Functional analysis of gap junctions in ovarian granulosa cells: distinct role for connexin43 in early stages of folliculogenesis
Bibliographic record
Abstract
Ovarian granulosa cells are coupled via gap junctions containing connexin43 (Cx43 or alpha-1 connexin). In the absence of Cx43, granulosa cells stop growing in an early preantral stage. However, the fact that granulosa cells of mature follicles express multiple connexins complicated interpretation of this finding. The present experiments were designed to clarify the role of Cx43 vs. these other connexins in the earliest stages of folliculogenesis. Dye injection experiments revealed that granulosa cells from Cx43 knockout follicles are not coupled, and this was confirmed by ionic current injections. Furthermore, electron microscopy revealed that gap junctions are extremely rare in mutant granulosa cells. In contrast, mutant granulosa cells were able to form gap junctions with wild-type granulosa cells in a dye preloading assay. It was concluded that mutant granulosa cells contain a population of connexons, composed of an unidentified connexin, that do not normally contribute to gap junctions. Therefore, although Cx43 is not the only gap junction protein present in granulosa cells of early preantral follicles, it is the only one that makes a significant contribution to intercellular coupling.
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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 | 0.000 | 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".