Peroxynitrite-induced myocardial injury is mediated through matrix metalloproteinase-2
Bibliographic record
Abstract
OBJECTIVES: Peroxynitrite (ONOO(-)) mediates in part both ischemia-reperfusion and pro-inflammatory cytokine-induced injury to the heart. As oxidants like ONOO(-) are known to activate matrix metalloproteinases (MMPs), we examined whether they play a role in the detrimental action of ONOO(-) in isolated perfused rat hearts. METHODS: Hearts were isolated from Sprague-Dawley rats and perfused retrogradely with Krebs-Henseleit buffer under constant flow. Peroxynitrite (30 and 80 microM) was infused into the hearts for 15 min. The release of MMPs into the coronary effluent and level of MMPs in the myocardium were measured by gelatin zymography. RESULTS: The main gelatinolytic activity in control effluent was 72-kDa corresponding to pro-MMP-2. Infusion of ONOO(-) (80 microM) for 15 min caused a vasodilatation which peaked at 5 min and then converted into vasoconstriction by 15 min. It also caused a rapid increase in the release of 72-kDa activity within 10 min and a progressive decline in cardiac mechanical function. In contrast, decomposed ONOO(-) caused no change in vascular tone, the release of 72-kDa activity or mechanical function. The MMPs inhibitor PD-166793 prevented the ONOO(-)-induced loss in myocardial mechanical function. Detoxification of ONOO(-) with glutathione prevented both the enhancement in coronary effluent 72-kDa activity and the decline in mechanical function. CONCLUSIONS: Acute cardiac toxicity induced by ONOO(-) is mediated by MMP-2.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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) | 0.003 | 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".