Strength and Numbers: The Role of Affinity and Avidity in the ‘Quality’ of T Cell Tolerance
Bibliographic record
Abstract
The ability of T cells to identify foreign antigens and mount an efficient immune response while limiting activation upon recognition of self and self-associated peptides is critical. Multiple tolerance mechanisms work in concert to prevent the generation and activation of self-reactive T cells. T cell tolerance is tightly regulated, as defects in these processes can lead to devastating disease; a wide variety of autoimmune diseases and, more recently, adverse immune-related events associated with checkpoint blockade immunotherapy have been linked to a breakdown in T cell tolerance. The quantity and quality of antigen receptor signaling depend on a variety of parameters that include T cell receptor affinity and avidity for peptide. Autoreactive T cell fate choices (e.g., deletion, anergy, regulatory T cell development) are highly dependent on the strength of T cell receptor interactions with self-peptide. However, less is known about how differences in the strength of T cell receptor signaling during differentiation influences the 'function' and persistence of anergic and regulatory T cell populations. Here, we review the literature on this subject and discuss the clinical implications of how T cell receptor signal strength influences the 'quality' of anergic and regulatory T cell populations.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".