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    A simplified empirical approach to evaluate the dissociation constant of a full agonist by the irreversible receptor inactivation method

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    The estimation of the dissociation constant (Ka) of full agonists represents an essential tool for the classification of drugs and drug receptors, in functional pharmacology. The evaluation of the Ka was a problem until the development of the Furchgott's method (irreversible partial receptor inactivation method), which surely represents the most used analysis for the evaluation of the agonist Ka in experimental protocols on isolated tissues. The Furchgott's method can furnish a reliable estimation of the Ka, but it requires a relatively complicated manipulation of experimental data. In this article, an alternative approach for the evaluation of the Ka is proposed, on the basis of empirical considerations. This method, also based on the partial alkylation of a fraction of receptors, needs only the knowledge of the location parameters of the concentration-response curves and the application of a very simple equation, without any complicated intermediate interpolation of the experimental data

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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