Uterine kisspeptin receptor critically regulates epithelial estrogen receptor α transcriptional activity at the time of embryo implantation in a mouse model
Bibliographic record
Abstract
Embryo implantation failure is a major cause of infertility in women of reproductive age and a better understanding of uterine factors that regulate implantation is required for developing effective treatments for female infertility. This study investigated the role of the uterine kisspeptin receptor (KISS1R) in the molecular regulation of implantation in a mouse model. To conduct this study, a conditional uterine knockout (KO) of Kiss1r was created using the Pgr-Cre (progesterone receptor-CRE recombinase) driver. Reproductive profiling revealed that while KO females exhibited normal ovarian function and mated successfully to stud males, they exhibited significantly fewer implantation sites, reduced litter size and increased neonatal mortality demonstrating that uterine KISS1R is required for embryo implantation and a healthy pregnancy. Strikingly, in the uterus of Kiss1r KO mice on day 4 (D4) of pregnancy, the day of embryo implantation, KO females exhibited aberrantly elevated epithelial ERα (estrogen receptor α) transcriptional activity. This led to the temporal misexpression of several epithelial genes [Cftr (Cystic fibrosis transmembrane conductance regulator), Aqp5 (aquaporin 5), Aqp8 (aquaporin 8) and Cldn7 (claudin 7)] that mediate luminal fluid secretion and luminal opening. As a result, on D4 of pregnancy, the lumen remained open disrupting the final acquisition of endometrial receptivity and likely accounting for the reduction in implantation events. Our data clearly show that uterine KISS1R negatively regulates ERα signaling at the time of implantation, in part by inhibiting ERα overexpression and preventing detrimentally high ERα activity. To date, there are no reports on the regulation of ERα by KISS1R; therefore, this study has uncovered an important and powerful regulator of uterine ERα during early pregnancy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".