Toxicokinetics of Brominated Azo Dyes in the Early Life Stages of Zebrafish (<i>Danio rerio</i>) Is Prone to Aromatic Substituent Changes
Bibliographic record
Abstract
Abstract Brominated azo dyes (BADs) have been identified as predominant indoor brominated pollutants in daycare dust; thus, their potential health risk to children is of concern. However, the toxicities of BADs remain elusive. In this study, the toxicokinetics of two predominant BADs, Disperse Blue 373 (DB373) and Disperse Violet 93 (DV93), and their suspect metabolite 2-bromo-4,6-dinitroaniline (BDNA) was investigated in embryos of zebrafish (Danio rerio). The bioconcentration factor of DV93 at 120 hpf is 6.2-fold lower than that of DB373. The nontarget analysis revealed distinct metabolism routes between DB373 and DV93 by reducing nitro groups to nitroso (DB373) or amine (DV93), despite their similar structures. NAD(P)H quinone oxidoreductase 1 (NQO1) and pyruvate dehydrogenase were predicted as the enzymes responsible for the reduction of DB373 and DV93 by correlating time courses of the metabolites and enzyme development. Further in vitro recombinant enzyme and in vivo inhibition results validated NQO1 as the enzyme specifically reducing DB373, but not DV93. Global proteome profiling revealed that the expression levels of proteins from the “apoptosis-induced DNA fragmentation” pathway were significantly upregulated by all three BADs, supporting the bioactivation of BADs to mutagenic aromatic amines. This study discovered the bioactivation of BADs via distinct eukaryotic enzymes, implying their potential health risks.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".