siRNA-mediated inhibition of NTT-MMP-2 reduces oxidative stress and apoptotic signaling in an ex vivo model of ischemia/reperfusion injury
Bibliographic record
Abstract
Matrix metalloproteinase-2 (MMP-2), particularly its N-terminally truncated isoform (NTT-MMP-2), plays a pivotal role in cardiac ischemia-reperfusion (I/R) injury. NTT-MMP-2 is induced by oxidative stress and activates both pro-inflammatory and pro-apoptotic pathways as well as an innate immune response within the cell. This study investigated the involvement of NTT-MMP-2 in oxidative stress, inflammation, and cardiomyocyte injury, focusing on its mitochondrial activity. Using an ex vivo Langendorff-perfused rat heart model, we demonstrated that I/R significantly increased mitochondrial NTT-MMP-2 activity, total ROS/RNS production, and markers of cardiac injury, including lactate dehydrogenase activity (LDH), and reduced cardiac mechanical function. NTT-MMP-2 activity and cytochrome c positively correlated with nuclear factor kappa B (NF-κB) expression and LDH activity, while negatively correlating with heart rate and rate pressure product (cytochrome c), suggesting NTT-MMP-2 involvement in mitochondrial dysfunction and apoptotic signaling. Partial inhibition of MMP-2 with siRNA reduced NTT-MMP-2 activity, preserved cardiac function, and decreased cytochrome c and NF-κB levels, although it paradoxically increased NFATc1 and IL-6 expression. These findings indicate that while NTT-MMP-2 contributes to oxidative and inflammatory damage during IRI, it may not be the sole regulator of innate immune activation. Moreover, IL-6 upregulation following MMP-2 silencing may reflect a compensatory cardioprotective response. This study identifies NTT-MMP-2 as a potential therapeutic target in ischemic heart disease, with siRNA-based strategies offering partial protection against I/R injury through modulation of mitochondrial stress and apoptosis pathways.
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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) | 0.001 | 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".