Platelets modulate gastric ulcer healing: Role of endostatin and vascular endothelial growth factor release
Bibliographic record
Abstract
Bleeding and delayed healing of ulcers are well recognized clinical problems associated with the use of aspirin and other nonsteroidal antiinflammatory drugs, which have been attributed to their antiaggregatory effects on platelets. We hypothesized that antiplatelet drugs might interfere with gastric ulcer healing by suppressing the release of growth factors, such as vascular endothelial growth factor (VEGF), from platelets. Gastric ulcers were induced in rats by serosal application of acetic acid. Daily oral treatment with vehicle, aspirin, or ticlopidine (an ADP receptor antagonist) was started 3 days later and continued for 1 week. Ulcer induction resulted in a significant increase in serum levels of VEGF and a significant decrease in serum levels of endostatin (an antiangiogenic factor). Although both aspirin and ticlopidine markedly suppressed platelet aggregation, only ticlopidine impaired gastric ulcer healing and angiogenesis as well as reversing the ulcer-associated changes in serum levels of VEGF and endostatin. The effects of ticlopidine on ulcer healing and angiogenesis were mimicked by immunodepletion of circulating platelets, and ticlopidine did not influence ulcer healing when given to thrombocytopenic rats. Incubation of human umbilical vein endothelial cells with serum from ticlopidine-treated rats significantly reduced proliferation and increased apoptosis, effects reversed by an antibody directed against endostatin. Ticlopidine treatment resulted in increased platelet endostatin content and release. These results demonstrate a previously unrecognized contribution of platelets to the regulation of gastric ulcer healing. Such effects likely are mediated through the release from platelets of endostatin and possibly VEGF. As shown with ticlopidine, drugs that influence gastric ulcer healing may do so in part through altering the ability of platelets to release growth factors.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".