Investigating the “two-hit hypothesis”: effects of prenatal maternal immune activation and adolescent cannabis use on neurodevelopment in mice
Bibliographic record
Abstract
Abstract Background Prenatal exposure to maternal immune activation (MIA) and chronic adolescent cannabis use are both risk factors for neuropsychiatric disorders. However, exposure to a single risk factor may not result in major mental illness, indicating that multiple exposures may be required for illness onset. Here, we examine whether combined exposure to prenatal MIA and adolescent delta-9-tetrahydrocannabinol (THC), the main psychoactive component of cannabis, lead to enduring neuroanatomical and behavioural changes in adulthood. Methods Mice were prenatally exposed to viral mimetic, poly I:C (5mg/kg), or vehicle at gestational day (GD)9, and postnatally exposed to chronic THC (5mg/kg, intraperitoneal) or vehicle during adolescence (postnatal day [PND]28-45). Longitudinal magnetic resonance imaging (MRI) was performed pre-treatment, PND25, post-treatment, PND50, and in adulthood, PND85, followed by behavioural tests for anxiety-like, social, and sensorimotor gating. Postmortem assessment of cannabinoid (CB)1 and 2 receptor expressing cells was performed in altered regions identified by MRI (anterior cingulate and somatosensory cortices, striatum, and hippocampus). Results Subtle deviations in neurodevelopmental trajectory and subthreshold anxiety-like behaviours were observed in mice exposed to both risk factors. Sex-dependent effects were observed in patterns of shared brain-behaviour covariation, indicative of potential sex differences in response to MIA and THC. Density of CB1 and CB2 receptor positive cells was significantly decreased in all mice exposed to MIA, THC, or both. Conclusions These findings suggest that there may be a cumulative effect of risk factor exposure on gross neuroanatomical development, and that the endocannabinoid system may be sensitive to both prenatal MIA, adolescent THC, or the combination.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".