A high level of cyclooxygenase-2 inhibitor selectivity is associated with a reduced interference of platelet cyclooxygenase-1 inactivation by aspirin
Bibliographic record
Abstract
Both nonsteroidal anti-inflammatory drugs, such as ibuprofen, and the prototypical selective cyclooxygenase (Cox)-2 inhibitors DuP-697 and NS-398 block the inhibition of Cox-1 by aspirin in vitro. However, clinical studies have shown that the Cox-2 selective drugs (or coxibs) rofecoxib and etoricoxib, at therapeutic doses, do not interfere with the antiplatelet effect of aspirin, in contrast to ibuprofen. Here, we have evaluated the relative potential of ibuprofen and various coxibs to interfere with the inactivation of Cox-1 by aspirin by using purified enzyme and calcium ionophore-activated human platelets. The irreversible inactivation of Cox-1 by aspirin can be antagonized by ibuprofen and coxibs, albeit with widely different potencies. The rank order of potencies for this process (ibuprofen > celecoxib > valdecoxib > rofecoxib > etoricoxib) parallels that obtained for the inhibition of Cox-1-mediated thromboxane B(2) production by calcium ionophore-stimulated platelets. The antagonism of aspirin therefore likely involves a competition at the enzyme active site. The EC(50) value for the antagonism against 10 microM aspirin for each drug is approximately 10- to 40-fold lower than the corresponding IC(50) value for inhibition of platelet Cox-1 activity, consistent with the much weaker initial binding of aspirin to Cox-1 as compared with arachidonic acid. These results show that a low affinity for Cox-1 and a high degree of Cox-2 selectivity confers a low potential to block aspirin inhibition of platelet Cox-1, consistent with the results of clinical studies.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.003 | 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".