Myometrial immune cells contribute to term parturition, preterm labour and post‐partum involution in mice
Bibliographic record
Abstract
This study aimed to determine the mechanism of uterine activation during labour, both term (TL) and preterm (PTL). We hypothesized that the peripheral leucocytes are recruited to uterine tissues by locally produced cytokines where they contribute to the initiation of parturition. Mouse uteri were collected (i) during gestation, TL and post-partum (PP), (ii) during PTL initiated by intrauterine infusion of LPS (125 μg) or (iii) injection of the progesterone receptor antagonist RU486 and analysed for multiple cytokine expression levels by real-time polymerase chain reaction (RT-PCR) and 23-plex Cytokine assay or enzymatically dispersed for assessment of immune cell populations. Markers of myeloid cell differentiation (Gr1, Neu7/4 and F4/80) were evaluated by FACS to define tissue macrophages (Macs), monocytes (M) and neutrophils (N) and by immunohistochemistry to detect tissue Macs and N. Our results indicate that: (1) Macs were elevated in mouse myometrium before TL (P < 0.05) followed by an increase in M and N; these changes were accompanied by an increase in multiple pro-inflammatory cytokines/chemokines genes. The expression of corresponding proteins increased PP. (2) TL and RU486-PTL models showed similar gene/protein expression profiles, (3) LPS-PTL was characterized by strong pro-inflammatory response and massive influx of N in myometrial tissues showing a pattern different from TL and RU486-PTL, (4) The PP period appears similar in all three models, with elevated myometrial cytokine levels and high infiltration of immune cells. We concluded that leucocytes infiltrate myometrium around the time of parturition implicating their potential role in labour activation (both term and preterm) and major role in 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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".