Disinfection Byproducts Confirmed over 50 Years: Systematic Curation, Modes of Toxic Action, and Toxicogenomics
Bibliographic record
Abstract
Research on water disinfection byproducts (DBPs) over the past 50 years has unveiled more than 700 DBPs, many of which pose unrecognized risks to human health. Despite significant progress, systematic integration of the chemical curation of the confirmed DBPs with emerging toxicological paradigms is missing. This review systematically curates 716 confirmed DBPs reported from 1974 to 2024, offering a comprehensive resource to support risk identification and prioritization. We introduce a multiple classification framework based on molecular scaffolds, functional groups, and halogenation patterns, enabling researchers to map structural diversity to toxicological profiles. The modes of action applied in DBP research outlined here include nonspecific baseline toxicity, receptor- or enzyme-specific interactions, and reactive mechanisms such as oxidative stress and genotoxicity. Furthermore, we provide a system-level toxicogenomic view of DBP-induced toxicity, which has progressed from static single- and multiomics approaches to emerging time-resolved omics. These approaches reveal DBP-induced perturbations: the genome defines susceptibility, the transcriptome reflects expression levels, the proteome indicates functional execution, and the metabolome captures phenotypic outcomes. This review underscores critical knowledge gaps while charting future directions for DBP risk assessment and regulation and supports global efforts toward clean and safe drinking water.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".