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Record W4417079703 · doi:10.1016/j.phrs.2025.108059

From the gut to the brain: Potential novel avenues for IBD treatment via serotonergic pathways

2025· review· en· W4417079703 on OpenAlexaff
Sara Ibgui, Daisy Lints, Simon Milling

Bibliographic record

VenuePharmacological Research · 2025
Typereview
Languageen
FieldPsychology
TopicPsychedelics and Drug Studies
Canadian institutionsInstitute of Infection and Immunity
Fundersnot available
KeywordsSerotonergicDysbiosisInflammatory bowel diseaseDiseaseUlcerative colitisNeuroinflammationPathogenesisGut floraSignalling

Abstract

fetched live from OpenAlex

Inflammatory bowel disease (IBD) is an idiopathic condition characterised by chronic relapsing intestinal inflammation, affecting approximately 6.8 million people globally. Crohn's disease and ulcerative colitis are two main subtypes. The microbiota in IBD patients has been extensively researched, and dysbiosis is associated with IBD onset. While current treatments reduce morbidity and improve the quality of life of IBD patients, they have strong anti-inflammatory effects, creating an immunosuppressed environment and increase the risk of comorbidities, highlighting the need for better therapeutics. The gut-brain axis (GBA) communication pathway allows bidirectional neural, hormonal, metabolic, immunological and microbial signalling. This review investigates the signalling pathways across the GBA and explores how dysbiosis, neuroinflammation and serotonergic dysregulation are interlinked and may contribute to IBD pathogenesis and neurological comorbidities. Focusing on the immunomodulation of serotonergic signalling and proposed mechanisms of action of psychotropic drugs, including antidepressants and psychedelic compounds, we highlight the serotonergic signalling pathway as a potential novel therapeutic target for IBD combination therapy.

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 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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.699
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.497
GPT teacher head0.588
Teacher spread0.091 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations2
Published2025
Admission routes1
Has abstractyes

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