Spanish National Research Council

About: Spanish National Research Council is a government organization based out in Madrid, Spain. It is known for research contribution in the topics: Population & Galaxy. The organization has 79563 authors who have published 220470 publications receiving 7698991 citations. The organization is also known as: CSIC & Consejo Superior de Investigaciones Científicas.

Oxidative dyhydrogenation of short chain alkanes on supported vanadium oxide catalysts

Abstract: This paper summarizes the main data appeared in the last years on the oxidative dehydrogenation (ODH) of short chain alkanes on supported vanadium oxide catalysts. The acid-base character of metal oxide support influences the dispersion of vanadium on the surface of the support, as well as the nature of the vanadium species. The reducibility and structure of surface vanadium oxide species and the acid-base character of catalysts, in addition to their catalytic properties in the ODH of C2–C4 alkanes, strongly depend on the metal oxide used as support and the vanadium loading. In this way, it appears that tetrahedral V5+-species are active and selective sites in the ODH of C2–C4 alkanes. The effect of the coordination number and aggregation state of surface vanadium oxide species, and the presence of acid/base sites on the catalytic behavior of supported vanadium oxide catalysts are discussed. It is concluded that these are important factors that must be considered to develop selective catalysts in ODH reactions.

Cannabinoid action induces autophagy-mediated cell death through stimulation of ER stress in human glioma cells

Abstract: Autophagy can promote cell survival or cell death, but the molecular basis underlying its dual role in cancer remains obscure. Here we demonstrate that delta(9)-tetrahydrocannabinol (THC), the main active component of marijuana, induces human glioma cell death through stimulation of autophagy. Our data indicate that THC induced ceramide accumulation and eukaryotic translation initiation factor 2alpha (eIF2alpha) phosphorylation and thereby activated an ER stress response that promoted autophagy via tribbles homolog 3-dependent (TRB3-dependent) inhibition of the Akt/mammalian target of rapamycin complex 1 (mTORC1) axis. We also showed that autophagy is upstream of apoptosis in cannabinoid-induced human and mouse cancer cell death and that activation of this pathway was necessary for the antitumor action of cannabinoids in vivo. These findings describe a mechanism by which THC can promote the autophagic death of human and mouse cancer cells and provide evidence that cannabinoid administration may be an effective therapeutic strategy for targeting human cancers.

Predicting extinction risks under climate change: coupling stochastic population models with dynamic bioclimatic habitat models.

Abstract: Species responses to climate change may be influenced by changes in available habitat, as well as population processes, species interactions and interactions between demographic and landscape dynamics. Current methods for assessing these responses fail to provide an integrated view of these influences because they deal with habitat change or population dynamics, but rarely both. In this study, we linked a time series of habitat suitability models with spatially explicit stochastic population models to explore factors that influence the viability of plant species populations under stable and changing climate scenarios in South African fynbos, a global biodiversity hot spot. Results indicate that complex interactions between life history, disturbance regime and distribution pattern mediate species extinction risks under climate change. Our novel mechanistic approach allows more complete and direct appraisal of future biotic responses than do static bioclimatic habitat modelling approaches, and will ultimately support development of more effective conservation strategies to mitigate biodiversity losses due to climate change.

Gaia Early Data Release 3: Photometric content and validation

Abstract: Gaia Early Data Release 3 contains astrometry and photometry results for about 1.8 billion sources based on observations collected by the ESA Gaia satellite during the first 34 months of operations. This paper focuses on the photometric content, describing the input data, the algorithms, the processing, and the validation of the results. Particular attention is given to the quality of the data and to a number of features that users may need to take into account to make the best use of the EDR3 catalogue. The treatment of the BP and RP background has been updated to include a better estimation of the local background, and the detection of crowding effects has been used to exclude affected data from the calibrations. The photometric calibration models have also been updated to account for flux loss over the whole magnitude range. Significant improvements in the modelling and calibration of the point and line spread functions have also helped to reduce a number of instrumental effects that were still present in DR2. EDR3 contains 1.806 billion sources with G-band photometry and 1.540 billion sources with BP and RP photometry. The median uncertainty in the G-band photometry, as measured from the standard deviation of the internally calibrated mean photometry for a given source, is 0.2 mmag at magnitude G=10 to 14, 0.8 mmag at G=17, and 2.6 mmag at G=19. The significant magnitude term found in the Gaia DR2 photometry is no longer visible, and overall there are no trends larger than 1 mmag/mag. Using one passband over the whole colour and magnitude range leaves no systematics above the 1% level in magnitude in any of the bands, and a larger systematic is present for a very small sample of bright and blue sources. A detailed description of the residual systematic effects is provided. Overall the quality of the calibrated mean photometry in EDR3 is superior with respect to DR2 for all bands.