EphA Receptors Inhibit Anti-CD3-Induced Apoptosis in Thymocytes
Bibliographic record
Abstract
The EphA receptor tyrosine kinases interact with membrane-bound ligands of the ephrin-A subfamily. Interaction induces EphA receptor oligomerization, tyrosine phosphorylation, and, as a result, EphA receptor signaling. EphA receptors have been shown to regulate cell survival, migration, and cell-cell and cell-matrix interactions. However, their functions in lymphoid cells are only beginning to be described. We show in this study that functional EphA receptors are expressed by murine thymocytes, including CD4(+)CD8(+), CD4(+)CD8(-), and CD4(-)CD8(+) subpopulations. We demonstrate that activation of EphA receptors by the ephrin-A1 ligand inhibits the anti-CD3-induced apoptosis of CD4(+)CD8(+) double-positive thymocytes. Furthermore, ephrin-A1 costimulation suppresses up-regulation of both the IL-2R alpha-chain (CD25) and early activation Ag CD69 and can block IL-2 production by CD4(+) single-positive cells. In agreement, EphA receptor activation in thymocytes also inhibits TCR-induced activation of the Ras-MAPK pathway. Our findings suggest that EphA receptor activation is antithetical to TCR signaling in thymocytes, and that the level of engagement by ephrin-A proteins on thymic APCs regulates thymocyte selection.
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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 | 0.001 |
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".