Matrix Metalloproteinase Expression in the Rat Myometrium During Pregnancy, Term Labor, and Postpartum
Bibliographic record
Abstract
Pregnancy, spontaneous term labor (TL), and postpartum (PP) involution are associated with changes in the cellular and extracellular matrix composition of the uterus. Both the uterine smooth muscle (myometrium) and the infiltrating peripheral blood leukocytes involved in the activation of labor secrete extracellular matrix-degrading enzymes (matrix metalloproteinases, MMPs) that can modulate cellular behavior and barrier function. MMP expression is induced by mechanical stretch in several tissues. We hypothesized that the expression and activity of myometrial MMPs and their tissue inhibitors (TIMPs) are modulated in preparation for TL and PP involution and are regulated by mechanical stretch of uterine walls imposed by the growing fetus. Myometrial tissues were collected from bilaterally and unilaterally pregnant rats across gestation, TL, and PP. Total RNA and proteins were subjected to real-time PCR and immunoblotting, respectively, and tissue localization and activity was examined by immunohistochemistry and in situ zymography. We found that Mmp7, Mmp11, and Mmp12 mRNA levels were upregulated during TL and PP, while Mmp2, Mmp3, Mmp8, Mmp9, Mmp10, and Mmp13 mRNAs were only upregulated during PP. Timp1-Timp4 were stably expressed throughout gestation with some fluctuations PP. Active MMP2 was induced in the empty uterine horn during gestation and in the gravid PP uterus, suggesting negative regulation by biological mechanical stretch. We conclude that specific subsets of uterine MMPs are differentially regulated in the rat myometrium in preparation for two major events: TL and PP uterine involution.
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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 | 0.000 | 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) | 0.001 | 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".