Effects of a single dose of psilocybin on cytokines, chemokines and leptin in rat serum
Bibliographic record
Abstract
Abstract Background and Aims The hallucinogenic drug psilocybin is being widely tested in humans for the treatment of psychiatric disorders. Psilocybin and other psychedelics are proposed to work through serotonin 2a (5-HT2a) receptors, which are tightly linked to immune function. The purpose of the present study was to assess the effects of a single dose of psilocybin on a panel of cytokines, chemokines, and peptides in the short term (24 h) and long term (seven days) in female rats. Methods Female rats were given a dose of psilocybin (20 mg kg−1, i.p.} or a dose of synthetic interstitial fluid. At 24 h, the control group and one group of rats were anesthetized, and blood was withdrawn by intracardiac puncture. In a third group of rats, blood was withdrawn after seven days. Serum was analyzed by a separate lab (Eve Laboratories, Calgary, Canada) for 27 immunomodulators. Results Serum levels of IL-1β, TNF-α, MCP-1, IP-10, G-CSF, IFN-γ, IL-10, IL-13, and leptin were significantly increased compared to controls after 24 h and were increased further after 7 days. Most of the other assays showed this same pattern of increase, although not statistically significant. Conclusions Psilocybin induces the release of multiple immune factors, consistent with a generalized activation of the immune system, which can persist for at least seven days after a single dose. These findings may relate to the mechanism of action. The implications of these findings require additional research to determine how these finding relate to the clinical effects of psilocybin.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".