Immunohistochemical expression of pituitary tumor transforming gene in pituitary adenomas: clinico‐pathological variables
Bibliographic record
Abstract
Pituitary tumor transforming gene (PTTG) was initially found to be overexpressed in GH4 rat pituitary adenomas (PA). PTTG overexpression has been correlated with patient survival, tumor grade, and/or invasiveness in several tumors including those of thyroid, breast, lung, and colon. Studies of PTTG as a prognostic indicator in PAs are limited and show conflicting results. We investigated PTTG immunostaining in 79 PAs of different subtypes (growth hormone (GH), 12; prolactin (PRL), 6, adrenocorticotropic hormone (ACTH), 11, gonadotroph, 21; null cell, 29) in relation to clinico‐pathological variables including patient age and sex, as well as tumor size, and invasiveness. The streptavidin‐biotin‐peroxidase method was used, with a monoclonal PTTG antibody (Abcam, Cambridge, UK). PTTG expression was found to be cytoplasmic in all PAs, with highest levels being present in GH adenomas and lowest in the PRL ones. No correlation was found with patient age, sex, tumor size or invasiveness. Thus, it appears that PTTG cannot serve as a prognostic marker in patients with PAs. PTTG has been implicated in several tumorigenic processes including angiogenesis, DNA damage repair and invasiveness. PTTG overexpression in PA warrants further research into its role in PA initiation and progression.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".