Prolactin regulation of testosterone secretion and testes growth in DLS rams at the onset of seasonal testicular recrudescence
Bibliographic record
Abstract
Our objective was to test the hypothesis that prolactin (PRL) acts at both the pituitary and testis levels to regulate testosterone secretion in the adult ram. The focus was on the mid-regression to mid-redevelopment stages of a photoperiod-condensed 'seasonal' testicular cycle. DLS rams (six per group) were given daily s.c. injections of bromocriptine (4 mg) or vehicle during the entire period. Serum PRL concentration in control rams peaked at 103.4+/-22.1 ng/ml in late regression and then steadily declined (P<0.01) to 19.5+/-4.3 ng/ml, whereas PRL in treated rams was always < or =4.0 ng/ml. Suppression of PRL tended (P<0.10) to increase the amplitude of natural LH pulses (transition stages) or reduce the number of LH receptors in the testis (regressed stage), although neither change disturbed testosterone levels in peripheral blood. These subtle changes were accompanied by significant (P<0.05) alterations in the capability of the pituitary to release LH (85% more) and of the testes to secrete testosterone (20% less). These effects of PRL were unmasked when rams were given highly stimulative i.v. injections of GNRH (single 3 microg dose) and NIH-oLH-S24 (three 5 microg doses given 20 min apart) respectively. PRL insufficiency also appeared to slow down the 'seasonal' rise in FSH secretion and slightly delayed (2 weeks) the times when the testes began to grow and were first significantly (P<0.05) enlarged from the regressed state. We conclude that PRL is an important part of the intricate regulation of the pituitary-gonadal system in moderately seasonal DLS rams.
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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".