Effect of electroconvulsive therapy on brain 5-HT<sub>2</sub>receptors in major depression
Bibliographic record
Abstract
BACKGROUND: Brain serotonin(2) (5-hydroxytryptamine(2); 5-HT(2)) receptors were considered potential targets for therapeutic efficacy of electroconvulsive therapy (ECT), but pre-clinical studies showed that electroconvulsive shock up-regulates 5-HT(2) receptors in contrast to antidepressant medications, which down-regulate brain 5-HT(2) receptors. Positron emission tomography (PET) studies in individuals with depression confirmed that antidepressant medications reduce brain 5-HT(2) receptors, but the effects of ECT on these receptors in individuals with depression are unknown. AIMS: To determine if a course of ECT alters brain 5-HT(2) receptors in individuals with depression and whether such changes correlate with improvement in symptoms. METHOD: Fifteen people with major depression, refractory to antidepressant therapy and referred for a course of ECT, had an [18F]setoperone scan during baseline drug-free washout period and another after a course of ECT. We assessed changes in brain 5-HT(2) receptors with ECT and their relationship to therapeutic outcome. RESULTS: Widespread reduction in brain 5-HT(2) receptors was observed in all cortical areas with changes slightly more prominent in the right hemisphere. There was a trend for correlation between reduction in brain 5-HT(2) receptors in right parahippocampal gyrus, right lingual gyrus and right medial frontal gyrus, and improvement in depressive symptoms. CONCLUSIONS: Unlike in rodents, and similar to antidepressants, ECT reduces brain 5-HT(2) receptors in individuals with depression. The ability of ECT to further down-regulate brain 5-HT(2) receptors in antidepressant non-responsive individuals may explain its efficacy in those people with antidepressant refractory depression.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".