Unequal Contribution of Akt Isoforms in the Double-Negative to Double-Positive Thymocyte Transition
Bibliographic record
Abstract
Pre-TCR signals regulate the transition of the double-negative (DN) 3 thymocytes to the DN4, and subsequently to the double-positive (DP) stage. In this study, we show that pre-TCR signals activate Akt and that pharmacological inhibition of the PI3K/Akt pathway, or combined ablation of Akt1 and Akt2, and to a lesser extent Akt1 and Akt3, interfere with the differentiation of DN3 and the accumulation of DP thymocytes. Combined ablation of Akt1 and Akt2 inhibits the proliferation of DN4 cells, while combined ablation of all Akt isoforms also inhibits the survival of all the DN thymocytes. Finally, the combined ablation of Akt1 and Akt2 inhibits the survival of DP thymocytes. Constitutively active Lck-Akt1 transgenes had the opposite effects. We conclude that, following their activation by pre-TCR signals, Akt1, Akt2, and, to a lesser extent, Akt3 promote the transition of DN thymocytes to the DP stage, in part by enhancing the proliferation and survival of cells undergoing beta-selection. Akt1 and Akt2 also contribute to the differentiation process by promoting the survival of the DP thymocytes.
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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 | 0.000 |
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".