Combination of histochemical analyses and micro-MRI reveals regional changes of the murine cervix in preparation for labor
Bibliographic record
Abstract
Abstract The cervix is responsible for maintaining pregnancy, and its timely remodeling is essential for the proper delivery of a baby. Cervical insufficiency, or “weakness”, may lead to preterm birth, which causes infant morbidities and mortalities worldwide. We used a mouse model of pregnancy and term labor, to examine the cervical structure by histology (Masson Trichome and Picrosirius Red staining), immunohistochemistry (Hyaluronic Acid Binding Protein/HABP), and ex-vivo MRI (T2-weighted and diffusion tensor imaging), focusing on two regions of the cervix (i.e., endocervix and ectocervix). Our results show that mouse endocervix has a higher proportion of smooth muscle cells and collagen fibers per area, with more compact tissue structure, than the ectocervix. With advanced gestation, endocervical changes, indicative of impending delivery, are manifested in fewer smooth muscle cells, expansion of the extracellular space, and lower presence of collagen fibers. MRI detected three distinctive zones in pregnant mouse endocervix: (1) inner collagenous layer, (2) middle circular muscular layer, and (3) outer longitudinal muscular layer. Diffusion MRI images detected changes in tissue organization as gestation progressed suggesting the potential application of this technique to non-invasively monitor cervical changes that precede the onset of labor in women at risk for preterm delivery.
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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 | 0.001 |
| 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".