Temporal changes in ERK phosphorylation are harmonious with 4E-BP1, but not p70S6K, during clenbuterol-induced hypertrophy in the rat gastrocnemius
Bibliographic record
Abstract
Extracellular signal-regulated kinase (ERK) is required for clenbuterol (CB)-dependent fast-type myofibril enlargement; however, its contribution to translation control is unclear. ERK mediates translational regulation through mammalian target of rapamycin complex 1 (mTORC1) activation and (or) mTORC1-independent pathways. In this study, we aimed to investigate the role of ERK in translational control during CB-induced muscular hypertrophy by measuring time-dependent changes in the phosphorylation statuses of ERK, p70 ribosomal S6 kinase (p70S6K; an indicator of mTORC1 activity), 4E-binding protein 1 (4E-BP1), eukaryotic elongation factor 2 (eEF2), and other related signaling molecules in rat gastrocnemius muscles. Five-day administration of CB induced phenotypes associated with muscular hypertrophy (significant increases in wet weight and isometric ankle flexion torque in the gastrocnemius muscle), but was not accompanied by elevated ERK or p70S6K phosphorylation. One-day administration of CB caused significant increases in the phosphorylation of ERK, p70S6K, and 4E-BP1. In contrast, 3-day administration of CB caused significant increases in the phosphorylation of ERK and 4E-BP1, but not p70S6K. In addition, positive correlations were observed between ERK and 4E-BP1 on days 1 and 3, whereas a correlation between ERK and p70S6K was only observed on day 1. eEF2 phosphorylation was unchanged on both days 1 and 3. These findings suggest that ERK accelerates the initiation of translation, but does not support the involvement of ERK in translational elongation. Furthermore, ERK may play a major role in promoting translational initiation by mediating the phosphorylation of 4E-BP1, and may contribute to the initial activation of mTORC1 during CB administration.
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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) | 0.001 | 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".