Maternal immune activation elicits rapid and sex-dependent changes in gene expression and vascular dysfunction in the rat placenta
Bibliographic record
Abstract
INTRODUCTION: Maternal immune activation (MIA), characterized by increased circulating inflammatory mediators during pregnancy, is associated with adverse pregnancy outcomes and neurodevelopmental deficits in offspring. These health outcomes often manifest differently depending on fetal-placental sex. A well-established model of MIA involves administration of a viral mimetic, polyinosinic:polycytidilic acid (PolyI:C), to pregnant rodents. Placental responses to PolyI:C contribute to the detrimental effects of MIA on offspring, but these responses have not yet been well characterized. In the present study, we profiled acute gene expression changes in male and female placentas following PolyI:C administration to pregnant rats during late gestation. METHODS: Pregnant rats received 4 mg/kg PolyI:C or saline intravenously on gestational day 18.5, and tissues were harvested 4-5 h later. Gene expression profiling on placental tissue was performed. Enzyme immunoassays and immunohistochemistry were conducted to determine levels of select proteins in maternal blood and placental tissue, respectively. RESULTS: Maternal PolyI:C exposure caused a robust increase in levels of inflammatory mediators in maternal blood and placental tissue. There were more genes differentially expressed in female placentas after PolyI:C exposure (765) than male placentas (221), including reduced expression of genes associated with maternal-fetal communication. Placentas also had increased expression of genes linked with vascular dysfunction after PolyI:C-induced MIA. DISCUSSION: PolyI:C elicited a powerful inflammatory response in the placenta along with vascular dysfunction, likely contributing to the adverse pregnancy outcomes triggered by MIA. Female placentas responded to PolyI:C more vigorously than male placentas, which could underlie the differential outcomes of MIA depending on sex.
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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) | 0.001 | 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".