Understanding the genetic diversity, spatial genetic structure and mating system at the hierarchical levels of fruits and individuals of a continuous Theobroma cacao population from the Brazilian Amazon

Understanding the mating patterns of populations of tree species is a key component of ex situ genetic conservation. In this study, we analysed the genetic diversity, spatial genetic structure (SGS) and mating system at the hierarchical levels of fruits and individuals as well as pollen dispersal patterns in a continuous population of Theobroma cacao in Para State, Brazil. A total of 156 individuals in a 0.56 ha plot were mapped and genotyped for nine microsatellite loci. For the mating system analyses, 50 seeds were collected from nine seed trees by sampling five fruits per tree (10 seeds per fruit). Among the 156 individuals, 127 had unique multilocus genotypes, and the remaining were clones. The population was spatially aggregated; it demonstrated a significant SGS up to 15m that could be attributed primarily to the presence of clones. However, the short seed dispersal distance also contributed to this pattern. Population matings occurred mainly via outcrossing, but selfing was observed in some seed trees, which indicated the presence of individual variation for self-incompatibility. The matings were also correlated, especially within ((r) over cap (p(m)) = 0.607) rather than among the fruits ((r) over cap (p(m)) = 0.099), which suggested that a small number of pollen donors fertilised each fruit. The paternity analysis suggested a high proportion of pollen migration (61.3%), although within the plot, most of the pollen dispersal encompassed short distances (28m). The determination of these novel parameters provides the fundamental information required to establish long-term ex situ conservation strategies for this important tropical species. Heredity (2011) 106, 973-985; doi:10.1038/hdy.2010.145; published online 8 December 2010

Inhibition of COX 1 and 2 prior to Renal Ischemia/Reperfusion Injury Decreases the Development of Fibrosis

Ischemia and reperfusion injury (IRI) contributes to the development of chronic interstitial fibrosis/tubular atrophy in renal allograft patients, Cyclooxygenase (COX) 1 and 2 actively participate in acute ischemic injury by activating endothelial cells and inducing oxidative stress. Furthermore, blockade of COX I and 2 has been associated with organ improvement after ischemic damage. The aim of this study was to evaluate the role of COX I and 2 in the development of fibrosis by performing a COX I and 2 blockade immediately before IRI We subjected C57BI/6 male mice to 60 min of unilateral renal pedicle occlusion, Prior to surgery mice were either treated with indomethacin (IMT) at days -1 and 0 or were untreated. Blood and kidney samples were collected 6 wks after IRI. Kidney samples were analyzed by real-time reverse transcription-poly me rase chain reaction for expression of transforming growth factor beta (TGF-beta), monocyte chemoattractant protein 1 (MCP-1), osteopontin (OPN), tumor necrosis factor alpha (TNF-alpha), interleukin (IL)-1 beta, IL-10, heme oxygenose 1 (HO-1), vimentin, connective-tissue growth factor (CTGF), collagen 1, and bone morphogenic protein 7 (BMP-7), To assess tissue fibrosis we performed morphometric analyses and Sirius red staining. We also performed immunohistochemical analysis of anti-actin smooth muscle, Renal function did not significantly differ between groups. Animals pretreated with IMT showed significantly less interstitial fibrosis than nontreated animals. Gene transcript analyses showed decreased expression of TGF-beta, MCP-1,TNF-alpha, IL-1-beta, vimentin, collagen 1, CTGF and IL-10 mRNA (all P < 0.05), Moreover, HO-I mRNA was increased in animals pretreated with IMT (P < 0.05) Conversely, IMT treatment decreased osteopontin expression and enhanced BMP-7 expression, although these levels did rot reach statistical significance when compared with control expression levels, I he blockade of COX 1 and 2 resulted in less tissue fibrosis, which was associated with a decrease in proinflammatory cytokines and enhancement of the protective cellular response.

Anandamide prior to sensitization increases cell-mediated immunity in mice

The endocannabinoid system has become a topic of great interest in pharmacology due to its remarkable distribution in mammal organisms and capacity to play a modulatory role on several physiological systems, including modulation of immunity. Many studies have shown that administration of cannabinoids causes inhibitory effects on immune cells, including decreased proliferation and antigen-presenting cell (APC) costimulatory activity. In contrast, other groups have shown that some cannabinoids might present stimulatory actions on macrophage activity and T cell activation. Therefore, we aimed to investigate whether a treatment in vivo with a low dose of anandamide (0.1 mg/kg) immediately prior to sensitization would have an immunosuppressive or immunostimulatory effect on cell-mediated immunity (Th1 response) in mice. We report here that anandamide, prior to sensitization, was able to increase the Th1 response to ovalbumin in vivo and ex vivo. Anandamide increased delayed type hypersensitivity (DTH), splenocyte proliferation, and IFN-gamma production in a co-culture of adherent and non-adherent splenocytes. Moreover, anandamide prior to sensitization increased both the expression of DC co-stimulatory molecules (CD80/CD86) and IL-12/IL23 (p40) production ex vivo. We have also assessed direct effects of anandamide in the IFN-gamma/IL-4 balance of ConA-stimulated splenocytes in vitro. Anandamide at nanomolar concentrations increased the production of IFN-gamma, while such production decreased at micromolar range. Thus, anandamide induced both the increment of DC activation and IFN-gamma production, which are likely the mechanisms involved in the increase of Th1 response reported here. (C) 2010 Elsevier B.V. All rights reserved.

HiPP: A Novel Hierarchical Point Placement Strategy and its Application to the Exploration of Document Collections

Point placement strategies aim at mapping data points represented in higher dimensions to bi-dimensional spaces and are frequently used to visualize relationships amongst data instances. They have been valuable tools for analysis and exploration of data sets of various kinds. Many conventional techniques, however, do not behave well when the number of dimensions is high, such as in the case of documents collections. Later approaches handle that shortcoming, but may cause too much clutter to allow flexible exploration to take place. In this work we present a novel hierarchical point placement technique that is capable of dealing with these problems. While good grouping and separation of data with high similarity is maintained without increasing computation cost, its hierarchical structure lends itself both to exploration in various levels of detail and to handling data in subsets, improving analysis capability and also allowing manipulation of larger data sets.

HIERARCHICAL DECOMPOSITION OF MULTICLASS PROBLEMS

Several popular Machine Learning techniques are originally designed for the solution of two-class problems. However, several classification problems have more than two classes. One approach to deal with multiclass problems using binary classifiers is to decompose the multiclass problem into multiple binary sub-problems disposed in a binary tree. This approach requires a binary partition of the classes for each node of the tree, which defines the tree structure. This paper presents two algorithms to determine the tree structure taking into account information collected from the used dataset. This approach allows the tree structure to be determined automatically for any multiclass dataset.

Hierarchical spherical model from a geometric point of view

A continuous version of the hierarchical spherical model at dimension d=4 is investigated. Two limit distributions of the block spin variable X(gamma), normalized with exponents gamma = d + 2 and gamma=d at and above the critical temperature, are established. These results are proven by solving certain evolution equations corresponding to the renormalization group (RG) transformation of the O(N) hierarchical spin model of block size L(d) in the limit L down arrow 1 and N ->infinity. Starting far away from the stationary Gaussian fixed point the trajectories of these dynamical system pass through two different regimes with distinguishable crossover behavior. An interpretation of this trajectories is given by the geometric theory of functions which describe precisely the motion of the Lee-Yang zeroes. The large-N limit of RG transformation with L(d) fixed equal to 2, at the criticality, has recently been investigated in both weak and strong (coupling) regimes by Watanabe (J. Stat. Phys. 115:1669-1713, 2004) . Although our analysis deals only with N = infinity case, it complements various aspects of that work.

Hierarchical spatial organization of geographical networks

In this work, we propose a hierarchical extension of the polygonality index as the means to characterize geographical planar networks. By considering successive neighborhoods around each node, it is possible to obtain more complete information about the spatial order of the network at progressive spatial scales. The potential of the methodology is illustrated with respect to synthetic and real geographical networks.

Hierarchical Assembly of CaMoO(4) Nano-Octahedrons and Their Photoluminescence Properties

Hierarchical assemblies of CaMoO4 (CM) nano-octahedrons were obtained by microwave-assisted hydrothemial synthesis at 120 degrees C for different times. These structures were structurally, morphologically and optically characterized by X-ray diffraction, micro-Raman spectroscopy, field-emission gun scanning electron microscopy, ultraviolet-visible absorption spectroscopy and photoluminescence measurements. First-principle calculations have been carried out to understand the structural and electronic order-disorder effects as a function of the particle/region size. Supercells of different dimensions were constructed to simulate the geometric distortions along both they and z planes of the scheelite structure. Based on these experimental results and with the help of detailed structural simulations, we were able to model the nature of the order-disorder in this important class of materials and discuss the consequent implications on its physical properties, in particular, the photoluminescence properties of CM nanocrystals.

Semiparametric Bayesian measurement error modeling

This work presents a Bayesian semiparametric approach for dealing with regression models where the covariate is measured with error. Given that (1) the error normality assumption is very restrictive, and (2) assuming a specific elliptical distribution for errors (Student-t for example), may be somewhat presumptuous; there is need for more flexible methods, in terms of assuming only symmetry of errors (admitting unknown kurtosis). In this sense, the main advantage of this extended Bayesian approach is the possibility of considering generalizations of the elliptical family of models by using Dirichlet process priors in dependent and independent situations. Conditional posterior distributions are implemented, allowing the use of Markov Chain Monte Carlo (MCMC), to generate the posterior distributions. An interesting result shown is that the Dirichlet process prior is not updated in the case of the dependent elliptical model. Furthermore, an analysis of a real data set is reported to illustrate the usefulness of our approach, in dealing with outliers. Finally, semiparametric proposed models and parametric normal model are compared, graphically with the posterior distribution density of the coefficients. (C) 2009 Elsevier Inc. All rights reserved.