mGlu5 receptor availability in youth at risk for addictions: effects of vulnerability traits and cannabis use
Bibliographic record
Abstract
Abstract The excitatory neurotransmitter glutamate has been implicated in experience-dependent neuroplasticity and drug-seeking behaviors. Type 5 metabotropic glutamate (mGlu5) receptors might be particularly important. They are critically involved in synaptic plasticity and their availability has been reported to be lower in people with alcohol, tobacco, and cocaine use disorders. Since these reductions could reflect effects of drug use or pre-existing traits, we used positron emission tomography to measure mGlu5 receptor availability in young adults at elevated risk for addictions. Fifty-nine participants (age 18.5 ± 0.6) were recruited from a longitudinal study that has followed them since birth. Based on externalizing traits that predict future substance use problems, half were at low risk, half were at high risk. Cannabis use histories varied markedly and participants were divided into three subgroups: zero, low, and high use. Compared to low risk volunteers, those at elevated risk had lower [11C]ABP688 binding potential (BPND) values in the striatum, amygdala, insula, and orbitofrontal cortex (OFC). Cannabis use by risk group interactions were observed in the striatum and OFC. In these regions, low [11C]ABP688 BPND values were only seen in the high risk group that used high quantities of cannabis. When these high risk, high cannabis use individuals were compared to all other participants, [11C]ABP688 BPND values were lower in the striatum, OFC, and insula. Together, these results provide evidence that mGlu5 receptor availability is low in youth at elevated risk for addictions, particularly those who frequently use cannabis.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".