Infiltration of myeloid cells into decidua is a critical early event in the labour cascade and post‐partum uterine remodelling
Bibliographic record
Abstract
Leucocyte infiltration in the decidua (maternal-foetal interface) before, during and after term (TL) and preterm labour (PTL) was studied in mouse. We also investigated the mechanism of peripheral leucocyte recruitment into decidua by analysing the tissue cytokine profiles. Decidual tissues were collected during late gestation, TL and post-partum (PP). PTL was initiated on gestational day 15 by intrauterine injection of Lipopolysaccharide (LPS, 125 μg) or progesterone signalling antagonism by RU486. Animals were killed during PTL or PP. Decidua basalis was analysed using FACS and immunohistochemistry. Markers of myeloid cell differentiation (Gr1, Ly6G, Neu7/4, F4/80) were assessed to define tissue monocytes (M), neutrophils (N) and macrophages (Macs). Flow cytometry revealed a significant (P < 0.05) increase in decidual Macs prior to TL; M and N numbers increased during TL and further increased during PP, which correlated with immunohistochemistry data. Massive influx of N, but not Macs and M, was detected by FACS during LPS-PTL (P < 0.05) but not RU486-PTL. Highest levels of N infiltration into the decidua occurred PP in both LPS and RU486 groups. Decidual infiltration during TL and RU486-PTL was accompanied by an increase in pro-inflammatory cytokines (IL1b and IL6) and CCL2 chemokine; LPS-PTL showed increases in multiple cytokines. PP period following TL and PTL was associated with further up-regulation of multiple cytokines/chemokines (P < 0.05). Our data suggest a programme of myeloid cells involvement in parturition with the pre-partum influx of Macs into the decidua contributing to the progression of labour, whereas the later influx of M and N contribute to PP decidual 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".