980 resultados para Sparse Data
Resumo:
Drug resistance is one of the major concerns regarding tuberculosis (TB) infection worldwide because it hampers control of the disease. Understanding the underlying mechanisms responsible for drug resistance development is of the highest importance. To investigate clinical data from drug-resistant TB patients at the Tropical Diseases Hospital, Goiás (GO), Brazil and to evaluate the molecular basis of rifampin (R) and isoniazid (H) resistance in Mycobacterium tuberculosis. Drug susceptibility testing was performed on 124 isolates from 100 patients and 24 isolates displayed resistance to R and/or H. Molecular analysis of drug resistance was performed by partial sequencing of the rpoB and katGgenes and analysis of the inhA promoter region. Similarity analysis of isolates was performed by 15 loci mycobacterial interspersed repetitive unit-variable number tandem repeat (MIRU-VNTR) typing. The molecular basis of drug resistance among the 24 isolates from 16 patients was confirmed in 18 isolates. Different susceptibility profiles among the isolates from the same individual were observed in five patients; using MIRU-VNTR, we have shown that those isolates were not genetically identical, with differences in one to three loci within the 15 analysed loci. Drug-resistant TB in GO is caused by M. tuberculosis strains with mutations in previously described sites of known genes and some patients harbour a mixed phenotype infection as a consequence of a single infective event; however, further and broader investigations are needed to support our findings.
Resumo:
Ireland’s waters constitute one of the richest habitats for cetaceans in Europe. Marine mammals, particularly cetaceans, are known to be definitive hosts of digestive parasites from the Fm.Anisakidae. The main aim of this study is to collect and compile all the information available out there regarding parasites of the Fm. Anisakidae and their definitive hosts. Secondary objectives are to relate the presence of cetacean species with the presence of parasites of the Fm. Anisakidae and to determine whether this greater number of cetaceans relates to a greater level of parasitism. Prevalence and burdens of anisakids in definitive hosts vary widely with host species, geographic location, and season. Results from several post-mortem exams are given. However, they cannot be compared due to differences in collecting techniques. Anisakis simplex is the most commonly and widespread parasite found in the majority of the samples and in a majornumber of hosts, which include harbour porpoise, short-beaked common dolphin and bottlenose dolphin. Studies on harbour porpoise obtained prevalences of Anisakis spp. of 46% (n=26) and of 100% (n= 12). Another study in common dolphin reported a prevalence of 68% (n=25). Several reasons could influence the variations in the presence of Anisakis. Studies on commerciallyexploited fish have reported prevalences of Anisakis simplex ranging from 65-100% in wildAtlantic salmon and from 42-53.4% in Atlantic cod
Resumo:
To test hypotheses about the universality of personality traits, college students in 50 cultures identified an adult or college-aged man or woman whom they knew well and rated the 11,985 targets using the 3rd-person version of the Revised NEO Personality Inventory. Factor analyses within cultures showed that the normative American self-report structure was clearly replicated in most cultures and was recognizable in all. Sex differences replicated earlier self-report results, with the most pronounced differences in Western cultures. Cross-sectional age differences for 3 factors followed the pattern identified in self-reports, with moderate rates of change during college age and slower changes after age 40. With a few exceptions, these data support the hypothesis that features of personality traits are common to all human groups.
Resumo:
Analyzing functional data often leads to finding common factors, for which functional principal component analysis proves to be a useful tool to summarize and characterize the random variation in a function space. The representation in terms of eigenfunctions is optimal in the sense of L-2 approximation. However, the eigenfunctions are not always directed towards an interesting and interpretable direction in the context of functional data and thus could obscure the underlying structure. To overcome such difficulty, an alternative to functional principal component analysis is proposed that produces directed components which may be more informative and easier to interpret. These structural components are similar to principal components, but are adapted to situations in which the domain of the function may be decomposed into disjoint intervals such that there is effectively independence between intervals and positive correlation within intervals. The approach is demonstrated with synthetic examples as well as real data. Properties for special cases are also studied.