Methamphetamine-Induced Degeneration of Dopaminergic Neurons Involves Autophagy and Upregulation of Dopamine Synthesis
Bibliographic record
Abstract
Methamphetamine (METH) selectively injures the neurites of dopamine (DA) neurons, generally without inducing cell death. It has been proposed that METH-induced redistribution of DA from the vesicular storage pool to the cytoplasm, where DA can oxidize to produce quinones and additional reactive oxygen species, may account for this selective neurotoxicity. To test this hypothesis, we used mice heterozygous (+/-) or homozygous (-/-) for the brain vesicular monoamine uptake transporter VMAT2, which mediates the accumulation of cytosolic DA into synaptic vesicles. In postnatal ventral midbrain neuronal cultures derived from these mice, METH-induced degeneration of DA neurites and accumulation of oxyradicals, including metabolites of oxidized DA, varied inversely with VMAT2 expression. METH administration also promoted the synthesis of DA via upregulation of tyrosine hydroxylase activity, resulting in an elevation of cytosolic DA even in the absence of vesicular sequestration. Electron microscopy and fluorescent labeling confirmed that METH promoted the formation of autophagic granules, particularly in neuronal varicosities and, ultimately, within cell bodies of dopaminergic neurons. Therefore, we propose that METH neurotoxicity results from the induction of a specific cellular pathway that is activated when DA cannot be effectively sequestered in synaptic vesicles, thereby producing oxyradical stress, autophagy, and neurite degeneration.
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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 | 0.000 |
| 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 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".