MicroRNA miR-133 Represses HERG K+ Channel Expression Contributing to QT Prolongation in Diabetic Hearts
Post-publication record
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Bibliographic record
Abstract
We have previously found that the ether-a-go-go related gene (ERG), a long QT syndrome gene encoding a key K(+) channel (I(Kr)) in cardiac cells, is severely depressed in its expression at the protein level but not at the mRNA level in diabetic subjects. The mechanisms underlying the disparate alterations of ERG protein and mRNA, however, remained unknown. We report here a remarkable overexpression of miR-133 in hearts from a rabbit model of diabetes, and in parallel the expression of serum response factor (SRF), which is known to be a transactivator of miR-133, was also robustly increased. Delivery of exogenous miR-133 into the rabbit myocytes and cell lines produced post-transcriptional repression of ERG, down-regulating ERG protein level without altering its transcript level and caused substantial depression of I(Kr), an effect abrogated by the miR-133 antisense inhibitor. Functional inhibition or gene silencing of SRF down-regulated miR-133 expression and increased I(Kr) density. Repression of ERG by miR-133 likely underlies the differential changes of ERG protein and transcript thereby depression of I(Kr), and contributes to repolarization slowing thereby QT prolongation and the associated arrhythmias, in diabetic hearts. Our study provided the first evidence for the pathological role of miR-133 in adult hearts and thus expanded our understanding of the cellular function and pathophysiological roles of miRNAs.
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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) | 0.001 | 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".