The effects of maternal immune activation on early developmental milestones and behaviour in outbred CD-1 mice.
Bibliographic record
Abstract
Maternal immune activation (MIA) in mice can be used to investigate the link between perinatal infection and early-life developmental disorders such as cerebral palsy and autism spectrum disorder. Studies have shown that adult mice exposed to a bacterial or viral immune response during early- to mid-embryonic development display reduced social communication and interaction, and increased repetitive stereotypic behaviour. To date however, few studies have looked at the effects of MIA on early behaviours and developmental milestones in mice. In the current study, pregnant CD-1 dams were injected at embryonic day 11.5 with either lipopolysaccharide (LPS) or polyinosinic:polycytidylic acid (PolyIC) to stimulate aspects of a bacterial or viral immune response, respectively. Offspring were then assessed from post-natal day 2-21 using a modified Fox developmental behavioural test battery to assess reflexive and morphological developmental milestones. Additionally, grooming, homing to maternal bedding, and activity/exploration in the open field were evaluated. Overall, accelerated development and alterations in behaviour were observed in the MIA mice compared to sham-injected controls. These results suggest that MIA results in differential physiological and behavioural characteristics that emerge during early post-natal development, and further highlight the need for research that focuses on the effects of MIA during this developmental period.
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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 | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".