Adolescent‐onset heavy cannabis use associated with significantly reduced glial but not neuronal markers and glutamate levels in the hippocampus
Bibliographic record
Abstract
Cannabis use has been associated with adverse mental health outcomes, the neurochemical underpinnings of which are poorly understood. Although preclinical evidence suggests glutamatergic dysfunction following cannabis exposure in several brain regions including the hippocampus, evidence from human studies have been inconsistent. We investigated the effect of persistent cannabis use on the brain levels of N-acetyl aspartate (NAA) and myoinositol, the metabolite markers of neurons and glia, the site of the main central cannabinoid CB1 receptor, and the levels of glutamate, the neurotransmitter directly affected by CB1 modulation. We investigated cannabis users (CUs) who started using during adolescence, the period of greatest vulnerability to cannabis effects and focused on the hippocampus, where type 1 cannabinoid receptors (CBR1) are expressed in high density and have been linked to altered glutamatergic neurotransmission. Twenty-two adolescent-onset CUs and 21 nonusing controls (NU), completed proton magnetic resonance spectroscopy, to measure hippocampal metabolite concentrations. Glutamate, NAA, and myoinositol levels were compared between CU and NU using separate analyses of covariance. CU had significantly lower myoinositol but not glutamate or NAA levels in the hippocampus compared with NU. Myoinositol levels in CU positively correlated with glutamate levels, whereas this association was absent in NU. Altered myoinositol levels may be a marker of glia dysfunction and is consistent with experimental preclinical evidence that cannabinoid-induced glial dysfunction may underlie cannabinoid-induced memory impairments. Future studies using appropriate imaging techniques such as positron emission tomography should investigate whether glial dysfunction associated with cannabis use underlies hippocampal dysfunction and memory impairment in CUs.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".