Discrete TCR Binding Kinetics Control Invariant NKT Cell Selection and Central Priming
Bibliographic record
Abstract
T cells; however, iNKT TCRs recognize Ags in a fundamentally different way. How the biophysical parameters of iNKT TCRs influence signal strength in vivo and how such signals affect the development and differentiation of these cells are unknown. In this study, we manipulated TCRs in vivo to generate clonotypic iNKT cells using TCR retrogenic chimeras. We report that the biophysical properties of CD1d-lipid-TCR interactions differentially impacted the development and effector differentiation of iNKT cells. Whereas selection efficiency strongly correlated with TCR avidity, TCR signaling, cell-cell conjugate formation, and iNKT effector differentiation correlated with the half-life of CD1d-lipid-TCR interactions. TCR binding properties, however, did not modulate Ag-induced iNKT cytokine production. Our work establishes that discrete TCR interaction kinetics influence iNKT cell development and central priming.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".