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Record W2061816351 · doi:10.3389/fnbeh.2014.00396

5-HT7 receptor signaling: improved therapeutic strategy in gut disorders

2014· review· en· W2061816351 on OpenAlexafffund
Janice Kim, Waliul I. Khan

Bibliographic record

VenueFrontiers in Behavioral Neuroscience · 2014
Typereview
Languageen
FieldMedicine
TopicGastrointestinal motility and disorders
Canadian institutionsMcMaster UniversityPopulation Health Research Institute
FundersCanadian Institutes of Health Research
KeywordsEnterochromaffin cellIrritable bowel syndromeReceptorEnteric nervous system5-HT receptorInflammatory bowel diseaseImmune systemColitisPathogenesisImmunologySerotoninMedicineBiologyDiseaseInternal medicine

Abstract

fetched live from OpenAlex

Serotonin (5-hydroxytryptamine; 5-HT) is most commonly known for its role as a neurotransmitter in the central nervous system (CNS). However, the majority of the body's 5-HT is produced in the gut by enterochromaffin (EC) cells. Alterations in 5-HT signaling have been associated with various gut disorders including inflammatory bowel disease (IBD), irritable bowel syndrome (IBS) and enteric infections. Recently, our studies have identified a key role for 5-HT in the pathogenesis of experimental colitis. 5-HT7 receptors are expressed in the gut and very recently, we have shown evidence of 5-HT7 receptor expression on intestinal immune cells and demonstrated a key role for 5-HT7 receptors in generation of experimental colitis. This review summarizes the key findings of these studies and provides a comprehensive overview of our current knowledge of the 5-HT7 receptor in terms of its pathophysiological relevance and therapeutic potential in intestinal inflammatory conditions, such as IBD.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.002

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 head0.071
GPT teacher head0.360
Teacher spread0.290 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations47
Published2014
Admission routes2
Has abstractyes

Explore more

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