Glucocorticoids (GCs) are commonly used to treat inflammatory disease; unfortunately, the long-term use of these steroids leads to a large number of debilitating side effects. The antiinflammatory effects of GCs are a result of GC receptor (GR)-mediated inhibition of expression of proinflammatory genes as well as GR-mediated activation of antiinflammatory genes. Similarly, side effects are most likely due to both activated and repressed GR target genes in affected tissues. An as yet unachieved pharmaceutical goal is the development of a compound capable of separating detrimental side effects from antiinflammatory activity. We describe the discovery and characterization of AL-438, a GR ligand that exhibits an altered gene regulation profile, able to repress and activate only a subset of the genes normally regulated by GCs. When tested in vivo, AL-438 retains full antiinflammatory efficacy and potency comparable to steroids but its negative effects on bone metabolism and glucose control are reduced at equivalently antiinflammatory doses. The mechanism underlying this selective in vitro and in vivo activity may be the result of differential cofactor recruitment in response to ligand. AL-438 reduces the interaction between GR and peroxisomal proliferator-activated receptor gamma coactivator-1, a cofactor critical for steroid-mediated glucose up-regulation, while maintaining normal interactions with GR-interacting protein 1. This compound serves as a prototype for a unique, nonsteroidal alternative to conventional GCs in treating inflammatory disease.

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This study explores the discrepancies of storm surge predictions driven by the parametric wind model and the numerical weather prediction model. Serving as a leading-order storm wind predictive tool, the parametric Holland wind model provides the frictional-free, steady-state, and geostrophic-balancing solutions. On the other hand, WRF-ARW (Weather Research and Forecasting-Advanced Research WRF) provides the results solving the 3D time-integrated, compressible, and non-hydrostatic Euler equations, but time-consuming. To shed light on their discrepancies for storm surge predictions, the storm surges of 2013 Typhoon Haiyan in the Leyte Gulf and the San Pedro Bay are selected. The Holland wind model predicts strong southeastern winds in the San Pedro Bay after Haiyan makes landfall at the Leyte Island than WRF-ARW 3 km and WRF-ARW 1 km. The storm surge simulation driven by the Holland wind model finds that the water piles up in the San Pedro Bay and its maximum computed storm surges are almost twice than those driven by WRF-ARW. This study also finds that the storm surge prediction in the San Pedro Bay is sensitive to winds, which can be affected by the landfall location, the storm intensity, and the storm forward speed. The numerical experiment points out that the maximum storm surges can be amplified by more 5–6% inside the San Pedro Bay if Haiyan’s forward speed is increased by 10%.

The title compounds were synthesized by replacing the thiophene moiety of A-86929(2a) with variously substituted pyridines. Dopamine D-1 and D-2 binding and adenylate cyclase assays indicate that 4,6-diaza compounds 15 are potent and selective full D1 agonists when R1 is H or a small substituent and R2 = H, with D1 binding affinity and adenylate cyclase functional potency equivalent to that of A-86929(2a).

Abstract:In this paper, we propose a current mode linear CMOS temperature sensor profiting on increasing the accuracy of thermal monitoring. Concerning the temperature dependence of threshold voltage drift and mobility degradation, the proposed method removes the critical nonlinear terms realizing very linear relationship. Through driving two temperature-dependent current sources into particular operation region with different bias conditions, we utilize a compensation scheme among the resulted complementary temperature dependences of current sources which cancels major nonlinear effect. By TSMC 0.35 μm CMOS process, within the temperature range from −20 • C to 100 • C, the measured results of an implemented chip show that temperature error and power consumption are ±0. Syst., vol. 5, no. 3, pp. 270-276, Sept. 1997. [4] M. Sasaki, M. Ikeda, and K. Asada, "A temperature sensor with an inaccuracy of −1/ + 0.8 • C using 90-nm 1-V CMOS for online thermal monitoring of VLSI circuits,"