Consequences of reprogramming acetyl-CoA metabolism by 2,3,7,8-tetrachlorodibenzo-p-dioxin in the mouse liver
Bibliographic record
Abstract
2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD) is a persistent environmental contaminant that induces the progression of steatosis to steatohepatitis with fibrosis in mice. Furthermore, TCDD reprograms hepatic metabolism by redirecting glycolytic intermediates while inhibiting lipid metabolism. Here, we examined the effect of TCDD on hepatic acetyl-coenzyme A (acetyl-CoA) and β-hydroxybutyrate levels as well as protein acetylation and β-hydroxybutyrylation. Acetyl-CoA is not only a central metabolite in multiple anabolic and catabolic pathways, but also a substrate used for posttranslational modification of proteins and a surrogate indicator of cellular energy status. Targeted metabolomic analysis revealed a dose-dependent decrease in hepatic acetyl-CoA levels coincident with the phosphorylation of pyruvate dehydrogenase (E1), and the induction of pyruvate dehydrogenase kinase 4 and pyruvate dehydrogenase phosphatase, while repressing ATP citrate lyase and short-chain acyl-CoA synthetase gene expression. In addition, TCDD dose-dependently reduced the levels of hepatic β-hydroxybutyrate and repressed ketone body biosynthesis gene expression. Moreover, levels of total hepatic protein acetylation and β-hydroxybutyrylation were reduced. AMPK phosphorylation was induced consistent with acetyl-CoA serving as a cellular energy status surrogate, yet subsequent targets associated with re-establishing energy homeostasis were not activated. Collectively, TCDD reduced hepatic acetyl-CoA and β-hydroxybutyrate levels eliciting starvation-like conditions despite normal levels of food intake.
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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 | 0.000 |
| 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 | 0.000 |
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".