Transducin-like Enhancer of Split-1 (TLE1) Combines with Forkhead Box Protein G1 (FoxG1) to Promote Neuronal Survival
Bibliographic record
Abstract
Transducin-like enhancer of split-1 (TLE1) plays a critical role in the regulation of neurogenesis by inhibiting the differentiation of neural progenitor cells into neurons. Although TLE1 is also expressed highly in the postnatal brain and through adulthood, its role in postmitotic neurons is not clear. Using cultures of cerebellar granule neurons, we show that expression of TLE1 is reduced in neurons primed to die. Reestablishment of elevated TLE1 levels by ectopic expression protects neurons from death, whereas suppression of TLE1 expression in otherwise healthy neurons induces cell death. These results show that TLE1 is necessary for the maintenance of neuronal survival. Experiments using pharmacological inhibitors as well as expression of point mutants indicate that phosphorylation of TLE1 by casein kinase-2 (CK2) at Ser-239 and Ser-253 is necessary for its survival-promoting activity. TLE1-mediated survival is also inhibited by pharmacological inhibition of PI3K-Akt signaling but not by inhibitors of Raf-MEK-ERK signaling or other molecules, including histone deacetylases, calcium calmodulin kinase, or CK1. The survival-promoting activity of TLE1 depends critically on interaction with FoxG1, another protein involved in the regulation of neurogenesis and shown previously to promote survival of postmitotic neurons. Likewise, the ability of FoxG1 to promote neuronal survival depends on TLE1. Taken together, our study demonstrates that TLE1 cooperates with FoxG1 to promote neuronal survival in a CK2- and PI3K-Akt-dependent manner.
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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".