The exploration of the behavioural and neurological consequences of prenatal THC exposure in male vs female offspring
Bibliographic record
Abstract
The developing brain is especially vulnerable to the schizophrenia-inducing effects of tetrahydrocannabinol (THC), the psychoactive chemical in cannabis. Although the mechanisms underlying schizophrenia remains unclear, aberrant mesocorticolimbic signaling and brain omega-3 deficiency may be involved. This study investigated chronic prenatal THC’s effects on schizophrenia-associated behaviour as well as the neuronal activity states and omega-3 levels in the mesocorticolimbic system. Behaviourally, THC induced social memory impairments in male offspring whereas female exposure increased anxiety and anhedonia. Electrophysiology revealed ventral tegmental area dopamine hyperactivity and ventral hippocampus glutamate hyperactivity in male offspring whereas female exposure induced glutamate hyperactivity in the prefrontal cortex and ventral hippocampus. Lastly, matrix-assisted laser desorption/ionization imaging mass spectrometry showed that THC induces omega-3 deficiency in the prefrontal cortex, nucleus accumbens, and ventral hippocampus. These findings suggest that prenatal THC may induce different schizophrenia-associated effects on male and female offspring which calls for sex-specific treatments to counter THC’s effects.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".