Multidrug Resistance Protein 4 (MRP4/ABCC4) Protects Cells from the Toxic Effects of Halobenzoquinones
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Halobenzoquinones (HBQs) are frequently detected disinfection byproducts (DBPs) in treated water. Recent studies have demonstrated that HBQs are highly cytotoxic and capable of inducing the generation of reactive oxygen species (ROS) and depleting cellular glutathione (GSH). Multidrug resistance proteins (MRPs/ABCCs) are known to play a critical role in the elimination of numerous drugs, carcinogens, toxicants, and their conjugated metabolites. In general, little is known about the roles of transporters in DBP toxicity. Here, we hypothesize that MRPs may play roles in the detoxication of HBQs. To test this hypothesis, we used human embryonic kidney 293 (HEK293) cells stably expressing MRPs (MRP1, 3, 4, and 5) and HEK293 cells with empty vector (HEK-V) to examine the comparative cytotoxicity of four HBQs: 2,6-dichloro-1,4-benzoquinone (2,6-DCBQ), 2,6-dibromo-1,4-benzoquinone (2,6-DBBQ), 2,6-dichloro-3-methyl-1,4-benzoquinone (DCMBQ), and 2,3,6-trichloro-1,4-benzoquinone (TriCBQ). The cytotoxicity (IC 50 ) of the four HBQs in HEK-MRP1, -MRP3, -MRP4, and -MRP5 cells and the control HEK-V cells clearly showed that MRP4 had the most significant effect on reducing the toxicity of the four HBQs. To further support MRP4-mediated detoxication of HBQs, we examined the HBQ-induced ROS levels in HEK-MRP4 and HEK-V cells. ROS levels were significantly reduced in HEK-MRP4 cells compared with HEK-V cells after HBQ treatment. Furthermore, it was found that MRP4-mediated detoxication of the HBQs was GSH dependent, as the cytotoxicity of the HBQs was increased in GSH-depleted HEK-MRP4 cells in comparison to HEK-MRP4 cells. The GSH-dependent protection of cells from HBQs supports the possibility of HBQ–GSH conjugate efflux by MRP4. This study demonstrates a role for MRP4 in cellular protection against HBQ DBP-induced toxicity and oxidative stress.
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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) | 0.002 | 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".