Loss of the Mono-ADP-ribosyltransferase, Tiparp, Increases Sensitivity to Dioxin-induced Steatohepatitis and Lethality
Bibliographic record
Abstract
The aryl hydrocarbon receptor (AHR) mediates the toxic effects of the environmental contaminant dioxin (2,3,7,8-tetrachlorodibenzo-p-dioxin; TCDD). Dioxin causes a range of toxic responses, including hepatic damage, steatohepatitis, and a lethal wasting syndrome; however, the mechanisms are still unknown. Here, we show that the loss of TCDD-inducible poly(ADP-ribose) polymerase (Tiparp), an ADP-ribosyltransferase and AHR repressor, increases sensitivity to dioxin-induced toxicity, steatohepatitis, and lethality. Tiparp(-/-) mice given a single injection of 100 μg/kg dioxin did not survive beyond day 5; all Tiparp(+/+) mice survived the 30-day treatment. Dioxin-treated Tiparp(-/-) mice exhibited increased liver steatosis and hepatotoxicity. Tiparp ADP-ribosylated AHR but not its dimerization partner, the AHR nuclear translocator, and the repressive effects of TIPARP on AHR were reversed by the macrodomain containing mono-ADP-ribosylase MACROD1 but not MACROD2. These results reveal previously unidentified roles for Tiparp, MacroD1, and ADP-ribosylation in AHR-mediated steatohepatitis and lethality in response to dioxin.
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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 | 0.001 |
| 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".