Effects of Long-term Storage on Some Spermatological Parameters in Cryopreserved Bull Semen.
Bibliographic record
Abstract
BACKGROUND: The effect of the long-term storage in liquid nitrogen on semen quality has not be reported. OBJECTİVE: The study measured the spermatological parameters of bull sperm after the long-term and short-term storage. MATERIALS AND METHODS: Vintage semen (obtained from 5 Brown Swiss bulls and frozen 30 years ago) and newly frozen semen collected from 5 bulls of the same breed and prepared at the International Center for Livestock Research and Training were used. For each bull, 10 straws (0.25 ml) were thawed and pooled. Sperm samples were analyzed by flow cytometry, computer assisted sperm analysis, and total oxidant-antioxidant levels were also tested. RESULTS: The ratios of necrotic (P < 0.001) and apoptotic (P = 0.006) spermatozoa, and the ratios of total antioxidant status (TAS) and total oxidant status (TOS) were significantly higher (P < 0.001) in long-term frozen spermatozoa. However, the early necrotic ratios (P < 0.001), velocity average pathway (VAP) (P = 0.008) and velocity curvi linear (VCL) (P = 0.01) values of long-term frozen semen were lower compared with short-term frozen semen. While necrotic and apoptotic spermatozoa ratios and total oxidant level were higher, VAP/VCL ratios were lower in long-term frozen sperms compared to short-term frozen semen. CONCLUSION: Long-term storage of sperm may adversely affect the spermatological and oxidative parameters of Brown Swiss bull 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 | 0.001 | 0.001 |
| 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) | 0.002 | 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".