Effects of Rifampicin, Dexamethasone, St. John's Wort and Thyroxine on Maternal and Foetal Expression of Abcb1 and Organ Distribution of Talinolol in Pregnant Rats
Bibliographic record
Abstract
It is well accepted that ABCB1 plays a critical role in absorption, distribution and elimination of many xenobiotics and drugs. Only little is known about the regulation and function of ABCB1 during pregnancy. Thus, the aim of this study is to investigate maternal, placental and foetal Abcb1 expression and function in pregnant rats after induction with rifampicin, dexamethasone, St. John's wort (SJW) or thyroxine. Wistar rats were orally treated with rifampicin (250 mg/kg), SJW (1.0 g/kg), thyroxine (9 μg/kg), dexamethasone (1 mg/kg) or 0.5% methylcellulose suspension (control) for 9 days during late pregnancy (each N = 5). Afterwards, organ mRNA expression and protein content of Abcb1a were determined. Tissue concentrations of the ABCB1 probe drug talinolol were measured after repeated administration of the drug (100 mg/kg, 9 days) and after induction with oral rifampicin (250 mg/kg, 9 days, N = 5). Abcb1 expression was substantially lower in foetal than in maternal organs. Abcb1 was significantly induced by SJW in the maternal jejunum and placenta, by dexamethasone in foetal brain and liver and by thyroxine in the placenta and maternal and foetal brain. Rifampicin induced Abcb1 in all maternal and foetal organs. However, organ distribution of talinolol was not influenced by comedication of rifampicin. In conclusion, maternal and foetal Abcb1 organ expression in pregnant rats is inducible by nuclear receptor agonists. Although rifampicin regulates maternal and foetal Abcb1 expression, organ distribution of talinolol remains unchanged most likely caused by the known inhibitory effect of rifampicin on Abcb1 function.
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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 | 0.001 | 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 | 0.001 |
| 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".