Agonist-Induced Activation of Matrix Metalloproteinase-7 Promotes Vasoconstriction Through the Epidermal Growth Factor–Receptor Pathway
Bibliographic record
Abstract
Matrix metalloproteinase (MMP)-dependent shedding of heparin-binding epidermal growth factor (HB-EGF) and subsequent activation of the EGF receptor (EGFR) in the cardiovasculature is emerging as a unique mechanism signaling growth effects of diverse G protein-coupled receptors (GPCRs). Among these GPCRs are adrenoceptors and angiotensin receptors that contribute to the pathogenesis of hypertension through their vasoconstrictive and growth effects. Focusing on alpha(1b)-adrenoceptors, we suggest here that MMP-dependent activation of the EGFR promotes vasoconstriction as well as growth. We identified MMP-7 as a major HB-EGF sheddase in rat mesenteric arteries and alpha(1b)-adrenoceptors, angiotensin receptors, and hypertension-stimulated MMP-7 activity. Adrenoceptors stimulated EGFR autophosphorylation in arteries, and this transactivation was opposed by the MMP-7 inhibitor GM6001 as well as MMP-7-specific antibodies. In isolated microperfused arteries, blockade of EGFR transactivation with inhibitors of the EGFR (AG1478 and PD153035), HB-EGF (CRM197 and neutralizing antibodies), or MMPs (doxycycline) inhibited adrenergic vasoconstriction. In spontaneously hypertensive rats but not in normotensive rats, the inhibition of MMPs with doxycycline (19.2 mg/d from week 7 until week 12) reduced systolic blood pressure and attenuated HB-EGF shedding in the mesenteric arteries. These findings suggest a previously unknown mechanism of vasoregulation whereby agonists of certain GPCRs (such as adrenoceptors and angiotensin receptors) activate MMPs (such as MMP-7) that shed EGFR ligands (such as HB-EGF), which then activate the EGFR, thereby promoting vasoconstriction as well as growth. Because this mechanism is triggered by agonists typically overexpressed in hypertension, its blockade may have therapeutic potential for simultaneously inhibiting pathological vasoconstriction and growth in hypertensive disorders.
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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) | 0.000 | 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 | 0.001 |
| 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".