Macrophages Infiltrate the Human and Rat Decidua During Term and Preterm Labor: Evidence That Decidual Inflammation Precedes Labor1
Bibliographic record
Abstract
Preterm delivery is the leading cause of perinatal mortality and morbidity. Current tocolytics target myometrial contractions, a late step in the labor cascade. Identifying earlier events in parturition may lead to more effective therapeutic strategies. We hypothesized that inflammatory events in decidua (the maternal-fetal interface), characterized by leucocyte infiltration, are an early event during term and preterm labor (PTL). Leucocyte abundance in decidua of human pregnancies was quantified following term labor and PTL (idiopathic and infection associated), in conjunction with investigation of temporal inflammatory events in rat uterus during the perilabor period and in PTL induced by mifepristone. In human decidua, macrophage numbers were 4-fold higher in term labor (P < 0.01) and 2.5-fold higher in non-infection-associated PTL (P < 0.05) than in term nonlaboring samples. Neutrophil abundance was unchanged with labor but elevated in PTL with infection (5- to 53-fold increase; P < 0.01). T and NK cells were more abundant in idiopathic PTL than TL (P < 0.05). In rat, decidual macrophage infiltration increased 4.5-fold 12 h prior to labor and remained elevated during labor and early postpartum (P < 0.01). Decidual infiltration preceded that of the myometrium and was 4-fold higher (P < 0.01). In rat PTL, decidual macrophage numbers were also elevated (P < 0.01) and exceeded those of the myometrium (P < 0.05). These studies show for the first time that leucocytes infiltrate decidua during labor at term and preterm, supporting a role for leucocyte-derived inflammatory mediators in decidual activation. In the rat, this occurred prior to labor, suggesting it is an early event during parturition and thus a potential target for intervention.
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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 | 0.000 |
| 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".