Circulating hormones and estrous stage predict cellular and stromal remodeling in murine uterus
Bibliographic record
Abstract
The understanding of how estrogen and progesterone (P(4)) drive uterine remodeling in rodents has largely been based on studies involving administration of exogenous hormones, using steroid receptor-deficient mice, or relying on vaginal smears. In all these cases, the actual serum levels of 17beta-estradiol (E(2)) and P(4) are not directly measured, and the relationship between physiological levels of female sex hormones and uterine remodeling in cycling mice has not been fully explored. Here, we measured the circulating levels of E(2) and P(4) in cycling mice and performed correlation analysis between hormone levels and epithelial and stromal uterine parameters, irrespective of the estrous stage. In parallel, these parameters were analyzed in relation to the more conventional method of vaginal smear classification of estrous stage. We found that circulating P(4) inversely correlated with uterine width, luminal epithelial proliferation, stromal apoptosis, and degradation of luminal epithelial basement membrane collagen type-IV. Circulating E(2) positively correlated with uterine width, stromal cell proliferation, and collagen type-I content, while it negatively correlated with glandular epithelial proliferation, loss of collagen type-IV surrounding glandular epithelium, and apoptosis in luminal, glandular, and stromal compartments. Our findings indicate that measuring P(4) or E(2) levels can predict many concurrent cellular and stromal events in the mouse uterus, suggesting that in naturally cycling mice cellular responses to hormone changes are not delayed, but occur very rapidly.
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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 | 0.001 | 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".