Cyclooxygenases, microsomal prostaglandin E synthase-1, and cardiovascular function
Bibliographic record
Abstract
We investigated the mechanisms by which inhibitors of prostaglandin G/H synthase-2 (PGHS-2; known colloquially as COX-2) increase the incidence of myocardial infarction and stroke. These inhibitors are believed to exert both their beneficial and their adverse effects by suppression of PGHS-2-derived prostacyclin (PGI(2)) and PGE(2). Therefore, the challenge remains to identify a mechanism whereby PGI(2) and PGE(2) expression can be suppressed while avoiding adverse cardiovascular events. Here, selective inhibition, knockout, or mutation of PGHS-2, or deletion of the receptor for PGHS-2-derived PGI(2), was shown to accelerate thrombogenesis and elevate blood pressure in mice. These responses were attenuated by COX-1 knock down, which mimics the beneficial effects of low-dose aspirin. PGE(2) biosynthesis is catalyzed by the coordinate actions of COX enzymes and microsomal PGE synthase-1 (mPGES-1). We show that deletion of mPGES-1 depressed PGE(2) expression, augmented PGI(2) expression, and had no effect on thromboxane biosynthesis in vivo. Most importantly, mPGES-1 deletion affected neither thrombogenesis nor blood pressure. These results suggest that inhibitors of mPGES-1 may retain their antiinflammatory efficacy by depressing PGE(2), while avoiding the adverse cardiovascular consequences associated with PGHS-2-mediated PGI(2) suppression.
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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) | 0.000 | 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 | 0.000 |
| 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".