Predicting sire fertility in artificial insemination of dairy cows by the ability of spermatozoa to bind to oviduct cell aggregates
Bibliographic record
Abstract
This study aimed to evaluate sperm morphofunctional characteristics and the ability of spermatozoa to bind to oviduct epithelial cell (OEC) aggregates as predictors of male field fertility. Based on pregnancy per artificial insemination (P/AI) data of 1,833 services in Holstein cows from a commercial dairy herd, sires were classified as of higher (HF, P/AI = 35.0% [362/1,034], n=3) or lower (LF, P/AI = 21.4% [171/799], n=4) fertility. Semen quality was assessed based on sperm motility (by computer-assisted sperm analysis, plasma and acrosome membrane integrity, mitochondrial membrane potential, membrane lipid peroxidation, and membrane fluidity [by flow cytometry], and OEC binding). For the analysis of OEC binding, the oviduct isthmus region from abattoir tracts was dissected, and cells were incubated for 24 h to allow OEC aggregate formation, followed by co-incubation with 1 × 10 5 motile sperm. Bound sperm were counted at 4 time points: 0.5, 12, 24, and 36 h. Statistical analyses were conducted using the GLIMMIX procedure in SAS 9.4 (SAS Institute Inc.). Sperm motility characteristics were not different between HF and LF sires, except for greater straight-line velocity in HF (HF: 94.7 ± 3.1 μm/s vs. LF: 80.9 ± 3.1 μm/s). Flow cytometry analysis was not able to explain the difference between fertility groups (P/AI). However, in the sperm binding test to OEC, the HF sires tended to have more bound sperm per millimeter of OEC than LF sires at 0.5 h of co-incubation (59.1 vs. 54.0). At h 12 (36.5 vs. 28.6), 24 (24.0 vs. 15.3), and 36 (26.0 vs. 12.1), HF sires had more bound sperm per millimeter of OEC than LF sires. Field fertility was positively correlated (r = 0.89) with the number of sperm bound per millimeter of OEC at 36 h of co-incubation. These results suggest that LF sires may have impaired fertility due to a reduced ability to bind to oviduct cells in vivo. In addition, the result showed the potential of sperm binding test to OEC for early evaluation or prediction of bulls' fertility, although more studies are being performed to refine the procedures during these assays, as well as to better understand other potential physiological mechanisms differing between HF and LF sires.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".