Imaging the serotonin transporter during major depressive disorder and antidepressant treatment
Bibliographic record
Abstract
This paper focuses on serotonin transporter 5-HTT imaging to investigate major depressive disorder (MDD) and antidepressant occupancy. Such investigations have only recently been possible as a result of major advances in ligand development. The state of the art method is [11C]DASB PET or [11C]-3-amino-4-(2-dimethylaminomethyl-phenylsulfanyl)-benzonitrile) positron emission tomography. [11C]DASB is a breakthrough for brain imaging 5-HTT. Compared with previous radioligands, [11C]DASB offers both high selectivity and a favourable ratio of specific binding relative to free and nonspecific binding. These characteristics contribute to valid, reliable quantitation of the 5-HTT binding potential (BP). The 5-HTT BP can be viewed as an index of 5-HTT density in a medication free state, or unblocked 5-HTT density in a medication-treated state. During major depressive episodes with no other axis I comorbidity, either no difference in regional 5-HTT BP or a trend toward elevated 5-HTT BP is typically found. During major depressive episodes (of MDD) with more severe symptoms of pessimism (dysfunctional attitudes), regional 5-HTT BP is elevated. In subjects with major depressive episodes and comorbid axis I psychiatric illnesses, decreased regional 5-HTT BP is often reported. With selective serotonin reuptake inhibitor (SSRI) treatment at doses that distinguish from placebo in the treatment of major depressive episodes, 5-HTT occupancy is approximately 80%, and there is a strong relation between plasma level and occupancy that is not predictable based on affinity alone. Implications of 5-HTT imaging findings for understanding major depressive disorder and antidepressant treatment will be discussed.
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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) | 0.001 | 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 | 0.001 | 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".