Evidence that a kinesin is associated with ectoplasmic specializations in the testis
Bibliographic record
Abstract
During spermatogenesis, spermatids undergo a “down and up” translocation event in the seminiferous epithelium. This event has been proposed to be microtubule‐based and to result from the movement of apical “ectoplasmic specializations” (adhesion junctions) along adjacent Sertoli cell microtubule tracts. Dynein is present at the junctions and is likely responsible for the upward movement of spermatids. A kinesin is likely responsible for the downward movement of spermatids. To test the hypothesis that a kinesin is associated with the junctions, we generated an antibody to the “LAGSE” sequence conserved amongst kinesins, and reacted the antibody with fixed frozen sections of epithelium or fixed epithelial fragments. In tissue processed for immunofluorescensce, the antibody reacted at sites known to contain apical ectoplasmic specializations, in addition to reacting with other structures in the epithelium known to contain kinesins. In material processed for immunogold localization, the antibody reacted with the cytoplasmic face of the endoplasmic reticulum component of ectoplasmic specializations. Kinesin mRNA transcript screens using mouse GeneChip arrays of testis and Sertoli cells indicated that a possible candidate kinesin for spermatid translocation is Rab6KIFL. Antibodies generated against a peptide sequence that is unique to this kinesin reacted with regions associated with spermatid heads, and with a band on immunoblots that is not present in other tissues and migrates at a higher molecular weight than that known for Rab6KIFL. We are currently identifying the protein. Our results are consistent with the prediction that a kinesin is associated with ectoplasmic specializations. CIHR MOP 62768
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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) | 0.003 | 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".