Dose-Dependent Metabolic Reprogramming and Differential Gene Expression in TCDD-Elicited Hepatic Fibrosis
Bibliographic record
Abstract
We have previously shown that in response to 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD)-elicited NAFLD progression, central carbon, glutaminolysis, and serine/folate metabolism are reprogrammed to support NADPH production and ROS defenses. To further investigate underlying dose-dependent responses associated with TCDD-induced fibrosis, female C57BL/6 mice were gavaged with TCDD every 4 days (d) for 28 d or 92 d. RNA-Seq, ChIP-Seq (2 h), and 28 d metabolomic (urine, serum, and hepatic extract) analyses were conducted with complementary serum marker assessments at 92 d. Additional vehicle and 30 µg/kg treatment groups were allowed to recover for 36 d following the 92-d treatment regimen to examine recovery from TCDD-elicited fibrosis. Histopathology revealed dose-dependent increases in hepatic fat accumulation, inflammation, and periportal collagen deposition at 92 days, with increased fibrotic severity in the recovery group. Serum proinflammatory and profibrotic interleukins-1β, -2, -4, -6, and -10, as well as TNF-α and IFN-γ, exhibited dose-dependent induction. An increase in glucose tolerance was observed with a concomitant 3.0-fold decrease in hepatic glycogen linked to increased ascorbic acid biosynthesis and proline metabolism, consistent with increased fibrosis. RNA-Seq identified differential expression of numerous matrisome genes including an 8.8-fold increase in Tgfb2 indicating myofibroblast activation. Further analysis suggests reprogramming of glycogen, ascorbic acid, and amino acid metabolism in support of collagen deposition and the use of proline as a substrate for ATP production via the proline cycle. In summary, we demonstrate that glycogen, ascorbic acid, and amino acid metabolism are also reorganized to support remodeling of the extracellular matrix, progressing to hepatic fibrosis in response to chronic injury from TCDD.
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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 | 0.000 | 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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".