MMP-2 Mediates Angiotensin II–Induced Hypertension Under the Transcriptional Control of MMP-7 and TACE
Bibliographic record
Abstract
Development of cardiovascular disease induced by excessive Gq protein-coupled receptor agonist stimulation depends on signaling networks involving multiple matrix metalloproteinases (MMPs) and metalloproteinase disintegrins (ADAMs). Here, we hypothesized that MMP-2, being a major gelatinase in cardiac and vascular tissue, was likely to play a key role in cardiovascular homeostasis. We targeted MMP-2 using complementary and overlapping approaches involving pharmacological inhibition and RNA interference in mice treated with angiotensin II (1.4 mg/kg per day) for 12 days. We studied the development of hypertension (by tail cuff plethysmography), cardiac hypertrophy (by M-mode echocardiography, cardiomyocyte cross-sectional area, and quantitative real-time polymerase chain reaction (qRT-PCR) analysis of hypertrophy marker genes), and fibrosis (by picrosirius red collagen staining and qRT-PCR analysis of fibrosis marker genes) in mice receiving angiotensin II. We found that angiotensin II infusion upregulated MMP-2 concurrent with the development of hypertension, hypertrophy, and fibrosis. This upregulation of MMP-2 depended on MMP-7 and TACE (tumor necrosis factor-α convertase, ADAM-17). RNA interference targeting MMP-7 and TACE attenuated the angiotensin II-induced upregulation of MMP-2 and prevented the development of hypertension, as well as development of cardiac hypertrophy and fibrosis. In contrast, pharmacological inhibition and RNA interference of MMP-2 attenuated angiotensin II-induced hypertension, without influencing development of cardiac hypertrophy or fibrosis. Downstream of MMP-7 and TACE, MMP-2 mediated angiotensin II-induced hypertension, but did not mediate cardiac hypertrophy or fibrosis. This suggests a functional specialization of MMP-2 in agonist-induced cardiovascular disease development that has potential implications for the design of metalloproteinase-based therapeutic strategies.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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 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".