Cardiovascular dysregulation of miR‐17‐92 causes a lethal hypertrophic cardiomyopathy and arrhythmogenesis
Bibliographic record
Abstract
MicroRNA cluster miR‐17‐92 has been implicated in cardiovascular development and function, yet its precise mechanisms of action in these contexts are uncertain. This study aimed to investigate the role of miR‐17‐92 in morphogenesis and function of cardiac and smooth muscle tissues. To do so, a mouse model of conditional overexpression of miR‐17‐92 in cardiac and smooth muscle tissues was generated. Extensive cardiac functional studies identified a dose‐dependent induction of dilated, hypertrophic cardiomyopathy, and arrhythmia inducibility in transgenic animals, which correlated with premature mortality (98.3±42.5 d, P <0.0001). Expression analyses revealed the abundance of Pten transcript, a known miR‐17‐92 target, to be inversely correlated with miR‐17‐92 expression levels and heart size. In addition, we demonstrated through 3′‐UTR luciferase assays and expression analyses that Connexin43 (Cx43) is a novel direct target of miR‐19a/b and its expression is suppressed in transgenic hearts. Taken together, these data demonstrate that dysregulated expression of miR‐17‐92 during cardiovascular morphogenesis results in a lethal cardiomyopathy, possibly in part through direct repression of Pten and Cx43. This study highlights the importance of miR‐17‐92 in both normal and pathological functions of the heart, and provides a model that may serve as a useful platform to test novel antiarrhythmic therapeutics.—Danielson, L. S., Park, D. S., Rotllan, N., Chamorro‐Jorganes, A., Guijarro, M. V., Fernandez‐Hernando, C., Fishman, G. I., Phoon, C. K. L., Hernando, E. Cardiovascular dysregulation of miR‐17‐92 causes a lethal hypertrophic cardiomyopathy and arrhythmogenesis. FASEB J. 27, 1460–1467 (2013). www.fasebj.org
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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 | 0.001 |
| 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".