High‐sensitivity 5‐, 6‐, and 7‐color PNH WBC assays for both Canto II and Navios platforms
Bibliographic record
Abstract
Background Paroxysmal Nocturnal Hemoglobinuria (PNH) is a rare acquired hematopoietic stem cell disorder characterized by an inability to make Glyco‐Phosphatidyl‐Inositol (GPI)‐linked cell surface structures. Fluorescent proaerolysin (FLAER‐Alexa488) is increasingly used to detect GPI‐deficient WBCs by flow cytometry. However, FLAER is not available in all countries and is expensive to obtain in others. An earlier study to compare FLAER‐based and non‐FLAER assays confirmed very good agreement between the two tubes suggesting a cost effective simultaneous evaluation of PNH neutrophils and monocytes is possible without FLAER. Methods We have used a single tube approach with a 7‐color assay comprising FLAER‐CD157‐CD15‐CD64‐CD24‐CD14‐CD45. Conjugates were carefully selected and validated so that stained samples could be analyzed on either 10‐color Navios or 8‐color FACSCanto II platforms. The 6‐color (minus CD14) and 5‐color (minus CD24 and CD14) versions were also developed and compared with our predicate clinical lab 5‐color assay comprising FLAER‐CD157PE‐CD64ECD‐CD15PC5‐CD45PC7. Results/Conclusions CD15‐gated PNH neutrophil clone size was quantified using either FLAER and CD157, FLAER and CD24, or CD157 and CD24. CD64‐gated PNH monocyte clone size was quantified using either FLAER and CD157, FLAER and CD14, or CD157 and CD14. Analysis of >40 PNH samples showed that the FLAER‐based plots derive virtually identical data to the non‐FLAER plot for neutrophils ( R 2 = 1) and monocytes ( R 2 = 0.9999) and that closely similar data can be acquired using both Canto II and Navios platforms with 7‐, 6‐, and 5‐color versions of the assay. Assessment of non‐PNH samples confirmed extremely low background rate of PNH phenotypes (neutrophils and monocytes) with all three approaches. © 2018 International Clinical Cytometry Society
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".