The effects of N-methyl-D-aspartate (NMDA) on opioid receptor-mediated G protein activation were explored in neuroblastoma X glioma hybrid (NG108-15) cells. Treatment of the cells with NMDA resulted in a remarkable attenuation of [35S]guanosine-5'-O-(3-thio)triphosphate binding stimulated by [D-Pen2,D-Pen5]-enkephalin (DPDPE), a delta-opioid receptor agonist. The effects of NMDA were dose and time dependent with an IC50 value of 5 nM and could be blocked by NMDA receptor antagonists. After NMDA treatment, the DPDPE dose-response curve shifted to the right (EC50 value increased approximately 7-fold, from 6 to 40 nM), and the maximal response induced by DPDPE was reduced by approximately 60%. The effects of NMDA were reversible, and the DPDPE response could recover within 60 min. The functional responses of delta-, mu-, and kappa-opioid receptors in primarily cultured neurons also were attenuated significantly by NMDA treatment. The inhibitory effects of NMDA on opioid receptor-mediated G protein activation could be blocked by coadministration of the protein kinase C (PKC) inhibitors or by elimination of the extracellular Ca2+. Correspondingly, NMDA treatment of NG108 cells significantly elevated cellular PKC activity and stimulated Gialpha2 phosphorylation. Transient transfection into NG108-15 cells of the wild-type Gialpha2 and a mutated Gialpha2 (Ser144Ala) resulted in a 2-fold increase in DPDPE-stimulated G protein activation. The DPDPE responses were greatly inhibited by NMDA treatment in the wild-type Gialpha2-transfected cells but much less affected in the mutant Gialpha2-transfected cells. In summary, NMDA attenuates opioid receptor/G protein coupling, and this process requires activation of PKC. 相似文献
Heuristic algorithms (HAs) are widely used in multi-objective reservoir optimal operation (MOROO) due to the rapidity of the calculation and simplicity of their design. The literature usually focuses on one or two categories of HAs and simply reviews the state of the art. To provide an overall understanding and a specific comparison of HAs in MOROO, differential evolution (DE), particle swarm optimisation (PSO), and artificial physics optimisation (APO), which serve as typical examples of the three categories of HAs, are compared in terms of the development and applications using a designed experiment. Besides, the general model with constraints and fitness function, and the solution process using a hybrid feasible domain restoration method and penalty function method are also presented. Taking a designed experiment with multiple scenarios, the mean average of the optimal objective function values, the standard deviation of optimal objective function values, the mean average of the computational time, and population diversity are used for comparisons. Results of the comparisons show that (a) the problem of optimal multipurpose reservoir long-term operation is a mathematic programming problem with narrow feasible region and monotonic objective function; (b) it is easy to obtain the same optimal objective function value, but different optimal solutions using HAs; and (c) comparisons do not result in a clear winner, but DE can be more appropriate for MOROO.
