MicroRNA205: A Key Regulator of Cardiomyocyte Transition from Proliferative to Hypertrophic Growth in the Neonatal Heart
Bibliographic record
Abstract
The mammalian myocardium grows rapidly during early development due to cardiomyocyte proliferation, which later transitions to cell hypertrophy to sustain the heart's postnatal growth. Although this cell transition in the postnatal heart is consistently preserved in mammalian biology, little is known about the regulatory mechanisms that link proliferation suppression with hypertrophy induction. We reasoned that the production of a micro-RNA(s) could serve as a key bridge to permit changes in gene expression that control the changed cell fate of postnatal cardiomyocytes. We used sequential expression analysis to identify miR205 as a micro-RNA that was uniquely expressed at the cessation of cardiomyocyte growth. Cardiomyocyte-specific miR205 deletion animals showed a 35% increase in heart mass by 3 months of age, with commensurate changes in cell cycle and Hippo pathway activity, confirming miR205's potential role in controlling cardiomyocyte proliferation. In contrast, overexpression of miR205 in newborn hearts had little effect on heart size or function, indicating a complex, probably redundant regulatory system. These findings highlight miR205's role in controlling the shift from cardiomyocyte proliferation to hypertrophic development in the postnatal period.
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".