The sigma–1 receptor: a mechanistically–informed therapeutic target for antidepressants
Bibliographic record
Abstract
INTRODUCTION: The mechanism of action of antidepressants is not fully ascertained. In addition to monoamines, disparate other effectors are also implicated in the molecular and cellular effects of chronic stress including neurogenesis, neurodifferentiation, and neuroplasticity. Evidence suggests sigma-1 receptors (S1Rs) as a putative target and possible mediator of antidepressant activity. AREAS COVERED: levels as well as immune inflammatory responses. The introduction of the N-Methyl-D-aspartic Acid (NMDA) antagonist/S1R agonist dextromethorphan-bupropion in August of 2022 represented the first time the Food and Drug Administration (FDA) permitted language that the hypothesized mechanism of an antidepressant involved activity at S1Rs. We also describe the physiology, pathophysiology, and function of S1Rs. EXPERT OPINION: Sigma-1 modulation is relevant to the mechanism of action of agents currently FDA-approved in major depressive disorder (MDD) (e.g. dextromethorphan-bupropion). Modulating sigma-1 systems is fit for purpose as it relates to future therapeutic discoveries and development in depressive and other mental disorders. Whether sigma-1 modulation is uniquely relevant to targeting dimensions of psychopathology that are more difficult to treat (i.e. anhedonia) awaits determination.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".