Thin-Layer Chromatographic Analysis of Human CYP3A-Catalyzed Testosterone 6P-Hydroxylation
Bibliographic record
Abstract
At least two cytochromes P450 belonging to the CYP3A subfamily may be expressed in adult human liver ( 1 ), CYP3A4 and CYP3A5. A third enzyme, CYP3A7, is expressed in human fetal liver ( 2 ). The CYP3A enzymes account for an estimated ~30% of total human cytochrome P450 content in adult liver ( 3 ), although large inter-individual differences exist in hepatic CYP3A content. CYP3A4 is present in all adult human livers and is inducible by drugs such as rifampin (rifampicin) and dexamethasone ( 4 – 6 ). By contrast, CYP3A5 is expressed in only ~ 10-30% of liver samples ( 7 ) and does not respond to typical CYP3A inducers ( 5 , 6 ). Triacetyloleandomycin ( 8 , 9 ) and gestodene ( 9 ) are CYP3A-selective chemical inhibitors. Many commonly used drugs are substrates for CYP3A, including erythromycin ( 10 ), infedipine ( 11 ) and midazolam ( 12 ). Immunoinhibition experiments with CYP3A subfamily-specific antibodies have established several microsomal enzyme activities, including nifedipine oxidase ( 11 , 13 ) and testosterone 6β-hydroxylase ( 14 , 15 ), as useful catalytic monitors for hepatic CYP3A In a recent study, an inhibitory antipeptide antibody against CYP3A4, which did not cross-react with cDNA-expressed CYP3A5 as judged by Western-blot analysis and did not inhibit cDNA-expressed CYP3A5-catalyzed testosterone 6β-hydroxylation, was found to inhibit virtually all of the testosterone 6β-hydroxylase activity in human liver microsomes ( 16 ), suggesting that this activity has a high specificity for hepatic CYP3A4.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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.
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".