Hallucinogenic/psychedelic 5HT2A receptor agonists as rapid antidepressant therapeutics: Evidence and mechanisms of action
Bibliographic record
Abstract
Major depressive disorder (MDD) is among the most prevalent mental health disorders worldwide, and it is associated with a reduced quality of life and enormous costs to health care systems. Available drug treatments show low-to-moderate response in most patients, with almost a third of patients being non-responders (treatment-resistant). Furthermore, most currently available medications need several weeks to achieve therapeutic effects, and the long-term use of these drugs is often associated with significant unwanted side effects and resultant reductions in treatment compliance. Therefore, more effective, safer, and faster-acting antidepressants with enduring effects are needed. Together with ketamine, psychedelics (or classic or serotoninergic hallucinogens) such as lysergic acid diethylamide (LSD), psilocybin, and ayahuasca are among the few compounds with recent human evidence of fast-acting antidepressant effects. Several studies in the 1950s to 1970s reported antidepressive and anxiolytic effects of these drugs, which are being confirmed by modern trials (LSD, one trial; psilocybin, five trials; ayahuasca, two trials). The effects of these drugs appear to be produced primarily by their agonism at serotonin (5-hydroxytryptamine, 5-HT) receptors, especially the 5-HT 2A receptor. Considering the overall burden of MDD and the necessity of new therapeutic options, the promising (but currently limited) evidence of safety and efficacy of psychedelics has encouraged the scientific community to explore more fully their beneficial effects in MDD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".