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Eltrombopag, an oral, small-molecule, nonpeptide thrombopoietin receptor agonist for the treatment of thrombocytopenia, is highly protein bound and primarily eliminated via metabolism in the liver and gastrointestinal tract. Single-dose eltrombopag pharmacokinetics were evaluated in participants with hepatic or renal impairment given possible changes in systemic exposure due to reduced plasma protein binding or reduced metabolism. All participants received a single 50-mg dose of eltrombopag. The adverse event profile was similar across groups, with headache, nausea, and back pain most frequently reported. Compared with healthy participants, participants with mild, moderate, or severe hepatic impairment had mean increases in AUC0-∞ of 41%, 93%, and 80%, and participants with mild, moderate, or severe renal impairment had mean decreases in AUC0-∞ of 32%, 36%, and 60%. There was high pharmacokinetic variability and significant overlap in exposures between participants with hepatic or renal impairment and healthy participants. Results suggest that patients with renal impairment may initiate eltrombopag with the standard 50-mg once-daily starting regimen, whereas patients with moderate or severe hepatic impairment should consider a lower 25-mg once-daily regimen. Patients with hepatic or renal impairment should be closely monitored for platelet response and safety, and eltrombopag doses should be adjusted accordingly. [ABSTRACT FROM PUBLISHER]

• Machine learning algorithms have been applied to estimate wheat yield for Australia. • Combining climate and satellite data achieves high performance for yield prediction. • The unique and overlapping information of climate and satellite data is quantified. • Optimal prediction performance can be achieved two-month lead time before maturity. Wheat is the most important staple crop grown in Australia, and Australia is one of the top wheat exporting countries globally. Timely and reliable wheat yield prediction in Australia is important for regional and global food security. Prior studies use either climate data, or satellite data, or a combination of these two to build empirical models to predict crop yield. However, though the performance of yield prediction using empirical methods is improved by combining the use of climate and satellite data, the contributions from different data sources are still not clear. In addition, how the regression-based methods compare with various machine-learning based methods in their performance in yield prediction is also not well understood and needs in-depth investigation. This work integrated various sources of data to predict wheat yield across Australia from 2000 to 2014 at the statistical division (SD) level. We adopted a well-known regression method (LASSO, as a benchmark) and three mainstream machine learning methods (support vector machine, random forest, and neural network) to build various empirical models for yield prediction. For satellite data, we used the enhanced vegetation index (EVI) from MODIS and solar-induced chlorophyll fluorescence (SIF) from GOME-2 and SCIAMACHY as metrics to approximate crop productivity. The machine-learning based methods outperform the regression method in modeling crop yield. Our results confirm that combining climate and satellite data can achieve high performance of yield prediction at the SD level (R2 ˜ 0.75). The satellite data track crop growth condition and gradually capture the variability of yield evolving with the growing season, and their contributions to yield prediction usually saturate at the peak of the growing season. Climate data provide extra and unique information beyond what the satellite data have offered for yield prediction, and our empirical modeling work shows the added values of climate variables exist across the whole season, not only at some certain stages. We also find that using EVI as an input can achieve better performance in yield prediction than SIF, primarily due to the large noise in the satellite-based SIF data (i.e. coarse resolution in both space and time). In addition, we also explored the potential for timely wheat yield prediction in Australia, and we can achieve the optimal prediction performance with approximately two-month lead time before wheat maturity. The proposed methodology in this paper can be extended to different crops and different regions for crop yield prediction. [ABSTRACT FROM AUTHOR]

Background and Purpose: The Intensive Blood Pressure Reduction In Acute Cerebral Haemorrhage Trial (INTERACT) study suggests that early intensive blood pressure (BP) lowering can attenuate hematoma growth at 24 hours after intracerebral hemorrhage. The present analyses aimed to determine the effects of treatment on hematoma and perihematomal edema over 72 hours., Methods: INTERACT included 404 patients with CT-confirmed intracerebral hemorrhage, elevated systolic BP (150 to 220 mm Hg), and capacity to start BP-lowering treatment within 6 hours of intracerebral hemorrhage. Patients were randomly assigned to an intensive (target systolic BP 140 mmHg) or standard guideline-based management of BP (target systolic BP 180 mm Hg) using routine intravenous agents. Baseline and repeat CTs (24 and 72 hours) were performed using standardized techniques with digital images analyzed centrally. Outcomes were increases in hematoma and perihematomal edema volumes over 72 hours., Results: Overall, 296 patients had all 3 CT scans available for the hematoma and 270 for the edema analyses. Mean systolic BP was 11.7 mm Hg lower in the intensive group than in the guideline group during 1 to 24 hours. Adjusted mean absolute increases in hematoma volumes (mL) at 24 and 72 hours were 2.40 and 0.15 in the guideline group compared with -0.74 and -2.31 in the intensive group, respectively, an overall difference of 2.80 (95% CI, 1.04 to 4.56; P=0.002). Adjusted mean absolute increases in edema volumes (mL) at 24 and 72 hours were 6.27 and 10.02 in the guideline group compared with 4.19 and 7.34 in the intensive group, respectively, for an overall difference of 2.38 (95% CI, -0.45 to 5.22; P=0.10)., Conclusions: Early intensive BP-lowering treatment attenuated hematoma growth over 72 hours in intracerebral hemorrhage. There were no appreciable effects on perihematomal edema.