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Record W2965251010 · doi:10.1016/j.jhepr.2019.04.004

The role of the gut microbiome in chronic liver disease: the clinical evidence revised

2019· review· en· W2965251010 on OpenAlexaff
Katherine J. P. Schwenger, Nayima M. Clermont‐Dejean, Johane P. Allard

Bibliographic record

VenueJHEP Reports · 2019
Typereview
Languageen
FieldMedicine
TopicLiver Disease Diagnosis and Treatment
Canadian institutionsToronto General HospitalUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsIntestinal permeabilityIntestinal MicrobiomeMicrobiomePathogenesisLiver diseaseGut floraDiseaseGut microbiomeFatty liverChronic liver diseaseImmunologyBiologyInflammatory bowel diseaseInflammationMedicineGastroenterologyBioinformaticsInternal medicineCirrhosis

Abstract

fetched live from OpenAlex

Recent research has suggested a role for the intestinal microbiota in the pathogenesis and potential treatment of a wide range of liver diseases. The intestinal microbiota and bacterial products may contribute to the development of liver diseases through multiple mechanisms including increased intestinal permeability, chronic systemic inflammation, production of short-chain fatty acids and changes in metabolism. This suggests a potential role for pre-, pro- and synbiotic products in the prevention or treatment of some liver diseases. In addition, there is emerging evidence on the effects of faecal microbial transplant. Herein, we discuss the relationship between the intestinal microbiota and liver diseases, as well as reviewing intestinal microbiota-based treatment options that are currently being investigated.

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)0.003
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 score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.096
GPT teacher head0.409
Teacher spread0.313 · 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

Citations169
Published2019
Admission routes1
Has abstractyes

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