The Unique Regulation of Brain Cytochrome P450 2 (CYP2) Family Enzymes by Drugs and Genetics
Bibliographic record
Abstract
Cytochrome P450 (CYP) enzymes in the brain may have a role in the activation or inactivation of centrally acting drugs, in the metabolism of endogenous compounds, and in the generation of damaging toxic metabolites and/or oxygen stress. CYPs are distributed unevenly among brain regions, and are found in neurons, glial cells and at the blood-brain interface. They have been observed in mitochondrial membranes, in neuronal processes and in the plasma membrane, as well as in endoplastic reticulum. Brain CYPs are inducible by many common hepatic inducers, however many compounds affect liver and brain CYP expression differently, and some CYPs which are constitutively expressed in liver are inducible in brain. CYP induction is isozyme-, brain region-, cell type- and inducer-specific. While it is unlikely that brain CYPs contribute to overall clearance of xenobiotics, their punctate, region- and cell-specific expression suggests that CNS CYPs may create micro-environments in the brain with differing drug and metabolite levels (not detected or predicted by plasma drug monitoring). Coupled with the sensitivity of CNS CYPs to induction, this may in part account for inter-individual variation in response to centrally acting drugs and neurotoxins, and may have implications for individual variation in receptor adaptation and cross-tolerance to different drugs. In addition, genetic variation in brain CYPs, depending on the type of polymorphism (structural versus regulatory), will alter enzyme activity. These aspects of brain CYP expression regulation and genetic influences are illustrated in this review using mRNA, protein, and enzyme activity data for CYP2D1/6, CYP2E1 and CYP2B1/6 in rat and human brain. The role of CYP-mediated metabolism in the brain, a highly heterogeneous and complex organ, is a new and relatively unexplored field of scientific enquiry. It holds promise for furthering our undestanding of inter-individual variability in response to centrally acting drugs as well as risk for neurological diseases and pathogies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".