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Record W2299136399 · doi:10.1016/s0741-8329(02)00211-2

Cellular and molecular mechanisms of alcoholic hepatitis

2002· review· en· W2299136399 on OpenAlexaboutno aff
Vishnudutt Purohit, Denise Hage Russo

Bibliographic record

VenueAlcohol · 2002
Typereview
Languageen
FieldMedicine
TopicAlcohol Consumption and Health Effects
Canadian institutionsnot available
Fundersnot available
KeywordsAlcoholic hepatitisAlcoholic liver diseaseHepatitisMedicineViral hepatitisLiver injuryCirrhosisPathogenesisChemokineImmunologyParenchymaLiver cellHepatitis CPathologyInflammationInternal medicine

Abstract

fetched live from OpenAlex

The National Institute on Alcohol Abuse and Alcoholism and the Office of Rare Diseases, National Institutes of Health, sponsored a satellite symposium on "Cellular and Molecular Mechanisms of Alcoholic Hepatitis" at the 24th Annual Scientific Meeting of the Research Society on Alcoholism, Montreal, Quebec, Canada, June 2001. Alcohol intake is a major cause of hepatitis that may lead to alcoholic cirrhosis-a major cause of death in the United States. In up to one third of heavy drinkers alcoholic hepatitis develops, which is characterized by liver cell death and infiltration of leukocytes in hepatic parenchyma. Although leukocytes have been implicated in the pathogenesis of alcoholic hepatitis, the underlying cellular and molecular mechanisms by which leukocytes migrate to hepatic parenchyma and initiate tissue injury are not clear. For this symposium, 10 speakers were invited to address the following aspects of the mechanisms of alcoholic hepatitis: role of Kupffer cells in initiating the process of alcoholic hepatitis; types of leukocytes involved in the pathogenesis of alcoholic hepatitis; chemokines that are responsible for the attraction of leukocytes; adhesion molecules that promote the attachment of leukocytes to the endothelial cells and hepatocytes; mechanisms of leukocyte transmigration to hepatic parenchyma; mechanisms by which leukocytes initiate tissue injury; and interactive effects of alcohol and hepatitis viral proteins on liver injury. This article provides an introduction to the problem and a summary of the 10 scientific presentations delivered at the symposium.

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 score0.006

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)0.0020.001

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 head0.124
GPT teacher head0.388
Teacher spread0.264 · 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

Citations26
Published2002
Admission routes1
Has abstractyes

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