Aggregation Limits Surface Expression of Homomeric GluA3 Receptors

AMPA receptors are glutamate-gated cation channels assembled from GluA1-4 subunits and have properties that are strongly dependent on the subunit composition. The subunits have different propensities to form homomeric or various heteromeric receptors expressed on cell surface, but the underlying mechanisms are still poorly understood. Here, we examined the biochemical basis for the poor ability of GluA3 subunits to form homomeric receptors, linked previously to two amino acid residues, Y454 and R461, in its ligand-binding domain (LBD). Surface expression of GluA3 was improved by co-assembly with GluA2 but not with stargazin, a trafficking chaperone and modulator of AMPA receptors. The secretion efficiency of GluA2 and GluA3 LBDs paralleled the transport difference between the respective full-length receptors and was similarly dependent on Y454/R461, but not on LBD stability. In comparison to GluA2, GluA3 homomeric receptors showed a strong and Y454/R461-dependent tendency to aggregate both in the macroscopic scale measured as lower solubility in nonionic detergent and in the microscopic scale evident as the preponderance of hydrodynamically large structures in density gradient centrifugation and native gel electrophoresis. We conclude that the impaired surface expression of homomeric GluA3 receptors is caused by nonproductive assembly and aggregation to which LBD residues Y454 and R461 strongly contribute. This aggregation inhibits the entry of newly synthesized GluA3 receptors to the secretory pathway.

Context-aware Approach for Determining the Threshold Price in Name-Your-Own-Price Channels

Key feature of a context-aware application is the ability to adapt based on the change of context. Two approaches that are widely used in this regard are the context-action pair mapping where developers match an action to execute for a particular context change and the adaptive learning where a context-aware application refines its action over time based on the preceding action’s outcome. Both these approaches have limitation which makes them unsuitable in situations where a context-aware application has to deal with unknown context changes. In this paper we propose a framework where adaptation is carried out via concurrent multi-action evaluation of a dynamically created action space. This dynamic creation of the action space eliminates the need for relying on the developers to create context-action pairs and the concurrent multi-action evaluation reduces the adaptation time as opposed to the iterative approach used by adaptive learning techniques. Using our reference implementation of the framework we show how it could be used to dynamically determine the threshold price in an e-commerce system which uses the name-your-own-price (NYOP) strategy.