Cytohesin Binder and Regulator Augments T Cell Receptor-induced Nuclear Factor of Activated T Cells·AP-1 Activation through Regulation of the JNK Pathway
Bibliographic record
Abstract
Cytohesin binder and regulator (Cybr; also known as CYTIP, CASP, and PSCDBP) is a cytokine-induced gene preferentially expressed in hematopoietic tissues and in T helper 1 cells. Cybr protein associates with members of the cytohesin family, which are known ADP-ribosylation factors-GDP/GTP exchange factors, and its functions appear to regulate lymphocyte adhesion and cell-cell contact. Here we show that Cybr mRNA and protein levels are increased upon T cell receptor engagement. Cybr expression then influences T cell receptor-dependent signaling events, such as nuclear factor of activated T cells and AP-1 transcriptional activity. In addition, expression of Cybr results in increased T cell receptor-mediated activation of the Rho/Rac exchange factor Vav and of the JNK-p38 MAPK signaling pathway. The effects of Cybr on nuclear factor of activated T cells and AP-1 are dependent on MAPK activation, and enhanced activation of this cascade results in cooperation between the two transcription factors in the regulation of gene expression. These findings provide the first evidence that the adaptor protein Cybr not only regulates lymphocyte adhesion and cell-cell interaction but also contributes to the regulation of the signaling cascade and of the genetic program downstream of the T cell receptor.
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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 | 0.001 |
| 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".