Can the gut-brain axis provide insight into psilocybin's therapeutic value in reducing stress?
Bibliographic record
Abstract
There is growing interest in exploring the therapeutic potential and mechanisms of action of psilocybin on stress-related neuropsychiatric disorders, including depression, generalized anxiety disorder (GAD), post-traumatic stress disorder (PTSD), obsessive-compulsive disorder (OCD), addiction, and disordered eating. Despite promising progressions in preclinical and clinical research, the neurobiological and physiological mechanisms underlying the therapeutic effects of psilocybin remain complex, involving multiple systems with numerous homeostatic feedback signaling pathways throughout the body. This review paper explores how psilocybin mechanistically interacts with the gut microbiota, enteric nervous system, hypothalamic-pituitary axis, and how psilocybin influences the bidirectional communication between peripheral and neuronal systems. Shifting towards a more integrated paradigm to unravel the mechanisms through which psilocybin affects the bidirectional gut-brain axis holds the promise of significantly advancing our understanding of psilocybin-based therapies from preparation of treatment, administration, to proceeding long-term integration. Such an understanding can extend beyond the treatment of psychiatric disorders, further encompassing a broader spectrum of inflammatory-related disorders.
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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) | 0.001 | 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 | 0.001 |
| 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".