High Proportion of Male Faeces in Jaguar Populations

Faeces provide relevant biological information which includes, with the application of genetic techniques, the sex and identity of individuals that defecated, thus providing potentially useful data on the behaviour and ecology of individuals, as well as the dynamics and structure of populations. This paper presents estimates of the sex ratio of different felid species (jaguar, Panthera onca; puma, Puma concolor; and ocelot/margay, Leopardus pardalis/Leopardus wiedi) as observed in field collected faeces, and proposes several hypotheses that could explain the strikingly high proportion of faeces from male jaguars. The proportion of male and female faeces was estimated using a non-invasive faecal sampling method in 14 study areas in Mexico and Brazil. Faecal samples were genetically analysed to identify the species, the sex and the individual (the latter only for samples identified as belonging to jaguars). Considering the three species, 72.6% of faeces (n = 493) were from males; however, there were significant differences among them, with the proportion from males being higher for jaguars than for pumas and ocelots/margays. A male-bias was consistently observed in all study areas for jaguar faeces, but not for the other species. For jaguars the trend was the same when considering the number of individuals identified (n = 68), with an average of 4.2 +/- 0.56 faeces per male and 2.0 +/- 0.36 per female. The observed faecal marking patterns might be related to the behaviour of female jaguars directed toward protecting litters from males, and in both male and female pumas, to prevent interspecific aggressions from male jaguars. The hypothesis that there are effectively more males than females in jaguar populations cannot be discarded, which could be due to the fact that females are territorial and males are not, or a tendency for males to disperse into suboptimal areas for the species.

Genetic characterization of fig tree mutants with molecular markers

The fig (Ficus carica L.) is a fruit tree of great world importance and, therefore, the genetic improvement becomes an important field of research for better crops, being necessary to gather information on this species, mainly regarding its genetic variability so that appropriate propagation projects and management are made. The improvement programs of fig trees using conventional procedures in order to obtain new cultivars are rare in many countries, such as Brazil, especially due to the little genetic variability and to the difficulties in obtaining plants from gamete fusion once the wasp Blastophaga psenes, responsible for the natural pollinating, is not found in Brazil. In this way, the mutagenic genetic improvement becomes a solution of it. For this reason, in an experiment conducted earlier, fig plants formed by cuttings treated with gamma ray were selected based on their agronomic characteristics of interest. We determined the genetic variability in these fig tree selections, using RAPD and AFLP molecular markers, comparing them to each other and to the Roxo-de-Valinhos, used as the standard. For the reactions of DNA amplification, 140 RAPD primers and 12 primer combinations for AFLP analysis were used. The selections did not differ genetically between themselves and between them and the Roxo-de-Valinhos cultivar. Techniques that can detect polymorphism between treatments, such as DNA sequencing, must be tested. The phenotypic variation of plants may be due to epigenetic variation, necessitating the use of techniques with methylation-sensitive restriction enzymes.

Combining meta-learning and search techniques to select parameters for support vector machines

Support Vector Machines (SVMs) have achieved very good performance on different learning problems. However, the success of SVMs depends on the adequate choice of the values of a number of parameters (e.g., the kernel and regularization parameters). In the current work, we propose the combination of meta-learning and search algorithms to deal with the problem of SVM parameter selection. In this combination, given a new problem to be solved, meta-learning is employed to recommend SVM parameter values based on parameter configurations that have been successfully adopted in previous similar problems. The parameter values returned by meta-learning are then used as initial search points by a search technique, which will further explore the parameter space. In this proposal, we envisioned that the initial solutions provided by meta-learning are located in good regions of the search space (i.e. they are closer to optimum solutions). Hence, the search algorithm would need to evaluate a lower number of candidate solutions when looking for an adequate solution. In this work, we investigate the combination of meta-learning with two search algorithms: Particle Swarm Optimization and Tabu Search. The implemented hybrid algorithms were used to select the values of two SVM parameters in the regression domain. These combinations were compared with the use of the search algorithms without meta-learning. The experimental results on a set of 40 regression problems showed that, on average, the proposed hybrid methods obtained lower error rates when compared to their components applied in isolation.

Evaluation of the genetic diversity of Histoplasma capsulatum var. capsulatum isolates from north-eastern Brazil

Since the beginning of the HIV epidemic, there has been a significant increase in the number of histoplasmosis cases in Ceara, a state in north-east Brazil. The lack of epidemiological data on the genotypes circulating in the north-east region shows the importance of more detailed studies on the molecular epidemiology of Histoplasma capsulatum var. capsulatum in this region. Different molecular techniques have been used to better characterize the genetic profile of H. capsulatum var. capsulatum strains. The aim of this study was to analyse the genetic diversity of H. capsulatum var. capsulatum isolates in Fortaleza, the capital of Ceara, through the sequencing of the internal transcribed spacer (ITS)1-5.8S-ITS2 region, and establish the molecular profile of these isolates, along with strains from south-east Brazil, by RAPD analysis, featuring the different clusters in those regions. The isolates were grouped into two clusters. Cluster 1 included strains from the south-east and north-east regions with separation of isolates into three distinct subgroups (subgroups 1a, 1 b and 1 c). Cluster 2 included only samples from north-east Brazil. Sequencing of the ITS1 -5.8S-ITS2 region allowed the detection of two major clades, which showed geographical correlation between them and their subgroups. Therefore, it can be concluded that the H. capsulatum var. capsulatum isolates from Ceara have a high degree of genetic polymorphism. The molecular data also confirm that populations of this fungus are composed of different genotypes in Brazil and worldwide.

Genetic polymorphisms modulate the folate metabolism of Brazilian individuals with Down syndrome

Individuals with Down syndrome (DS) carry three copies of the Cystathionine beta-synthase (C beta S) gene. The increase in the dosage of this gene results in an altered profile of metabolites involved in the folate pathway, including reduced homocysteine (Hcy), methionine, S-adenosylhomocysteine (SAH) and S-adenosylmethionine (SAM). Furthermore, previous studies in individuals with DS have shown that genetic variants in genes involved in the folate pathway influence the concentrations of this metabolism's products. The purpose of this study is to investigate whether polymorphisms in genes involved in folate metabolism affect the plasma concentrations of Hcy and methylmalonic acid (MMA) along with the concentration of serum folate in individuals with DS. Twelve genetic polymorphisms were investigated in 90 individuals with DS (median age 1.29 years, range 0.07-30.35 years; 49 male and 41 female). Genotyping for the polymorphisms was performed either by polymerase chain reaction (PCR) based techniques or by direct sequencing. Plasma concentrations of Hcy and MMA were measured by liquid chromatography-tandem mass spectrometry as previously described, and serum folate was quantified using a competitive immunoassay. Our results indicate that the MTHFR C677T, MTR A2756G, TC2 C776G and BHMT G742A polymorphisms along with MMA concentration are predictors of Hcy concentration. They also show that age and Hcy concentration are predictors of MMA concentration. These findings could help to understand how genetic variation impacts folate metabolism and what metabolic consequences these variants have in individuals with trisomy 21.