Kit Ligand 2 Promotes Murine Oocyte Growth In Vitro1
Bibliographic record
Abstract
Oocyte-granulosa cell communication, mediated by paracrine factors, is essential for oocyte development. Kit ligand (KITL) is expressed in granulosa cells as soluble (KITL1) or membrane-associated (KITL2) proteins. However, the relative biopotency of each isoform during oocyte development is unknown. Our initial results showed that Kitl2 was down-regulated in cultured granulosa cells. To determine the effect of the two isoforms of KITL on oocyte growth, Kitl-deficient fibroblasts were transfected with constructs expressing either KITL1 or KITL2, and growing oocytes were isolated from 12-day-old mice and cultured on the transfected fibroblasts for 2 days. At the end of culture, oocyte diameters were measured, the incidence of spontaneous germinal vesicle breakdown (GVBD) was noted, and oocytes were analyzed for KIT receptor expression. Oocyte growth occurred only in the presence of the KITL2-producing fibroblasts, and suppression of KITL2 expression impaired oocyte growth. Up-regulation of KIT expression occurred in the presence of KITL2 but not KITL1. The presence of KITL2 inhibited spontaneous GVBD. Meiosis inhibitors did not attenuate the GVBD that occurred in the absence of KITL2, suggesting that this process reflects oocyte degeneration rather than meiotic progression. These results indicate that KITL2 is the principal KITL isoform required for oocyte growth and survival in vitro.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".