The antioxidant N-acetylcysteine prevents cortical neuropathological phenotypes caused by adolescent Δ-9-tetrahydrocannabinol exposure in male rats
Bibliographic record
Abstract
Clinical and pre-clinical evidence demonstrates that adolescent Δ-9-tetrahydrocannabinol (THC) exposure, the primary psychoactive component of cannabis, increases the risk of developing neuropsychiatric symptoms in later life. The medial prefrontal cortex (mPFC) serves as a pathophysiological nexus point underlying many cannabis-related pathophysiological outcomes. Nevertheless, the molecular mechanisms underlying these risk factors are poorly understood. THC increases oxidative stress, which is a well-established causal factor for increased neuropsychiatric risk, including schizophrenia. N-acetylcysteine (NAC) is an antioxidant glutathione precursor that normalizes glutamate and GABA activity in neuropathological states. We examined if NAC may prevent the pathophysiological impacts of THC using a rodent model of adolescent brain development and chronic THC exposure. We report that NAC treatment prevents cognitive, synaptic, neuronal and neurochemical deficits induced by adolescent THC. These findings highlight the critical role of THC-induced oxidative stress as a contributing factor to cannabinoid-mediated neuropsychiatric risk and identifies a novel antioxidant treatment candidate for the prevention and/or reversal of these pathophysiological outcomes.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".