Thymic progenitors of TCRαβ+ CD8αα intestinal intraepithelial lymphocytes require RasGRP1 for development
Bibliographic record
Abstract
Strong T cell receptor (TCR) signaling largely induces cell death during thymocyte development, whereas weak TCR signals induce positive selection. However, some T cell lineages require strong TCR signals for differentiation through a process termed agonist selection. The signaling relationships that underlie these three fates are unknown. RasGRP1 is a Ras activator required to transmit weak TCR signals leading to positive selection. Here, we report that, despite being dispensable for thymocyte clonal deletion, RasGRP1 is critical for agonist selection of TCRαβ+CD8αα intraepithelial lymphocyte (IEL) progenitors (IELps), even though both outcomes require strong TCR signaling. Bim deficiency rescued IELp development in RasGRP1−/− mice, suggesting that RasGRP1 functions to promote survival during IELp generation. Additionally, expression of CD122 and the adhesion molecules α4β7 and CD103 define distinct IELp subsets with differing abilities to generate TCRαβ+CD8αα IEL in vivo. These findings demonstrate that RasGRP1-dependent signaling underpins thymic selection processes induced by both weak and strong TCR signals and is differentially required for fate decisions derived from a strong TCR stimulus.
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) | 0.001 | 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".