The Effects of Peripubertal THC Exposure in Neurodevelopmental Rat Models of Psychopathology
Bibliographic record
Abstract
Adolescent exposure to cannabinoids as a postnatal environmental insult may increase the risk of psychosis in subjects exposed to perinatal insult, as suggested by the two-hit hypothesis of schizophrenia. Here, we hypothesized that peripubertal Δ9-tetrahydrocannabinol (aTHC) may affect the impact of prenatal methylazoxymethanol acetate (MAM) or perinatal THC (pTHC) exposure in adult rats. We found that MAM and pTHC-exposed rats, when compared to the control group (CNT), were characterized by adult phenotype relevant to schizophrenia, including social withdrawal and cognitive impairment, as revealed by social interaction test and novel object recognition test, respectively. At the molecular level, we observed an increase in cannabinoid CB1 receptor (Cnr1) and/or dopamine D2/D3 receptor (Drd2, Drd3) gene expression in the prefrontal cortex of adult MAM or pTHC-exposed rats, which we attributed to changes in DNA methylation at key regulatory gene regions. Interestingly, aTHC treatment significantly impaired social behavior, but not cognitive performance in CNT groups. In pTHC rats, aTHC did not exacerbate the altered phenotype nor dopaminergic signaling, while it reversed cognitive deficit in MAM rats by modulating Drd2 and Drd3 gene expression. In conclusion, our results suggest that the effects of peripubertal THC exposure may depend on individual differences related to dopaminergic neurotransmission.
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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 | 0.001 | 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) | 0.001 | 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".