Serum levels of D-cycloserine predict antidepressant effects in pharmacologically enhanced intermittent theta-burst stimulation
Bibliographic record
Abstract
BACKGROUND: Transcranial magnetic stimulation is an important treatment option for treatment resistant major depressive disorder. Pairing stimulation with adjuncts such as the partial N-Methyl-d-Aspartate (NMDA) receptor agonist, D-Cycloserine, has emerged as a strategy to enhance treatment outcomes. However, the effects of D-Cycloserine are concentration dependent, and higher concentrations may blunt TMS-induced plasticity. This is clinically important due to the potential for accumulation with repeated dosing and individual differences in volume of distribution. METHODS: We recruited n = 12 individuals with a moderate-severe depressive episode for a pharmacokinetic characterization of repeated D-Cycloserine dosing in the context of a 4 week (20 treatments) open-label trial pairing intermittent theta-burst stimulation (iTBS) using a weight based dose of D-Cycloserine (25 mg/17.5 kg). Prior to treatment, we serially sampled peripheral blood with a 100 mg dose for comparison. Then, serum samples were characterized in conjunction with 25 mg/17.5 kg dosing for the first, the 5th (accumulation), and the 6th (elimination) doses. RESULTS: iTBS+D-Cycloserine was associated with a potent antidepressant effect, achieving 83.3 % response and 75.0 % remission at treatment end with no serious adverse events. Improvements in depressive symptoms were predicted by serum D-Cycloserine concentration. Although we found evidence for accumulation after five doses, the weekend hiatus was sufficient for elimination and the concentration remained within the NMDA receptor agonist range. Serum concentrations did not significantly differ between 100 mg and 25 mg/17.5 kg doses. CONCLUSIONS: Our data confirm the antidepressant effects and safety of extended iTBS+D-Cycloserine, while highlighting the importance of adequate serum concentrations within the agonist range. Weight-based dosing may not be required by default.
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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 | 0.001 |
| 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".