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https://www.selleckchem.com/products/SNS-032.html Many plant water use models predict leaves maximize carbon assimilation while minimizing water loss via transpiration. Alternate scenarios may occur at high temperature, including heat avoidance, where leaves increase water loss to evaporatively cool regardless of carbon uptake; or heat failure, where leaves non-adaptively lose water also regardless of carbon uptake. We hypothesized that these alternative scenarios are common in species exposed to hot environments, with heat avoidance more common in species with high construction cost leaves. Diurnal measurements of leaf temperature and gas exchange for 11 Sonoran Desert species revealed that 37% of these species increased transpiration in the absence of increased carbon uptake. High leaf mass per area partially predicted this behaviour (r2 = 0.39). These data are consistent with heat avoidance and heat failure, but failure is less likely given the ecological dominance of the focal species. These behaviours are not yet captured in any extant plant water use model.Dynamic combinatorial libraries (DCLs) is a powerful tool for ligand discovery in biomedical research; however, the application of DCLs has been hampered by their low diversity. Recently, the concept of DNA encoding has been employed in DCLs to create DNA-encoded dynamic libraries (DEDLs); however, all current DEDLs are limited to fragment identification, and a challenging process of fragment linking is required after selection. We report an anchor-directed DEDL approach that can identify full ligand structures from large-scale DEDLs. This method is also able to convert unbiased libraries into focused ones targeting specific protein classes. We demonstrated this method by selecting DEDLs against five proteins, and novel inhibitors were identified for all targets. Notably, several selective BD1/BD2 inhibitors were identified from the selections against bromodomain 4 (BRD4), an important anti-cancer drug targe
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