Bibliographic record
Abstract
Behavioral models used to test potential antidepressants have shown that ligands that bind to sigma receptors possess "antidepressant-like" properties. The focus of this review is to discuss the literature concerning sigma receptors and their ligands, with respect to their antidepressants properties. In addition to the behavioral data, we discuss electrophysiological and biochemical models demonstrating sigma receptors' ability to modulate important factors in the pathophysiology of depression and/or the mechanisms of action of antidepressants such as the serotonergic neurotransmission in the dorsal raphe nucleus (DRN) and the glutamatergic transmission in the hippocampus. We also discuss the significance of these two systems in the mechanism of action of antidepressants. Sigma ligands have potential as antidepressant medications with a fast onset of action as they produce a rapid modulation of the serotonergic system in the DRN and the glutamatergic transmission in the hippocampus. As these effects of sigma ligands may produce antidepressant properties by completely novel mechanisms of action, they may provide an alternative to the antidepressants currently available and may prove to be beneficial for treatment-resistant depressed patients.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".