Absence of both<scp>MDR</scp>1 (<scp>ABCB</scp>1) and Breast Cancer Resistance Protein (<scp>ABCG</scp>2) Transporters Significantly Alters Rivaroxaban Disposition and Central Nervous System Entry
Bibliographic record
Abstract
Rivaroxaban is a novel factor 10a inhibitor, where hepatic metabolism and renal clearance account for its overall disposition. Renal impairment is known to increase rivaroxaban-associated bleeding risk in patients. As renal rivaroxaban clearance exceeds glomerular filtration rate, we suggested that active secretion by efflux transporters P-glycoprotein (MDR1) and breast cancer resistance protein (BCRP) contributes to rivaroxaban clearance. The ability of MDR1 and BCRP efflux transporters to mediate rivaroxaban transport in vitro was assessed in polarized cell monolayers. A significantly greater vectorial transport of rivaroxaban was observed in the basal to apical direction in Caco-2 cells, which was attenuated in the presence of the selective inhibitors. After oral administration of rivaroxaban (2 mg/kg), plasma concentrations did not significantly differ between wild-type and Mdr1a(def) or Bcrp(-/-) mice (n = 6 per group). However, rivaroxaban clearance was significantly reduced in Mdr1a/Mdr1b(-/-)/Bcrp(-/-) mice. Interestingly, rivaroxaban brain-to-plasma ratio did not differ in mice lacking only Mdr1a or Bcrp, but more than two times higher in the Mdr1a/Mdr1b(-/-)/Bcrp(-/-) mice. Rivaroxaban is a shared substrate of MDR1 and BCRP. In vivo, MDR and BCRP function synergistically to modulate rivaroxaban disposition and appear to be particularly relevant to limiting its central nervous system entry. These data have important implications for safety and efficacy of anticoagulation therapy with rivaroxaban as many drugs in clinical use are known MDR1 inhibitors and loss-of-function polymorphisms in BCRP are common.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".