Prenatal administration of IL-1Ra attenuate the neurodevelopmental impacts following non-pathogenic inflammation during pregnancy
Bibliographic record
Abstract
Prenatal inflammation negatively affects placental function, subsequently altering fetal development. Pathogen-associated molecular patterns (PAMPs) are used to mimics infections in preclinical models but rarely detected during pregnancy. Our group previously developed an animal model of prenatal exposure to uric acid (endogenous mediator), leading to growth restriction alongside IL-1-driven placental inflammation (Brien et al. in J Immunol 198(1):443-451, 2017). Unlike PAMPs, the postnatal impact of prenatal non-pathogenic inflammation is still poorly understood. Therefore, we investigated the effects of prenatal uric acid exposure on postnatal neurodevelopment and the therapeutic potential of the IL-1 receptor antagonist; IL-1Ra. Uric acid induced growth restriction and placental inflammation, which IL-1Ra protected against. Postnatal evaluation of both structural and functional aspects of the brain revealed developmental changes. Both astrogliosis and microgliosis were observed in the hippocampus and white matter at postnatal day (PND)7 with IL-1Ra being protective. Decreased myelin density was observed at PND21, and reduced amount of neuronal precursor cells was observed in the Dentate Gyrus at PND35. Functionally, motor impairments were observed as evaluated with the increased time to fully turn upward (180 degrees) on the inclined plane and the pups were weaker on the grip strength test. Prenatal exposure to sterile inflammation, mimicking most clinical situation, induced growth restriction with negative impact on neurodevelopment. Targeted anti-inflammatory intervention prenatally could offer a strategy to protect brain development during pregnancy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".