Effect of freeze–thawing process on lipid peroxidation, miRNAs, ion channels, apoptosis and global DNA methylation in ram spermatozoa
Bibliographic record
Abstract
This study was carried out to investigate the effect of the semen freeze-thawing process on the functionality and molecular structure of ram spermatozoa. The temperature of pooled and diluted semen at 38°C (group 1, control) was lowered to 5°C (group 2), and it was subjected to glycerolisation-equilibration (group 3), frozen and thawed (group 4). Compared to the control, deterioration in spermatological parameters and significant increases in lipid peroxidation and global DNA methylation levels were observed in groups 3 and 4. When compared with the control, significant downregulation in the levels of miR-485 of group 2, miR-29a of group 3 and let-7a, miR-485 and miR-29a of group 4, and significant upregulation in the levels of miR-107 of group 3 and miR-127 of groups 3 and 4 were detected. In comparison to the control, significant upregulation in the levels of CatSper1, CatSper2, CatSper3, CatSper4, ANO1 and TRPM3 of group 2, CatSper4, ANO1 and TRPM3 of group 3 and KCNJ11 of group 4, and significant downregulation in the CatSper 3 level of group 4 were determined. As a result, the semen freeze-thawing process causes motility and morphological disorders in rams. This may be due to molecular changes associated with lipid peroxidation in spermatozoa.
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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".