Progesterone and Gravidity Differentially Regulate Expression of Extracellular Matrix Components in the Pregnant Rat Myometrium1
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Bibliographic record
Abstract
Myometrial growth and remodeling during pregnancy depends on increased synthesis of interstitial matrix proteins. We hypothesize that the presence of mechanical tension in a specific hormonal environment regulates the expression of extracellular matrix (ECM) components in the uterus. Myometrial tissue was collected from pregnant rats on Gestational Days 0, 12, 15, 17, 19, 21, 22, 23 (labor), and 1 day postpartum and ECM expression was analyzed by Northern blotting. Expression of fibronectin, laminin beta2, and collagen IV mRNA was low during early gestation but increased dramatically on Day 23 during labor. Expression of fibrillar collagens (type I and III) peaked Day 19 and decreased near term. In contrast, elastin mRNA remained elevated from midgestation onward. Injection of progesterone (P4) on Days 20-23 (to maintain elevated plasma P4 levels) delayed the onset of labor, caused dramatic reductions in the levels of fibronectin and laminin mRNA, and prevented the fall of collagen III mRNA levels on Day 23. Treatment of pregnant rats with the progesterone receptor antagonist RU486 on Day 19 induced preterm labor on Day 20 and a premature increase in mRNA levels of collagen IV, fibronectin, and laminin. Analysis of the uterine tissue from unilaterally pregnant rats revealed that most of the changes in ECM gene expression occurred specifically in the gravid horn. Our results show a decrease in expression of fibrillar collagens and a coordinated temporal increase in expression of components of the basement membrane near term associated with decreased P4 and increased mechanical tension. These ECM changes contribute to myometrial growth and remodeling during late pregnancy and the preparation for the synchronized contractions of labor.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 it