Radioimmunoassays for Bull Seminal Plasma Proteins (BSP-A1/-A2, BSP-A3, and BSP-30-Kilodaltons), and Their Quantification in Seminal Plasma and Sperm1
Bibliographic record
Abstract
Three proteins, BSP-A1/-A2, BSP-A3, and BSP-30 kilodaltons (collectively called BSP proteins), represent the major proteins of bovine seminal plasma (BSP). At ejaculation, these proteins bind to the sperm surface and induce molecular changes in the plasma membrane that are deemed to be essential for sperm capacitation. The present study was carried out to develop specific radioimmunoassays (RIAs) for the quantification of each of the BSP proteins in BSP and sperm. RIAs were developed using polyclonal antibodies raised in rabbits against each BSP protein. The purified and iodinated BSP proteins were used as standard and tracer, respectively. The RIAs that were developed were shown to be specific for each protein and the cross-reactivity toward various antigens was negligible (<2%). The average sensitivity limit was 5 ng/ml of sample for BSP-A1/-A2 and BSP-A3, and 40 ng/ml of sample for BSP-30-kDa. The concentration of BSP proteins was determined by analyzing the RIA data with spline function. BSP proteins represented 40% to 57% of seminal plasma total protein (25% to 47% of BSP-A1/-A2, 3% to 5% of BSP-A3, and 3% to 7% of BSP-30 kDa) and 4% to 6% of sperm total protein (2.5% to 4% of BSP-A1/-A2, 0.4% to 0.9% of BSP-A3, and 0.5% to 1% of BSP-30-kDa). We also determined the concentration of BSP proteins that were sperm-bound after semen cryopreservation in Tris-egg yolk-glycerol extender. A significant decrease (70%-80%) in sperm-bound BSP proteins was noted after cryopreservation. The availability of reliable RIA procedures should aid in the further understanding of the role of BSP proteins in sperm function as well as their effect on sperm cryopreservation.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".