Canonical signaling and nuclear activity of <scp>mTOR</scp>—a teamwork effort to regulate metabolism and cell growth
Bibliographic record
Abstract
Mechanistic (or mammalian) target of rapamycin (mTOR) is a kinase that regulates almost all functions related to cell growth and metabolism in response to extra- and intracellular stimuli, such as availability of nutrients, the presence of growth factors, or the energy status of the cell. As part of two distinct protein complexes, mTORC1 and mTORC2, the kinase has been shown to influence cell growth and proliferation by controlling ribosome biogenesis, mRNA translation, carbohydrate and lipid metabolism, protein degradation, autophagy as well as microtubule and actin dynamics. In addition to these well-characterized functions, mTOR can also influence gene transcription. While most studies focused on investigating how canonical mTOR signaling regulates the activity of transcription factors outside the nucleus, recent findings point to a more direct role for mTOR as a transcription factor operating on chromatin in the nucleus. In particular, recent genome-wide identification of mTOR targets on chromatin reveals that its activities in the nucleus and cytoplasm are functionally and biologically linked, thus uncovering a novel paradigm in mTOR function.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".