Characterization and Biological Potency of Mono- to Tetra-Halogenated Carbazoles
Bibliographic record
Abstract
This paper deals with the characterization and aryl hydrocarbon receptor (AhR) agonist activities of a series of chlorinated, brominated, and mixed bromo/chlorocarbazoles, some of which have been identified in various environmental samples. Attention is directed here to the possibility that halogenated carbazoles may currently be emitted into the environment as a result of the production of carbazole-containing polymers present in a wide variety of electronic devices. We have found that any carbazole that is not substituted in the 1,3,6,8 positions may be lost during cleanup of environmental extracts if a multilayer column is utilized, as is common practice for polychlorinated dibenzo-p-dioxin (dioxin) and related compounds. In the present study, (1)H NMR spectral shift data for 11 relevant halogenated carbazoles are reported, along with their gas chromatographic separation and analysis by mass spectrometry. These characterization data allow for confident structural assignments and the derivation of possible correlations between structure and toxicity based on the halogenation patterns of the isomers investigated. Some halogenated carbazoles exhibit characteristics of persistent organic pollutants and their potential dioxin-like activity was further investigated. The structure-dependent induction of CYP1A1 and CYP1B1 gene expression in Ah-responsive MDA-MB-468 breast cancer cells by these carbazoles was similar to that observed for other dioxin-like compounds, and the magnitude of the fold induction responses for the most active halogenated carbazoles was similar to that observed for 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD). 2,3,6,7-Tetrachlorocarbazole was one of the most active halogenated carbazoles and, like TCDD, contains 4 lateral substituents; however, the estimated relative effect potency for this compound (compared to TCDD) was 0.0001 and 0.0032, based on induction of CYP1A1 and CYP1B1 mRNA, respectively.
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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".