471. MATERNAL IMMUNE ACTIVATION LEADS TO SCHIZOPHRENIA-RELATED BEHAVIOURAL AND NEUROPHYSIOLOGICAL DEFICITS IN MOTHERS AND JUVENILE OFFSPRING
Bibliographic record
Abstract
Abstract Background Effectively treating schizophrenia remains a significant challenge, particularly in addressing the full spectrum of symptoms following the initial onset. Current interventions often focus on individuals at high risk of developing the disorder, leading researchers to employ animal models to test potential treatments and identify relevant biomarkers. Evidence suggests that stress during the critical transition to adulthood may exacerbate psychotic symptoms in high-risk populations. In animal studies, this phenomenon is often modelled through prenatal immune activation. Aims & Objectives This study explores the impact of maternal immune activation (MIA) on maternal and offspring behavior, with an emphasis on identifying early markers of prodromal schizophrenia during adolescence. Method To simulate maternal immune responses during pregnancy, lipopolysaccharide (LPS) was administered prenatally, and the offspring were further subjected to hypothalamic-pituitary-adrenal (HPA) axis activation during adolescence. Behavioral assessments included the social interaction test, the novel object recognition test, and the open field test, which were applied to post-gestation mothers and their juvenile offspring. Electroencephalographic (EEG) recordings were also conducted to measure evoked response potential (ERP) using the negativity mismatch paradigm. Results The results highlighted notable sex-specific effects. Male offspring exposed to LPS exhibited reduced social engagement and impaired cognitive performance, whereas female offspring showed altered social behavior and heightened anxiety-like tendencies. Additionally, LPS-exposed dams demonstrated changes in their own social and cognitive behaviors. ERP recordings revealed marked deficits in MIA-exposed animals. Further analysis of correlations between maternal and offspring behaviors are under way. Discussion & Conclusions This research sheds light on behavioral changes that may signal the early stages of schizophrenia and underscores the importance of both maternal and offspring factors in understanding the disorder's development. By identifying these early behavioral markers, the study provides a foundation for future research aimed at developing effective prevention strategies.
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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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".