CYTOTOXICITY, ANTI-POLIOVIRUS ACTIVITY AND IN SILICO BIOLOGICAL EVALUATION OF CONSTITUENTS FROM MAYTENUS GONOCLADA (CELASTRACEAE)

Objective: The in silico free access web tools PASS online and ChemMapper were used to predict potential biological activities of compounds 1 to 8 isolated from Maytenus gonoclada (Celastraceae). The constituents 4'-O-methylepigalocatequin (6), tingenone (7) and proanthocyanidin A (8), and ethanolic extracts were subjected to in vitro cytotoxicity using VERO cells and anti-Poliovirus assays. Methods: QSAR and molecular superposition, correlating the average number of pharmacophores were used in the prediction studies. Cellular line VERO ATCC CCL-81 was used to determine anti-Poliovirus effect, observed by colorimetric (MTT) method. The annexing V/propidium iodide assay was used to determine the occurrence of apoptosis in the cytotoxicity assays. Results: The experimental results found for constituents 6-8 were in accordance with observed data obtained through PASS online and ChemMapper simulation. Conclusion: Compound 7 showed higher cytotoxic and apoptosis induction properties, and 6 and 8 presented anti-Poliovirus activity

SAMARAS OF AUSTROPLENCKIA POPULNEA (CELASTRACEAE): NEW CONSTITUENTS AND EFFECT OF EXTRACTS AND FRIEDELIN ON GERMINATION OF BIDENS PILOSA (ASTERACEAE)

Objective: Evaluation of the impact of extracts and constituents from samaras of Austroplenckia populnea on percentage of seed germination (%SG), germination speed index (GSI), length of rootlets (LR), seedling length (SL), and on dry mass (DM) of Bidens pilosa L weed.Methods: The  powder  of  samaras  was  extracted  with  organic  solvents  providing  the  hexane  (SAPEH),  chloroform  (SAPEC),  ethyl  acetate  (SAPEAE) and ethanol  (SAPEE)  extracts. The terpene 1 was isolated from SAPEH by means of column and thin layer chromatography and identified through NMR spectroscopy. Each extract and 1 were subjected to growth inhibition assays evaluating the following parameters: %SG, GSI, LR, SL and DM, with five repetitions.Results: The compounds Friedelin (1), 7-hydroxy-clerodan-3-en-16,15:18,20-diolide (2), 3,5,7,4'-tetrahydroxy-6-methoxy-8-prenylflavanone (3), tetradecanamide (4), and 4-hydroxy-1,6,15-acetyloxy-8,9-benzoyloxy-agarofurane (5) were isolated from hexane extract of samaras of A. populnea and identified by spectroscopic data. The compounds 2, 3 and 5 were not previously described as being chemical constituents from Celastraceae family. In addition, the novel compounds 3 and 5 were described here for the first time. Substantial effect on the germination of B. pilosa L. (picão-preto) was observed after treatment of seeds with nonpolar extracts from Samaras of A. populnea. Friedelin inhibited the seed germination in the tested concentrations showing toxic properties against picão-preto.Conclusion: The germination inhibition of seeds was higher using nonpolar extracts than polar extract. Friedelin inhibited the seed germination in the tested concentrations showing toxic properties against B. pilosa.Â

Pecking order theory versus trade-off theory : are service SMEs’ capital structure decisions different?

This paper seeks to analyse if the capital structure decisions of service small and medium-sized enterprises (SMEs) are different from those of other types of firm. To do so, we consider four research samples: (i) 610 service SMEs; (ii) 126 service large firms; (iii) 679 manufacturing and construction SMEs; and (iv) 132 manufacturing and construction large firms. Using the two-step estimation method, the empirical evidence obtained in this study shows that the capital structure decisions of service SMEs are different from those of other types of firm. Service SMEs’ capital structure decisions are closer to the assumptions of Pecking Order Theory and further removed from those of Trade-Off Theory compared with the case of other types of firm

<i>Gaia</i> Data Release 1. Summary of the astrometric, photometric, and survey properties

Context. At about 1000 days after the launch of Gaia we present the first Gaia data release, Gaia DR1, consisting of astrometry and photometry for over 1 billion sources brighter than magnitude 20.7. Aims. A summary of Gaia DR1 is presented along with illustrations of the scientific quality of the data, followed by a discussion of the limitations due to the preliminary nature of this release. Methods. The raw data collected by Gaia during the first 14 months of the mission have been processed by the Gaia Data Processing and Analysis Consortium (DPAC) and turned into an astrometric and photometric catalogue. Results. Gaia DR1 consists of three components: a primary astrometric data set which contains the positions, parallaxes, and mean proper motions for about 2 million of the brightest stars in common with the HIPPARCOS and Tycho-2 catalogues – a realisation of the Tycho-Gaia Astrometric Solution (TGAS) – and a secondary astrometric data set containing the positions for an additional 1.1 billion sources. The second component is the photometric data set, consisting of mean G-band magnitudes for all sources. The G-band light curves and the characteristics of ∼3000 Cepheid and RR-Lyrae stars, observed at high cadence around the south ecliptic pole, form the third component. For the primary astrometric data set the typical uncertainty is about 0.3 mas for the positions and parallaxes, and about 1 mas yr−1 for the proper motions. A systematic component of ∼0.3 mas should be added to the parallax uncertainties. For the subset of ∼94 000 HIPPARCOS stars in the primary data set, the proper motions are much more precise at about 0.06 mas yr−1. For the secondary astrometric data set, the typical uncertainty of the positions is ∼10 mas. The median uncertainties on the mean G-band magnitudes range from the mmag level to ∼0.03 mag over the magnitude range 5 to 20.7. Conclusions. Gaia DR1 is an important milestone ahead of the next Gaia data release, which will feature five-parameter astrometry for all sources. Extensive validation shows that Gaia DR1 represents a major advance in the mapping of the heavens and the availability of basic stellar data that underpin observational astrophysics. Nevertheless, the very preliminary nature of this first Gaia data release does lead to a number of important limitations to the data quality which should be carefully considered before drawing conclusions from the data

Euclid preparation: XII. Optimizing the photometric sample of the Euclid survey for galaxy clustering and galaxy-galaxy lensing analyses

Photometric redshifts (photo-zs) are one of the main ingredients in the analysis of cosmological probes. Their accuracy particularly affects the results of the analyses of galaxy clustering with photometrically selected galaxies (GCph) and weak lensing. In the next decade, space missions such as Euclid will collect precise and accurate photometric measurements for millions of galaxies. These data should be complemented with upcoming ground-based observations to derive precise and accurate photo-zs. In this article we explore how the tomographic redshift binning and depth of ground-based observations will affect the cosmological constraints expected from the Euclid mission. We focus on GCph and extend the study to include galaxy-galaxy lensing (GGL). We add a layer of complexity to the analysis by simulating several realistic photo-z distributions based on the Euclid Consortium Flagship simulation and using a machine learning photo-z algorithm. We then use the Fisher matrix formalism together with these galaxy samples to study the cosmological constraining power as a function of redshift binning, survey depth, and photo-z accuracy. We find that bins with an equal width in redshift provide a higher figure of merit (FoM) than equipopulated bins and that increasing the number of redshift bins from ten to 13 improves the FoM by 35% and 15% for GCph and its combination with GGL, respectively. For GCph, an increase in the survey depth provides a higher FoM. However, when we include faint galaxies beyond the limit of the spectroscopic training data, the resulting FoM decreases because of the spurious photo-zs. When combining GCph and GGL, the number density of the sample, which is set by the survey depth, is the main factor driving the variations in the FoM. Adding galaxies at faint magnitudes and high redshift increases the FoM, even when they are beyond the spectroscopic limit, since the number density increase compensates for the photo-z degradation in this case. We conclude that there is more information that can be extracted beyond the nominal ten tomographic redshift bins of Euclid and that we should be cautious when adding faint galaxies into our sample since they can degrade the cosmological constraints

Euclid preparation: X. The Euclid photometric-redshift challenge

Forthcoming large photometric surveys for cosmology require precise and accurate photometric redshift (photo-z) measurements for the success of their main science objectives. However, to date, no method has been able to produce photo-zs at the required accuracy using only the broad-band photometry that those surveys will provide. An assessment of the strengths and weaknesses of current methods is a crucial step in the eventual development of an approach to meet this challenge. We report on the performance of 13 photometric redshift code single value redshift estimates and redshift probability distributions (PDZs) on a common set of data, focusing particularly on the 0.2−2.6 redshift range that the Euclid mission will probe. We designed a challenge using emulated Euclid data drawn from three photometric surveys of the COSMOS field. The data was divided into two samples: one calibration sample for which photometry and redshifts were provided to the participants; and the validation sample, containing only the photometry to ensure a blinded test of the methods. Participants were invited to provide a redshift single value estimate and a PDZ for each source in the validation sample, along with a rejection flag that indicates the sources they consider unfit for use in cosmological analyses. The performance of each method was assessed through a set of informative metrics, using cross-matched spectroscopic and highlyaccurate photometric redshifts as the ground truth. We show that the rejection criteria set by participants are efficient in removing strong outliers, that is to say sources for which the photo-z deviates by more than 0.15(1 + z) from the spectroscopic-redshift (spec-z). We also show that, while all methods are able to provide reliable single value estimates, several machine-learning methods do not manage to produce useful PDZs. We find that no machine-learning method provides good results in the regions of galaxy color-space that are sparsely populated by spectroscopic-redshifts, for example z > 1. However they generally perform better than template-fitting methods at low redshift (z < 0.7), indicating that template-fitting methods do not use all of the information contained in the photometry. We introduce metrics that quantify both photo-z precision and completeness of the samples (post-rejection), since both contribute to the final figure of merit of the science goals of the survey (e.g., cosmic shear from Euclid). Template-fitting methods provide the best results in these metrics, but we show that a combination of template-fitting results and machine-learning results with rejection criteria can outperform any individual method. On this basis, we argue that further work in identifying how to best select between machine-learning and template-fitting approaches for each individual galaxy should be pursued as a priority

Euclid preparation: XVI. Exploring the ultra-low surface brightness Universe with Euclid /VIS

Context. While Euclid is an ESA mission specifically designed to investigate the nature of dark energy and dark matter, the planned unprecedented combination of survey area (∼15â 000 deg2), spatial resolution, low sky-background, and depth also make Euclid an excellent space observatory for the study of the low surface brightness Universe. Scientific exploitation of the extended low surface brightness structures requires dedicated calibration procedures that are yet to be tested. Aims. We investigate the capabilities of Euclid to detect extended low surface brightness structure by identifying and quantifying sky-background sources and stray-light contamination. We test the feasibility of generating sky flat-fields to reduce large-scale residual gradients in order to reveal the extended emission of galaxies observed in the Euclid survey. Methods. We simulated a realistic set of Euclid/VIS observations, taking into account both instrumental and astronomical sources of contamination, including cosmic rays, stray-light, zodiacal light, interstellar medium, and the cosmic infrared background, while simulating the effects of background sources in the field of view. Results. We demonstrate that a combination of calibration lamps, sky flats, and self-calibration would enable recovery of emission at a limiting surface brightness magnitude of μlim = 29.5-0.27+0.08 mag arcsec-2 (3σ, 10â ×â 10 arcsec2) in the Wide Survey, and it would reach regions deeper by 2 mag in the Deep Surveys. Conclusions.Euclid/VIS has the potential to be an excellent low surface brightness observatory. Covering the gap between pixel-To-pixel calibration lamp flats and self-calibration observations for large scales, the application of sky flat-fielding will enhance the sensitivity of the VIS detector at scales larger than 1″, up to the size of the field of view, enabling Euclid to detect extended surface brightness structures below μlimâ =â 31 mag arcsec-2 and beyond

Euclid preparation: XV. Forecasting cosmological constraints for the Euclid and CMB joint analysis

The combination and cross-correlation of the upcoming Euclid data with cosmic microwave background (CMB) measurements is a source of great expectation since it will provide the largest lever arm of epochs, ranging from recombination to structure formation across the entire past light cone. In this work, we present forecasts for the joint analysis of Euclid and CMB data on the cosmological parameters of the standard cosmological model and some of its extensions. This work expands and complements the recently published forecasts based on Euclid-specific probes, namely galaxy clustering, weak lensing, and their cross-correlation. With some assumptions on the specifications of current and future CMB experiments, the predicted constraints are obtained from both a standard Fisher formalism and a posterior-fitting approach based on actual CMB data. Compared to a Euclid-only analysis, the addition of CMB data leads to a substantial impact on constraints for all cosmological parameters of the standard Λ-cold-dark-matter model, with improvements reaching up to a factor of ten. For the parameters of extended models, which include a redshift-dependent dark energy equation of state, non-zero curvature, and a phenomenological modification of gravity, improvements can be of the order of two to three, reaching higher than ten in some cases. The results highlight the crucial importance for cosmological constraints of the combination and cross-correlation of Euclid probes with CMB data