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Record W4384129355 · doi:10.1093/jcag/gwad020

Emerging Roles of Gut Serotonin in Regulation of Immune Response, Microbiota Composition and Intestinal Inflammation

2023· article· en· W4384129355 on OpenAlexafffund
Jensine A. Grondin, Waliul I. Khan

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsMcMaster UniversityPopulation Health Research Institute
FundersCanadian Institutes of Health Research
KeywordsImmune systemInflammationPathogenesisGut floraImmunologyContext (archaeology)BiologyAutophagyImmunityGenetics

Abstract

fetched live from OpenAlex

Although the exact etiology of inflammatory bowel diseases (IBD) is unknown, studies have shown that dysregulated immune responses, genetic factors, gut microbiota, and environmental factors contribute to their pathogenesis. Intriguingly, serotonin (5-hydroxytryptamine or 5-HT) seems to be a molecule with increasingly strong implications in the pathogenesis of intestinal inflammation, affecting host physiology, including autophagy and immune responses, as well as microbial composition and function. 5-HT may also play a role in mediating how environmental effects impact outcomes in IBD. In this review, we aim to explore the production and important functions of 5-HT, including its impact on the gut. In addition, we highlight the bidirectional impacts of 5-HT on the immune system, the gut microbiota, and the process of autophagy and how these effects contribute to the manifestation of intestinal inflammation. We also explore recent findings connecting 5-HT signalling and the influence of environmental factors, particularly diet, in the pathogenesis of IBD. Ultimately, we explore the pleiotropic effects of this ancient molecule on biology and health in the context of intestinal inflammation.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.646
Threshold uncertainty score0.966

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.005
GPT teacher head0.228
Teacher spread0.223 · 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 designObservational
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".

Quick stats

Citations44
Published2023
Admission routes2
Has abstractyes

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