Glucocorticoids and phenobarbital induce murine<i>CYP2B</i>genes by independent mechanisms
Bibliographic record
Abstract
BACKGROUND: Genes for CYP of the 2B subfamily (CYP2B genes) have long been known to be inducible in murine liver by phenobarbital and phenobarbital-like inducers. More recently, it has become clear that glucocorticoids can also induce these genes by a mechanism independent of that of phenobarbital-like inducers. OBJECTIVE: To summarize the evidence for the existence of two distinct molecular mechanisms for induction of murine CYP2B genes and to analyze the wider implications of this situation for inducible xenobiotic metabolism. METHODS: The mechanism of action of phenobarbital-like inducers of murine CYP2B genes is first briefly summarized. The role of glucocorticoids in the induction of various proteins, particularly rat phosphoenolpyruvate carboxykinase, where transcriptional activation is achieved via a glucocorticoid response unit, is also discussed. Finally, recent results are presented on glucocorticoid induction of murine CYP2B genes, including evidence for the presence of a functional glucocorticoid response unit in the rat CYP2B2 gene and for the role of constitutive androstane receptor as an accessory factor in this response. RESULTS/CONCLUSION: Murine CYP2B genes are seen to respond to two distinct regulatory mechanisms, but much remains to be learned concerning the interactions between these two regulatory loops, as well as the details of glucocorticoid induction.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.003 | 0.004 |
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.
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".