Immunoexpression of the human kallikrein‐10 in surgically removed human pituitary tumors (1048.12)
Bibliographic record
Abstract
Human kallikrein 10 (hK10), a serine protease, plays an important role in the regulation of cell proliferation and tumor growth. Its presence was demonstrated in lactotrophs and corticotrophs of the nontumorous human pituitary. In this work, we investigated hK10 immunoexpression in 59 surgically removed human pituitary tumors. Tissues were fixed in formalin, embedded in paraffin. Immunostaining was performed by the streptavidin‐biotin‐peroxidase complex protocol using the LSAB+ Kit (DAKO, Carpenteria, CA) and an hK10‐specific rabbit polyclonal antibody (1:150). Results showed that lactotroph adenomas removed from patients receiving no dopamine agonist medication were conclusively immunopositive for hK10. Immunopositivity was localized in the cytoplasm and was clearly visible in many adenoma cells. In the various tumor types (silent corticotroph subtype 1 & 2, oncocytic and gonadotrophic adenomas, somatotroph adenomas, and carcinomas), immunopositivity was very mild, seen only in few unevenly distributed tumor cells. Previous studies showed that hK10 possesses tumor suppressing properties and is decreased in rapidly growing tumor cells. Future studies should focus on hK10 immunoexpression in lactotroph adenomas exposed to dopamine agonist therapy which inhibits tumor growth. This study was supported by the Jarislowsky and Lloyd Carr‐Harris Foundations.
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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 | 0.000 | 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) | 0.002 | 0.001 |
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".