IL-1 Blockade Mitigates Autism and Cerebral Palsy Traits in Offspring In-Utero Exposed to Group B Streptococcus Chorioamnionitis
Bibliographic record
Abstract
(GBS) is one of the most common bacteria responsible for placental and neonatal infection and inflammation resulting in lifelong neurobehavioral impairments. In particular, GBS-induced chorioamnionitis is known in preclinical models to upregulate inflammatory pathways, primarily through the activation of the interleukin-1 (IL-1) pathway, leading to brain injury and subsequent neurodevelopmental issues. Previous studies from our laboratory using Lewis rat pups have shown that male offspring exposed in utero to GBS chorioamnionitis develop brain injuries leading to neurobehavioral impairments such as autistic traits. In the present study, we aimed to explore whether blocking the IL-1 pathway could prevent or mitigate these neurodevelopmental impairments in adulthood. Using our established preclinical model, we administered IL-1 receptor antagonist (IL-1Ra) to dams with GBS-induced chorioamnionitis. Here, we show that IL-1Ra administration to dams reversed autistic and cerebral palsy traits in male adult offspring exposed in utero to GBS. Hence, IL-1 blockade could serve as a therapeutic intervention against pathogen-induced neurodevelopmental disorders. This research supports the need for future human randomized controlled trials to assess IL-1 blockade administered during pregnancy or in newborns as a strategy to reduce the long-term neurobehavioral consequences of prenatal infections, such as autism, cerebral palsy, learning disabilities, and other 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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".