miR-29b promotes skin wound healing and reduces excessive scar formation by inhibition of the TGF-β1/Smad/CTGF signaling pathway
Bibliographic record
Abstract
The hypertrophic scar is a medical difficulty of humans, which has caused great pain to patients. Here, we investigated the inhibitory effect of miR-29b on scar formation. The scalded model was established in mice and miR-29b mimics or a negative control was subcutaneously injected into the injury skin. Then various molecular biological experiments were performed to assess the effect of miR-29b on scar formation. According to our present study, first, the results demonstrated that miR-29b was down-regulated in thermal injury tissue and miR-29b treatment could promote wound healing, inhibit scar formation, and alleviate histopathological morphologic alteration in scald tissues. Additionally, miR-29b treatment suppressed collagen deposition and fibrotic gene expression in scar tissues. Finally, we found that miR-29b treatment inhibited the TGF-β1/Smad/CTGF signaling pathway. Taken together, our data suggest that miR-29b treatment has an inhibitory effect against scar formation via inhibition of the TGF-β1/Smad/CTGF signaling pathway and may provide a potential molecular basis for future treatments for hypertrophic scars.
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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 | 0.000 |
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".