Differential Regulation of Human and Mouse Myometrial Contractile Activity by FSH as a Function of FSH Receptor Density
Bibliographic record
Abstract
Previous studies from our laboratory revealed that the follicle-stimulating hormone receptor (FSHR) is expressed at low levels in nonpregnant human myometrium and that it is up-regulated in pregnant term nonlaboring myometrium; however, the physiological relevance of these findings was unknown. Herein, we examined signaling pathways stimulated by FSH in immortalized uterine myocytes expressing recombinant FSHR at different densities and showed that cAMP accumulation is stimulated in all cases but that inositol phosphate accumulation is stimulated only at high FSHR densities. Because an increase in cAMP quiets myometrial contractile activity but an increase in 1,4,5-triphosphoinositol stimulates contractile activity, we hypothesized that FSHR density dictates whether FSH quiets or stimulates myometrial contractility. Indeed, in human and mouse nonpregnant myometrium, which express low levels of FSHR, application of FSH resulted in a quieting of contractile activity. In contrast, in pregnant term nonlaboring myometrium, which expresses higher levels of FSHR, application of FSH resulted in increased contractile activity. Examination of pregnant mouse myometrium from different stages of gestation revealed that FSHR levels remained low throughout most of pregnancy. Accordingly, through mid-gestation, the application of FSH resulted in a quieting of contractile activity. At Pregnancy Day (PD) 16.5, FSHR was up-regulated, although not yet sufficiently to mediate stimulation of contractility in response to FSH. This outcome was not observed until PD 19.5, when FSHR was further up-regulated. Our studies describe a novel FSHR signaling pathway that regulates myometrial contractility, and suggest that myometrial FSHR levels dictate the quieting vs. stimulation of uterine contractility in response to FSH.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".