982 resultados para 382.09861051
Resumo:
Toxoplasma gondii é um protozoário parasita que infecta animais de sangue quente, incluindo seres humanos. Pequenos roedores e marsupiais têm papel importante na epidemiologia do T. gondii, pois são fontes de infecção para os felídeos domésticos e selvagens. Amostras de soro de 151 roedores e 48 marsupiais, capturados na Mata Atlântica, Estado de São Paulo, Sudeste do Brasil, foram analisadas para a pesquisa de anticorpos anti-T. gondii. Os anticorpos foram detectados pelo Teste de Aglutinação Modificada (MAT ≥ 25), com 8,6% (13/151) dos roedores e 10,4% (5/48) dos marsupiais soropositivos, com títulos variando de 25 a 6.400 e de 25 a 3.200, respectivamente, para os roedores e os marsupiais. Três das oito espécies de roedores (Akodon spp., Oligoryzomys nigripes e Rattus norvegicus) e uma das quatro espécies de marsupiais (Didelphis aurita) apresentaram animais positivos. A presença de anticorpos anti-T. gondii foi descrita pela primeira vez no roedor Oligoryzomys nigripes.
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The study was undertaken to investigate how willing would farmers be to pay for agricultural extension service in Nigeria. A multistage random sampling technique was used to select 268 respondents. Results showed that most farmers (95.1 per cent) were willing to pay for improved extension service as long as the service remained relevant to their needs. Farmers were willing to pay N1000 annually as their own share of the service cost. The most important factors that influenced farmers’ willingness to pay were states of origin, items originally paid for, major occupation, minor occupation, number of years in school and sale of farm produce.
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In attempting to answer the question ‘How is disability represented in plays?’ two approaches are considered, one semiotic and literary and the other concerned with notions of stereotyping drawn from disability studies. The five plays on which the discussion is based are school examination set texts, raising questions about classroom discourse and interpretation. Pilot study data drawn from students’ work in examinations are offered to suggest possible answers to those questions.
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Parabens (alkyl esters of p-hydroxybenzoic acid) are used extensively as preservatives in consumer products, and intact esters have been measured in several human tissues. Concerns of a potential link between parabens and breast cancer have been raised, but mechanistic studies have centred on their oestrogenic activity and little attention has been paid to any carcinogenic properties. In the present study, we report that parabens can induce anchorage-independent growth of MCF-10A immortalized but non-transformed human breast epithelial cells, a property closely related to transformation and a predictor of tumour growth in vivo. In semi-solid methocel suspension culture, MCF-10A cells produced very few colonies and only of a small size but the addition of 5 × 10-4 M methylparaben, 10–5 M n-propylparaben or 10–5 M n-butylparaben resulted in a greater number of colonies per dish (P < 0.05 in each case) and an increased average colony size (P < 0.001 in each case). Dose-responses showed that concentrations as low as 10–6 M methylparaben, 10–7 M n-propylparaben and 10–7 M n-butylparaben could increase colony numbers (P = 0.016, P = 0.010, P = 0.008, respectively): comparison with a recent measurement of paraben concentrations in human breast tissue samples from 40 mastectomies (Barr et al., 2012) showed that 22/40 of the patients had at least one of the parabens at the site of the primary tumour at or above these concentrations. To our knowledge, this is the first study to report that parabens can induce a transformed phenotype in human breast epithelial cells in vitro, and further investigation is now justified into a potential link between parabens and breast carcinogenesis.
Resumo:
Interest in attributing the risk of damaging weather-related events to anthropogenic climate change is increasing1. Yet climate models used to study the attribution problem typically do not resolve the weather systems associated with damaging events2 such as the UK floods of October and November 2000. Occurring during the wettest autumn in England and Wales since records began in 17663, 4, these floods damaged nearly 10,000 properties across that region, disrupted services severely, and caused insured losses estimated at £1.3 billion (refs 5, 6). Although the flooding was deemed a ‘wake-up call’ to the impacts of climate change at the time7, such claims are typically supported only by general thermodynamic arguments that suggest increased extreme precipitation under global warming, but fail8, 9 to account fully for the complex hydrometeorology4, 10 associated with flooding. Here we present a multi-step, physically based ‘probabilistic event attribution’ framework showing that it is very likely that global anthropogenic greenhouse gas emissions substantially increased the risk of flood occurrence in England and Wales in autumn 2000. Using publicly volunteered distributed computing11, 12, we generate several thousand seasonal-forecast-resolution climate model simulations of autumn 2000 weather, both under realistic conditions, and under conditions as they might have been had these greenhouse gas emissions and the resulting large-scale warming never occurred. Results are fed into a precipitation-runoff model that is used to simulate severe daily river runoff events in England and Wales (proxy indicators of flood events). The precise magnitude of the anthropogenic contribution remains uncertain, but in nine out of ten cases our model results indicate that twentieth-century anthropogenic greenhouse gas emissions increased the risk of floods occurring in England and Wales in autumn 2000 by more than 20%, and in two out of three cases by more than 90%.
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Nest site selection in arboreal, domatia-dwelling ants, particularly those coexisting on a single host plant, is little understood. To examine this phenomenon we studied the African savannah tree Vachellia erioloba, which hosts ants in swollen-thorn domatia. We found four ant species from different genera (Cataulacus intrudens, Tapinoma subtile, Tetraponera ambigua and an unidentified Crematogaster species). In contrast to other African ant plants, many V. erioloba trees (41 % in our survey) were simultaneously co-occupied by more than one ant species. Our study provides quantitative field data describing: (1) aspects of tree and domatia morphology relevant to supporting a community of mutualist ants, (2) how ant species occupancy varies with domatia morphology and (3) how ant colony size varies with domatia size and species. We found that Crematogaster sp. occupy the largest thorns, followed by C. intrudens, with T. subtile in the smallest thorns. Thorn age, as well as nest entrance hole size correlated closely with ant species occupant. These differing occupancy patterns may help to explain the unusual coexistence of three ant species on individual myrmecophytic trees. In all three common ant species, colony size, as measured by total number of ants, increased with domatia size. Additionally, domatia volume and species identity interact to predict ant numbers, suggesting differing responses between species to increased availability of nesting space. The proportion of total ants in nests that were immatures varied with thorn volume and species, highlighting the importance of domatia morphology in influencing colony structure.
Resumo:
As in any field of scientific inquiry, advancements in the field of second language acquisition (SLA) rely in part on the interpretation and generalizability of study findings using quantitative data analysis and inferential statistics. While statistical techniques such as ANOVA and t-tests are widely used in second language research, this review article provides a review of a class of newer statistical models that have not yet been widely adopted in the field, but have garnered interest in other fields of language research. The class of statistical models called mixed-effects models are introduced, and the potential benefits of these models for the second language researcher are discussed. A simple example of mixed-effects data analysis using the statistical software package R (R Development Core Team, 2011) is provided as an introduction to the use of these statistical techniques, and to exemplify how such analyses can be reported in research articles. It is concluded that mixed-effects models provide the second language researcher with a powerful tool for the analysis of a variety of types of second language acquisition data.
Resumo:
Sea ice friction models are necessary to predict the nature of interactions between sea ice floes. These interactions are of interest on a range of scales, for example, to predict loads on engineering structures in icy waters or to understand the basin-scale motion of sea ice. Many models use Amonton's friction law due to its simplicity. More advanced models allow for hydrodynamic lubrication and refreezing of asperities; however, modeling these processes leads to greatly increased complexity. In this paper we propose, by analogy with rock physics, that a rate- and state-dependent friction law allows us to incorporate memory (and thus the effects of lubrication and bonding) into ice friction models without a great increase in complexity. We support this proposal with experimental data on both the laboratory (∼0.1 m) and ice tank (∼1 m) scale. These experiments show that the effects of static contact under normal load can be incorporated into a friction model. We find the parameters for a first-order rate and state model to be A = 0.310, B = 0.382, and μ0 = 0.872. Such a model then allows us to make predictions about the nature of memory effects in moving ice-ice contacts.
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Rationale:Metabolic Syndrome (MetS) is a high prevalence condition characterized by altered energy metabolism, insulin resistance and elevated cardiovascular risk.Objectives:Although many individual single nucleotide polymorphisms (SNPs) have been linked to certain MetS features, there are few studies analyzing the influence of SNPs on carbohydrate metabolism in MetS.Methods:904 SNPs (tag SNPs and functional SNPs) were tested for influence in eight fasting and dynamic markers of carbohydrate metabolism, performing an intravenous glucose tolerance test in 450 participants of the LIPGENE study.Findings:From 382 initial gene-phenotype associations between SNPs and any phenotypic variables, 61 (a 16 % of the pre-selected) remained significant after Bootstrapping. Top SNPs affecting glucose metabolism variables were as follows: fasting glucose: rs26125 (PPARGC1B); fasting insulin: rs4759277 (LRP1); C peptide: rs4759277 (LRP1); HOMA-IR: rs4759277 (LRP1); QUICKI: rs184003 (AGER); SI: rs7301876 (ABCC9), AIRg: rs290481 (TCF7L2) and DI: rs12691 (CEBPA).Conclusions:We describe here the top SNPs linked to phenotypic features in carbohydrate metabolism among aproximately 1000 candidate gene variations in fasting and postprandial samples of 450 patients with MetS from the LIPGENE study.
Resumo:
The new compounds [Ru(R-DAB)(acac)2] (R-DAB = 1,4-diorganyl-
1,4-diazabuta-1,3-diene; R = tert-butyl, 4-methoxyphenyl,
2,6-dimethylphenyl; acac– = 2,4-pentanedionate) exhibit intrachelate ring bond lengths 1.297
Resumo:
This paper investigates whether survey forecasters are able to make more accurate forecasts than simply supposing that the future values of the variable will move monotonically to the long-run expectation. We consider the forecasts individually, and the consensus forecasts. Consensus survey forecasts are able to do so to varying degrees depending on the variable, but this ability is largely limited to forecasts of the current quarter.