The Role of Hormones, Growth Factors and Their Receptors in Pituitary Tumorigenesis
Bibliographic record
Abstract
Numerous factors have been shown to govern adenohypophysial cell proliferation. Human and animal models have documented that the hypothalamic trophic hormone growth hormone-releasing hormone stimulates cell proliferation, and prolonged stimulation leads to tumor formation. Similarly, lack of dopaminergic inhibition of lactotrophs and lack of feedback suppression by adrenal, gonadal or thyroid hormones are implicated, perhaps through hypothalamic stimulatory mechanisms, in pituitary adenoma formation superimposed on hyperplasia. However, most pituitary tumors are not associated with underlying hyperplasia. Overexpression of growth factors and their receptors, such as EGF, TGFalpha, EGF-R and VEGF has been identified in pituitary adenomas, and reduction of follistatin expression has been implicated in gonadotroph adenomas. Aberrant expression of members of the FGF family, an FGF antisense gene and FGF receptors have all been described in pituitary adenomas. The clonal composition of pituitary adenomas attests to the molecular basis of pituitary tumorigenesis, however, the evidence suggests that these various hypophysiotropic hormones and growth factors likely play a role as promoters of tumor cell growth in genetically transformed cells.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".