Rewiring the future: drugs abused in adolescence may predispose to mental illness in adult life by altering dopamine axon growth
Bibliographic record
Abstract
Adolescence is a period of increased exploration and novelty-seeking, which includes new social behaviors, as well as drug experimentation, often spurred on by peer pressure. This is unfortunate, as the immature state of the adolescent brain makes it particularly susceptible to the negative developmental impact of drug use. During adolescence, dopamine terminals, which have migrated from the ventral tegmental area, pause in the nucleus accumbens, before segregating by either forming local connections or growing towards the prefrontal cortex (PFC). This developmentally late and lengthy process renders adolescent dopamine axon pathfinding vulnerable to disruption by substance use. Indeed, exposure to stimulant drugs in adolescent male mice, but not females, triggers dopamine axons to mistarget the nucleus accumbens and to grow ectopically to the PFC. Some evidence suggests that at this novel site, the functional organization of the ectopic dopamine axons mirrors that of the intended target. The structural rewiring dysregulates local synaptic connectivity, leading to poor impulse control ability, deficits of which are a core symptom of substance-use disorders. In the present commentary, we argue that different substances of abuse induce dopamine mistargeting events with the off-target trajectory prescribed by the type of drug, leading to psychiatric outcomes later in life.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".