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- Prusti, T., et al.
(author)
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The Gaia mission
- 2016
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In: Astronomy and Astrophysics. - : EDP Sciences. - 0004-6361 .- 1432-0746. ; 595
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Journal article (peer-reviewed)abstract
- Gaia is a cornerstone mission in the science programme of the European Space Agency (ESA). The spacecraft construction was approved in 2006, following a study in which the original interferometric concept was changed to a direct-imaging approach. Both the spacecraft and the payload were built by European industry. The involvement of the scientific community focusses on data processing for which the international Gaia Data Processing and Analysis Consortium (DPAC) was selected in 2007. Gaia was launched on 19 December 2013 and arrived at its operating point, the second Lagrange point of the Sun-Earth-Moon system, a few weeks later. The commissioning of the spacecraft and payload was completed on 19 July 2014. The nominal five-year mission started with four weeks of special, ecliptic-pole scanning and subsequently transferred into full-sky scanning mode. We recall the scientific goals of Gaia and give a description of the as-built spacecraft that is currently (mid-2016) being operated to achieve these goals. We pay special attention to the payload module, the performance of which is closely related to the scientific performance of the mission. We provide a summary of the commissioning activities and findings, followed by a description of the routine operational mode. We summarise scientific performance estimates on the basis of in-orbit operations. Several intermediate Gaia data releases are planned and the data can be retrieved from the Gaia Archive, which is available through the Gaia home page.
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- Brown, A. G. A., et al.
(author)
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Gaia Data Release 1 Summary of the astrometric, photometric, and survey properties
- 2016
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In: Astronomy and Astrophysics. - : EDP Sciences. - 0004-6361 .- 1432-0746. ; 595
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Journal article (peer-reviewed)abstract
- 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 similar to 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 similar to 0.3 mas should be added to the parallax uncertainties. For the subset of similar to 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 similar to 10 mas. The median uncertainties on the mean G-band magnitudes range from the mmag level to similar 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.
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| 5. |
- Jiang, LQ, et al.
(author)
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Diacylglycerol kinase-δ regulates AMPK signaling, lipid metabolism, and skeletal muscle energetics
- 2016
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In: American journal of physiology. Endocrinology and metabolism. - : American Physiological Society. - 1522-1555 .- 0193-1849. ; 310:1, s. E51-E60
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Journal article (peer-reviewed)abstract
- Decrease of AMPK-related signal transduction and insufficient lipid oxidation contributes to the pathogenesis of obesity and type 2 diabetes. Previously, we identified that diacylglycerol kinase-δ (DGKδ), an enzyme involved in triglyceride biosynthesis, is reduced in skeletal muscle from type 2 diabetic patients. Here, we tested the hypothesis that DGKδ plays a role in maintaining appropriate AMPK action in skeletal muscle and energetic aspects of contraction. Voluntary running activity was reduced in DGKδ+/−mice, but glycogen content and mitochondrial markers were unaltered, suggesting that DGKδ deficiency affects skeletal muscle energetics but not mitochondrial protein abundance. We next determined the role of DGKδ in AMPK-related signal transduction and lipid metabolism in isolated skeletal muscle. AMPK activation and signaling were reduced in DGKδ+/−mice, concomitant with impaired lipid oxidation and elevated incorporation of free fatty acids into triglycerides. Strikingly, DGKδ deficiency impaired work performance, as evident by altered force production and relaxation dynamics in response to repeated contractions. In conclusion, DGKδ deficiency impairs AMPK signaling and lipid metabolism, thereby highlighting the deleterious role of excessive lipid metabolites in the development of peripheral insulin resistance and type 2 diabetes pathogenesis. DGKδ deficiency also influences skeletal muscle energetics, which may lead to low physical activity levels in type 2 diabetes.
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