Prolactin Regulation of Pro-Opiomelanocortin Gene Expression in the Arcuate Nucleus of the Rat Hypothalamus
Bibliographic record
Abstract
It is well known that the opiate peptides, especially the pro-opiomelanocortin (POMC)-related peptide beta-endorphin, stimulate the release of prolactin (PRL) in the rat. In order to evaluate the involvement of PRL on the activity of POMC neurons in the arcuate nucleus, we have studied the effects of the injection of PRL into the third ventricle of intact and hypophysectomized rats as well as the effects of hyperprolactinemia induced by pituitary implants under the kidney capsule on POMC gene expression. The amounts of POMC mRNA in the arcuate nucleus were measured by in situ hybridization using a [35S]-labelled cDNA probe encoding for POMC. Hypophysectomy performed 2 weeks previously decreased by 24% the number of silver grains/unit of surface of labelled neurons. Intracerebroventricular injection of 3 micrograms of PRL 4 h before sacrifice induced a significant decrease in the hybridization signal of 32 and 20% in the intact and hypophysectomized rat, respectively. Hyperprolactinemia achieved by pituitary implants also led to a significant decrease in POMC mRNA levels. The present data show that hypophysectomy depresses hypothalamic POMC mRNA levels and that this effect is not related to the suppression of PRL secretion since this hormone exerts an inhibitory action on POMC gene expression. They suggest that the regulation of PRL secretion by short loop feedback mechanism might be well mediated by beta-endorphin which has already been shown to inhibit dopaminergic neuron activity in the arcuate nucleus.
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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) | 0.001 | 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".