Alleviation of Estrogen-Induced Hyperprolactinemia through Intracerebral Transplantation of Hypothalamic Tissue Containing Dopaminergic Neurons
Bibliographic record
Abstract
Prolactin-secreting pituitary tumors can be induced in young rats through prolonged estrogen treatment. Recent evidence suggests that such tumors are associated with a degeneration of tuberoinfundibular dopaminergic (TI-DA) neurons, which normally inhibit prolactin secretion by the anterior pituitary's lactrophs. For this study, chronic hyperprolactinemia was induced in young, ovariectomized Fisher 344 rats through Silastic capsule implants of 17 beta-estradiol, placed subcutaneously for 1 month prior to removal. Rats with such estrogen-induced hyperprolactinemia then received transplants of neonatal arcuate-median eminence (ME) tissue (containing TI-DA neurons) or amygdala (control) tissue, placed either within the third ventricle or bilaterally within the hypothalamus. Blood samples were obtained 1 month after transplantation and prolactin concentrations measured by radioimmunoassay. Two of 4 animals receiving ventricularly-placed arcuate-ME transplants and 4 of 7 animals receiving bilateral arcuate-ME transplants showed substantial reductions in plasma prolactin levels compared to mean values in control animals. Follow-up catecholamine (CA) histochemistry indicated a bright fluorescence intensity in the median eminence of animals remaining hyperprolactinemic with ineffective transplants. Furthermore, in sharp contrast to the very low, nonpulsatile LH levels found during a second bleeding in recipients bearing ineffective transplants, recipients with effective arcuate-ME transplants had the high, pulsatile levels of LH characteristic of normal, ovariectomized rats. These data suggest that developing TI-DA neurons, within effective arcuate-ME transplants, became functional to reinstate or accentuate DA inhibition of prolactin secretion and, in so doing, indirectly normalized LH secretion as well.
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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".