Serotonin Transporter Concentration is Decreased in Cerebral Cortex but not in Striatum of Chronic MDMA (ecstasy) Users
Bibliographic record
Abstract
Background: Ecstasy (3,4-methylenedioxymethamphetamine, MDMA) is an amphetamine derivative that is used recreationally and is now being tested in clinical trials for treatment of posttraumatic stress disorder. Ecstasy can damage serotonin neurones in brain of experimental animals; however, relevance of these findings to the human is debated. Aim: To measure by positron emission tomography (PET) levels of binding to the serotonin transporter (SERT), a marker of serotonin neurones, in brain of chronic ecstasy users and in matched controls. Methods: An estimate of brain SERT levels was obtained, using the PET tracer 11C-DASB, in 50 chronic (confirmed by drug hair testing) ecstasy users (mean age, 26 years; mean duration of drug use, 3.9 years; median drug withdrawal time, 38 days) and 50 (drug-hair negative) control subjects (mean age 26 years). Results: SERT binding levels in the ecstasy group were significantly decreased by 22 to 46% in frontal, temporal, cingulate, insular and occipital cortices, and by 23% in hippocampus. However, concentrations were distinctly normal in the SERT-rich caudate, putamen, ventral striatum and thalamus. Conclusion: Our imaging data suggest that cerebral cortical SERT concentration is below normal in some ecstasy users for at least one month after last use of the drug. However, it remains to be established whether low SERT might have preceded drug use, reflects actual loss of brain serotonin neurones, or is causally related to any functional impairment in the ecstasy users. (Supported by US NIH NIDA DA017301).
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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 | 0.001 | 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) | 0.002 | 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".