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Record W2240173975 · doi:10.1111/bcp.12885

Mechanism of isoniazid‐induced hepatotoxicity: then and now

2016· review· en· W2240173975 on OpenAlexafffund
Imir G. Metushi, Jack Uetrecht, Elizabeth Phillips

Bibliographic record

VenueBritish Journal of Clinical Pharmacology · 2016
Typereview
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicDrug-Induced Hepatotoxicity and Protection
Canadian institutionsUniversity of Toronto
FundersUniversity of California, San DiegoCanada Research Chairs
KeywordsIdiosyncrasyLiver injuryIsoniazidMetaboliteImmune systemDrugMedicineMechanism (biology)Liver failurePhenotypePharmacologyTuberculosisImmunologyBiologyInternal medicinePathologyBiochemistryGene

Abstract

fetched live from OpenAlex

Isoniazid (INH) remains a mainstay for the treatment of tuberculosis despite the fact that it can cause liver failure. Previous mechanistic hypotheses have classified this type of drug-induced liver injury (DILI) as 'metabolic idiosyncrasy' which was thought not to involve an immune response and was mainly due to the bioactivation of the acetylhydrazine metabolite. However, more recent studies support an alternative hypothesis, specifically, that INH itself is directly bioactivated to a reactive metabolite, which in some patients leads to an immune response and liver injury. Furthermore, there appear to be two phenotypes of INH-induced liver injury. Most cases involve mild liver injury, which resolves with immune tolerance, while other cases appear to have a more severe phenotype that is associated with the production of anti-drug/anti-CYP P450 antibodies and can progress to liver failure.

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 score0.003
Threshold uncertainty score0.011

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 studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.327
GPT teacher head0.546
Teacher spread0.219 · 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

Citations216
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueBritish Journal of Clinical PharmacologySame topicDrug-Induced Hepatotoxicity and ProtectionFrench-language works237,207