Implantation Failure in Female Kiss1−/− Mice Is Independent of Their Hypogonadic State and Can Be Partially Rescued by Leukemia Inhibitory Factor
Bibliographic record
Abstract
The hypothalamic kisspeptin signaling system is a major positive regulator of the reproductive neuroendocrine axis, and loss of Kiss1 in the mouse results in infertility, a condition generally attributed to its hypogonadotropic hypogonadism. We demonstrate that in Kiss1(-/-) female mice, acute replacement of gonadotropins and estradiol restores ovulation, mating, and fertilization; however, these mice are still unable to achieve pregnancy because embryos fail to implant. Progesterone treatment did not overcome this defect. Kiss1(+/-) embryos transferred to a wild-type female mouse can successfully implant, demonstrating the defect is due to maternal factors. Kisspeptin and its receptor are expressed in the mouse uterus, and we suggest that it is the absence of uterine kisspeptin signaling that underlies the implantation failure. This absence, however, does not prevent the closure of the uterine implantation chamber, proper alignment of the embryo, and the ability of the uterus to undergo decidualization. Instead, the loss of Kiss1 expression specifically disrupts embryo attachment to the uterus. We observed that on the day of implantation, leukemia inhibitory factor (Lif), a cytokine that is absolutely required for implantation in mice, is weakly expressed in Kiss1(-/-) uterine glands and that the administration of exogenous Lif to hormone-primed Kiss1(-/-) female mice is sufficient to partially rescue implantation. Taken together, our study reveals that uterine kisspeptin signaling regulates glandular Lif levels, thereby identifying a novel and critical role for kisspeptin in regulating embryo implantation in the mouse. This study provides compelling reasons to explore this role in other species, particularly livestock and humans.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".