Influence of calcium ions in the flow cytometric analysis of human CD8‐positive cells
Bibliographic record
Abstract
BACKGROUND: The CD8 co-receptor is an important marker used to identify various lymphocyte subsets. A significant decrease in CD8alpha staining intensity was observed in the presence of divalent cation chelators. METHODS: Peripheral blood mononuclear cells (PBMC) obtained from healthy volunteers were treated with calcium chelators, stained with different anti-human CD8 mAbs, and analyzed by flow cytometry. RESULTS: Calcium chelators caused a dose-dependent decrease in fluorescence intensity, using specific anti-human CD8alpha mAbs. This phenomenon was not due to CD8 internalization and could be reversed by the addition of calcium ions. In contrast, calcium depletion increased staining intensity with one anti-CD8beta mAb. CONCLUSIONS: Divalent cation chelators are used as cell anti-clumping agents in MACS or FACS applications. Researchers should be aware that such treatment could lead to the almost complete loss of fluorescence with selected anti-human CD8alpha mAbs. Since CD8 staining is used in conjunction with tetramer staining to identify antigen-specific cytotoxic human T cells, the effect of calcium depletion should be taken into account in experimental design.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".