3 resultados para inter-subject variability

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo


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Ureaplasma diversum in veterinary studies is an undesirable microbe, which may cause infection in bulls and may result in seminal vesiculitis, balanopostitis, and alterations in spermatozoids, whereas in cows, it may cause placentitis, fetal alveolitis, abortion, and birth of weak calves. U. diversum is released through organic secretions, especially semen, preputial and vaginal mucus, conjunctival secretion, and milk. The aim of the present study was to develop a TaqMan probe, highly sensitive and specific quantitative PCR (qPCR) assay for the detection and quantification of U. diversum from genital swabs of bovines. Primers and probes specific to U. diversum 16S rRNA gene were designed. The specificity, detection limit, intra- and inter-assay variability of qPCR to detect this ureaplasma was compared with the results of the conventional PCR assay (cPCR). Swabs of vaginal mucus from 169 cows were tested. The qPCR assay detected as few as 10 copies of U. diversum and was 100-fold more sensitive than the cPCR. No cross-reactivity with other Mollicutes or eubacteria was observed. U. diversum was detected in 79 swabs (46.42%) by qPCR, while using cPCR it was detected in 42 (25%) samples. The difference in cPCR and qPCR ureaplasma detection between healthy and sick animals was not statistically significant. But the U. diversum load in samples from animals with genital disorders was higher than in healthy animals. The qPCR assay developed herein is highly sensitive and specific for the detection and quantification of U. diversum in vaginal bovine samples.

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Intra-and inter-population genetic variability and the demographic history of Heliothis virescens (F.) populations were evaluated by using mtDNA markers (coxI, coxII and nad6) with samples from the major cotton-and soybean-producing regions in Brazil in the growing seasons 2007/08, 2008/09 and 2009/10. AMOVA indicated low and non-significant genetic structure, regardless of geographical scale, growing season or crop, with most of genetic variation occurring within populations. Clustering analyzes also indicated low genetic differentiation. The haplotype network obtained with combined datasets resulted in 35 haplotypes, with 28 exclusive occurrences, four of them sampled only from soybean fields. The minimum spanning network showed star-shaped structures typical of populations that underwent a recent demographic expansion. The recent expansion was supported by other demographic analyzes, such as the Bayesian skyline plot, the unimodal distribution of paired differences among mitochondrial sequences, and negative and significant values of neutrality tests for the Tajima's D and Fu's F-S parameters. In addition, high values of haplotype diversity ((H) over cap) and low values of nucleotide diversity (pi), combined with a high number of low frequency haplotypes and values of theta(pi)<theta(W), suggested a recent demographic expansion of H. virescens populations in Brazil. This demographic event could be responsible for the low genetic structure currently found; however, haplotypes present uniquely at the same geographic regions and from one specific host plant suggest an initial differentiation among H. virescens populations within Brazil.

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This paper uses administrative data to follow Brazilian workers over time and examine what happens to the inter-regional wage differentials after controlling for unmeasured workers' characteristics that are fixed over time. Since the data allow us to track the same workers over the years, we are in the unusual position of obtaining the individual wages before and after the migration process. As a significant share of workers changed States in the sample period, it is possible to examine to what extent the wage differentials reflect the concentration of high-skilled individuals in some States. The results show that the overall wage variability across States drops to almost one third of its original value and the ranking of the State effects is significantly altered after we take into account the workers' fixed effects. A great deal of the inter-regional differentials, therefore, reflects differences in the average ability of workers across States.