In vitro effects of cyclooxygenase inhibitors in whole blood of horses, dogs, and cats
Bibliographic record
Abstract
OBJECTIVE: To determine potency and selectivity of nonsteroidal anti-inflammatory drugs (NSAID) and cyclooxygenase- (COX-) specific inhibitors in whole blood from horses, dogs, and cats. SAMPLE POPULATION: Blood samples from 30 healthy horses, 48 healthy dogs, and 9 healthy cats. PROCEDURE: Activities of COX-1 and COX-2 were determined by measuring coagulation-induced thromboxane and lipopolysaccharide-induced prostaglandin E2 concentrations, respectively, in whole blood with and without the addition of various concentrations of phenylbutazone, flunixin meglumine, ketoprofen, diclofenac, indomethacin, meloxicam, carprofen, 5-bromo-2[4-fluorophenyl]-3-14-methylsulfonylphenyl]-thiophene (DuP 697), 5,5-dimethyl-3-(3-fluorophenyl)-4-(4-methylsulphonyl) phenyl-2(5H)-furan one (DFU), 3-(3,4-difluorophenyl)-4-(4-(methylsulfonyl)phenyl)-2-(5H)-furanone (MF-tricyclic), and celecoxib. Potency of each test compound was determined by calculating the concentration that resulted in inhibition of 50% of COX activity (IC50). Selectivity was determined by calculating the ratio of IC50 for COX-1 to IC50 for COX-2 (COX-1/COX-2 ratio). RESULTS: The novel compound DFU was the most selective COX-2 inhibitor in equine, canine, and feline blood; COX-1/COX-2 ratios were 775, 74, and 69, respectively. Carprofen was the weakest inhibitor of COX-2, compared with the other COX-2 selective inhibitors, and did not inhibit COX-2 activity in equine blood. In contrast, NSAID such as phenylbutazone and flunixin meglumine were more potent inhibitors of COX-1 than COX-2 in canine and equine blood. CONCLUSIONS AND CLINICAL RELEVANCE: The novel COX-2 inhibitor DFU was more potent and selective in canine, equine, and feline blood, compared with phenylbutazone, flunixin meglumine, and carprofen. Compounds that specifically inhibit COX-2 may result in a lower incidence of adverse effects, compared with NSAID, when administered at therapeutic dosages to horses, dogs, and cats.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".