Sequential Activation of Matrix Metalloproteinase 9 and Transforming Growth Factor β in Arterial Elastocalcinosis
Bibliographic record
Abstract
OBJECTIVE: Isolated systolic hypertension is associated with increased elastase activity, vascular calcification, and vascular stiffness. We sought to determine the importance of elastase activity and matrix degradation in the development of elastocalcinosis. METHODS AND RESULTS: Elastocalcinosis was induced in vivo and ex vivo using warfarin. Hemodynamic parameters, calcium deposition, elastin degradation, transforming growth factor (TGF)-beta signaling, and elastase activity were evaluated at different time points in the in vivo model. Metalloproteinases, serine proteases, and cysteine proteases were blocked to measure their relative implication in elastin degradation. Gradual elastocalcinosis was obtained, and paralleled the elastin degradation pattern. Matrix metalloproteinase (MMP)-9 activity was increased at 5 days of warfarin treatment, whereas TGF-beta signaling was increased at 7 days. Calcification was significantly elevated after 21 days. Blocking metalloproteinases activation with doxycycline and TGF-beta signaling with SB-431542 were able to prevent calcification. CONCLUSIONS: Early MMP-9 activation precedes the increase of TGF-beta signaling, and overt vascular elastocalcinosis and stiffness. Modulation of matrix degradation could represent a novel therapeutic avenue to prevent the gradual age-related stiffening of large arteries, leading to isolated systolic 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) | 0.000 | 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) | 0.001 | 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".