Evidence for Involvement of GIP and GLP-1 Receptors and the Gut-Gonadal Axis in Regulating Female Reproductive Function in Mice
Bibliographic record
Abstract
Substantial evidence suggests crosstalk between reproductive and gut-axis but mechanisms linking metabolism and reproduction are still unclear. The present study evaluated the possible role of glucose-dependent-insulinotropic-polypeptide (GIP) and glucagon-like-peptide-1 (GLP-1) in reproductive function by examining receptor distribution and the effects of global GIPR and GLP-1R deletion on estrous cycling and reproductive outcomes in mice. GIPR and GLP-1R gene expression were readily detected by PCR in female reproductive tissues including pituitary, ovaries and uterine horn. Protein expression was confirmed with histological visualisation of incretin receptors using GIPR-Cre and GLP1R-Cre mice in which the incretin receptor expressing cells were fluorescently tagged. Functional studies revealed that female GIPR−/− and GLP-1R−/− null mice exhibited significantly (p < 0.05 and p < 0.01) deranged estrous cycling compared to wild-type controls, indicative of reduced fertility. Furthermore, only 50% and 16% of female GIPR−/− and GLP-1R−/− mice, respectively produced litters with wild-type males across three breeding cycles. Consistent with a physiological role of incretin receptors in pregnancy outcome, litter size was significantly (p < 0.001–p < 0.05) decreased in GIPR−/− and GLP-1R−/− mice. Treatment with oral metformin (300 mg/kg body-weight), an agent used clinically for treatment of PCOS, for a further two breeding periods showed no amelioration of pregnancy outcome except that litter size in the GIPR−/− group was approximately 2 times greater in the second breeding cycle. These data highlight the significance of incretin receptors in modulation of female reproductive function which may provide future targets for pharmacological intervention in reproductive disorders.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".