EFNB1 and EFNB2 physically bind to IL-7R-alpha and retard its internalization from the cell surface (57.2)
Bibliographic record
Abstract
Abstract IL-7 plays vital roles in thymocyte development, T cell homeostasis and the survival of these cells. IL-7 receptor alpha (IL-7R-alpha) on the thymocytes and T cells is rapidly internalized upon IL-7 ligation. Ephrins (EFN) are cell surface molecules and are ligands of the largest family of receptor kinases, Eph kinases. We discovered that T cell-specific double deletion of EFNB1 and EFNB2 (double KO) in mice led to reduced IL-7R-alpha expression in thymocytes and T cells, and that IL-7R-alpha downregulation in double KO CD4 cells upon IL-7 treatment was accelerated. On the other hand, EFNB1 and EFNB2 overexpression in T cell line EL4 cells retarded IL-7R-alpha downregulation. The EFNB1/EFNB2 double KO T cells manifested compromised homeostatic proliferation, which is an IL-7-dependent process. Using fluorescent resonance energy transfer (FRET), we demonstrated that EFNB1 and EFNB2 physically interacted with IL-7R-alpha. Such interaction likely retarded IL-7R-alpha internalization, as EFNB1 and EFNB2 were not subjected to internalization. Therefore, we revealed a novel function of EFNB1 and EFNB2 in stabilizing the IL-7R-alpha expression at the post-translational level, and a previously unknown modus operandi of EFNBs in the regulation of the expression of other vital cell surface receptors.
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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) | 0.003 | 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".