High Level of Vascular Endothelial Growth Factor in Hemorrhagic Pleural Effusion of Cancer
Bibliographic record
Abstract
Angiogenic cytokines, such as vascular endothelial growth factor (VEGF), basic fibroblast growth factor (bFGF) and angiogenin, are candidates for the induction of pleural effusions because they have been implicated in the induction of neovascularization, vascular permeability, and hemorrhage both in the inflammatory process and in tumor progression. Thus, we hypothesized that these angiogenic factors in effusion might be involved in the clinical manifestation of malignant pleural disease. We measured the levels of VEGF, bFGF, and angiogenin in pleural effusions and sera from 40 patients. Pleural effusions due to malignancy (1,350 pg/ml) contained significantly higher levels of VEGF than effusions due to inflammatory diseases (102 pg/ml; p = 0.034). Furthermore, hemorrhagic effusions showed significantly higher VEGF levels (1,942 pg/ml) than non-hemorrhagic effusions (202 pg/ml; p = 0.016) in malignant patients. In contrast, neither bFGF nor angiogenin were correlated with any clinical manifestation of pleural effusion. Immunohistochemical study revealed that malignant cells in the pleura were stained with anti-VEGF antibody. Our data suggest that VEGF secreted from tumor cells may be involved in the accumulation of pleural effusion in malignancy, and that increased levels of VEGF may induce hemorrhagic effusion.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".