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Record W2167319215 · doi:10.3390/biom5032023

Alcoholic Liver Disease: Role of Cytokines

2015· review· en· W2167319215 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBiomolecules · 2015
Typereview
Languageen
FieldMedicine
TopicAlcohol Consumption and Health Effects
Canadian institutionsHealth Sciences CentreSunnybrook Health Science CentreUniversity of Toronto
Fundersnot available
KeywordsPathogenesisInflammationImmune systemAlcoholic liver diseaseLipopolysaccharideImmunologyProinflammatory cytokineTumor necrosis factor alphaChemokineKupffer cellMedicineBiologyCirrhosisInternal medicine

Abstract

fetched live from OpenAlex

The present review spans a broad spectrum of topics dealing with alcoholic liver disease (ALD), including clinical and translational research. It focuses on the role of the immune system and the signaling pathways of cytokines in the pathogenesis of ALD. An additional factor that contributes to the pathogenesis of ALD is lipopolysaccharide (LPS), which plays a central role in the induction of steatosis, inflammation, and fibrosis in the liver. LPS derived from the intestinal microbiota enters the portal circulation, and is recognized by macrophages (Kupffer cells) and hepatocytes. In individuals with ALD, excessive levels of LPS in the liver affect immune, parenchymal, and non-immune cells, which in turn release various inflammatory cytokines and recruit neutrophils and other inflammatory cells. In this review, we elucidate the mechanisms by which alcohol contributes to the activation of Kupffer cells and the inflammatory cascade. The role of the stellate cells in fibrogenesis is also discussed.

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.

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 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 score0.984
Threshold uncertainty score0.955

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.186
GPT teacher head0.442
Teacher spread0.256 · 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