Silencing of <i>Mustn1</i> inhibits myogenic fusion and differentiation
Bibliographic record
Abstract
Mustn1 (Mustang, musculoskeletal temporally activated novel gene) was originally identified in fracture callus tissue, but its greatest expression is detected in skeletal muscle. Thus, we conducted experiments to investigate the expression and function of Mustn1 during myogenesis. Temporally, quantitative real-time PCR analysis of muscle samples from embryonic day 17 to 12 mo of age reveals that Mustn1 mRNA expression is greatest at 3 mo of age and beyond, consistent with the expression pattern of Myod. In situ hybridization shows abundant Mustn1 expression in somites and developing skeletal muscles, while in adult muscle, Mustn1 is localized to some peripherally located nuclei. Using RNA interference (RNAi), we investigated the function of Mustn1 in C2C12 myoblasts. Though silencing Mustn1 mRNA had no effect on myoblast proliferation, it did significantly impair myoblast differentiation, preventing myofusion. Specifically, when placed in low-serum medium for up to 6 days, Mustn1-silenced myoblasts elongated poorly and were mononucleated. In contrast, control RNAi-treated and parental myoblasts presented as large, multinucleated myotubes. Further supporting the morphological observations, immunocytochemistry of Mustn1-silenced cells demonstrated significant reductions in myogenin (Myog) and myosin heavy chain (Myhc) expression at 4 and 6 days of differentiation as compared with control and parental cells. The decreases in Myog and Myhc protein expression in Mustn1-silenced cells were associated with robust ( approximately 3-fold or greater) decreases in the expression of Myod and desmin (Des), as well as the myofusion markers calpain 1 (Capn1), caveolin 3 (Cav3), and cadherin 15 (M-cadherin; Cadh15). Overall, we demonstrate that Mustn1 is an essential regulator of myogenic differentiation and myofusion, and our findings implicate Myod and Myog as its downstream targets.
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) | 0.001 | 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".