T cell receptor binding kinetics required for T cell activation depend on the density of cognate ligand on the antigen-presenting cell
Bibliographic record
Abstract
CD8(+) T cells recognize peptides of eight to nine amino acid residues long in the context of MHC class I molecules on the surface of antigen-presenting cells (APCs). This recognition event is highly sensitive, as evidenced by the fact that T cells can be activated by cognate peptide/MHC complex (pMHC) at extremely low densities (1-50 molecules). High sensitivity is particularly valuable for detection of antigens at low density, such as those derived from tumor cells and intracellular pathogens, which can down-modulate cognate pMHCs from the surface of APCs to evade recognition by the adaptive immune system. T cell activation is only triggered in response to interactions between the T cell receptor (TCR) and the pMHC ligand that reach a specific half-life threshold. However, interactions with excessively long half-lives result in impaired T cell activation. Thus, efficient T cell activation by pMHC on the surface of APCs requires an optimal dwell time of TCR-pMHC interaction. Here, we show that, although this is a requirement at low cognate pMHC density on the APC surface, at high epitope density there is no impairment of T cell activation by extended TCR-pMHC dwell times. This observation was predicted by mathematical simulations for T cell activation by pMHC at different densities and supported by experiments performed on APCs selected for varied expression of cognate pMHC. According to these results, effective T cell activation depends on a complex interplay between inherent TCR-pMHC binding kinetics and the epitope density on the APC.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".