, and ramorum blight in North America and Europe. We sequenced the genomes of 107 isolates to determine how this pathogen can overcome the invasion paradox. Mitotic recombination (MR) associated with transposons and low gene density has generated runs of homozygosity (ROH) affecting 2,698 genes, resulting in novel genotypic diversity within the lineages. One ROH enriched in effectors was fixed in the NA1 lineage. An independent ROH affected the same scaffold in the EU1 lineage, suggesting an MR hot spot and a selection target. Differences in host infection between EU1 isolates with and without the ROH suggest that they may differ in aggressiveness. Non-core regions (not shared by all lineages) had signatures of accelerated evolution and were enriched in putative pathogenicity genes and transposons. There was a striking pattern of gene loss, including all effectors, in the non-core EU2 genome. Positive selection was observed in 8.0% of RxLR and 18.8% of Crinkler effector genes compared with 0.9% of the core eukaryotic gene set. We conclude that the P. ramorum lineages are diverging via a rapidly evolving non-core genome and that the invasive asexual lineages are not clonal, but display genotypic diversity caused by MR

Robust estimation of microbial diversity in theory and in practice

Quantifying diversity is of central importance for the study of structure, function and evolution of microbial communities. The estimation of microbial diversity has received renewed attention with the advent of large-scale metagenomic studies. Here, we consider what the diversity observed in a sample tells us about the diversity of the community being sampled. First, we argue that one cannot reliably estimate the absolute and relative number of microbial species present in a community without making unsupported assumptions about species abundance distributions. The reason for this is that sample data do not contain information about the number of rare species in the tail of species abundance distributions. We illustrate the difficulty in comparing species richness estimates by applying Chao's estimator of species richness to a set of in silico communities: they are ranked incorrectly in the presence of large numbers of rare species. Next, we extend our analysis to a general family of diversity metrics ("Hill diversities"), and construct lower and upper estimates of diversity values consistent with the sample data. The theory generalizes Chao's estimator, which we retrieve as the lower estimate of species richness. We show that Shannon and Simpson diversity can be robustly estimated for the in silico communities. We analyze nine metagenomic data sets from a wide range of environments, and show that our findings are relevant for empirically-sampled communities. Hence, we recommend the use of Shannon and Simpson diversity rather than species richness in efforts to quantify and compare microbial diversity.Comment: To be published in The ISME Journal. Main text: 16 pages, 5 figures. Supplement: 16 pages, 4 figure