In Vitro and In Vivo Assessment of Renal Drug Transporters in the Disposition of Mesna and Dimesna
Bibliographic record
Abstract
Mesna and its dimer, dimesna, are coadministered for mitigation of ifosfamide- and cisplatin-induced toxicities, respectively. Dimesna is selectively reduced to mesna in the kidney, producing its protective effects. In vitro screens of uptake and efflux transporters revealed saturable uptake by renal organic anion transporters OAT1, OAT3, and OAT4. Efflux transporters breast cancer resistance protein; multidrug and toxin extrusion 1 (MATE1); multidrug resistance proteins MRP1, MRP2, MRP4, and MRP5; and P-glycoprotein (Pgp) significantly reduced dimesna accumulation. Further investigation demonstrated that renal apical efflux transporters MATE1, MRP2, and Pgp were also capable of mesna efflux. Administration of OAT inhibitor probenecid to healthy subjects significantly increased combined mesna and dimesna plasma exposure (91% ± 34%) while decreasing the renal clearance due to net secretion (67.0% ± 12.7%) and steady-state volume of distribution (45.2% ± 13.4%). Thus, the kidney represents a significant sink of total mesna, whereas function of renal drug transporters facilitates clearance in excess of glomerular filtration rate and likely the presence of active mesna in the urine. Loss of renal transporter function due to genetic variability or drug-drug interactions may decrease the efficacy of chemoprotectants, increasing the risk of ifosfamide- and cisplatin-induced toxicities.
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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 | 0.001 | 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) | 0.002 | 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".