INFLUENCE OF NITRIC OXIDE-DONATING NONSTEROIDAL ANTI-INFLAMMATORY DRUGS ON THE EVOLUTION OF ACUTE PANCREATITIS
Bibliographic record
Abstract
Microcirculatory disturbances and leukocyte activation are main events in the pathogenesis of acute pancreatitis (AP) that is characterized by inflammatory up-regulation. Nitric oxide-donating nonsteroidal anti-inflammatory drugs (NO-NSAIDs) regulate vascular function and mitigate inflammation. To investigate the influence of NO-NSAIDs on AP. AP was induced by the biliopancreatic duct outlet exclusion-closed duodenal loops model. Treatment with NO-flurbiprofen, NO-ibuprofen, NO-aspirin, or their parental drugs was done (i) 1 h before, (ii) 1 h after, (iii) 1 h before and 4 h after, or (iv) 4 h after surgery. The degree of severity was evaluated using biochemical and histopathological analyses. NO-NSAIDs given before and during the first hour of the noxia decreased blood levels of amylase, lipase, C-reactive protein, IL-6, IL-10, heat shock protein 72, prostaglandin E2 inactive metabolite, and 8-isoprostane, as well as pancreatic and lung myeloperoxidase and cyclooxygenase. Acinar and fat necrosis, hemorrhage, and leukocyte infiltrate were also reduced. The best protection was achieved when treatment was performed 1 h before and 4 h after triggering AP. NO-flurbiprofen was the most effective drug. AP severity was significantly ameliorated by NO-NSAIDs being the administration time essential to achieve optimal pancreatic protection that may result to be useful in the prevention of postendoscopic severe AP.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".