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Record W2240173975 · doi:10.1111/bcp.12885

Mechanism of isoniazid‐induced hepatotoxicity: then and now

2016· review· en· W2240173975 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.
fundA Canadian funder is recorded on the work.

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.

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)0.009
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.986
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0020.000

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 head0.327
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