Malignant Transformation of Human Uroepithelial Cells Induced by Long-Term Exposure to a Disinfection Byproduct─2,6-Dichlorobenzoquinone
Bibliographic record
Abstract
Halobenzoquinones (HBQs), a class of water disinfection byproducts (DBPs), have emerged as potential bladder carcinogens. However, evidence regarding the long-term health effects of HBQ exposure and their potential to induce malignant transformation remains limited. Here, we examined the chronic effects of 2,6-dichlorobenzoquinone (2,6-DCBQ) exposure on human immortalized uroepithelial cells (SV-HUC-1), with a focus on malignant transformation. Cells were continuously exposed to a noncytotoxic concentration of 2,6-DCBQ for over three months. The long-term transformed cells exhibited cellular and nuclear pleomorphism and anchorage-independent cell growtha hallmark of cancer cell transformation. Proteomic analysis identified 60 differentially expressed proteins (DEPs), 20 of which are strongly associated with specific pathways of urinary bladder and urothelial cells. Enrichment analysis highlighted the actin cytoskeleton and extracellular matrix (ECM)-receptor interaction pathways. These molecular changes were supported by immunofluorescence assay, revealing filamentous actin disorganization and vinculin mislocalization in 2,6-DCBQ-treated cells. Together, these results suggest that cytoskeletal destabilization and adhesion collapse are key features associated with 2,6-DCBQ-induced malignant transformation, indicating that chronic exposure to low-level waterborne HBQs is associated with human bladder carcinogenesis.
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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 | 0.000 |
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".