The tumor suppressor protein PDCD4 is a critical regulator of muscle cell differentiation
Bibliographic record
Abstract
The mammalian target of rapamycin complex 1/S6 ribosomal protein kinase 1 (mTORC1/S6K1) pathway is a critical regulator of mRNA translation and skeletal muscle mass. It does this in part by inhibiting the tumor suppressor protein, programmed cell death 4 (PDCD4). In C2C12 and L6 muscle cells, we showed that PDCD4 abundance was high on day 1 and then decreased as myoblasts differentiated into myotubes (p<0.05). siRNA‐mediated knockdown of S6K1 reversed the decrease in PDCD4 abundance and significantly decreased myosin heavy chain 1 (MHC 1) protein abundance, suggesting that PDCD4 regulation was vital for differentiation. Indeed, cells depleted of PDCD4 had reduced MHC abundance, showed delayed myoblast fusion and abnormal myotube formation. On days 3 and 4 of differentiation, myotubes depleted of PDCD4 showed 40–60% reductions in myotube protein synthesis. This study unravels a link between PDCD4 and muscle cell differentiation, and suggests that this mTORC1/S6K1 substrate may be of therapeutic significance for muscle recovery following injury or atrophy. Funded by NSERC.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 0.001 |
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".