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Anthocyanins and proanthocyanins (PAs) are two end products of the flavonoid biosynthesis pathway. They are believed to be synthesized in the endoplasmic reticulum and then sequestered into the vacuole. In Arabidopsis thaliana, TRANSPARENT TESTA 19 (TT19) is necessary for both anthocyanin and PA accumulation. Here, we found that MtGSTF7, a homolog of AtTT19, is essential for anthocyanin accumulation but not required for PA accumulation in Medicago truncatula. MtGSTF7 was induced by the anthocyanin regulator LEGUME ANTHOCYANIN PRODUCTION 1 (LAP1), and its tissue expression pattern correlated with anthocyanin deposition in M. truncatula. Tnt1-insertional mutants of MtGSTF7 lost anthocyanin accumulation in vegetative organs, and introducing a genomic fragment of MtGSTF7 could complement the mutant phenotypes. Additionally, the accumulation of anthocyanins induced by LAP1 was significantly reduced in mtgstf7 mutants. Yeast-one-hybridization and dual-luciferase reporter assays revealed that LAP1 could bind to the MtGSTF7 promoter to activate its expression. Ectopic expression of MtGSTF7 in tt19 mutants could rescue their anthocyanin deficiency, but not their PA defect. Furthermore, PA accumulation was not affected in the mtgstf7 mutants. Taken together, our results show that the mechanism of anthocyanin and PA accumulation in M. truncatula is different from that in A. thaliana, and provide a new target gene for engineering anthocyanins in plants.

 

Severe winds produced by thunderstorm downbursts pose a serious risk to the structural integrity of wind turbines. However, guidelines for wind turbine design (such as the International Electrotechnical Commission Standard, IEC 61400-1) do not describe the key physical characteristics of such events realistically. In this study, a large-eddy simulation model is employed to generate several idealized downburst events during contrasting atmospheric stability conditions that range from convective through neutral to stable. Wind and turbulence fields generated from this dataset are then used as inflow for a 5-MW land-based wind turbine model; associated turbine loads are estimated and compared for the different inflow conditions. We first discuss time-varying characteristics of the turbine-scale flow fields during the downbursts; next, we investigate the relationship between the velocity time series and turbine loads as well as the influence and effectiveness of turbine control systems (for blade pitch and nacelle yaw). Finally, a statistical analysis is conducted to assess the distinct influences of the contrasting stability regimes on extreme and fatigue loads on the wind turbine. 

Abstract Many measurements at the LHC require efficient identification of heavy-flavour jets, i.e. jets originating from bottom (b) or charm (c) quarks. An overview of the algorithms used to identify c jets is described and a novel method to calibrate them is presented. This new method adjusts the entire distributions of the outputs obtained when the algorithms are applied to jets of different flavours. It is based on an iterative approach exploiting three distinct control regions that are enriched with either b jets, c jets, or light-flavour and gluon jets. Results are presented in the form of correction factors evaluated using proton-proton collision data with an integrated luminosity of 41.5 fb -1 at  √s = 13 TeV, collected by the CMS experiment in 2017. The closure of the method is tested by applying the measured correction factors on simulated data sets and checking the agreement between the adjusted simulation and collision data. Furthermore, a validation is performed by testing the method on pseudodata, which emulate various mismodelling conditions. The calibrated results enable the use of the full distributions of heavy-flavour identification algorithm outputs, e.g. as inputs to machine-learning models. Thus, they are expected to increase the sensitivity of future physics analyses.