Elastase and matrix metalloproteinase inhibitors induce regression, and tenascin-C antisense prevents progression, of vascular disease
Bibliographic record
Abstract
Increased expression of the glycoprotein tenascin-C (TN) is associated with progression of clinical and experimental pulmonary hypertension. In cultured smooth muscle cells (SMCs) TN is induced by matrix metalloproteinases (MMPs) and amplifies the proliferative response to growth factors. Conversely, suppression of TN leads to SMC apoptosis. We now report that hypertrophied rat pulmonary arteries in organ culture, which progressively thicken in association with cell proliferation and matrix accumulation, can be made to regress by inhibiting either serine elastases or MMPs. This effect is associated with reduced TN, suppression of SMC proliferation, and induction of apoptosis. Selective repression of TN by transfecting pulmonary arteries with antisense/ribozyme constructs also induces SMC apoptosis and arrests progressive vascular thickening but fails to induce regression. This failure is related to concomitant expansion of a SMC population, which produces an alternative cell survival alpha(v)beta(3) ligand, osteopontin (OPN), in response to pro-proliferative cues provided by a proteolytic environment. OPN rescues MMP inhibitor-induced SMC apoptosis, and alpha(v)beta(3) blockade induces apoptosis in hypertrophied arteries. Our data suggest that proteinase inhibition is a novel strategy to induce regression of vascular disease because this overcomes the pluripotentiality of SMC-matrix survival interactions and induces coordinated apoptosis and resorption of matrix.
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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".