A simple method for inducing estrous cycle stage-specific morphological changes in the vaginal epithelium of immature female mice
Bibliographic record
Abstract
The vaginal epithelium of the adult female laboratory rodent changes from mucous secretion to cornification over the course of the estrous cycle. The morphophysiological changes occur with such regularity, accuracy and precision that the specific stage of the estrous cycle in the rat can be determined by inspection of the vaginal opening and/or exfoliative vaginal cytology. However, in the mouse, post-mortem vaginal histology is often required to determine the estrous cycle stage for ensuring the required level of reliability. Consequently, an excess number of female adult mice are needed to allow for the delivery of sufficient numbers of mice in a desired estrous cycle stage. In this study, we demonstrate that the standard procedure for oocyte superovulation and collection in the laboratory mouse (e.g. injection of equine chorionic gonadotropin followed 48 h later by human chorionic gonadotropin) can also be reliably used to induce changes in the epithelium of 3.5-week-old mouse vaginas in an estrous cycle stage-specific manner (e.g. establishment and replacement of a mucous secreting epithelium with a cornified epithelium; induction of cornification-associated loricrin expression). The superovulation protocol thus allows for the efficient and economic induction of estrous cycle stage-specific characteristics in the Müllerian duct-derived vagina thereby avoiding the necessity of post-mortem identification of the estrous cycle stage. In addition, our study indicates that the laboratory mouse vagina is an excellent organ for studying the sequence of events leading to cornification.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".