Molecular Pathways of the Therapeutic Effects of Ayahuasca, a Botanical Psychedelic and Potential Rapid-Acting Antidepressant
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Ayahuasca is a psychoactive brew traditionally used in indigenous and religious rituals and ceremonies in South America for its therapeutic, psychedelic, and entheogenic effects. It is usually prepared by lengthy boiling of the leaves of the bush Psychotria viridis and the mashed stalks of the vine Banisteriopsis caapi in water. The former contains the classical psychedelic N,N-dimethyltryptamine (DMT), which is thought to be the main psychoactive alkaloid present in the brew. The latter serves as a source for β-carbolines, known for their monoamine oxidase-inhibiting (MAOI) properties. Recent preliminary research has provided encouraging results investigating ayahuasca’s therapeutic potential, especially regarding its antidepressant effects. On a molecular level, pre-clinical and clinical evidence points to a complex pharmacological profile conveyed by the brew, including modulation of serotoninergic, glutamatergic, dopaminergic, and endocannabinoid systems. Its substances also interact with the vesicular monoamine transporter (VMAT), trace amine-associated receptor 1 (TAAR1), and sigma-1 receptors. Furthermore, ayahuasca’s components also seem to modulate levels of inflammatory and neurotrophic factors beneficially. On a biological level, this translates into neuroprotective and neuroplastic effects. Here we review the current knowledge regarding these molecular interactions and how they relate to the possible antidepressant effects ayahuasca seems to produce.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it