Effect of erythropoietin on hepatic cytochrome<scp>P</scp>450 expression and function in an adenine‐fed rat model of chronic kidney disease
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Erythropoietin (EPO) is used to treat anaemia associated with chronic kidney disease (CKD). Hypoxia is associated with anaemia and is known to cause a decrease in cytochrome P450 (P450) expression. As EPO production is regulated by hypoxia, we investigated the role of EPO on P450 expression and function. EXPERIMENTAL APPROACH: Male Wistar rats were subjected to a 0.7% adenine diet for 4 weeks to induce CKD. The diet continued for an additional 2 weeks while rats received EPO by i.p. injection every other day. Following euthanasia, hepatic P450 mRNA and protein expression were determined. Hepatic enzyme activity of selected P450s was determined and chromatin immunoprecipitation was used to characterize binding of nuclear receptors involved in the transcriptional regulation of CYP2C and CYP3A. KEY RESULTS: EPO administration decreased hepatic mRNA and protein expression of CYP3A2 (P < 0.05), but not CYP2C11. Similarly, EPO administration decreased CYP3A2 protein expression by 81% (P < 0.001). A 32% decrease (P < 0.05) in hepatic CYP3A enzymatic activity (Vmax ) was observed for the formation of 6βOH-testosterone in the EPO-treated group. Decreases in RNA pol II recruitment (P < 0.01), hepatocyte nuclear factor 4α binding (P < 0.05) and pregnane X receptor binding (P < 0.01) to the promoter region of CYP3A were also observed in EPO-treated rats. CONCLUSIONS AND IMPLICATIONS: Our data show that EPO decreases the expression and function of CYP3A, but not CYP2C in rat liver.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".