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Record W2585183403 · doi:10.1139/cjpp-2017-0014

Downregulation of cytochrome P450 2C8 by 3-methylcholanthrene in human hepatocellular carcinoma cell lines

2017· article· en· W2585183403 on OpenAlexafffundvenue
Rucha Utgikar, David S. Riddick

Bibliographic record

VenueCanadian Journal of Physiology and Pharmacology · 2017
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmacogenetics and Drug Metabolism
Canadian institutionsUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsDownregulation and upregulationCytochrome P450Cell cultureMethylcholanthreneHepatocyteHepatocellular carcinomaCYP2C8BiologyMessenger RNAChemistryCancer researchCell biologyCarcinogenEndocrinologyMetabolismIn vitroBiochemistryGeneCYP2C9Genetics

Abstract

fetched live from OpenAlex

The marked induction of cytochromes P450 such as CYP1A1 caused by polycyclic aromatic hydrocarbons (PAHs) like 3-methylcholanthrene (MC) is often accompanied by suppression of other hepatic P450s. The molecular mechanisms, functional consequences, and human relevance of P450 downregulation by PAHs are poorly understood. MC suppresses mRNA levels for CYP2C8, an important human P450, in cultured human hepatocytes. To avoid hepatocyte lot-to-lot variability, we assessed CYP2C8 regulation by MC in HepaRG cells, a terminally differentiated human hepatocellular carcinoma cell line that maintains high P450 expression. MC strongly induced CYP1A1 mRNA levels and markedly downregulated CYP2C8 mRNA levels in HepaRG cells. Although MC also suppressed CYP2C8 mRNA levels in the HepG2 human hepatocellular carcinoma cell line, basal CYP2C8 expression was extremely low. HepaRG cells appear to be an appropriate model system for studying the mechanisms and functional consequences of CYP2C8 downregulation by PAHs.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.061
GPT teacher head0.380
Teacher spread0.319 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations1
Published2017
Admission routes3
Has abstractyes

Explore more

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