Expression of cyclooxygenase-2 in ovarian mature cystic teratomas with malignant transformation
Bibliographic record
Abstract
Cyclooxygenase-2 (COX-2) has been reported to be associated with tumor progression and angiogenesis and we previously reported that an increase in COX-2 expression might be associated with malignant transformation and tumorigenesis of epithelial ovarian neoplasms. In this study, COX-2 expression of ovarian mature cystic teratomas with malignant transformation, a rare entity accounting for just 1.8% of all mature cystic teratomas, was investigated using immunohistochemical techniques. There were 89 cases of mature cystic teratomas treated with surgery as their initial therapy at Osaka City University Medical School Hospital between 1995 and 2001. Ten cases of these were selected for study; five cases of mature cystic teratoma with malignant transformation, and five cases of mature benign teratoma. Expressions of CD34, vascular endothelial growth factor (VEGF), and COX-2 were investigated. Expressions of VEGF and COX-2 were strong in tissues of mature cystic teratomas with squamous cell carcinoma; however, expressions of them were hardly apparent in mature benign teratomas and in mature cystic teratomas with adenocarcinomas. These results tend to suggest that COX-2 is associated with tumor growth and progression in mature cystic teratomas with squamous cell carcinoma, as opposed to mature benign teratomas and mature cystic teratomas with adenocarcinomas.
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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) | 0.000 | 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".