Ephrin-A5 Is Required for Optimal Fertility and a Complete Ovulatory Response to Gonadotropins in the Female Mouse
Bibliographic record
Abstract
Follicle growth and ovulation involve the coordinated expression of many genes, driven by FSH and LH. Reports indicate that Eph receptors and ephrins are expressed in the ovary, suggesting roles in follicle growth and/or ovulation. We previously reported FSH-induced expression of ephrin-A5 (EFNA5) and 4 of its cognate Eph receptors in mouse granulosa cells. We now report that female mice lacking EFNA5 are subfertile, exhibit a compromised response to LH, and display abnormal ovarian histology after superovulation. Efna5(-/-) females litters were 40% smaller than controls, although no difference in litter frequency was detected. The ovarian response to superovulation was also compromised in Efna5(-/-) females, with 37% fewer oocytes ovulated than controls. These results corresponded with a reduction in ovarian mRNA levels of several LH-responsive genes, including Pgr, Ptgs2, Tnfaip6, Ereg, Btc, and Adamts4, suggesting that Efna5(-/-) ovaries exhibit a partially attenuated response to LH. Histopathological analysis indicated that superovulated Efna5(-/-) females exhibited numerous ovarian defects, including intraovarian release of cumulus oocyte complexes, increased incidence of oocytes trapped within luteinized follicles, granulosa cell and follicular fluid emboli, fibrin thrombi, and interstitial hemorrhage. In addition, adult Efna5(-/-) ovaries exhibited a 4-fold increase in multioocyte follicles compared with controls, although no difference was detected in 3-week-old mice, suggesting the possibility of follicle merging. Our observations indicate that loss of EFNA5 in female mice results in subfertility and imply that Eph-ephrin signaling may also play a previously unidentified role in the regulation of fertility in women.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".