Seminal Plasma Proteins as Potential Markers of Relative Fertility in Boars
Bibliographic record
Abstract
This study investigated whether specific proteins from distinct seminal plasma fractions of boars could be related to in vivo fertility. Nine boars with acceptable sperm motility and morphology for use in artificial insemination demonstrated major differences in total number born and pregnancy rate when low sperm doses (1.5 billion sperm) were used to breed a minimum of 50 gilts per boar. The 2 lowest-fertility and 2 highest-fertility boars were chosen for evaluation of specific seminal plasma proteins. On 4 occasions, semen was collected and separated into 3 fractions based on sperm concentration (Sperm-Peak, Sperm-Rich, and Sperm-Free), and the fractions were analyzed for total protein concentration and abundance of major seminal plasma glycoprotein (PSP-I), AWN-1, and osteopontin protein using Western blotting techniques. The concentrations of these seminal plasma proteins were lower in the Sperm-Peak fractions compared with the Sperm-Free fractions (P < .05). Seminal plasma from the pooled Sperm-Rich fraction used for artificial insemination was also subjected to two-dimensional gel electrophoresis to investigate novel protein markers related to in vivo fertility. Total piglets born (r = -0.76, P = .01) and sperm motility at day 7 (r = -0.74, P = .037) were again negatively correlated with a 22-kDa protein identified by mass spectrometry as PSP-I. However, fertility index and farrowing rate tended to be positively correlated (P < .10) with a 25-kDa protein, identified as glutathione peroxidase (GPX5), an antioxidant enzyme that may protect sperm membranes from oxidative damage. These candidate proteins merit further investigation as markers of fertility in boars.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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) | 0.000 | 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".