Cryopreservation in Different Concentrations of Glycerol Alters Boar Sperm and Their Membranes
Bibliographic record
Abstract
To test the hypothesis that glycerol would concomitantly affect sperm membrane structure and the function of the intact cells, boar semen (4 ejaculates from 4 boars) was cryopreserved in an egg yolk extender with 0%, 2%, 4%, or 8% glycerol in 0.5-mL straws using previously derived optimal cooling and thawing rates. Increasing glycerol concentrations increased spermatozoal progressive motility immediately after thawing and after 2 hours at 43 degrees C, but decreased the percentage of sperm with normal acrosomal morphology. The mathematical products of the motility and acrosomal integrity scores (MOT x NAR index) were low in 0% and 8% glycerol, and significantly higher in 2% and 4% glycerol. The fluidity of sperm-head plasma membranes, a measure of molecular interaction, was assessed with the lipid probes trans-parinaric acid and cisparinaric acid (tPNA, cPNA), during a 2.5-hour incubation with or without 1 mM Ca2+. Membrane fluidity detected by each probe differed significantly, indicating the presence of at least 2 domains whose constituent molecules had unique dynamics. Behavior of each domain was radically altered by cryopreservation. Increasing glycerol concentration caused a variably faster loss of fluidity in the cPNA domain, and had highly variable effects on fluidity change over time in the tPNA domain. Normal acrosomal ridge (NAR) and the MOT x NAR index correlated significantly with the fluidity of the more mobile cPNA domain (+/- 1 mM Ca2+), supporting the hypothesis of an interrelationship of glycerol concentration during cryopreservation with sperm membrane structure and cell function. The MOT x NAR index may be a useful guide in choosing optimal cryoprotectant concentrations.
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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".