Immunohistochemical study on tumor angiogenic factors in non-small cell lung cancer.
Bibliographic record
Abstract
BACKGROUND: In order to elucidate the roles of tumor angiogenesis in lung carcinogenesis, the expressions of several angiogenic factors in lung carcinoma tissues were examined. MATERIALS AND METHODS: Tissue specimens from 112 cases of resected non-small cell lung cancer (NSCLC) were studied. The expressions of platelet-derived endothelial cell growth factor (PD-ECGF) and vascular endothelial growth factor (VEGF) were examined immunohistochemically. Microvessel density (MVD) was also evaluated. RESULTS: VEGF-positive cases were observed more frequently in advanced stage lung cancers than in early cancers, and VEGF-positive tumors had higher MVD than VEGF-negative tumors, while such differences were not observed for PD-ECGF. In squamous cell carcinoma, the patients with high-MVD tumor had significantly worse survival than those with low-MVD tumor. CONCLUSIONS: Our results suggest that VEGF plays an important role in angiogenesis of lung cancers, while the contribution of PD-ECGF may be limited.
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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 | 0.001 | 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".