Thymus-derived innate CD8+CD44hi T cells display features of antigen-experienced T cells with bystander helper properties (153.43)
Bibliographic record
Abstract
Abstract Innate CD8 T cells are abundant in several transcription factors (TFs)-deficient mouse models, but little is known about their development in wild-type animals. We used the RAG2-GFP mouse model to discriminate between memory, naïve classic and innate TCRαβ CD8 cells in the thymus. Relative to classic T cells, innate thymocytes display increased levels of numerous cell surface molecules (TCR, CD2, CD3, CD5, CD38, CD62L, B7H1) and enhanced expression of the TFs T-bet, EOMES, Id3 and KFL2. Hematopoietic chimera studies revealed that non-hematopoietic MHCI+ cells are required for innate CD8 T cell selection in the thymus. Mice expressing the transgenic OTI TCR generate both classic and innate CD8 thymocytes suggesting that both subsets have overlapping TCR repertoires. Innate CD8 T cells were also found to rapidly produce high levels of IFNγ upon stimulation and to readily proliferate in response to IL2 and IL4. Under lymphopenic conditions, classic CD8 T cell expansion was 2-3 fold greater than that of innate T cells, which constitutively express B7H1 making them unduly susceptible to apoptosis. To test their bystander properties, we added classic or innate T cells as third-party cells to an in vitro antigen presentation assay. Innate T cells were capable of promoting the proliferation and activation of responding T cells in a CD44-dependent manner. These observations show that innate CD8 T cells represent a subset of thymocytes that differ in many ways from classic CD8 T cells.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".