Selective serotonin reuptake inhibitor (SSRI) modulation of striatal dopamine measured with [<sup>11</sup>C]‐raclopride and positron emission tomography
Bibliographic record
Abstract
The effect of a pharmacologic increase in serotonin concentrations on striatal dopamine (D2) receptor availability has been measured in several studies using positron emission tomography (PET) and the radiotracer [11C]-raclopride as a method for the in vivo imaging of serotonin modulation of striatal dopamine in human subjects. These studies have shown that an acute increase in serotonin concentrations produced a decrease in striatal D2 receptor availability. The current study was undertaken to measure the effects of a more pharmacologically selective serotonergic agent compared to previous studies, the serotonin reuptake inhibitor, citalopram, on striatal D2 receptor availability. Twelve healthy control subjects underwent two PET scans performed on the same day following i.v. administration of saline (Scan 1) and citalopram (Scan 2, 40 mg, i.v.). The [11C]-raclopride data were analyzed with a graphical analysis method using the cerebellum as the input function. Plasma levels of citalopram, cortisol, and prolactin were measured. The citalopram concentrations peaked at the end of infusion (EOI) and remained relatively consistent from 30 min to 3 h postinfusion. An increase in cortisol and prolactin concentrations was observed from the EOI until 60 min after the EOI. A significant decrease in striatal D2 receptor availability was observed after citalopram infusion (-5%), presumably due to an increase in endogenous dopamine concentrations. In summary, i.v. administration of the selective serotonin reuptake inhibitor, citalopram, produced modest reductions in striatal D2 receptor availability, consistent with other human [11C]-raclopride studies using less pharmacologically selective serotonergic agents.
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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) | 0.002 | 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".