Composition and significance of detergent resistant membranes in mouse spermatozoa
Bibliographic record
Abstract
Mammalian spermatozoa acquire the ability to fertilize an oocyte as they ascend the female reproductive tract. This process is characterized by a complex cascade of biophysical and biochemical changes collectively know as "capacitation." The attainment of a capacitated state is accompanied by a dramatic reorganization of the surface architecture to render spermatozoa competent to recognize the oocyte and initiate fertilization. Emerging evidence indicates that this process is facilitated by molecular chaperone-mediated assembly of a multimeric receptor complex on the sperm surface. However, the mechanisms responsible for gathering key recognition molecules within this putative complex have yet to be defined. In this study, we provide the first evidence that chaperones partition into detergent resistant membrane fractions (DRMs) within capacitated mouse spermatozoa and co-localize in membrane microdomains enriched with the lipid raft marker, G(M1) ganglioside. During capacitation, these microdomains coalesce within the apical region of the sperm head, a location compatible with a role in sperm-zona pellucida interaction. Significantly, DRMs isolated from spermatozoa possessed the ability to selectively bind to the zona pellucida of unfertilized, but not fertilized, mouse oocytes. A comprehensive proteomic analysis of the DRM fractions identified a total of 100 proteins, a number of which have previously been implicated in sperm-oocyte interaction. Collectively, these data provide compelling evidence that mouse spermatozoa possess membrane microdomains that provide a platform for the assembly of key recognition molecules on the sperm surface and thus present an important mechanistic insight into the fundamental cell biological process of sperm-oocyte interaction.
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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 | 0.000 |
| 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".