Therapeutic potential of platelet-activating factor antagonism in the management of myocardial infarction.
Bibliographic record
Abstract
BACKGROUND: Antagonists of platelet-activating factor (PAF) reduce myocardial postischemia reperfusion injury when given before the onset of ischemia. However, the effects of PAF antagonists when administered at a clinically modelled time (during ischemia but before reperfusion) are controversial. Moreover, the extended survival (eight day) and the characteristics of scar formation after treatment with PAF antagonists have not been investigated. OBJECTIVES: To determine the therapeutic potential of PAF antagonist TCV-309 for the treatment of regional myocardial ischemia-reperfusion injury; and to determine the effects of TCV-309 on cardiovascular recovery, evolution of scar formation and survival eight days after a myocardial infarction treated with reperfusion. ANIMALS AND METHODS: Swine underwent regional myocardial ischemia for 60 mins by ligation of the left anterior descending coronary artery, followed by reperfusion for eight days. The treated group (n=7) received PAF antagonist TCV-309 (0.1 mg/kg) 45 mins after ligation; the untreated group (n=7) received vehicle only. RESULTS: Untreated animals experienced significantly (P<0.001) lower systemic arterial blood pressure during the reperfusion period than animals treated with TCV-309. Furthermore, untreated animals required significantly more (P<0.01) antiarrhythmic and inotropic support. Only two of seven animals in the untreated group survived, which was significantly different (P<0.05) from the six of seven treated animals that survived for eight days. Morphometric analyses did not show differences between groups in the characteristics of scar formation following reperfusion for eight days. CONCLUSIONS: PAF antagonist TCV-309 improves survival and reduces cardiovascular dysfunctions associated with regional myocardial ischemia reperfusion injury when administered at a clinically modelled time.
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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 | 0.001 |
| 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".