PD‐1 is not required for natural or peripherally induced regulatory T cells: Severe autoimmunity despite normal production of regulatory T cells
Bibliographic record
Abstract
The expression of the coinhibitor PD-1 on T cells is important for the establishment of immune homeostasis. We previously found that PD-1 is particularly critical for the control of self-tolerance during lymphopenia-induced proliferation of recent thymic emigrants (RTEs). Previous studies suggested that PD-1 modulates the generation of Treg cells, particularly peripherally induced Treg (pTreg) cells, and controls Th17 cells. However, these conclusions were derived indirectly from studies on the ligand PD-L1, and not PD-1 itself. Herein we directly tested whether T-cell PD-1 expression was needed for Treg cell generation and examined if a paucity of Treg cells or enhanced Th17 cells could explain the severe lymphopenia-potentiated autoimmunity caused by PD-1 KO RTEs. Employing the murine FoxP3(EGFP) reporter system to simultaneously monitor conversion of WT and PD-1 KO T cells to pTreg cells in the same animal, we found that PD-1 deficiency did not inhibit pTreg cell generation or lead to Th17-cell-mediated autoimmunity. Surprisingly, pTreg cell numbers were increased in PD-1 KO versus WT cell populations. Furthermore, we noted an increased conversion to pTreg cells by RTEs. Our data suggest that the primary role for PD-1 is to restrain T-cell activation/proliferation to self-Ags rather than promote generation of Treg cells.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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; 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".