Fetal Brain mTOR Signaling Activation in Tuberous Sclerosis Complex
Bibliographic record
Abstract
Tuberous sclerosis complex (TSC) is characterized by developmental malformations of the cerebral cortex known as tubers, comprised of cells that exhibit enhanced mammalian target of rapamycin (mTOR) signaling. To date, there are no reports of mTORC1 and mTORC2 activation in fetal tubers or in neural progenitor cells lacking Tsc2. We demonstrate mTORC1 activation by immunohistochemical detection of substrates phospho-p70S6K1 (T389) and phospho-S6 (S235/236), and mTORC2 activation by substrates phospho-PKCα (S657), phospho-Akt (Ser473), and phospho-SGK1 (S422) in fetal tubers. Then, we show that Tsc2 shRNA knockdown (KD) in mouse neural progenitor cells (mNPCs) in vitro results in enhanced mTORC1 (phospho-S6, phospho-4E-BP1) and mTORC2 (phospho-Akt and phospho-NDRG1) signaling, as well as a doubling of cell size that is rescued by rapamycin, an mTORC1 inhibitor. Tsc2 KD in vivo in the fetal mouse brain by in utero electroporation causes disorganized cortical lamination and increased cell volume that is prevented with rapamycin. We demonstrate for the first time that mTORC1 and mTORC2 signaling is activated in fetal tubers and in mNPCs following Tsc2 KD. These results suggest that inhibition of mTOR pathway signaling during embryogenesis could prevent abnormal brain development in TSC.
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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) | 0.002 | 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".