Glutathione-Mediated Detoxification of Halobenzoquinone Drinking Water Disinfection Byproducts in T24 Cells
Bibliographic record
Abstract
Halobenzoquinones (HBQs) are a new class of drinking water disinfection byproducts (DBPs) and are capable of producing reactive oxygen species and causing oxidative damage to proteins and DNA in T24 human bladder carcinoma cells. However, the exact mechanism of the cytotoxicity of HBQs is unknown. Here, we investigated the role of glutathione (GSH) and GSH-related enzymes including glutathione S-transferase (GST) and glutathione peroxidase (GPx) in defense against HBQ-induced cytotoxicity in T24 cells. The HBQs are 2,6-dichloro-1,4-benzoquinone (DCBQ), 2,6-dichloro-3-methyl-1,4-benzoquinone (DCMBQ), 2,3,6-trichloro-1,4-benzoquinone (TriCBQ), and 2,6-dibromobenzoquinone (DBBQ). We found that depletion of cellular GSH could sensitize cells to HBQs and extracellular GSH supplementation could attenuate HBQ-induced cytotoxicity. HBQs caused significant cellular GSH depletion and increased cellular GST activities in a concentration-dependent manner. Our mass spectrometry study confirms that HBQs can conjugate with GSH, explaining in part the mechanism of GSH depletion by HBQs. The effects of HBQs on GPx activity are compound dependent; DCMBQ and DBBQ decrease cellular GPx activities, whereas DCBQ and TriCBQ have no significant effects. Pearson correlation analysis shows that the cellular GSH level is inversely correlated with ROS production and cellular GST activity in HBQ-treated cells. These results support a GSH and GSH-related enzyme-mediated detoxification mechanism of HBQs in T24 cells.
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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 | 0.001 |
| 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 | 0.000 |
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".