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Chlorinated Methanes and Liver Injury: Highlights of the Past 50 Years

2000· review· en· W2157579438 on OpenAlexaff
Gàbriel L. Plaa

Bibliographic record

VenueThe Annual Review of Pharmacology and Toxicology · 2000
Typereview
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicDrug-Induced Hepatotoxicity and Protection
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsCarbon tetrachlorideHexobarbitalSteatosisLiver injuryBiotransformationAdverse Outcome PathwayLipid peroxidationCirrhosisChemistryEndoplasmic reticulumLong-term potentiationBiochemistryPharmacologyMedicineMicrosomeBiologyInternal medicineOrganic chemistryOxidative stressIn vitroEnzyme

Abstract

fetched live from OpenAlex

The chlorinated methanes, particularly carbon tetrachloride and chloroform, are classic models of liver injury and have developed into important experimental hepatoxicants over the past 50 years. Hepatocellular steatosis and necrosis are features of the acute lesion. Mitochondria and the endoplasmic reticulum as target sites are discussed. The sympathetic nervous system, hepatic hemodynamic alterations, and role of free radicals and biotransformation are considered. With carbon tetrachloride, lipid peroxidation and covalent binding to hepatic constituents have been dominant themes over the years. Potentiation of chlorinated methane-induced liver injury by alcohols, aliphatic ketones, ketogenic compounds, and the pesticide chlordecone is discussed. A search for explanations for the potentiation phenomenon has led to the discovery of the role of tissue repair in the overall outcome of liver injury. Some final thoughts about future research are also presented.

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)0.001
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 score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.004
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.002

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 head0.086
GPT teacher head0.435
Teacher spread0.349 · 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

Citations82
Published2000
Admission routes1
Has abstractyes

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