Transgenerational epigenetic and transcriptomic effects of 2,3,7,8-tetrachlorodibenzo-p-dioxin exposure in rat
Bibliographic record
Abstract
In rats, direct exposure to TCDD causes myriad toxicities. Exposed rats experience hepatotoxicity, wasting syndrome and immune suppression, amongst others. “Inherited exposure”, as occurs in the F3 generation of directly exposed F0 animals, has also been shown to cause toxicity: both male and female F3 rats demonstrate an increased incidence of adult onset disease, females also display reproductive abnormalities and increased incidence of ovarian diseases while males show increased incidence of kidney disease and an altered sperm epigenome. Here, we explore the hepatic transcriptomic profile of male and female F3 Sprague–Dawley rats bred through the paternal germ line from F0 dams exposed to a single dose of TCDD (0, 30, 100, 300 or 1000 ng/kg body weight) by oral gavage. We hypothesize that RNA transcripts with altered abundance in livers of unexposed F3 progeny of treated F0 Sprague–Dawley rats may result from epigenetic modifications to the genome. We further survey patterns of differential methylation within male F3 rat testis. Female F3 rats demonstrated more TCDD-mediated hepatic transcriptomic changes than males, with differences primarily in the lowest dose group. In testis from male F3 rats, multiple olfactory receptors displayed patterns of differential methylation. Hypermethylation of Egfr and Mc5r among testes from TCDD lineage rats was observed, but without corresponding changes in hepatic mRNA abundance. Further studies examining these differences in other tissue types are warranted.
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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 | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".