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Record W2497999703 · doi:10.1007/978-1-59745-350-9_14

Cytokines and Pharmacokinetic Drug Interactions

2007· book-chapter· en· W2497999703 on OpenAlexaff
Kenneth W. Renton

Bibliographic record

VenueMethods in pharmacology and toxicology · 2007
Typebook-chapter
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmacogenetics and Drug Metabolism
Canadian institutionsDalhousie University
Fundersnot available
KeywordsCytokineCytochrome P450InflammationTumor necrosis factor alphaTranscription factorBiologyDrugProinflammatory cytokineInterleukinImmunologyPharmacologyEnzymeGeneBiochemistry

Abstract

fetched live from OpenAlex

The expression of cytochrome P450 and P-glycoprotein is altered during the operation of host defense mechanisms. The basis for this interaction is predominantly through cytokine-mediated pathways. Most of the major cytokines, including interleukin (IL)-1α, IL-1β, IL-2β, IL-6, tumor necrosis factor-α, inteferon-α, inteferon-γ, and transforming growth factor-β, are known to downregulate the major forms of cytochrome P450 and P-glycoprotein. In most cases individual cytochrome P450 forms are downregulated at the level of gene transcription, with a resulting decrease in the corresponding messenger ribonucleic acid, protein, and enzyme activity. The cytokine-mediated loss in drug metabolism is channeled predominantly through the modification of specific transcription factors. Similar pathways appear to alter the expression of P-glycoprotein. In clinical medicine, there are numerous examples of a decreased capacity to handle drugs during infections and disease states that involve an inflammatory component and the production of cytokines. The direct administration of cytokines to humans depresses the levels of several cytochrome P450-mediated pathways. The production of cytokines in humans often results in altered drug responses and increased toxicities, which has major implications in inflammation and infection when the capacity of the liver and other organs to handle drugs is severely compromised. Changes in drug-handling capacity during inflammation/infection will continue to be one of the many factors that complicate therapeutics.

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 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)0.004
metaresearch head score (Gemma)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.915
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.005
Insufficient payload (model declined to judge)0.0100.000

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 head0.180
GPT teacher head0.534
Teacher spread0.354 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Citations5
Published2007
Admission routes1
Has abstractyes

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