Delayed expansion of a restricted T cell repertoire by low-density TCR ligands
Bibliographic record
Abstract
The role of TCR ligand density (i.e. the number of antigen-MHC complexes) in modulating the diversity of a T cell response selected from a pool of naive precursors remains largely undefined. By measuring early-activation markers up-regulation and proliferation following stimulation with staphylococcal enterotoxin A (SEA), we demonstrate that decreasing the ligand dose below an optimal concentration leads to the delayed activation of a restricted set of TCRVbeta-bearing T cells, with the specific, non-stochastic exclusion of some TCRVbeta+ T cells from the activated pool. Our results suggest that the failure of these TCRVbeta-bearing T cells to reach the activation threshold at sub-optimal ligand concentration is due to the inefficiency of TCR engagement, as measured by TCR internalization, and does not correlate with the relative precursor frequency in the non-immune repertoire. Moreover, even at SEA concentrations that lead to the simultaneous proliferation of all SEA-reactive T cells, we observe marked differences in the ability to secrete cytokines among the different responsive TCRVbeta-bearing T cells. Altogether, our results indicate that the development of a T cell response to a scarce display of ligand significantly narrows TCR repertoire diversity by mechanisms that involve focusing of the repertoire on the expansion of those T cells with the highest avidity of TCR engagement.
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How this classification was reachedexpand
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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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; both teacher heads agree on what is shown here.
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".