Myocardial MMP-2 contributes to SERCA2a proteolysis during cardiac ischaemia–reperfusion injury
Bibliographic record
Abstract
AIMS: Matrix metalloproteinase-2 (MMP-2) is a zinc-dependent protease which contributes to cardiac contractile dysfunction when activated during myocardial ischaemia-reperfusion (IR) injury. MMP-2 is localized to several subcellular sites inside cardiac myocytes; however, its role in the sarcoplasmic reticulum (SR) is unknown. The Ca2+ ATPase SERCA2a, which pumps cytosolic Ca2+ into the SR to facilitate muscle relaxation, is degraded in cardiac IR injury; however, the protease responsible for this is unclear. We hypothesized that MMP-2 contributes to cardiac contractile dysfunction by proteolyzing SERCA2a, thereby impairing its activity in IR injury. METHODS AND RESULTS: Isolated rat hearts were subjected to IR injury in the presence or absence of the selective MMP inhibitor ARP-100, or perfused aerobically as a control. Inhibition of MMP activity with ARP-100 significantly improved the recovery of cardiac mechanical function and prevented the increase of a 70 kDa SERCA2a degradation fragment following IR injury, although 110 kDa SERCA2a and phospholamban levels appeared unchanged. Electrophoresis of IR heart samples followed by LC-MS/MS confirmed the presence of a SERCA2a fragment of ∼70 kDa. MMP-2 activity co-purified with SR-enriched microsomes prepared from the isolated rat hearts. Endogenous SERCA2a in SR-enriched microsomes was proteolyzed to ∼70 kDa products when incubated in vitro with exogenous MMP-2. MMP-2 also cleaved purified porcine SERCA2a in vitro. SERCA activity in SR-enriched microsomes was decreased by IR injury; however, this was not prevented with ARP-100. CONCLUSION: This study shows that MMP-2 activity is found in SR-enriched microsomes from heart muscle and that SERCA2a is proteolyzed by MMP-2. The cardioprotective actions of MMP inhibition in myocardial IR injury may include the prevention of SERCA2a degradation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".