Effects of different extenders on epigenetic patterns and functional parameters of bull sperm during cryopreservation process
Bibliographic record
Abstract
The cryopreservation process induces alterations in cellular parameters and epigenetic patterns in bull sperm, which can be prevented by adding cryoprotectants in the freezing extenders. The purpose of this study was to compare the protective effects of two extenders based on soybean lecithin (SLE) and egg yolk (EYE) on epigenetic patterns and quality parameters of sperm such as motility parameters, mitochondrial membrane integrity, DNA fragmentation, viability, and apoptotic-like changes of bull sperm after cryopreservation. Results demonstrated that cryopreservation significantly (p < .05) reduced the level of DNA global methylation, H3K9 histone acetylation, and H3K4 histone methylation in both frozen groups compared to the fresh sperm. Also, the level of H3K9 acetylation was lower in the frozen SLE group (21.2 ± 1.86) compared to EYE group (15.2 ± 1.86). In addition, the SLE frozen group had a higher percentage of viability, progressive motility, and linearity (LIN) in SLE frozen group compared to EYE frozen group. However, no difference was observed in mitochondrial membrane integrity and DNA fragmentation between SLE and EYE frozen groups. While soybean-lecithin-based extender showed some initial positive impacts of epigenetics and semen parameters, further investigations can provide useful information for better freezing.
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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".