Morphologic, Steroidogenic, and Transcriptomic Assessment of the Corpus Luteum in Holstein Cows after Spontaneous or Hormone-Induced Ovulation
Bibliographic record
Abstract
There is evidence that replacing the gonadotropin-releasing hormone (GnRH) with porcine luteinizing hormone (pLH) to synchronize ovulation prior to artificial insemination (AI) increased pregnancy per AI in dairy cows without affecting blood progesterone (P4) concentrations. Whether morphologic, steroidogenic, and transcriptomic differences exist among corpora lutea (CL) formed after ovulation induced by GnRH and pLH is unclear. Our main objective, therefore, was to compare CL characteristics between GnRH- and pLH-induced CL. In 24 non-lactating Holstein cows, ovulations were spontaneous (Spont-Ov) or induced with 100 µg GnRH, 25 mg pLH, or 1 mg estradiol benzoate (EB), with CL excised 12 d after ovulation. In pLH- versus GnRH-treated cows, the duration of elevated LH (above baseline) was prolonged (10 versus 6 h, respectively, p < 0.01), but CL dimensions, pixel intensity of CL images, proportions of steroidogenic and non-steroidogenic luteal cells, and mean plasma LH did not significantly differ. Post-ovulation mean plasma P4 (ng/mL) did not differ among Spont-Ov (3.0) pLH (3.1) or GnRH (3.0) cows but were lower in EB cows (2.0). In vitro P4 concentration was greater in luteal explants of pLH-treated cows than in all other groups (combined means, 16.0 vs. 12.3 µg/mL, p < 0.02). Relative abundance of mRNA for oxytocin receptor (OXTR) was 2-fold higher (p < 0.01) in CL of pLH vs. GnRH cows and highest in Spont-Ov CL. In summary, pLH-treated cows had a longer LH peak, and greatest luteal tissue concentrations and in vitro production of P4. We inferred that increased P4 concentrations at the ovarian–uterine level in pLH-treated cows could have promoted embryo development and increased pregnancy per AI.
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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".