Effect of Seminal Phospholipid-Binding Proteins and Follicular Fluid on Bovine Sperm Capacitation1
Bibliographic record
Abstract
Bovine seminal plasma (BSP) contains a family of novel phospholipid-binding proteins (BSP-A1/-A2, BSP-A3, and BSP-30-kDa; collectively called BSP proteins) that potentiate sperm capacitation induced by heparin or by serum high-density lipoprotein (HDL). BSP proteins stimulate lipid efflux from sperm that may occur during the early events of capacitation. Here, we investigated the role of BSP proteins, bovine follicular fluid (FF), and bovine follicular fluid HDL (FF-HDL) in sperm capacitation. FF and FF-HDL alone stimulated epididymal sperm capacitation (19.5% +/- 0.8% and 18.2% +/- 2.8%, respectively, control, 9.0% +/- 1.9%) that was increased by preincubation with BSP-A1/-A2 proteins (30.2% +/- 0.4% and 30.9% +/- 1.5%, respectively). In contrast, lipoprotein-depleted follicular fluid (LD-FF) alone was ineffective, and a preincubation with BSP-A1/-A2 proteins was necessary before sperm capacitation was stimulated (up to 22.8% +/- 1.4%). The interaction of BSP proteins with FF components was analyzed using ultracentrifugation, Lipo-Gel electrophoresis, SDS-PAGE, and gel filtration. We established that the BSP proteins interact with factors present in FF including FF-HDL. Additionally, we obtained evidence that BSP proteins, found associated with FF-HDL, were released from the sperm membrane during capacitation. These results confirm that the BSP proteins and the FF-HDL play a role in sperm capacitation.
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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) | 0.001 | 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".