Endocannabinoids protect the rat isolated heart against ischaemia
Bibliographic record
Abstract
1 The purpose of this study was to determine whether endocannabinoids can protect the heart against ischaemia and reperfusion. 2 Rat isolated hearts were exposed to low-flow ischaemia (0.5-0.6 ml min(-1)) and reperfusion. Functional recovery as well as CK and LDH overflow into the coronary effluent were monitored. Infarct size was determined at the end of the experiments. Phosphorylation levels of p38, ERK1/2, and JNK/SAPK kinases were measured by Western blots. 3 None of the untreated hearts recovered from ischaemia during the reperfusion period. Perfusion with either 300 nM palmitoylethanolamide (PEA) or 300 nM 2-arachidonoylglycerol (2-AG), but not anandamide (up to 1 micro M), 15 min before and throughout the ischaemic period, improved myocardial recovery and decreased the levels of coronary CK and LDH. PEA and 2-AG also reduced infarct size. 4 The CB(2)-receptor antagonist, SR144528, blocked completely the cardioprotective effect of both PEA and 2-AG, whereas the CB(1)-receptor antagonist, SR141716A, blocked partially the effect of 2-AG only. In contrast, both ACEA and JWH015, two selective agonists for CB(1)- and CB(2)- receptors, respectively, reduced infarct size at a concentration of 50 nM. 5 PEA enhanced the phosphorylation level of p38 MAP kinase during ischaemia. PEA perfusion doubled the baseline phosphorylation level of ERK1/2, and enhanced its increase upon reperfusion. The cardioprotective effect of PEA was completely blocked by the p38 MAP kinase inhibitor, SB203580, and significantly reduced by the ERK1/2 inhibitor, PD98059, and the PKC inhibitor, chelerythrine. 6 In conclusion, endocannabinoids exert a strong cardioprotective effect in a rat model of ischaemia-reperfusion that is mediated mainly through CB(2)-receptors, and involves p38, ERK1/2, as well as PKC activation.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".