Characterization of Arsenic Hepatobiliary Transport Using Sandwich-Cultured Human Hepatocytes
Bibliographic record
Abstract
Arsenic is a proven human carcinogen and is associated with a myriad of other adverse health effects. This metalloid is methylated in human liver to monomethylarsonic acid (MMA(V)), monomethylarsonous acid (MMA(III)), dimethylarsinic acid (DMA(V)), and dimethylarsinous acid (DMA(III)) and eliminated predominantly in urine. Hepatic basolateral transport of arsenic species is ultimately critical for urinary elimination; however, these pathways are not fully elucidated in humans. A potentially important human hepatic basolateral transporter is the ATP-binding cassette (ABC) transporter multidrug resistance protein 4 (MRP4/ABCC4) that in vitro is a high-affinity transporter of DMA(V) and the diglutathione conjugate of MMA(III) [MMA(GS)(2)]. In rats, the related canalicular transporter Mrp2/Abcc2 is required for biliary excretion of arsenic as As(GS)(3) and MMA(GS)(2). The current study used sandwich cultured human hepatocytes (SCHH) as a physiological model of human arsenic hepatobiliary transport. Arsenic efflux was detected only across the basolateral membrane for 9 out of 14 SCHH preparations, 5 had both basolateral and canalicular efflux. Basolateral transport of arsenic was temperature- and GSH-dependent and inhibited by the MRP inhibitor MK-571. Canalicular efflux was completely lost after GSH depletion suggesting MRP2-dependence. Treatment of SCHH with As(III) (0.1-1 µM) dose-dependently increased MRP2 and MRP4 levels, but not MRP1, MRP6, or aquaglyceroporin 9. Treatment of SCHH with oltipraz (Nrf2 activator) increased MRP4 levels and basolateral efflux of arsenic. In contrast, oltipraz increased MRP2 levels without increasing biliary excretion. These results suggest arsenic basolateral transport prevails over biliary excretion and is mediated at least in part by MRPs, most likely including MRP4.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".