Eadie-Hofstee analysis of red blood cell deformability
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Bibliographic record
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.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it