Amphetamine disrupts dopamine axon growth in adolescence by a sex-specific mechanism
Bibliographic record
Abstract
Abstract Initiating drug use during adolescence increases the risk of developing addiction and psychiatric disorders later in life, with long-term outcomes varying according to sex and exact timing of use. Even though most individuals begin experimenting with drugs of abuse in adolescence, to date, the cellular and molecular underpinnings explaining differential sensitivity to detrimental drug effects remain unknown. The Netrin-1/DCC guidance cue system plays a critical role in the adolescent development of mesocorticolimbic dopamine circuitry, segregating the cortical and limbic pathways. Adolescent experiences, including exposure to drugs of abuse, can regulate Dcc expression in male mice, placing Netrin-1/DCC signaling as a potential molecular link between experience and enduring changes to circuitry and behavior. Here we show that exposure to a recreational-like regimen of amphetamine (AMPH) in adolescence induces sex- and age-specific alterations in Dcc expression in the ventral tegmental area. Female mice are protected against the deleterious long-term effects of AMPH-induced Dcc regulation by compensatory changes in the expression of its binding partner, Netrin-1. AMPH induces targeting errors in mesolimbic dopamine axons and triggers their ectopic growth to the prefrontal cortex, only in early-adolescent male mice, underlying a male-specific vulnerability to its enduring cognitive effects. Upregulating DCC receptor expression in dopamine neurons in adolescent males using a neuron-optimized CRISPR/dCas9 Activation System induces female-like protection against the persistent effects of AMPH in early adolescence on inhibitory control. Netrin-1/DCC signaling is therefore a molecular switch which can be differentially regulated in response to the same experience as function of age and sex of the individual, leading to divergent long-term outcomes associated with vulnerable or resilient phenotypes.
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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) | 0.000 | 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".