111 research outputs found

    Preparation, characterization, and pharmacological activity of Cymbopogon winterianus Jowitt ex Bor (Poaceae) leaf essential oil of B-cyclodextrin inclusion complexes

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    This study aimed to evaluate the orofacial antinociceptive effect of the Cymbopogon winterianus essential oil (LEO) complexed in B-cyclodextrin (LEO-CD) and to assess the possible involvement of the central nervous system (CNS). The LEO was extracted, chromatographed, and complexed in B-cyclodextrin. The complex was characterized by differential scanning calorimetry (DSC) and thermogravimetry derivative (TG/DTG). Male Swiss mice (2-3 months) were treated with LEO-CD (50–200 mg/kg, p.o.), vehicle (distilled water, p.o.), or standard drug (i.p.) and subjected to the orofacial nociception formalin-, capsaicin-, and glutamateinduced. After the formalin test, the animals were perfused and the brains subjected to immunofluorescence for Fos. The rota-rod test (7 rpm/min) was carried out. Geraniol (37.57%) was the main compound of LEO. DSC and TG/DTG proved the complexation. The orofacial nociceptive behavior was significantly (p < 0.05) reduced. The number of Fos-positive cells was significantly changed in the dorsal raphe nucleus (p < 0.01), locus coeruleus (p < 0.001), trigeminal nucleus (p < 0.05), and trigeminal thalamic tract (p < 0.05). LEO-CD did not cause changes in motor coordination in the rota-rod test. Thus, our results suggested that LEO-CD has an orofacial antinociceptive profile, probably mediated by the activation of the CNS without changing the motor coordination

    Prevalence of self-reported constipation in adults from the general population

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    OBJECTIVE To estimate the prevalence of self-reported constipation and associated factors in the general population of a Brazilian city. METHOD Secondary analysis of an epidemiological study, population-based, cross-sectional study, about bowel habits of Brazilian population. A total of 2,162 individuals were interviewed using two instruments: sociodemographic data and the adapted and validated Brazilian version of the "Bowel Function in the Community" tool. RESULTS There was a prevalence of 25.2% for the self-reported constipation, 37.2% among women and 10.2% among men. Stroke and old age were associated with constipation in the three statistical models used. CONCLUSION The prevalence found showed to be similar to the findings in the literature, although some associated factors obtained here have never been investigated

    A catalogue of structural and morphological measurements for DES Y1

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    We present a structural and morphological catalogue for 45 million objects selected from the first year data of the Dark Energy Survey (DES). Single Sersic fits and non-parametric ÂŽ measurements are produced for g, r, and i filters. The parameters from the best-fitting Sersic ÂŽ model (total magnitude, half-light radius, Sersic index, axis ratio, and position angle) are mea- ÂŽ sured with GALFIT; the non-parametric coefficients (concentration, asymmetry, clumpiness, Gini, M20) are provided using the Zurich Estimator of Structural Types (ZEST+). To study the statistical uncertainties, we consider a sample of state-of-the-art image simulations with a realistic distribution in the input parameter space and then process and analyse them as we do with real data: this enables us to quantify the observational biases due to PSF blurring and magnitude effects and correct the measurements as a function of magnitude, galaxy size, Sersic ÂŽ index (concentration for the analysis of the non-parametric measurements) and ellipticity. We present the largest structural catalogue to date: we find that accurate and complete measurements for all the structural parameters are typically obtained for galaxies with SEXTRACTOR MAG AUTO I ≀ 21. Indeed, the parameters in the filters i and r can be overall well recovered up to MAG AUTO ≀ 21.5, corresponding to a fitting completeness of ∌90 per cent below this threshold, for a total of 25 million galaxies. The combination of parametric and non-parametric structural measurements makes this catalogue an important instrument to explore and understand how galaxies form and evolve. The catalogue described in this paper will be publicly released alongside the DES collaboration Y1 cosmology data products at the following URL: https://des.ncsa.illinois.edu/releases

    Redshift distributions of galaxies in the Dark Energy Survey Science Verification shear catalogue and implications for weak lensing

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    We present photometric redshift estimates for galaxies used in the weak lensing analysis of the Dark Energy Survey Science Verification (DES SV) data. Four model- or machine learning-based photometric redshift methods—ANNZ2, BPZ calibrated against BCC-Ufig simulations, SKYNET, and TPZ—are analyzed. For training, calibration, and testing of these methods, we construct a catalogue of spectroscopically confirmed galaxies matched against DES SV data. The performance of the methods is evaluated against the matched spectroscopic catalogue, focusing on metrics relevant for weak lensing analyses, with additional validation against COSMOS photo-z’s. From the galaxies in the DES SV shear catalogue, which have mean redshift 0.72 0.01 over the range 0.3 < z < 1.3, we construct three tomographic bins with means of z ÂŒ f0.45; 0.67; 1.00g. These bins each have systematic uncertainties ÎŽz â‰Č 0.05 in the mean of the fiducial SKYNET photo-z nĂ°zÞ. We propagate the errors in the redshift distributions through to their impact on cosmological parameters estimated with cosmic shear, and find that they cause shifts in the value of σ8 of approximately 3%. This shift is within the one sigma statistical errors on σ8 for the DES SV shear catalogue. We further study the potential impact of systematic differences on the critical surface density, ÎŁcrit, finding levels of bias safely less than the statistical power of DES SV data. We recommend a final Gaussian prior for the photo-z bias in the mean of nĂ°zÞ of width 0.05 for each of the three tomographic bins, and show that this is a sufficient bias model for the corresponding cosmology analysis

    Pervasive gaps in Amazonian ecological research

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    Photography-based taxonomy is inadequate, unnecessary, and potentially harmful for biological sciences

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    The question whether taxonomic descriptions naming new animal species without type specimen(s) deposited in collections should be accepted for publication by scientific journals and allowed by the Code has already been discussed in Zootaxa (Dubois & NemĂ©sio 2007; Donegan 2008, 2009; NemĂ©sio 2009a–b; Dubois 2009; Gentile & Snell 2009; Minelli 2009; Cianferoni & Bartolozzi 2016; Amorim et al. 2016). This question was again raised in a letter supported by 35 signatories published in the journal Nature (Pape et al. 2016) on 15 September 2016. On 25 September 2016, the following rebuttal (strictly limited to 300 words as per the editorial rules of Nature) was submitted to Nature, which on 18 October 2016 refused to publish it. As we think this problem is a very important one for zoological taxonomy, this text is published here exactly as submitted to Nature, followed by the list of the 493 taxonomists and collection-based researchers who signed it in the short time span from 20 September to 6 October 2016

    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
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