Serotonin Transporter Occupancy of Five Selective Serotonin Reuptake Inhibitors at Different Doses: An [<sup>11</sup>C]DASB Positron Emission Tomography Study
Bibliographic record
Abstract
OBJECTIVE: Minimum therapeutic doses of paroxetine and citalopram produce 80% occupancy for the serotonin (5-HT) transporter (5-HTT). The authors used [(11)C]DASB positron emission tomography to measure occupancies of three other selective serotonin reuptake inhibitors (SSRIs) at minimum therapeutic doses. The relationship between dose and occupancy was also investigated. METHOD: Striatal 5-HTT binding potential was measured in 77 subjects before and after 4 weeks of medication administration. Binding potential is proportional to the density of receptors not blocked by medication. Subjects received citalopram, fluoxetine, sertraline, paroxetine, or extended-release venlafaxine. Healthy subjects received subtherapeutic doses; subjects with mood and anxiety disorders received therapeutic doses. Percent reduction in 5-HTT binding potential for each medication and dose was calculated. To obtain test-retest data, binding potential was measured before and after 4 weeks in six additional healthy subjects. RESULTS: Substantial occupancy occurred at subtherapeutic doses for all SSRIs. Compared to test-retest data, each drug at the minimum therapeutic dose had a significant effect on striatal 5-HTT binding potential. Mean occupancy at this dose was 76%-85%. At higher plasma SSRI concentrations, 5-HTT occupancy tended to increase above 80%. For each drug, as the dose (or plasma level) increased, occupancy increased nonlinearly, with a plateau for higher doses. CONCLUSIONS: At tolerable doses, SSRIs have increasing occupancy with increasing plasma concentration or dose. Occupancy of 80% across five SSRIs occurs at minimum therapeutic doses. This suggests that 80% 5-HTT blockade is important for therapeutic effect. Occupancy should be measured during development of antidepressant compounds targeting the 5-HTT.
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) | 0.001 | 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 | 0.000 | 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".