Human CD4<sup>+</sup> lymphocytes for antigen quantification: Characterization using conventional flow cytometry and mass cytometry
Bibliographic record
Abstract
To transform the linear fluorescence intensity scale obtained with fluorescent microspheres to an antibody bound per cell (ABC) scale, a biological cell reference material is needed. Optimally, this material should have a reproducible and tight ABC value for the expression of a known clinical reference biomarker. In this study, we characterized commercially available cryopreserved peripheral blood mononuclear cells (PBMCs) and two lyophilized PBMC preparations, Cyto-Trol and PBMC-National Institute for Biological Standard and Control (NIBSC) relative to freshly prepared PBMC and whole blood samples. It was found that the ABC values for CD4 expression on cryopreserved PBMC were consistent with those of freshly obtained PBMC and whole blood samples. By comparison, the ABC value for CD4 expression on Cyto-Trol is lower and the value on PBMC-NIBSC is much lower than those of freshly prepared cell samples using both conventional flow cytometry and CyTOF™ mass cytometry. By performing simultaneous surface and intracellular staining measurements on these two cell samples, we found that both cell membranes are mostly intact. Moreover, CD4(+) cell diameters from both lyophilized cell preparations are smaller than those of PBMC and whole blood. This could result in steric interference in antibody binding to the lyophilized cells. Further investigation of the fixation effect on the detected CD4 expression suggests that the very low ABC value obtained for CD4(+) cells from lyophilized PBMC-NIBSC is largely due to paraformaldehyde fixation; this significantly decreases available antibody binding sites. This study provides confirmation that the results obtained from the newly developed mass cytometry are directly comparable to the results from conventional flow cytometry when both methods are standardized using the same ABC approach.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".