Tissue Distribution and Gender-Divergent Expression of 78 Cytochrome P450 mRNAs in Mice
Bibliographic record
Abstract
Cytochrome P450 (Cyp) enzymes from the first four families (Cyp1-4) play a major role in metabolizing xenobiotics, affecting drug pharmacokinetics and chemical-induced toxicity. Due to cloning of the mouse genome, many novel Cyp isoforms have been identified, but their tissue distribution of expression is unknown. This study compared the tissue distribution of all 78 Cyps from the Cyp1-4 families in C57BL/6 mice providing not only an indication of which tissues novel Cyps may have their greatest importance but also a cohesive comparison of the tissue distribution of all Cyp1-4 isoforms. Transcripts of the 78 Cyps were quantified by multiplex suspension arrays and quantitative real-time PCR in 14 tissues. Hierarchical clustering indicated that in male mice, 52% of the Cyp species were expressed highest in liver, 10% in kidney, 10% in duodenum/jejunum, 10% in testes, 5% in lung, and < 4% in colon, brain, heart, and stomach. Female mice had a similar pattern of Cyp messenger RNA expression; however, compared with males, females had 7% more Cyps that were liver predominant, 2% more Cyps that were stomach predominant, but 1% less Cyps that were kidney and lung predominant. Differences in gender expression were observed in 29 of the Cyps, with 24 being higher in females than males. Additionally, the data suggest a correlation between the spatial arrangement of genes within a gene cluster and their organ-predominant expression, indicating a common regulatory mechanism may be present within these clusters. In conclusion, this study provides novel data on the tissue distribution and gender-divergent expression of 78 functional mouse 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 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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".