Ischaemia–reperfusion injury activates matrix metalloproteinases in the human heart
Bibliographic record
Abstract
AIMS: Matrix metalloproteinases (MMPs) and tissue inhibitors of metalloproteinases (TIMPs) regulate matrix remodelling in the heart and play a pivotal role in myocardial dysfunction immediately following ischaemia-reperfusion injury ex vivo in rats. We investigated the changes in MMPs and TIMPs in acute myocardial ischaemia-reperfusion injury in humans. METHODS AND RESULTS: Fifteen patients with stable angina undergoing coronary artery bypass graft surgery with cardiopulmonary bypass were enrolled. Left ventricular stroke work index was monitored prior to bypass and for 24 h following reperfusion. Left atrial biopsy samples were obtained at the start of bypass before cardioplegia and within 10 min after removal of the aortic cross-clamp. Plasma samples were collected from the radial artery and coronary sinus 1, 5, and 10 min following removal of the cross-clamp. In cardiac biopsies there was a marked increase in 72 kDa MMP-2 and 92 kDa MMP-9 activities, and a decrease in TIMP-1 upon reperfusion. Increased MMP activity correlated positively with cross-clamp duration and inversely with cardiac mechanical function 3 h following reperfusion. TIMP-1 correlated inversely with cross-clamp time and positively with cardiac mechanical function. Plasma samples revealed a significant increase in both 92 kDa MMP-9 and 64 kDa MMP-2 activities 1 min following removal of cross-clamp. CONCLUSION: Reperfusion following cardioplegia activates MMPs in the myocardium and plasma of patients undergoing coronary artery bypass grafting. This is the first correlation of MMP myocardial activity with cardiac function in humans. The early increase in MMP activity produces a proteolytic environment that may contribute to myocardial stunning injury in humans.
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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 | 0.001 |
| 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) | 0.003 | 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".