Cyclooxygenase‐2 expression in human pituitary tumors
Bibliographic record
Abstract
BACKGROUND: Cyclooxygenase-2 (COX-2) plays a role in progression of colon, breast, pancreas, and lung carcinomas. The authors investigated COX-2 expression in pituitary tumors. METHODS: Expression of COX-2 was evaluated in 164 surgically removed human pituitary tumors. Correlation of COX-2 with MIB-1, a cell proliferation marker, as well as angiogenesis, patient age, gender, tumor type, size, invasiveness, and metastatic potential was investigated. RESULTS: Cyclooxygenase-2 immunoreactivity was confined to the cytoplasm of tumor cells, whereas the nuclei were unlabeled. Few normal peritumoral adenohypophysial cells showed slight COX-2 cytoplasmic immunoreactivity. The staining intensity and the percentage of immunopositive cells were higher in tumors. Most pituitary tumors (96%) were COX-2-immunopositive. Expression was strong in 60 (44%), moderate in 39 (28%), and weak in 32 (24%). Male gonadotroph adenomas and null cell adenomas showed a high level of COX-2 expression. Growth hormone-producing adenomas, prolactin-producing adenomas, thyrotropic hormone-producing adenomas, female gonadotroph adenomas, silent adrenocorticotropic hormone-producing adenomas, and silent subtype 3 adenomas had a low level of COX-2 expression. Significant correlation was demonstrated with patient age, but not with tumor size, invasiveness, and MIB-1 labeling indices. Expression was medium to high in 76% of macroadenomas and in only 45% of microadenomas. Strong correlations were noted with angiogenesis markers, such as microvessel density and surface density. CONCLUSIONS: Correlation with angiogenesis suggests that COX-2 may be involved in the regulation of angiogenesis in pituitary tumors. Phamacologic inhibition of COX-2 activity might suppress angiogenesis in pituitary tumors and may provide a novel approach for medical therapy.
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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".