The Quantity of TCR Signal Determines Positive Selection and Lineage Commitment of T Cells
Bibliographic record
Abstract
It is generally accepted that the avidity of TCR for self Ag/MHC determines the fate of immature thymocytes. However, the contribution of the quantity of TCR signal to T cell selection has not been well established, particularly in vivo. To address this issue, we analyzed DO-TCR transgenic CD3zeta-deficient (DO-Tg/zetaKO) mice in which T cells have a reduced TCR on the cell surface. In DO-Tg/zetaKO mice, very few CD4 single positive (SP) thymocytes developed, indicating that the decrease in TCR signaling resulted in a failure of positive selection of DO-Tg thymocytes. Administration of the peptide Ag to DO-Tg/zetaKO mice resulted in the generation of functional CD4 SP mature thymocytes in a dose-dependent manner, and, unexpectedly, DO-Tg CD8 SP cells emerged at lower doses of Ag. TCR signal-dependent, sequential commitment from CD8(+) SP to CD4(+) SP was also shown in a class I-restricted TCR-Tg system. These in vivo analyses demonstrate that the quantity of TCR signal directly determines positive and negative selection, and further suggest that weak signal directs positively selected T cells to CD8 lineage and stronger signal to CD4 lineage.
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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 | 0.000 |
| 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 | 0.000 |
| 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".