Interaction paths promote module integration and network-level robustness of spliceosome to cascading effects

CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQFUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESPThe functionality of distinct types of protein networks depends on the patterns of protein-protein interactions. A problem to solve is understanding the fragility of protein networks to predict system malfunctioning due to mutations and other errors. Spec8111CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQFUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESPCONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQFUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESPsem informação2017/08406-7, 2017/06994-9We thank Ana Paula Assis, Pâmela C. Santana and Leandro Giacobelli for helpful comments. PRG was supported by CNPq and FAPESP (2017/08406-7). PPC was supported by FAPESP (2017/06994-9). MC was supported by a PMP/BS postdoctoral fellowship (UFPR/UNIVALI 4

Thermal fluctuations of a quantized massive scalar field in Rindler background

Thermal fluctuations for a massive scalar field in the Rindler wedge are obtained by applying the point-splitting procedure to the zero temperature Feynman propagator in a conical spacetime. Renormalization is implemented by removing the zero temperature contribution. It is shown that for a field of non vanishing mass the thermal fluctuations, when expressed in terms of the local temperature, do not have Minkowski form. As a by product, Minkowski vacuum fluctuations seen by an uniformly accelerated observer are determined and confronted with the literature.Comment: 10 pages; Latex fil

Nestedness across biological scales

Biological networks pervade nature. They describe systems throughout all levels of biological organization, from molecules regulating metabolism to species interactions that shape ecosystem dynamics. The network thinking revealed recurrent organizational patterns in complex biological systems, such as the formation of semi-independent groups of connected elements (modularity) and non-random distributions of interactions among elements. Other structural patterns, such as nestedness, have been primarily assessed in ecological networks formed by two non-overlapping sets of elements; information on its occurrence on other levels of organization is lacking. Nestedness occurs when interactions of less connected elements form proper subsets of the interactions of more connected elements. Only recently these properties began to be appreciated in one-mode networks (where all elements can interact) which describe a much wider variety of biological phenomena. Here, we compute nestedness in a diverse collection of one-mode networked systems from six different levels of biological organization depicting gene and protein interactions, complex phenotypes, animal societies, metapopulations, food webs and vertebrate metacommunities. Our findings suggest that nestedness emerge independently of interaction type or biological scale and reveal that disparate systems can share nested organization features characterized by inclusive subsets of interacting elements with decreasing connectedness. We primarily explore the implications of a nested structure for each of these studied systems, then theorize on how nested networks are assembled. We hypothesize that nestedness emerges across scales due to processes that, although system-dependent, may share a general.Facultad de Ciencias Naturales y Muse

Nestedness across biological scales

Biological networks pervade nature. They describe systems throughout all levels of biological organization, from molecules regulating metabolism to species interactions that shape ecosystem dynamics. The network thinking revealed recurrent organizational patterns in complex biological systems, such as the formation of semi-independent groups of connected elements (modularity) and non-random distributions of interactions among elements. Other structural patterns, such as nestedness, have been primarily assessed in ecological networks formed by two non-overlapping sets of elements; information on its occurrence on other levels of organization is lacking. Nestedness occurs when interactions of less connected elements form proper subsets of the interactions of more connected elements. Only recently these properties began to be appreciated in one-mode networks (where all elements can interact) which describe a much wider variety of biological phenomena. Here, we compute nestedness in a diverse collection of one-mode networked systems from six different levels of biological organization depicting gene and protein interactions, complex phenotypes, animal societies, metapopulations, food webs and vertebrate metacommunities. Our findings suggest that nestedness emerge independently of interaction type or biological scale and reveal that disparate systems can share nested organization features characterized by inclusive subsets of interacting elements with decreasing connectedness. We primarily explore the implications of a nested structure for each of these studied systems, then theorize on how nested networks are assembled. We hypothesize that nestedness emerges across scales due to processes that, although system-dependent, may share a general.Facultad de Ciencias Naturales y Muse

Growth of Long Range Forward-Backward Multiplicity Correlations with Centrality in Au+Au Collisions at sNN\sqrt{s_{NN}} = 200 GeV

Forward-backward multiplicity correlation strengths have been measured with the STAR detector for Au+Au and $\textit{p+p}$ collisions at $\sqrt{s_{NN}}$ = 200 GeV. Strong short and long range correlations (LRC) are seen in central Au+Au collisions. The magnitude of these correlations decrease with decreasing centrality until only short range correlations are observed in peripheral Au+Au collisions. Both the Dual Parton Model (DPM) and the Color Glass Condensate (CGC) predict the existence of the long range correlations. In the DPM the fluctuation in the number of elementary (parton) inelastic collisions produces the LRC. In the CGC longitudinal color flux tubes generate the LRC. The data is in qualitative agreement with the predictions from the DPM and indicates the presence of multiple parton interactions.Comment: 6 pages, 3 figures The abstract has been slightly modifie

K/pi Fluctuations at Relativistic Energies

We report results for $K/\pi$ fluctuations from Au+Au collisions at $\sqrt{s_{NN}}$ = 19.6, 62.4, 130, and 200 GeV using the STAR detector at the Relativistic Heavy Ion Collider. Our results for $K/\pi$ fluctuations in central collisions show little dependence on the incident energies studied and are on the same order as results observed by NA49 at the Super Proton Synchrotron in central Pb+Pb collisions at $\sqrt{s_{NN}}$ = 12.3 and 17.3 GeV. We also report results for the collision centrality dependence of $K/\pi$ fluctuations as well as results for $K^{+}/\pi^{+}$, $K^{-}/\pi^{-}$, $K^{+}/\pi^{-}$, and $K^{-}/\pi^{+}$ fluctuations. We observe that the $K/\pi$ fluctuations scale with the multiplicity density, $dN/d\eta$, rather than the number of participating nucleons.Comment: 6 pages, 4 figure

Scaling of nestedness in complex networks

Nestedness characterizes the linkage pattern of networked systems, indicating the likelihood that a node is linked to the nodes linked to the nodes with larger degrees than it. Networks of mutualistic relationship between distinct groups of species in ecological communities exhibit such nestedness, which is known to support the network robustness. Despite such importance, quantitative characteristics of nestedness is little understood. Here we take graph-theoretic approach to derive the scaling properties of nestedness in various model networks. Our results show how the heterogeneous connectivity patterns enhance nestedness. Also we find that the nestedness of bipartite networks depend sensitively on the fraction of different types of nodes, causing nestedness to scale differently for nodes of different types.Comment: 9 pages, 4 figures, final versio

Effects of external nutrient sources and extreme weather events on the nutrient budget of a Southern European coastal lagoon

The seasonal and annual nitrogen (N), phosphorus (P), and carbon (C) budgets of the mesotidal Ria Formosa lagoon, southern Portugal, were estimated to reveal the main inputs and outputs, the seasonal patterns, and how they may influence the ecological functioning of the system. The effects of extreme weather events such as long-lasting strong winds causing upwelling and strong rainfall were assessed. External nutrient inputs were quantified; ocean exchange was assessed in 24-h sampling campaigns, and final calculations were made using a hydrodynamic model of the lagoon. Rain and stream inputs were the main freshwater sources to the lagoon. However, wastewater treatment plant and groundwater discharges dominated nutrient input, together accounting for 98, 96, and 88 % of total C, N, and P input, respectively. Organic matter and nutrients were continuously exported to the ocean. This pattern was reversed following extreme events, such as strong winds in early summer that caused upwelling and after a period of heavy rainfall in late autumn. A principal component analysis (PCA) revealed that ammonium and organic N and C exchange were positively associated with temperature as opposed to pH and nitrate. These variables reflected mostly the benthic lagoon metabolism, whereas particulate P exchange was correlated to Chl a, indicating that this was more related to phytoplankton dynamics. The increase of stochastic events, as expected in climate change scenarios, may have strong effects on the ecological functioning of coastal lagoons, altering the C and nutrient budgets.Portuguese Science and Technology Foundation (FCT) [POCI/MAR/58427/2004, PPCDT/MAR/58427/2004]; Portuguese Science and Technology Foundation (FCT

Biological Function and Molecular Mapping of M Antigen in Yeast Phase of Histoplasma capsulatum

Histoplasmosis, due to the intracellular fungus Histoplasma capsulatum, can be diagnosed by demonstrating the presence of antibodies specific to the immunodominant M antigen. However, the role of this protein in the pathogenesis of histoplasmosis has not been elucidated. We sought to structurally and immunologically characterize the protein, determine yeast cell surface expression, and confirm catalase activity. A 3D-rendering of the M antigen by homology modeling revealed that the structures and domains closely resemble characterized fungal catalases. We generated monoclonal antibodies (mAbs) to the protein and determined that the M antigen is present on the yeast cell surface and in cell wall/cell membrane preparations. Similarly, we found that the majority of catalase activity was in extracts containing fungal surface antigens and that the M antigen is not significantly secreted by live yeast cells. The mAbs also identified unique epitopes on the M antigen. The localization of the M antigen to the cell surface of H. capsulatum yeast and the characterization of the protein's major epitopes have important implications since it demonstrates that although the protein may participate in protecting the fungus against oxidative stress it is also accessible to host immune cells and antibody