Spatial distribution pattern of Euxylophora paraensis Huber in a natural managed forest in the Eastern Amazon.

O objetivo desse trabalho foi caracterizar o padrão de distribuição espacial de Euxylophora paraensis (pau-amarelo), para subsidiar estratégias de conservação dessa espécie em floresta de terra firme manejada no estado do Pará. A área de estudo está localizada na Fazenda Rio Capim, pertencente a CKBV Florestal Ltda., no município de Paragominas. Para a análise da distribuição espacial das árvores utilizou-se a geoestatística, a partir da modelagem de semivariograma e confecção de mapas de krigagem. Todas as avaliações tiveram melhor ajuste ao modelo esférico, apresentando o maior coeficiente de determinação em relação aos outros modelos testados. Euxylophora paraensis apresentou padrão de distribuição agregada na floresta estudada, com dependência espacial descrita pelo modelo esférico, formando reboleiras de 300 a 1000 m

Chemical Characterization and Source Apportionment of Household Fine Particulate Matter in Rural, Peri-urban, and Urban West Africa

Household air pollution in sub-Saharan Africa and other developing regions is an important cause of disease burden. Little is known about the chemical composition and sources of household air pollution in sub-Saharan Africa, and how they differ between rural and urban homes. We analyzed the chemical composition and sources of fine particles (PM2.5) in household cooking areas of multiple neighborhoods in Accra, Ghana, and in peri-urban (Banjul) and rural (Basse) areas in The Gambia. In Accra, biomass burning accounted for 39–62% of total PM2.5 mass in the cooking area in different neighborhoods; the absolute contributions were 10–45 μg/m3. Road dust and vehicle emissions comprised 12–33% of PM2.5 mass. Solid waste burning was also a significant contributor to household PM2.5 in a low-income neighborhood but not for those living in better-off areas. In Banjul and Basse, biomass burning was the single dominant source of cooking-area PM2.5, accounting for 74–87% of its total mass; the relative and absolute contributions of biomass smoke to PM2.5 mass were larger in households that used firewood than in those using charcoal, reaching as high as 463 μg/m3 in Basse homes that used firewood for cooking. Our findings demonstrate the need for policies that enhance access to cleaner fuels in both rural and urban areas, and for controlling traffic emissions in cities in sub-Saharan Africa

Alteration of mesopontine cholinergic function by the lack of KCNQ4 subunit

The pedunculopontine nucleus (PPN), a structure known as a cholinergic member of the reticular activating system (RAS), is source and target of cholinergic neuromodulation and contributes to the regulation of the sleep-wakefulness cycle. The M-current is a voltage-gated potassium current modulated mainly by cholinergic signaling. KCNQ subunits ensemble into ion channels responsible for the M-current. In the central nervous system, KCNQ4 expression is restricted to certain brainstem structures such as the RAS nuclei. Here, we investigated the presence and functional significance of KCNQ4 in the PPN by behavioral studies and the gene and protein expressions and slice electrophysiology using a mouse model lacking KCNQ4 expression. We found that this mouse has alterations in the adaptation to changes in light-darkness cycles, representing the potential role of KCNQ4 in the regulation of the sleep-wakefulness cycle. As cholinergic neurons from the PPN participate in the regulation of this cycle, we investigated whether the cholinergic PPN might also possess functional KCNQ4 subunits. Although the M-current is an electrophysiological hallmark of cholinergic neurons, only a subpopulation of them had KCNQ4-dependent M-current. Interestingly, the absence of the KCNQ4 subunit altered the expression patterns of the other KCNQ subunits in the PPN. We also determined that, in wild-type animals, the cholinergic inputs of the PPN modulated the M-current, and these in turn can modulate the level of synchronization between neighboring PPN neurons. Taken together, the KCNQ4 subunit is present in a subpopulation of PPN cholinergic neurons, and it may contribute to the regulation of the sleep-wakefulness cycle.Fil: Bayasgalan, T.. University of Debrecen; HungríaFil: Stupniki, Sofia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones Bioquímicas de Bahía Blanca. Universidad Nacional del Sur. Instituto de Investigaciones Bioquímicas de Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Biología, Bioquímica y Farmacia; ArgentinaFil: Kovács, A.. University of Debrecen; HungríaFil: Csemer, A.. University of Debrecen; HungríaFil: Szentesi, P.. University of Debrecen; HungríaFil: Pocsai, K.. University of Debrecen; HungríaFil: Dionisio, Leonardo Raul. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones Bioquímicas de Bahía Blanca. Universidad Nacional del Sur. Instituto de Investigaciones Bioquímicas de Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Biología, Bioquímica y Farmacia; ArgentinaFil: Spitzmaul, Guillermo Federico. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones Bioquímicas de Bahía Blanca. Universidad Nacional del Sur. Instituto de Investigaciones Bioquímicas de Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Biología, Bioquímica y Farmacia; ArgentinaFil: Pal, B.. University of Debrecen; Hungrí

Measurement error in a multi-level analysis of air pollution and health: a simulation study.

BACKGROUND: Spatio-temporal models are increasingly being used to predict exposure to ambient outdoor air pollution at high spatial resolution for inclusion in epidemiological analyses of air pollution and health. Measurement error in these predictions can nevertheless have impacts on health effect estimation. Using statistical simulation we aim to investigate the effects of such error within a multi-level model analysis of long and short-term pollutant exposure and health. METHODS: Our study was based on a theoretical sample of 1000 geographical sites within Greater London. Simulations of "true" site-specific daily mean and 5-year mean NO2 and PM10 concentrations, incorporating both temporal variation and spatial covariance, were informed by an analysis of daily measurements over the period 2009-2013 from fixed location urban background monitors in the London area. In the context of a multi-level single-pollutant Poisson regression analysis of mortality, we investigated scenarios in which we specified: the Pearson correlation between modelled and "true" data and the ratio of their variances (model versus "true") and assumed these parameters were the same spatially and temporally. RESULTS: In general, health effect estimates associated with both long and short-term exposure were biased towards the null with the level of bias increasing to over 60% as the correlation coefficient decreased from 0.9 to 0.5 and the variance ratio increased from 0.5 to 2. However, for a combination of high correlation (0.9) and small variance ratio (0.5) non-trivial bias (> 25%) away from the null was observed. Standard errors of health effect estimates, though unaffected by changes in the correlation coefficient, appeared to be attenuated for variance ratios > 1 but inflated for variance ratios < 1. CONCLUSION: While our findings suggest that in most cases modelling errors result in attenuation of the effect estimate towards the null, in some situations a non-trivial bias away from the null may occur. The magnitude and direction of bias appears to depend on the relationship between modelled and "true" data in terms of their correlation and the ratio of their variances. These factors should be taken into account when assessing the validity of modelled air pollution predictions for use in complex epidemiological models

Experimental and theoretical study of line mixing in methane spectra. IV. Influence of the temperature and of the band

The infrared bands line-mixing effects of methane perturbed by nitrogen were discussed at different pressures. The spectral shapes of the ν2, ν4 and ν3 bands were compared at room temperature while the ν3 region was employed for the investigation of thermal effects. The effects of collisions in the ν4 region's spectra were calculated at the room temperature. The Coriolis coupling between ν2 and ν4 vibrational states resulted in the failure of evolution modeling with increasing pressure of absorption.© 2000 American Institute of PhysicsPeer Reviewe

Yacon syrup: food applications and impact on satiety in healthy volunteers.

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