Transgenic mice over-expressing galanin exhibit pituitary adenomas and increased secretion of galanin, prolactin and growth hormone
Bibliographic record
Abstract
Galanin is a biologically active 29 amino acid peptide, widely distributed in the central and peripheral nervous system, and most abundantly in the hypothalamus where it may serve in the regulation of anterior pituitary hormones. We herein report that mice carrying the rat preprogalanin cDNA specifically targeted to the somatomammotroph cell lineage, under the control of the rat GH promoter, over-express and over-secrete galanin. Galanin peptide is localised within the GH and prolactin secretory granules. GH and prolactin release is increased as well, predominantly in males, while older transgenic animals develop pituitary hyperplasia and adenoma. In both male and female transgenic mice there is a significant increase in serum galanin (P<0.00003 and P<0.001 respectively) and prolactin (P<0.002 and P<0.05 respectively) levels, while only in male transgenic mice is there a significant increase in the serum levels of GH. Furthermore, in male transgenic mice serum prolactin levels are significantly correlated with the serum galanin levels (P<0.03). We conclude that galanin plays a key role in the process of pituitary hyperplasia, acting as a growth factor to promote pituitary cell proliferation, and participates in pituitary adenoma formation not necessarily dependent on oestrogens. Targeted over-expression and over-secretion of galanin in the somatomammotroph cell lineage stimulates predominantly hyperprolactinaemia in an oestrogen-independent manner.
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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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".