The pesticide adjuvant, Toximul™, alters hepatic metabolism through effects on downstream targets of PPARα
Bibliographic record
Abstract
Previous studies demonstrated that chronic dermal exposure to the pesticide adjuvant (surfactant), Toximul (Tox), has significant detrimental effects on hepatic lipid metabolism. This study demonstrated that young mice dermally exposed to Tox for 12 days have significant increases in expression of peroxisomal acyl-CoA oxidase (mRNA and protein), bifunctional enzyme (mRNA) and thiolase (mRNA), as well as the P450 oxidizing enzymes Cyp4A10 and Cyp4A14 (mRNA and protein). Tox produced a similar pattern of increases in wild type adult female mice but did not induce these responses in PPARalpha-null mice. These data support the hypothesis that Tox, a heterogeneous blend of nonionic and anionic surfactants, modulates hepatic metabolism at least in part through activation of PPARalpha. Notably, all three groups of Tox-treated mice had increased relative liver weights due to significant accumulation of lipid. This could be endogenous in nature and/or a component(s) of Tox or a metabolite thereof. The ability of Tox and other hydrocarbon pollutants to induce fatty liver despite being PPARalpha agonists indicates a novel consequence of exposure to this class of chemicals, and may provide a new understanding of fatty liver in populations with industrial exposure.
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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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".