Real-Time Polymerase Chain Reaction Analysis of CYP1B1 Gene Expression in Human Liver
Bibliographic record
Abstract
Procarcinogen-activating cytochrome P450 (CYP) enzymes such as CYP1B1, CYP1A1, and CYP1A2 are considered to play an important role in chemical carcinogenesis. However, conflicting data exist with respect to CYP1B1 expression in human liver. In the present study, we measured CYP1B1 mRNA and protein expression in liver samples from 12 individuals (7 nonsmokers, 4 smokers, and 1 ex-smoker) and compared the levels to those of CYP1A1 and CYP1A2. As analyzed by real-time polymerase chain reaction, CYP1B1 mRNA was present in all samples and the inter-individual variability was 16-fold. The group mean level was 5-fold greater in smokers than nonsmokers (121 +/- 46 vs. 26 +/- 5 molecules/ng double-stranded DNA, p < 0.05). By comparison, CYP1A1 mRNA was detectable in samples from 4 of 7 nonsmokers, 3 of 4 smokers, and one ex-smoker, whereas CYP1A2 mRNA was detectable in samples from 5 nonsmokers, 4 smokers, and the ex-smoker. The mean levels of CYP1A1 and CYP1A2 mRNA were 4-fold and 9-fold greater, respectively, in smokers than nonsmokers, but the differences were not statistically significant. The inter-individual variability in CYP1A1 and CYP1A2 mRNA expression was 26-fold and 500-fold, respectively. Immunoblot analysis using several antibodies and with a larger panel (n = 27) of liver microsomes showed that CYP1A1 and CYP1B1 proteins were undetectable, whereas CYP1A2 was detectable in all samples and quantifiable in 24 of 27 samples. In summary, our novel finding indicates that CYP1B1 mRNA is expressed in human liver and the levels are increased in smokers, but the protein is undetectable.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".