PolyI:C Maternal Immune Activation on E9.5 Causes the Deregulation of Microglia and the Complement System in Mice, Leading to Decreased Synaptic Spine Density
Bibliographic record
Abstract
Maternal immune activation (MIA) is a risk factor for multiple neurodevelopmental disorders; however, animal models developed to explore MIA mechanisms are sensitive to experimental factors, which has led to complexity in previous reports of the MIA phenotype. We sought to characterize an MIA protocol throughout development to understand how prenatal immune insult alters the trajectory of important neurodevelopmental processes, including the microglial regulation of synaptic spines and complement signaling. We used polyinosinic:polycytidylic acid (polyI:C) to induce MIA on gestational day 9.5 in CD-1 mice, and measured their synaptic spine density, microglial synaptic pruning, and complement protein expression. We found reduced dendritic spine density in the somatosensory cortex starting at 3-weeks-of-age with requisite increases in microglial synaptic pruning and phagocytosis, suggesting spine density loss was caused by increased microglial synaptic pruning. Additionally, we showed dysregulation in complement protein expression persisting into adulthood. Our findings highlight disruptions in the prenatal environment leading to alterations in multiple dynamic processes through to postnatal development. This could potentially suggest developmental time points during which synaptic processes could be measured as risk factors or targeted with therapeutics for neurodevelopmental disorders.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".