Inhibin Inactivation in Female Mice Leads to Elevated FSH Levels, Ovarian Overstimulation, and Pregnancy Loss
Bibliographic record
Abstract
Inhibins are members of the transforming growth factor-β family, composed of a common α-subunit disulfide-linked to 1 of 2 β-subunits (βA in inhibin A or βB in inhibin B). Gonadal-derived inhibin A and B act in an endocrine manner to suppress the synthesis of follicle-stimulating hormone (FSH) by pituitary gonadotrope cells. Roles for inhibins beyond the pituitary, however, have proven difficult to delineate because deletion of the inhibin α-subunit gene (Inha) results in unconstrained expression of activin A and activin B (homodimers of inhibin β-subunits), which contribute to gonadal tumorigenesis and lethal cachectic wasting. Here, we generated mice with a single point mutation (Arg233Ala) in Inha that prevents proteolytic processing and the formation of bioactive inhibin. In vitro, this mutation blocked inhibin maturation and bioactivity, without perturbing activin production. Serum FSH levels were elevated 2- to 3-fold in InhaR233A/R233A mice due to the loss of negative feedback from inhibins, but no pathological increase in circulating activins was observed. While inactivation of inhibin A and B had no discernible effect on male reproduction, female InhaR233A/R233A mice had increased FSH-dependent follicle development and enhanced natural ovulation rates. Nevertheless, inhibin inactivation resulted in significant embryo-fetal resorptions and severe subfertility and was associated with disrupted maternal ovarian function. Intriguingly, heterozygous Inha+/R233A females had significantly enhanced fecundity, relative to wild-type littermates. These studies have revealed novel effects of inhibins in the establishment and maintenance of pregnancy and demonstrated that partial inactivation of inhibin A/B is an attractive approach for enhancing female fertility.
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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) | 0.002 | 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 | 0.000 |
| 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".