Interleukin 15 modulates the effects of poly I:C maternal immune activation on offspring behaviour
Why this work is in the frame
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Bibliographic record
Abstract
Maternal infections during pregnancy are linked with an increased risk for disorders like Autism Spectrum Disorder and schizophrenia in the offspring. Although precise mechanisms are still unclear, clinical and preclinical evidence suggest a strong role for maternal immune activation (MIA) in the neurodevelopmental disruptions caused by maternal infection. Previously, studies using the Polyinosinic:Polycytidylic (Poly I:C) MIA preclinical model showed that cytokines like Interleukin 6 (Il6) are important mediators of MIA's effects. In this study, we hypothesized that Il15 may similarly act as a mediator of Poly I:C MIA, given its role in the antiviral immune response. To test this hypothesis, we induced Poly I:C MIA at gestational day 9.5 in wildtype (WT) and Il15−/− rat dams and tested their offspring in adolescence and adulthood. Poly I:C MIA and Il15 knockout produced both independent and synergistic effects on offspring behaviour. Poly I:C MIA decreased startle reactivity in adult WT offspring but resulted in increased adolescent anxiety and decreased adult locomotor activity in Il15−/− offspring. In addition, Poly I:C MIA led to genotype-independent effects on locomotor activity and prepulse inhibition. Finally, we showed that Il15−/− offspring exhibit distinct phenotypes that were unrelated to Poly I:C MIA including altered startle reactivity, locomotion and signal transduction in the auditory brainstem. Overall, our findings indicate that the lack of Il15 can leave offspring either more or less susceptible to Poly I:C MIA, depending on the phenotype in question. Future studies should examine the contribution of fetal versus maternal Il15 in MIA to determine the precise developmental mechanisms underlying these changes.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it