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Record W2104585553 · doi:10.1503/jpn.120133

Cytochrome P450–mediated drug metabolism in the brain

2013· review· en· W2104585553 on OpenAlexafffundvenue
Sharon Miksys, Rachel F. Tyndale

Bibliographic record

VenueJournal of Psychiatry and Neuroscience · 2013
Typereview
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmacogenetics and Drug Metabolism
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
FundersNational Institute on Drug AbuseCanadian Institutes of Health Research
KeywordsDrug metabolismCytochrome P450DrugPharmacologyMetabolismCYP2D6MedicineNeuroscienceBiologyInternal medicine

Abstract

fetched live from OpenAlex

Cytochrome P450 enzymes (CYPs) metabolize many drugs that act on the central nervous system (CNS), such as antidepressants and antipsychotics; drugs of abuse; endogenous neurochemicals, such as serotonin and dopamine; neurotoxins; and carcinogens. This takes place primarily in the liver, but metabolism can also occur in extrahepatic organs, including the brain. This is important for CNS-acting drugs, as variation in brain CYP-mediated metabolism may be a contributing factor when plasma levels do not predict drug response. This review summarizes the characterization of CYPs in the brain, using examples from the CYP2 subfamily, and discusses sources of variation in brain CYP levels and metabolism. Some recent experiments are described that demonstrate how changes in brain CYP metabolism can influence drug response, toxicity and drug-induced behaviours. Advancing knowledge of brain CYP-mediated metabolism may help us understand why patients respond differently to drugs used in psychiatry and predict risk for psychiatric disorders, including neurodegenerative diseases and substance abuse.

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 score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.004

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 head0.132
GPT teacher head0.456
Teacher spread0.324 · 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

Citations131
Published2013
Admission routes3
Has abstractyes

Explore more

Same venueJournal of Psychiatry and NeuroscienceSame topicPharmacogenetics and Drug MetabolismFrench-language works237,207