Plasminogen Activator Inhibitor-1 Regulates Tumor Growth and Angiogenesis
Bibliographic record
Abstract
Elevated expression of plasminogen activator inhibitor-1 (PAI-1) in tumors is associated with a poor prognosis in many cancers. Reduced tumor growth and angiogenesis have also been reported in mice deficient in PAI-1. These results suggest that PAI-1 may be required for efficient angiogenesis and tumor growth. In the present study, we demonstrate that PAI-1 can both enhance and inhibit the growth of M21 human melanoma tumors in nude mice and that this appears to be due to PAI-1 regulation of angiogenesis. Quantitative analysis of angiogenesis in a Matrigel implant assay indicated that in PAI-1 null mice angiogenesis was reduced approximately 60% compared with wild-type mice, while in mice overexpressing PAI-1, angiogenesis was increased nearly 3-fold. Furthermore, addition of PAI-1 to implants in wild-type mice enhanced angiogenesis up to 3-fold at low concentrations but inhibited angiogenesis nearly completely at high concentrations. Together, these data demonstrate that PAI-1 is a potent regulator of angiogenesis and hence of tumor growth and suggest that understanding the mechanism of this activity may lead to the development of important new therapeutic agents for controlling pathologic angiogenesis.
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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".