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Record W4407387126 · doi:10.1093/ijnp/pyae059.134

PSILOCYBIN MITIGATES BEHAVIORAL DESPAIR AND COGNITIVE RECOGNITION IMPAIRMENTS BY REGULATING THE HYPOTHALAMIC- PITUITARY-ADRENAL (HPA) AXIS VIA THE BRAIN-DERIVED NEUROTROPHIC FACTOR (BDNF) SIGNALING PATHWAY MEDIATED BY THE ENDOCANNABINOID SYSTEM (ECS)

2025· article· en· W4407387126 on OpenAlexaff
Zitong Wang, Yanbo Zhang, Xin‐Min Li

Bibliographic record

VenueThe International Journal of Neuropsychopharmacology · 2025
Typearticle
Languageen
FieldPsychology
TopicPsychedelics and Drug Studies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsBrain-derived neurotrophic factorNeuroscienceEndocannabinoid systemNeurotrophic factorsPsychologyMedicineInternal medicineReceptor

Abstract

fetched live from OpenAlex

Abstract Background Dr. George Engel introduced the biopsychosocial model into the field of psychiatry 40 years ago, highlighting the profound connection between social environment and mental health. Factors have been categorized into biological, psychological, and socio-environmental domains. Numerous animal models have been developed to investigate the pathophysiology and treatment of depression; however, none have effectively encapsulated the biopsychosocial model.Several studies have underscored the importance of the HPA axis in regulating mood and cognitive functions under stress. The Endocannabinoid System (ECS) is a well-studied neuromodulatory system that operates within the CNS, playing a central role in stress response. Hypothalamus contains cannabinoid CB1 receptors and synthesizes endocannabinoids, which facilitate rapid negative-feedback regulation of the HPA axis through retrograde release.In recent years, research efforts have focused on the therapeutic effects of psilocybin in psychiatric conditions, including depression. This has raised questions about whether psilocybin can serve as a mono therapy and what is the mechanism behinds it. Aims & Objectives 1) Compare the behavioral outcomes of psilocybin treatment in two distinct animal models of depression; 2) Investigate the regulation of stress hormones and the underlying mechanisms influenced by psilocybin. Methods The study employed two animal models: 1) The biopsychosocial animal model of depression, represented by introducing chronic social instability stress (SIS) to Wistar-Kyoto (WKY) rats - the model of treatment-resistant depression; 2) The stress-induced animal model of depression, generated by subjecting Wistar (WIS) rats, a wildtype control, to chronic SIS. Series of behavioral test have been conducted followed by postmortem analysis. Results In the OFT, 1.0mg/kg psilocybin notably increased the distance traveled and reduced immobility in stressed WIS rats but not in stressed WKY rats. The EPM showed no significant reductions in freezing time or time spent in the arms for both strains, yet risk assessment time was significantly reduced. In the FST, psilocybin reduced immobility and increased swimming and climbing in both strains. In the SPT, psilocybin elevated sucrose preference in stressed WIS rats. Lastly, in the NOR, psilocybin significantly enhanced recognition in both rat strains. Biochemical analysis of cardiac blood revealed that 1.0mg/kg psilocybin significantly downregulated ACTH and corticosterone levels in stressed WIS rats but not in stressed WKY rats. In contrast, it upregulated TSH and melatonin levels in both rat strains. Psilocybin also increased BDNF levels in blood and specific brain regions, affecting the PFC, amygdala, hippocampus, and hypothalamus. Psilocybin was found to upregulate the levels of CB1R and TrkB and activate Akt, ERK, and mTOR pathways. Additionally, psilocybin improved the level of 2-AG in all four brain regions in both rat strains. Discussion and Conclusion Psilocybin appears to mitigate stress-induced dysregulation of the HPA axis by modulating the BDNF signaling pathway mediated by the ECS. This contributes to the observed positive effects on depressive- like behavior and cognitive impairment. This study enhances our understanding of how psilocybin exerts antidepressant-like effects and offers insights into the development of depression treatment strategies by providing a biopsychosocial animal model of depression. References BECKER, M., PINHASOV, A. & ORNOY, A. 2021. Animal Models of Depression: What Can They Teach Us about the Human Disease? Diagnostics (Basel), 11. BOLTON, D. &GILLETT, G. 2019. The biopsychosocial model of health and disease: New philosophical and scientific developments, Springer Nature. LU, H. C. &MACKIE, K. 2016. An Introduction to the Endogenous Cannabinoid System. Biol Psychiatry, 79, 516-25. PAPADIMITRIOU, G. 2017. The "Biopsychosocial Model": 40 years of application in Psychiatry. Psychiatriki, 28, 107-110. PLANCHEZ, B., SURGET, A. &BELZUNG, C. 2019. Animal models of major depression: drawbacks and challenges. J Neural Transm (Vienna), 126, 1383-1408. WANG, Q., TIMBERLAKE, M. A., 2ND, PRALL, K. &DWIVEDI, Y. 2017. The recent progress in animal models of depression. Prog Neuropsychopharmacol Biol Psychiatry, 77, 99-109.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.602
Threshold uncertainty score0.807

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.025
GPT teacher head0.321
Teacher spread0.295 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

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Citations0
Published2025
Admission routes1
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