The <i>H19</i> long noncoding RNA gives rise to microRNAs miR-675-3p and miR-675-5p to promote skeletal muscle differentiation and regeneration
Bibliographic record
Abstract
Regulated expression of the H19 long noncoding RNA gene has been well characterized as a paradigm for genomic imprinting, but the H19 RNA's biological function remains largely unclear. H19 is abundantly expressed maternally in embryonic tissues but is strongly repressed after birth, and significant transcription persists only in skeletal muscle. Thus, we examined the role of the H19 RNA in skeletal muscle differentiation and regeneration. Knockdown of H19 RNA in myoblast cells and H19 knockout mouse satellite cells decreases differentiation. H19 exon1 encodes two conserved microRNAs, miR-675-3p and miR-675-5p, both of which are induced during skeletal muscle differentiation. The inhibition of myogenesis by H19 depletion during myoblast differentiation is rescued by exogenous expression of miR-675-3p and miR-675-5p. H19-deficient mice display abnormal skeletal muscle regeneration after injury, which is rectified by reintroduction of miR-675-3p and miR-675-5p. miR-675-3p and miR-675-5p function by directly targeting and down-regulating the anti-differentiation Smad transcription factors critical for the bone morphogenetic protein (BMP) pathway and the DNA replication initiation factor Cdc6. Therefore, the H19 long noncoding RNA has a critical trans-regulatory function in skeletal muscle differentiation and regeneration that is mediated by the microRNAs encoded within H19.
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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) | 0.002 | 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".