Histomorphometric analysis of the endometrium in an ectopic model of endometriosis in mice
Bibliographic record
Abstract
Objective: Evaluate histomorphometry of ectopic and eutopic endometrial tissues in receptor mice. Method: Eighteen female Balb/c were divided into 3 groups, 6 animals each: GI Control, no procedure; GII – Sham, animals that had the same procedures as GIII without receiving the ectopic endometrial implant. Instead, they received saline solution; GIII – endometriosis model, animals had surgical intervention with an ectopic endometrial implant. GI and GIII mice were treated with 17β-estradiol, 100 µg/kg each. All animals were euthanized to collect uterine horns, which were fixed in 4% paraformaldehyde, embedded in paraffin, stained with Hematoxilin and Eosin and submitted to histomorphometric analyzes. Data underwent one-way ANOVA followed by Tukey’s test. Results: Local tissue growth, showing important lesions and adhesions, as well as dark cysts were noticed. In GIII group, there was an increase in number of blood vessels and glands (GIII ≥ GI and GIII p > .001). Thickening of the GIII endometrial epithelial was also evident (GIII ≥ GI and GIII. p > .001). We also noticed an increase in the number of eosinophils (GIII (GIII ≥ GI and GIII. p > .001). Conclusion: Easy to perform model, capable of reproducing morphological endometriosis characteristics. From our findings, there was an increase of endometrial thickness as well as an increase in the eosinophils population.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".