Hepatocyte-Specific Deletion of TIPARP, a Negative Regulator of the Aryl Hydrocarbon Receptor, Is Sufficient to Increase Sensitivity to Dioxin-Induced Wasting Syndrome
Bibliographic record
Abstract
The aryl hydrocarbon receptor (AHR) mediates the toxic effects of dioxin (2, 3, 7, 8-tetrachlorodibenzo-p-dioxin; TCDD), which includes thymic atrophy, steatohepatitis, and a lethal wasting syndrome in laboratory rodents. Although the mechanisms of dioxin toxicity remain unknown, AHR signaling in hepatocytes is necessary for dioxin-induced liver toxicity. We previously reported that loss of TCDD-inducible poly(adenosine diphosphate [ADP]-ribose) polymerase (TIPARP/PARP7/ARTD14), an AHR target gene and mono-ADP-ribosyltransferase, increases the sensitivity of mice to dioxin-induced toxicities. To test the hypothesis that TIPARP is a negative regulator of AHR signaling in hepatocytes, we generated Tiparpfl/fl mice in which exon 3 of Tiparp is flanked by loxP sites, followed by Cre-lox technology to create hepatocyte-specific (Tiparpfl/flCreAlb) and whole-body (Tiparpfl/flCreCMV; TiparpEx3-/-) Tiparp null mice. Tiparpfl/flCreAlb and TiparpEx3-/- mice given a single injection of 10 μg/kg dioxin did not survive beyond days 7 and 9, respectively, while all Tiparp+/+ mice survived the 30-day treatment. Dioxin-exposed Tiparpfl/flCreAlb and TiparpEx3-/- mice had increased steatohepatitis and hepatotoxicity as indicated by greater staining of neutral lipids and serum alanine aminotransferase activity than similarly treated wild-type mice. Tiparpfl/flCreAlb and TiparpEx3-/- mice exhibited augmented AHR signaling, denoted by increased dioxin-induced gene expression. Metabolomic studies revealed alterations in lipid and amino acid metabolism in liver extracts from Tiparpfl/flCreAlb mice compared with wild-type mice. Taken together, these data illustrate that TIPARP is an important negative regulator of AHR activity, and that its specific loss in hepatocytes is sufficient to increase sensitivity to dioxin-induced steatohepatitis and lethality.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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; 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".