Role of platelet activating factor in cardiac dysfunction, apoptosis and nitric oxide synthase mRNA expression in the ischemic-reperfused rabbit heart.
Bibliographic record
Abstract
BACKGROUND: The role of platelet activating factor (PAF) and nitric oxide in myocardial ischemia-reperfusion (MIR) injury and the interrelationship of the two mediators is poorly understood. The contribution of PAF to apoptosis during MIR has not been studied. OBJECTIVES: To determine the contribution of PAF to ex vivo cardiac dysfunction during the initial 5 h of postischemia reperfusion, to determine the contribution of PAF to inducible nitric oxide synthase (NOS) and endothelial NOS mRNA expression during MIR, and to determine whether PAF contributes to apoptosis during MIR. METHODS: Isolated blood-perfused rabbit hearts underwent 30 min of global ischemia and 5 h reperfusion. Animals were divided into four groups, which received either PAF antagonist TCV-309 or vehicle before ischemia, or were sham operated (heart perfusion only), or were control (no heart perfusion). RESULTS: Administration of the PAF antagonist significantly improved myocardial contractility (614 mmHg/s versus 308 mmHg/s, positive dP/dt, P<0.0001) and coronary vascular flow rate (5.5 mL/min versus 3.9 mL/min, P<0.01) during reperfusion compared with untreated animals (values at 5 h reperfusion). Treatment with PAF antagonist significantly increased mRNA expression of endothelial NOS (2.8 versus 1.3 ratio, P<0.05) compared with the untreated group. PAF antagonist reduced procaspase-3 cleavage (66 versus 108 ratio, P<0.05) and DNA fragmentation (8.2 versus 11.0 positive cells per field) compared with untreated animals. CONCLUSIONS: PAF antagonism with TCV-309 protected against myocardial contractile depression and coronary vasoconstriction during the initial 5 h reperfusion. PAF may play a role in the regulation of endothelial NOS mRNA expression and contribute to apoptosis during ischemia-reperfusion in the heart.
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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 | 0.000 |
| 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".