Identification of Danger Signals in Nevirapine-Induced Skin Rash
Bibliographic record
Abstract
Nevirapine (NVP) can cause serious skin rashes and hepatotoxicity. It also causes an immune-mediated skin rash in rats but not hepatotoxicity. This rash is caused by a metabolite of NVP; specifically, NVP is oxidized in the liver to a benzylic alcohol (12-OH-NVP), which travels to the skin where it forms a reactive benzylic sulfate. This could both act as a hapten and induce a danger signal. In contrast, most of the covalent binding in the liver involves oxidation of the methyl group leading to a reactive quinone methide. In this study, we examined the effects of NVP and 12-OH-NVP on gene expression in the liver and skin. Both NVP and 12-OH-NVP induced changes in the liver, but the list of genes was different, presumably reflecting different bioactivation pathways. In contrast, many more genes were up-regulated in the skin by 12-OH-NVP than by NVP, which is consistent with the fact that 12-OH-NVP is an obligate intermediate in the formation of the reactive sulfate in the skin. Genes up-regulated by 12-OH-NVP in the skin included TRIM63 (18-fold increase), S100a7a (7-fold increase), IL22-RA2 (4-fold increase), and DAPK1 (3-fold increase). TRIM63 acts as a ubiquitin ligase, which is consistent with protein damage leading to an increase in protein turnover. In addition, TRIM proteins are involved in inflammasome activation, and it appears that inflammasome activation is an essential step in the induction of NVP-induced skin rash. S100A7 is considered a danger signal, and its upregulation supports the danger hypothesis. Upregulation of the IL-22 RA2 gene marks an immune response. DAPK1 is involved with inflammasome assembly through binding directly to NLRP3, a NOD-like receptor expressed in keratinocytes. These results provide important clues to how NVP causes the induction of an immune response, in this case leading to skin rash.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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; 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".