<i>Slit1</i> inhibits ovarian follicle development and female fertility in mice
Bibliographic record
Abstract
Previous in vitro studies have suggested that SLIT ligands could play roles in regulating ovarian granulosa cell proliferation and gene expression, as well as luteolysis. However, no in vivo study of Slit gene function has been conducted to date. Here, we investigated the potential role of Slit1 in ovarian biology using a Slit1-null mouse model. Female Slit1-null mice were found to produce larger litters than their wild-type counterparts due to increased ovulation rates. Increased ovarian weights in Slit1-null animals were found to be due to the presence of greater numbers of healthy antral follicles with similar numbers of atretic ones, suggesting both an increased rate of follicle recruitment and a decreased rate of atresia. Consistent with this, treatment of cultured granulosa cells with exogenous SLIT1 induced apoptosis in presence or absence of follicle-stimulating hormone, but had no effect on cell proliferation. Although few alterations in the messenger RNA levels of follicle-stimulating hormone-responsive genes were noted in granulosa cells of Slit1-null mice, luteinizing hormone target gene mRNA levels were greatly increased. Finally, increased phospho-AKT levels were found in granulosa cells isolated from Slit1-null mice, and SLIT1 pretreatment of cultured granulosa cells inhibited the ability of both follicle-stimulating hormone and luteinizing hormone to increase AKT phosphorylation, suggesting a mechanism whereby SLIT1 could antagonize gonadotropin signaling. These findings therefore represent the first evidence for a physiological role of a SLIT ligand in the ovary, and define Slit1 as a novel autocrine/paracrine regulator of follicle development.
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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 | 0.001 | 0.001 |
| 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".