Human MRP2 polymorphisms and their impact on substrate transport
Bibliographic record
Abstract
Multidrug resistance protein 2 (MRP2/ABCC2) mediates the biliary excretion of endo‐ and xenobiotic organic anion conjugates. Single nucleotide polymorphisms (SNPs) in the MRP2 gene contribute to variability in drug response and adverse effects between individuals and different ethnic populations. We characterized the transport of wild type MRP2 (WT) and two MRP2 SNP variants, M4 (A1450T) and M5 (V417I) for the substrates LTC 4 (leukotrieneC4), E 2 3G (estradiol‐3‐glucuronide), TUDC (tauroursodeoxycholic acid) and E 2 17G (estradiol‐17β‐lucuronide) Methods : WT, M4 and M5 were expressed in Sf9 insect cells and kinetic parameters (K m , μM; V max , pmol/mg −1 .min −1 ; Hill coefficient [HC]) of ATP dependant transport of 3 H‐LTC 4 , 3 H‐E 2 3G, 3 H‐TUDC and 3 H‐E 2 17G determined in Sf9 plasma membrane vesicles. Transport activity of M4 and M5 was normalized to WT protein expression. Results Conclusion The SNP in the nucleotide‐binding domain of M4 decreased the V max by 50% for LTC 4 , E 2 3G and TUDC and decreased the HC for TUDC and E 2 17G. The SNP in the transmembrane domain 2 of M5 minimally influenced the V max , but increased the K m 2–3 fold, increased the HC for TUDC and decreased the HC for E 2 17G. (HD 58299)
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) | 0.000 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".