Increased Vesicular Monoamine Transporter 2 (VMAT2;<i>Slc18a2</i>) Protects against Methamphetamine Toxicity
Bibliographic record
Abstract
The psychostimulant methamphetamine (METH) is highly addictive and neurotoxic to dopamine terminals. METH toxicity has been suggested to be due to the release and accumulation of dopamine in the cytosol of these terminals. The vesicular monoamine transporter 2 (VMAT2; SLC18A2) is a critical mediator of dopamine handling. Mice overexpressing VMAT2 (VMAT2-HI) have an increased vesicular capacity to store dopamine, thus augmenting striatal dopamine levels and dopamine release in the striatum. Based on the altered compartmentalization of intracellular dopamine in the VMAT2-HI mice, we assessed whether enhanced vesicular function was capable of reducing METH-induced damage to the striatal dopamine system. While wildtype mice show significant losses in striatal levels of the dopamine transporter (65% loss) and tyrosine hydroxylase (46% loss) following a 4 × 10 mg/kg METH dosing regimen, VMAT2-HI mice were protected from this damage. VMAT2-HI mice were also spared from the inflammatory response that follows METH treatment, showing an increase in astroglial markers that was approximately one-third of that of wildtype animals (117% vs 36% increase in GFAP, wildtype vs VMAT2-HI). Further analysis also showed that elevated VMAT2 level does not alter the ability of METH to increase core body temperature, a mechanism integral to the toxicity of the drug. Finally, the VMAT2-HI mice showed no difference from wildtype littermates on both METH-induced conditioned place preference and in METH-induced locomotor activity (1 mg/kg METH). These results demonstrate that elevated VMAT2 protects against METH toxicity without enhancing the rewarding effects of the drug. Since the VMAT2-HI mice are protected from METH despite higher basal dopamine levels, this study suggests that METH toxicity depends more on the proper compartmentalization of synaptic dopamine than on the absolute amount of dopamine in the brain.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".