Divergent effects of new cyclooxygenase inhibitors on gastric ulcer healing: Shifting the angiogenic balance
Bibliographic record
Abstract
Delayed gastric ulcer healing is a well recognized problem associated with the use of cyclooxygenase (COX) inhibitors. In contrast, NO-releasing COX inhibitors do not interfere with ulcer healing. These divergent effects may in part be due to differences in their effects on platelets, which are known to influence ulcer healing. Therefore, we compared the effects of a nonselective COX inhibitor (flurbiprofen), a nitric oxide-releasing COX inhibitor (HCT-1026), and a selective COX-2 inhibitor (celecoxib) on gastric ulcer healing, angiogenesis, and platelet/serum levels of vascular endothelial growth factor (VEGF) and endostatin. Gastric ulcers were induced in rats by serosal application of acetic acid. Daily treatment with the test drugs was started 3 days later and continued for 1 week. Celecoxib and flurbiprofen impaired angiogenesis and delayed ulcer healing, as well as increasing serum endostatin levels relative to those of VEGF. HCT-1026 did not delay ulcer healing nor impair angiogenesis, and also did not change the ratio of serum endostatin to VEGF. Incubation of human umbilical vein endothelial cells with serum from celecoxib- or flurbiprofen-treated rats resulted in suppressed proliferation and increased apoptosis, effects that were reversed by an antiendostatin antibody. These results demonstrate a previously unrecognized mechanism through which nonsteroidal antiinflammatory drugs can delay ulcer healing, namely, through altering the balance of anti- and proangiogenic factors in the serum. The absence of a delaying effect of HCT-1026 on ulcer healing may be related to the maintenance of a more favorable balance in serum levels of pro- and antiangiogenic growth factors.
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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".