Immunoexpression of endoglin and CD‐34 in various human pituitary adenoma types
Bibliographic record
Abstract
Angiogenesis is a crucial event in tumor growth, invasion and development of metastasis. Endoglin (CD‐105), a disulfide‐linked homodimeric cell membrane glycoprotein of 180 kDa, located on chromosome 9q and binds to several components of the TGF beta family. In contrast to other endothelial cell markers, endoglin can be demonstrated only in proliferating endothelial cells. We investigated endoglin immunoexpression in various surgically removed human pituitary tumor types and compared the results with CD‐34 immunoexpression. For immunohistochemistry, the streptavidin‐biotin‐peroxidase complex method was used and the number of vessels were counted in 10 low power fields. Results show that endoglin immunostains fewer vessels than CD‐34 in every pituitary adenoma type. The number of endoglin immunopositive vessels is highest in untreated prolactinomas and subtype 3 silent pituitary adenomas and lowest in subtype 1 silent corticotroph adenomas and GH adenomas exposed to somatostatin analogs and prolactinomas exposed to dopamine agonists. Our findings are consistent with the view that endoglin is upregulated in proliferating endothelial cells and its expression can be used as an indicator of vascular neoformation in pituitary tumors. The low levels of endoglin expression in pituitary tumors exposed to somatostatin or dopamine agonists suggests that these therapeutic drugs can inhibit 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 | 0.001 | 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".