Antiparkinsonian Mechanism of Electroconvulsive Therapy in MPTP-Lesioned Non-Human Primates
Bibliographic record
Abstract
BACKGROUND: Electroconvulsive therapy (ECT), an effective treatment for depression, also improves motor symptomatology in Parkinson's disease (PD). We have previously demonstrated that ECT stimulates dopamine (DA) function in the striatum of healthy non-human primates, suggesting that DA may contribute to antidepressant effects. OBJECTIVE: We investigated the potential role of DA mechanisms in the amelioration of PD symptoms following a clinical course of ECT. METHODS: We treated non-human primates rendered mildly bilaterally or unilaterally parkinsonian with 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP), with a course of 6 ECT treatments. Using positron emission tomography, animals were scanned at baseline and at various time points after ECT with tracers of the DA system. Data were analyzed using the Logan reference tissue model and statistics were performed using orthogonal polynomial contrasts. RESULTS: There was no change in binding of the DA transporter tracer in the lesioned striata after ECT as opposed to what we measured in the striatum of healthy animals. Raclopride binding to the D(2/3) receptors was unaffected in all groups. However, there were increases in vesicular monoamine transporter type 2 and D(1) receptor binding in the MPTP-lesioned striata after ECT, returning towards baseline by 6 weeks. CONCLUSION: We suggest that the effects of ECT in PD may proceed from a mechanism similar to that in healthy animals but with a blunted dopaminergic response, likely due to the significant loss of striatal DA terminals. The safety of ECT, its mild side effects and its stimulatory effects of the DA system may thus make it an attractive adjunct to antiparkinsonian treatment.
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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) | 0.001 | 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".