Ephrin-B1 Is Critical in T-cell Development
Bibliographic record
Abstract
Eph kinases are the largest family of receptor tyrosine kinases, and their ligands, ephrins (EFNs), are also cell surface molecules. In this study, we investigated the role of EFNB1 and the Ephs it interacts with (collectively called EFNB1 receptors) in mouse T-cell development. In the thymus, CD8 single positive (SP) and CD4CD8 double positive (DP) cells expressed high levels of EFNB1 and EFNB1 receptors, whereas CD4 SP cells had moderate expression of both. Soluble EFNB1-Fc in fetal thymus organ culture caused significant subpopulation ratio skew, with increased CD4 SP and CD8 SP and decreased DP percentage, while the cellularity of the thymus remained constant. Moreover, in EFNB1-treated fetal thymus organ culture, CD117(+), CD25(+), DP, CD4 SP, and CD8 SP cells all had significantly enhanced proliferation history, according to bromodeoxyuridine uptake. In vitro culture of isolated thymocytes revealed that EFNB1-Fc on solid-phase protected thymocytes from anti-CD3-induced apoptosis, with concomitant augmentation of several antiapoptotic factors, particularly in CD4 SP and CD8 SP cells; on the other hand, soluble EFNB1-Fc promoted anti-CD3-induced apoptosis, as was the case in vivo. This study reveals that EFNB1 and EFNB1 receptors are critical in thymocyte development.
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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) | 0.002 | 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".