Overexpression of sTnC polypeptide in muscle cells is controlled by its rapid degradation
Bibliographic record
Abstract
The check-points that maintain stoichiometric synthesis of muscle proteins were examined by misexpression of slow troponin C (sTnC) in mouse C2 myotubes. The sTnC mRNA was overexpressed in myotubes by transfecting these cells with a plasmid construct containing the constitutive CMV promoter-driven sTnC cDNA. An approximately four-fold increase of sTnC mRNA level in the transfected cells was observed. However, the increased mRNA level did not produce a corresponding increase of the sTnC polypeptide level in transfected cells. Only a modest 1.5-fold increase of the sTnC polypeptide level in the transfected cells was observed. The excess sTnC polypeptide in transfected cells was found in the soluble form which was not complexed with other thin filament proteins. The difference between the increase of sTnC mRNA and the polypeptide levels in transfected cells was not due to inefficient translation of the overexpressed sTnC mRNA. Analyses of the stability of the sTnC polypeptide in the thin filament and in the unassembled soluble forms showed that the excess soluble sTnC polypeptide was degraded more rapidly than the sTnC polypeptide of the thin filament. Analyses of the mRNA and polypeptide levels of several thin filament complements showed no effect of overexpression of the sTnC mRNA.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".