40 research outputs found

    SPECT cerebral na doença de Huntington antes e após terapia com olanzapina: relato de caso

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    Olanzapine, an atypical antipsychotic drug, was administered to a patient with Huntington's disease (HD) with marked choreiform movements. Brain SPECT with 99mTc-HMPAO was performed before and after treatment. Brain SPECT imaging has been performed in patients with HD in order to determine the status of basal ganglia perfusion. The use of brain SPECT with 99mTc-HMPAO before and after treatment in patients with HD has not been yet reported. The marked hypoperfusion of the basal ganglia on brain SPECT performed before therapy with olanzapine improved significantly after treatment.Olanzapina, um antipsicĂłtico atĂ­pico, foi administrada a uma paciente com doença de Huntington (DH) com acentuados movimentos coreicos. O SPECT cerebral com HMPAO-99mTc foi realizado antes da paciente iniciar qualquer tratamento e apĂłs tratamento com olanzapina. O SPECT cerebral tem sido realizado em pacientes com DH para avaliar a perfusĂŁo dos nĂșcleos da base. O uso do SPECT cerebral com HMPAO-99mTc antes e apĂłs terapia em pacientes com DH ainda nĂŁo foi relatado. A acentuada hipoperfusĂŁo observada nos nĂșcleos da base na imagem de SPECT cerebral, obtida antes da terapia com olanzapina, melhorou de forma significativa apĂłs o tratamento.86386

    Microsatellite diversity and genetic structure among common bean (Phaseolus vulgaris L.) landraces in Brazil, a secondary center of diversity

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    Brazil is the largest producer and consumer of common bean (Phaseolus vulgaris L.), which is the most important source of human dietary protein in that country. This study assessed the genetic diversity and the structure of a sample of 279 geo-referenced common bean landraces from Brazil, using molecular markers. Sixty-seven microsatellite markers spread over the 11 linkage groups of the common bean genome, as well as Phaseolin, PvTFL1y, APA and four SCAR markers were used. As expected, the sample showed lower genetic diversity compared to the diversity in the primary center of diversification. Andean and Mesoamerican gene pools were both present but the latter gene pool was four times more frequent than the former. The two gene pools could be clearly distinguished; limited admixture was observed between these groups. The Mesoamerican group consisted of two sub-populations, with a high level of admixture between them leading to a large proportion of stabilized hybrids not observed in the centers of domestication. Thus, Brazil can be considered a secondary center of diversification of common bean. A high degree of genome-wide multilocus associations even among unlinked loci was observed, confirming the high level of structure in the sample and suggesting that association mapping should be conducted in separate Andean and Mesoamerican Brazilian samples

    TRY plant trait database – enhanced coverage and open access

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    Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

    Pervasive gaps in Amazonian ecological research

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    Pervasive gaps in Amazonian ecological research

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    Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

    Impact of common cardio-metabolic risk factors on fatal and non-fatal cardiovascular disease in Latin America and the Caribbean: an individual-level pooled analysis of 31 cohort studies

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    Background: Estimates of the burden of cardio-metabolic risk factors in Latin America and the Caribbean (LAC) rely on relative risks (RRs) from non-LAC countries. Whether these RRs apply to LAC remains un- known. Methods: We pooled LAC cohorts. We estimated RRs per unit of exposure to body mass index (BMI), systolic blood pressure (SBP), fasting plasma glucose (FPG), total cholesterol (TC) and non-HDL cholesterol on fatal (31 cohorts, n = 168,287) and non-fatal (13 cohorts, n = 27,554) cardiovascular diseases, adjusting for regression dilution bias. We used these RRs and national data on mean risk factor levels to estimate the number of cardiovascular deaths attributable to non-optimal levels of each risk factor. Results: Our RRs for SBP, FPG and TC were like those observed in cohorts conducted in high-income countries; however, for BMI, our RRs were consistently smaller in people below 75 years of age. Across risk factors, we observed smaller RRs among older ages. Non-optimal SBP was responsible for the largest number of attributable cardiovascular deaths ranging from 38 per 10 0,0 0 0 women and 54 men in Peru, to 261 (Dominica, women) and 282 (Guyana, men). For non-HDL cholesterol, the lowest attributable rate was for women in Peru (21) and men in Guatemala (25), and the largest in men (158) and women (142) from Guyana. Interpretation: RRs for BMI from studies conducted in high-income countries may overestimate disease burden metrics in LAC; conversely, RRs for SBP, FPG and TC from LAC cohorts are similar to those esti- mated from cohorts in high-income countries
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