Design and synthesis of pyrazole derivatives against neutrophilic inflammation.

Neutrophils are the most abundant immune cells. However, neutrophil dysregulation leads to acute and chronic inflammation and is involved in various diseases. The aim of this study was to develop anti-inflammatory agents in human neutrophils. A drug screening was conducted on in-house compounds with the potential to inhibit the respiratory burst, which involves the generation of superoxide anions in human neutrophils. Bioisosteric replacement was then applied to design more active derivatives. The most potent inhibitors of superoxide anion generation activity were compounds 58 and 59, which had IC50 values of 13.30 and 9.06 nM, respectively. The inhibitory effects of 58 and 59 were reversed by H89, a PKA inhibitor. PDE selective screening indicated that the best inhibitory effects were PDE4B1 and PDE4D2, and the inhibitory activities were 83% and 85%, respectively, at a 10 µM concentration of 59. The final molecular simulation experiment highlighted the slightly different binding poses of 58 and 59 in the PDE4 active site. An in vivo pharmacokinetic study revealed that the half-life of 59 was approximately 79 min when using intravenous bolus administration. This work introduced a new class structure of PDE4 inhibitors resulting in potent neutrophil inactivation activity, with the aim of contributing to new anti-inflammatory drug discovery.

An Investigation to Manufacturing Analytical Services Composition using the Analytical Target Cascading Method.

As cloud computing is increasingly adopted, the trend is to offer software functions as modular services and compose them into larger, more meaningful ones. The trend is attractive to analytical problems in the manufacturing system design and performance improvement domain because 1) finding a global optimization for the system is a complex problem; and 2) sub-problems are typically compartmentalized by the organizational structure. However, solving sub-problems by independent services can result in a sub-optimal solution at the system level. This paper investigates the technique called Analytical Target Cascading (ATC) to coordinate the optimization of loosely-coupled sub-problems, each may be modularly formulated by differing departments and be solved by modular analytical services. The result demonstrates that ATC is a promising method in that it offers system-level optimal solutions that can scale up by exploiting distributed and modular executions while allowing easier management of the problem formulation.