Beyond Protein Synthesis; The Multifaceted Roles of Tuberin in Cell Cycle Regulation
Bibliographic record
Abstract
The ability of cells to sense diverse environmental signals, including nutrient availability and conditions of stress, is critical for both prokaryotes and eukaryotes to mount an appropriate physiological response. While there is a great deal known about the different biochemical pathways that can detect and relay information from the environment, how these signals are integrated to control progression through the cell cycle is still an expanding area of research. Over the past three decades the proteins Tuberin, Hamartin and TBC1D7 have emerged as a large protein complex called the Tuberous Sclerosis Complex. This complex can integrate a wide variety of environmental signals to control a host of cell biology events including protein synthesis, cell cycle, protein transport, cell adhesion, autophagy, and cell growth. Worldwide efforts have revealed many molecular pathways which alter Tuberin post-translationally to convey messages to these important pathways, with most of the focus being on the regulation over protein synthesis. Herein we review the literature supporting that the Tuberous Sclerosis Complex plays a critical role in integrating environmental signals with the core cell cycle machinery.
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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 | 0.001 |
| 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 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".