Comparative genomic analysis of Fischer F344 rat livers exposed for 90 days to 3-methylfuran or its parental compound furan
Bibliographic record
Abstract
Furan is a naturally forming compound found in heat-processed foods such as coffee, canned meats, and jarred baby food. It is concurrently found with analogues including 2-methylfuran (2-MF) and 3-methylfuran (3-MF), and toxicity studies demonstrate all are potent liver toxins. Toxicity studies found 3-MF is more toxic than either furan, or 2-MF. The present analysis assesses the transcriptional response in liver samples taken from male Fischer (F344) rats exposed to furan or 3-MF from 0 to 2.0 and 0-1.0 mg/kg bw/day, respectively, for 90 days. Transcriptional analyses found decreased liver function and fatty acid metabolism are common responses to both furan and 3-MF exposure. Furan liver injury promotes a ductular reaction through Hippo and TGFB signalling, which combined with increased immune response results in ameliorating perturbed bile acid homeostasis in treated rats. Failure to activate these pathways in 3-MF exposed rats and decreased p53 activity leads to cholestasis, and increased toxicity. Finally, BMD analysis indicate many of the most sensitive pathways affected by furan and 3-MF exposure relate to metabolism - malate dehydrogenase and glucose metabolism with BMDLs of 0.03 and 0.01 mg/kg bw/day for furan and 3-MF exposure, respectively, which agrees with BMDLs previously reported for apical and microarray data.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".