Pericarp structure in Banisteriopsis CBRob. and Diplopterys A.Juss. (Malpighiaceae): new data supporting generic segregation

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Crystal Structure Determination of Mebendazole Form A Using High-Resolution Synchrotron X-Ray Powder Diffraction Data

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Evolution and population structure of africanized honey bees in Brazil: Evidence from spatial analysis of morphometric data

In recent years, studies based on isoenzymatic patterns of geographic variation have revealed that what is usually called the Africanized honey bee does not constitute a single population. Instead, several local populations exist with various degrees of admixture with European honey bees. In this paper, we evaluated new data on morphometric patterns of Africanized honey bees collected at 42 localities in Brazil, using univariate and multivariate (canonical) trend surface and spatial autocorrelation analyses. The clinal patterns of variation found for genetically independent characters (wing size characters and some wing venation angles) are concordant with previous studies of malate dehydrogenase (MDH) allelic frequencies and support the hypothesis that larger honey bees in southern and southeastern Brazil originated by racial admixture in the initial phases of African honey bee colonization. Geographic variation patterns of Africanized honey bee populations reflect a demic diffusion process in which European genes were gradually lost because of the higher fitness of the African gene pool in Neotropical environmental conditions.

Gravity Data and Crustal Structure of North-Central Brazil

The Bouguer gravity anomaly of the northwest Ceará state in north-central Brazil was separated into its regional and residual components which were interpreted separately. By assuming that the sources of the regional anomalies are the depth variations of the crust-mantle interface, the mapping of these variations permited identifying crustal thickening zones which may be related to regional structures. The gravity residual sources coincide with occurrences of high-grade rocks (granulites) associated to medium-grade gneisses. Besides, the major strike-slip zones present significant signatures in the gravity data. This geophysical interpretation is compatible with the interpretation that the tectonic framework of the area is related to two crustal blocks conjoined by an A-type suture. The blocks are displaced along an oblique ramp with dextral movement, which played an important role in uplifting high-grade rocks from the lower crust to upper crustal levels. The suture zone corresponds to an imbricated compressive system dipping to the east and complicated by late dextral strike-slip shear zones.

Adult mortality estimate based on information on age structure of deaths, and application to data for San Felipe around 1787

Includes bibliography

Modelling the surface circulation and thermal structure of a tropical reservoir using three-dimensional hydrodynamic lake model and remote-sensing data

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Comparison of wing geometry data and genetic data for assessing the population structure of Aedes aegypti

Aedes aegypti is the most important vector of dengue viruses in tropical and subtropical regions. Because vaccines are still under development, dengue prevention depends primarily on vector control. Population genetics is a common approach in research involving Ae. aegypti. In the context of medical entomology, wing morphometric analysis has been proposed as a strong and low-cost complementary tool for investigating population structure. Therefore, we comparatively evaluated the genetic and phenotypic variability of population samples of Ae. aegypti from four sampling sites in the metropolitan area of Sao Paulo city, Brazil. The distances between the sites ranged from 7.1 to 50 km. This area, where knowledge on the population genetics of this mosquito is incipient, was chosen due to the thousands of dengue cases registered yearly. The analysed loci were polymorphic, and they revealed population structure (global F-ST = 0.062; p < 0.05) and low levels of gene flow (Nm = 0.47) between the four locations. Principal component and discriminant analyses of wing shape variables (18 landmarks) demonstrated that wing polymorphisms were only slightly more common between populations than within populations. Whereas microsatellites allowed for geographic differentiation, wing geometry failed to distinguish the samples. These data suggest that microevolution in this species may affect genetic and morphological characters to different degrees. In this case, wing shape was not validated as a marker for assessing population structure. According to the interpretation of a previous report, the wing shape of Ae. aegypti does not vary significantly because it is stabilised by selective pressure. (C) 2011 Elsevier B.V. All rights reserved.

Analyzing the dependence structure of microarray data: a copula–based approach

The main aim of this Ph.D. dissertation is the study of clustering dependent data by means of copula functions with particular emphasis on microarray data. Copula functions are a popular multivariate modeling tool in each field where the multivariate dependence is of great interest and their use in clustering has not been still investigated. The first part of this work contains the review of the literature of clustering methods, copula functions and microarray experiments. The attention focuses on the K–means (Hartigan, 1975; Hartigan and Wong, 1979), the hierarchical (Everitt, 1974) and the model–based (Fraley and Raftery, 1998, 1999, 2000, 2007) clustering techniques because their performance is compared. Then, the probabilistic interpretation of the Sklar’s theorem (Sklar’s, 1959), the estimation methods for copulas like the Inference for Margins (Joe and Xu, 1996) and the Archimedean and Elliptical copula families are presented. In the end, applications of clustering methods and copulas to the genetic and microarray experiments are highlighted. The second part contains the original contribution proposed. A simulation study is performed in order to evaluate the performance of the K–means and the hierarchical bottom–up clustering methods in identifying clusters according to the dependence structure of the data generating process. Different simulations are performed by varying different conditions (e.g., the kind of margins (distinct, overlapping and nested) and the value of the dependence parameter ) and the results are evaluated by means of different measures of performance. In light of the simulation results and of the limits of the two investigated clustering methods, a new clustering algorithm based on copula functions (‘CoClust’ in brief) is proposed. The basic idea, the iterative procedure of the CoClust and the description of the written R functions with their output are given. The CoClust algorithm is tested on simulated data (by varying the number of clusters, the copula models, the dependence parameter value and the degree of overlap of margins) and is compared with the performance of model–based clustering by using different measures of performance, like the percentage of well–identified number of clusters and the not rejection percentage of H0 on . It is shown that the CoClust algorithm allows to overcome all observed limits of the other investigated clustering techniques and is able to identify clusters according to the dependence structure of the data independently of the degree of overlap of margins and the strength of the dependence. The CoClust uses a criterion based on the maximized log–likelihood function of the copula and can virtually account for any possible dependence relationship between observations. Many peculiar characteristics are shown for the CoClust, e.g. its capability of identifying the true number of clusters and the fact that it does not require a starting classification. Finally, the CoClust algorithm is applied to the real microarray data of Hedenfalk et al. (2001) both to the gene expressions observed in three different cancer samples and to the columns (tumor samples) of the whole data matrix.

New computational biology tools for the systematic analysis of the structure and expression of human genes

From the late 1980s, the automation of sequencing techniques and the computer spread gave rise to a flourishing number of new molecular structures and sequences and to proliferation of new databases in which to store them. Here are presented three computational approaches able to analyse the massive amount of publicly avalilable data in order to answer to important biological questions. The first strategy studies the incorrect assignment of the first AUG codon in a messenger RNA (mRNA), due to the incomplete determination of its 5' end sequence. An extension of the mRNA 5' coding region was identified in 477 in human loci, out of all human known mRNAs analysed, using an automated expressed sequence tag (EST)-based approach. Proof-of-concept confirmation was obtained by in vitro cloning and sequencing for GNB2L1, QARS and TDP2 and the consequences for the functional studies are discussed. The second approach analyses the codon bias, the phenomenon in which distinct synonymous codons are used with different frequencies, and, following integration with a gene expression profile, estimates the total number of codons present across all the expressed mRNAs (named here "codonome value") in a given biological condition. Systematic analyses across different pathological and normal human tissues and multiple species shows a surprisingly tight correlation between the codon bias and the codonome bias. The third approach is useful to studies the expression of human autism spectrum disorder (ASD) implicated genes. ASD implicated genes sharing microRNA response elements (MREs) for the same microRNA are co-expressed in brain samples from healthy and ASD affected individuals. The different expression of a recently identified long non coding RNA which have four MREs for the same microRNA could disrupt the equilibrium in this network, but further analyses and experiments are needed.

German validation of the Conners Adult ADHD Rating Scales–self-report (CAARS-S) I: Factor structure and normative data

Attention-deficit/hyperactivity disorder (ADHD) often persists into adulthood. Instruments for diagnosing ADHD in childhood are well validated and reliable, but diagnosis of ADHD in adults remains problematic. Attempts have been made to develop criteria specific for adult ADHD, resulting in the development of self-report and observer-rated questionnaires. To date, the Conners Adult ADHD Rating Scales (CAARS) are the international standard for questionnaire assessment of ADHD. The current study evaluates a German version of the CAARS self-report (CAARS-S).

Fine-scale population structure analysis of seven local Swiss sheep breeds using genome-wide SNP data

As part of the global sheep Hapmap project, 24 individuals from each of seven indigenous Swiss sheep breeds (Bundner Oberländer sheep (BOS), Engadine Red sheep (ERS), Swiss Black-Brown Mountain sheep (SBS), Swiss Mirror sheep (SMS), Swiss White Alpine (SWA) sheep, Valais Blacknose sheep (VBS) and Valais Red sheep (VRS)), were genotyped using Illumina’s Ovine SNP50 BeadChip. In total, 167 animals were subjected to a detailed analysis for genetic diversity using 45 193 informative single nucleotide polymorphisms. The results of the phylogenetic analyses supported the known proximity between populations such as VBS and VRS or SMS and SWA. Average genomic relatedness within a breed was found to be 12 percent (BOS), 5 percent (ERS), 9 percent (SBS), 10 percent (SMS), 9 percent (SWA), 12 percent (VBS) and 20 percent (VRS). Furthermore, genomic relationships between breeds were found for single individuals from SWA and SMS, VRS and VBS as well as VRS and BOS. In addition, seven out of 40 indicated parent–offspring pairs could not be confirmed. These results were further supported by results from the genome-wide population cluster analysis. This study provides a better understanding of fine-scale population structures within and between Swiss sheep breeds. This relevant information will help to increase the conservation activities of the local Swiss sheep breeds.

Visualization and quantification of air embolism structure by processing postmortem MSCT data.

Venous air embolism (VAE) is an often occurring forensic finding in cases of injury to the head and neck. Whenever found, it has to be appraised in its relation to the cause of death. While visualization and quantification is difficult at traditional autopsy, Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) offer a new potential in the diagnosis of VAE. This paper reports the findings of VAE in four cases of massive head injury examined postmortem by Multislice Computed Tomography (MSCT) prior to autopsy. MSCT data of the thorax were processed using 3D air structure reconstruction software to visualize air embolism within the vascular system. Quantification of VAE was done by multiplying air containing areas on axial 2D images by their reconstruction intervals and then by summarizing the air volumes. Excellent 3D visualization of the air within the vascular system was obtained in all cases, and the intravascular gas volume was quantified.

Decomposition of $\rm R\times C$ contingency table chi -square: Application to binned DNA fragment size data and population structure analysis

The purpose of this research is to develop a new statistical method to determine the minimum set of rows (R) in a R x C contingency table of discrete data that explains the dependence of observations. The statistical power of the method will be empirically determined by computer simulation to judge its efficiency over the presently existing methods. The method will be applied to data on DNA fragment length variation at six VNTR loci in over 72 populations from five major racial groups of human (total sample size is over 15,000 individuals; each sample having at least 50 individuals). DNA fragment lengths grouped in bins will form the basis of studying inter-population DNA variation within the racial groups are significant, will provide a rigorous re-binning procedure for forensic computation of DNA profile frequencies that takes into account intra-racial DNA variation among populations. ^