Dopamine Creates a Physical Barrier to Inhibit Prolactin Release in Mammotrophs of Estradiol-Primed Male Rats
Bibliographic record
Abstract
After finding that ergocristine and somatostatin can cause extensive changes in mammotroph ultrastructure within 2 min of administration, we chose dopamine, the putative physiological prolactin-inhibiting factor, to correlate ultrastructural changes to inhibition of prolactin release. In order to choose a dose of dopamine for this study we tested the effects of 2 doses of dopamine (10 and 1,000 micrograms/kg) on inhibition of prolactin release. The higher dose of dopamine (1,000 micrograms/kg) completely inhibited prolactin release immediately (in less than 2 min) and maintained complete blockage for a period of 14 min. For the ultrastructural study we injected dopamine (1,000 micrograms/kg) in the right atrium of conscious free-moving rats through indwelling cannulae, and killed the rats by decapitation 2 min after dopamine administration. The following changes in mammotrophs were observed after the dopamine treatment: (1) increased numbers of secretory granules, (2) peripheral relocation of rough endoplasmic reticulum, and (3) increased numbers of 'intracellular bodies' (putative prolactin granule disposal system) associated with secretory granules. Because these rapid ultrastructural changes have been observed after treatment with three different compounds (dopamine, somatostatin and ergocristine), we do not believe that they are the unique effect of any one compound but the common denominator of the three compounds, i.e., inhibition of prolactin secretion being closely linked to the ultrastructural changes. We thus propose that the extensive ultrastructural changes that occurred in such a short period of time following dopamine administration are the mechanism of inhibition of prolactin release.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".