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 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 | 0.001 | 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".