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Record W4205983767 · doi:10.1038/s41385-021-00479-3

The double-edged sword of gut bacteria in celiac disease and implications for therapeutic potential

2022· review· en· W4205983767 on OpenAlexafffund
Heather J. Galipeau, Elena F. Verdú

Bibliographic record

VenueMucosal Immunology · 2022
Typereview
Languageen
FieldMedicine
TopicCeliac Disease Research and Management
Canadian institutionsPopulation Health Research InstituteMcMaster University
FundersCanadian Institutes of Health Research
KeywordsPathogenesisDiseaseMechanism (biology)GlutenImmune systemImmunologyMedicineAdjuvantBioinformaticsBiologyPathology

Abstract

fetched live from OpenAlex

Celiac disease (CeD) is an immune-mediated disease, triggered by gluten ingestion, in genetically susceptible individuals. The gluten-free diet (GFD) is the only current treatment for CeD, but is difficult to follow, has high non-adherence rates, and does not always lead to symptomatic or mucosal remission. Microbially-mediated mechanisms have been proposed to contribute to disease pathogenesis, and clinical studies support an association, but mechanistic insight has been difficult to obtain. Recent advances using translational approaches have provided clues to the mechanisms through which bacteria could contribute to CeD pathogenesis. In this review we discuss these bacterially mediated mechanisms, which include the modulation of pathogenic or protective pathways. Targeting these pathways through microbial therapeutics could provide adjuvant therapies to the GFD.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.002

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 head0.077
GPT teacher head0.391
Teacher spread0.314 · 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

Citations25
Published2022
Admission routes2
Has abstractyes

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