Regulation of Galanin by Dexamethasone in the Rat Anterior Pituitary and the Uterus
Bibliographic record
Abstract
Galanin is a 29 amino acid neuropeptide widely distributed throughout the mammalian nervous and endocrine system. We have previously reported that estrogen dramatically increases galanin gene expression and protein synthesis in the anterior pituitary (AP), while the expression in the uterus (UT) of the same animals is transient and similar to the induction of protooncogenes (c-fos, c-jun, c-myc). In order to examine if this pattern of induction is specific to estrogen administration, we investigated the effect of glucocorticoids, another steroid, on the gene expression of galanin in the AP and in the UT of ovariectomized female rats and in the AP of male rats. Using Northern blot analysis, the AP and the UT showed almost undetectable levels of galanin mRNA, but in vivo treatment of female rats with 1 mg/kg body weight of dexamethasone (DEX) led to a significant increase of galanin mRNA levels in both AP and UT. Similarly, DEX (0.1-5 mg/kg i.p.) significantly stimulated galanin mRNA levels in the AP of the male rats. In both males and females the peak of induction was at 9 h after injection that is different from the 3-hour peak after estrogen administration. Daily injection of DEX for up to 7 days sustained the levels of galanin mRNA in both the AP and the UT, in contrast to the transient induction of galanin in the UT after estrogen administration. No change was noted in the galanin protein content of AP (control = 30 +/- 3.5 ng/mg protein; DEX treated = 38 +/- 4.2 ng/mg protein). Interestingly, in the UT of ovariectomized rats the combination of DEX and DES (diethylstilbestrol) treatment for 2 days resulted in a synergistic stimulation of galanin mRNA. In summary, these data demonstrate a tissue- and steroid-specific regulation of the galanin gene in AP and UT and suggest that DEX regulates the galanin gene possibly through a pathway different from estrogen.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".