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Biodiversity continues to decline in the face of increasing anthropogenic pressures such as habitat destruction, exploitation, pollution and introduction of alien species. Existing global databases of species' threat status or population time series are dominated by charismatic species. The collation of datasets with broad taxonomic and biogeographic extents, and that support computation of a range of biodiversity indicators, is necessary to enable better understanding of historical declines and to project - and avert - future declines. We describe and assess a new database of more than 1.6 million samples from 78 countries representing over 28,000 species, collated from existing spatial comparisons of local-scale biodiversity exposed to different intensities and types of anthropogenic pressures, from terrestrial sites around the world. The database contains measurements taken in 208 (of 814) ecoregions, 13 (of 14) biomes, 25 (of 35) biodiversity hotspots and 16 (of 17) megadiverse countries. The database contains more than 1% of the total number of all species described, and more than 1% of the described species within many taxonomic groups - including flowering plants, gymnosperms, birds, mammals, reptiles, amphibians, beetles, lepidopterans and hymenopterans. The dataset, which is still being added to, is therefore already considerably larger and more representative than those used by previous quantitative models of biodiversity trends and responses. The database is being assembled as part of the PREDICTS project (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems - ). We make site-level summary data available alongside this article. The full database will be publicly available in 2015.
Background: We evaluated the effect of insulin stimulation and dietary changes on myocardial, skeletal muscle and brain [18F]-fluorodeoxyglucose (FDG) kinetics and uptake in vivo in intact mice. Methods: Mice were anesthetized with isoflurane and imaged under different conditions: non-fasted (n = 7; "controls"), non-fasted with insulin (2 IU/kg body weight) injected subcutaneously immediately prior to FDG (n = 6), fasted (n = 5), and fasted with insulin injection (n = 5). A 60-min small-animal PET with serial blood sampling and kinetic modeling was performed. Results: We found comparable FDG standardized uptake values (SUVs) in myocardium in the non-fasted controls and non-fasted-insulin injected group (SUV 45-60 min, 9.58 ± 1.62 vs. 9.98 ± 2.44; p = 0.74), a lower myocardial SUV was noted in the fasted group (3.48 ± 1.73; p < 0.001). In contrast, the FDG uptake rate constant (Ki) for myocardium increased significantly by 47% in non-fasted mice by insulin (13.4 ± 3.9 ml/min/100 g vs. 19.8 ± 3.3 ml/min/100 g; p = 0.030); in fasted mice, a lower myocardial Ki as compared to controls was observed (3.3 ± 1.9 ml/min/100 g; p < 0.001). Skeletal muscle SUVs and Ki values were increased by insulin independent of dietary state, whereas in the brain, those parameters were not influenced by fasting or administration of insulin. Fasting led to a reduction in glucose metabolic rate in the myocardium (19.41 ± 5.39 vs. 3.26 ± 1.97 mg/min/100 g; p < 0.001), the skeletal muscle (1.06 ± 0.34 vs. 0.34 ± 0.08 mg/min/100 g; p = 0.001) but not the brain (3.21 ± 0.53 vs. 2.85 ± 0.25 mg/min/100 g; p = 0.19). Conclusions: Changes in organ SUVs, uptake rate constants and metabolic rates induced by fasting and insulin administration as observed in intact mice by small-animal PET imaging are consistent with those observed in isolated heart/muscle preparations and, more importantly, in vivo studies in larger animals and in humans. When assessing the effect of insulin on the myocardial glucose metabolism of non-fasted mice, it is not sufficient to just calculate the SUV - dynamic imaging with kinetic modeling is necessary.