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Record W2002724414 · doi:10.1097/mcg.0b013e31816d922c

Understanding Why Probiotic Therapies Can be Effective in Treating IBD

2008· review· en· W2002724414 on OpenAlexaff
Richard N. Fedorak

Bibliographic record

VenueJournal of Clinical Gastroenterology · 2008
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicProbiotics and Fermented Foods
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineInflammatory bowel diseasePathogenesisImmune systemImmunologyProbioticInflammationMucusDiseaseBarrier functionGut floraMechanism (biology)BiologyInternal medicineBacteria

Abstract

fetched live from OpenAlex

Probiotics, for the treatment of inflammatory bowel disease, are a group of specific nonpathogenic bacteria that are functionally and genetically defined by their ability to reduce inflammation in the intestine. Although probiotics also seem to have broad beneficial effects in humans, both as a food and as a therapeutic agent, there are specific identified mechanisms in some, but not all, of these bacteria that are important relative to the pathogenesis of inflammatory bowel disease. Recently, studies relative to the mechanism of action of probiotics have identified that these organisms can have a direct effect on epithelial cell function and intestinal health, including enhancing epithelial barrier function, modulating epithelial cytokine secretion into an anti-inflammatory dominant profile, altering mucus production, changing bacterial luminal flora, modifying the innate and systemic immune system, and inducing regulatory T-cell effects. For probiotics to have a therapeutic role in the management of clinical inflammatory bowel disease, their therapeutic mechanism of action must be aligned with the pathogenic mechanism of action of the disease. In this regard, the role of probiotics for the clinical treatment of inflammatory bowel disease is emerging as the mechanisms and pathogenesis are being unraveled. It remains clear that probiotics are able to reduce gastrointestinal inflammation by exerting positive effects on epithelial cell and mucosal immune dysfunction.

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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.977
Threshold uncertainty score0.618

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.219
GPT teacher head0.375
Teacher spread0.155 · 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 designOther design
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

Citations42
Published2008
Admission routes1
Has abstractyes

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