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Record W2946614799 · doi:10.1152/ajpgi.00063.2019

Role for diet in normal gut barrier function: developing guidance within the framework of food-labeling regulations

2019· review· en· W2946614799 on OpenAlexaff
Michael Camilleri, Barbara J. Lyle, Karen Madsen, Justin L. Sonnenburg, Kristin Verbeke, Gary D. Wu

Bibliographic record

VenueAmerican Journal of Physiology-Gastrointestinal and Liver Physiology · 2019
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsUniversity of Alberta
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institutes of Health
KeywordsBarrier functionFunction (biology)DiseaseConceptual frameworkRisk analysis (engineering)BiologyMedicinePathology

Abstract

fetched live from OpenAlex

A reduction in intestinal barrier function is currently believed to play an important role in pathogenesis of many diseases, as it facilitates passage of injurious factors such as lipopolysaccharide, peptidoglycan, whole bacteria, and other toxins to traverse the barrier to damage the intestine or enter the portal circulation. Currently available evidence in animal models and in vitro systems has shown that certain dietary interventions can be used to reinforce the intestinal barrier to prevent the development of disease. The relevance of these studies to human health is unknown. Herein, we define the components of the intestinal barrier, review available modalities to assess its structure and function in humans, and review the available evidence in model systems or perturbations in humans that diet can be used to fortify intestinal barrier function. Acknowledging the technical challenges and the present gaps in knowledge, we provide a conceptual framework by which evidence could be developed to support the notion that diet can reinforce human intestinal barrier function to restore normal function and potentially reduce the risk for disease. Such evidence would provide information on the development of healthier diets and serve to provide a framework by which federal agencies such as the US Food and Drug Administration can evaluate evidence linking diet with normal human structure/function claims focused on reducing risk of disease in the general public.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.904
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.020
GPT teacher head0.285
Teacher spread0.266 · 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.

Study designBench or experimental
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

Citations104
Published2019
Admission routes1
Has abstractyes

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