Cutting Edge: Detection of Antigen-Specific CD4+ T Cells by HLA-DR1 Oligomers Is Dependent on the T Cell Activation State
Bibliographic record
Abstract
Class I MHC tetramers have proven to be invaluable tools for following and deciphering the CD8(+) T cell response, but the development of similar reagents for detection of CD4(+) T cells based on class II MHC proteins has been more difficult. We evaluated fluorescent streptavidin-based oligomers of HLA-DR1 for use as reagents to analyze Ag-specific human CD4(+) T cells. Staining was blocked at low temperatures and by drugs that disrupt microfilament formation and endocytosis. Cell-associated MHC oligomers were resistant to a surface stripping protocol and were observed by microscopy in intracellular compartments. This behavior indicates that detection of CD4(+) T cells using class II MHC oligomers can depend on an active cellular process in which T cells cluster and/or endocytose their Ag receptors. T cells of identical specificity but in different activation states varied greatly in their ability to be detected by class II MHC oligomers.
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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 | 0.000 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".