324 ADJUSTING SPERM CONCENTRATION USED TO INSEMINATE SUPERSTIMULATED BEEF COWS, IN ORDER TO AVOID DECLINE IN EMBRYO PRODUCTION
Bibliographic record
Abstract
The quantity and quality of semen may affect conception rate after artificial insemination (AI). The concentration of motile spermatozoa, after thawing, varies according to the sire and lot of frozen semen used. The minimum amount of spermatozoa required in a semen straw was determined to obtain pregnancy after a single AI of a non-superovulated animal. However, superstimulation of embryo donors results in the availability of many more oocytes (an average 10–20) for fertilization than in a non-superovulated female (1 oocyte). The purpose of the present work was to verify if by adjusting the concentration of motile spermatozoa, in straws with low sperm concentration, the percentage of viable embryos is comparable to those obtained using straws with high sperm concentration after thawing. Nelore cows (Bostaurusindicus) were superstimulated with a protocol termed P36 (Barros CM et al. 2003 Theriogenology 59, 524 abst), in which the ovulation is induced by exogenous LH (12.5 mg, Lutropin®, Vetrepharm, London, Ontario, Canada), administered 36 h after PGF2a. One sample of each lot of semen was analyzed by CASA (computer-assisted semen analysis), and motile sperm concentration, after thawing, was adjusted to a minimum of 25–30 × 106 spermatozoa, which is approximately 3 to 4 times higher than the sperm concentration used for a regular AI. Fixed-time AI (FTAI) was performed 12, 24, and sometimes 36 h after exogenous LH. The number of semen straws necessary to obtain at least 25 × 106 spermatozoa varied from 2 to 6 (Groups 2 to 6, respectively). Since at least two semen straws were used per animal, there is no Group 1. The number of FTAI was adjusted according to the number of straws used, i.e., 2 straws (FTAI 12 and 24 h after LH), and 3 or more straws (12, 24, and 36 h after LH). Mean total structures (oocytes, viable embryos and degenerate embryos), mean viable embryos per flushing, and viability rate (percentage of viable embryos/total structures) were, respectively: 12.2, 8.9, and 73.6% (Group 2, n = 19 flushings); 13.5, 9.6, and 70.9% (Group 3, n = 101); 13.3, 9.4, and 70.9% (Group 4, n = 22); 5.5, 4.0, and 72.7% (Group 5, n = 4); and 24.0, 13.0, and 54.2% (Group 6, n = 1). When the results from Groups 4, 5, and 6 were pooled, total structures, viable embryos, and viability rate were: 12.5, 8.7, and 69.8% (n = 27). The statistical analysis was performed using the ratio of viable embryos/total structures for each flushing, transformed in square root followed by arc sin. Data from groups 4, 5 and 6 were pooled before comparing to the other groups by ANOVA. In order to facilitate the comprehension of the results, data were presented as viability rate instead of means of arc sin. There was no difference when comparing pooled data from Groups 4, 5, and 6 with the other groups (2 or 3; P = 0.87; ANOVA). It is concluded that by adjusting the concentration of motile spermatozoa in straws with low sperm concentration (Groups 4, 5, and 6), the viability rates are comparable to those obtained using semen with high sperm concentration (Group 2 or 3). Nogueira has a fellowship from FAPESP (Sã Paulo).
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".