7 H -benzo[ c ]fluorene: a major DNA adduct-forming component of coal tar
Bibliographic record
Abstract
Coal tar is a complex mixture that exhibits high carcinogenic potency in lungs of animals when administered in the diet. Studies have noted that lung tumor induction does not correlate with the benzo[a]pyrene content of coal tar, suggesting that other hydrocarbons may be involved in the observed tumorigenicity. Our previous studies have demonstrated that a major 'unknown' chemical-DNA adduct is formed in the lung of mice exposed to coal tar. We have used an in vitro rat microsomal activation system to generate the 'unknown' adduct with neat coal tar and fractions of coal tar obtained by chemical fractionation and HPLC. Chemical-DNA adduct formation was evaluated by (32)P-postlabeling using both multi-dimensional TLC and HPLC. GC-MS analysis of the coal tar fractions obtained from HPLC, which produced the 'unknown' adduct in vitro, demonstrated that the adducting hydrocarbon had a mass of 216. A careful evaluation of candidate hydrocarbons led to the conclusion that a benzofluorene derivative may be responsible for forming the 'unknown' chemical-DNA adduct. Comparative in vitro and in vivo studies on the adducting properties of all three isomers of benzofluorene indicated that 7H-benzo[c]fluorene is responsible for producing the 'unknown' adduct observed in the lung of mice ingesting coal tar. Animal feeding studies also demonstrated that 7H-benzo[c]fluorene formed considerably more lung DNA adducts than 11H-benzo[a]fluorene and 11H-benzo[b]fluorene. These data indicate that the four-ring polycyclic aromatic hydrocarbon 7H-benzo[c]fluorene, a hydrocarbon not previously shown to form DNA adducts in lung, is in fact a potent lung DNA adductor and is a candidate PAH for causing lung tumors in animals treated with coal tar.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.028 | 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; both teacher heads agree on what is shown here.
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".