Comparative proteome and lipid profiles of bovine epididymosomes collected in the intraluminal compartment of the caput and cauda epididymidis
Bibliographic record
Abstract
During the epididymal maturation, spermatozoa interact with different populations of epididymosomes and sequentially acquire some epididymosome-associated proteins critical to sperm functions. Although very few proteins associated with epididymosomes have been identified, the physiological importance of these vesicles in the sperm maturation remains unclear. To document these relevant issues, lipid and protein analysis of epididymosomes from caput and cauda epididymal fluids was determined. Lipid analysis revealed a particular composition of specific phospholipids in these vesicles; the levels of phosphatidyl-ethanolamine, phosphatidyl-inositol and phosphatidyl-choline being higher in caput epididymosomes. From the 555 and 438 proteins identified in caput- and cauda-derived epididymosomes, respectively, 231 proteins were identified in both types of epididymosome. Proteins exclusively identified in caput and cauda epididymosomes are mainly enzymes and transporter molecules. The presence of several glycan-modifying enzymes is the hallmark of the caput epididymosomes proteome. Among the common proteins in both types of epididymosome, a subset of Rab and SNARE proteins implicated in vesicle trafficking and membrane fusion were identified. Together, these data suggest that epididymosome-associated proteins are involved in various molecular functions suggesting that during the epididymal transit, spermatozoa interact with different populations of epididymosomes, which could modify the male gamete in a sequential manner.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".