New insights towards understanding the mechanisms of sperm protection by egg yolk and milk
Bibliographic record
Abstract
Mammalian sperm preservation in extenders containing egg yolk (EY) and/or milk has been used for over half a century. However, the mechanism by which EY or milk protects sperm during storage remains elusive. Studies conducted over the past two decades in our laboratory have revealed that a family of lipid-binding proteins (BSP proteins) present in bull seminal plasma is detrimental to sperm preservation since these proteins induce cholesterol and phospholipid removal from the sperm membrane. Interestingly, these detrimental factors of seminal plasma interact with the low-density lipoproteins (LDL) present in EY. This interaction minimizes lipid removal from the sperm membrane, which positively influences sperm storage in liquid or frozen states. Based on several lines of evidence, we suggest that the sequestration of BSP proteins by LDL (BSP proteins: lipoprotein interaction) is the major mechanism of sperm protection by EY. Skimmed milk, which is devoid of lipoproteins, also protects sperm during storage. Several studies indicate that the active components involved in sperm protection by milk are casein micelles. Thus, it appears that the mechanism by which milk protects sperm involves a BSP protein: casein micelle interaction. In view of these new insights, novel strategies have been suggested to improve the efficiency of semen preservation.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".