Mechanisms underlying the anti‐inflammatory activity and gastric safety of acemetacin
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Acemetacin is regarded as a pro-drug of indomethacin and induces significantly less gastric damage but the reasons for this greater gastric safety of acemetacin are unclear. The anti-inflammatory effects of acemetacin have been attributed, at least in part, to its hepatic biotransformation to indomethacin. The aim of this study was to determine the effects of acemetacin and indomethacin in an in vivo model of acute inflammation and to examine the importance of biotransformation of acemetacin (to indomethacin) to its anti-inflammatory actions. EXPERIMENTAL APPROACH: The zymosan airpouch model was used in rats. Indomethacin or acemetacin (2.7-83.8 micromol kg(-1)) were administered orally or directly into the pouch. Leukocyte infiltration, prostaglandin (PG) E(2) and leukotriene (LT) B(4) levels in exudates, and whole blood thromboxane (TX) B(2) synthesis were measured. KEY RESULTS: Acemetacin was rapidly converted to indomethacin after its administration. Both acemetacin and indomethacin elicited comparable, dose-dependent reductions of leukocyte infiltration and of PGE(2) and TXB(2) synthesis. However, indomethacin induced more gastric damage than acemetacin and elevated LTB(4) production in the airpouch. CONCLUSIONS AND IMPLICATIONS: The similar effects of acemetacin and indomethacin on leukocyte infiltration and PG synthesis are consistent with rapid biotransformation of acemetacin to indomethacin. Some of this biotransformation may occur extra-hepatically, for instance in inflammatory exudates. Acemetacin probably exerts actions independent of conversion to indomethacin, given the different effects of these two drugs on LTB(4) production. Such differences may contribute to the relative gastric safety of acemetacin compared to indomethacin.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".