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Record W2072674441 · doi:10.2133/dmpk.dmpk-10-rv-085

Involvement of the Immune System in Idiosyncratic Drug Reactions

2010· review· en· W2072674441 on OpenAlexafffund
Xiachu Zhang, Feng Liu, Xin Chen, Xu Zhu, Jack Uetrecht

Bibliographic record

VenueDrug Metabolism and Pharmacokinetics · 2010
Typereview
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicDrug-Induced Hepatotoxicity and Protection
Canadian institutionsUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsImmune systemDrugMechanism (biology)BiologyLiver injuryMitochondrionImmunologyPharmacologyCell biology

Abstract

fetched live from OpenAlex

There is strong evidence that most idiosyncratic drug reactions (IDRs) are immune-mediated and are caused by reactive metabolites of a drug rather than by the drug itself. Several hypotheses have been proposed by which a drug could induce an immune response. The major hypotheses are the hapten hypothesis and the danger hypothesis; however, the characteristics and spectrum of IDRs are different with different drugs, and this likely reflects mechanistic differences; therefore, no one hypothesis is likely to explain all IDRs. Some IDRs appear to involve epigenetic effects, direct activation of antigen-presenting cells, or disturbing the normal balance of the immune system. It has been suggested that many cases of idiosyncratic liver injury are not immune-mediated, and other mechanisms such as mitochondrial injury may be involved. It is essential that any hypothesis be consistent with the clinical characteristics of the IDR. Although the characteristics of most idiosyncratic liver injury do not suggest that mitochondria are the major target, it is quite possible that milder mitochondrial injury could stimulate an immune-mediated reaction. The observation that IDRs can vary widely among different drugs and different patients is most easily explained by an immune mechanism in which the target of the immune response is different.

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)0.001
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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.089
GPT teacher head0.395
Teacher spread0.305 · 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

Citations51
Published2010
Admission routes2
Has abstractyes

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