MétaCan
Menu
← Back to cohort

Metabolic Stress Evokes Decreases in Epithelial Barrier Function

2009· review· en· W1950694960 on OpenAlexafffund
Kimberley J. Lewis, Derek M. McKay

Bibliographic record

VenueAnnals of the New York Academy of Sciences · 2009
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsUniversity of Calgary
FundersCanadian Institutes of Health Research
KeywordsBarrier functionFunction (biology)ChemistryStress (linguistics)Cell biologyBiophysicsBiology

Abstract

fetched live from OpenAlex

The epithelial lining of the gastrointestinal tract is the major interface between the external world (e.g., the gut lumen) and the body, and as such the proper maintenance and regulation of epithelial barrier function is a key determinant of digestive health and host well-being. Many enteropathies are associated with increased gut permeability, including inflammatory bowel disease (IBD). Maintaining the barrier function of the epithelium, independent of whether paracellular or transcellular permeation pathways are considered, is an energy-dependent process. Here we present an overview of the impact that metabolic stress (e.g., reductions in epithelial ATP synthesis) can have on permeability characteristics of epithelial monolayers and show that metabolic stress in the presence of a commensal flora results in a significant loss of epithelial integrity, and that this increase in epithelial permeability can be enhanced by the presence of tumor necrosis factor-alpha (TNFalpha). We speculate that the combination of these factors in vivo would result in significant perturbations in epithelial barrier function that could be of pathophysiological significance and contribute to the initiation of IBD or the induction of disease relapses.

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 score0.002
Threshold uncertainty score0.008

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 studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.090
GPT teacher head0.379
Teacher spread0.289 · 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

Citations39
Published2009
Admission routes2
Has abstractyes

Explore more

Same venueAnnals of the New York Academy of Sciences→Same topicGut microbiota and health→French-language works237,207→