Quantification of the expression and inducibility of 12 rat cytochrome P450 isoforms by quantitative RT–PCR
Bibliographic record
Abstract
The administration of xenobiotics may significantly alter the expression of cytochromes P450 (CYPs), thereby leading to potentially toxic cellular, physiologic, and pharmacologic responses. Indeed, an important task in the development of new therapeutic entities is to evaluate efficiently and quantitatively their potential effects on the expression level of different CYPs. In this report, reverse transcriptase polymerase chain reaction (RT-PCR) was used to measure basal and induced mRNA of a wide range of rat CYP isoforms. Rats (n=3 per treatment) were treated with five prototype inducers of CYP isoforms or with vehicle only. RT and PCR efficiencies were determined using appropriate RNA and DNA standards. Messenger RNA was quantified by PicoGreen standard curves and normalized to cyclophilin. Quantitative RT-PCR was used successfully to demonstrate that CYP isoforms were induced at the mRNA level following drug administration. Notably, phenobarbital resulted in significant induction of CYP2B1, CYP2B2, CYP2C6, CYP2C13, CYP2E1, CYP3A1, and CYP3A2. 3-Methylcholanthrene induced CYP1A1, CYP1A2, and CYP1B1. CYP2C11 expression was highly variable and suppressed by pyridine, whereas the expression of CYP2E1 was suppressed by dexamethasone. We demonstrated that quantitative RT-PCR can be used to evaluate efficiently the effect of compounds on the expression of a wide range of CYP isoforms. The technique is advantageous over others in that it is very sensitive, efficient and applicable to highly homologous CYP isoforms.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".