Chronic ergot exposure in adult bulls suppresses prolactin but minimally impacts results of typical breeding soundness exams
Bibliographic record
Abstract
Canadian standards allow ≤3000 μg ergot alkaloids/kg cattle feed. A concentration-response relationship was hypothesized between ergot in feed and reductions in plasma prolactin, sperm motility, sperm function, and increase in sperm abnormalities. The study consisted of pre-treatment (12 weeks), treatment (9 weeks), and post-treatment periods (10 weeks). Adult bulls were fed 1113 (n = 8; low ergot group) or 2227 (n = 6; high) μg/kg of dry matter intake. Endpoints were measured every two weeks. Ejaculates were analyzed for sperm concentration, total and progressive motility, plasma membrane and acrosome integrity, mitochondrial membrane potential and sperm abnormalities. Data were analyzed by repeated measures MIXED PROC in SAS. Average outside ambient temperature during the pre-treatment, treatment, and post-treatment periods was -13 (-31 to 1), 0.5 (-18 to 19), and 21 (13-28) °C. Plasma prolactin decreased markedly during treatment (-52.4%; Experimental period p < 0.01). Rectal temperature increased during the treatment and post-treatment periods (EP p < 0.01) but was within the normal physiological range. Bull weight increased during the study (EP p < 0.01). Scrotal circumference in low ergot group increased during treatment (+0.8 cm; Tx∗EP p = 0.05). Progressive motility in high ergot group decreased during treatment (-7%; Tx∗EP p = 0.05), however, semen volume and sperm concentrations were unaffected (p ≥ 0.11). Live sperm with high and medium MMP decreased during treatment (-1.4 and -3.7%; EP p < 0.01). Results suggest that feeding ≤2227 μg ergot alkaloids/kg has only minor effects on adult bull semen quality.
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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) | 0.003 | 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".