Stromal regulation of vessel stability by MMP14 and TGFβ
Bibliographic record
Abstract
Innate regulatory networks within organs maintain tissue homeostasis and facilitate rapid responses to damage. We identified a novel pathway regulating vessel stability in tissues that involves matrix metalloproteinase 14 (MMP14) and transforming growth factor beta 1 (TGFbeta(1)). Whereas plasma proteins rapidly extravasate out of vasculature in wild-type mice following acute damage, short-term treatment of mice in vivo with a broad-spectrum metalloproteinase inhibitor, neutralizing antibodies to TGFbeta(1), or an activin-like kinase 5 (ALK5) inhibitor significantly enhanced vessel leakage. By contrast, in a mouse model of age-related dermal fibrosis, where MMP14 activity and TGFbeta bioavailability are chronically elevated, or in mice that ectopically express TGFbeta in the epidermis, cutaneous vessels are resistant to acute leakage. Characteristic responses to tissue damage are reinstated if the fibrotic mice are pretreated with metalloproteinase inhibitors or TGFbeta signaling antagonists. Neoplastic tissues, however, are in a constant state of tissue damage and exhibit altered hemodynamics owing to hyperleaky angiogenic vasculature. In two distinct transgenic mouse tumor models, inhibition of ALK5 further enhanced vascular leakage into the interstitium and facilitated increased delivery of high molecular weight compounds into premalignant tissue and tumors. Taken together, these data define a central pathway involving MMP14 and TGFbeta that mediates vessel stability and vascular response to tissue injury. Antagonists of this pathway could be therapeutically exploited to improve the delivery of therapeutics or molecular contrast agents into tissues where chronic damage or neoplastic disease limits their efficient delivery.
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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".