Objective:The paper aims at developing a method of defining and visualizing the scope of the basic medical insurance pharmacy service, and provides a new way of thinking for the designated pharmacy planning. Methods:Collecting the basic data and information on administrative divisions in the planning area taking equity and efficiency as the guidance, using ArcGIS and its function modules to define and visualize the scope of the medical in-surance pharmacy service. The procedure of issue focus, method improvement, data simulation, expert consultation, methodology perfecting were followed to define and visualize the scope. Results:Forming a whole set of operative pro-cedures of defining and visualizing the scope of the medical insurance pharmacy service based on medical resources allocation standard, and the operation commands and procedures in ArcGIS were clarified. Conclusion:Operating ac-cording to the appropriate method steps, the following can be achieved:(1) The adjacent scope of medical insurance pharmacy service are adjacent to each other but do not overlap or cross;(2) Spatial relations can be clearly and ef-fectively expressed;(3) The shape is flat and regular;(4) The data collected at different times can be comparable in space, providing good prerequisites for medical insurance designated pharmacy planning.

G protein-coupled receptors (GPCRs) are involved in all human physiological systems where they are responsible for transducing extracellular signals into cells. GPCRs signal in response to a diverse array of stimuli including light, hormones, and lipids, where these signals affect downstream cascades to impact both health and disease states. Yet, despite their importance as therapeutic targets, detailed molecular structures of only 30 GPCRs have been determined to date. A key challenge to their structure determination is adequate protein expression. Here we report the quantification of protein expression in an insect cell expression system for all 826 human GPCRs using two different fusion constructs. Expression characteristics are analyzed in aggregate and among each of the five distinct subfamilies. These data can be used to identify trends related to GPCR expression between different fusion constructs and between different GPCR families, and to prioritize lead candidates for future structure determination feasibility.
Animals ; Computational Biology ; Crystallography, X-Ray ; Gene Expression ; Humans ; Plasmids ; genetics ; metabolism ; Protein Domains ; Receptors, Adrenergic, beta-1 ; Receptors, G-Protein-Coupled ; classification ; genetics ; metabolism ; Receptors, Odorant ; metabolism ; Receptors, Purinergic P1 ; genetics ; metabolism ; Sf9 Cells ; Spodoptera