EVOLUTION OF FLORAL MORPHOLOGY AND POLLINATION SYSTEM IN BIGNONIEAE (BIGNONIACEAE)

The radiation of angiosperms is associated with shifts among pollination modes that are thought to have driven the diversification of floral forms. However, the exact sequence of evolutionary events that led to such great diversity in floral traits is unknown for most plant groups. Here, we characterize the patterns of evolution of individual floral traits and overall floral morphologies in the tribe Bignonieae (Bignoniaceae). We identified 12 discrete traits that are associated with seven floral types previously described for the group and used a penalized likelihood tree of the tribe to reconstruct the ancestral states of those traits at all nodes of the phylogeny of Bignonieae. In addition, evolutionary correlations among traits were conducted using a maximum likelihood approach to test whether the evolution of individual floral traits followed the correlated patterns of evolution expected under the ""pollination syndrome"" concept. The ancestral Bignonieae flower presented an Anemopaegma-type morphology, which was followed by several parallel shifts in floral morphologies. Those shifts occurred through intermediate stages resulting in mixed floral morphologies as well as directly from the Anemopaegma-type morphology to other floral types. Positive and negative evolutionary correlations among traits fit patterns expected under the pollination syndrome perspective, suggesting that interactions between Bignonieae flowers and pollinators likely played important roles in the diversification of the group as a whole.

Tamoxifen Is Effective in the Treatment of Leishmania amazonensis Infections in Mice

Background: Chemotherapy is still a critical issue in the management of leishmaniasis. Until recently, pentavalent antimonials, amphotericin B or pentamidine compounded the classical arsenal of treatment. All these drugs are toxic and have to be administered by the parenteral route. Tamoxifen has been used as an antiestrogen in the treatment and prevention of breast cancer for many years. Its safety and pharmacological profiles are well established in humans. We have shown that tamoxifen is active as an antileishmanial compound in vitro, and in this paper we analyzed the efficacy of tamoxifen for the treatment of mice infected with Leishmania amazonensis, an etiological agent of localized cutaneous leishmaniasis and the main cause of diffuse cutaneous leishmaniasis in South America. Methodology/Principal Findings: BALB/c mice were infected with L. amazonensis promastigotes. Five weeks post-infection, treatment with 15 daily intraperitoneal injections of 20 mg/kg tamoxifen was administered. Lesion and ulcer sizes were recorded and parasite burden quantified by limiting dilution. A significant decrease in lesion size and ulcer development was noted in mice treated with tamoxifen as compared to control untreated animals. Parasite burden in the inoculation site at the end of treatment was reduced from 10(8.5 +/- 0.7) in control untreated animals to 10(5.0 +/- 0.0) in tamoxifen-treated mice. Parasite load was also reduced in the draining lymph nodes. The reduction in parasite number was sustained: 6 weeks after the end of treatment, 10(15.5 +/- 0.5) parasites were quantified from untreated animals, as opposed to 10(5.1 +/- 0.1) parasites detected in treated mice. Conclusions/Significance: Treatment of BALB/c mice infected with L. amazonensis for 15 days with tamoxifen resulted in significant decrease in lesion size and parasite burden. BALB/c mice infected with L. amazonensis represents a model of extreme susceptibility, and the striking and sustained reduction in the number of parasites in treated animals supports the proposal of further testing of this drug in other models of leishmaniasis.

Characterization of subgraph relationships and distribution in complex networks

A network can be analyzed at different topological scales, ranging from single nodes to motifs, communities, up to the complete structure. We propose a novel approach which extends from single nodes to the whole network level by considering non-overlapping subgraphs (i.e. connected components) and their interrelationships and distribution through the network. Though such subgraphs can be completely general, our methodology focuses on the cases in which the nodes of these subgraphs share some special feature, such as being critical for the proper operation of the network. The methodology of subgraph characterization involves two main aspects: (i) the generation of histograms of subgraph sizes and distances between subgraphs and (ii) a merging algorithm, developed to assess the relevance of nodes outside subgraphs by progressively merging subgraphs until the whole network is covered. The latter procedure complements the histograms by taking into account the nodes lying between subgraphs, as well as the relevance of these nodes to the overall subgraph interconnectivity. Experiments were carried out using four types of network models and five instances of real-world networks, in order to illustrate how subgraph characterization can help complementing complex network-based studies.

Particle competition for complex network community detection

In many real situations, randomness is considered to be uncertainty or even confusion which impedes human beings from making a correct decision. Here we study the combined role of randomness and determinism in particle dynamics for complex network community detection. In the proposed model, particles walk in the network and compete with each other in such a way that each of them tries to possess as many nodes as possible. Moreover, we introduce a rule to adjust the level of randomness of particle walking in the network, and we have found that a portion of randomness can largely improve the community detection rate. Computer simulations show that the model has good community detection performance and at the same time presents low computational complexity. (C) 2008 American Institute of Physics.

Chain motifs: The tails and handles of complex networks

A great part of the interest in complex networks has been motivated by the presence of structured, frequently nonuniform, connectivity. Because diverse connectivity patterns tend to result in distinct network dynamics, and also because they provide the means to identify and classify several types of complex network, it becomes important to obtain meaningful measurements of the local network topology. In addition to traditional features such as the node degree, clustering coefficient, and shortest path, motifs have been introduced in the literature in order to provide complementary descriptions of the network connectivity. The current work proposes a different type of motif, namely, chains of nodes, that is, sequences of connected nodes with degree 2. These chains have been subdivided into cords, tails, rings, and handles, depending on the type of their extremities (e.g., open or connected). A theoretical analysis of the density of such motifs in random and scale-free networks is described, and an algorithm for identifying these motifs in general networks is presented. The potential of considering chains for network characterization has been illustrated with respect to five categories of real-world networks including 16 cases. Several interesting findings were obtained, including the fact that several chains were observed in real-world networks, especially the world wide web, books, and the power grid. The possibility of chains resulting from incompletely sampled networks is also investigated.

Free-standing urethane/urea elastomer films undoped and doped with ferro-nano-particles

We report on an experimental study of the structures presented by urethane/urea elastomeric films without and with ferromagnetic nanoparticles incorporated. The study is made by using the X-ray diffraction, nuclear magnetic resonance (NMR), optical, atomic and magnetic force (MFM) microscopy techniques, and mechanical assays. The structure of the elastomeric matrix is characterized by a distance of 0.46 nm between neighboring molecular segments, almost independent on the stretching applied. The shear casting performed in order to obtain the elastomeric films tends to orient the molecules parallel to the flow direction thus introducing anisotropy in the molecular network which is reflected on the values obtained for the orientational order parameter and its increase for the stretched films. In the case of nanoparticles-doped samples, the structure remains nearly unchanged although the local order parameter is clearly larger for the undoped films. NMR experiments evidence modifications in the molecular network local ordering. Micrometer size clusters were observed by MFM for even small concentration of magnetic particles.

Atomistic molecular dynamics study of interface formation: Al on poly(p-phenylene vinylene)

We model interface formation by metal deposition on the conjugated polymer poly-para-phenylene vinylene, studying direct aluminum and layered aluminum-calcium structures Al/PPV and Al/Ca/PPV. To do that we use classical molecular dynamics simulations, checked by ab initio density-functional theory calculations, for selected relevant configurations. We find that Al not only migrates easily into the film, with a strong charge transfer to the neighboring chains, but also promotes rearrangement of the polymer in the interfacial region to the hexagonal structure. On the other hand, our results indicate that a thin Ca layer is sufficient to protect the film and maintain a well-defined metal/polymer interface, and that also a thin Al capping layer may protect the whole from environmental degradation.

Communication structure of cortical networks

Large-scale cortical networks exhibit characteristic topological properties that shape communication between brain regions and global cortical dynamics. Analysis of complex networks allows the description of connectedness, distance, clustering, and centrality that reveal different aspects of how the network's nodes communicate. Here, we focus on a novel analysis of complex walks in a series of mammalian cortical networks that model potential dynamics of information flow between individual brain regions. We introduce two new measures called absorption and driftness. Absorption is the average length of random walks between any two nodes, and takes into account all paths that may diffuse activity throughout the network. Driftness is the ratio between absorption and the corresponding shortest path length. For a given node of the network, we also define four related measurements, namely in-and out-absorption as well as in-and out-driftness, as the averages of the corresponding measures from all nodes to that node, and from that node to all nodes, respectively. We find that the cat thalamo-cortical system incorporates features of two classic network topologies, Erdos-Renyi graphs with respect to in-absorption and in-driftness, and configuration models with respect to out-absorption and out-driftness. Moreover, taken together these four measures separate the network nodes based on broad functional roles (visual, auditory, somatomotor, and frontolimbic).

Automatic Network Fingerprinting through Single-Node Motifs

Complex networks have been characterised by their specific connectivity patterns (network motifs), but their building blocks can also be identified and described by node-motifs-a combination of local network features. One technique to identify single node-motifs has been presented by Costa et al. (L. D. F. Costa, F. A. Rodrigues, C. C. Hilgetag, and M. Kaiser, Europhys. Lett., 87, 1, 2009). Here, we first suggest improvements to the method including how its parameters can be determined automatically. Such automatic routines make high-throughput studies of many networks feasible. Second, the new routines are validated in different network-series. Third, we provide an example of how the method can be used to analyse network time-series. In conclusion, we provide a robust method for systematically discovering and classifying characteristic nodes of a network. In contrast to classical motif analysis, our approach can identify individual components (here: nodes) that are specific to a network. Such special nodes, as hubs before, might be found to play critical roles in real-world networks.

Border detection in complex networks

One important issue implied by the finite nature of real-world networks regards the identification of their more external (border) and internal nodes. The present work proposes a formal and objective definition of these properties, founded on the recently introduced concept of node diversity. It is shown that this feature does not exhibit any relevant correlation with several well-established complex networks measurements. A methodology for the identification of the borders of complex networks is described and illustrated with respect to theoretical (geographical and knitted networks) as well as real-world networks (urban and word association networks), yielding interesting results and insights in both cases.

Sublattice magnetism in sigma-phase Fe(100-x)Vx (x=34.4, 39.9, and 47.9) studied via zero-field (51)V NMR

The successful measurements of a sublattice magnetism with (51)V NMR techniques in the sigma-phase Fe(100-x)V(x) alloys with x=34.4, 39.9, and 47.9 are reported. Vanadium atoms, which were revealed to be present on all five crystallographic sites, are found to be under the action of the hyperfine magnetic fields produced by the neighboring Fe atoms, which allow the observation of (51)V NMR signals. Their nuclear magnetic properties are characteristic of a given site, which strongly depend on the composition. Site A exhibits the strongest magnetism while site D is the weakest. The estimated average magnetic moment per V atom decreases from 0.36 mu(B) for x=34.4 to 0.20 mu(B) for x=47.9. The magnetism revealed at V atoms is linearly correlated with the magnetic moment of Fe atoms, which implies that the former is induced by the latter.

TESTING STATISTICAL HYPOTHESIS ON RANDOM TREES AND APPLICATIONS TO THE PROTEIN CLASSIFICATION PROBLEM

Efficient automatic protein classification is of central importance in genomic annotation. As an independent way to check the reliability of the classification, we propose a statistical approach to test if two sets of protein domain sequences coming from two families of the Pfam database are significantly different. We model protein sequences as realizations of Variable Length Markov Chains (VLMC) and we use the context trees as a signature of each protein family. Our approach is based on a Kolmogorov-Smirnov-type goodness-of-fit test proposed by Balding et at. [Limit theorems for sequences of random trees (2008), DOI: 10.1007/s11749-008-0092-z]. The test statistic is a supremum over the space of trees of a function of the two samples; its computation grows, in principle, exponentially fast with the maximal number of nodes of the potential trees. We show how to transform this problem into a max-flow over a related graph which can be solved using a Ford-Fulkerson algorithm in polynomial time on that number. We apply the test to 10 randomly chosen protein domain families from the seed of Pfam-A database (high quality, manually curated families). The test shows that the distributions of context trees coming from different families are significantly different. We emphasize that this is a novel mathematical approach to validate the automatic clustering of sequences in any context. We also study the performance of the test via simulations on Galton-Watson related processes.

Spectroscopic, structural, and functional characterization of the alternative low-spin state of horse heart cytochrome c

The alternative low-spin states of Fe3+ and Fe2+ cytochrome c induced by SDS or AOT/hexane reverse micelles exhibited the heme group in a less rhombic symmetry and were characterized by electron paramagnetic resonance, UV-visible, CD, magnetic CD, fluorescence, and Raman resonance. Consistent with the replacement of Met 80 by another strong field ligand at the sixth heme iron coordination position, Fe3+ ALSScytc exhibited 1-nm Soret band blue shift and e enhancement accompanied by disappearance of the 695-nm charge transfer band. The Raman resonance, CD, and magnetic CD spectra of Fe3+ and Fe2+ ALSScytc exhibited significant changes suggestive of alterations in the heme iron microenvironment and conformation and should not be assigned to unfold because the Trp(59) fluorescence remained quenched by the neighboring heme group. ALSScytc was obtained with His(33) and His(26) carboxyethoxylated horse cytochrome c and with tuna cytochrome c (His(33) replaced by Asn) pointing out Lys(79) as the probable heme iron ligand. Fe3+ ALSScytc retained the capacity to cleave tert-butylhydroperoxide and to be reduced by dithiothreitol and diphenylacetaldehyde but not by ascorbate. Compatible with a more open heme crevice, ALSScytc exhibited a redox potential similar to 200 mV lower than the wild-type protein (1220 mV) and was more susceptible to the attack of free radicals.

O Itamaraty nos anos de chumbo: o Centro de Informações do Exterior (CIEX) e a repressão no Cone Sul (1966-1979)

Neste artigo, examina-se o funcionamento do Centro de Informações do Exterior (CIEX), órgão do Itamaraty e vinculado ao Serviço Nacional de Informações (SNI) que foi encarregado de espionar políticos e militantes contrários ao regime militar brasileiro que se exilaram nos países vizinhos. Trata-se de um estudo que visa a desvendar como agia um dos elos do sistema repressivo montado pela ditadura brasileira, que tinha um relativo grau de interação com as outras ditaduras militares da região do Cone Sul. O artigo demonstra que o Itamaraty colaborou intensamente com o regime militar brasileiro, inclusive com a repressão.

Multi-objective analysis of impacts of distributed generation placement on the operational characteristics of networks for distribution system planning

Recent advances in energy technology generation and new directions in electricity regulation have made distributed generation (DG) more widespread, with consequent significant impacts on the operational characteristics of distribution networks. For this reason, new methods for identifying such impacts are needed, together with research and development of new tools and resources to maintain and facilitate continued expansion towards DG. This paper presents a study aimed at determining appropriate DG sites for distribution systems. The main considerations which determine DG sites are also presented, together with an account of the advantages gained from correct DG placement. The paper intends to define some quantitative and qualitative parameters evaluated by Digsilent (R), GARP3 (R) and DSA-GD software. A multi-objective approach based on the Bellman-Zadeh algorithm and fuzzy logic is used to determine appropriate DG sites. The study also aims to find acceptable DG locations both for distribution system feeders, as well as for nodes inside a given feeder. (C) 2010 Elsevier Ltd. All rights reserved.