Occupancy of Norepinephrine Transporter by Duloxetine in Human Brains Measured by Positron Emission Tomography with (S,S)-[18F]FMeNER-D2
Bibliographic record
Abstract
Background: The norepinephrine transporter in the brain has been targeted in the treatment of psychiatric disorders. Duloxetine is a serotonin and norepinephrine reuptake inhibitor that has been widely used for the treatment of depression. However, the relationship between dose and plasma concentration of duloxetine and norepinephrine transporter occupancy in the human brain has not been determined. In this study, we examined norepinephrine transporter occupancy by different doses of duloxetine. Methods: We calculated norepinephrine transporter occupancies from 2 positron emission tomography scans using (S,S)-[18F]FMeNER-D2 before and after a single oral dose of duloxetine (20 mg, n = 3; 40 mg, n = 3; 60 mg, n =2). Positron emission tomography scans were performed from 120 to 180 minutes after an i.v. bolus injection of (S,S)-[18F]FMeNER-D2. Venous blood samples were taken to measure the plasma concentration of duloxetine just before and after the second positron emission tomography scan. Results: Norepinephrine transporter occupancy by duloxetine was 29.7% at 20 mg, 30.5% at 40 mg, and 40.0% at 60 mg. The estimated dose of duloxetine inducing 50% norepinephrine transporter occupancy was 76.8 mg, and the estimated plasma drug concentration inducing 50% norepinephrine transporter occupancy was 58.0 ng/mL. Conclusions: Norepinephrine transporter occupancy by clinical doses of duloxetine was approximately 30% to 40% in human brain as estimated using positron emission tomography with (S,S)-[18F]FMeNER-D2.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.003 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".