Levomilnacipran, but Not Duloxetine, Inhibits Serotonin and Norepinephrine Reuptake Throughout Its Therapeutic Range
Bibliographic record
Abstract
The primary aim of this study was to establish that levomilnacipran potently inhibits norepinephrine (NE) reuptake in human participants starting at a minimally efficacious regimen in major depressive disorder (MDD) and to determine the dose needed to significantly inhibit serotonin (5-HT) reuptake. The secondary aim was to confirm that duloxetine is a selective 5-HT reuptake inhibitor at its minimally effective regimen in MDD and that it significantly inhibits NE reuptake only with dose escalation. Inhibition of the NE reuptake process was estimated by assessing the attenuation of the systolic blood pressure produced by intravenous injections of small doses of tyramine. Inhibition of the 5-HT reuptake process was estimated using depletion of whole blood 5-HT. Healthy male participants took ascending daily doses of levomilnacipran (40, 80, and 120 mg), duloxetine (60, 90, and 120 mg) each for 7 days, or a placebo pill (n=10, 9, and 10, respectively), and all assays were carried out 2-6 hours after the last dose. The study took place between February 2018 and October 2022. Plasma levels of both medications increased in dose-dependent levels. Neither the tyramine pressor responses nor 5-HT levels were significantly altered in the placebo group. For the attenuation of the tyramine pressor response, levomilnacipran separated from baseline starting at 40 mg and duloxetine separated from baseline only at 120 mg. Both drugs robustly decreased 5-HT levels to the same extent at all 3 doses. Levomilnacipran is a potent dual reuptake inhibitor from its minimally effective dose in MDD, whereas the dose of duloxetine needs to reach 120 mg/day to consistently inhibit NE reuptake. ClinicalTrials.gov identifier: NCT03249311.
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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".