Skeletal muscle protein synthesis and the abundance of the mRNA translation initiation repressor PDCD4 are inversely regulated by feed deprivation and refeeding in rats
Bibliographic record
Abstract
Optimal skeletal muscle mass is vital to health as defects in muscle protein metabolism underlie or exacerbate human diseases. The mTORC1 is a critical regulator of mRNA translation and protein synthesis. These functions are mediated in part by the ribosomal protein S6 kinase 1 (S6K1) through mechanisms that are poorly understood. The tumor suppressor programmed cell death 4 (PDCD4) has been identified as a novel substrate of S6K1. Here, we examined the expression of PDCD4 in skeletal muscle and its regulation by nutrition. Male rats (~100g, n = 6) were subjected to feed deprivation (FD) for 48 h; some rats were re‐fed for 2 h. FD suppressed muscle protein synthesis and serine 67 phosphorylation of PDCD4 (−50%) but increased PDCD4 abundance (P<0.05); re‐feeding reversed these changes ( P <0.05). Consistent with these effects being regulated by S6K1, activation of this kinase was suppressed by FD (−91%, P<0.05) but was increased by re‐feeding. Gavaging rats subjected to FD with a mixture of amino acids (AA) restored muscle protein synthesis and reduced PDCD4 abundance relative to FD (P<0.05). Finally, when myoblasts were grown in AA‐ and serum‐free medium, rates of proteins synthesis in cells depleted of PDCD4 more than doubled the values in cells with a normal level of this protein ( P <0.0001). Thus, AA stimulate protein synthesis in skeletal muscle in parallel with the reduction of the abundance of PDCD4.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 | 0.001 |
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".