6 resultados para Oocyte morphological classification

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP)


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We studied superclusters of galaxies in a volume-limited sample extracted from the Sloan Digital Sky Survey Data Release 7 and from mock catalogues based on a semi-analytical model of galaxy evolution in the Millennium Simulation. A density field method was applied to a sample of galaxies brighter than M(r) = -21+5 log h(100) to identify superclusters, taking into account selection and boundary effects. In order to evaluate the influence of the threshold density, we have chosen two thresholds: the first maximizes the number of objects (D1) and the second constrains the maximum supercluster size to similar to 120 h(-1) Mpc (D2). We have performed a morphological analysis, using Minkowski Functionals, based on a parameter, which increases monotonically from filaments to pancakes. An anticorrelation was found between supercluster richness (and total luminosity or size) and the morphological parameter, indicating that filamentary structures tend to be richer, larger and more luminous than pancakes in both observed and mock catalogues. We have also used the mock samples to compare supercluster morphologies identified in position and velocity spaces, concluding that our morphological classification is not biased by the peculiar velocities. Monte Carlo simulations designed to investigate the reliability of our results with respect to random fluctuations show that these results are robust. Our analysis indicates that filaments and pancakes present different luminosity and size distributions.

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We detail an innovative new technique for measuring the two-dimensional (2D) velocity moments (rotation velocity, velocity dispersion and Gauss-Hermite coefficients h(3) and h(4)) of the stellar populations of galaxy haloes using spectra from Keck DEIMOS (Deep Imaging Multi-Object Spectrograph) multi-object spectroscopic observations. The data are used to reconstruct 2D rotation velocity maps. Here we present data for five nearby early-type galaxies to similar to three effective radii. We provide significant insights into the global kinematic structure of these galaxies, and challenge the accepted morphological classification in several cases. We show that between one and three effective radii the velocity dispersion declines very slowly, if at all, in all five galaxies. For the two galaxies with velocity dispersion profiles available from planetary nebulae data we find very good agreement with our stellar profiles. We find a variety of rotation profiles beyond one effective radius, i.e. rotation speed remaining constant, decreasing and increasing with radius. These results are of particular importance to studies which attempt to classify galaxies by their kinematic structure within one effective radius, such as the recent definition of fast- and slow-rotator classes by the Spectrographic Areal Unit for Research on Optical Nebulae project. Our data suggest that the rotator class may change when larger galactocentric radii are probed. This has important implications for dynamical modelling of early-type galaxies. The data from this study are available on-line.

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Oocyte developmental competence depends on maternal stores that support development throughout a transcriptionally silent period during early embryogenesis. Previous attempts to investigate transcripts associated with oocyte competence have relied on prospective models, which are mostly based on morphological. criteria. Using a retrospective model, we quantitatively compared mRNA among oocytes with different embryo development competence. A cytoplasm biopsy was removed from in vitro matured oocytes to perform comparative analysis of amounts of global polyadenylated (polyA) mRNA and housekeeping gene transcripts. After parthenogenetic activation of biopsied oocytes, presumptive zygotes were cultured individually in vitro and oocytes were classified according to embryo development: (i) blocked before the 8-cell stage; (ii) blocked between the 8-cell and morulae stages; or (iii) developed to the blastocyst stage. Sham-manipulated controls confirmed that biopsies did not alter development outcome. Total polyA mRNA amounts correlate with oocyte diameter but not with the ability to develop to the 8-cell and blastocyst stages. The last was also confirmed by relative quantification of GAPDH, H2A and Hprt1 transcripts. In conclusion, we describe a novel retrospective model to identify putative markers of development competence in single oocytes and demonstrate that global mRNA amounts at the metaphase II stage do not correlate with embryo development in vitro.

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Epidendrum L. is the largest genus of Orchidaceae in the Neotropical region; it has an impressive morphological diversification, which imposes difficulties in delimitation of both infrageneric and interspecific boundaries. In this study, we review infrageneric boundaries within the subgenus Amphiglottium and try to contribute to the understanding of morphological diversification and taxa delimitation within this group. We tested the monophyly of the subgenus Amphiglottium sect. Amphiglottium, expanding previous phylogenetic investigations and reevaluated previous infrageneric classifications proposed. Sequence data from the trnL-trnF region were analyzed with both parsimony and maximum likelihood criteria. AFLP markers were also obtained and analyzed with phylogenetic and principal coordinate analyses. Additionally, we obtained chromosome numbers for representative species within the group. The results strengthen the monophyly of the subgenus Amphiglottium but do not support the current classification system proposed by previous authors. Only section Tuberculata comprises a well-supported monophyletic group, with sections Carinata and Integra not supported. Instead of morphology, biogeographical and ecological patterns are reflected in the phylogenetic signal in this group. This study also confirms the large variability of chromosome numbers for the subgenus Amphiglottium (numbers ranging from 2n = 24 to 2n = 240), suggesting that polyploidy and hybridization are probably important mechanisms of speciation within the group.

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We investigated the evolution of anuran locomotor performance and its morphological correlates as a function of habitat use and lifestyles. We reanalysed a subset of the data reported by Zug (Smithson. Contrib. Zool. 1978; 276: 1-31) employing phylogenetically explicit statistical methods (n = 56 species), and assembled morphological data on the ratio between hind-limb length and snout-vent length (SVL) from the literature and museum specimens for a large subgroup of the species from the original paper (n = 43 species). Analyses using independent contrasts revealed that classifying anurans into terrestrial, semi-aquatic, and arboreal categories cannot distinguish between the effects of phylogeny and ecological diversification in anuran locomotor performance. However, a more refined classification subdividing terrestrial species into `fossorials` and `non-fossorials`, and arboreal species into `open canopy`, `low canopy` and `high canopy`, suggests that part of the variation in locomotor performance and in hind-limb morphology can be attributed to ecological diversification. In particular, fossorial species had significantly lower jumping performances and shorter hind limbs than other species after controlling for SVL, illustrating how the trade-off between burrowing efficiency and jumping performance has resulted in morphological specialization in this group.

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The design of binary morphological operators that are translation-invariant and locally defined by a finite neighborhood window corresponds to the problem of designing Boolean functions. As in any supervised classification problem, morphological operators designed from a training sample also suffer from overfitting. Large neighborhood tends to lead to performance degradation of the designed operator. This work proposes a multilevel design approach to deal with the issue of designing large neighborhood-based operators. The main idea is inspired by stacked generalization (a multilevel classifier design approach) and consists of, at each training level, combining the outcomes of the previous level operators. The final operator is a multilevel operator that ultimately depends on a larger neighborhood than of the individual operators that have been combined. Experimental results show that two-level operators obtained by combining operators designed on subwindows of a large window consistently outperform the single-level operators designed on the full window. They also show that iterating two-level operators is an effective multilevel approach to obtain better results.