Connexins and steroidogenesis in mouse Leydig cells
Bibliographic record
Abstract
Connexin43 has been recognized as forming gap junctions in Leydig cells. However, previous work has shown that mouse Leydig cells lacking this connexin do not suffer any limitation of their ability to produce testosterone when stimulated with luteinizing hormone. The objective of this study was to identify additional connexins in mouse Leydig cells that could be required for steroidogenesis. A reverse transcription - polymerase chain reaction screen involving isolated adult Leydig cells identified connexin36 and connexin45 as expressed along with connexin43. Treatment of dissociated testes with carbenoxolone, a nonspecific blocker of gap junctional coupling, significantly reduced testosterone output as did treatment with quinine, which disrupts coupling provided by connexin36 and connexin45 gap junctions but not those composed of connexin43, indicating that either or both of connexins 36 and 45 could be involved in supporting Leydig cell steroidogenesis. Immunolabeling of adult mouse testis sections confirmed the localization of connexin36 along with connexin43 in Leydig cell gap junctions but not connexin45, which is distributed throughout the cells. It was concluded that connexin36, connexin43, and connexin45 are coexpressed in Leydig cells with connexins 36 and 43 contributing to gap junctions. The role of connexin45 remains to be elucidated.
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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".