The function of Rad in the regulation of myogenic satellite cells
Bibliographic record
Abstract
Muscle satellite cells are integral for muscle growth and regeneration, but their molecular regulation is not yet fully elucidated. We have previously demonstrated that a novel Ras related low molecular weight GTPase, Rad, is up‐regulated during the phases of muscle regeneration corresponding to the proliferation and differentiation of muscle satellite cells. To define Rad's role in the regulation of the C2C12 muscle satellite cell line Rad was up‐regulated and down‐regulated, using an over‐expression plasmid or siRNA respectively. Rad up‐regulation significantly improved proliferation vs. control (235 ± 3%), while the opposite occurred with Rad down‐regulation (74.3±3%). Myotube formation was enhanced with an increased amount Rad, while impaired by Rad's inhibition. As Rad function has been linked to cytoskeletal modifications, we undertook migration (scratch) assays to investigate the role of Rad in chemotaxis. A reduction in Rad significantly impaired migration such that it was 84.4 ±4% of control. We hypothesize that during the early phases of muscle regeneration Rad inhibits L‐type calcium channels delaying satellite cell differentiation, while during the latter phases Rad encourages differentiation by inhibiting Rho/ROK signaling. In summary, these findings expand our knowledge of myogenic satellite cell regulation and will help to improve the therapeutic application of this cell population.
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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 | 0.000 |
| 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".