Effects of repeated lysergic acid diethylamide (LSD) on the mouse brain endocannabinoidome and gut microbiome
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Psychedelics elicit prosocial, antidepressant and anxiolytic effects via neuroplasticity, neurotransmission and neuro-immunomodulatory mechanisms. Whether psychedelics affect the brain endocannabinoid system and its extended version, the endocannabinoidome (eCBome) or the gut microbiome, remains unknown. EXPERIMENTAL APPROACH: Adult C57BL/6N male mice were administered lysergic acid diethylamide (LSD) or saline for 7 days. Sociability was assessed in the direct social interaction and three chambers tests. Prefrontal cortex and hippocampal endocannabinoids, endocannabinoid-like mediators and metabolites were quantified via high-pressure liquid chromatography with tandem mass spectrometry (HPLC-MS/MS). Neurotransmitter levels were assessed via HPLC-UV/fluorescence. Gut microbiome changes were investigated by 16S ribosomal DNA sequencing. KEY RESULTS: ); thromboxane 2 and kynurenine. Prefrontal eCBome mediator and metabolite levels were less affected by the treatment. LSD decreased Shannon alpha diversity of the gut microbiota, prevented the decrease in the Firmicutes:Bacteroidetes ratio observed in saline-treated mice and altered the relative abundance of the bacterial taxa Bifidobacterium, Ileibacterium, Dubosiella and Rikenellaceae RC9. CONCLUSIONS AND IMPLICATIONS: The prosocial effects elicited by repeated LSD administration are accompanied by alterations of hippocampal eCBome and kynurenine levels, and the composition of the gut microbiota. Modulation of the hippocampal eCBome and kynurenine pathway might represent a mechanism by which psychedelic compounds elicit prosocial effects and affect the gut microbiome.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".