Development and Function of Innate Polyclonal TCRαβ+ CD8+ Thymocytes
Bibliographic record
Abstract
Innate CD8 T cells are found in mutant mouse models, but whether they are produced in a normal thymus remains controversial. Using the RAG2p-GFP mouse model, we found that ∼10% of TCRαβ(+) CD4(-)CD8(+) thymocytes were innate polyclonal T cells (GFP(+)CD44(hi)). Relative to conventional T cells, innate CD8 thymocytes displayed increased cell surface amounts of B7-H1, CD2, CD5, CD38, IL-2Rβ, and IL-4Rα and downmodulation of TCRβ. Moreover, they overexpressed several transcripts, including T-bet, Id3, Klf2, and, most of all, Eomes. Innate CD8 thymocytes were positively selected, mainly by nonhematopoietic MHCIa(+) cells. They rapidly produced high levels of IFN-γ upon stimulation and readily proliferated in response to IL-2 and IL-4. Furthermore, low numbers of innate CD8 thymocytes were sufficient to help conventional CD8 T cells expand and secrete cytokine following Ag recognition. This helper effect depended on CD44-mediated interactions between innate and conventional CD8 T cells. We concluded that innate TCRαβ(+) CD8 T cells represent a sizeable proportion of normal thymocytes whose development and function differ in many ways from those of conventional CD8 T 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".