miR-26a is required for skeletal muscle differentiation and regeneration in mice
Bibliographic record
Abstract
Multiple microRNAs are known to be induced during the differentiation of myoblasts to myotubes. Yet, experiments in animals have not provided clear evidence for the requirement of most of these microRNAs in myogenic differentiation in vivo. miR-26a is induced during skeletal muscle differentiation and is predicted to target a well-known inhibitor of differentiation, the transforming growth factor β/bone morphogenetic protein (TGF-β/BMP) signaling pathway. Here we show that exogenous miR-26a promotes differentiation of myoblasts, while inhibition of miR-26a by antisense oligonucleotides or by Tough-Decoys delays differentiation. miR-26a targets the transcription factors Smad1 and Smad4, critical for the TGF-β/BMP pathway, and expression of microRNA-resistant forms of these transcription factors inhibits differentiation. Injection of antagomirs specific to miR-26a into neonatal mice derepressed both Smad expression and activity and consequently inhibited skeletal muscle differentiation. In addition, miR-26a is induced during skeletal muscle regeneration after injury. Inhibiting miR-26a in the tibialis anterior muscles through the injection of adeno-associated virus expressing a Tough-Decoy targeting miR-26a prevents Smad down-regulation and delays regeneration. These findings provide evidence for the requirement of miR-26a for skeletal muscle differentiation and regeneration in vivo.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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".