Changes in gene expression induced by aromatic amine drugs: Testing the danger hypothesis
Why this work is in the frame
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Bibliographic record
Abstract
Virtually all drugs that contain a primary aromatic amine are associated with a high incidence of idiosyncratic drug reactions (IDRs), suggesting that this functional group has biological effects that may be used as biomarkers to predict IDR risk. Most IDRs exhibit evidence of immune involvement and the ability of aromatic amines to form reactive metabolites and redox cycle may be responsible for initiation of an immune response through induction of cell stress, as postulated by the Danger Hypothesis. If true, danger signals could be biomarkers of IDR risk. A previous attempt to test the Danger Hypothesis found that sulfamethoxazole (SMX), the only aromatic amine tested, was also the only drug not associated with an increase of cell stress genes in mice. To ensure that these observations were not species-specific, and to determine biomarkers of IDR risk common to aromatic amines, rats were treated with SMX and two other aromatic amine drugs, dapsone (DDS) and aminoglutethimide (AMG), and hepatic gene expression was determined using microarrays. As in mice, SMX induced minimal gene changes in the rat, and none indicated cell stress, whereas DDS and AMG induced several changes including up-regulation of enzymes such as aldo-keto reductase, glutathione-S-transferase, and aldehyde dehydrogenase, which may represent danger signals. Early insulin-induced hepatic gene (Eiih) was up-regulated by all three drugs. Some mRNA changes were observed in the Keap-1-Nrf2-ARE pathway; however, the pattern was significantly different for each drug. Overall, the most salient finding was that the changes in the liver were minimal, even though aromatic amines cause a high incidence of IDRs. The liver generates a large number of reactive species; however, the ability of aromatic amines to be bioactivated by cells of the immune system may be why they cause a high incidence of IDRs.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it