Curcumin‐induced fibroblast apoptosis and <i>in vitro</i> wound contraction are regulated by antioxidants and heme oxygenase: implications for scar formation
Bibliographic record
Abstract
Fibroblast apoptosis plays a crucial role in normal and pathological scar formation and therefore we studied whether the putative apoptosis-inducing factor curcumin affects fibroblast apoptosis and may function as a novel therapeutic. We show that 25-microM curcumin causes fibroblast apoptosis and that this could be inhibited by co-administration of antioxidants N-acetyl-l-cysteine (NAC), biliverdin or bilirubin, suggesting that reactive oxygen species (ROS) are involved. This is supported by our observation that 25-microM curcumin caused the generation of ROS, which could be completely blocked by addition of NAC or bilirubin. Since biliverdin and bilirubin are downstream products of heme degradation by heme oxygenase (HO), it has been suggested that HO-activity protects against curcumin-induced apoptosis. Interestingly, exposure to curcumin maximally induced HO-1 protein and HO-activity at 10-15 microM, whereas, at a concentration of >20-microM curcumin HO-1-expression and HO-activity was negligible. NAC-mediated inhibition of 25-microM curcumin-induced apoptosis was demonstrated to act in part via restored HO-1-induction, since the rescuing effect of NAC could be reduced by inhibiting HO-activity. Moreover pre-induction of HO-1 using 5-microM curcumin protected fibroblasts against 25-microM curcumin-induced apoptosis. On a functional level, fibroblast-mediated collagen gel contraction, an in vitro wound contraction model, was completely prevented by 25-microM curcumin, while this could be reversed by co-incubation with NAC, an effect that was also partially HO-mediated. In conclusion, curcumin treatment in high doses (>25 microM) may provide a novel way to modulate pathological scar formation through the induction of fibroblast apoptosis, while antioxidants, HO-activity and its effector molecules act as a possible fine-tuning regulator.
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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) | 0.001 | 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".