microRNA-29b knocks down collagen type I production in cultured rainbow trout (<i>Oncorhynchus mykiss</i>) cardiac fibroblasts
Bibliographic record
Abstract
Warm acclimation of rainbow trout can cause a decrease in the collagen content of the heart. This ability to remove cardiac collagen is particularly interesting considering that collagen deposition in the mammalian heart, following an injury, is permanent. We hypothesized that collagen removal can be facilitated by microRNA-29b, a highly conserved, small, non-coding RNA, as a reduction in this microRNA has been reported during the development of fibrosis in the mammalian heart. We also used a bioinformatics approach to investigate the binding potential of miR-29b to the seed sequences of vertebrate collagen isoforms. Cultured trout cardiac fibroblasts were transfected with zebrafish mature miR-29b mimic for 7 d with re-transfection occurring after 3 d. Transfection induced a 17.8-fold increase in miR-29b transcript abundance (P<0.05) as well as a 54% decrease in the transcript levels of col1a3, compared to non-transfected controls (P<0.05). Western blotting demonstrated that the levels of collagen type I protein was 85% lower in cells transfected with miR-29b than in control cells (P<0.05). Finally, bioinformatic analysis suggested that the predicted 3'UTR of rainbow trout col1a3 has a comparatively higher binding affinity for miR-29b than the 3'UTR of col1a1. Together these results suggest that miR-29b is a highly conserved regulator of collagen type I protein in vertebrates and that this microRNA decreases collagen in the trout heart by targeting col1a3.
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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) | 0.002 | 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".