title: Eadie-Hofstee analysis of red blood cell deformability.
abstract: In recent years, linear data transformation has become an accepted method to simplify the analysis of red blood cell (RBC) deformability curves obtained by ektacytometry. In this study, we introduce the Eadie-Hofstee transformation as an alternative linearization method for the analysis of RBC deformability. RBCs were treated with hydrogen peroxide (H(2)O(2)), tert-butyl-hydroperoxide (t-BuOOH), or methyl β-cyclodextrin (MβCD) and analyzed via ektacytometry (LORCA). RBC hemopathological clinical isolates (hereditary spherocytosis and α-thalassemia) were also analyzed by LORCA. Following ektacytometry, Eadie-Hofstee linearization was performed to obtain the maximum deformability (EI(max)) and shear stress at half maximal deformation (K(EI)) parameters. Significant changes in deformability parameters were observed with all agents tested. For H(2)O(2) and t-BuOOH, the K(EI) values increased significantly accompanied by marginal changes in EI(max), while treatment with MβCD resulted in a dose dependant decrease in EI(max). Contrasting deformability profiles were also observed in the two hematological disorders tested. In this study we have demonstrated the ability of Eadie-Hofstee linearization to detect and resolve changes in RBC deformability induced in vitro as well as deformability changes associated with in vivo hematological disorders. This technique shows promise in basic research, blood bank and clinical hematology settings.
authors.affiliation: Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Canada.
authors.forename: H
authors.initials: H
authors.lastname: Stadnick
authors.forename: R
authors.initials: R
authors.lastname: Onell
authors.forename: J P
authors.initials: JP
authors.lastname: Acker
authors.forename: J L
authors.initials: JL
authors.lastname: Holovati
mesh_terms: D004907:Erythrocyte Deformability / Q000502:physiology*; D004912:Erythrocytes / Q000737:chemistry* / Q000187:drug effects; D006801:Humans; D016014:Linear Models; D008954:Models, Biological