Nitric Oxide, Aspirin-Triggered Lipoxins and NO-Aspirin in Gastric Protection
Bibliographic record
Abstract
The use of nonsteroidal anti-inflammatory drugs is associated with an incidence of severe gastrointestinal adverse events of 2-4%, the most common of which is bleeding. These events are largely attributable to the ability of these drugs to suppress prostaglandin and thromboxane synthesis. Prostaglandins perform a number of important functions in the gastrointestinal tract, particularly with respect to resistance of the mucosa to injury. Nitric oxide also appears to be a key mediator of gastrointestinal mucosal defence, and this has been exploited in the development of a novel class of anti-inflammatory drugs, called "NO-NSAIDs", which exhibit little if any gastrointestinal toxicity. NO-NSAIDs are more effective than traditional NSAIDs in reducing pain and inflammation. Another class of inflammatory mediators that contribute to gastrointestinal mucosal defence are the lipoxins. These products of arachidonic acid metabolism can increase the resistance of the stomach to the damaging effects of aspirin. Indeed, aspirin can trigger the formation of a lipoxin by the stomach which acts to diminish the damaging effects of this drug. Lipoxins and nitric oxide are important mediators of mucosal defence in the stomach (and elsewhere in the gastrointestinal tract) and represent attractive therapeutic targets for reducing the incidence of gastric ulceration.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".