Wound collagen deposition in rats: effects of an NO‐NSAID and a selective COX‐2 inhibitor
Bibliographic record
Abstract
Selective cyclo-oxygenase (COX)-2 inhibitors and nitric oxide-releasing nonsteroidal anti-inflammatory drugs (NSAIDs) exhibit reduced toxicity in the gastrointestinal tract, but may affect wound healing in other tissues. In this study, we have compared the effects of a selective COX-2 inhibitor (celecoxib), a nitric-oxide releasing derivative of naproxen (HCT-3012) and naproxen in a model of wound collagen deposition in the rat. Polyvinyl alcohol sponges were implanted subcutaneously in rats. The rats were treated daily for 5 days with the test drugs at equieffective anti-inflammatory doses. Naproxen (10 mg kg(-1)) significantly decreased (45%) collagen deposition at the wound site relative to the vehicle-treated control group. In contrast, HCT-3012 (14.5 mg kg(-1)) significantly increased (62%) collagen deposition, while celecoxib (10 mg kg(-1)) had no effect. Naproxen and HCT-3012 suppressed prostaglandin (PG) E(2) levels at the wound site and whole blood thromboxane synthesis to similar degrees. Celecoxib had no significant effect on wound fluid PGE(2) levels, but slightly reduced whole blood thromboxane synthesis (by 17%). COX-1 mRNA and protein were expressed in the wound exudate, the skin surrounding the wound and in normal skin. In contrast, COX-2 mRNA, but not protein, was expressed in wound and normal skin. These results demonstrate that HCT-3012 can significantly enhance collagen deposition at a wound site, despite inhibiting prostaglandin synthesis to the same extent as the parent drug. Nitric oxide-releasing NSAIDs may represent a safer alternative to standard NSAIDs for use as anti-inflammatory and analgesic agents by post-surgery patients.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".