Inhibition of matrix metalloproteinase‐2 improves endothelial function and prevents hypertension in insulin‐resistant rats
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Insulin resistance is often found to be associated with high blood pressure. We propose that in insulin-resistant hypertension, endothelial dysfunction is the consequence of increased activity of vascular MMP-2. As MMP-2 proteolytically cleaves a number of extracellular matrix proteins, we hypothesized that MMP-2 impairs endothelial function by proteolytic degradation of endothelial NOS (eNOS) or its cofactor, heat shock protein 90 (HSP90). EXPERIMENTAL APPROACH: We tested our hypothesis in bovine coronary artery endothelial cells and fructose-fed hypertensive rats (FHR), a model of acquired systolic hypertension and insulin resistance. KEY RESULTS: Treatment of FHRs with the MMP inhibitor doxycycline, preserved endothelial function as well as prevented the development of hypertension, suggesting that MMPs impair endothelial function. Furthermore, incubating endothelial cells in vitro with a recombinant MMP-2 decreased NO production in a dose-dependent manner. Using substrate cleavage assays and immunofluorescence microscopy studies, we found that MMP-2 not only cleaves and degrades HSP90, an eNOS cofactor but also co-localizes with both eNOS and HSP90 in endothelial cells, suggesting that MMPs functionally interact with the eNOS system. Treatment of FHRs with doxycycline attenuated the decrease in eNOS and HSP90 expression but did not improve insulin sensitivity. CONCLUSIONS AND IMPLICATIONS: Our data suggest that increased activity of MMP-2 in FHRs impairs endothelial function and promotes hypertension. Inhibition of MMP-2 could be a potential therapeutic strategy for the management of hypertension.
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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 | 0.000 |
| 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 | 0.001 |
| 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".