Leishmania-Specific Surface Antigens Show Sub-Genus Sequence Variation and Immune Recognition

Background: A family of hydrophilic acylated surface (HASP) proteins, containing extensive and variant amino acid repeats, is expressed at the plasma membrane in infective extracellular (metacyclic) and intracellular (amastigote) stages of Old World Leishmania species. While HASPs are antigenic in the host and can induce protective immune responses, the biological functions of these Leishmania-specific proteins remain unresolved. Previous genome analysis has suggested that parasites of the sub-genus Leishmania (Viannia) have lost HASP genes from their genomes. Methods/Principal Findings: We have used molecular and cellular methods to analyse HASP expression in New World Leishmania mexicana complex species and show that, unlike in L. major, these proteins are expressed predominantly following differentiation into amastigotes within macrophages. Further genome analysis has revealed that the L. (Viannia) species, L. (V.) braziliensis, does express HASP-like proteins of low amino acid similarity but with similar biochemical characteristics, from genes present on a region of chromosome 23 that is syntenic with the HASP/SHERP locus in Old World Leishmania species and the L. (L.) mexicana complex. A related gene is also present in Leptomonas seymouri and this may represent the ancestral copy of these Leishmania-genus specific sequences. The L. braziliensis HASP-like proteins (named the orthologous (o) HASPs) are predominantly expressed on the plasma membrane in amastigotes and are recognised by immune sera taken from 4 out of 6 leishmaniasis patients tested in an endemic region of Brazil. Analysis of the repetitive domains of the oHASPs has shown considerable genetic variation in parasite isolates taken from the same patients, suggesting that antigenic change may play a role in immune recognition of this protein family. Conclusions/Significance: These findings confirm that antigenic hydrophilic acylated proteins are expressed from genes in the same chromosomal region in species across the genus Leishmania. These proteins are surface-exposed on amastigotes (although L. (L.) major parasites also express HASPB on the metacyclic plasma membrane). The central repetitive domains of the HASPs are highly variant in their amino acid sequences, both within and between species, consistent with a role in immune recognition in the host.

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.

Generalized connectivity between any two nodes in a complex network

This article focuses on the identification of the number of paths with different lengths between pairs of nodes in complex networks and how these paths can be used for characterization of topological properties of theoretical and real-world complex networks. This analysis revealed that the number of paths can provide a better discrimination of network models than traditional network measurements. In addition, the analysis of real-world networks suggests that the long-range connectivity tends to be limited in these networks and may be strongly related to network growth and organization.

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.

Electron collisions with the CH(2)O-H(2)O complex

We report cross sections for elastic collisions of low-energy electrons with the CH(2)O-H(2)O complex. We employed the Schwinger multichannel method with pseudopotentials in the static-exchange and in the static-exchange-polarization approximations for energies from 0.1 to 20 eV. We considered four different hydrogen-bonded structures for the complex that were generated by classical Monte Carlo simulations. Our aim is to investigate the effect of the water molecule on the pi* shape resonance of formaldehyde. Previous studies reported a pi* shape resonance for CH(2)O at around 1 eV. The resonance positions of the complexes appear at lower energies in all cases due to the mutual polarization between the two molecules. This indicates that the presence of water may favor dissociation by electron impact and may lead to an important effect on strand breaking in wet DNA by electron impact.

Particle-species dependent modification of jet-induced correlations in Au plus Au collisions at root s(NN)=200 GeV

Measurements in Au + Au collisions at root s(NN) = 200 GeV of jet correlations for a trigger hadron at intermediate transverse momentum (p(T,trig)) with associated mesons or baryons at lower p(T,assoc) indicate strong modification of the away-side jet. The ratio of jet-associated baryons to mesons increases with centrality and p(T,assoc). For the most central collisions, the ratio is similar to that for inclusive measurements. This trend is incompatible with in-vacuum fragmentation but could be due to jetlike contributions from correlated soft partons, which recombine upon hadronization.

Time correlation function in systems with two coexisting biological species

We study a stochastic lattice model describing the dynamics of coexistence of two interacting biological species. The model comprehends the local processes of birth, death, and diffusion of individuals of each species and is grounded on interaction of the predator-prey type. The species coexistence can be of two types: With self-sustained coupled time oscillations of population densities and without oscillations. We perform numerical simulations of the model on a square lattice and analyze the temporal behavior of each species by computing the time correlation functions as well as the spectral densities. This analysis provides an appropriate characterization of the different types of coexistence. It is also used to examine linked population cycles in nature and in experiment.

Experimental observation of a complex periodic window

The existence of a special periodic window in the two-dimensional parameter space of an experimental Chua's circuit is reported. One of the main reasons that makes such a window special is that the observation of one implies that other similar periodic windows must exist for other parameter values. However, such a window has never been experimentally observed, since its size in parameter space decreases exponentially with the period of the periodic attractor. This property imposes clear limitations for its experimental detection.

Jensen inequalities for tunneling probabilities in complex systems

The Jensen theorem is used to derive inequalities for semiclassical tunneling probabilities for systems involving several degrees of freedom. These Jensen inequalities are used to discuss several aspects of sub-barrier heavy-ion fusion reactions. The inequality hinges on general convexity properties of the tunneling coefficient calculated with the classical action in the classically forbidden region.

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.

Iridium(III)-surfactant complex immobilized in mesoporous silica via templated synthesis: a new route to optical materials

In this work we report the preparation of a new blue-emitting material based on the templated synthesis of mesoporous silica (MCM-41) using micellar solutions of the newly synthesized monocationic metallosurfactant complex bis[1-benzyl-4-(2,4-difluorophenyl)-1H-1,2,3-triazole](4,4'-diheptadecyl-2,2'- bipyridine)-iridium(III) chloride in hexadecyl-trimethyl-ammonium bromide (CTAB). Under ambient conditions, significant increases in excited state lifetime and quantum yield values (up to 45%), were obtained for the solid materials in comparison to the corresponding micellar solutions. Solid state (1)H and (19)F NMR spectroscopies were successfully employed for quantifying the luminophore content in terms of Ir-surfactant to CTAB and Ir-surfactant to silica ratios.

Purine nucleoside phosphorylase from Schistosoma mansoni in complex with ribose-1-phosphate

Schistosomes are blood flukes which cause schistosomiasis, a disease affecting approximately 200 million people worldwide. Along with several other important human parasites including trypanosomes and Plasmodium, schistosomes lack the de novo pathway for purine synthesis and depend exclusively on the salvage pathway for their purine requirements, making the latter an attractive target for drug development. Part of the pathway involves the conversion of inosine (or guanosine) into hypoxanthine (or guanine) together with ribose-1-phosphate (R1P) or vice versa. This inter-conversion is undertaken by the enzyme purine nucleoside phosphorylase (PNP) which has been used as the basis for the development of novel anti-malarials, conceptually validating this approach. It has been suggested that, during the reverse reaction, R1P binding to the enzyme would occur only as a consequence of conformational changes induced by hypoxanthine, thus making a binary PNP-R1P complex unlikely. Contradictory to this statement, a crystal structure of just such a binary complex involving the Schistosoma mansoni enzyme has been successfully obtained. The ligand shows an intricate hydrogen-bonding network in the phosphate and ribose binding sites and adds a further chapter to our knowledge which could be of value in the future development of selective inhibitors.

Adenosine binding to low-molecular-weight purine nucleoside phosphorylase: the structural basis for recognition based on its complex with the enzyme from Schistosoma mansoni

Schistosomes are unable to synthesize purines de novo and depend exclusively on the salvage pathway for their purine requirements. It has been suggested that blockage of this pathway could lead to parasite death. The enzyme purine nucleoside phosphorylase (PNP) is one of its key components and molecules designed to inhibit the low-molecular-weight (LMW) PNPs, which include both the human and schistosome enzymes, are typically analogues of the natural substrates inosine and guanosine. Here, it is shown that adenosine both binds to Schistosoma mansoni PNP and behaves as a weak micromolar inhibitor of inosine phosphorolysis. Furthermore, the first crystal structures of complexes of an LMW PNP with adenosine and adenine are reported, together with those with inosine and hypoxanthine. These are used to propose a structural explanation for the selective binding of adenosine to some LMW PNPs but not to others. The results indicate that transition-state analogues based on adenosine or other 6-amino nucleosides should not be discounted as potential starting points for alternative inhibitors.

Gene Expression Complex Networks: Synthesis, Identification, and Analysis

Thanks to recent advances in molecular biology, allied to an ever increasing amount of experimental data, the functional state of thousands of genes can now be extracted simultaneously by using methods such as cDNA microarrays and RNA-Seq. Particularly important related investigations are the modeling and identification of gene regulatory networks from expression data sets. Such a knowledge is fundamental for many applications, such as disease treatment, therapeutic intervention strategies and drugs design, as well as for planning high-throughput new experiments. Methods have been developed for gene networks modeling and identification from expression profiles. However, an important open problem regards how to validate such approaches and its results. This work presents an objective approach for validation of gene network modeling and identification which comprises the following three main aspects: (1) Artificial Gene Networks (AGNs) model generation through theoretical models of complex networks, which is used to simulate temporal expression data; (2) a computational method for gene network identification from the simulated data, which is founded on a feature selection approach where a target gene is fixed and the expression profile is observed for all other genes in order to identify a relevant subset of predictors; and (3) validation of the identified AGN-based network through comparison with the original network. The proposed framework allows several types of AGNs to be generated and used in order to simulate temporal expression data. The results of the network identification method can then be compared to the original network in order to estimate its properties and accuracy. Some of the most important theoretical models of complex networks have been assessed: the uniformly-random Erdos-Renyi (ER), the small-world Watts-Strogatz (WS), the scale-free Barabasi-Albert (BA), and geographical networks (GG). The experimental results indicate that the inference method was sensitive to average degree k variation, decreasing its network recovery rate with the increase of k. The signal size was important for the inference method to get better accuracy in the network identification rate, presenting very good results with small expression profiles. However, the adopted inference method was not sensible to recognize distinct structures of interaction among genes, presenting a similar behavior when applied to different network topologies. In summary, the proposed framework, though simple, was adequate for the validation of the inferred networks by identifying some properties of the evaluated method, which can be extended to other inference methods.