ICAT expression disrupts -catenin-TCF interactions and impairs survival of thymocytes and activated mature T cells
Bibliographic record
Abstract
T cell factor (TCF) family of transcription factors and beta-catenin critically regulate T cell development as demonstrated by the deletion of the tcf gene, which results in a block early in development that becomes complete in mice bearing tcf/lef double deletion. However, the role of beta-catenin, a major TCF cofactor, remains controversial. To directly address this, we have generated transgenic mice expressing Inhibitor of beta-catenin and TCF (ICAT), a naturally occurring inhibitor that specifically disrupts TCF and beta-catenin interactions. In this report, we demonstrate that disrupting the interaction of beta-catenin with TCF renders adult thymocytes and activated T cells highly susceptible to apoptosis. In contrast to previously reported observations during fetal thymocyte development, these data show that in adult mice, survival and not differentiation of thymocytes, depends on transcription by TCF and beta-catenin. Indeed, we demonstrate that expression of ICAT impedes thymocyte survival by reducing the expression of Bcl(xL) in thymocytes below a critical threshold. Survival of activated mature T cells was also impaired due to diminished expression of activation-induced Bcl(xL). Accordingly, expression of transgenic Bcl-2 rescued activated ICAT-Tg CD4 T cells from apoptosis. Thus, disruption of TCF-beta-catenin interactions specifically impairs the survival of thymocytes and activated T cells.
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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) | 0.001 | 0.000 |
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".